Category Archives: Genome

In VAs Million Veteran Program, researchers are mapping the human genome by using genotypinga process that spells out several hundred thousand data points, one-by-one. (Photo for illustrative purposes only Getty Images/alanphillips)

May 19, 2022

By Mike Richman VA Research Communications

"The importance of this cannot be overstated. Using TOPMed's imputation panel vastly enriches MVP's genetic database."

Since 2011, more than 875,000 Veterans have donated their DNA to the VA Million Veteran Program (MVP). In the program, VA researchers are sequencing Veterans' genomesa complete set of genetic materialto better understand how genes, lifestyles, and military exposures can affect a persons health and risk for illness.

Centrifugation helps scientists extract DNA from a Veteran's blood sample and prepare the DNA for genetic analysis, either through genotyping or whole genome sequencing.

Centrifugation helps scientists extract DNA from a Veteran's blood sample and prepare the DNA for genetic analysis, either through genotyping or whole genome sequencing.

Researchers map the genomes using genotypinga process that spells out several hundred thousand data points, one-by-one. To fill in any missing data, scientists look to genomes where all data points have been fully sequenced. These genomes are used as a reference to determine the missing letters.

MVP has created whole genome sequences for over 140,000 Veterans. However, it takes time to process this large amount of data and make it available for research. It takes even more time to develop a calculation toolcalled an imputation panelto determine the missing data points that remain when genotyping is complete.

In efforts to find a more accurate and cost-effective method for predicting missing genomic data points, VA investigators found a potential interim solution just across town in Bethesda, Maryland: a genomic research program at the National Institutes of Health (NIH).

As part of that solution, MVP has been collaborating with NIH to use a reference panel for imputation.

The panel is run by TOPMedthe Trans-Omics for Precision Medicine Program. The program, funded by NIHs National Heart, Lung, and Blood Institute (NHLBI), aims to generate scientific resources that will improve the understanding of heart, lung, blood, and sleep disorders and advance precision medicine, an approach in health care that takes into account a persons gene variants and his or her environment and lifestyle to find the right treatment.

Since 2014, TOPMed has collected the entire genome sequence of more than 100,000 people. Scientists created a new reference genome and imputation panel based off these whole-genome sequences.

This first-of-its kind imputation panel offers far more statistical accuracy than any previous imputation panels. In that way, it will help scientists develop better treatments specific to a persons genes and environment.

MVP wanted to find a way to use this tool to improve its genetic database, now one of the largest in the world. The database supports the work of more than 500 researchers across VA. With better genetic data, the researchers can uncover new genetic markers associated with disease in Veterans that could someday revolutionize their health care. As such, MVP leaders set out to strike up a partnership with their colleagues in Bethesda.

In 2018, TOPMed and VA began discussions with the goal of using this new imputation panel to re-do genetic analysis on DNA shared by hundreds of thousands of Veterans in MVP.

The importance of this cannot be overstated, says Dr. Phil Tsao, MVPs co-principal investigator in data generation and access. Using TOPMeds imputation panel vastly enriches MVPs genetic database. Over 500 researchers use MVP data to find new genetic markers related to health and illness in Veterans. With better data, they can make better findings. With better findings, we can offer Veterans better care with more laser-focused accuracy.

The TOPMed reference genome for this imputation panel was selected with racial and ethnic diversity in mind. This means VA can make much more accurate sequencing predictions for people who come from non-European ancestry. This is critical for MVP, since approximately 30% of the more than 875,000 Veterans in MVP are from non-European descent.

To be able to more accurately assemble their genome means the research we do on non-European Veteran populations will be much more thorough, says Dr. Sumitra Muralidhar, the director of MVP. That means we can discover new, never-before-known genetic markers connected with health and disease in Veteran populations of non-European descent.

In 2020, VA acquired the TOPMed imputation panel from NIH, and researchers began methodically re-analyzing and updating more than 650,000 genomes from Veterans who provided blood samples when they joined MVP. In December 2021, the update was complete and the new, upgraded data on hundreds of thousands of Veterans became available to research.

Due to our collaboration with TOPMed, we have better genetic data now, which will hopefully lead to findings of new genetic markers for diseases, specifically in diverse Veterans, Muralidhar says. The end result will hopefully be new discoveries and better treatments, as well as a better understanding of the biology of diseases. That way, we can offer more precise treatments for diseases and other health conditions.

Now that MVPs genetic data is updated with TOPMeds reference panel, any findings from MVP data can becompared and validated with findings from other research based on genomes that were also imputed using TOPMeds reference panel.

Use of the TOPMed reference panel in MVP, which is one of the worlds largest genomic biobanks, allows for more collaboration between NIH and VA scientists to cross-validate each others analysis results, says Dr. Saiju Pyarajan, director of the Center for Data and Computational Sciences at the VA Boston Healthcare System. The more people around the world who have been compared to the same reference sample, the more were able to drastically increase the confidence in the conclusions or results from these genomic analyses. This is wonderful for the future of precision medicine.

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Mapping out the human genome - VA's Office of Research and Development

Every cancer is unique because every person is unique, and one of the most important weapons in any cancer battle is information. Isabl offers that in abundance through rapid sequencing of cancer cells entire genomes, potentially showing which therapies will and wont be effective within days. The company has received a breakthrough designation from the FDA and raised $3 million to bring its approach to market.

The last 10 years have brought numerous medical advances due to the commoditization of genomic processes from sequencing to analysis, and cancer treatment is no exception. In fact, because cancer is (though it is a simplification) a genetic mutation that has gotten out of hand, understanding those genes is an especially promising line of research.

Panel tests look within the DNA of cancerous cells for mutations in a selection of several hundred genes known to affect prognosis and clinical strategy. For instance, a cancer may have certain mutations that render it susceptible to radiation treatment but resistant to chemo, or vice versa its incredibly helpful to know which.

Isabl co-founder and CEO Elli Papaemmanuil explains that however helpful panel tests are, theyre only the beginning.

These tests have been designed very carefully to look for the most common mutations, and they have revolutionized cancer diagnosis for patients with common cancers, she said. But patients with rare cancers and what we define as a rare cancer is still a third of patients dont benefit from them.

Even many with common cancers may find that their condition does not involve mutations of these most predictive genes. The relevant genes are somewhere among the other two billion base pairs current tests only look at about 1% of the genome.

While the technology exists to look at that other 99%, it has historically been expensive and slow compared with panels, and analysis of the resulting large body of data was likewise difficult and time consuming. But Isabls tests show that its definitely worthwhile.

Image Credits: Isabl

It turns out that whole-genome sequencing can detect many more clinically relevant findings results we can act on today. And what weve done is develop a platform that lets us summarize it in a way that doctors can read and use, in a day, Papaemmanuil said. They call it a clinically actionable whole genome and transcriptome test, or cWGTS.

The company was formed out of research Papaemmanuil did at Memorial Sloan Kettering, a cancer care and science nexus in New York. You could see all these successes from panel testing, then all these patients who werent benefiting. But in my lab we had the tech and the know-how, she recalled. They collected and combined three different data sets: the germline (i.e., patients) genomes; the tumors genome and also its transcriptome, essentially what the body produces from transcribing the DNA.

This gives a really full picture of the profile of the tumor, she said. Rather than having a classifier or a model that annotates the mutations [i.e., an automated panel test], we have analytics that integrate those three layers to interpret the role of the mutation and its relevance to each tumor type.

Though it does own the whole process from sampling to report, Isabls key advance is data based and therefore there is no technical obstacle to making this solution available today. And weve demonstrated we can do it at scale, Papaemmanuil said. But in the medical world, just because its possible doesnt mean its permitted. The FDA has granted the technology with breakthrough status, which is a fast track but even the fast track is slow in the federal government.

While full clinical approval is probably 3-5 years away, thats much faster than the 5-10 years estimated by the industry for this type of application. But research, both for validation and other purposes, is ongoing, having just published the main paper proving out the process today in Nature Communications. (Though this study focuses on pediatric and young adults cancers, the technique is not limited to those demographics.)

The seed round is very much to let us do the roadmap its a good starting point for getting the necessary evidence and approvals, Papaemmanuil said. Were already partnering with cancer centers to do studies, and most importantly, to hear from oncologists on what they need and how theyd like the data.

From left, Isabl co-founders Andrew Kung, Elli Papaemmanuil and Juan Santiago Medina. Image Credits: Isabl

The $3 million round was led by Two Sigma Ventures, with participation from Y Combinator, BoxOne Ventures and other firms. Papaemmanuils co-founders are CTO Juan Santiago Medina and Andrew Kung.

She also made it clear that Isabls research would be conducted openly We have a very strong scientific foundation and will be active in publishing the work. The data needs to be both published and made accessible in a form that will enable further research, she said. The self-reinforcing play of producing and identifying predictive data could prove an incredibly valuable resource across many disciplines.

Isabl is an example of the power of a more or less pure data play in an industry more frequently associated with advances in the lab though of course it took a lot of lab work to produce in the first place. But when automation of key processes, in this case DNA transcription, enables a huge uptick in data capture, theres always value to be found in it. In this case that value could save many lives.

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Isabls rapid whole-genome analysis opens the playbook for cancer treatment - TechCrunch

Nevan Krogan, PhD, speaks with research associate Antoine Forget, PhD, and specialist Rasika Vartak in his lab. Image by Noah Berger

Breast cancer, COVID-19, and autism may seem unrelated, but they share some surprising connections. Some of the same genes that are mutated in breast cancer also get hijacked by COVID-19, and some other genes mutated in cancer are also implicated in autism.

Commonalities like these have led Nevan Krogan, PhD, director of UCSFs Quantitative Biosciences Institute, to examine in detail the effects of a handful of genes that seem to play an outsize role in a wide array of diseases.

Those effects rely on proteins, for which genes are the blueprints. When a gene is mutated, so is its protein.

Our genome is relatively static, but proteins arent, said Krogan. Theyre constantly interacting with other proteins in different contexts that change over time.

Many conditions involve dozens of mutations, he added. Seeing the full landscape of a persons disease means piecing together how each of those mutated proteins contributes to it.

More than a decade ago, Krogan began employing sophisticated quantitative approaches to create cell maps that compare thousands of these protein-protein interactions, or PPIs, in healthy and diseased cells across a range of mutations in cancer, autism, and infectious disease.

He believes that zeroing in on these PPIs can elucidate how mutations disrupt cell functions and uncover entry points for safer and more effective treatments.

Already, collaborations between Krogan and researchers in the U.S. and around the world have revealed how mutations in different genes sometimes bungle the same cellular pathways, illuminating connections between diseases that may look quite different at the genetic level.

In other cases, the same gene is implicated in more than one disease: a mutation at point A may contribute to cancer, while a mutation at point B may create a predisposition to a psychiatric disorder.

Were finding the Achilles heels of the genome, Krogan said. By going beyond DNA and looking at these networks of protein interaction, were able to connect dots that we didnt even know existed before.

To find those dots and draw the lines between them, Krogan, along with his collaborators, use his cell maps to see exactly how a specific mutation in a particular gene translates into changes in protein interactions.

A gene called PIK3CA, for example, is involved in a sizable percentage of cancers, as well as autism and other brain disorders. There are hundreds of known mutations in PIK3CA, each of which has a specific effect on the protein machinery.

Krogan has catalogued not only how each of these mutations leads to disease but also how PIK3CAs various pathways play out in healthy cells, allowing him to identify the intersection where each of these mutations throws the cells protein interactions off track.

Achieving this granular approach involves overlaying large sets of data and finding patterns that pinpoint the molecular moment when a cellular process goes awry. Krogans teams use mass spectrometry to weigh the protein molecules and combines it with other methods that assess the proteins structure. Advanced computational techniques are needed to crunch the enormous amount of data involved.

These maps can help provide a prognosis based on proteins resulting from the mutations found in a particular patients genes; help clinicians choose one treatment over another; and reveal where a drug might be able to stop a disease without interfering with other healthy cell functions.

While some researchers have studied PPIs associated with individual gene mutations, Krogan has spent his career investigating them on a massive scale. Theres great value in looking at the big picture, he said. It makes these analyses exponentially more powerful.

Krogan likens the protein maps to a computer-generated geographic map. You can zoom out to see a large area, then zoom in to see local detail, then zoom back out again to put that detail into context.

Being able to see those varying levels of detail can potentially help researchers identify FDA-approved drugs that could be tested for unexpected applications, said Krogan. These cell maps are an entirely new way of looking at disease and drug discovery.

Ultimately, Krogans goal is to enable researchers to apply artificial intelligence to these maps, so they can predict a patients prognosis and the best combination of drugs to treat them.

Once we understand this underlying biology, attacking the disease becomes so much more straightforward, Krogan said. Were perfectly positioned to build this bridge from the genome to the clinic for a whole range of disorders.

Were at the cusp of such great things.

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Navigating From the Genome to the Clinic Using 'Cell Maps' - University of California San Francisco

In the early 1980s, a quiet revolution sparked to life in Los Angeles.

Michael Waterman, then a recently hired professor of mathematics at the USC Dornsife College of Letters, Arts and Sciences, had published a new algorithm with colleague Temple Smith that determined similar regions of protein or DNA sequences. The Smith-Waterman algorithm would serve as a foundational piece of an emerging field of study, computational biology and bioinformatics.

Forty years later, Waterman is considered a father of quantitative and computational biology and his work forms the basis of numerous seminal studies, including the landmark Human Genome Project. The results of his work enabled researchers to analyze and identify long strings of genetic code, profoundly impacting molecular biology and medicine, cancer treatment and biofuel development and changing the way we view life on Earth. He will be recognized for his contributions to the field at the USC Computational Biology Symposium 2022 beginning Thursday.

But when he first proposed applying mathematical models to biological systems, peers didnt know what to make of his work.

We submitted my first paper in this area to a journal and it was roundly rejected.

Michael Waterman, University Professor Emeritus

We submitted my first paper in this area to a journal and it was roundly rejected, infuriating my co-author. Part of the rejection was that they felt the paper satisfied neither the biologists nor the mathematicians, said Waterman, a University Professor Emeritus at USC. Papers that attempt to address the spaces between subjects are usually worthless except when they arent.

I was convinced this was really going to be an area with important insights. I had no idea where we were going. But what started to get people interested was the Human Genome Project.

The launch of the Human Genome Project the international research effort to determine the DNA sequence of the entire human genome in the early 1990s exploded our understanding of biology and foreshadowed the increasing importance of computing in the natural sciences. Waterman developed two algorithms essential to the projects success. The Lander-Waterman algorithm accelerated physical mapping of genetic sequences, while the earlier Smith-Waterman algorithm serves as the foundation of computation genetics and remains the standard for gene and protein analysis.

The popularity and importance of the project thrust Waterman into the spotlight and earned him numerous accolades, including a Guggenheim Fellowship, the Canada Gairdner International Award and elections as a foreign member of the French Acadmie des Sciences and the Chinese Academy of Sciences.

I was a scientist who didnt publicize himself and didnt give too many talks on my research, but the Human Genome Project transformed me, he said. I started giving talks to mathematicians about biology and talks to biologists about what math could do for them. All because there werent that many people doing this research. Of course, today its thousands, if not tens of thousands of people.

When Waterman joined USC in 1982, he found a nascent genetics program and an administration open to developing an interdisciplinary research approach. His computational molecular biology group within the Department of Mathematics resulted in the creation of the worlds first PhD program in computational biology and bioinformatics. Nearly 40 years later, in 2021, USC Dornsife College announced the creation of the Department of Quantitative and Computation Biology. It hosts some of the top researchers in the field, including Remo Rohs, Geoffrey Fudenberg, Mark Chaisson and others, and their success puts the future of the field in good stead, Waterman said.

Professor Watermans legacy at USC are many firsts.

Remo Rohs, USC Dornsife professorof quantitative and computational biology

Professor Watermans legacy at USC are many firsts the first PhD program in computational biology and bioinformatics in the world and one of the first undergraduate majors in quantitative biology [QBIO] in the country, said Rohs, professor of quantitative and computational biology and founding chair of the Department of Quantitative and Computational Biology. I enjoy seeing that the QBIO undergraduate students still have a special place in professor Watermans heart I think they will be his proudest university achievement.

Now we have an academic unit so whatever the future of the field, its in their hands rather than being diffused, Waterman added. I like the group of young faculty that are in the department now they are the future, and they have written some really excellent articles and books. It excites me to see them doing so well.

This year marks two major milestones for Waterman. He rings in his 80th birthday and will be honored at the USC Computational Biology Symposium. Celebrating the 40th anniversary of quantitative biology and bioinformatics at USC, the symposium will feature Waterman and other luminaries in the field.

Waterman remains abreast of the latest developments in computational biology, regularly sitting in on departmental meetings and offering insights. He is especially interested in the analysis of molecular dynamics within cells, which fittingly marries biology and physics to allow scientists to more fully understand how cells operate.

Biology is one of those subjects where the more you learn, the more complicated it gets. Im not somebody who just drills down into pure math, he said. Pure math interests me less now than interacting with the world and its reflections.

More stories about: Computational Biology, Faculty

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An architect of the landmark Human Genome Project looks back - USC News

Genomic features

The quadripartite structure of 22 samples of 17 species in Amaranthus consists of a large single-copy region (LSC with 83, 38284, 062bp), a small single-copy region (SSC with 17, 937 18, 124bp), and a pair of inverted repeat regions (IRs with 23, 96424, 357bp). The full length of the 22 cp genomes ranges from 149,949bp in A. polygonoides to 150, 756bp in A. albus (Table 1). The chloroplast genome sequences were deposited in GenBank (Table 1).

The total GC content was 36.5% to 36.6%, only A. albus, A. blitoides and A. polygonoides have a GC content of 36.5% (Table 1). The chloroplast genome contains a total of 133 genes, including 88 protein-coding genes, 37 tRNA genes, and 8 rRNA genes, 18 of which were duplicated in the inverted repeat regions (see Supplementary Table S1 online). The gene rps12 was trans-spliced; the 50-end exon was located in the LSC region, whereas the 30- intron and exon were duplicated and located in the inverted repeat regions. The partial duplicate of rps19 and ycf1 genes appeared as pseudogenes as they lost their protein-coding ability. 16 genes have introns.

The length of the SSC region was conserved among the subgenera by comparing the length of the chloroplast genomes of 22 individuals from 17 species. A. palmeri, A. tuberculatus and A. arenicola in subgen. Acnida were 18,02718,042bp in length, the SSC length of 5 species of subgen. Amaranthus was 17,93717,948bp, and the SSC length of 8 species of subgen. Albersia was 18,05718,124bp (Tables 1, 2). There were about 77bp InDels in ndhE-G and 180bp InDels in ndhG-I, which induced the variation of SSC length among subgenera (Table 2; see Supplementary Fig. S1 online). The frequencies of SNPs and InDels in the chloroplast genomes of the 17 species were 1.79% and 2.86%, respectively (Table 3). The frequencies of SNPs and InDels in the genes were 1.22% and 1.14%, and the frequencies of SNPs and InDels in the intergenic spacer were 3.25% and 7.32%, respectively (Table 3). In general, the variation mainly occurred in the intergenic spacer region, and InDels mainly occurred in the non-coding region (Table 3). The longest InDel was 387bp, which occurred on ycf2, followed by 384bp InDel on psbM-trnD.

Each species has 28 to 38 repeats, distributed in 30 locations, including 11 to 14 forward repeats, 11 to 17 palindromic repeats, and 6 to 8 reverse repeats ranging from 30 to 64bp in length. There were 19 common repeats locations, of which 11 had no variation and 8 had variation in length. The R3, R8, R11 and R13 had the most abundant variation (Fig.2). The R12 (forward and reverse repeats) was distributed in LSC, IRa, SSC and IRb. The R12 on SSC is almost opposite to R12 on LSC, dividing the entire circular genome into two parts of nearly equal length. The repeats on LSC were mainly concentrated near Repeat 12 (loci 29,57246,282), loci 81668327, loci 29,572 and loci 75,230. The repeats on IRs are constant within the genus. There were two common repeats in SSC, and one was a palindrome sequence shared by subgen. Acnida, subgen. Amaranthus, and A. albus.

The distribution of repeat sequences at 30 loci in Amaranthus. R is short for repeat. The red line segment R12 and the black line segments are repeats in all 17 species, the orange line segment represents a repeating sequence in some species. A repeat with only one line segment indicates that there is only one repeat at the site, and vice versa indicates that there are several different repeats at the site. The chloroplast genome figure was generated by the Geneious Prime v. 2020.1.2 software.

MISA analysis showed that each cp genome of Amaranthus contained 2939 SSRs (see Supplementary Table S4 online). On average, the number of SSR types from more to less was mono-, tetra-, di-, tri-, penta- and hexa-nucleotides in order (see Supplementary Table S4 online). About 55.56% of those SSRs were composed of A or T bases. Among all SSRs, most loci located in LSC (77.78%) and IGS (71.91%). About 12 repeat motifs were shared by all species in the genus while the remaining motifs were species-specific or subgenus-specific (see Supplementary Table S4 online). Different combinations of SSR markers could distinguish all species except A. standleynaus and A. crispus, A. dubius and A. spinosus (see Supplementary Table S4 online).

The topologies of the phylogenetic trees constructed by maximum likelihood and Bayesian methods were the same basically. A. palmeri, A. arenicola and A. tuberculatus clustered together (BS/PP=100/1) to form subgen. Acnida, or the Dioecious Clade (Fig.3). A. hybridus, A. hypochondriacus, A. dubius, A. spinosus, A. retroflexus clustered together (BS/PP=100/1) to represent subgen. Amaranthus, or the Hyridus Clade (Fig.3). And the above two clades were very close (BS/PP=100/1) (Fig.3). A. albus and A. blitoides were clustered with low/moderate value (BS/PP=35/0.84) and separated from subgen. Albersia and were closely related to subgen. Amaranthus and subgen. Acnida (BS/PP=58/0.99) (Fig.3). Among the three species of subgen. Albersia distributed in Galpagos, A. polygonoides became a single basal branch. The other two species, A. albus and A. blitoides, formed a separate clade (Galpagos Clade). The rest of subgen. Albersia were clustered into one branch, namely the ESA+South American Clade (BS/PP=100/1) (Fig.3).

A maximum likelihood topological tree based on chloroplast genome of Amaranthus and three outgroups. Values at each node indicate maximum likelihood bootstrap support (BS)/Bayesian inference posterior probability (PP) value. Individuals marked with grey backgrounds represent major monophyletic branches in the genus. The newick format files are imported into MEGA version 6 to generate the final topology tree.

The partially qualified fragment regions searched by exhaustive method were overlapped, and the overlapped regions were combined together as a hotspot region. Finally, 16 hotspot fragments with a length of 737 to 2818bp were obtained, and the SNP variation frequency ranged from 0.78 to 1.49% (see Supplementary Table S3 online). The topological trees constructed by the alignments of these 17 hot fragments and the topological trees constructed by the alignment sequences of each gene and intergenic spacer were consistent with the chloroplast genome topological tree, namely, the hotspots with more than 90% bootstrap value support for the subgen. Amaranthus, subgen. Acnida and subgen. Albersia branch (excluding A. albus, A. polygonoides, and A. blitoides) were ndhF-rpl32, ycf1 and rpoC2 (Fig.4).

Three maximum likelihood topological trees based on rpoC2, ndhF-rpl32 and ycf1 of Amaranthus and three outgroups. Values at each node indicate maximum likelihood bootstrap support (BS)/Bayesian inference posterior probability (PP) value. AMA represented the subgen. Amaranthus, ACN represented the subgen. Acnida, ALB represented the subgen. Albersia. The newick format files are imported into MEGA version 6 to generate the final topology tree.

In several similar taxa, there were 25 InDels and 11 SNPs between A. tunetanus and A. standleyanus. A. crispus and A. standleyanus had no difference. There are 46 SNPs and 144 InDels between A. arenicola and A. tuberculatus. By sequence alignment and variation analysis, it was found that trnK-UUU-atpF, trnT-UGU-atpB, psbE-clpP, rpl14-rps19, ndhF-D could be used to distinguish A. tunetanus from A. standleyanus, A. crispus, and A. arenicola from A. tuberculatus.

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Genetic variation and structure of complete chloroplast genome in alien monoecious and dioecious Amaranthus weeds | Scientific Reports - Nature.com

Sequencing the genome of cancer tumours is often used to help identify the type of cancer a person has and the best treatment for it.

Although cancer genomics has been used for a few years now, scientists are still learning about the best way to use genomic information to grade and categorize cancers.

One area that has received little attention until now is the methylation status of the cancer genome around specific genes. Methylation refers to the presence or absence of a methyl group on a base molecule within a gene that can affect whether or not a gene is expressed. This control of genetic expression is referred to as epigenetics.

Levels of expression of certain genes can also be affected by copy number variants (CNVs). CNVs arise because some sections of DNA are repeated, and the number of repeats varies between individuals due to deletions or duplications of DNA.

This leaves some people with many copies of a particular DNA sequence, whilst others have far fewer. These variations between individuals can be normal and harmless however, they can also underpin disease.

A type of brain cancer called meningioma is known for the diversity of CNVs that occur between the genomes of different tumors. CNVs can also affect methylation, which further affects gene expression.

In a study by researchers at Northwestern University in Evanston, IL, the scientists decided to look at both the level of methylation in the meningioma genomes and the number of repeats in different CNVs. They included certain genes in the cancer genome known to control growth and repair to see if this provided any insight into outcomes.

The findings are published in the journal Nature Genetics.

Using genomic data from 565 tumors taken from two cohorts of patients who had been followed up for 56 years, researchers profiled the DNA methylation of the cancer genomes. They then analyzed this alongside the presence of DNA repeats at certain points in the genome and also looked at the RNA present in the tumors to determine which genes had and hadnt been expressed.

They found that looking at the number of repeats within certain genes alone did not predict patient outcomes accurately, but looking at the number of repeats of genes alongside the level of methylation revealed three different grades of tumor.

Just over one-third of the tumors in the cohort were designated merlin intact meningiomas, where patients had the best outcomes. These tumors did not involve abnormal numbers of repeats on the gene that codes for a protein called merlin, which acts as a tumor suppressor. There was also normal methylation around this gene, allowing it to be expressed normally.

Conversely, 38% had immune-enriched meningiomas where patients had intermediate outcomes. These tumors were characterized by loss of the gene that codes for merlin and downregulation of other tumor-suppressing genes due to methylation.

This allowed them to overcome normal responses from the immune system.

A further 28% had hypermitotic meningiomas where the patient not only had fewer repeats of the gene that codes for merlin but a number of other gene repeats that caused either increased growth or decreased tumor suppression.

They also had methylation that allowed the increased expression of a gene known to promote cell growth. These patients had the least favorable outcomes.

Using this information, the researchers then tested the drug abemaciclib, a cancer drug already used for breast cancer, on tumor cells in cell lines, organoids, and xenografts in mice.

Results from these experiments indicated the drug could be used to treat individuals who had been identified as having either immune-enriched tumors or hypermitotic tumors.

Previously trials have failed to identify drugs that could reliably treat meningioma, but the identification of a biomarker could help identify patients who could benefit from certain treatments, said lead study author Dr. Stephen Magill.

Dr. Magill is an assistant professor of neurological surgery at Northwestern University Feinberg School of Medicine. He told Medical News Today in an interview: Some of our findings are really raising the possibility that the more we know about the biology, [the more] we can then say: this isnt just a meningioma, you have a hypermitotic meningioma.

So we can really use that as a biomarker to stratify who would go into a clinical trial.

Cancer researcher professor Noam Shomron from the Sackler Faculty of Medicine from Tel Aviv University, Israel, who was not involved in the research told Medical News Today:

I think its a wonderful study, because its so comprehensive, and it spans molecular and clinical findings and structural variations and methylation which is epigenetics [and something that] doesnt often take center stage.

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Brain tumor growth may be halted with breast cancer drug - Medical News Today

From UF/IFAS

New research led by a University of Florida scientist shows a development regulator can help plants grow. In the bigger picture, the studys results also may help genome editing and as a result, plant breeding.

Development regulators are genes that regulate plant development and growth. UF/IFAS scientists have discovered that one such gene can help deliver DNA into a plant to promote shoot growth from either a stem of a whole plant or young leaves cultured in a petri dish.

Results from the study show that injection of a plant developmental regulator known as PLT5 into the stem helps some snapdragons and tomatoes grow into new shoots. In addition, scientists found that the PLT5 can help young leaves or petioles of cabbages grow into a whole plant after culturing them in the petri dish.

Generally, it is extremely difficult for cells from some plants to grow into whole plants from a tissue culture, said Alfred Huo, an assistant professor of horticultural sciences at the UF/IFAS Mid-Florida Research and Education Center. By applying PLT5, scientists can more effectively deliver genes or DNA fragments into plant cells, which means plants can grow from the cellular level to adulthood more efficiently.

This research can help scientists address some questions in basic plant breeding, including how to get certain genes into plants, Huo said. It can also help scientists as they apply genome editing to many plant species.

This finding can accelerate a breeding program, Huo said. You want to use genome editing for plant breeding. But you need to deliver a genome editing toolbox to plants to make the editing happen. With this process, scientists can eventually create some desirable traits in plants and develop new cultivars. In this case, the PLT5 regulator can help deliver this toolbox and help grow young leaves or stems into new plants carrying these desirable traits.

More than 20 scientists across Florida including Huo are part of the UF/IFAS Plant Breeding team. They develop new varieties of citrus, tomatoes, strawberries, blueberries, cattle forages, peanuts, sugarcane, ornamental plants, and more.

The mission of the University of Florida Institute of Food and Agricultural Sciencesis to develop knowledge relevant to agricultural, human, and natural resources and to make that knowledge available to sustain and enhance the quality of human life. With more than a dozen research facilities, 67 county Extension offices, and award-winning students and faculty in the UF College of Agricultural and Life Sciences, UF/IFAS brings science-based solutions to the states agricultural and natural resources industries and all Florida residents. ifas.ufl.edu.

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UF scientist based in Apopka may have found a way to more efficiently apply genome editing to plant breeding - The Apopka Voice

New York, May 19, 2022 (GLOBE NEWSWIRE) -- Reportlinker.com announces the release of the report "Synthetic Biology Market Forecast to 2028 - COVID-19 Impact and Global Analysis By Products, Technology, and Application" - https://www.reportlinker.com/p06279470/?utm_source=GNW The increasing investments in synthetic biology and the rising number of start-ups are driving the market growth. However, the renewed regulations for biotechnology hamper the market growth.

Synthetic biology is the science of designing, altering, and building simple organisms to perform specific therapeutic or industrial utilities. The organisms created are genetically modified organisms (GMOs), which do not require a definition that distinguishes them from genetic modifications.

The rising number of start-ups is expected to support market growth during the forecast period.Biotechnology entrepreneurs easily raise funds and procure equipment and space from governments of the respective countries.

Indie Bio (California, US) and EU (Ireland) are among the first synthetic biology accelerators.The start-ups are emerging in Asia Pacific, as governments in this region are providing funds for the domestic development of synthetic biology.

For instance, the Government of India funded IITM Bioincubator, a department of the Indian Institute of Technology Madras, to start a state-of-the-art research facility for cancer biology and a Bioinformatics Infrastructure Facility.The funds were provided by agencies such as the Council of Scientific and Industrial Research (CSIR), the Department of Biotechnology (DBT), and the Department of Science and Technology (DST).

The Indian Institute of Technology Madras raised US$ 7.86 million (550 million rupees) in the fiscal year 20162017. In China, Chinaccelerator is a financer that provides mentorship programs for helping start-ups. It is also associated with SOSV, a venture capital and investment management firm,, which helps establish start-ups by providing funds under programs such as RebelBio and Indie Bio. The easy availability of funds for ideas is motivating entrepreneurs in the world to establish synthetic biology businesses.

Siolta Therapeutics, a US-based firm founded in 2016, produces therapeutic microbial consortia to prevent and treat inflammatory illnesses. It evaluates clinical data and develops mixed-species therapies for oral supplementation. Unlike existing medications for allergies, the microbiome-based approach operates before the onset of the immune dysfunction cascade. STMC-103H, a flagship therapeutic candidate of Siolta Therapeutics, is being studied for the treatment of allergic asthma as well as other chronic inflammatory illnesses, including atopic dermatitis and allergic rhinitis.

Kinnva Ltd., established in 2017, is a synthetic biology start-up catering to biotech, cleantech, and Agri-tech segments. Using a unique fermentation technology and sophisticated processing methods, Kinnva produces high-value biochemicals for applications in the food, feed, nutraceuticals, and cosmetics industries.

Genecis, a Canadian firm established in 2016, employs synthetic biology techniques to convert the trash into high-value commodities. The company used bacterial culture to treat food waste from landfills into compostable polyhydroxyalkanoate (PHA) bioplastics. These bioplastics are suitable for the food, agriculture, and textiles businesses, among others, willing to replace plastics with more sustainable alternatives. PHA polymers, unlike ordinary plastics, disintegrate within a year.

Thus, start-ups are contributing significantly to the synthetic biology market expansion.

Based on product, the synthetic biology market is segmented into oligonucleotides, chassis organisms, enzymes, and xeno-nucleic acid.The oligonucleotides segment is likely to hold the largest share of the market in 2021.

Moreover, the same segment is anticipated to register the highest CAGR in the market during the forecast period of 2021 to 2028.Based on technology, the synthetic biology market is segmented into, gene synthesis, genome engineering, measurement & modeling, cloning & sequencing, nanotechnology, and others.

In 2021, the gene synthesis segment is likely to hold the largest share of the market.However, the genome engineering segment is expected to register highest CAGR during 2021 to 2028.

The growth of genome engineering segment is owing to the rising applications of genetic engineering and gene therapy. Further, based on application, the synthetic biology market is segmented into medical applications, industrial applications, enviornmental applications, food and agriculture, and others. The medical applications segment is further segmented as, drug discovery & therapeutics and pharmaceuticals. In 2021, the medical applications segment held the largest market share, and it is expected to register the highest CAGR during 20212028.

Various organic and inorganic strategies are adopted by companies operating in the synthetic biology market.The organic strategies mainly include product launches and product approvals.

Inorganic growth strategies witnessed in the market are acquisitions, collaboration, and partnerships.These growth strategies have allowed the synthetic biology market players in expanding their business and enhancing their geographic presence, along with contributing to the overall market growth.

Additionally, growth strategies such as acquisitions and partnerships helped them strengthen their customer base and extend their product portfolios. A few of the significant developments by key players in the synthetic biology market are listed below.

In February 2022, Thermo Fisher Scientific announced the launch of GeneMapper Software, a flexible genotyping software package that provides DNA sizing and quality allele calls for all Thermo Fisher Scientific electrophoresis-based genotyping.

In January 2022, Thermo Fisher Scientific announced the launch of Oncomine BRCA Assay GX. It is a targeted next-generation sequencing (NGS) assay designed to provide comprehensive amplification of all coding regions of the human BRCA1 and BRCA2 genes, enabling accurate and sensitive detection of various mutation classes.

In April 2022, Merck KGaA Acquisition of MAST Platform from Lonza, a Leading Automated Bioreactor Sampling System. The acquisition of the MAST platform is another milestone to accelerate innovation in Mercks Process Solutions business unit.

In February 2022, Merck announced the transaction closing to acquire Exelead, following regulatory clearances and the fulfillment of other customary closing conditions, for approximately USD 780 million in cash.

A few of the key primary and secondary sources referred to while preparing the report on the synthetic biology market are the World Health Organization (WHO), the National Institute of Health (NIH), and the National Center for Biotechnology Information (NCBI).Read the full report: https://www.reportlinker.com/p06279470/?utm_source=GNW

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In 2021, the gene synthesis segment is likely to hold the largest share of the market.However, the genome engineering segment is expected to register...

DUBLIN--(BUSINESS WIRE)--The "Metagenomic Sequencing Market by Product & Services (Reagent, Consumables, Instrument), Workflow (Sample Preparation, Sequencing), Technology (16S rRNA, Shotgun, Whole-genome), Application (Drug Discovery, Diagnostic) - Global Forecast to 2027" report has been added to ResearchAndMarkets.com's offering.

The metagenomic sequencing market is expected to reach USD 4.3 billion by 2027 from USD 1.9 billion in 2022, at a CAGR of 18.4% during the forecast period.

Growth in the metagenomic sequencing market is mainly driven by continuous technological innovations in NGS platforms, increasing initiatives and funding from government & private bodies for large-scale sequencing projects, declining costs of genome sequencing, and the significant applications of metagenomics in various fields.

Market Dynamics

Based on technology, the metagenomic sequencing market is segmented into 16S rRNA sequencing, shotgun metagenomic sequencing, whole-genome sequencing & de novo assembly, and metatranscriptomics. The shotgun metagenomic sequencing segment is estimated to grow at the highest CAGR during the forecast period. This can be attributed to its advantages over other techniques, the growing adoption of shotgun metagenomic sequencing among researchers and healthcare professionals, and the increasing number of metagenomic sequencing-based research activities.

Based on workflow, the market has been segmented into sample processing & library preparation, sequencing, and data processing & analysis. The sample processing & library preparation segment accounted for the largest share of the metagenomic sequencing market in 2021. The large share of this segment can be attributed to the growing number of metagenome sequencing research projects being conducted, the availability of technologically advanced and robust sample processing and library preparation assay kits, and the demand for efficient library preparation products.

The market in Asia Pacific is expected to register the highest growth rate during the forecast period, primarily due to the increasing financial support from public as well as private agencies, the increasing number of NGS-based research projects, increasing awareness about precision medicine, and the rising prevalence of chronic diseases.

North America accounted for the largest share of the metagenomic sequencing market in 2021. Factors such as the increasing applications of metagenomics in diagnostics and genomics research, the availability of research funding, and the development of NGS data analysis solutions are driving the growth of the metagenomic sequencing market in North America.

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Technological Innovations in NGS Platforms - A Key Factor Driving Growth in the Metagenomic Sequencing Market - ResearchAndMarkets.com - Business Wire

Trinity scientists, along with international colleagues, have explored the importance of sea travel in prehistory by examining the genomes of ancient Maltese humans and comparing these with the genomes of this period from across Europe. Previous findings from the archaeological team had suggested that towards the end of the third millennium BC the use of the Maltese temples declined. Now, using genetic data from ancient Maltese individuals the current interdisciplinary research team has suggested a potential contributing cause. Researchers found that these ancient humans lacked some of the signatures of genetic changes that swept across Europe in this period, because of their island separation. Scientists concluded that physical topography, in particular seascapes played a central role as barriers to genetic exchange.

The study is published today [Thursday 19th May 2022] in the journal Current Biology.

Researchers found these Mediterranean islanders were unusual for their time. They showed evidence of inbreeding in their family history, a sign of small, restricted population size indicating genetic isolation. Interestingly researchers found that one of the ancient individuals analysed was the offspring of second-degree relatives. This was an outstanding find as the number of highly inbred individuals is very low even in ancient times, and this is the second most inbred individual yet detected from the Neolithic world.

Scientists in the ancient DNA laboratory in Trinity sequenced the genomes of ancient (4500-5000 yrs old) Maltese humans from the collective cave burials at the Xaghra Circle and compared these with genomes of contemporary groups from around Europe. Trinity collaborated with colleagues from Queens University Belfast, the University of Cambridge, the Superintendence of Cultural Heritage Malta and others on the study (See full list of collaborators in Editors Notes below).

Scientists recreated the genetic geography across the whole of Europe at the time of the earliest farmers. They found evidence that it was fundamentally shaped by its seascapes which include barriers distinguishing Ireland and Britain from the continental mainland, and especially distinguishing the populations from the Scottish Orkney islands. These examples are powerful illustrations of genomic insularity. For genes at least, the seaways were more retardant than accelerant of connection.

The first settlers in the Maltese islands were Neolithic, dated by Queens University from the sixth millennium BC. Communities developed through a series of cultural phases, with some material indications of external connectivity. Maltese culture flourished from 3600 BC with distinctive craft and architecture only found on the islands. One example was the development of elaborate mortuary structures, such as the Xagra circle, Gozo. This monumentalized underground tomb yielded the remains of hundreds of individuals and underwent remodelling and enlargement until around 2500 BC when it was abandoned, possibly as part of a wider population decline or replacement.

To examine the demography of Late Neolithic Malta, scientists sequenced genomes from this burial site. The elucidation of fine structure among closely related groups such as European Neolithic populations is challenging, and requires a fine scale genetic analysis. Therefore, to examine these in a wider context, the team additionally imputed genome wide diploid genotypes from published ancient genomes and assessed long chunks of genomes shared within and between genomes to estimate genetic geography and demographies across Neolithic Europe.

A high resolution picture of the genetic background of ancient human populations allowed scholars to unveil their history, relatedness and migration. For example, it was discovered that ancient Neolithic people from Malta experienced an unusual drop in their size perhaps because of external factors such as the deterioration of the local environment and economy. Moreover, the genetic structure of modern human populations in Europe was mostly already present in the ancient communities that lived thousands of years ago. This discovery will surely open new questions about seafaring in ancient times.

Bruno Ariano, PhD student at Trinity College Dublin, now also Senior Bioinformatician at Open Target and first author of the study said:

"Was the sea a barrier or a highway in connecting regions during ancient times? Our research shows that seafaring increased the differentiation between populations from islands and mainland Europe. Thanks to the analysis of hundreds of ancient genomes we discovered a level of structure among populations that correlates with their geographic location. This unprecedented level of resolution will most likely lead to new theories about migration and seafaring."

Caroline Malone, Professor of Prehistory, School of Natural and Built Environment, Queens University Belfast and co-author, said:

The builders of the temples of prehistoric Malta showed enormous resilience and creativity for over a thousand years, as confirmed by a detailed dating programme at Queens Belfast. The new biological evidence demonstrates that they were also challenged by the maritime distance of their island home.

Simon Stoddart, Professor of Prehistory, Department of Archaeology, University of Cambridge, and co-author said:

"For the first time, we have a scientific understanding of the scale of prehistoric society in Malta. These results suggest that small communities were closely associated with the guardianship of the famous temples"

Funding for this research came from, the Wellcome Trust, Science Foundation Ireland, Health Research Board and the European Research Council (FRAGSUS Advanced grant).

You can read a full copy of the paper: Ancient Maltese genomes and the genetic

geography of Neolithic Europe, in the journal Current Biology, here: https://www.cell.com/current-biology/fulltext/S0960-9822(22)00705-9

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Scientists reveal how seascapes of the ancient world shaped genetic structure of European populations - EurekAlert