Category Archives: Transhuman News

With over 300 tombs, the Little River (Xiaohe) Cemetery, a Bronze Age burial located in the Tarim Basin in Xinjiang, Western China, contains the largest number of mummies found at any single site to date. Located on the Silk Road at the confluence of the Eastern and Western cultures, the naturally mummified human remains in boat coffins dating to circa 2,000 BCE to 200 CE have inspired speculations on their enigmatic origins.

Whereas some placed the origin of these mummies among the early farmers of the Iranian Plateau, many believed their origins to be Caucasoiddescendants of migrating Yamnaya herders from the steppes of the Black Sea region of southern Russiadue to their Western physical appearance, clothing, and agropastoral economy. This has led to global attention on these archeological remains.

To solve this enigma, an international team of scientists from Jilin University, the Institute of Vertebrate Paleontology and Paleoanthropology, the Max Planck Institute for Evolutionary Anthropology, Seoul National University of Korea, and Harvard University have generated and analyzed genome-wide data from thirteen of the earliest known Tarim Basin mummies, dating to circa 2,100 to 1,700 BCE, together with five individuals dating to circa 3,000 to 2,800 BCE, from the neighboring Dzungarian Basin.

This premiere genome-scale study of prehistoric populations in the Xinjiang Uyghur Autonomous Region is reported in an article in the journal Nature titled, The genomic origins of the Bronze Age Tarim Basin mummies.

A naturally mummified woman from burial M11 of the Xiaohe cemetery. [Wenying Li/Xinjiang Institute of Cultural Relics and Archaeology]Contrary to their expectations, the genomic study found that the Tarim Basin mummies were not newcomers to the area but rather appear to be direct descendants of Ancient North Eurasiansa once widespread Pleistocene population that had nearly disappeared by the end of the last Ice Age. This population survives only fractionally in the genomes of present-day populations, with Indigenous populations in Siberia and the Americas having the highest known proportions, at about 40%.

In contrast to present day populations, genomes of the Tarim Basin mummies show no admixture with other Holocene groups, demonstrating their genetic isolation.

Archaeogeneticists have long searched for Holocene Ancient North Eurasians populations to better understand the genetic history of Inner Eurasia. We have found one in the most unexpected place, says Choongwon Jeong, a senior author of the study and a professor of Biological Sciences at Seoul National University.

Genome analysis of the neighboring Dzungarian Basin mummies showed that they descended not only from local populations but also from Western steppe cattle herders with strong genetic links to the Early Bronze Age Yamanya. The genetic characterization of the Early Bronze Age Dzungarians also helped to clarify the ancestry of other cattle faming groups (Chemurchek) who later spread northward to the Altai mountains and into Mongolia.

These findings add to our understanding of the eastward dispersal of Yamnaya ancestry and the scenarios under which admixture occurred when they first met the populations of Inner Asia, says Chao Ning, co-lead author of the study and a professor at the School of Archaeology and Museology at Peking University.

The widespread genetic mixing all around the Tarim Basin throughout the Bronze Age make it even more remarkable that the Tarim Basin mummies exhibit no evidence of genetic admixture. Yet, they were not culturally isolated.

Typical Xiaohe boat coffin with oar. The coffin is covered with a cattle hide. [Wenying Li/Xinjiang Institute of Cultural Relics and Archaeology]Dietary proteins are trapped in calcifying dental plaque (dental calculus) and preserve a record of the individuals diet. Proteomic analysis of dental calculus from the Tarim mummies show cattle, sheep, and goat dairying was already practiced by the founding population, and that they were connected to neighboring cultures, cuisines, and technologies.

Despite being genetically isolated, the Bronze Age peoples of the Tarim Basin were remarkably culturally cosmopolitanthey built their cuisine around wheat and dairy from the West Asia, millet from East Asia, and medicinal plants like Ephedrafrom Central Asia, says Christina Warinner, a senior author of the study, a professor of Anthropology at Harvard University, and a research group leader at the Max Planck Institute for Evolutionary Anthropology in Leipzig, Germany.

Dietary DNA is difficult to recover from dental calculus, and DNA cannot be used to easily distinguish specific dietary sources (e.g., meat vs. milk). Proteomics is more suitable for studying ancient diets in this context, explains Warinner.

One of the technical challenges of sequencing ancient genomes is DNA damage. The length of ancient DNA is short and contains specific forms of damage (cytosine deamination). We use this expected form of damage to authenticate DNA fragments as being ancient and to ensure accurate sequence calls. To analyze the ancient DNA sequences, we used software pipelines specifically designed for analyzing ultrashort fragments of ancient DNA, explains Warinner.

The new genomic and proteomic data presented in the paper builds upon decades of painstaking archaeological work that has fostered insights on the lifestyle and culture of the early inhabitants of the Tarim Basin. Warinner clarifies, We were able to contribute new genomic and proteomic data to this rich body of knowledge, including the first whole genome sequences for the Tarim Basin mummies. Together with our archaeologist colleagues and coauthors, we have been able to reconstruct a more complete and complex picture of the populations who first colonized the Tarim Basin more than 4,000 years ago.

Reconstructing the origins of the Tarim Basin mummies has had a transformative effect on our understanding of the region, and we will continue the study of ancient human genomes in other eras to gain a deeper understanding of the human migration history in the Eurasian steppes, says Yinquiu Cui, a senior author of the study and professor in the School of Life Sciences at Jilin University.

Future palaeogenomic and archeological research on subsequent Tarim Basin populations will focus on better understanding the later history of populations in the Tarim Basin and their role in the rise of Silk Road trade networks, says Warinner.

The Tarim mummy genomes provide a critical reference point for genetically modeling Holocene-era populations and reconstructing the population history of Asia, the authors conclude.

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Ancient Genomes and Proteomes Help Uncover Unexpected Origins and Cultural Connections - Genetic Engineering & Biotechnology News

Nobody knows who she was, just that she was different: a teenage girl from over 50,000 years ago of such strange uniqueness she looked to be a 'hybrid' ancestor to modern humans that scientists had never seen before.

Only recently, researchers have uncovered evidence she wasn't alone. In a 2019 study analysing the complex mess of humanity's prehistory, scientists used artificial intelligence (AI) to identify an unknown human ancestor species that modern humans encountered and shared dalliances with on the long trek out of Africa millennia ago.

"About 80,000 years ago, the so-called Out of Africa occurred, when part of the human population, which already consisted of modern humans, abandoned the African continent and migrated to other continents, giving rise to all the current populations", explainedevolutionary biologist Jaume Bertranpetit from the Universitat Pompeu Fabra in Spain.

As modern humans forged this path into the landmass of Eurasia, they forged some other things too breeding with ancient and extinct hominids from other species.

Up until recently, these occasional sexual partners were thought to include Neanderthals and Denisovans, the latter of which were unknown until 2010.

But in this study, a third ex from long ago was isolated in Eurasian DNA, thanks to deep learning algorithms sifting through a complex mass of ancient and modern human genetic code.

Using a statistical technique called Bayesian inference, the researchers found evidence of what they call a "third introgression" a 'ghost' archaic population that modern humans interbred with during the African exodus.

"This population is either related to the Neanderthal-Denisova clade or diverged early from the Denisova lineage," the researchers wrote in their paper, meaning that it's possible this third population in humanity's sexual history was possibly a mix themselves of Neanderthals and Denisovans.

In a sense, from the vantage point of deep learning, it's a hypothetical corroboration of sorts of the teenage girl 'hybrid fossil' identified in 2018;although there's still more work to be done, and the research projects themselves aren't directly linked.

"Our theory coincides with the hybrid specimen discovered recently in Denisova, although as yet we cannot rule out other possibilities", one of the team, genomicist Mayukh Mondal from the University of Tartu in Estonia, said in a press statement at the time of discovery.

That being said, the discoveries being made in this area of science are coming thick and fast.

Also in 2018, another team of researchers identified evidence of what they called a "definite third interbreeding event" alongside Denisovans and Neanderthals, and a pair of papers published in early 2019 traced the timeline of how those extinct species intersected and interbred in clearer detail than ever before.

There's a lot more research to be done here yet. Applying this kind of AI analysis is a decidedly new technique in the field of human ancestry, and the known fossil evidence we're dealing with is amazingly scant.

But according to the research, what the team has found explains not only a long-forgotten process of introgression it's a dalliance that, in its own way, informs part of who we are today.

"We thought we'd try to find these places of high divergence in the genome, see which are Neanderthal and which are Denisovan, and then see whether these explain the whole picture," Bertranpetit told Smithsonian.

"As it happens, if you subtract the Neanderthal and Denisovan parts, there is still something in the genome that is highly divergent."

The findings were published in Nature Communications.

A version of this article was originally published in February 2019.

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Artificial Intelligence Has Found an Unknown 'Ghost' Ancestor in The Human Genome - ScienceAlert

DNA sequencing has become the foundation for biological advancementsby enabling the exploration of genetic variants and structural changes in DNA. Historically, technologies for genetic testing fall into two categories: low-throughput and costly options such as whole genome sequencing, and high-throughput but limited technologies like genotyping arrays.

Gencove solves the too much or too little quandary by combining low-pass whole genome sequencing (reading the DNA fewer times) with a proprietary software-as-a-service (SAAS) computation layer. The result is a unique high-throughput and cost-effective whole genome sequencing solution.

"We believe the next revolution in genomics will be driven by software," said Joseph Pickrell, Ph.D., co-founder, and CEO of Gencove. "It's rewarding to work with investors who recognize the value our platform provides to the agricultural, biotechnology, clinical testing, and pharmaceutical industries."

In addition to Gencove's low-pass whole genome sequencing and SAAS platform, the company has developed large cross-species genomic datasets and reference panels. For its customers, these data equate to greater accuracy, more meaning, and increased research flexibility, today and in the future.

"Gencove's platform and datasets can help unlock the genetic underpinnings of our health and wellbeing," said Larry Page, Ph.D., managing director at Lewis and Clark AgriFood. "We are thrilled to be part of a company whose technology has such broad consumer and industrial applications from agrigenomics, biotechnology, virology to medical diagnoses, disease susceptibility, and response to medical treatment."

"The new round of funding will enable us to systematically address the significant demand for industrial-scale genomics we're seeing in the market," said Tomaz Berisa, Ph.D., Gencove's co-founder, and CTO. "We look forward to bringing our novel genomics platform to more customers as quickly as possible to support their important work."

About Gencove

Gencove is democratizing genome sequencing by making genomic information more accessible and interpretable through the development of molecular and computational tools. Gencove's low-pass sequencing platform is setting a new standard for high-throughput, cost-effective genomics research across species. The company operates a laboratory in New York and offers both low-pass sequencing and analytics software as a service. Together with academic, agriculture, biotechnology, and pharmaceutical companies,Gencove is dedicated to solving the world's most pressing challenges. More information is available at http://www.gencove.com.

About Lewis & Clark AgriFood

Lewis & Clark AgriFood is a St. Louis-based group of experienced investment professionals who are passionate about investing in growth-stage companies that are at the forefront of food and agriculture innovation. We look for companies that deliver benefits to the stakeholders in the food and agriculture sector, from the producer, through the supply chain, all the way to the consumer. As founders, operators, investors, and scientists, our seasoned investment team brings a breadth of quality sector experience to every investment. For more information, visitwww.lewisandclarkagrifood.com or connect with us onLinkedIn orTwitter.

Contacts

For Gencove:Kristi Ashton, 650.224.8231[emailprotected]

For Lewis & Clark AgriFood:Jessie Chapel, 314-651-4915[emailprotected]

SOURCE Gencove

https://www.gencove.com

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Gencove Raises $10 Million to Meet the Global Demand for Accessible and Interpretable Whole Genome Sequencing at Scale - PRNewswire

Vampire bats have an unusual, blood-only diet that's high in protein but lacking in other nutrients. Now, a new study hints that "missing" genes may explain how the flying mammals survive on nothing but blood meals, lapped from their victims' open wounds in the dead of night, The Scientist Magazine reported.

In the new study, posted Oct. 19 to the preprint database bioRxiv, researchers compared the genome of the common vampire bat (Desmodus rotundus) with those of 25 other bat species. The analysis revealed that D. rotundus lacks functional copies of 13 genes that appear in the other bats; these missing genes are either completely absent from the vampires' genome, or they contain so many mutations that they likely can't produce functional proteins, study co-author Michael Hiller, a genomicist at the LOEWE Centre for Translational Biodiversity Genomics in Germany, told The Scientist.

And it turns out, vampire bats might benefit from having ditched these 13 genes. Losing the genes may help them extract nutrients from blood in ways other bats can't, according to the study, which has not been peer-reviewed.

Related: Famous fangs: Tales of our favorite vampires

For example, two of the missing genes drive the secretion of insulin from the pancreas, with insulin being a hormone that regulates the amount of sugar in the blood by moving glucose into cells. Past studies have shown that vampire bats secrete little insulin, which makes sense given that the blood they drink contains few carbohydrates, Hiller told The Scientist. This lack of insulin secretion may help the bats conserve what little sugar they consume, by keeping that sugar available in the bloodstream, he said.

The vampire bat genome also lacked a gene called REP15, which is usually activated in the cells of the gastrointestinal tract, the authors noted in their study. Losing this gene would likely increase the amount of iron that can slip into the bats' gastrointestinal cells, by boosting the number of "doors" that iron can pass through on the cell surface. These iron-laden cells would therefore turn over more quickly than in other bats, helping the vampires efficiently rid themselves of all the iron acquired through their diets, and thus avoid metal poisoning, the study authors wrote.

Another missing gene, CTRL, would usually turn down the activity of trypsin, an enzyme involved in protein digestion and absorption, The Scientist reported. Without CTRL, trypsin activity is likely increased in vampire bats, helping them to break down their protein-heavy blood meals.

Several of the other missing genes appear to be involved in the bats' digestion and metabolism, whereas others are related to the bats' cognitive abilities and vision, the authors noted. And some of the missing genes have unknown effects on the bats' physiology and warrant further study.

Three of the 13 missing genes had actually been uncovered through previous research, published in the journals Molecular Biology and Evolution and Proceedings of the Royal Society B; these genes would usually code for taste receptors that detect sweet and bitter flavors, which are largely absent from vampire bats' diets.

Read more about the missing vampire bat genes in The Scientist Magazine.

Originally published on Live Science.

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Vampire bats' 'missing' genes may help them survive on all-blood diet - Livescience.com

The AVENIO Tumor Tissue Comprehensive Genomic Profiling Kit could allow for more accessible genetic testing and result in more personalized treatments.

The launch of the AVENIO Tumor Tissue Comprehensive Genomic Profiling (CGP) Kit could bring a more personalized medicine approach to patients with cancer by making genetic testing more readily accessible, according to a press release from the developer, Roche.

A future iteration of the kit, which complements currently the CGP portfolio at Roche, may bring additional resources to clinicians to help them diagnose and treat cancer, as well as presently enabling laboratories to further expand their oncology research efforts in house. Deviating from the results garnered from smaller panels including hotspot and single gene tests, CGP testing offers comprehensive information in a single test on complex genomic information on tumor mutational burden, microsatellite instability, and loss of heterozygosity.

To treat cancer effectively, we must understand what drives it at a molecular level. CGP helps inform decisions about available treatment options, including targeted therapies, immunotherapies, tumor-agnostic treatments and clinical trial participation, based on the unique genomic profile of a patients tumor, Thomas Schinecker, chief executive officer at Roche Diagnostics, said in a press release.

The kit is a research use only, next generation sequencing test can offer an end-to-end workflow from DNA extraction and library preparation to a generation of variant results obtained via the FoundationOne Analysis platform. The gene panel was based on the FoundationOne platform, which was designed to match the FoundationOne CDx panel in order to assess 324 cancer related genes in 4 main classes of genomic alterations and genomic signatures that have been known to result in cancer.

Every kit can run 24 samples and can be completed within 5 days from DNA isolation to variant results. The AVENIO CPG kit runs on Illumina IVD systems NextSeq 500/550 RUO, as well as NextSeq 550 Dx System in research mode. The 2 companies entered into an agreement in January 2020 to develop, produce, and commercialize AVENIO tests for both tissue and blood utilizing Illuminas IVD systems.

The kit will launch in multiple regions across the world, and Roche is planning to add additional solutions to the portfolio.

The launch of this kit will significantly expand access to genomic profiling globally by providing an in-house solution for those who cannot otherwise access our portfolio of tests through our centralised laboratories, Brian Alexander, chief executive officer at Foundation Medicine, said in a press release.

Roche launches comprehensive genomic profiling kit to expand access to personalised cancer research. News Release. Roche. October 25, 2021. Accessed October 28, 2021. https://bit.ly/3CseK1Q

Originally posted here:
New Genomic Profiling Kit May Provide More Accessible Testing and Personalized Care to Patients with Cancer - Cancer Network

Use of comprehensive genomic profiling in patients with advanced nonsmall cell lung cancer (NSCLC) was linked with significant improvements in progression-free survival and overall survival.

Comprehensive genomic profiling (CGP) in the management of advanced nonsmall cell lung cancer (NSCLC) was shown to assist in matching patients with targeted therapies and clinical trials with those matched to these therapies associated with improved survival outcomes. Findings were published in BMC Medicine.

Despite the identification of several new targetable drivers in advanced NSCLC, the standard of care for these populations only includes genetic testing for EGFR, ALK, and ROS1 mutations. Notably, previous research shows use of the broader CGP profiling can better assess for emerging mutations, but research regarding its efficacy has not yet been determined.

Patients carrying alterations other than EGFR, ALK, and ROS1 now have increased access to targeted drugs off label or through a clinical protocol, said the study authors. Therefore, a re-evaluation on the clinical implications of CGP in the current treatment landscape of advanced NSCLC is warranted.

Seeking to further examine the clinical utility of CGP, they prospectively applied the approach to Chinese patients with advanced NSCLC registered in the Precision Medicine Project from October 2016 to October 2019 (N = 1564).

Efficacy of CGP in treatment selection was measured by the proportion of patients receiving a genomic profilingdirected, matched targeted therapy and the proportion of patients being enrolled into a biomarker-selected clinical trial directed by their profiling results.

Those provided with genotype-matched therapy were compared with those who were not matched for progression-free survival (PFS) and overall survival (OS).

In their findings, tumor genomic profiles were established in 1166 participants who underwent CGP:

Compared with patients with a nonmatched therapy, those who were given genotype-matched therapies showed significant improvements in PFS (9.0 vs 4.9 months; P < .001) and OS (3.9 vs 2.5 years; P < .001).

After excluding patients with standard targeted therapies, genomic profiling led to a matched targeted therapy in 16.7% (n = 24) and a matched trial enrollment in 11.2% (n = 16) of patients. Contrary to that found in the overall cohort, no PFS (4.7 vs 4.6 months; P = .530) or OS (1.9 vs 2.4 years; P = .238) benefit was observed with the use of genotype-matched targeted therapies in these populations.

In concluding, researchers said that given the low likelihood of benefit from the investigational or off-label use of targeted therapies, applicability of genomic profiling results should be taken with caution in patients without standard-of-care drugs.

Reference

Zhao S, Zhang Z, Zhan J, et al. Utility of comprehensive genomic profiling in directing treatment and improving patient outcomes in advanced non-small cell lung cancer. BMC Med. Published online October 1, 2021. doi:10.1186/s12916-021-02089-z

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Genomic Profiling Linked With Improved Patient Outcomes in Advanced NSCLC - AJMC.com Managed Markets Network

Ziad Bakouny, MD, MSc, discusses recent ongoing research into the genomic drivers and biology of tRCC that could lead to improved outcomes for patients.

Due to the rareness of the disease, investigators have made few developments in the treatment of patients with translocation renal cell carcinoma (tRCC). Current therapeutic options often involve therapies that have shown efficacy in other forms of kidney cancer, but often do not yield positive outcomes in this patient population, said Ziad Bakouny, MD, MSc.

If we do not understand the biology [of the disease], we are not going to be able to target it correctly, Bakouny said. Currently, extrapolating treatments from clear cell RCC has not yielded optimal outcomes. Because of this, we want to understand the biology more to be able to target the disease better, treat patients better, and ultimately get them better clinical outcomes.

In an interview withOncLive during the 2021 Kidney Cancer Research Summit, Bakouny, a research associate at Dana-Farber Cancer Institute and resident in internal medicine at Brigham and Womens Hospital, discussed recent ongoing research into the genomic drivers and biology of tRCC that could lead to improved outcomes for patients.

Bakouny: tRCC is a very rare disease that affects primarily young patients, and interestingly, females more than males. It is thought to account for 1% to 5% of all RCCs in adults, and in children, it accounts for 20% to 50% of kidney cancers. The disease is aggressive, and what we know about is actually that we do not know that much. There have been large studies on more frequent forms of kidney cancer, including clear cell RCC and papillary RCC, and because of these efforts, there is quite a bit understood about the genomic drivers of this disease.

However, rarer forms, like tRCC, have not been studied as extensively, and we do not know much about them. This contributes to the fact that we do not have many therapies that work for them. All the therapies currently used for tRCC are extrapolated from clear cell RCC, as well as from other forms of kidney cancer.

The reason it is important to understand the biology of tRCC is because it is aggressive, and patients, unfortunately, often have poor outcomes, Additionally, it disproportionately affects young patients, and there is a significant burden of disease for these young patients, particularly young women.

Because of how rare this disease is, we realized that we could not do this on our own, in the sense that no one center anywhere across the world would have been able to get enough samples to study the molecular characteristics of the disease, in addition to the clinical characteristics. What we did was pull data from approximately 10 different data sets that were publicly available, including some of our own. We put it all together and we analyzed it, using some unorthodox methods, to be able to ask the questions about what the molecular characteristics of these tumors are, what is driving these tumors, and what therapies might work for them.

To do this, we pulled the data together and included genomic data such as DNA level analyses and mutations. We also looked at fusions because these tumors are known to be driven by a characteristic fusion involving the TFE family of genes. Then we looked at was transcriptomic data, as well, and wanted to know what the transcriptomic characteristics of these tumors are. Finally, we looked at clinical responses to therapies.

In the DNA-level analyses of data, we found that these tumors have a silent genomethey do not have a lot of mutations, they do not have a lot of copy number alterations. Despite that, they do seem to have some recurrent alterations that we have identified, primarily 9p21.3 deletion, which is the CDK2NA locus that seems to be deleted in up to 20% of these tumors, as well as a few mutations that we detected in DNA damage response genes and SWI/SNF genes. That was the mutational bucket, in fusion bucket, it is known that these tumors evolve TFE3, TFEB, and MITF genes. What we noticed is that the pattern of how these fusions form, what they conserve as part of these genes, differs between fusions. These genes seem to conserve the C-terminal domain, the DNA binding domain, of these proteins well, but depending on the actual gene itself, there are different parts of the protein domains that are conserved in the fusion product between them, so we that was characterized.

On the transcriptomic side of things, what we found is that these tumors seem to have a distinct transcriptional signature that is different from all other forms of RCC. This is characterized by genes that are known to be targets of TFE3. We then used cell lines to transfect the fusion into this alliance [and were then able to] deduct that the transcriptional program of these tumors appears to be induced by the fusion itself. We then asked, what is this transcriptional program and what is it characterized by? What we found is that it is characterized by activation of the NRF2 transcriptional program, and that is a program that has been known to be activated across several malignancies.

Now that we know what the genomic characteristics are, we know what the fusion looks like, and we know what the transcriptomics look like for these tumors, we are left with the clinical response. What we found is that, as expected, these NRF2-expressing tumors do not seem to respond well to targeted therapies, which explains the usually poor outcomes seen in this patient population. We used to treat clear cell RCC with targeted therapies like mTOR inhibitors and VEGF inhibitors, and because of the NRF2 activation, we see poor responses to those with tRCC. However, they [do seem to] respond well to immune checkpoint inhibitors. We used our own data, as well as data from tRCCs that were identified post hoc in the phase 3 IMmotion151 trial (NCT02420821) to show that these tumors respond well to immune checkpoint inhibitors. This is still preliminary data, but given how rare this disease is, we believe they are convincing data that patients with these tumors may do well on immune checkpoint inhibitors or immune checkpoint inhibitor-based combinations.

I am excited that through our study, and from multiple other studies that have been done in this space, we now have a firmer grasp on what the genomics of these tumors are and what the drivers are. What remains to be understood is how these interplay with each other. For instance, what is the fusion doing with the CDKN2A loss? How are they cooperating to drive the pathogenesis of these tumors?

The next step that I am excited about is figuring out the underlying biology and following up on some of the signals that we have seen on how [these factors] interact with each other to drive tumor pathogenesis. The hope is that with a more granular understanding of these tumors, we will be able to develop specific therapies that target the pathogenic processes and be able to improve the outcomes of these patients, which is still a huge unmet clinical need.

Unfortunately, the main therapeutic developments are the ones I previously mentioned as part of our study and others. These therapeutic developments are using the treatments we already have for RCC and seeing how they do in tRCC. This alludes to some of our own work that was just mentioned about how immune checkpoint inhibitors might do well in these tumors. There is corroborating data from other studies that have shown similar things, and right now, that is the most exciting space, in terms something that is clinically actionable. That said, the next steps are targeting the underlying biology of disease. That is what may drive improvement in the outcomes of patients with these tumors.

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Research Efforts Seek to Understand Biology, Genomic Driver of Translocation RCC - OncLive

Study of RUNX2 locus in modern and ancient humans

The sequences of the RUNX2 locus (Chr6:45,318,00045,670,000 hg38, for a total of 352.000 bases) have been aligned in AMH and ancient species (Neandertal and Denisovan) genomes to map the changes occurred during recent evolution. We have identified 459 and 470 changes (including nucleotide substitutions, indels, and annotated human SNPs) acquired in AMH compared with Neandertal and Denisovan, respectively (Supplementary File 1 and Fig.2). Our analysis confirmed that no change occurred within RUNX2 exons. Selected changes map within the P1 and P2 promoter sequences, and in both proximal and distal 3UTRs (Fig.2). In addition, to confirm which of these nucleotide changes have occurred during the recent human evolution, we also analysed the RUNX2 sequences of non-human Primates [chimpanzee (Pan troglodytes), gorilla (Gorilla gorilla), Sumatran orangutan (Pongo abelii), gibbon (Nomascus leucogenys) and rhesus macaque (Macaca mulatta)] focusing our attention on changes mapping in promoters and 3UTRs (Supplementary File 1).

Divergence of RUNX2 locus in AHM compared with ancient hominins. The pie charts display the extent of genomic divergence in terms of number of sequence changes and corresponding locations found in AMH compared with the Neandertal (a) and the Denisovan (b) species identified using the Integrative Genomics Viewer (IGV) tool. Most of the sequence changes are found in intronic regions, whereas few substitutions occur in the regulatory regions outside the open reading frame: Promoter 1, Promoter 2, proximal 3UTR and distal 3UTR. The Neandertal skull in the upper left panel of this figure is exhibited at the Natural History Museum of London (personal picture, credits to W. Lattanzi); the AMHs and Denisovans skulls were created with BioRender.com (note that a reliable reconstruction of the Denisovan skull is not available).

The P1 sequence in AMH differs for as little as one nucleotide from Neandertal and Denisovan genes (Supplementary File 1 and Fig.2). In the P2 sequence, we found three changes in AMH compared with both ancient hominins, plus an additional change differing exclusively between AMH and Neandertal (Supplementary File 1 and Fig.2). Interestingly, three substitutions mapping in the P2 promoter were not present in any of the tested Primates species, which retained the same nucleotides observed in the ancient hominins species. These changes seem indeed to be specific to AMH (Supplementary File 1).

The proximal 3UTR sequence of AMH differs in 4 and 2 nucleotides, compared to Neandertal and Denisovan species, respectively (Supplementary File 1 and Fig.2). Our analysis revealed that one change in the proximal 3UTR identified in Denisovan RUNX2 sequence is also conserved in all non-human Primates analysed (Supplementary File 1). The sequence of the distal 3UTR region of AMH, instead, differs from both Neandertal and Denisovan due to two nucleotide substitutions (Supplementary File 1 and Fig.2). All the tested Primates genome sequences differ from both modern and ancient humans in one of these changes (Supplementary File 1).

RUNX2 locus also includes two additional genes, recently classified as lncRNAs antisense to RUNX2, namely, AL096865.1 and RUNX2 antisense RNA 1 (RUNX2-AS1) (Fig.1). AL096865.1 partially overlaps with the RUNX2 P2 region and contains 3 sequence changes that occurred in the AMH genome compared with both Neandertal and Denisovan (i.e. the same changes already described for P2 sequence; Supplementary File 1). RUNX2-AS1 encodes a transcript (ENST00000563807.1) with two exons, and maps on the reverse strand of the last intron of the RUNX2 ENST00000576263.5 coding isoform (see Fig.1). Our results showed that 6 changes map within the RUNX2-AS1 gene, 2 of which fall in the first exon (Supplementary File 1). Three of the substitutions mapping in the RUNX2-AS1 locus were not found in the tested Primates genomes, which shared the same nucleotides observed in the ancient hominins (Supplementary File 1).

To assess the putative functional consequence of the sequence changes observed in the RUNX2 gene regulatory regions, we have performed in silico predictive analysis.

We first focused on the analysis of nucleotide substitutions within the two promoter regions, P1 and P2. As discussed above, P1 sequence in AMH differs from that of Neandertal and Denisovan for just 1 nucleotide. Downstream analysis using different bioinformatic tools (Meme suite https://meme-suite.org/meme/, Consite http://consite.genereg.net/ and rVista 2.0 https://rvista.dcode.org/)27,28,29 did not reveal any association of this genomic substitution with putative regulatory regions.

For P2, we found four nucleotide changes, three differing in AMH compared with both ancient hominins, and 1 differing exclusively between AMH and Neandertal. Three of these substitutions also overlap with the antisense lncRNA AL096865.1 (Supplementary File 1). Motif analysis using MEME suite27 indicated that 3 substitutions map within 3 conserved CCYCCCWCCTC sequence motifs (Fig.3a, red boxes). Interestingly, analysis of transcription factor binding using Tomtom30 identified this motif as a putative binding site for the C2H2-type zinc finger protein ZNF263 (Fig.3b). We therefore applied position weigh matrix (PWM) analysis to investigate if the identified substitutions could affect binding of this transcription factor to RUNX2 P2 promoter. Analysis of position-specific scoring matrices using available software (FIMO, Find Individual Motif Occurrences, https://meme-suite.org)31 indicated that: (i) two of these substitutions (A/G in position 45421497 and T/C in position 45421552) decreased ZNF263 matrix score in AMHs from 17.102 to 15.734, and from to 6.637 to 4.959, respectively, while (ii) the inclusion of a T in Denisovan and AMHs (position 45421406) increases the matrix score from 4.204 to 4.653 (Supplementary File 2). ZNF263 was recently shown to participate in the CCCTC binding factor (CTCF)-mediated chromatin looping32 and its motif is also enriched in lncRNAs located at chromatin boundaries33. As chromatin looping was previously associated with the regulation of RUNX234, we hypothesize that the tested nucleotide changes could alter chromatin looping and therefore influence the levels of gene expression. To support this hypothesis, we first investigated if P2 promoter was indeed bound by CTCF and ZNF263. To this end, we explored available ENCODE (https://www.encodeproject.org/) genome-wide datasets from different human cell lines (osteoblasts, HEK293 and K562 cells), using the UCSC Genome browser resources (https://genome.ucsc.edu). Data shown in Fig.3c show that CTCF binding is enriched at the P2 promoter in all cell lines analysed, whereas ZNF263 binding was found in the two cell lines for which there were ENCODE data available (HEK293 and K562). Finally, analysis of the GeneHancer database revealed different loop interactions involving the RUNX2 P2 promoter and other regulatory elements in the region, such as SUPT3H (SPT3 homolog, SAGA and STAGA complex component) promoter (Fig.3c). Altogether, these analyses suggested that the genomic changes at the ZNF263 binding sites comprised within the RUNX2 P2 promoter/AL096865.1 lncRNA sequence could influence DNA looping and therefore differentially regulate RUNX2 expression in AMH as compared with ancient hominins.

Genomic variants in RUNX2 P2 promoter overlap with ZNF263 binding sites at CTCF-mediated loop anchor regions. (a) Motif analysis using MEME suite of the P2 proximal promoter region, containing a cluster of three nucleotide variants in AMHs compared with Denisovan/Neandertal species (chr6:45,421,39845,421,567), identified three CCYCCCWCCTC motifs overlapping with the three genomic variants. (b) In silico analysis using Tomtom identified ZNF263 as a transcription factor binding the CCYCCCWCCTC motif. (c) Scheme of the RUNX2 locus (Chr6:45,318,00045,670,000 GRCh38/hg38) showing the different RUNX2 isoforms and regulatory regions and available Encode data. These include: ChIP-seq tracks (fold change over control) for CTCF binding (light blue) in osteoblasts, HEK293 and K562 cell lines, ChIP-seq tracks (fold change over control) for Znf263 binding (dark blue) in HEK293 and K562, short nucleotide clinical variants ClinVar SNVs and GeneHancer regulatory elements (GH Reg Elem (DE)), including 3D chromatin loop formation.

We then focused further analyses on the study of the nucleotide substitutions within the regulatory elements at the 3 ends of RUNX2, to evaluate possible implications in post-transcriptional regulation.

Using the UCSC Genome browser resources, we observed that the proximal 3UTR belongs to a hotspot region of variants annotated in the ClinVar database (https://www.ncbi.nlm.nih.gov/clinvar/; see Fig.3c). As mentioned above, the proximal 3UTR sequence of AMH differs in six nucleotides respect to ancient hominis (in particular, four respect to Neanderthal and two nucleotides compared to Denisovan). Of these, four nucleotides specific for ancient hominis represent common variants annotated in the Homo sapiens genome (rs144321470, rs188598788, rs537488922, rs182124295), as benign mutations in CCD cohorts. Also, the variants in the distal 3UTR of Neandertal and Denisovan correspond to common variants observed in Homo sapiens (rs74697776, rs6458457) that are not annotated in ClinVar.

The 3'UTR of a mRNA can be bound by miRNAs that modify the stability and half-life of the target transcripts and/or protein translation. We thus tested the hypothesis that the nucleotide changes found in the 3UTRs of RUNX2 could influence miRNA binding. We first used different online databases and tools (miRDB http://mirdb.org/, TargetScanHuman http://www.targetscan.org/vert_72/, miRbase http://www.mirbase.org/ and PolymiRTS Database 3.0 http://compbio.uthsc.edu/miRSNP/), to select the list of miRNAs that, based on sequence complementarity, most likely bind the RUNX2 3UTRs. Then, we annotated all the miRNAs whose seed sequence fall into one of the sequence regions that diverge between AMH and ancient hominins.

Our results showed that the substitutions fixed in the proximal 3UTR of RUNX2 affected the binding of different miRNAs, indicating that during recent human evolution, the AMH RUNX2 genomic region acquired or lost miRNA binding sites, potentially involved in post-transcriptional regulation (Supplementary File 3 and Fig.4a).

In silico prediction of miRNA binding sites within RUNX2 3UTRs in AMH, Neandertal and Denisovan. The picture shows the nucleotide changes (highlighted in red) identified in the untranslated regions (UTRs) at the 3 ends of RUNX2 transcripts in Neandertal and Denisovan hominins compared with that of anatomically modern humans (AMH). The substitutions are apparently able to modify the pattern of miRNA binding both in the proximal 3UTR (a) and in the distal 3UTR (b).

Our data showed also that the distal 3UTR does not differ between Neandertal and Denisovan species, suggesting a similar miRNA-dependent post-transcriptional regulation pattern. We predicted that the sequence divergence between AMH and ancient hominins observed in this 3UTR fall within the binding sites of 16 different miRNAs in AMH (Supplementary File 3 and Fig.4b). In particular, the in silico analysis suggested that the 2 nucleotide changes that were fixed in AMH generate new binding sites for several miRNAs (Fig.4b). The first substitution in the distal 3UTR found in the ancient hominins instead should allow the binding of an additional miRNA, namely miR-5589-5p (Fig.4b).

All the genomic loci of the selected miRNAs were comparatively analysed in the aligned sequences of AMH and ancient hominins, using the IGV tool, to evaluate the evolutionary conservation of their DNA sequences across human species. Our analysis showed that nucleotide changes occurred in the AMH miR-3143, compared with the Denisovan sequence, and in the AMH miR-149-3p, compared both with Neandertal and Denisovan species (Supplementary File 4). Nonetheless, both these fixed changes fall outside the seed sequences of these two miRNAs. All the other miRNAs did not present any nucleotide change.

To delve into functional aspects, we have assessed the differential contribution of the alternative transcript isoforms of the RUNX2 gene to the osteogenic cascade activation. To this end, we have analysed the expression of the different RUNX2 transcript variants in mesenchymal stromal cells isolated from calvarial sutures (CMSC) isolated from unfused suture tissues obtained as surgical waste from surgery of nonsyndromic craniosynostosis (NCS) patients. We relied on this cellular model as a benchmark for the study of membranous ossification, previously optimized and standardized in our lab35. P1-derived transcripts, P2-derived transcripts, splice variants containing the proximal 3UTR and the distal 3UTR, were independently amplified by Real-Time PCR using isoform-specific oligonucleotide primer pairs.

CMSC were induced toward the osteogenic lineage up to 21days in order to assess the regulation of each transcript group during the in vitro differentiation process at different timepoints (i.e. 3, 6, 10, 14 and 21days). Our results showed that total RUNX2 levels undergo an initial down-regulation during the first days of commitment, followed by an increase thereafter (Fig.5a). The upregulation of the RUNX2 P1-derived isoforms and of the RUNX2 isoforms containing the proximal 3UTR was significant until 21days of osteogenic induction (Fig.5b,c). Instead, the expression of RUNX2 P2-derived isoforms and of the RUNX2 isoforms with the distal 3UTR appeared to reach a peak at 10days of in vitro differentiation and thereafter decrease or lose statistical significance (Fig.5d,e). The expression of the Sp7 transcription factor gene (osterix, OSX) and of the alkaline phosphatase (ALP) gene were evaluated to confirm that the cells were differentiating along the osteogenic lineage (Fig.5f,g).

Relative expression of RUNX2 isoforms during osteogenic induction in vitro. The graphs show the expression of total RUNX2 levels (a), RUNX2 P1-derived transcripts (b), RUNX2 splice variants containing the proximal 3UTR (c), P2-derived transcripts (d), isoforms with the distal 3UTR (e), OSX (f) and ALP (g) transcripts measured by Real Time PCR, in cells undergoing osteogenic induction up to 21days. The fold change of expression levels is expressed as relative quantity (RQ), calculated according to the Ct method, setting the day 0 (when the standard growth medium has been replaced with the osteogenic medium) value as reference. All data are expressed as mean fold changestandard deviation across replicates. *p0.05; **p0.01; ***p0.001; ****p0.0001.

The expression of the two long noncoding transcripts AL096865.1 and RUNX2-AS1 was also assessed in CMSC and correlated to the levels of RUNX2, to evaluate the possible involvement of these two lncRNAs in regulating RUNX2 expression. We focused our analysis during the early stages of the osteogenic commitment (0-to-10days of osteogenic induction), as a functionally relevant timeframe for gene expression regulation. AL096865.1 levels were significantly upregulated after 6 and 10days of differentiation (Fig.6a); also RUNX2-AS1 levels showed an increasing trend during osteogenic differentiation (Fig.6b). Furthermore, our analysis showed a significant positive correlation between the expression of AL096865.1 and that of RUNX2 total isoforms (Fig.6c), of RUNX2 P2-derived isoforms (Fig.6d) and of RUNX2 isoforms containing the proximal 3UTR (Fig.6e). A significant positive correlation could be also outlined for RUNX2-AS1 and the RUNX2 isoforms containing the proximal 3UTR (Fig.6f). These data might suggest a feasible involvement of AL096865.1 and RUNX2-AS1 in modulating RUNX2 expression.

lncRNAs expression during osteogenic induction in vitro. (a,b) The bar graphs show the expression of AL096865.1 (a) and RUNX2-AS1 (b) measured by real time PCR, in cells undergoing osteogenic induction up to 10days. The fold change of expression levels is expressed as relative quantity (RQ), calculated according to the Ct method, setting the day 0 (when the standard growth medium has been replaced with the osteogenic medium) value as reference. All data are expressed as mean fold changestandard deviation across replicates. *p0.05; **p0.01. (cf) The line graphs draw the linear regressions during the first phases of osteogenic induction (up to 10days) of the relative expression levels of AL096865.1 with total RUNX2 levels (c), RUNX2 P2-derived transcripts (d) and RUNX2 splice variants containing the proximal 3UTR (e), and of RUNX2-AS1 with the group of RUNX2 isoforms containing the proximal 3UTR (f). Pearson correlation was evaluated and the Pearson correlation coefficient (r value) and p-value (p) were reported.

We further focused our analysis on the distal 3UTR of RUNX2 (ENST00000576263.5), given the structural peculiarity of this gene, which includes an additional coding exon (see Fig.1), and taking into consideration that the nucleotide substitutions identified in the proximal 3UTR were annotated as clinical variants (though benign, to date).

In silico protein modelling, based on the I-TASSER tool, revealed that the presence of this terminal exon introduces a leucine-zipper DNA binding motif in the protein (Fig.7a), likely affecting RUNX2 function as a transcriptional regulator.

In silico modelling and miRNA profiling. (a) The images show the three-dimensional computational modelling of the last coding exon of the RUNX2 isoform containing the distal 3UTR and its predicted interaction with DNA, by I-TASSER tool (https://zhanglab.ccmb.med.umich.edu/I-TASSER/). (b) Surface plasmon resonance data showed the changes in miRNA-target binding affinities. Representative graph showing the interaction of the synthetic sequence that mimics the miR-3150a-3p with the 3UTR of anatomically modern human (AMH) at different concentration (RU: response unit). Empty circles represent the experimental traces at different analytes concentration, while the black lines are the global fit using a 1:1 kinetic model. (ch) The bar graphs show the changes in relative expression of miR-3150a-3p, miR-6825-5p, miR-4700-5p, miR-149-3p, miR-4486 and miR-6785-5p measured by Real Time PCR, in cells undergoing osteogenic induction up to 21days. The fold change of expression levels is expressed as relative quantity (RQ), calculated according to the Ct method, setting the day 0 (when the standard growth medium has been replaced with the osteogenic medium) value as reference. All data are expressed as mean fold changestandard deviation across replicates. *p0.05; **p0.01; ****p0.0001. (i,j) The line graphs show the linear regressions during the osteogenic induction (up to 21days) between the relative expression levels of miR-3150a-3p and miR-6785-5p and RUNX2 total isoforms. Pearson correlation was analysed and the relative Pearson correlation coefficient (r value) and p-value (p) were reported.

We thereafter investigated in vitro if the nucleotide changes in this 3UTR actually affect miRNA binding. To this end, we used Surface Plasmon Resonance (SPR) to determine the affinity of the molecular interactions between the 15 selected miRNAs and the target sequences on the distal 3UTR of AMH and Neandertal/Denisovan RUNX2 genes. The resulting dissociation constant values obtained for each tested miRNA are reported in Table 1. Of the 15 miRNAs tested, eight failed to show any interaction. The remaining seven miRNAs showed differential binding affinities to the species-specific RUNX2 transcripts: (i) namely, miR-4700-5p, miR-6825-5p, miR-3150a-3p, miR-6763-5p showed interaction exclusively with the AMH RUNX2 gene; (ii) miR-149-3p showed a higher affinity for the AMH RUNX2 mRNA; and (iii) miR-6785-5p and miR-4486 showed higher affinity in the interaction with the ancient species target sequence (see Table 1). A representative figure corresponding to the interaction of the RUNX2 3UTR of AMH with the synthetic sequence that mimics the miR-3150a-3p is reported in Fig.7b.

To validate these data at the functional level in the biological context, we have analysed in CMSC the levels of the miRNAs previously selected through SPR (miR-3150a-3p, miR-6825-5p, miR-4700-5p, miR-149-3p, miR-4486 and miR-6785-5p). Our results showed that all the miRNAs are expressed in CMSC and that their expression vary during osteogenic differentiation. The expression levels measured during the osteogenic induction were variable across the replicates and it was not always possible to identify a clear trend of activation/silencing during the osteogenesis process (Fig.7ch). Due to this technical limitation, we could not detect any significant correlation between the trend of expression of the selected miRNAs and that of the RUNX2 isoform with the distal 3UTR during the osteogenic induction (data not shown). However, the expression levels of miR-3150a-3p and of miR-6785-5p inversely correlated with those of RUNX2 total isoforms: while the expression of RUNX2 increased during the osteogenesis in vitro, the levels of miR-3150a-3p and miR-6785-5p decreased (Fig.7i,j). This may suggest that these two miRNAs could have gained a function as post-transcriptional regulators of RUNX2 in AMHs, tampering excessive production of this transcription factor and delaying ossification.

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Shaping modern human skull through epigenetic, transcriptional and post-transcriptional regulation of the RUNX2 master bone gene | Scientific Reports...

This article was originally published here

Euro Surveill. 2021 Oct;26(43). doi: 10.2807/1560-7917.ES.2021.26.43.2002066.

ABSTRACT

BackgroundIn the SARS-CoV-2 pandemic, viral genomes are available at unprecedented speed, but spatio-temporal bias in genome sequence sampling precludes phylogeographical inference without additional contextual data.AimWe applied genomic epidemiology to trace SARS-CoV-2 spread on an international, national and local level, to illustrate how transmission chains can be resolved to the level of a single event and single person using integrated sequence data and spatio-temporal metadata.MethodsWe investigated 289 COVID-19 cases at a university hospital in Munich, Germany, between 29 February and 27 May 2020. Using the ARTIC protocol, we obtained near full-length viral genomes from 174 SARS-CoV-2-positive respiratory samples. Phylogenetic analyses using the Auspice software were employed in combination with anamnestic reporting of travel history, interpersonal interactions and perceived high-risk exposures among patients and healthcare workers to characterise cluster outbreaks and establish likely scenarios and timelines of transmission.ResultsWe identified multiple independent introductions in the Munich Metropolitan Region during the first weeks of the first pandemic wave, mainly by travellers returning from popular skiing areas in the Alps. In these early weeks, the rate of presumable hospital-acquired infections among patients and in particular healthcare workers was high (9.6% and 54%, respectively) and we illustrated how transmission chains can be dissected at high resolution combining virus sequences and spatio-temporal networks of human interactions.ConclusionsEarly spread of SARS-CoV-2 in Europe was catalysed by superspreading events and regional hotspots during the winter holiday season. Genomic epidemiology can be employed to trace viral spread and inform effective containment strategies.

PMID:34713795 | DOI:10.2807/1560-7917.ES.2021.26.43.2002066

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Genomic epidemiology reveals multiple introductions of SARS-CoV-2 followed by community and nosocomial spread, Germany, February to May 2020 - DocWire...

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GenscriptHorizon Discovery GroupLonzaMerck KGaASangamo TherapeuticsThermo Fisher Scientific

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CRISPRTALENZFNS

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Cell Line EngineeringAnimal Genetic EngineeringPlant Genetic Engineering

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Global Genome Editing Market 2021 Overview, Opportunities, In-Depth Analysis by 2027 : Genscript, Horizon Discovery Group, Lonza, Merck KGaA, Sangamo...