Category Archives: Genome

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

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...

Researchers have developed a new method that uses artificial intelligence to foresee the most likely mutations of pathogens like SARS-COV-2, the virus that causes COVID-19.

The new research has implications for the rapid development of vaccines, treatments and diagnostic tests that would be much less likely to be impacted by new or emerging variants of concern.

Mohammad Kohandel, a professor and head of the Mathematical Medicine Laboratory in the Department of Applied Mathematics at the University of Waterloo, helped pioneer the research in the context of the ongoing pandemic.

With a highly infectious pathogen like SARS-COV-2, we want to have a method for extracting the mutational information as quickly as possible, Kohandel said. Variants are a huge problem because we dont know whether the diagnostic tests that are available are going to work or whether the treatments or vaccines will be effective in the long run.

Kohandels research team initially focused on using a single ancestral sequence to identify the parts of the viral genome that are not significantly affected by mutations. These are the so-called conserved part of the virus.

Identifying the conserved parts of a pathogen is valuable because even if there are mutations, it will not impact the efficacy of vaccines, treatments or tests that work by targeting those stable pieces.

Imagine that from the beginning of the pandemic, we knew exactly which parts of the genome were going to be stable and which ones would likely change, said Amirhossein Darooneh, a member of the research team and a professor in applied mathematics at Waterloo. Everything would be different right now.

Now that we have so much data on the sequencing of SARS-COV2 and its variants, we are able to use all that information to train a neural network to predict the most likely mutations of the genome. Our AI can predict the mutations that happened with really high accuracy.

After identifying the conserved parts, the team trained an AI to anticipate the mutations that would occur in a pathogen. The machine learning program assessed millions of genomic sequences as part of its training process. The AI was then tested on the genomic sequence of the original strain of coronavirus.

Based on its analysis of the original virus, the AI predicted and identified the variants that came to be known as alpha, beta, gamma, delta and other variants of concern as most likely mutable regions of the genome. Had this information been available at the early stages of the pandemic and when vaccines were first being developed, it could have led to more effective tests and vaccines that were much more resilient against current variants.

Along with its impacts on the pandemic, the new technology can also contribute to other medical treatments.

Even with cancer, we should be able to identify the therapeutic targets for overcoming mutation-driven drug resistance, said Michelle Przedborski, another of the team members and a professor of applied mathematics at Waterloo. Lots of drugs are targeting a specific part of the protein in cancer cells. But if there are mutations in those, then drugs wouldnt be effective anymore. We can apply the same analysis and AI method to other pathogens.

Kohandel, Darooneh and Przedborski are working towards commercializing their AI-based software for pathogen mutation prediction with the University of Waterloo Commercialization Office (WatCo).

This article has been republished from the following materials. Note: material may have been edited for length and content. For further information, please contact the cited source.

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AIs Ability To Predict Virus Mutations Helps To Design More Effective Drugs and Vaccines - Technology Networks

There are now 75 AY lineages identified, each with different additional defining mutations in their genome.AY.4 has accounted for 63% of new UK cases in the last 28 days

No sooner than you thought all the talk of new COVID variants was over, theres news of yet another one: AY.4.2. But what is it, where did it come from, and should we be concerned?

AY.4.2 is whats termed a lineage. These are labels given to branches of the COVID evolutionary tree to illustrate their relatedness. They are overseen by the diligent Pango network, a joint team of researchers from the universities of Edinburgh and Oxford, who act as the custodians of lineages and handle the assignment of new ones.

If we go back to April of this year, we can trace the origins of AY.4.2. Our team in Northumbria, working as part of Cog-UK the British consortium that sequences the genomes of COVID samples to see how the virus is changing had just sequenced two samples connected via travel history to India.

At the time we knew the lineage circulating in India was B.1.617, but the cases we had sampled didnt match this. Variants are distinguished by the different mutations they have in their genetic material and, looking at the mutations in our samples, it appeared our cases were missing some of the commonly accepted mutations of B.1.617 but also had some additional ones.

What we were reporting to colleagues in Cog-UK was classified the following week as B.1.617.2, one of three main sub-lineages of B.1.617, and which was later named delta by the World Health Organization.

AY is a further evolutionary step forward from here. Once a lineages labelling gets five levels deep, a new letter combination is started to avoid the name getting too long. So the AY forms of the virus arent vastly different from whats come before, even though their labelling is different. They are all sub-lineages of delta.

There are now 75 AY lineages identified, each with different additional defining mutations in their genome. One of these AY.4 has been steadily growing in proportion in the UK over the last few months, accounting for 63% of new UK cases in the last 28 days.

Does AY.4 have an advantage?

Were still not sure if AY.4s mutations confer a genuine advantage or if the increasing frequency of the lineage is simply down to whats called a founder effect. This is when a subset of viruses get separated from the overall viral population, and then reproduce in isolation. In the area where the separated viruses are, all subsequent viruses will therefore be descendants of this subset.

With COVID, this might have happened by there being a single case at a large event. This lone virus would have been the founder, the only virus spreading at the event. If it infected a sizeable number of people, who later infected others, this may have quickly built up a large amount of virus all from the same origin. Sometimes, for a certain form of a virus to dominate, it doesnt have to be better than others it simply needs to be in the right place at the right time.

But, given its rise to dominance in the UK, AY.4 might well have a selective advantage. The defining change in AY.4 is the mutation A1711V, which affects the viruss Nsp3 protein, which plays a number of roles in viral replication. However, the impact of this mutation is unknown.

This brings us to AY.4.2 a sub-lineage of AY.4 which was first noted at the end of September, though it appears it surfaced in the UK around June. Its defined by two additional genetic mutations, Y145H and A222V, that affect the spike protein. The spike protein is a key part of the viruss outer surface, and is the part of its structure that it uses to get inside cells.

AY.4.2 has grown steadily in volume to the point where it now accounts for about 9% of UK cases in the last 28 days. It has also been observed in a few European nations: Denmark, Germany and Ireland, to name a few.

But whether its two mutations offer the virus a selective advantage is unclear as well. A222V was previously seen last year in the B.1.177 lineage that probably emerged in Spain and was then spread across northern Europe, most likely by holidaymakers. At the time, many were sceptical that A222V conferred an advantage. Indeed, the increase in the form of the virus thats become known as AY.4.2 seems to have only occurred since it acquired its Y145H mutation.

This mutation is within an antigenic supersite of the spike protein a part of the protein that antibodies frequently recognise and target. We know that this part of the spike protein has already been modified once before by a mutation in deltas genetic material, and that this possibly contributes to deltas greater ability to escape immunity, as antibodies have a harder time targeting it as a result.

However, the research exploring this is still in preprint, meaning it is yet to be formally reviewed so we need to treat its findings with caution.

But its therefore possible the Y145H mutation could give the virus an even greater ability to escape immunity by making this supersite less recognisable to antibodies.

The counterargument is that, despite introduction into several European countries, AY.4.2 has failed to take hold, dropping off the radar in Germany and Ireland though it is lingering in Denmark. This would suggest its ability to get around immunity isnt any greater than deltas. Equally, it might just be that there wasnt enough of AY.4.2 arriving in these places for it to take hold.

Really, its too early to tell if this is the beginning of the next dominant lineage. Any ability it might have to escape immunity needs to be confirmed by experimental work. Clearly, though, its emergence shows that theres a continued need for genomic surveillance of the virus.

Matthew Bashton, Senior Fellow in Computational Biology, Northumbria University, Newcastle et Darren Smith, Professor of Bacteriophage Biology, Northumbria University, Newcastle

This article is republished from The Conversation under a Creative Commons license. Read the original article.

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COVID-19: How worried should we be about the new AY.4.2 lineage of the coronavirus? - Down To Earth Magazine

JAMA Netw Open. 2021 Oct 1;4(10):e2131020. doi: 10.1001/jamanetworkopen.2021.31020.

ABSTRACT

IMPORTANCE: Understanding interactions among health service, sociodemographic, clinical, and genomic factors in breast cancer disparities research has been limited by a disconnect between health services and basic biological approaches.

OBJECTIVE: To describe the first linkage of Surveillance, Epidemiology, and End Results (SEER)-Medicare data to physical tumor samples and to investigate the interaction among screening detection, socioeconomic status, tumor stage, tumor biology, and breast cancer outcomes within a single context.

DESIGN, SETTING, AND PARTICIPANTS: This population-based cohort study used tumor specimen blocks from a subset of women aged 66 to 75 years with newly diagnosed nonmetastatic, estrogen receptor-positive invasive breast cancer from January 1, 1993, to December 31, 2007. Specimens were obtained from the Iowa and Hawaii SEER Residual Tissue Repositories (RTRs) and linked with Medicare claims data and survival assessed through December 31, 2015. Data were analyzed from August 1, 2018, to July 25, 2021.

EXPOSURES: Screening- vs symptom-based detection of tumors was assessed using validated claims-based algorithms. Demographic factors and zip code-based educational attainment and poverty socioeconomic characteristics were obtained via SEER.

MAIN OUTCOMES AND MEASURES: Molecular subtyping and exploratory genomic analyses were completed using the NanoString Breast Cancer 360 gene expression panel containing the 50-gene signature classifier. Factors associated with overall and breast cancer-specific (BCS) survival were analyzed using Cox proportional hazards regression models combining sociodemographic, clinical, and genomic data.

RESULTS: SEER-Medicare data were available for 3522 women (mean [SD] age, 70.9 [2.6] years; 3049 [86.6%] White), of whom 1555 (44.2%) were diagnosed by screening mammogram. In the SEER-Medicare cohort, factors associated with increased BCS mortality included symptomatic detection (hazard ratio [HR], 1.49 [95% CI, 1.16-1.91]), advanced disease stage (HR for stage III, 2.33 [95% CI, 1.41-3.85]), and high-grade disease (HR, 1.85 [95% CI, 1.46-2.34]). The molecular cohort of 130 cases with luminal A/B cancer further revealed increased all-cause mortality associated with genomic upregulation of transforming growth factor activation and p53 dysregulation (eg, p53 dysregulation: HR, 2.15 [95% CI, 1.20-3.86]) and decreased mortality associated with androgen receptor, macrophage, cytotoxicity, and Treg signaling (eg, androgen receptor signaling: HR, 0.23 [95% CI, 0.12-0.45]). Symptomatic detection (HR, 2.49 [95% CI, 1.19-5.20]) and zip codes with low levels of educational attainment (HR, 5.17 [95% CI, 2.12-12.60]) remained associated with mortality after adjusting for all clinical and demographic factors.

CONCLUSIONS AND RELEVANCE: Linkage of SEER-Medicare data to physical tumor specimens may elucidate associations among biology, health care access, and disparities in breast cancer outcomes. The findings of this study suggest that screening detection and socioeconomic status are associated with survival in patients with locally advanced, estrogen receptor-positive tumors, even after incorporating clinical and genomic factors.

PMID:34714340 | DOI:10.1001/jamanetworkopen.2021.31020

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Analysis of Sociodemographic, Clinical, and Genomic Factors Associated With Breast Cancer Mortality in the Linked Surveillance, Epidemiology, and End...

Scientists are exploring why some creatures throw away bits of their DNA during development

To do their lab work, Laura Ross and her team must conduct an itty-bitty surgery. First, they dissect out the reproductive tissues of the black-winged fungus gnat, a diminutive black fly about one-sixteenth to one-eighth of an inch long. Then they home in on particular cells in that tissue: the germ cells, which produce eggs and sperm and so hold the keys to the genome of the next generation.

Ross, an evolutionary biologist at the University of Edinburgh in Scotland, roots around in fungus-gnat parts because theres something odd about the cells in these flies: They dont follow the textbook rules. In sexually reproducing creatures, one full copy of the mothers genetic material generally fuses with one full copy of the fathers to create the complete, doubled-up set of DNA found in cells throughout the body.

But the fungus gnat does something bizarre. Early in the embryos development, most of the cells jettison two specific chromosomes enormous ones, compared with the others so the pair never ends up in the lions share of the gnats body. Only the cells that become germ cells retain the bonus DNA and pass it on to the next generation.

How and why this feature evolved remains largely mysterious, though biologists first spotted it a century ago. And black-winged fungus gnats arent the only genetic screwballs. A surprisingly wide array of creatures, all the way up to some vertebrates, dump significant stretches of DNA during early development, so the stretches dont end up in most of their body cells.

To date, scientists have observed the phenomenon in various insects, in lampreys and hagfish, in hairy one-celled life forms called ciliates, in parasitic roundworms and tiny crustaceans called copepods. Theyve seen it in rat-like marsupials called bandicoots and in songbirds probably all songbirds, according to recent work. And they expect to find many more cases.

A lot of these weird genomic features tend to be fairly rare, but they do evolve repeatedly, Ross says. Its not just one freak event. Presumably, then, there must be some selective advantage to the creatures that go down that evolutionary route. But what is it?

Beyond their fascinating oddness, these quirks may hold broader lessons on how genomes work the way they do, scientists think, and how and why the DNA in germ cells is treated differently from the DNA in the rest of the developing critters body.

Its a fundamental difference between the DNA thats going on to the next generation and the DNA thats in all the other cell types, says Jeramiah Smith, a geneticist at the University of Kentucky who studies the phenomenon in lampreys anddescribed it in the 2020Annual Review of Animal Biosciences.

Starting in the late 1800s, well before scientists nailed down the link between DNA and heredity, biologists peering down microscopes used dyes to study tiny, twig-like bodies inside dividing cells, watching as the twigs grouped together and then separated. German anatomist Wilhelm von Waldeyer-Hartz named these structures chromosomes in 1888, for the ease with which they took up dye.

Around the same time, cell biologists observed chunks of chromosomes being discarded in a parasitic roundworm calledParascaris univalensthat infects horses a much-studied worm because its pair of huge chromosomes were easy to view under a microscope. In later decades, researchers described other worm species that dropped segments from several chromosomes during early rounds of cell division in embryos. But they didnt have the technology to really explore it, says Richard Davis, an emeritus molecular biologist at the University of Colorado School of Medicine in Aurora.

Davis, who dedicated the last decade of his career to studying how this casting-off happens in a handful of roundworms, initially thought that the DNA being eliminated carried no blueprint for any genes. Most biologists (those whove heard of the phenomenon, anyway) have assumed the same thing, he says.

It turned out, though, that this ditched DNA contains genes lots of them. Roundworms from the genus Ascaris, which infect pigs and people, dump about 5 percent of their genes, while those of the genus Parascaris cast off about 10 percent. Only the cells that are destined to form the worms body do the DNA ditching: Just like the black-winged fungus gnat, the full set of genes remain in the cells destined to form eggs and sperm. The worms offspring, and its offsprings offspring, repeat the exact same process.

Davis also noticed something else: Most of the genes that are retained in the germ cellsare active in those cells, implying theyre needed there. And so Davis thinks that tossing the genes away in all the other body cells may be the worms ironclad method of making sure the genes dont become active where they arent meant to.

Guaranteeing that genes are active at certain times but not others, or in some tissues but not others, is a critical function for any living thing. Think of the many different cell types in our bodies: All contain the same DNA sequence, but our heart cells produce different proteins than our skin cells do, so that each can do its specialized job. And even within a particular type of cell, the proteins that are produced vary during a creatures lifespan.

Perhaps what these dropped genes do would be so damaging to adult cells that eliminating them is a better-safe-than-sorry device, Davis says. Its total speculation, though because theres no proof of anything.

But that also presents a puzzler thats yet to be solved. Most living things already have ways to silence specific genes by adding chemical tags. So why do they choose to do this? Davis says.

Smith thinks the same type of extreme gene silencing may be at play in lampreys. His labstumbled upon DNA elimination in these ancient jawless fishwhile working with colleagues on decoding the lamprey genome. Smith had seen research from the 1980s reporting chromosome loss in the closely related hagfish. He decided to see if lampreys were doing the same thing.

Lamprey physiology makes it easy to extract eggs and sperm from the animals Smith likens it to milking a cow or squeezing toothpaste out of a tube. He then fertilized the eggs and watched the embryos develop and found that they were dropping chromosomes 1.5 to 3 days after fertilization.

Lampreys lose 12 entire chromosomes out of their initial set of 96, and perhaps some bits and pieces from the chromosomes that remain. The losses are pre-programmed to occur in almost all the cells of the embryo except for a small handful of cells destined to soon become germ cells. Ultimately, those bits end up in sperm and egg cells, but not in any other lamprey cells.

Using advanced sequencing methods that were just coming online at the time, Smith and his colleagues identified many genes in the eliminated DNA. Intriguingly, about 60 percent to 70 percent of the genes are similar to ones that, in our species, are thought to boost cancer when their activity gets out of control. Whatever their normal function is, those genes might be especially dangerous ones to keep around in body cells. We think lamprey are getting rid of these genes as a means of permanently silencing them, Smith says.

Rosss fungus gnats,Bradysia( Sciara) coprophila, have their own special mystery. They have been bred and maintained for decades, passing from lab to lab. Researchers in the 1920s studying how chromosomes behave in the cell noticed that these flies lose two chromosomes in some cells. (Some insects, its now known, have more than 80 chromosomes to dispose of.) But these chromosomes called germline restricted chromosomes because they are only retained in the germline are almost as large as the rest of the gnats genome.

In fact, theyarebasically an entire genome, as they contain an entire extra set of the genes a gnat has. But fungus gnats are weirder still. When Ross and her team sequenced the chromosomes, she found that the genes they bear arent especially similar to ones of the species they reside in. It looks like the genome of a completely different species, Ross says of an entirely different group of flies.

Rosss best guess is that during a rare mating event between two different species eons ago,the genome of one got integrated into the genome of the otherand somehow got shunted to the germline alone. For her, this still-hypothetical freak event along with other weirdnesses over how flies pass on their genetic material points to a fundamental mystery. The definition of life is being able to copy and paste your genetic material into future generations, she says. Why is this process so variable, and what drives that variation?

That same question drives Alexander Suh, an evolutionary biologist at the University of East Anglia in the UK and Uppsala University in Sweden, who studies a germline-restricted chromosome in the zebra finch, a songbird. Researchers first reported its existence in 1998. As a zebra finch embryo develops, this chromosome somehow magically, says Suh, and I say that with quotes just because I have no explanation yet, gets dropped from all cells except the germ cells.

This bizarre chromosome, too, is chock-full of genes, many of them present in multiple sometimes hundreds of copies. And many are active in the germline.Suh and colleaguesand another groupindependently reported in 2019 that the chromosome dates back to the common ancestor of songbirds, and that all songbirds about half of all birds carry it.

Whatever it is, its been around for 50 million years, Suh says. Its somehow made sure that the host cannot exist without it.

Now Suhs team and others are puzzling out the possible role of this chromosome by looking at the function of the genes it contains. In the zebra finch at least, many of them seem related to development of the female gonad. Others appear to be involved in other aspects of early development.

But its a head scratcher, Suh says, why these genes get passed down in a roundabout way that differs from the standard system of heredity. Smith, Ross and Davis are similarly pondering the reasons for the systems that they study in lampreys, flies and worms.

Perhaps the chromosomes (or bits of chromosomes) are selfish just in it for themselves and have engineered ways to be retained. Or maybe these germline-restricted chromosomes have a benefit for example, by serving as incubators where newly evolved genes are safely housed until it can be determined if theyre beneficial or damaging to the organism.

Alternatively, the processes could be holdovers from earlier evolutionary events. Maybe, says Smith, this silencing technique evolved before or in parallel with some of the silencing methods that vertebrates use today. Is this something that at one period of time defined our ancestors biology?

But whatever the answer or answers turns out to be, its striking, Suh says, how few people, even among biologists, are aware that genes and heredity so often work in peculiar ways.

Maybe, he says, this is something we need to start teaching earlier on: how even more fascinating the genome is than we already thought.

This article originally appeared in Knowable Magazine, an independent journalistic endeavor from Annual Reviews. Sign up for the newsletter.

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The curious case of the shrinking genome - Knowable Magazine

Researchers led by the University of Bath in collaboration with the University of Birmingham observed the evolution of two strains of the soil bacteria Pseudomonas fluorescens (SBW25 and Pf0-1). When the scientists removed a gene that enables the bacteria to swim, both strains of the bacteria quickly evolved the ability to swim again, but using different routes. These findings shed light on how to predict the evolution of bacteria and viruses over time.

The research was published in the journal Nature Communications in a paper titled, A mutational hotspot that determines highly repeatable evolution can be built and broken by silent genetic changes.

Mutational hotspots can determine evolutionary outcomes and make evolution repeatable. Hotspots are products of multiple evolutionary forces including mutation rate heterogeneity, but this variable is often hard to identify, the researchers wrote. In this work, we reveal that a near-deterministic genetic hotspot can be built and broken by a handful of silent mutations.

The researchers compared the DNA sequences of the two strains to understand the differences they observed. They found that in the SBW25 strain, which mutated in a predictable way, there was a region where the DNA strand looped back on itself forming a hairpin-shaped tangle.

Our experiments show that we were able to create or remove mutational hotspots in the genome by altering the sequence to cause or prevent the hairpin tangle, explained Tiffany Taylor, PhD, a research fellow at the Milner Centre for Evolution.This shows that while natural selection is still the most important factor in evolution, there are other factors at play too.

If we knew where the potential mutational hotspots in bacteria or viruses were, it might help us to predict how these microbes could mutate under selective pressure.

This information can help scientists better understand how bacteria and viruses evolve, which can help in developing vaccines against new variants of diseases. It can also make it easier to predict how microbes might develop resistance to antibiotics.

James Horton, PhD, a postdoc at the Milner Centre for Evolution, added: Like many exciting discoveries, this was found by accident. The mutations we were looking at were so-called silent because they dont change the resulting protein sequence, so initially, we didnt think they were particularly important.

However our findings fundamentally challenge our understanding of the role that silent mutations play in adaptation.

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DNA Tangles Found to Create Mutational Hotspots in the Genomes of Bacteria - Genetic Engineering & Biotechnology News

Centre dAnthropobiologie et de Gnomique de Toulouse, Universit Paul Sabatier, Toulouse, France

Pablo Librado,Naveed Khan,Antoine Fages,Mariya A. Kusliy,Tomasz Suchan,Laure Tonasso-Calvire,Stphanie Schiavinato,Duha Alioglu,Aurore Fromentier,Charleen Gaunitz,Lorelei Chauvey,Andaine Seguin-Orlando,Clio Der Sarkissian&Ludovic Orlando

Department of the Diversity and Evolution of Genomes, Institute of Molecular and Cellular Biology SB RAS, Novosibirsk, Russia

Mariya A. Kusliy&Alexander S. Graphodatsky

W. Szafer Institute of Botany, Polish Academy of Sciences, Krakw, Poland

Tomasz Suchan&Magdalena Moskal-del Hoyo

Genoscope, Institut de biologie Franois-Jacob, Commissariat lEnergie Atomique (CEA), Universit Paris-Saclay, Evry, France

Aude Perdereau

Gnomique Mtabolique, Genoscope, Institut de biologie Franois Jacob, CEA, CNRS, Universit dEvry, Universit Paris-Saclay, Evry, France

Jean-Marc Aury&Patrick Wincker

Earth System Science Department, University of California, Irvine, Irvine, CA, USA

John Southon

Department of Ecology and Evolutionary Biology, University of California, Santa Cruz, Santa Cruz, CA, USA

Beth Shapiro

Howard Hughes Medical Institute, University of California, Santa Cruz, Santa Cruz, CA, USA

Beth Shapiro

Department of Archaeology, Ethnography and Museology, Altai State University, Barnaul, Russia

Alexey A. Tishkin,Kirill Yu. Kiryushin&Nikolai N. Seregin

Department of Archaeological Heritage Preservation, Institute of Archaeology of the Russian Academy of Sciences, Moscow, Russia

Alexey A. Kovalev

Zoology Department, College of Science, King Saud University, Riyadh, Saudi Arabia

Saleh Alquraishi,Ahmed H. Alfarhan&Khaled A. S. Al-Rasheid

Institute for Archaeology, Heritage Conservation Studies and Art History, University of Bamberg, Bamberg, Germany

Timo Seregly

Museum stjylland, Randers, Denmark

Lutz Klassen

Saxo Institute, section of Archaeology, University of Copenhagen, Copenhagen, Denmark

Rune Iversen

ArScAn-UMR 7041, Equipe Ethnologie prhistorique, CNRS, MSH-Mondes, Nanterre Cedex, France

Olivier Bignon-Lau,Pierre Bodu&Monique Olive

Musum dhistoire naturelle, Secteur des Vertbrs, Geneva, Switzerland

Jean-Christophe Castel

UMR 5199 De la Prhistoire lActuel : Culture, Environnement et Anthropologie (PACEA), CNRS, Universit de Bordeaux, Pessac Cedex, France

Myriam Boudadi-Maligne&Mlanie Pruvost

Geneva Natural History Museum, Geneva, Switzerland

Nadir Alvarez

Department of Genetics and Evolution, University of Geneva, Geneva, Switzerland

Nadir Alvarez

OD Earth & History of Life, Royal Belgian Institute of Natural Sciences, Brussels, Belgium

Mietje Germonpr

Institute of Systematics and Evolution of Animals, Polish Academy of Sciences, Krakw, Poland

Jarosaw Wilczyski&Sylwia Pospua

Institute of Archaeology and Ethnology Polish Academy of Sciences, Krakw, Poland

Anna Lasota-Ku&Krzysztof Tunia

Institute of Archaeology, Jagiellonian University, Krakw, Poland

Marek Nowak

Department of Archaeology, Institute of History and Archaeology, Tartu, Estonia

Eve Ranname

Department of Zoology, Institute of Ecology and Earth Sciences, University of Tartu, Tartu, Estonia

Urmas Saarma

Diamond and Precious Metals Geology Institute, SB RAS, Yakutsk, Russia

Gennady Boeskorov

Archaeological Research Collection, Tallinn University, Tallinn, Estonia

Lembi Lugas

Department of Natural Sciences and Archaeometry, Institute of Archaeology of the Czech Academy of Sciences, Prague, Czechia

Ren Kysel

Prague, Czechia

Lubomr Peke

Vasile Prvan Institute of Archaeology, Department of Bioarchaeology, Romanian Academy, Bucharest, Romania

Adrian Blescu,Valentin Dumitracu&Roxana Dobrescu

Institute of Archaeogenomics, Research Centre for the Humanities, Etvs Lornd Research Network, Budapest, Hungary

Daniel Gerber,Anna Szcsnyi-Nagy&Balzs G. Mende

Department of Genetics, Etvs Lornd University, Budapest, Hungary

Daniel Gerber

Institute of Archaeology, Research Centre for the Humanities, Etvs Lornd Research Network, Budapest, Hungary

Viktria Kiss,Gabriella Kulcsr&Erika Gl

satrs Ltd., Kecskemt, Hungary

Zsolt Gallina

Rippl-Rnai Municipal Museum with Country Scope, Kaposvr, Hungary

Krisztina Somogyi

School of History, Classics and Archaeology, University of Edinburgh, Old Medical School, Edinburgh, UK

Robin Bendrey

Trace and Environmental DNA (TrEnD) Lab, School of Molecular and Life Sciences, Curtin University, Perth, Western Australia, Australia

Morten E. Allentoft

Lundbeck Foundation GeoGenetics Centre, GLOBE Institute, University of Copenhagen, Copenhagen, Denmark

Morten E. Allentoft

Department of Academic Management, Academy of Science of Moldova, Chiinu, Republic of Moldova

Ghenadie Sirbu

Center of Archaeology, Institute of Cultural Heritage, Academy of Science of Moldova, Chiinu, Republic of Moldova

Valentin Dergachev

Archaeological Institute of America, Boston, MA, USA

Henry Shephard

Centre National de Recherche Scientifique, Musum national dHistoire naturelle, Archozoologie, Archobotanique (AASPE), CP 56, Paris, France

Nomie Tomadini,Sandrine Grouard,Benoit Clavel,Sbastien Lepetz&Marjan Mashkour

Institute for the History of Material Culture, Russian Academy of Sciences (IHMC RAS), St Petersburg, Russia

Aleksei Kasparov,Vladimir Pitulko,Alexander Bessudnov&Nikolay A. Bokovenko

Geological Institute, Russian Academy of Sciences, Moscow, Russia

Alexander E. Basilyan&Pavel A. Nikolskiy

Arctic and Antarctic Research Institute, St Petersburg, Russia

Mikhail A. Anisimov&Elena Y. Pavlova

Institute of Animal Breeding and Genetics, University of Veterinary Medicine Vienna, Vienna, Austria

Gottfried Brem&Barbara Wallner

Department of Prehistory and Western Asian/Northeast African Archaeology, Austrian Archaeological Institute, Austrian Academy of Sciences, Vienna, Austria

Christoph Schwall

Estonian Biocentre, Institute of Genomics, University of Tartu, Tartu, Estonia

Marcel Keller

Department of Archaeogenetics, Max Planck Institute for the Science of Human History, Jena, Germany

Marcel Keller,Johannes Krause&Wolfgang Haak

SFB 1070 Resource Cultures, University of Tbingen, Tbingen, Germany

Keiko Kitagawa

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The origins and spread of domestic horses from the Western Eurasian steppes - Nature.com

Jamaica now has a device that can test for different strains of COVID-19.

Prime Minister Andrew Holness on Friday announcedthat the device a Genome Sequencer is now at the University Hospital of the West Indies.

The long-awaited Genome Sequencer, which will test for different strains for COVID-19, was handed over to the National Influenza Centre at the University Hospital of the West Indies this morning (Friday), Holness said on his social media page.

According to the World Health Organisation (WHOGenomic sequencing has beenimportant for the COVID-19 response.

"New variants are forming all the time, so genomic data has guided countries to make quick and informed public health decisions since the start of the pandemic," a release from WHO has said.

Jamaica recorded 173 new COVID-19 over 24 hours up to Thursday, October 21, according to the Health and Wellness Ministry.

This is while 20 COVID-19 deaths occurred from August 23 to October 19 and were recorded on Thursday, bringing the overall coronavirus death toll in Jamaica to 2,153.

The newly confirmed COVID-19 cases brought the total number on record for the island to 87,970.

And as authorities work to keep cases down Minister of Health and Wellness, DrChristopher Tufton in Septemberannouncedthat the Mu strain of the Coronavirus was in the island.

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Device that can test for different strains of COVID-19 now in Jamaica | Loop Jamaica - Loop News Jamaica