Monthly Archives: May 2023

PRESS RELEASE

Published May 4, 2023

The global Digital Genome Market was valued at USD 28.2 Billion in 2022 and it is anticipated to grow up to USD 64.6 Billion by 2032, at a CAGR of 8.6% during the forecast period.

Deep learning is a subset of machine learning in artificial intelligence (AI) that has networks capable of learning unsupervised from data that is unstructured or unlabeled. Also known as deep neural learning or deep neural networks (DNNs), deep learning models are neural networks (algorithms used to simulate the workings of the human brain in order to recognize patterns) that can learn and make predictions on their own by analyzing data, finding patterns, and making decisions.

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Market Trends and Drivers

Surge in adoption of precision medicine will remain a key growth driver

The demand for digital genome is rapidly gaining popularity owing to continuous reduction in the cost and time required. The sequencing is widely used in the field of oncology, reproductive health and genetics. As a result, firms such as Illumina, Thermo Fisher and Qiagen are developing new innovative technologies in the field of genomics. Digital genomics market will further grow as rising application of sequencing in diagnosis of genetic disorders such as Duchenne Muscular Dystrophy, Fragile X syndrome and FAM Hypercholesterolemia etc. Advent of new technology coupled with rising demand of precision medicines will escalate market over forecast period. The major factors limiting the growth of digital genome market is lack of awareness regarding the digital genome, security & privacy of patient data, and incorrect results. In addition, lack of trained staff for digital genome in various developing economies will further impede the industry growth.

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Global Digital Genome Market Segmentation

By Product

By Application

By End-user

Major Players in the Global Digital Genome Market

The key players in the Digital Genome Market Agilent Technologies, Inc., Becton Dickinson, Pacific Biosciences, Perkin Elmer, Sigma Aldrich and Thermo Fisher, among others.

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Digital Genome Market is expand at a CAGR of 8.6% to reach USD ... - Digital Journal

The goal of the program is not only to make base editing accessible to high school students, but also to encourage critical thinking and reflect on base editing in social and cultural contexts. Komors team asked students to think about the difference between a disease and a trait and to consider the implications of germline genome editing, in which edits are inherited by all future descendants of the edited individual, regardless of whether those descendants consent to the procedure.

The ethical discussion is what hits a home run with the students, said Vasquez. Theyll be responsible for future gene-editing policies. Its interesting to see them thinking about the ethical side of science.

Weve had some really good discussions about what is a disease and what is a trait, stated Evanoff. If we have the ability to make genetic-disease corrections, who will be able to afford those treatments? Where does the equitability lie in this technology? We don't have the answers to that. I say to students, That's going to be your job to figure out!

This research was supported by the National Science Foundation (MCB-2048207), the National Institute of General Medical Sciences (T32 GM007240-41), the National Institute of Health (T32 GM112584), the Howard Hughes Medical Institute (GT13672 and the Gilliam Fellowship Program) and the National Academies of Sciences, Engineering, and Medicine Ford Foundation Predoctoral Fellowship Program.

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High School Students Learn the Basics of Base Editing to Cure GFP ... - University of California San Diego

Genome-wide association studies (GWAS) play a crucial role in medical research. By examining millions of genetic variants across the entire genome in large populations, these studies can identify genetic variations that contribute to a particular disease or trait. GWAS have already led to breakthroughs in disease prevention, personalised medicine and drug development.

However, Dr Denis Bauer, who leads the Transformational Bioinformatics Group at the Commonwealth Scientific and Industrial Research Organisation (CSIRO), notes that traditional GWAS evaluate disease association for each genomic location individually, which can be limiting for complex diseases.

These diseases, such as dementia, represent the largest burden on the healthcare system and involve genes that interact with each other to create disease risk, she explains.

Statistical models struggle to evaluate the joint contribution of variants across the genome. So other common approaches compromise by investigating interactions between locations that have already shown association with the disease. Unfortunately, this approach runs the risk of not including the real drivers of disease that may have no effect individually but jointly contribute to disease development.

This limitation in traditional GWAS is one of the main reasons CSIRO created VariantSpark. The scalable machine learning framework, which recently became available on Microsofts Azure Marketplace. VariantSpark enables researchers to quickly and accurately analyse high-dimensional genomic data data sets with a large number of variables to find novel disease genes or predictive biomarkers.

In complex diseases, we are hunting very subtle signals, which means we need very large data sets to make robust statements, says Dr Bauer. VariantSpark can scale to mega-biobanks with millions of samples and is 90 per cent faster than traditional compute frameworks.

This puts researchers on the right track for finding evidence of epistasis, the non-additive gene-gene interactions that are postulated to drive complex diseases. It also boosts their ability to find predictive biomarkers that allow disease to be diagnosed early to potentially stop or delay progression.

Another reason CSIRO created VariantSpark was to help its research collaborators analyse their increasingly large and complex genomic data sets.

We were involved in analysing a cohort of several thousand individuals, and all the other tools failed on the size. So we either needed to compromise by analysing only a subset of the data, or innovate, says Dr Bauer.

We wanted to make VariantSpark publicly available because if we have problems processing large volumes of data or deeply interrogating complex cohorts, a lot of other researchers probably have that problem too.

While VariantSpark can scale to handle large and complex data sets, Dr Bauer notes that the solution also caters to researchers with smaller volumes of data.

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Genomic researchers gain access to CSIRO's AI-powered data ... - Microsoft

Machine-learning-based prediction of splicing in extinct hominin species highlights the effect of natural selection on splice-altering variants and reveals phenotypic differences with modern humans.

The sequencing of the genomes of archaic hominins has fostered a renewed interest in the identity of our extinct relatives and their legacy in the genome of modern humans. However, characterization of the phenotypes of archaic hominins is limited by the scarcity of remains and the rapid degradation of soft tissues after death. Various attempts have been made to infer archaic phenotypes on the basis of their DNA methylation patterns1 or through the study of the regulatory alleles that they share with modern humans2. Yet, the extensive purge of archaic DNA from the genome of modern humans3 and the possibility of regulatory divergence between archaic and modern humans4 limit the effectiveness of these approaches. Writing in Nature Ecology & Evolution, Brand et al.5 implemented a solution to this issue by focusing on alternative splicing, which informs us on the phenotypes of archaic hominins and reveals how splice-altering variants (SAVs) that modern humans inherited from their archaic relatives helped them to adapt to their environment, but also contributed to disease (Fig. 1).

a, Brand et al. infer genetic differences between modern humans and four lineages of archaic hominin. b, They evaluate the effect on splicing of thousands of archaic alleles and show an increased deleteriousness of SAVs that are specific to one or more archaic lineages relative to those that are shared with modern humans. c,d, They further overlap these SAVs with disease genes to reveal specific traits of archaic humans (c) and explore the effect of introgressed SAVs on human phenotypes and adaptation to environmental pressures (d). Created with BioRender.com.

Alternative splicing the process by which exons of a gene are joined in different combinations to form alternative mRNA molecules is a major contributor to the heritability of complex traits, on a par with variants that affect gene expression levels6. Because molecular mechanisms that underlie alternative splicing are deeply conserved across eukaryotes7, Brand et al. reasoned that the same rules should govern alternative splicing in modern humans and archaic hominins. They used a deep-learning algorithm known as SpliceAI8 to predict allele-specific effects on splicing at more than 1.5 million loci that differ between modern humans and four archaic hominins (three Neanderthals and one Denisovan). The authors identified thousands of SAVs present in archaic hominins, of which 37% are specific to these hominins (referred to as archaic-specific SAVs). The remainder included both ancient alleles that predate the split between modern humans and their archaic relatives and have survived in modern humans to this day (59%) (referred to as ancient SAVs), as well as alleles of archaic origin that were introgressed into modern humans through admixture (4%) (referred to as introgressed SAVs).

The authors showed that archaic alleles that are specific to a single lineage (for example, specific to the Neanderthals from Vindija Cave) are enriched for SAVs compared to archaic alleles that are shared across multiple lineages of archaic hominin. This result, which they attribute to the purging of SAVs that appeared early in archaic hominin evolution, is consistent with SAVs being more frequently found within Neanderthal lineages. Indeed, Neanderthals had a smaller effective population size relative to Denisovans and natural selection was thus less efficient at purging deleterious alleles from their genomes. Brand et al. further showed that archaic-specific SAVs are more likely than ancient SAVs to alter conserved sites and disrupt protein function. Finally, the authors analysed the phenotypic effect of the genetic burden carried by our late archaic relatives, by intersecting archaic-specific SAVs with known disease genes (identified by genome-wide association studies or associated with rare Mendelian disorders). In doing so, they pinpointed the specific phenotypes that are associated with SAV-containing genes in each archaic lineage, such as fragile skin in Neanderthals or muscular abnormalities in Denisovans.

Next, Brand et al. focused on SAVs that were introgressed in modern humans. The authors found that introgressed SAVs are enriched near genes that are expressed in a tissue-specific manner and show that the vast majority of SAVs observed in humans today are older than the split between Denisovans and Neanderthals. These results suggest that natural selection purged more-recent SAVs from human genomes shortly after their introgression, leaving only SAVs with more-localized effects on gene expression. Yet, the authors further showed that introgressed SAVs are enriched near susceptibility genes for several phenotypes, including hay fever and allergies, Helicobacter pylori serological status or systemic sclerosis, which suggests that SAVs inherited from archaic hominins still contribute to disease today.

Finally, the authors explored how SAVs that modern humans inherited from their archaic relatives helped them to adapt to their environment. In addition to previously described SAVs associated with COVID-19 susceptibility at the OAS1 locus and rhinitis at the TLR1 locus, the authors report SAVs at the EPAS1 locus, where an Denisovan-introgressed haplotype has contributed to the adaptation of Tibetan peoples to high altitudes9. The reported SAV leads to nonsense-mediated decay of EPAS1 and correlates with lower haemoglobin levels in Tibetan individuals10, consistent with the positive effect of EPAS1 on altitude-induced erythropoiesis11. At the ERAP2 locus, the authors identify three introgressed SAVs of potential evolutionary importance. First, they identify an ancient SAV evolving under balancing selection that is associated with stimulation-induced splicing of ERAP212 and increased survival during the Black Death13. In addition, they report two Neanderthal-specific SAVs of unknown functional relevance, one of which is predicted to induce nonsense-mediated decay of ERAP2. Together, these results highlight how SAVs inherited from archaic hominins have contributed to human adaptation.

The work presented by Brand et al. shows us how the prediction of molecular phenotypes from DNA sequence8 can teach us about extinct species and their effect on the evolutionary history of their living relatives. Yet, it also has some limitations. First, it relies heavily on the accuracy of the underlying predictions. Its conclusions could thus suffer from the poor performance of current prediction methods when applied to deep intronic variants and distal enhancers. Second, Brand et al. only consider variants with a widespread effect on splicing. Yet, context-specific splicing has been shown to have an essential role in the development of the brain and testis14 and may have had a role in the purging of archaic variants observed in these tissues4. Although the general splicing machinery is extremely conserved, such dynamic and tissue-specific splicing may be much more variable across species, which may complicate the portability of predictions across hominins. More-accurate models powered by massively parallel splicing assays15 and the mapping of splice quantitative trait loci6 are needed to embrace the complexity of such context-specific splicing. Finally, structural variants (for example, insertions and/or deletions) and variants located on sex chromosomes have so far been left aside, despite their relevance for human phenotypes and hybrid infertility. Future efforts must assess the role of these variants in the purge of archaic alleles from modern human genomes.

The work of Brand et al. is a powerful proof of concept that lays the foundations for future studies that aim to resurrect the alternative splicing landscape of extinct species.

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Archaic hominin traits through the splicing lens - Nature.com

A critical vulnerability, with the highest possible CVSS score of 10, was discovered in Illumina's genome sequencing tool that allows an adversary to remotely upload and execution code on targeted systems.

The Cybersecurity and Infrastructure Security Agency (CISA) and the Food and Drug Administration (FDA) both issued alerts urging network admin to apply available patches.

The Cybersecurity and Infrastructure Security Agency (CISA) and the Food and Drug Administration (FDA) both issued alerts urging network admin to apply available patches. The bug was found in Illumina's Universal Copy Service function. According to researchers, the bug (CVE-2023-1968) can be exploited remotely and is easy to trigger with a "low attack complexity."

The CVE carries a CVSS v3 score: 10.0 is one of two bugs found within the platform. The second bug, tracked as CVE-2023-1966, carries a CVSS v3 score of7.4 and considered a high risk.

"Successful exploitation of these vulnerabilities could allow an attacker to take any action at the operating system level. A threat actor could impact settings, configurations, software, or data on the affected product; a threat actor could interact through the affected product via a connected network," according to the CISA alert.

The two bugs are a binding to an unrestricted IP address flaw and an execution with unnecessary privileges and found in versions of iScan Control Software, iSeq 100, MiniSeq, MiSeqDX, NextSeq, and NovaSeq products. These tools perform various next-gen sequencing, as well as bioinformatics.

According to the FDA, these are medical devices for either research use or clinical diagnostic use for the sequencing of individuals DNA for genetic conditions.

The critical flaws are tied to the universal copy service function v2.x of the platform, which copies the sequencing output files from the devices run folder to the output folder. However, its bound to an unrestricted IP address, which could allow an unauthenticated attacker to use the UCS to listen on all IP addresses, including those that accept remote communications.

Meanwhile, the unnecessary privileges vulnerability ranked 7.4 in severity is found in instruments leveraging both v1.x and v2.x platforms. The flaw could enable an unauthenticated threat actor to remotely upload and execute code at the operating system level, allow them to change settings, configurations and software, or even access sensitive information.

The FDA warns an attacker would not need to gain credentials to remotely deploy malicious activities, including the possible alteration of data contained on both the instrument or customers networks. An exploit could also impact the result of genetic data contained on the instruments, leading the instruments to provide no results, incorrect results, altered results, or a potential data breach.

At this time, the FDA and Illumina have not received any reports indicating this vulnerability has been exploited, according to the alert.

Illumina reported the vulnerability to CISA and created guidance for system users based on specific configurations to mitigate the impact. The company has already developed a software patch to protect against exploit.

The FDA is urging providers and laboratory personnel to be aware of the required actions to mitigate these cybersecurity risks. For many of the impacted devices, configuration is recommended for the UCS account credentials, while other systems software will need to be updated.

Illumina also created instructional videos for clients, which is protected from external access by the use of credentials. The company directly sent notices about the vulnerabilities to users earlier this month, urging them to look out for signs of exploit on the impacted devices.

Fortunately, there have been no public exploits reported targeting these flaws. But as that can quickly change given the state of the threat landscape, CISA recommends network defenders take defensive measures to minimize the risk of exploit, including minimizing the exposure for all control systems and devices and preventing access from the internet.

Virtual Private Networks should be used when remote access is required or another secure method. But VPNs come with their own vulnerabilities, so defenders should ensure the tools are updated to the most current version to reduce possible risks.

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Critical bug in genome sequencing device scores '10' on CVSS ratings - SC Media

All human beings are genetically very similar, sharing approx. 99.9% of the DNA code. The remaining 0.1% explains the natural differences between people, including our predisposition to hereditary diseases. Although sequencing of our genetic material is becoming a routine diagnostic analysis, it is unfortunately far from simple to determine whether specific small differences in our DNA affect our risk of developing disease. The usefulness of DNA sequencing is therefore often limited to the few cases where it is already known if a gene variant increases the risk of disease.

Researchers at the Department of Biology, University of Copenhagen, have now contributed to solving this problem for a specific gene calledGCK. The study has just been published inGenome Biology.

Rasmus Hartmann-Petersen, Professor at the Department of Biology, explains:

- TheGCKgene, which codes for the enzyme glucokinase, regulates the secretion of insulin in the pancreas.GCKgene variants can therefore cause a form of hereditary diabetes. Although the connection betweenGCKand diabetes has been known for several years, we have, until now, only known the effect of a few percent of the possible variants of this gene.

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Together with colleagues at the PRISM centre, UCPH, who are currently studying the effects of genetic variations, the researchers measured the effect of all of the possible variants ofGCK.

PhD student Sarah Gersing, who is the first author of the article, explains:

- We used yeast cells to measure the activity of over 9000 differentGCKvariants. In this way, we were able to generate a list of the effects both of already known variants, but also of variants that patients might carry, but that have not yet been discovered. This provides us with a reference for futureGCKdiagnostics.

Prof. Kresten Lindorff-Larsen, who heads the PRISM centre, continues:

- Our results are quite unique; not only have we measured the effect of several thousand variants, but for many of the variants, we can now explain what they do to the glucokinase protein. In our centre, we have gathered researchers working across a range of research fields, bridging from data analysis and biophysics to cell biology and medicine, and it is now clear how this broad approach pays off in explaining how diseases arise.

Gene variants ofGCKcan, among other things, cause a form of hereditary diabetes called "GCK maturity onset diabetes of the young" (GCK-MODY).

Professor of genetics, dr. med. Torben Hansen, who is also a member of the PRISM centre, says: - "Although GCK-MODY patients exhibit elevated blood glucose levels, this is often not associated with complications. Hence, unlike other forms of diabetes, most GCK-MODY patients might therefore not need to be treated with medication. However, due to missing or inaccurate genetic data, more than half of the GCK-MODY patients are classified with having either type 1 or type 2 diabetes and are therefore unnecessarily medicated. We estimate that approx. 1% of those who have recently been diagnosed with type 2 diabetes in Denmark have a variant in theGCKgene, meaning that they dont need treatment, or need to be treated differently. Our new map ofGCKvariants can hopefully help give these patients a more correct diagnosis.

The next step for PRISM is to transfer these methods to other genes and diseases.

- "We are already well underway with genes involved in e.g., neurodegenerative diseases, and we are trying to develop precise methods that can provide us with insights on disease mechanisms", says Rasmus Hartmann-Petersen.

Kresten Lindorff-Larsen continues:

- "Our data gives us the opportunity to test and develop computational models for variant effects, which will then be transferable to other genes and diseases."

- Now, we have measured the effects of almost all variants ofGCK, giving us knowledge on which variants that function, and which that do not. The next step is to understand why, and how the same underlying molecular mechanisms can give rise to a wide range of different diseases", concludes Sarah Gersing.

Reference:Gersing S, Cagiada M, Gebbia M, et al. A comprehensive map of human glucokinase variant activity. Genome Biol. 2023;24(1):97. doi:10.1186/s13059-023-02935-8

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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Novel Genomic Approach Ensures Better Diagnosis of Hereditary ... - Technology Networks

Intellia Therapeutics: Revolutionary Genome Editing Techniques

Intellia Therapeutics (NASDAQ:NTLA), the clinical stage genome editing company, is all set to release its quarterly earnings data before the market opens on Thursday, May 4th. This Boston-based biotech firm engages in developing curative therapeutics that fix disease-associated genes with a single treatment.

What sets Intellia apart from others in the field is their revolutionary CRISPR/Cas9 system. Using a highly advanced gene editing technology, Intellia creates engineered cells, which help treat oncological and immunological diseases. The capability of CRISPR/Cas to permanently edit or correct disease-associated genes apply to patients for their lifetime, requiring no repeated dosing.

BMO Capital Markets upgraded Intellia from a market perform rating to an outperform rating and raised their price target for the company from $54.00 to $57.00 in March of 2017. Notably, William Blair restated an outperform rating on shares of Intellia in late March. As per reports, Wells Fargo & Company lowered Intellias price target from $135.00 to $120.00 and set an overweight rating on the stock in early January of this year.

Citigroup also provided support by upgrading Intellia from a sell rating to a neutral rating while dropping its price target for the firm from $48.00 to $39.00 in late January 2017. Finally, Oppenheimer decreased its price target on NTLA from $115.00 to $93.00 but gave it an outperform rating in late February based on current economic growth indicators.

All told, one equities research analyst gave the stock a sell-rating while three have issued hold ratings throughout 2016-17 period when these analyses were conducted by various firms. Overall, sixteen analysts rated the stock as buy. Data from Bloomberg reveals its consensus target price is $85.67 and the consensus rating is Moderate Buy.

Intellias gene-editing techniques have several utilities in healthcare, including basic research in genetics, cell-line engineering for producing beneficial proteins, development of advanced gene therapies and improving agriculture for food production.

We look forward to Intellias earnings data later this week to inform us further as to how very clear evidence suggests a burgeoning realm of opportunities.

Intellia Therapeutics Inc.s latest earnings report released on February 23rd, 2021, showed a quarter full of ups and downs for the biotechnology company. The report revealed that Intellia posted ($1.40) per share earnings for Q4, meeting the consensus estimate of ($1.40), while accumulating an impressive revenue of $13.60 million compared to analysts expectations of $10.71 million.

Despite Q4s net profit taking a hit as evidenced by the negative return on equity of 48.70%, Intellia realized an increase in revenue by 5.4% from the same quarter in the previous year. This is remarkable given that the previous years net earnings per share were ($1.09).

Analysts have projected that IntelliTherapeutics is set to buck up its operations with losses predicted to stand at $6 EPS both for this fiscal year and the next one to follow yet to come.

For investors interested in dabbling in this firm, at-$36.29 trading price within NASDAQ exchange rates located today, hovering between lowest and highest markers of $32.44 and $76.45 respectively within its 52-week game plan a market capitalization valuation of $3.20 billion is priced into NTLA stock.

Investment experts at Atria Wealth Solutions Inc., Canada Pension Plan Investment Board, Dynamic Technology Lab Private Ltd, Glenmede Trust Co-NA and First Republic Investment Management Inc have added new stakes totaling about $1,404 million some few years ago.

Nonetheless, Intellia Therapeutics has left investors starved since unrelenting market forces have weighed aggressively on their shares over time may probably need strategic repackaging efforts to fix their brands appeal amongst institutional clients? Time will tell if these sneaky tweaks will lead NTLA on a better path towards profitability soon enough!

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Intellia Therapeutics: Leading the Way in Revolutionary Genome ... - Best Stocks

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