Category Archives: Genome

This article was originally published here

Clin Chim Acta. 2022 Jan 19:S0009-8981(22)00019-5. doi: 10.1016/j.cca.2022.01.010. Online ahead of print.

ABSTRACT

BACKGROUND AND AIMS: Cleidocranial dysplasia (CCD) represents a rare autosomal dominant skeletal dysplasia caused by mutations that induce haploinsufficiency in RUNX2, the important transcription factor of osteoblasts related to bone/cartilage development and maintenance. Clavicular hypoplasia, which involves aberrant tooth/craniofacial bone/skeletal formation, is a feature of classic CCD. RUNX2 mutations can be found in approximately 60-70% of patients with CCD, and around 10% of these mutations are microdeletions. The present paper describes the radiological and clinical characteristics of a 5-year-old girl who showed representative CCD features, including extra teeth, aplasia of clavicles, sloping shoulders, marked calvarial hypomineralization, and osteoporosis.

MATERIALS AND METHODS: We obtained genomic DNA of her family members and performed whole-genome sequencing (WGS) for samples collected from the proband. Quantitative fluorescent PCR (QF-PCR) and specific PCR plus electrophoresis were then performed as validation assays for all participants. In vitro analysis was performed. Luciferase assay for Runx2 transcription activity and evaluation of mRNA levels of Runx2 downstream osteogenic markers were conducted.

RESULTS: WGS identified a 11.38-kb microdeletion in RUNX2 comprising 8-9 exons, which was validated by QF-PCR and specific PCR plus electrophoresis. In vitro experiments confirmed the pathogenicity of this variation.

CONCLUSION: The present study identified a 11.38-kb microdeletion in RUNX2 that causes CCD. The deletion in the PST domain of RUNX2 reduces its transcription activity and reduces osteogenic marker levels, eventually decreasing the differentiation of osteoblasts. These findings clarify the role of the CCD-related mechanism in the development of CCD and suggest that it is important to consider copy number variation for the suspected familial patients early.

PMID:35065050 | DOI:10.1016/j.cca.2022.01.010

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Genome sequencing identified a novel exonic microdeletion in the RUNX2 gene that causes cleidocranial dysplasia - DocWire News

January 20, 2022

TheDepartment for Environment, Food and Rural Affairs (DEFRA) has announced new legislation to cut red tape for gene editing plant research.

Prof Andrew Thompson, Head of the Cranfield Soil and AgriFood Institute, said:

The older technology of genetic manipulation has allowed us to create plants that use water more efficiently, generating more crop per drop- vital where food production is limited by water availability. Achieving the same goal using novel gene editing approaches in a more permissive regulatory framework will certainly help this and other beneficial traits to be fully exploited for the benefit of farmers, consumers and the environment.

Prof John Dupre, Professor in Philosophy of Science, and Director of Egenis, the Centre for the Study of Life Sciences, University of Exeter, said:

This announcement on genome editing of plants looks like a positive movement forward. Provided, crucially, that a robust regulatory process remains in place and that this is integrated into a general and wide-ranging agricultural strategy, it should open up the possibility of valuable improvements in quantity, quality and environmental impact of crop production.

Professor Robbie Waugh, director of the International Barley Hub, said:

If the response to COVID-19 has sent one important message to the British public, its been to listen to the science.Relaxation of the regulations around gene-edited plants announced today by DEFRA is, I believe, a positive reflection of DEFRA listening to scientific evidence that unequivocally demonstrates that minor genetic changes induced by gene editing are indistinguishable from those that randomly arise in nature all of the time.The big difference is they can be introduced reliably and with incredible precision.For those of us involved in developing strategies to address some of the major challenges facing the planet today, the announcement reflects a progressive and scientifically justifiable decision based on science, and will undoubtedly increase our ability to address these challenges head-on.

Prof Wendy Harwood, Head of the Crop Transformation Group at the John Innes Centre, said:

Genome editing allows us, for the first time, to make small precise changes in a plants existing DNA that mimic changes that could occur naturally. The technique overcomes the random nature and long time-scales associated with older traditional technologies. This means that essential characteristics such as better resilience to climate extremes could be made available more rapidly, helping to ensure a secure food supply. Field trials are an essential part of the process to develop improved crops. The changes announced are welcomed as they will make field trials of genome edited crops easier and less expensive, further speeding up the process of delivering benefits to farmers and consumers.

Prof Martin Warren, Head, Food Innovation and Health Programme, Quadram Institute, said:

Gene editing provides the opportunity to enhance the nutritional quality of plants a really important issue as we embrace more plant-rich diets.

Gene editing represents a very precise way to improve specific qualities such as the accumulation of higher levels of micronutrients, including minerals and vitamins, which are often found in low abundance in crops.

The announcement by Defra is welcomed as it will allow the faster development of such plants, which can be used to tackle key national and global challenges associated with malnutrition.

Dr Brittany Hazard, Group Leader, Quadram Institute, said:

The ability to employ gene editing technology in our research program will provide a substantial opportunity to accelerate the development of staple crops that can deliver health benefits to consumers.

We anticipate that gene editing will allow us to overcome many challenges and lengthy timescales of conventional breeding and rapidly generate wheat with enhanced levels of dietary fibre that could easily be adopted by plant breeders.

Prof Ian A Graham FRS, Director of BioYork and Weston Chair of Biochemical Genetics at the University of York, said:

The Defra Gene Editing Announcement is an exciting prospect for UK agriculture at a time when we need to be urgently responding to the challenges of climate change and biodiversity loss. Deployment of gene editing will enable careful, precision engineering based improvement of existing crops and the development of novel agricultural products in a way that was simply not possible until now. The Governments decision has come not a moment too soon.

Dr Penny Hundleby, Senior Scientist at the John Innes Centre, said:

Defras announcement sends a clear message of support for UK science and the future of our agritech and farming industries. These technologies will help support agrobiodiversity, plant health and our commitment to food security, sustainability and developing crops for a changing climate.

Gene editing, together with access to genome sequencing (where the UK is strong) moves us into an exciting era of affordable, intelligent and precision-based plant breeding. We will also see more products aimed at the convenience / consumer preference markets e.g. more nutrient-dense salads, pitless cherries, naturally decaffeinated coffee etc.

Professor Sophien Kamoun FRS, Group Leader at The Sainsbury Laboratory in Norwich, said:

Genome editing technology can be used to remove genes from crop genomes that make them susceptible to diseases. Researchers at The Sainsbury Laboratory demonstrated this by removing 48 nucleotides from the tomato genome to make it resistant to powdery mildew. Powdery mildew disease is one of the main reasons why UK tomato growers spray fungicides on their crops. The edited tomato, named Tomelo, offers the opportunity to dramatically reduce these chemical inputs with benefits for farmers health and the environment, not to mention reduced production costs. We need to be able to use these innovations if we want to provide enough food for our growing human population without causing further damage to our environment.

Back in 2013, our scientists at The Sainsbury Laboratory were among the very first to develop the CRISPR gene editing tech in plants, a technology that carries so much potential and so many opportunities for world agriculture. Yet, we had to sit back and watch other countries, like the US and Japan, bring their CRISPR bio-edited plants to market. I hope that we can finally capitalize on the world-leading research base we have in this country in plant sciences and help make agriculture more sustainable.

Prof Derek Stewart, director of the James Hutton Institutes Advanced Plant Growth Centre, said:

The relaxation of the regulation of gene-edited crops offers many opportunities to deliver the next generation of crops that will be able to deliver simultaneously to the economic, environmental, biodiversity and net-zero agendas in the UK. To do this, we will need state-of-the-art science and translation facilities such as the Advanced Plant Growth Centre at the James Hutton Institute to create, develop and translate these new crops into the field environment and ensure they are both suitable for purpose and environmentally appropriate.

Prof Ian Crute, former Chief Scientist of AHDB and former Director of Rothamsted Research, said:

After decades of research, plant scientists now better understand the genetic components of crops defences against pests and pathogens. Gene editing provides the logical next-step in applying this knowledge to deliver, more efficiently, pest and disease resistant varieties that can be grown successfully without recourse to the regular use of agrochemicals.

Prof Johnathan Napier, Flagship Leader at Rothamsted Research, said:

This is a really positive development and I am genuinely excited by the opportunities this shift in the classification of genome editing in plants will bring. When I carried out the UKs first field trial of a GE crop in 2018, Defra was of the opinion that our edited Camelina plants were not GM, so it is great to see a return to that position. I strongly believe that genome editing can contribute to making crops to be more nutritious, more sustainable and more resilient, and this change to how field trials are regulated is a welcome first step in liberalising how the UK regulates new genetic technologies like GE and GM. I look forward to being part of this exciting new chapter, one where the UK can better realise its potential as a world leader in plant biotechnology to deliver food security.

Prof Huw Jones, Chair in Translational Genomics for Plant Breeding, Aberystwyth University, said:

Investigating how plants with novel genetic traits behave under field conditions should be a natural part of the experimental process. The use of some modern breeding methods have until now made this transition difficult and hampered applied plant research. I welcome this announcement, which will normalise the lab to field step for innovative breeding via gene editing that has the potential to make food production safer and more sustainable. To ensure a level playing field for research, I urge the Welsh and Scottish authorities to make similar changes.

Prof Lesley Torrance, Executive Director of Science at the James Hutton Institute, said:

We welcome this decision; while it is important to thoroughly scrutinise new breeding technologies to ensure the highest standards for food safety, it is also important that regulations are updated to take account of new information and new developments.This decision reflects this approach and is a step in the right direction by facilitating field trials in relevant environments.Further work is needed to develop the rules around gene-edited crops for commercial release and we look forward to contributing to the next steps to enable new gene-edited crops to be safely released and fulfil their potential for climate resilience and provide healthy, nutritious food while safeguarding the environment.

Prof Nick Talbot FRS, Executive Director of The Sainsbury Laboratory in Norwich, said:

Genome editing provides the opportunity to deliver knowledge-based plant breeding and harness plant biodiversity. We can achieve the outcomes of plant breedingwhich has been so successful in controlling diseases and improving yieldsbut in a much more precise manner. In this way, we can aim to produce nutritious crops requiring much lower fertiliser inputs and with greater resilience. We need innovation to help us escape from the chemical treadmill of current agriculture. In the face of the climate emergency, doing nothing is no longer an option.

Prof Jonathan Jones FRS, Group Leader at The Sainsbury Laboratory in Norwich, said:

I welcome the decision of DEFRA to act on the scientific consensus about the utility and safety of gene editing for crop improvement. Enabling plant breeders to take advantage of these benign and useful methods is essential to increase food production by 50% by 2050, in a warming world, while minimizing agrichemical use.

Im also pleased to see in the DEFRA statement that there are plans to adopt a more scientific and proportionate approach to the regulation of genetic technologies. In our own work, we use the GM method to move immune receptors from one plant to another, increasing the plants capacity to activate its defences quickly enough to thwart disease. The government must not miss the opportunity to facilitate use of this benign and helpful method for reducing the environmental impact of agriculture, and I look forward to seeing this reassessment implemented.

Declared interests

Prof Nick Talbot:Nick is in receipt of funding from The Gatsby Charitable Foundation, The Leverhulme Trust and UKRI (BBSRC and GCRF Funding) and is a Gatsby Plant Science Advisor. He is also a member of the John Innes Governing Council and Board member of PBL Technology.

Prof Jonathan Jones:Professor Jonathan Jones is a senior investigator at The Sainsbury Laboratory in Norwich, and uses molecular and genetic approaches to study disease resistance in plants. Jones co-founded Norfolk Plant Sciences in 2007 with Prof Cathie Martin of JIC, with the goal of bringing flavonoid-enriched tomatoes to market (www.norfolkplantsciences.com). Jones is on the board ofwww.isaaa.org, the science advisory board of the 2Blades foundation (www.2blades.org) and the board of NIAB Cambridge University Farm. Jones has isolated and is deploying new resistance genes against potato late blight from wild relatives of potato, and conducting field trials to evaluate how well they work to protect the crop in the field and to generate improved varieties of potato (seehttp://www.tsl.ac.uk/news/blight-resistant-maris-piper/). See alsohttp://www.tsl.ac.uk/groups/jones-group/.

Dr Penny Hundleby: uses gene editing in crops to better understand the role of plant genes. She is currently on secondment to the Anglian Innovation Partnership as a Science Advisor covering the Norwich Research Park.

Prof Sophien Kamoun: I consult and receive funding from the biotech and plant breeding industry, notably BASF, Limagrain and Rijk Zwaan. Im a member of the Two Blades Foundation Science Advisory Board. My other professional activities and recent research funding are listed athttp://kamounlab.dreamhosters.com/pdfs/SKamoun_CV.pdf.

Prof Johnathan Napier: is currently running both GM and GE field trials at Rothamsted, and last year sowed 600,000 GM camelina plants growing in the field, as part of a project to make a sustainable source of omega-3 fish oils.

Prof Huw Jones:

Direct employment: Aberystwyth University 2016 current; Rothamsted Research 1998 2016.

Other fee-paid work from relevant organisations, consultancies etc.: BBSRC grant review panels 2000 current; FSA ACNFP 2019 current; Expert, GMO panel, European Food Safety Authority 2009 2018. As external examiner of the university PhD viva process, I have sometimes receive a small honorarium in addition to travel and accommodation costs from the university hosting the examination (since 2007 I have been external examiner for ten PhD viva voce examinations in UK and abroad). I have received small payments of royalties from publishers for academic books written or edited.

Membership, affiliation, trusteeships or decision-making position with relevant organisations: Fellow of Royal Society of Biology 2002 current. Honorary Professor, School of Biosciences, Nottingham University 2009 2018. Honorary researcher, Rothamsted Research UK, 2016-2019. Member of the EPSO Plants for the Future. Gene editing working group 2019 current. Chair, UK Plant Sciences Federation Working Group on Regulatory Frameworks 2014-2015. Monogram steering committee, 2011 2015. Member of BBSRC pool of experts, Jan 2017 current.

Other personal interests: I am invited to attend typically between 5 and 10 conferences or other meetings per year where the travel and accommodation (if applicable) are paid for by the host organisations. I have never received a fee to participate in such meetings.

Indirect financial or non-financial support from relevant organisations: I am a member of the IBERS Aberystwyth University research team in receipt of a BBSRC Core Strategic Programme Grant Resilient Crops BBS/E/W/0012843. I am one of four academic supervisors for an Aberystwyth University/Syngenta PhD studentship, using molecular genetics to design sentinel plants for detecting biotic stress, 2017-2020. I am a UK representative of an EU COST Action PlantEd Genome editing in plants a technology with transformative potential 2019 2022. I am a UK representative, working group and management committee member of an EU COST Action iPlanta CA15223. Modifying plants to produce interfering RNA 2017 2020. I led a research project: Smart Labels for GMO foods, Aberystwyth University Transforming Social Science Fund, 1K Jan, 2017. Rothamsted Research was in receipt of funding from BBSRC Tools and Resources Development Fund BB/L017768/1, 2014 2016, HD Jones & K Edwards, Development of specific TALENs for precision engineering in wheat.

Prof Wendy Harwood: I am a member of the Food Standards Agency Advisory Committee on Novel Foods and Processes (ACNFP) but this quotation is in a personal capacity.

None others received.

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expert reaction to new legislation for genome editing in plants, as announced by Defra - Science Media Centre

Genomics, from its inception, has encompassed evolutionary and interspecies comparisons (1), in a tacit acknowledgment that genome sequence is almost meaningless without context. Comparative genomics harnesses evolution to investigate genome function. The second genome sequenced for a free-living organism (Mycoplasma genitalium) was immediately compared to the first (Haemophilus influenzae) (2). The human genome was compared to mouse (3), chicken (4), dog (5), and then 28 mammals simultaneously (6), and recently to 240 mammals (7). The first plant genome, the model organism Arabidopsis thaliana (8), was compared to eight other crucifers (9). Genomic positions that resist change over long periods of time may be essential for survival, and those that accumulate changes unusually quickly in particular lineages may be involved in development and propagation of advantageous phenotypes.

Evolutionary innovations in nonhuman species have already resulted in new therapeutics. Decades before the advent of genomics, the ovarian cancer drug paclitaxel (Taxol) was discovered in the Pacific yew tree, where it protected against pathogens (10). Transcription activator-like effectors, discovered in a plant pathogenic bacterium, led to the development of novel genome editing tools and a new therapeutic for acute lymphoblastic leukemia (11).

Despite this legacy, genomics has increasingly focused on humans (Fig. 1). The United Kingdom Biobank Project (12) and All Of Us Research Program (13) are scaling to millions of humans. Meanwhile, only 4% of animals and 2% of plants have a single representative genome assembly (14). Rather than advocating a shift away from humans, we propose broadening the scope to include more nonhuman data. By removing barriers that silo comparative genomics and human genomics into distinct disciplines, and integrating with nongenomic disciplines, we can transform every species into a model organism and accelerate discovery.

A broader focus is essential to protecting the ecosystems we depend on. Biodiversity is the unrecoverable foundation of comparative genomics. It is being lost at an alarming rate (15). Combining genomic tools with meticulous phenotyping and creative cross-disciplinary collaboration can help address this crisis (16, 17).

Evolution is an unparalleled tool for research. Functionally, it is somewhat analogous to a long-term clinical trial, initiated several billion years ago and enrolling all life on Earth. It includes species with evolutionary trajectories altered by human action, through both accelerated natural selection and experimental selection, creating populations we use as research models (Fig. 2 and SI Appendix, Table S1). As mutations arise, they are evaluated for their effect on survival and reproduction, as eloquently described by Charles Darwin more than 150 y ago:

Different types of study populations have different strengths. Diversity: genetic diversity in populations, ranging from inbred (e.g., laboratory mice) to outbred/highly diverse. Humans (midpoint) are outbred but less diverse than many species. Complexity: genetic complexity of traits; low in the laboratory mouse, with controlled genetic background and environment, and high in humans, where most traits are complex. Phenotyping: ease of collecting phenotype data, ranging from only noninvasive phenotyping in natural environments, to invasive laboratory phenotyping. In humans (midpoint), resources like electronic medical records make it possible, but not easy, to collect detailed phenotypes at scale. Sampling: ease of collecting samples, ranging from only minimally invasive sampling in wild-caught individuals, to populations where euthanasia and tissue collection are feasible. Sample size: number of individuals that can be sampled, ranging from <100 (endangered species or laboratory animals requiring costly care) to millions (humans). Function: potential for functional genomics (epigenomics, cellular and organoid models, genetic engineering, and so forth). In humans, cellular models are well developed, but organism-level experimentation is not possible.

It may be said that natural selection is daily and hourly scrutinising, throughout the world, every variation, even the slightest; rejecting that which is bad, preserving and adding up all that is good; silently and insensibly working, whenever and wherever opportunity offers, at the improvement of each organic being in relation to its organic and inorganic conditions of life (18).

By comparing genomes within and between species, and connecting genomic variation to changes in cells, organisms, and ecosystems, we access the results of a natural experiment carried out on an unfathomable scale.

Genomic studies that include only humans capture just the last 50,000 y or so of evolution. Even so, naturally occurring human mutations guided the design of safe and effective drugs. Rare coding mutations that cause abnormally low cholesterol inspired the new class of PCSK9 inhibitor drugs (19), which reduce the risk of vascular events without major offsetting adverse events.

Other species routinely exhibit evolutionary adaptations that allow them to tolerate conditions that are disease-causing in humans. Hibernating mammals become obese and insulin-resistant in preparation for hibernation and, while hibernating, lose synaptic connectivity and suffer repeated episodes of ischemia and reperfusion (20). Yet they emerge healthy each spring in a physiological feat that holds clues for treating obesity, neurodegeneration, and heart disease (21).

Traits like hibernation are the outcome of a complex and iterative evolutionary process. Organisms adapt to changes in their environment, and by doing so, change that environment, driving adaptation in other species, and so on, ad infinitum. The substrate for this evolutionary arms race is mutation, both small (single nucleotide) and large-scale (structural variants and polyploidy), and the backdrop is a series of unpredictable natural events that constantly reset the stage. The mass extinction that marked the demise of nonavian dinosaurs opened up ecospace for the diversification of mammals (22) and birds (23) into thousands of species extant today.

The sheer complexity of evolution may encourage a reductionist approach, but this is insufficient. Even when the mechanism of a single variant is known in great detail, its effect in the context of other genome variation can be unpredictable (24). Discovering the emergent properties of complex systems using large datasets is a more powerful approach, as demonstrated in biophysics (25), comparative genomics (7, 26), and human genomics (12).

We are poised to enter a new age of science heralded by new genome-editing technologies (27, 28). Scientists can directly edit DNA to achieve desired outcomes, whether curing heritable diseases, depleting invasive populations, reducing pathogen reservoirs, or engineering crops resilient to environmental stress. Even as we contemplate the role of genetic creators, we cannot yet predict the organismal impact of changing even simple genomes.

To understand how genomic variation shapes organismal variation and function, it is both possible and necessary for research to encompass the full scope of the evolution of life. We can now measure and modify the natural world with unprecedented precision, but researchers pursuing innovative and cross-disciplinary research encounter systemic and logistical barriers. By addressing these challenges, all species can contribute as genetic systems for understanding and protecting our world.

There is grandeur in this view of life, with its several powers, having been originally breathed into a few forms or into one; and that whilst this planet has gone cycling on according to the fixed law of gravity, from so simple a beginning endless forms most beautiful and most wonderful have been, and are being, evolved (18).

All organisms on Earth share a common origin, each being one of billions of variations on a common theme. Hundreds of genes shared between yeast and humans are so functionally similar that the human version can substitute in yeast (29). Sponge enhancers control cell-typespecific gene expression in zebrafish and mice, lineages that last shared a common ancestor 700 million y ago (30).

If genomes are the source code of life, then the interpretation is an interaction between that code, the cellular machinery that reads it, and the environment in which it is manifested. While a genome sequence may be essential, it is not sufficient to elucidate the complex processes underlying development, growth, differentiation, host defense, environmental responses, and countless other facets of biology. This requires transcriptomic and epigenomic data that vary by cell type and over time, samples from many individuals per species, and many samples per individual (31). It also requires new technology for collecting functional data, phenotypes, and environmental measurements at scale, including epigenomic assays (32), remote sensing [e.g., airborne lidar (33)], thermal and fluorescence imaging (34), passive environmental sampling (35), geographic information system mapping (36), and participatory science (37). Finally, it requires situating genomic change in the evolutionary timeline and in relation to geologic, ecologic, and anthropologic events.

Just as technology for large-scale sequencing transformed genomics, new technologies for large-scale data collection are transforming how we study the natural world. Biology is transitioning from a single-investigator, hypothesis-based endeavor to team-driven, discovery-based science. Collaborations that encompass biology, medicine, computer sciences, and historical sciences, as well as data-driven methods for studying complex systems, can support a more systems-based, and less reductionist, investigation of organisms and ecosystems.

Here, we call for a more Darwinian approach to genomics that considers all forms of life, their interactions, and the natural environment that shaped them. Charles Darwin developed his theory of evolution by natural selection by studying a wide range of species, including insects, plants, arthropods, and vertebrates. The groundbreaking first edition of On the Origin of Species (18) illustrates how a broader perspective enables discoveries not possible when focused on a single species. For scientists today, this requires collaborations that span diverse communities, within and outside of science, and the technology, scale, and skills to address multidimensional questions. Below, we review key discoveries that illustrate the potential of this approach, and propose strategies to support the cross-disciplinary integration essential to success (Box 1).

Perspectives in Comparative Genomics and Evolution Workshop.

In August 2019, three funding agenciesthe National Human Genome Research Institute (NIH), the National Institute of Food and Agriculture (US Department of Agriculture), and the National Science Foundationconvened a 2-d workshop on Perspectives in Comparative Genomics and Evolution, where 120 participants evaluated the state of the field, focusing on commonalities across humans, model organisms (traditional and nontraditional), agricultural and wildlife species, and microbes. For this paper, the authors synthesized common themes, roadblocks, and strategies that emerged from the workshop.

We use the term Darwinian after careful deliberation. For many scientists, Darwins name, more than any other single word, evokes the connection between the processes of evolution and the organisms and ecosystems most beautiful and most wonderful (18) of the natural world. Since its publication, Darwins work has been misused to lend a false veneer of scientific credibility to racist, ableist, and sexist beliefs that continue to cause immeasurable damage. We recognize our obligation to confront this history, and to work to undo the harm it has caused.

Collaboration is essential for expanding the scope of comparative genomics; this requires overcoming traditional barriers separating disciplines and scientists from communities. To reconstruct the historic dispersal of Oryza sativa ssp. japonica, the progenitor of much of our domesticated rice, sequence data for 1,400 strains was insufficient. Combining geographic, environmental, archaeobotanical, and paleoclimate information revealed that rice diversified into temperate and tropical japonica rice during a global cooling event 4,200 y ago, suggesting that further research might find adaptations to changing climates (38).

Collaborations that span ethnic, geographic, and socioeconomic backgrounds improve productivity and data richness (39), but require communication, leadership, open thinking, and appreciation for all participants (40). Particularly when collaborations span fields with different norms, or include remote study locations, success depends on trust and ensuring all participants are acknowledged (41). Funding agencies, journal editors, and academic institutions can encourage collaborations with reward structures that credit all team members(42) . Scientists sequencing the genome of the tuatara, a reptile endemic to New Zealand and the only living member of its order, partnered with Ngtiwai, the Mori iwi (tribe) holding guardianship over the individual tuatara studied (43). Their successful collaboration, recognized with authorship, was guided by common goals of increasing knowledge and supporting conservation, with Ngtiwai participating in data-use and benefit-sharing discussions. People working within Indigenous or traditional knowledge systems can offer information on species behavior, habitats, and conservation issues unfamiliar to scientists working within Western knowledge systems (44). Using DNA barcoding technology, scientists in the Velliangiri Hills of India identified three species of herbaceous plants new to science, but already classified as distinct species in the local traditional knowledge system (45).

Engaging community members directly in research can facilitate collection of large and geographically disparate datasets needed to explore real-world evolutionary processes, while positively impacting communities. Using eBird, a community science project whose participants have collected over 915 million bird observations (46), scientists had sufficient data to assess whether speciation is associated with niche divergence in Aphelocoma jays (47). The spread of the cabbage white butterfly, Pieris rapae, a destructive agricultural pest, was traced using samples collected by over 150 volunteers from 32 countries, which implicated specific human activities as possible drivers (48). Children in India, Kenya, Mexico, and the United States surveyed mammalian biodiversity near their schools using camera traps, collecting high-quality data while learning to value their local natural history (49).

Such research should align with the Convention on Biological Diversity, ensuring local knowledge is included and attributed, that data are correctly interpreted, and that cultural practices are respected (44). All stakeholders, including local communities, should benefit (50). Full partnership with field scientists is vital. Their meticulous observations and careful sample collection, along with the curation and annotation of the specimens in both living and natural history collections, are the keystone of interdisciplinary research.

Our conception of a more collaborative approach to comparative genomics is rooted in the open-data culture of genomics, exemplified by the Human Genome Project (51) and the sometimes controversial (52) shift to team projects that generate and analyze multidimensional datasets (53). Today, genomic data dominate, but other data types are expanding [imaging, personal wearable devices, remote sensing, and electronic medical records (54)]. Resources like the Global Biodiversity Information Facility (GBIF) (55) and the Integrated Digitized Biocollections (iDigBio) provide standards and open-source tools for unifying disparate organismal occurrence data (56). The Genomic Observatories Metadatabase (GEOME) (57) links the Sequence Read Archive (SRA) (58) to ecological data repositories not configured for genomic information.

A single reference genome is rarely sufficient for answering biological questions, but when shared, supports many different studies (53). Historically, researchers were forced to weigh the often considerable cost of generating a reference against the value of other data that could be collected instead. Today, falling costs and new technology are making high-quality reference genomes more achievable (59). The Earth BioGenome Project proposes producing reference genomes for 2 million known eukaryotic species in the next 10 years (60).

High-quality reference genomes can lead to discoveries even in well-studied organisms. Using the highly contiguous genome for the bioenergy crop switchgrass (Panicum virgatum), scientists compared hundreds of plants grown in common gardens spanning 1,800 km of latitude. They discovered genetic variation accumulating on the less constrained subgenome, suggesting a polyploid genome may enhance adaptive potential (36). Comparing high-contiguity genomes for six bat species revealed positive selection at hearing-related genes, suggesting echolocation is an ancestral trait lost in the nonecholocating bats (61).

Data structures that accommodate genetic diversity within species are still under development. The traditional linear genome structure struggles even with human data, introducing pervasive reference biases (62). For species with more genetic diversity, like gorillas and butterflies (63, 64), new representations, like graph-based pangenomes, are essential (65).

With falling sequencing costs, functional genomic assays [e.g., RNA-sequencing, chromatin accessibility assays, Hi-C, PRO-seq, and ribosome profiling (6669)] can capture cellular change over time, by cell and tissue types, and with environment. Comparing the epigenomic landscape in 10 mammalian species using chromatin immunoprecipitation-sequencing uncovered unexpected plasticity in regulatory elements, including switching from promoter to enhancer, and vice versa (70).

Functional genomic assays are essential for investigating mechanisms of action. To pinpoint a variant conferring increased obesity risk in humans, scientists combined long-range chromatin interactions, expression quantitative-trait locus analysis, luciferase reporter assays, and directed perturbations in primary cells (71). Joint analysis with comparative genomic data identified an endogenous retrovirus insertion that encoded an enhancer involved in activating the inflammasome, and may be a pathogen-response adaptation (72).

In more easily manipulated laboratory models, single-cell, single-nucleus, and spatial sequencing methods are revealing the fundamental biology of the cell. By embedding sequence barcodes in fertilized zebrafish eggs, and editing them with each cell division, cell lineages were tracked throughout embryo development and the lineage tree reconstructed (73).

For single-cell organismsincluding bacteria, archaea, and protistssingle-cell genomics captures culture-independent diversity. Single-cell transcriptomics on organisms from the hindgut of wood-feeding termites showed four protist species with distinct roles in wood degradation, suggesting microbiome diversity is essential for termite survival (74).

Cloud-computing resources, which offer massive compute and storage capacity, are essential as sequence datasets grow (75). When cohorts reach half a million, and phenotypes number over 7,000, correlating genotype and phenotype requires millions of CPU hours. Using cloud-based clusters, such jobs are completed in a week (76). Today, the compute time required to align genomes, essential for comparative genomics, scales quadratically with genome size (77), although algorithmic advances could improve efficiency. To make protein structure prediction more accurate and efficient, AlphaFolds neural network-based algorithm predicts energy landscapes rather than calculating binary contact maps (21, 74).

Extending genomics to consider all forms of life requires prioritizing sample collection in challenging environments. Long-read sequencing technology is of little use if the input DNA is fragmented due to sample degradation. Chromatin conformation capture can measure the three-dimensional structure of the genome only if samples have intact nuclei. To measure the response of cells to stimuli, living cell cultures are needed, an expensive and labor-intensive resource to establish (SI Appendix, Fig. S1).

Collecting high-quality samples from species living in regions remote from scientists is particularly challenging. Sampling three highland wild dogs in New Guinea required field biology studies, GPS tagging, video, and collaboration with local scientists, but rediscovered a population of free-living dogs long thought extinct (78). While captive populations may be easier to sample, zoos house representatives of only 12% of the 31,771 terrestrial vertebrate species (79, 80), and botanical gardens capture only a fraction of plant species (81).

The number of samples is sometimes more critical than sample quality, particularly when a high-quality reference genome is available. Pairing samples with metadata, such as collection dates, locations, and phenotypes, makes it possible to evaluate population demography, and identify mutations that can impact fitness. Whole-genome sequencing of century-old gorilla specimens, annotated with collection dates, revealed a drop in genetic diversity associated with increased inbreeding in the critically endangered Grauers gorillas, but not in the mountain gorilla, which did not experience the same population declines (82).

New methods for extracting and analyzing DNA allow samples in less-than-ideal condition to be used. The oldest DNA sequence, recovered from wooly mammoths living in Siberia 1 million y ago, shows that North American mammoths likely descended from a hybridization event, with cold climate adaptations already present (83). By sequencing slow-degrading structural proteins in samples 3.5 million y old, the origin of modern camels was traced to the forested Arctic of the Mid-Pliocene (84). Sequencing can characterize complex mixes of species in paleo-samples. Fossil rodent middens are mixtures of plant and animal remains, collected by foraging rodents ranging 100 m, and preserved for thousands of years. Sequencing them captures the community of plants, animals, bacteria, and fungi at a single location in the past with exquisite resolution (85). Epigenomic profiling of ancient specimens, while technically challenging, could improve predictions of species resilience (86).

Methods developed for old or degraded samples support studies of natural populations where invasive collections are not possible. Methods that enrich host DNA make feces samples, dominated by microbes, more useful (87). DNA extracted from elephant tusks traced samples to their source, helping law enforcement disrupt poaching activities (88).

Portable sequencing technology, deployable in remote locations, could be transformative by eliminating shipping risks and supporting field-based training with local scientists leading environmental efforts (89). In the Ecuadorian Choc rainforest, one of the world's most imperiled biodiversity hotspots, on-site sequencing distinguished species through DNA barcoding (90). In Hawaii, long ribosomal DNA sequencing in the field yielded a phylogeny of 83 spiders that captured the adaptive radiation of the genus Tetragnatha (91).

Genomic, epigenomic, and proteomic assays all require destructive sampling, and this cost should be carefully considered. The scientists who identified the first archaic human from the Denisovan lineage did so by destroying part of a tiny sliver of bone, the only sample available for DNA extraction (92). Their work showed Denisovans were evolutionarily distinct from Neanderthals and modern humans, transforming our understanding of human evolution.

Destructive sampling puts museums in the difficult position of judging which projects are worthy. Genomic data offers a window into the past unattainable through other technology (93). Sequencing of 28 fossils, including 7 from museums, discovered a now-extinct horse genus endemic to North America, adding a branch to the phylogeny of mammals (94). Museums may be reluctant to authorize damage to specimens in their care (95), but collecting genomic data could also mitigate, somewhat, loss of collections in the future. Even minimal genomic data from the 20 million samples lost when Brazils National Museum burned down in 2018 (96) would comprise an unparalleled scientific resource. Further complicating the question, the same sample may yield more information with time. Two years after the first Denisovan paper (92), a subsequent paper described a DNA library preparation method requiring half as much input (97). Guidelines are needed for researchers, museums, and journals to ensure samples are used responsibly, projects are high quality and ethically executed, and that data and specimen information are shared (98).

Collecting, quantifying, and comparing complex phenotypes in diverse species, at scale, is perhaps the greatest challenge in comparative genomics (99). The observable phenotype of an organism reflects the interaction of preprogrammed traits encoded in a genome with its environment, suggesting we could, in theory, predict its structure and function from its genome. To understand how phenotypes evolve, we must compare the same species in differing environments (36), different species with shared traits (100), and outliers with incredible adaptations.

In laboratory models, phenotyping technology is well developed and genomic resources are robust, elevating species such as yeast, fruit fly, nematodes, zebrafish, rat, mouse, Arabidopsis, rice, and others as primary models for fundamental biological questions. Using an experimental design that inverts traditional gene mapping, the International Mouse Phenotyping Consortium disrupted 3,328 genes and produced models for 360 human diseases, including the first for some bleeding disorders and ciliopathies (101). Deeply sequencing 1,504 mutant lines of the model rice cultivar Kitaake (O. sativa ssp. japonica) found 90,000 mutations affecting 58% of genes, including a causal mutation for short-grain rice (102).

Laboratory models are diversifying with the emergence of versatile, species-agnostic gene knockout technology. Making a primate model carrying even one biallelic mutation through breeding is difficult, given long maturation times and low reproduction rates. With CRISPR-based genome editing, multiple variants can be engineered in parallel, producing new models for human polygenic diseases (103). Integrating large DNA constructs into mammalian stem cells allows systematic locus-scale analysis of genome function (104). In the future, editing ancient DNA sequences into living cells could enable paleoepigenomics.

Domesticated species are natural models for linking phenotypes, many from intentional and inadvertent selective breeding, to genomic changes. The phenotypically diverse food cropscabbage, kale, collards, Brussels sprouts, broccoli, and cauliflowerwere developed from a single plant species, Brassica oleracea, primed for a dramatic response to breeding by an ancient whole-genome triplication (105). Strong, recent selective breeding, as in ornamental goldfish (106) and dog breeds (107), leaves distinctive signals around causal variants. Testing for signals of selection in 82 strains of budding yeast connected the unique ability of cheese-making strains to grow quickly on galactose to the replacement of the GAL1, GAL7, and GAL10 genes with orthologs from another species (108).

The very large population sizes and, for commercially relevant traits, rigorous phenotyping in modern commercial livestock make them useful genomic models. One million chickens are vaccinated every hour against an oncogenic herpesvirus using a vaccine repeatedly reformulated for more virulent strains (109), making commercial chicken farms a model for intersecting host genomics, viral evolution, and disease epidemiology. The vaccine prevents severe disease but not transmission, and effectively controls outbreaks (110), reassuring for humans suffering through the COVID-19 pandemic.

In natural populations, genomic studies focused on dissecting the etiology of traits are challenged by the need for large numbers of well-phenotyped samples (111), yet technologies like Google Earth (112) can provide rich new data sources. To detect systems-level patterns in ecological diversity, and the impact of environmental change, researchers paired sequencing of samples collected by community scientists with habitat, bioclimate, soil, topography, and vegetation data (113). To collect tick samples with the geographic, temporal, and image data needed to study pathogen transmission dynamics, scientists used social media to enlist the help of thousands of community scientists (114).

Combining genomic and nongenomic data can identify drivers of disease spread, thereby informing the design of effective interventions. Phylogenomic analysis of 772 complete SARS-CoV-2 genomes, when paired with epidemiology data, showed how superspreader events shaped the course of the COVID-19 pandemic (115).

A perspective that considers all species, rather than focusing on humans or a few familiar models, provides more options for selecting the optimal model for the scientific question at hand (Fig. 2). The protein CD163 was identified as the likely host receptor for the porcine virus PRRSV (116) using cells from African green monkey cells (116), leading to the production of PRRSV-resistant pigs that could save hundreds of millions of dollars per year (117).

After my return to England it appeared to me that collecting all facts which bore in any way on the variation of animals & plants under domestication & nature, some light might perhaps be thrown on the whole subject ( 128).

Darwin developed his theory of natural selection by considering patterns shared across seemingly very different species. His input data were a naturalists observations, but adopting this approach in genomics requires far more complex resources. We must go beyond the obvious (e.g., integrating genetics, bioinformatics, and medicine), and engage with anthropology and other historical sciences, experts using different knowledge systems, and the public. In the process, it is critical to address the systemic racism, sexism, and ableism that has been reinforced by twisted interpretations of Darwins evolutionary theory. Collaborations where each field retains its unique strengths, rather than developing a single perspective, are essential, as are new modalities for communicating across skill sets that are currently domain specific (SI Appendix, Table S1). We suggest six pillars for accomplishing this.

First, we propose that biology is the starting point for developing a common dialogue. In genomics, the work of biologists is too often perceived as the sample-collecting prelude to the main project, but connecting genomic variation to changes in organisms and ecosystems is fundamentally a biological research challenge. Thus, the contribution of biologists, particularly nonmolecular and noncomputational biologists, should be carefully considered and appropriately resourced when setting funding and sample dispersal priorities.

Second, increasing the number of and training for computational biologists is critical. The field is understaffed and underfunded, and those in it struggle with conflicting priorities. We need to recruit computational experts into the biological sciences, and provide the training in biology and biomedicine tailored to their area of interest, ranging from laboratory work to field biology (129).

Third, comprehensive training in computational biology should be a requirement for all fields. While not reducing the need for highly skilled computational biologists, it will enable field and laboratory-based scientists to do crucial initial analyses. Better computational and data literacy, taught as an integral part of science education (130), will facilitate collaborations between those collecting data and those doing much of the analysis. Existing training opportunities [e.g., Data Carpentry workshops (131); weeklong NSF-sponsored Genomics of Diseases of Wildlife courses (132)] should be expanded globally, and more extended programs developed (e.g., embedding in another research group for a semester).

Fourth, training opportunities in science communication should be expanded (133). Genomics is a global science, and as such requires engagement between scientists and nonscientists alike. Education programs that embrace narrative, social learning, digital media, and gamification reach hundreds of thousands of people (134). Ongoing, effective communication between all stakeholders will help ensure that research ultimately benefits public health, sustainable agriculture, and biodiversity conservation.

Fifth, we call for data-sharing with minimal restriction and delay, and adherence to the FAIR (findability, accessibility, interoperability, and reuse of digital assets) data principles (135). The FAIR principles are followed by major genomic consortia including ENCODE (136), FAANG (Functional Annotation of Animal Genomes) (137), the Alliance of Genome Resources (138), and the Genomic Standards Consortium (139). When necessary, we should modify existing data standards to support cross-species comparisons.

Finally, more support for museums, including zoos, aquaria, and botanical gardens, is an absolute necessity (140). Museums are irreplaceable reservoirs of specimens, history, and ideas, and communicate the value of science. They are essential partners in any effort to understand all of the worlds species. Rather than sample providers, we envision museums as something akin to a public library, where information is shared, specimens are protected, and safeguards supporting responsible access are in place.

We stand at the precipice of a new genomic age, with the power to both read and write DNA. Even as therapeutics based on genome editing save lives (141), we grapple with the ethical dilemmas inherent in editing germline cells (142). The most useful guidebook to this brave new world is the evolutionary past, and its constant testing of new variants through natural selection. With the technology to sequence DNA, assay cellular activity, and measure phenotypes at massive scales, we can read the results of that grand experiment.

To understand how genomes shape organisms and ecosystems, we must look outside our own species to all life on Earth. The conceptual foundation is basic evolutionary theory, some of it first described by Charles Darwin, but it requires scale and scope that would have been difficult for the 19th century naturalist to grasp, yet is now achievable. It is incumbent on us to figure out how we use these tools effectively for scientific discovery, for advancing medicine, and for protecting our world.

To illustrate the potential, we return to the Galapagos for a thought experiment with Darwins finches (143). Imagine we could collect genome sequences not just for every bird on those islands, but for all the animals, plants, and microbes interacting with each bird, and imagine we could do so for every generation since the birds first colonized the islands. Our data collection continues to the present day, and we capture the disruption of the Industrial Age, and know the history of geopolitical events. We measure organismal phenotypes, from morphology to health to feeding behavior to reproduction, and record all interactions between species, and changes with each generation, with incredible precision. Finally, we collect detailed data on rainfall, sea and air temperatures, and other meteorological events.

In reality, in-depth monitoring can inflict unacceptable damage on fragile ecosystems, illustrating the need for careful study design, and technology that minimizes harm. Any project so broad in scope raises complicated ethical, legal, and social issues that must be carefully addressed (144). The potential for discovery in such rich datasets, extending far beyond genomics, encapsulates the vision of a more extensive, inclusive, Darwinian approach to genomics.

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Darwinian genomics and diversity in the tree of life - pnas.org

British scientists have created a fast, less costly process for genome sequencing each coronavirus case they examine.

Britain is now a world leader in COVID-19 sequencing. This helps public health officials follow the spread of new variants, develop vaccines and decide when restrictions on movement are necessary.

Researchers at the Sanger Institute in Cambridge and other laboratories in Britain have a new mission. They are sharing what they have learned with scientists around the world.

The Omicron variant now spreading in many countries shows the need for worldwide cooperation, said Ewan Harrison. He is a top researcher at Sanger.

Omicron was first found by scientists in southern Africa who quickly informed the world and gave officials time to prepare.

Since dangerous mutations of the virus can happen anywhere, scientists must continually watch its development to protect everyone, Harrison said.

We cant just kind of put a fence around an individual country or parts of the world, because thats just not going to cut it, he said.

Cambridge University Professor Sharon Peacock understood the importance of sequencing the virus early in the pandemic. She knew sequencing would be important to fighting the virus. She received British government money for a national organization of scientists, laboratories and testing centers known as the COVID-19 Genomics UK Consortium.

The consortium is now working to increase knowledge of sequencing around the world. It has built training programs for researchers in developing countries. The programs include planned online classes on information sharing and working with public health officials. The goal is to help researchers build national programs to sequence COVID-19 viruses.

There is inequity in access to sequencing worldwide, the group said, adding that it wants to end the unequal situation.

By sequencing as many cases of the virus as possible, researchers hope to identify variants of concern as quickly as possible. They can then follow their spread and give early warnings to health officials.

Britain has supplied more COVID-19 sequences to researchers around the world than any country other than the United States. It has also sequenced a bigger percentage of its cases than any large nation.

Researchers in Britain have released about 1.68 million sequences, or about 11 percent of reported cases, said GISAID. GISAID is an international organization that works for quick sharing of virus information.

Over the past two years, labs around Britain have refined the process of gathering and studying COVID-19 viruses.

This has helped cut the cost of examining each genome by 50 percent. It has also reduced the time is takes to sequence from three weeks to five days, said the research group Wellcome Sanger.

Increasing sequencing ability is like building a pipeline, said Dr. Eric Topol. He is head of innovative medicine at Scripps Research in San Diego, California. In addition to buying costly sequencing machines, countries need supplies of reactive chemicals for the machines. They also need trained people to do the work and who understand the sequences. They also need systems to share the information quickly.

Meeting those needs has been difficult for many nations, including the U.S. It is even harder for developing nations, Topol said.

Many of these low- and middle-income countries dont have the sequencing capabilities, particularly with any reasonable turnaround time, he said. So, the idea that theres a helping hand there from the Wellcome Center is terrific. We need that.

Virus samples arrive from around the country. Lab assistants carefully prepare the genetic material. It is placed into the sequencing devices that read each samples unique DNA. Scientists then examine the information and compare it with other identified genomes to follow mutations. They want to see how the virus is developing.

Because COVID-19 mutates all the time, it is important to look for new, more dangerous variants that might be resistant to vaccines, Harrison said. This information will help researchers change existing vaccines or create new ones to fight the virus.

Harrison praised South Africa for quickly informing the world about the Omicron variant. But other countries, he said, punished South Africa by restricting travel and harming its economy. All nations must be permitted to publish new variant information without fear of being punished, he said.

Im Susan Shand.

The Associated Press reported this story. Susan Shand adapted it for Learning English.

__________________________________________

genome n. the entire set of genetic instructions found in a cell

sequencing n. a process of finding out the order of the amino acids forming the genetic material of an organism

variant n. something that is different in some way from others of the same kind

mutation n. a permanent change in the genes of an organism

consortium n. a group of people or companies that agree to work together

access n. the ability to get something, enter a place or meet someone

refine v. to improve (something) by making small changes

sample n. a small amount of something that is used to give information about what it was taken from

unique adj. used to say that something or someone is unlike anything or anyone else

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British Labs Supply the World with Genetic Information about COVID-19 - VOA Learning English

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The United Kingdom declared BA.2 a variant under investigation amid an increase in the number of patients infected by the that sub-lineage of the omicron variant of the novel coronavirus. The prevalence of the variant has increased to 426 since it was first isolated in the country December 6. 2021.

At least 40 countries have detected this variant since November 17, 2021. India has reported 530 samples to the Global Initiative on Sharing Avian Influenza Data (GISAID) the worlds largest database of novel coronavirus genome sequences. The variant has also been found in Denmark, Sweden, Philippines, France, Norway and Singapore.

The designation was based on rising numbers domestically and globally, the United Kingdom Health Security Agency (UKHSA) noted in its latest update from January 21, 2021. There is still uncertainty around the significance of the changes to the viral genome, and further analyses will now be undertaken.

So far, there is insufficient evidence to determine whether BA.2 causes more severe illness than Omicron BA.1, said Dr Meera Chand, COVID-19 Incident Director at UKHSA. She added:

We do know that the BA.2 variant does not have the mutation which results in an S-gene target failure (SGTF) during some polymerase chain reaction (PCR) tests a quick method used widely to detect which variant of the SARS-CoV-2 variant it is since genome sequencing is a time consuming process. This is why it was popularly dubbed as the 'stealth variant' in December when it was first discovered.

The stealth variant has 32 mutations in common with BA.1 but also has 28 other mutations, she noted. It remains to be seen what this means for the virus' virulence and infectivity.

BA.2 is unlikely to have any severe impact on the ongoing omicron wave, argued Tom Peacock, a virologist at the Imperial College London, in a series of tweets. Several countries are near, or even past the peak of BA.1 waves. I would be very surprised if BA.2 caused a second wave at this point.

Even with slightly higher transmissibility, this absolutely is not a delta to omicron change and instead is likely to be slower and more subtle, he said. While BA.1 is now the dominant strain in UK, BA.2 is likely to replace it soon.

The stealth version is less likely to evade immunity than omicron to evade immunity, according to predictions by Bloom Lab, a Seattle-based lab studying molecular evolution of proteins and viruses, made in December last year.

Read our coverage of the COVID-19 pandemic here.

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COVID-19 update: Why did UK call BA.2 a 'variant under investigation'? - Down To Earth Magazine

Baylor College of Medicine: C. Thomas Caskey

C. Thomas Caskey, professor of molecular and human genetics at Baylor College of Medicine, has died at the age of 83. Caskey began his career with Baylor College of Medicine in 1971, when he also founded the Institute for Molecular Genetics, currently known as the Department of Molecular and Human Genetics. In 1994 Caskey moved on to Merck Research Laboratories, where he was senior vice president of human genetics and vaccines discovery. He later returned to Houston to become CEO of the Brown Foundation Institute of Molecular Medicine at the University of Texas Health Science Center, and in 2011 came back to Baylor to work in his current role. In addition, in 2019 he became chief medical officer at Human Longevity.

His research identified the genetic basis of 25 major inherited diseases and clarified the understanding of "anticipation" in the triplet repeat diseases fragile X syndrome and myotonic muscular dystrophy, Baylor said. His personal identification patent is the basis of worldwide application for forensic science, and he was a consultant to the FBI in forensic science. His recent publications addressed the utility of genome-wide sequencing to prevent adult-onset diseases, and his research focused on the application of whole-genome sequencing and metabolomics of individuals to understand disease risk and its prevention, the school noted.

Caskey was a member of the National Academy of Sciences, the National Academy of Medicine (serving as chair of the Board of Health Sciences Policy), and the Royal Society of Canada. He was a past president of the American Society of Human Genetics, the Human Genome Organization, and the Texas Academy of Medicine, Engineering and Science.

UK Biobank: Mahesh Pancholi

Mahesh Pancholi has joined the UK Biobank as chief information officer. Previously, he was an enterprise account manager for genomics and life sciences research at Amazon Web Services, and prior to that, a business development manager at OCF. Before that, he was head of research computing at Queen Mary University of London, where he also received a bachelor's degree in genetics.

CS Genetics: Jeremy Preston

Genomics technology company CS Genetics has named Jeremy Preston as chief commercial officer. Preston joins the company from Illumina, most recently serving as VP of regional and segment marketing. Earlier roles at Illumina included VP of specialty sales and marketing and senior director of product marketing. Prior to Illumina, Preston was associate director of product marketing at Affymetrix. He completed his postdoc in molecular biology at Japan's Riken, and his Ph.D. in molecular biology at La Trobe University in Melbourne.

For additional recent items on executive appointments and promotions in omics and molecular diagnostics, please see the People in the News page on our website.

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People in the News: Baylor's Thomas Caskey Dies; New Appointments at UK Biobank, CS Genetics, More - GenomeWeb

A major new genomic study into the genetic markers of the rare Lop pig breed has reinforced the need for robust measures to be in place to tackle in-breeding and prevent further decrease in the population of the rare breed.

The findingspave the way for action to save the rare native pig breed that is far more bespoke and scientifically informed than ever before,said Rare Breeds Survival Trust (RBST) which commissioned the study in conjunctionwith the British Lop Pig Society.

Hair samples were collected from 190 individual pigs raised in 40 farms, constituting a cross section of the current breeding population. The hair samples were used by experts at SRUC (Scotlands Rural College) to derive genome-wide genotypes for each pig.

Professor Georgios Banos at SRUC explained: This work demonstrates the genetic uniqueness of the British Lop pig.We used modern technologies and data to derive information that may be used as a practical breed purity test and also inform breeding strategies aiming to safeguard the integrity of the breed.

The studyidentified unique genetic markers for the Lop breed for the first time, as well as identifying a high level of genomic inbreeding and a decrease in the Lops effective breeding population size to a concerning level of 40-45.

The Lop pig is in a perilous position and is categorised as a Priority Breed on the RBST Watchlist due to its low numbers and concerns about genetic diversity, said rare breeds survival trust chief executive Christopher Price.

This first ever identification of the genetic markers of the Lop breed not only provides the basis for best animal selection for breeding programmes and for storing genetic material, but it also enables us to form tailored programmes to increase genetic diversity within the breed.

Mr Price called the study really important to ensure other rare native breeds survive too, and said they now hope it will set a template for how other rare breeds could access similar genetic data.

Giles Eustice, who farms with British Lop pigs at Trevaskis Farm in Cornwall and is chairman of the British Lop Pig Society, said the new genomic data was a fantastic boost for the breed as it proves there is still the diversity required to bounce back.

We have a committed following of old and new breeders and I am confident with the new tools we have been given we can achieve the diversity goal required, said Mr Eustice. I am interested in using the sequencing to explore some of the Celtic white pigs in existence with much similarity to the British Lop; they could hold a diversity key that may be needed.

The genomic study is part of a five year project which began in 2019 as partnership between RBST and the British Lop Pig Society with major funding from the Gerald Fallowes Discretionary Trust.

Along with the genome study, the project is collecting embryos and semen to support the strength of the breed now and to bank genetic material in preparation for a future crisis for the breed.

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New genomic study highlights robust measures needed to save rare Lop pig breed - Pig World

Abstract

The field of genomics has benefited greatly from its openness approach to data sharing. However, with the increasing volume of sequence information being created and stored and the growing number of international genomics efforts, the equity of openness is under question. The United Nations Convention of Biodiversity aims to develop and adopt a standard policy on access and benefit-sharing for sequence information across signatory parties. This standardization will have profound implications on genomics research, requiring a new definition of open data sharing. The redefinition of openness is not unwarranted, as its limitations have unintentionally introduced barriers of engagement to some, including Indigenous Peoples. This commentary provides an insight into the key challenges of openness faced by the researchers who aspire to protect and conserve global biodiversity, including Indigenous flora and fauna, and presents immediate, practical solutions that, if implemented, will equip the genomics community with both the diversity and inclusivity required to respectfully protect global biodiversity.

Since the early days of the Bermuda Accord (1), Human Genome Project (2), and the Fort Lauderdale Agreement (3), the field of genomics has been strongly committed to open data sharing, and the calls for improved data-sharing approaches have only become even louder in the recent response to the COVID-19 outbreak (4). Rapid sequencing and open release of SARS-CoV-2 viral genome sequences throughout the outbreak have aided vaccine development, efficacy assessments, and continual monitoring of the viruss evolution in ways unimaginable a few decades ago (5). Similarly, the open release of the human reference genome and follow-up studies, such as the 1000 Genomes and the gnomAD data resource, have transformed our understanding of human genomic variation and disease and are exemplars of successful community resource-building projects. Now, new projects, such as the Earth BioGenome Project (6), aim to sequence the genomes of all living eukaryotic species to further understand molecular evolution, catalog the worlds biodiversity, and inform future conservation efforts. Such projects have the potential to bring the benefits of genomics to all people and species, but the past model of large consortia generating vast troves of data, favoring the inclusion of some over the exclusion of others, is both damaging and inequitable, requiring movement beyond the principles defined in Bermuda and updated in Toronto (7). These ambitious projects will require contributions from community and academic partners around the globe, and so the genomics community must develop and implement inclusive data-sharing policies and infrastructure that respect the rights and interests of all people.

Unfettered openness of genomic data, and the hows and whys of its enforcing open-science norms, impinge on the rights of Indigenous Peoples. As one example, the Navajo Nation became rightfully wary of freely contributing samples and genomic data and, in 2002, placed a tribal-wide Banishment Order on genetics research (8). In Canada, the three councils that fund research have formally adopted policies that were developed by Indigenous Peoples and scholars, which include that data and samples from Indigenous communities must be collected, analyzed, and disseminated under the terms of a mutually determined research agreement that respects community preferences to maintain control over, and access to, data and human biological materials collected for research (9). Only by reconsidering the definition of openness and who it benefits within the context of the current inequitable infrastructures can a more inclusive genomics community be built to responsibly sequence all of life for the future of life (6).

The prospect of cataloging the genome reference sequences for a huge number of representative species is only possible thanks to the exponential technological advances of the genomics community over the past 40 y. Whereas the initial Human Genome Project cost several billion in todays dollars (USD), the sequencing and assembly of high-quality vertebrate reference genomes now costs under $10,000 and continues to drop rapidly. Leveraging these new sequencing technologies, the Vertebrate Genomes Project has now generated over 100 new vertebrate reference genomes (10), and in the coming year, the Human Pangenome Reference Consortium (https://humanpangenome.org/) aims to create hundreds of new reference genomes that will better represent human genetic diversity. Along with reductions in sequencing costs, the underlying technologies are also becoming increasingly portable, with nanopore-based technologies now enabling on-site sequencing in the most remote corners of the world (11).

This genomics revolution is timely, in the midst of the Earths sixth mass extinction with 35,500 species on the International Union for Conservation of Nature Red (threatened) List (https://www.iucnredlist.org/en). Unlike the mass extinctions of the past, the sixth has been caused as a result of the actions of just one species, humans, and as a species we must act swiftly to halt the dangerous loss of biodiversity and extensively catalog what remains. Providing a catalog of genomic sequences for all life will be important for informing decisions about the effects of climate change on species diversity (12), the development of conservation strategies for threatened and endangered flora and fauna (13), assessing the success of ongoing conservation efforts, and for the preservation of genomic biodiversity before it is lost forever to extinction (6).

The importance of conserving biodiversity is universally recognized, but Earths biodiversity is not uniformly distributed. The Critical Ecosystem Partnership Fund currently recognizes 36 biodiversity hotspots, defined as regions with over 1,500 endemic vascular plant species. These hotspots have suffered a 70% loss of their native vegetation (14). Hotspots will be a top priority for any genomic conservation project, but many of these hotspots overlap Indigenous lands. Indigenous Peoples and lands historically have been exploited and excluded, and not engaged by the genomics community (15). Thus, it is imperative for the genomics community to work as equal partners with Indigenous Peoples going forward. To move forward, however, new infrastructure and policies are required to facilitate alternative modes of data sharing that can coexist with the current open-sharing policies of international genomics consortia. Current blanket open data-sharing policies override the rights of Indigenous Peoples, specifically the right to determine the use and mode of sharing Indigenous resources, which includes data. A fact that contravenes the United Nations (UN) Convention on Biological Diversity (CBD) as a matter of international law (16), violates several rights stipulated in the UN Declaration on the Rights of Indigenous Peoples (17), and results in perpetuating the marginalization of these Indigenous Peoples (18).

Open genomic data are defined here as genomic sequence information that is made freely available without restrictions on use, copying, or distribution. The worlds most popular molecular sequence databasessuch as the National Center for Biotechnology Informations GenBank, the European Nucleotide Archive, and DNA Database of Japanstrictly adhere to this model. Furthermore, in 2011 a Joint Data Archive Policy was drafted and adopted by many leading journals that reinforced open data sharing (19). Open data sharing in genomics has fostered a productive and collaborative international research community; it aspires to reduce systematic wealth and power inequalities by extending research opportunities from partners with a large investment in genomics capacity and capability to those partners with lower investment. In addition, open data sharing has provided knowledge that is more transparent, accessible, and verifiable, which has improved the efficiency and reliability of genomic research (20). However, despite its success, by negating local and regional representation and participation in governance, it has also resulted in the development of data-sharing policies that do not maximize opportunities for all participants in an equitable manner (21).

Moreover, when strictly mandated, open data policies can have the unintended consequence of excluding many minority communities, including those Indigenous Peoples who wish, for a variety of legitimate reasons, to retain control over the resources and data derived from their lands, species, and waters. The lack of clear, respectful, and operational policy that respects Indigenous rights breeds mistrust among Indigenous partners and not only hinders the inclusion of Indigenous science in international biodiversity and conservation efforts, but can also build opposition that results in the stagnation and reversal of Indigenous genomics projects (22). By demanding rigid policies on data sharing, the genomics community has forged rules premised on a single worldview. It undermines the rights and interests associated with traditional knowledge, a phenomenon scholars of Indigenous communities call epistemicide (23). Despite international consortia recognizing the rights of Indigenous Peoples, a lack of accountability and clarity for implementation of appropriate policies has exacerbated tensions between Indigenous communities and international genomic efforts (21).

In the past, the worlds of genomic science and Indigenous communities intersected mainly through Indigenous Peoples being used as subjects of research conducted by non-Indigenous researchers. Research was done on Indigenous Peoples, not by them and very rarely for them. The mistrust of the scientific community among Indigenous communities is well-earned: it has been caused by years of exploitation, mistrust, power imbalances, and inequality (24). It has included decades of taking and using Indigenous samples and data without adequate consent and consultation (24, 25); Indigenous data and samples not being properly attributed or acknowledged as coming from Indigenous lands and waters; Indigenous data being misused through bioprospecting and biopiracy (2628); Indigenous data being scientifically interpreted without cultural or contextual knowledge (29); and researchers who have claimed authority over the Indigenous world by relying on quantitative data rather than traditional knowledge and lived experience (30). Furthermore, the failure of researchers to disseminate research outcomes respectfully through mechanisms that are meaningful and applicable to Indigenous partners, such as asset-based approaches (31), has fomented a sense of a lack of control, lack of access, lack of opportunities to derive benefits from the use of traditional knowledge and genetic resources, and a lack of opportunity to integrate traditional ways of knowing into research plans (32). Through asset-based approaches, results can be communicated more meaningfully and ameliorate the five Ds of statistical data on Indigenous Peoples: disparity, deprivation, disadvantage, dysfunction, and difference (33).

Indigenous Peoples are the guardians and sovereign authorities of their lands and have been since time immemorial. Indigenous Peoples have their own unique beliefs, values, and worldviews. They are highly diverse; however, a commonality shared among many is a deep interconnectedness, interdependence, and intimate connection to their lands and waters (34). In regions of Africa, for example, life is not perceived through an individualistic lens but is experienced as relational and collective; this worldview is known as Ubuntu (35), an example of Indigenous or traditional knowledge that is based upon lived experience extending as far back as the Pleistocene era (36). It has been developed over time, informed by an extensive system of principles, beliefs, and traditions. In New Zealand, a governmental inquiry into the Mori knowledge system, or Mtauranga Mori, concluded that this system of knowledge is fundamentally different from Western science. The Mori knowledge framework has evolved through its own cultural context and evolutionary pathway (37). These epistemological differences in knowledge sharing and individual possession are largely incommensurate with existing intellectual property rights, which privilege and support Eurocentric notions of knowledge commons with no or limited rules around access to knowledge and property. However, rather than being treated as outdated or inferiorattitudes that embody cognitive imperialism and epistemic violencetraditional knowledge systems should be acknowledged, integrated, treated as a coequal, and considered when interpreting findings. One system of knowledge should not eclipse the other. When recognized in this way, traditional knowledge is integral to knowledge production contributing both technically and scientifically to the protection and sustainable development of Indigenous lands, resources, and data through an intrinsic understanding of the interdependence of land and its inhabitants (38).

Any complete catalog of Earths biodiversity must necessarily include species on the lands of Indigenous Peoples. Thus, for global genomic conservation efforts to succeed, the genomics community will need to adapt its open data policies to Indigenous data sovereignty and knowledge systems. To achieve this, policies must be operationalized that embrace multiparadigmatic research approaches (39, 40) that recognize the inherent sovereignty of Indigenous Peoples and that remove barriers to those Indigenous communities who wish to contribute to bioconservation as equal partners.

Over the past two decades there has been an international call for the recognition and protection of Indigenous data rights. Indigenous data sovereignty (IDSov) refers to the individual and collective rights of Indigenous Peoples to control data from and about their communities, land, species, and waters (30).

In 2010, the Nagoya Protocol was established and adopted by the UN CBD (41) to protect, promote, and fulfill this right. It has been fundamental in providing guidance on access and benefit-sharing of Indigenous resources and data. Article 12 states that parties shall, in accordance with domestic law, take into consideration Indigenous and local communities customary laws, community protocols, and procedures. The Nagoya Protocol now has 2,000 internationally recognized certificates of compliance, but notably does not include some nations that have both Indigenous Peoples and a large genomic research program (e.g., the United States, Canada, New Zealand, and Australia). Despite this, domestic legislation over a sample/genetic resource from a signatory nation extends to where that sample/genetic resource is housed or used. Thus, nonsignatory countries are expected to implement Nagoya legislation if resources have been obtained from a country where the Nagoya Protocol is enforced.

In 2014, the UNs General Assembly adopted the United Nations Declaration on the Rights of Indigenous Peoples (17), which affirms the right of Indigenous Peoples to control, protect, and develop manifestations of their sciences, technologies, and cultures, including human and genetic resources (Article 31), the right to the conservation and protection of the environment and the productive capacity of their lands (Article 29), as well as the right to participate in decision-making in matters which would affect their rights (Article 18). Furthermore, the UN has also developed 17 Sustainable Development Goals (SDG) to be achieved by 2030. In 2015, these were agreed upon and adopted by 193 countries worldwide, including the United States, Canada, New Zealand, and Australia (42). SDG 15 aims to Protect, restore and promote sustainable use of terrestrial ecosystems, sustainably manage forests, combat desertification, and halt and reverse land degradation and halt biodiversity loss (42). Its associated Sustainable Development Solutions Network Target 15.6 aims to ensure fair and equitable sharing of the benefits arising from the utilization of genetic resources, and promote appropriate access to genetic resources (42), a provision that has particular importance for marginalized communities, including Indigenous Peoples. Additionally, many individual nations have binding legislation covering their own Indigenous populations. For example, in New Zealand, the founding charter, subsequent legislation, and other policies covering Indigenous species require that all data and intellectual property be retained by the government within New Zealand (43, 44). Indigenous claims to cultural and intellectual property are also being addressed in New Zealand, where a work program to address the issues identified in WAI262 Report Ko Aotearoa Tenei has just been developed and some projects have been initiated (45, 46).

Rights secured through IDSov can be at odds with the open by default culture of the genomics field, leaving Indigenous genomic data unsupported by the decades of open infrastructure that has been built by the genomics community. In an effort to close the gap, higher-income countries, such as Australia, Canada, and New Zealand, have established national Indigenous-driven human genomic efforts, including the work of the National Centre for Indigenous Genomics (https://ncig.anu.edu.au/), the Silent Genomes project, and the Aotearoa Variome, respectively (47). These national efforts are examples of Indigenous-driven human genomics research programs intended to directly benefit Indigenous Peoples. In Canada, protocols have also been established for the protection of nonhuman data, specifically through the Tri-Council Policy Statement (48) on research ethics that provides protection over Indigenous samples. Furthermore, research licensing in the three territories of Canada protects samples and data collected on Indigenous lands (4951).

To date, three national-level IDSov networks provide processes and protocols to enable Indigenous data governance (SI Appendix, Table S1): Te Mana Raraunga Mori Data Sovereignty Network, the United States Indigenous Data Sovereignty Network, and the Maiam nayri Wingara Aboriginal and Torres Strait Islander Data Sovereignty Group in Australia. However, blanket adoption of national efforts is not feasible in countries that lack substantial genomics investment or in which Indigenous governance structures are less established or respected.

Alongside the national efforts, IDSov is also gaining recognition on an international level through a variety of initiatives. For example, in 2019 the Global Indigenous Data Alliance (GIDA) (https://www.gida-global.org) was established to build a global community for the development of data-sharing infrastructure, data-driven research, and data use policies. In 2020, ENRICH (Equity in Indigenous Research and Innovation Co-ordinating Hub) was established in a collaboration between New York University and the University of Waikato. ENRICH supports IDSov-based protocols, Indigenous-centered standard-setting mechanisms, and machine-focused technology that informs policy and transforms institutional and research practices (https://www.enrich-hub.org/bc-labels). Platforms such as the International IDSov Interest Group have also been set up under the Research Data Alliance (https://www.rd-alliance.org/groups/international-indigenous-data-sovereignty-ig). These initiatives include the development of specific tools and practical mechanisms alongside education and training to provide a foundation for further development of ethical research guidelines that address Indigenous rights and interests.

The FAIR principles are a common refrain of open data efforts that encourage data to be Findable, Accessible, Interoperable, and Reusable (52). In 2019, GIDA released a set of complementary CARE' Principles (53) that highlight the core values and expectations of Indigenous Peoples when engaging with the scientific community. These principles encourage the consideration of collective benefit, authority to control, responsibility, and ethics in Indigenous data governance. Such efforts toward developing new policies to respect and promote IDSov are essential; however, there is now the difficult challenge of informing and implementing IDSov principles, policy, and mechanisms within the global field of genomics (54).

A brief inspection of the publicly available data access and governance policies of international genomics-based consortia showcases where progress has been made and where it is needed the most. Notable exceptions include the H3Africa Consortium (55), which has led the way in the adoption of Indigenous policies for human genomics, providing clarity to researchers through an in-depth set of principles and guidelines that hold participating researchers accountable for their implementation. At present, many nonhuman-focused consortia lack governance and data policy information. Some claim to recognize the rights of Indigenous Peoples but provide no pragmatic implementation plan or accountability measures. Exceptions in the nonhuman space include Genomics Aotearoa (56), which have actively developed engagement and biobanking frameworks in partnership with Mori to guide all consortium members while engaging with Indigenous data. However, for many other efforts, the lack of clear and transparent adoption of IDSov policy is problematic for a successful engagement between genomic researchers and Indigenous partners, given the incompatibility of unfettered open data and IDSov. Moreover, there remain ongoing practical challenges in keeping provenance and cultural connections between Indigenous communities and the data generated from their lands and waters transparent and clear within the databases themselves. Open data have successfully encouraged transparency and inclusion among international genomic research collaborations, but it is now time to ensure such success extends to including Indigenous partners and IDSov in these collaborative infrastructures.

The conflicts between IDSov and open data in genomics research are not new and have been extensively discussed (18). Progress, although slow, is being made to identify and provide solutions to these incompatibilities. Local Contexts is a key international initiative that recognizes and advances the rights of Indigenous Peoples in museum collections and their data through a unique set of traditional knowledge and biocultural labels and notices (with licenses under development) (57). Inspired by the Creative Commons licensing structure (https://creativecommons.org/), Local Contexts initiated this work in 2010, producing a suite of practical mechanisms designed to enhance the protection of Indigenous communities and hold researchers accountable. That process entailed community partnership and collaboration, as will scientific projects that follow its precepts. As durable digital tags with unique IDs, the labels (for communities) and the notices (58) (for researchers and institutions) provide an opportunity to include Indigenous protocols and expectations around the sharing of knowledge as metadata within the data infrastructures. As a result, this information, such as the origin of samples and data, travels with the data across platforms. Through this mechanism, Indigenous partners are given a voice, and future research engagement is encouraged; its aspiration is to leave no one behind.

The field of genomics is operating under data-sharing practices established decades ago. A status quo that began with the Bermuda Principles defining the best mode of data sharing with respect to human data, these principles were then extended by the Fort Lauderdale Agreement to include nonhuman data and further updated in Toronto (59). Since Toronto, community-based efforts such as the Global Alliance for Genomics and Health (https://www.ga4gh.org) have reconsidered these data-sharing frameworks, developing responsible and inclusive human data-sharing policies and toolkits for genomics researchers.

An equal effort is now needed for nonhuman data, and nonhuman genomics continues to embed inherent biases and inequality, doing little to address existing disparities. Indigenous Peoples are part of contemporary life, they are not outside of modernity. Indigenous voices need to be heard. It is both a moral responsibility and a legal obligation to share benefits of research fairly and to respect traditional knowledge derived from their lands and waters. Genomics research needs to implement a future that has hitherto been mainly aspirational, a future that builds intellectual bridges between different ways of knowing and being. The appropriate acknowledgment, understanding, and implementation of Indigenous Peoples rights while conducting genomic research provide a foundation to reach this goal.

Change must happen both at the individual and institutional level to ensure that Earths genomic biodiversity can be ethically cataloged. Several suggestions, references, and resources are provided to aid this transformation.

Operationalizing clear policies that respect Indigenous rights will communicate to potential Indigenous research partners what principles guide the research activity, the manner in which the researchers will conduct themselves, and the standards enforced and upheld. By providing clarity and increasing transparency, trust can be built and remove potential impediments to building relationships with Indigenous partners. When implementing these policies, inclusion does not equal assimilation. Respecting and cultivating divergent practices and beliefs is important to avoid monoculturalization. Indigenous Peoples wishes regarding data access and benefit-sharing must be honored, making one-size-fits-all open data licenses inappropriate. International consortia seeking to perform Indigenous research must implement IDSov policies and engage with Indigenous communities in a manner that allows them to contribute on mutually agreed terms.

To change the culture from research that is done to Indigenous Peoples rather than by or for them, researchers, institutes, scientific journals, repositories, and funding bodies must change the status quo. Researchers must reflect upon their personal assumptions and biases and listen attentively to alternative frameworks. This can be done through questioning scientific orthodoxies and recognizing that research, even when good is intended for all humanity, can create power and benefit imbalances. In beginning a new project, researchers must question the expectations of each research partner, the genomics community, the institutions, the funding bodies, the ethics review boards, the Indigenous partners, and the Indigenous communities who have provenance over the data and organisms in question. Rather than pushing the boundaries, attempt to foresee the consequences and deeply consider at the outset of each research project its social license and duty to diverse societies.

Although significant progress toward policy development has been made, further clarity is particularly needed for nonhuman Indigenous data. As species do not respect country or land borders, policy is required to provide clarity to researchers regarding species that straddle the borders of Indigenous and non-Indigenous lands, and those species that are of special importance to Indigenous Peoples but are found also on non-Indigenous lands.

To ensure an even distribution of power, financial resourcing, and benefit, researchers who wish to partner with Indigenous communities must first ensure their own cultural competency while also prioritizing engagement with Indigenous communities at the onset of the study. This allows the necessary time for a partner relationship to be built from mutual agreement as to the role and responsibilities of both groups, the community, and the researchers. Early engagement also provides Indigenous communities with relevant details pertaining to all aspects of the project, from sample collection to potential research publications and intellectual property development and benefit-sharing in a clear, transparent, and accessible fashion, including: the background, the scope of the research, potential outcomes of the project, and any foreseen risks associated with the research. By doing so, both researchers and Indigenous partners have all of the necessary information and education to conceptualize and design the research project in a concerted fashion that acknowledges the communities long-standing relationship with local species and greater breadth of knowledge of the ecological systems and how they are changing (60, 61). This equips all parties with a fair and equal voice in setting research goals, understanding and contextualizing data, and planning of the time and budgetary requirements needed to achieve research goals ethically. Early engagement also allows project outcomes to be jointly interpreted, drafted, and disseminated by multiple parties, rather than the typical one-sided reporting driven by research institutions. Furthermore, the dissemination of outcomes in the Indigenous local languages will enhance accessibility for Indigenous community partners so that the community can relay the outcomes to others, and this process does not depend on an external scientist. This joint dissemination of research outcomes is extremely important for maintaining trust, communicating mutual benefits, and ensuring that Indigenous knowledge is not misappropriated. Indigenous partners should also be included in the evaluation phases of a project to include Indigenous best practice and better understand research impacts in an Indigenous context.

Projects that have been conceptualized and funded prior to engagement already fall outside the best practices for engagement with Indigenous Peoples. Here, other considerations are crucial for a successful partnership, such as minimizing power inequalities throughout the remaining research period. Indigenous Peoples, such as the African San tribe, Mori in New Zealand, and the Australian Institute of Aboriginal and Torres Strait Islander Studies in Australia, have considered and documented the best practices and expectations for engagement in these circumstances (60, 62, 63). These best practices include understanding and incorporating the expectations of Indigenous communities into the research plan; clearly communicating the scope of research, timelines, funding, methods of consent as informed by the Indigenous research partners, and all potential research outcomes; identifying short- and long-term risks and benefits and how they will be shared; building sustainable long-term governance and communication frameworks; discussing potential barriers to project completion and the impacts of project incompletion on partners; and evaluating the cultural competency of the research team. A focus on the process rather than the product is also helpful in assuring that the project has an adequate timeframe and budget to achieve its stated outcomes in a respectful manner, keeping in mind that fast-paced, product-oriented, and extractive strategies are not compatible with Indigenous cultures and may lead to irrevocable harm (24).

The fully open model of sharing must be challenged; the inclusion of some should not be valued over the exclusion of others. Policies need to be cognizant of the history, needs, and worldviews distinct to each Indigenous community (64). To operationalize situated openness, a pragmatic implementation of IDSov policies and licenses is necessary. As it stands, IDSov policies are being actively developed and adopted; however, progress depends on implementing and enforcing these policies by the genomics research community. Ambitious international goals, such as the push to catalog all genomic information on Earth, sit at the interface of genomic science and Indigenous ways of knowing. Effective implementation of IDSov policies and power sharing between communities is necessary to ethically realize such visions. This will require multiparadigm research methodologies built upon commonalities, but also accepting of divergent beliefs and practices, to move away from the extractive and exploitative strategies of past research on Indigenous Peoples. The task is hard, but eminently achievable, as recently demonstrated by more inclusive, diverse, and political research paradigms developed by researchers in New Zealand, Australia, North America, Africa, Central and South America, and the Pacific (40). These stand as positive examples for how to best champion polycultural expression and establish a new status quo for the genomics community.

Open data sharing in genomics has fueled progress and brought benefits to a field that continues to grow, even as it ramifies into many different fields of research and application. However, it is evident that those doing the sharing, to date, have taken on very little riskand in many cases, stand to benefitfrom the act of openly sharing. To impose the same open data requirements on those with the most to lose by relinquishing control over use of resources and data is unfair, and when openness is stated as a prerequisite for participation, it can have the unintended effect of excluding marginalized communities. An infrastructure that allows for multiple modes of data sharing is needed, particularly modes that allow for materials and data over which Indigenous communities exert stewardship to remain under their control, and with respectful communication of findings and sharing of benefits with Indigenous communities. The Native BioData Consortium is the first tribal-driven BioBank in the United States (NBDC; https://nativebio.org/) and provides a model of how to facilitate the flexibility needed to share data in a manner respectful of all parties and worldviews. In an Aboriginal and Torres Strait Islander context, the idea of kinship speaks toward the interconnectedness and interdependence of all life (65), as well as water and geographical features. This relationship to land is shared among Mori (66), and First Nations and Inuit Peoples (67). Adequate time and resources must be assigned to directly coordinate conservation efforts with Indigenous partners who are the experts on implementing systems thinking approaches within their own lands.

To sequence everything requires the help and participation of everyone on equal and mutually agreed terms. Ultimately, genomic technologies can be advanced to the point of becoming commonplace, and initiatives are already under way to bring DNA sequencing into classrooms (68). As the field of genomics progresses, all research partners have the responsibility and opportunity to build a trustworthy and inclusive research community. Investing in outreach programs that pass on the latest technologies and methods such as the SING Consortium (https://www.singconsortium.org/) and IndigiData (https://indigidata.nativebio.org/) workshops, this capacity building will facilitate local research, fueled by local priorities and guided by local best practice. Graduate and undergraduate genomics courses should also include training in ethics and engagement best practices to improve the cultural competency of non-Indigenous researchers that may enter this space. This provides cultural safety but also alleviates expectations and responsibilities resting solely on Indigenous researchers shoulders (47). Infrastructure and opportunities for media producers local to the study should also be developed for the dissemination of genomic research findings in multiple languages, regions, and formats. These efforts will enable all partners, including Indigenous and other marginalized communities, to directly contribute to ongoing international genomics efforts and by fostering diversity within the field. It can help ensure that genomics infrastructure will be accessible and beneficial for all, and practices put in place to foster trust over the long haul.

Parties to the UN CBD and its Nagoya Protocol are currently reviewing the meaning of digital sequence information (DSI) and the requirement for a change to access and benefit-sharing policies under the convention that pertain to such DSI (41). As it stands, the term DSI is a placeholder used to facilitate discussions surrounding three data types: 1) DNA and RNA; 2) DNA, RNA nucleotide sequences, and protein-peptide amino acid sequences; and 3) DNA, RNA, and protein sequences as well as digital information pertaining to metabolites and macromolecules. All three of these definitions would include data contributing to reference genome sequences for nonhuman organisms. Prior to these discussions, there had been a fourth option for associated information, including traditional knowledge (69), but this was removed during the revision.

Despite the Nagoya Protocol calling for access and benefit-sharing, to date only 16 signatory countries have domestic legislation regarding DSI. Eighteen additional signatories are planning to or are in the process of drafting such legislation (70). The United States is not a signatory to the Convention, but United States representatives have attended the November 2021 review conference in China, and will attend further discussions in 2022. Many nations involved in the Earth BioGenome Project, European Reference Genome Atlas (https://vertebrategenomesproject.org/erga), the Human Pangenome Reference Consortium, and other international genomic collaborations are signatories. The ongoing CBD review has the goal of standardizing terms for access and benefit-sharing among all signatories, and discussions continue to include DSI. The international committee overseeing the CBD has expressed discontent with the status quo. Disparate policies among signatories and other major nations have led to the interpretation of open access to DSI as sufficient to fulfill access and benefit-sharing requirements in some cases, while in other cases formal agreements are required to share samples or sequence data. The review considers 13 recent publications relevant to access, benefit-sharing, and sequence data that have been categorized into five policy archetypes, some of which are mutually exclusive, while others can be combined (Table 1). Each archetype will be considered for cost-effectiveness, feasibility, and practicality, as well as uses of traditional knowledge. Access and benefit-sharing standards will be addressed again before a standardized policy is agreed upon and incorporated into the convention framework.

Potential policy options under review of the Convention on Biological Diversity, with respect to access and benefit-sharing and digital sequence information

The lack of infrastructure to trace the geographic origin of samples and DSI is readily apparent: only 12% of the sequence data in publicly available databases specifies a country of origin. The lack of proper infrastructure to monitor compliance with access, benefit-sharing, and sharing of DSI at each point in the value chain has also been flagged as a potential barrier to agreement, with block chain smart contracts highlighted as a potential solution (71).

Policies about access and benefit-sharing, and about sharing of DSI are in flux, but it is clear that unfettered open access to data and materials, including sharing of sequence data, is being questioned when it comes into conflict with Indigenous rights. National and international law are likely to evolve, and the scientific community would be wise to both directly engage in helping set the standards and practices but also to comply with the emerging laws, norms, and practices governed by national and international law.

Following basic principles in a transparent manner, with all parties having access to and an equal understanding of the research project, will help remove the barriers between the genomics community and Indigenous partners, and will facilitate a long-term partnership founded on trust, safety, honesty, and accountability. The genomics community must engage with each Indigenous partner in accordance with that communitys specific traditional beliefs, practices, and connections to the organisms being studied and the appropriate way to engage with other people in discussions of other organisms. As Chip Colwell, previous senior curator of anthropology at the Denver Museum of Nature and Science, stated during SING Aotearoa (https://www.singaotearoa.nz), Indigenous People are not anti-science [but] they demand a science that restores the dignity of Indigenous Peoples and is carried out with fundamental respect (72). This is now the responsibility of each researcher, consortium, journal, data repository, and funding body that seeks engagement with data or resources derived from Indigenous lands. Practical mechanisms like the traditional knowledge and biocultural labels and notices, and Indigenous-driven biobanks such as the Native BioData Consortium, provide proven models. The field has come a long way in working toward diversity, and the wind is at our back. Indigenous researchers have already put great effort into developing guidelines, best practices, legal and extralegal tools, and new research paradigms (SI Appendix, Table S1). Equipped with this knowledge, the community must now capitalize on the opportunity to build an inclusive, respectful, and mutually beneficial future for genomics.

There are no data underlying this work.

We thank Carla Easter (Education and Outreach Department of the National Human Genome Research Institute, NIH), Jenny Reardon (University of California, Santa Cruz), Harris Lewin (University of California, Davis), and Jacob S. Sherkow (University of Illinois) for their time in reviewing and consulting in preparation of this manuscript; and IndigiData and SING USA, Canada, and Aotearoa for their support and guidance throughout the manuscript-drafting process. This work was supported, in part, by the Intramural Research Program of the National Human Genome Research Institute, NIH (A.M.M.C. and A.M.P.). J.G. is funded by NIH Grant 5R01CA237118-02 and a Canadian Institutes of Health Research Fellowship (202012MFE-459170-174211). Development of the Biocultural Label Initiative has been supported by Catalyst Seeding funds for the project Te Tukiri o te Tonga: Recognizing Indigenous Interests in Genetic Resources provided by the New Zealand Ministry of Business, Innovation and Employment and administered by the Royal Society Te Aprangi (19UOW008CSG to M.L.H. and J.A.), leveraging the existing Local Contexts (https://localcontexts.org/) platform supported by the National Endowment for the Humanities (PR 234372-16 and PE 263553-19 to J.A.) and the Institute of Museums and Library Services in the United States (RE-246475-OLS-20 to J.A.), New York University Graduate School of Arts and Sciences, and the University of Waikato. Continuing infrastructure development is supported through the Equity for Indigenous Research and Innovation Co-ordinating Hub based at New York University and University of Waikato (https://www.enrich-hub.org/). The Biocultural Label Initiative is extended through use cases, supported and refined by the Aotearoa Biocultural Label Working Group, Federation of Mori Authorities Innovation (https://www.foma.org.nz/), Te Mana Rauranga (https://www.temanararaunga.maori.nz/), Genomics Aotearoa (https://www.genomics-aotearoa.org.nz/), Indigenous Design and Innovation Aotearoa (https://www.idia.nz/), the Genomics Observatories Metadatabase (https://geome-db.org/), the Ira Moana Genes of the Sea Project (https://sites.massey.ac.nz/iramoana/), supported by Catalyst Seeding funds provided by the New Zealand Ministry of Business, Innovation and Employment and administered by the Royal Society Te Aprangi, 17MAU309CSG to L.L.), and a Massey University Research Fund to L.L. L.L. is supported by a Rutherford Foundation Discovery Fellowship. J.G. and R.C.-D. are funded by the US National Cancer Institute through Grant R01 CA227118 (sulstonproject.org). M.Z.A. is funded by NIH Grant R01AI148788 and NSF CAREER 2046863.

Author contributions: A.M.M.C., J.A., L.L., M.L.H., M.Z.A., B.T., J.G., R.C.-D., and H.R.P. designed research; A.M.M.C. and A.M.P. wrote the paper; and J.A., L.L., M.L.H., M.Z.A., B.T., J.G., R.C.-D., and H.R.P. contributed to drafting text.

The authors declare no competing interest.

This article is a PNAS Direct Submission.

This article contains supporting information online at https://www.pnas.org/lookup/suppl/doi:10.1073/pnas.2115860119/-/DCSupplemental.

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Balancing openness with Indigenous data sovereignty: An opportunity to leave no one behind in the journey to sequence all of life - pnas.org

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Ascend in the openness to specific poison or change in climate might expand the Genomic Biomarkers Market will inspire the market development, additionally expansion in the mindfulness about treatment and mechanical progression and fast reception of fresher definitions and novel measurements structures are a portion of the significant elements among others driving the Genomic Biomarkers Market. In addition, ascend in the innovative work exercises on the lookout and ascend in the interest from arising economies will additionally set out new open doors for the Genomic Biomarkers Market in the conjecture time of2022-2029.

The market report is segmented into the application by the following categories:

Global Genomic Biomarkers Market, By Type (Oncology, Cardiovascular Diseases, Neurological Diseases, Others), End- User (Diagnostic and Research Laboratories, Hospitals Others), Country (U.S., Canada, Mexico, Germany, Italy, U.K., France, Spain, Netherlands, Belgium, Switzerland, Turkey, Russia, Rest of Europe, Japan, China, India, South Korea, Australia, Singapore, Malaysia, Thailand, Indonesia, Philippines, Rest of Asia- Pacific, Brazil, Argentina, Rest of South America, South Africa, Saudi Arabia, UAE, Egypt, Israel, Rest of Middle East & Africa) Industry Trends and Forecast to 2029.

ACCESS FULL REPORT:https://www.databridgemarketresearch.com/reports/global-genomic-biomarkers-market?utm_source=Shiv&utm_medium=Shiv&utm_id=Shiv

In any case, lacking information about Genomic Biomarkers Market in some agricultural nations and patent expiry from many organizations and presentation of nonexclusive medications of marked variant are the main considerations among others going about as restrictions, and will additionally challenge the Genomic Biomarkers Market in the conjecture time frame referenced previously.

Highlights Points of The Market:

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Genomic Biomarkers Market 2022 Industry Development and Growth Forecast to 2029 The Oxford Spokesman - The Oxford Spokesman

Scientists investigating the DNA outside our genes the dark genome have discovered recently evolved regions that code for proteins associated with schizophrenia and bipolar disorder.

They say these new proteins can be used as biological indicators to distinguish between the two conditions, and to identify patients more prone to psychosis or suicide.

Schizophrenia and bipolar disorder are debilitating mental disorders that are hard to diagnose and treat. Despite being amongst the most heritable mental health disorders, very few clues to their cause have been found in the sections of our DNA known as genes.

The scientists think that hotspots in the dark genome associated with the disorders may have evolved because they have beneficial functions in human development, but their disruption by environmental factors leads to susceptibility to, or development of, schizophrenia or bipolar disorder.

The results are published today (December 23, 2021) in the journal Molecular Psychiatry.

By scanning through the entire genome weve found regions, not classed as genes in the traditional sense, which create proteins that appear to be associated with schizophrenia and bipolar disorder, said Dr Sudhakaran Prabakaran, who was based in the University of Cambridges Department of Genetics when he conducted the research, and is senior author of the report.

He added: This opens up huge potential for new druggable targets. Its really exciting because nobody has ever looked beyond the genes for clues to understanding and treating these conditions before.

The researchers think that these genomic components of schizophrenia and bipolar disorder are specific to humans the newly discovered regions are not found in the genomes of other vertebrates. It is likely that the regions evolved quickly in humans as our cognitive abilities developed, but they are easily disrupted resulting in the two conditions.

The traditional definition of a gene is too conservative, and it has diverted scientists away from exploring the function of the rest of the genome, said Chaitanya Erady, a researcher in the University of Cambridges Department of Genetics and first author of the study.

She added: When we look outside the regions of DNA classed as genes, we see that the entire human genome has the ability to make proteins, not just the genes. Weve found new proteins that are involved in biological processes and are dysfunctional in disorders like schizophrenia and bipolar disorder.

The majority of currently available drugs are designed to target proteins coded by genes. The new finding helps to explain why schizophrenia and bipolar disorder are heritable conditions, and could provide new targets for future treatments.

Schizophrenia is a severe, long-term mental health condition that may result in hallucinations, delusions, and disordered thinking and behavior, while bipolar disorder causes extreme mood swings ranging from mania to depression. The symptoms sometimes make the two disorders difficult to tell apart.

Prabakaran left his University position earlier this year to create the company NonExomics, in order to commercialize this and other discoveries. Cambridge Enterprise, the commercialization arm of the University of Cambridge, has assisted NonExomics by licensing the intellectual property. Prabakaran has raised seed funding to develop new therapeutics that will target the proteins implicated in schizophrenia and bipolar disorder, and other diseases.

His team has now discovered 248,000 regions of DNA outside of the regions conventionally defined as genes, which code for new proteins that are disrupted in disease.

Reference: Novel open reading frames in human accelerated regions and transposable elements reveal new leads to understand schizophrenia and bipolar disorder by Chaitanya Erady, Krishna Amin, Temiloluwa O. A. E. Onilogbo, Jakub Tomasik, Rebekah Jukes-Jones, Yagnesh Umrania, Sabine Bahn and Sudhakaran Prabakaran, 23 December 2021, Molecular Psychiatry.DOI: 10.1038/s41380-021-01405-6

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Recently Evolved Region of the Dark Genome Offers Clues to Treatment of Schizophrenia and Bipolar Disorder - SciTechDaily