Category Archives: Genome

The release of the draft human genome sequence in 2001 was a seismic moment in our understanding of the human genome, and paved the way for advances in our understanding of the genomic basis of human biology and disease.

But sections were left unsequenced, and some sequence information was incorrect. Now, two decades later, we have a much more complete version, published as a preprint (which is yet to undergo peer review) by an international consortium of researchers.

Technological limitations meant the original draft human genome sequence covered just the euchromatic portion of the genome the 92% of our genome where most genes are found, and which is most active in making gene products such as RNA and proteins.

The newly updated sequence fills in most of the remaining gaps, providing the full 3.055 billion base pairs (letters) of our DNA code in its entirety. This data has been made publicly available, in the hope other researchers will use it to further their research.

Much of the newly sequenced material is the heterochromatic part of the genome, which is more tightly packed than the euchromatic genome and contains many highly repetitive sequences that are very challenging to read accurately.

These regions were once thought not to contain any important genetic information but they are now known to contain genes that are involved in fundamentally important processes such as the formation of organs during embryonic development. Among the 200 million newly sequenced base pairs are an estimated 115 genes predicted to be involved in producing proteins.

Read more: Explainer: what is the Human Genome Project?

Two key factors made the completion of the human genome possible:

1. Choosing a very special cell type

The newly published genome sequence was created using human cells derived from a very rare type of tissue called a complete hydatidiform mole, which occurs when a fertilised egg loses all the genetic material contributed to it by the mother.

Most cells contain two copies of each chromosome, one from each parent and each parents chromosome contributing a different DNA sequence. A cell from a complete hydatidiform mole has two copies of the fathers chromosomes only, and the genetic sequence of each pair of chromosomes is identical. This makes the full genome sequence much easier to piece together.

2. Advances in sequencing technology

After decades of glacial progress, the Human Genome Project achieved its 2001 breakthrough by pioneering a method called shotgun sequencing, which involved breaking the genome into very small fragments of about 200 base pairs, cloning them inside bacteria, deciphering their sequences, and then piecing them back together like a giant jigsaw.

This was the main reason the original draft covered only the euchromatic regions of the genome only these regions could be reliably sequenced using this method.

The latest sequence was deduced using two complementary new DNA-sequencing technologies. One was developed by PacBio, and allows longer DNA fragments to be sequenced with very high accuracy. The second, developed by Oxford Nanopore, produces ultra-long stretches of continuous DNA sequence. These new technologies allows the jigsaw pieces to be thousands or even millions of base pairs long, making it easier to assemble.

The new information has the potential to advance our understanding of human biology including how chromosomes function and maintain their structure. It is also going to improve our understanding of genetic conditions such as Down syndrome that have an underlying chromosomal abnormality.

Well, no. An obvious omission is the Y chromosome, because the complete hydatidiform mole cells used to compile this sequence contained two identical copies of the X chromosome. However, this work is underway and the researchers anticipate their method can also accurately sequence the Y chromosome, despite it having highly repetitive sequences.

Even though sequencing the (almost) complete genome of a human cell is an extremely impressive landmark, it is just one of several crucial steps towards fully understanding humans genetic diversity.

Read more: How much junk is in our DNA?

The next job will be to study the genomes of diverse populations (the complete hydatidiform mole cells were European). Once the new technology has matured sufficiently to be used routinely to sequence many different human genomes, from different populations, it will be better positioned to make a more significant impact on our understanding of human history, biology and health.

Both care and technological development are needed to ensure this research is conducted with a full understanding of the diversity of the human genome to prevent exacerbation of health disparities by limiting discoveries to specific populations.

Read more from the original source:
Why it took 20 years to 'finish' the human genome and why there's still more to do - The Conversation AU

By Melissa Southey, Monash University and Tu Nguyen-Dumont, Monash University

The release of the draft human genome sequence in 2001 was a seismic moment in our understanding of the human genome, and paved the way for advances in our understanding of the genomic basis of human biology and disease.

But sections were left unsequenced, and some sequence information was incorrect. Now, two decades later, we have a much more complete version, published as a preprint (which is yet to undergo peer review) by an international consortium of researchers.

Technological limitations meant the original draft human genome sequence covered just the euchromatic portion of the genome the 92% of our genome where most genes are found, and which is most active in making gene products such as RNA and proteins.

The newly updated sequence fills in most of the remaining gaps, providing the full 3.055 billion base pairs (letters) of our DNA code in its entirety. This data has been made publicly available, in the hope other researchers will use it to further their research.

Much of the newly sequenced material is the heterochromatic part of the genome, which is more tightly packed than the euchromatic genome and contains many highly repetitive sequences that are very challenging to read accurately.

These regions were once thought not to contain any important genetic information but they are now known to contain genes that are involved in fundamentally important processes such as the formation of organs during embryonic development. Among the 200 million newly sequenced base pairs are an estimated 115 genes predicted to be involved in producing proteins.

Read more: Explainer: what is the Human Genome Project?

Two key factors made the completion of the human genome possible:

The newly published genome sequence was created using human cells derived from a very rare type of tissue called a complete hydatidiform mole, which occurs when a fertilised egg loses all the genetic material contributed to it by the mother.

Most cells contain two copies of each chromosome, one from each parent and each parents chromosome contributing a different DNA sequence. A cell from a complete hydatidiform mole has two copies of the fathers chromosomes only, and the genetic sequence of each pair of chromosomes is identical. This makes the full genome sequence much easier to piece together.

After decades of glacial progress, the Human Genome Project achieved its 2001 breakthrough by pioneering a method called shotgun sequencing, which involved breaking the genome into very small fragments of about 200 base pairs, cloning them inside bacteria, deciphering their sequences, and then piecing them back together like a giant jigsaw.

This was the main reason the original draft covered only the euchromatic regions of the genome only these regions could be reliably sequenced using this method.

The latest sequence was deduced using two complementary new DNA-sequencing technologies. One was developed by PacBio, and allows longer DNA fragments to be sequenced with very high accuracy. The second, developed by Oxford Nanopore, produces ultra-long stretches of continuous DNA sequence. These new technologies allows the jigsaw pieces to be thousands or even millions of base pairs long, making it easier to assemble.

The new information has the potential to advance our understanding of human biology including how chromosomes function and maintain their structure. It is also going to improve our understanding of genetic conditions such as Down syndrome that have an underlying chromosomal abnormality.

Well, no. An obvious omission is the Y chromosome, because the complete hydatidiform mole cells used to compile this sequence contained two identical copies of the X chromosome. However, this work is underway and the researchers anticipate their method can also accurately sequence the Y chromosome, despite it having highly repetitive sequences.

Even though sequencing the (almost) complete genome of a human cell is an extremely impressive landmark, it is just one of several crucial steps towards fully understanding humans genetic diversity.

The next job will be to study the genomes of diverse populations (the complete hydatidiform mole cells were European). Once the new technology has matured sufficiently to be used routinely to sequence many different human genomes, from different populations, it will be better positioned to make a more significant impact on our understanding of human history, biology and health.

Both care and technological development are needed to ensure this research is conducted with a full understanding of the diversity of the human genome to prevent exacerbation of health disparities by limiting discoveries to specific populations.

Melissa Southey, Chair Precision Medicine, Monash University and Tu Nguyen-Dumont, Senior research fellow, Monash University

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

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Why it took 20 years to finish the human genome - Cosmos Magazine

Genomic surveillance allows researchers to examine the genome sequence of the viral strains infecting the population.

The genome of the SARS-CoV-2 virus is composed of Ribonucleic Acid or RNA, a single strand of 30,000 units (called bases) that make up all its genes.

The genome of the SARS-CoV-2 virus is composed of Ribonucleic Acid or RNA, a single strand of 30,000 units (called bases) that make up all its genes. As the virus multiplies inside human cells, it needs to copy its genome to make more viral particles, a process called replication. Copying errors are sometimes introduced in this process because the enzyme that copies the RNA is error-prone. These copying errors introduce mutations or changes to the genomic sequence. The changes alter the viral genes, leading to a change in the viral proteins encoded by them.

While most of these changes are either of no consequence or harmful to the virus itself and, therefore, dont get noticed, some of these changes can have biological effects in terms of affecting the infectivity, transmission and/or other features of the virus that are governed by the viral proteins. Thus, though mutations arise in the normal course of viral replication, they can then get selected for their beneficial properties to the virus. The only means of replication available to a virus is inside its human host, therefore, higher disease spread and increasing infections provide greater avenues for the viral genome to develop multiple mutations and their combinations, that are known as variants. Over the past year and a half of the pandemic, SARS-CoV-2 has been accumulating mutations at the rate of ~2 changes per month.

Continuous monitoring of viral genome variations is very useful in tracing the path of the spread of the disease. Such information can be very useful in containment measures and strategies. Mutations can also influence the course of the pandemic, by altering the properties of the virus and generating new variants. A Variant of Interest' (VOI) has one or more mutations that are believed to have biological consequences, such as increased transmission or have been observed in other lineages with detrimental effects. If further assessment predicts or documents the role of a particular VOI in decreasing effectiveness of current measures, for example, evidence for increased transmission, virulence or immune escape, it becomes a Variant of Concern (VOC) and is closely monitored. With vaccinations now being undertaken in many countries, mutations conferring immune escape are of particular concern. This is the phenomenon by which the virus acquires the ability to bypass host immunity that has been either acquired by a previous SARS-CoV-2 infection, or conferred by vaccination.

Genomic surveillance allows researchers to examine the genome sequence of the viral strains infecting the population. We can thus track the effects of emerging mutations by sequencing the viral genomes and associating new changes with significant differences in viral circulation trends. Carrying out genomic surveillance in a populous country like India requires rapid and temporal sequencing of viral genomes across multiple states in order to identify potential concerns and mitigate the spread of the virus. For this purpose, the Indian SARS-CoV-2 Genome Sequencing Consortia (INSACOG) was formed towards the end of 2020 with the aim of sequencing a fraction of positive cases to follow the emergence of variants, etc. The viral genome sequences are deposited in a global public database called Global Initiative on Sharing All Influenza Data (GISAID) to enable data-sharing among researchers for analysis.

India has constituted a lab network of academic institutions under the INSACOG, to expand genomic surveillance across the country. CSIR-CCMB (Centre for Cellular and Molecular Biology) is a partner institute in this initiative and has been spearheading the COVID-19 testing and sequencing of viral samples from infected cases, especially across Telangana and Andhra Pradesh. We have sequenced ~4000 viral genomes and analyzed viral variants circulating across the country to follow emergent mutation trends. The sequences and mutations analysis are hosted on an interactive dashboard, GEAR-19 (Genome Evolution Analysis Resource for COVID-19 ), with an easy graphical user interface so that the data is publicly available to researchers across the country and the globe.

Also read:Variant, strain and mutation of SARS-CoV-2 all mean different things

GISAID currently hosts 18,73,981 SARS-CoV-2 genome sequences globally. Approximately 20,000 sequences of viral genomes isolated from Indian patients are currently available on GISAID, with INSACOG having submitted ~13,000 sequences in the last five months since its inception. This has been possible due to the large network developed with major hospitals and COVID testing centres as well as state governments over the last year of the pandemic, for access to patient samples and epidemiological data. However, given the countrys population and COVID-19 case burden, the number of sequences available for the country remains disproportionately low, and insights available from existing efforts need to be sharpened to keep pace with the rapidly evolving situation. We are now incorporating further measures to upscale genomic surveillance programmes across the country by ramping up sequencing efforts, bioinformatics and data sharing, especially from rural setting and areas affected more in the second wave of COVID-19 .

One thing that has emerged during this pandemic is the use of sophisticated techniques to address crucial questions related to epidemiology and dynamics of this disease. Diagnostics that was costing about Rs 4,000 per test is now available at under Rs 200 per test. We are able to track the level of infection in the population from the sewage sample. These are so cheap and effective that future surveillance is going to be of much greater effectiveness. Genomics is going to be the very basic tool for handling of not only infectious diseases but also for personalized and precision medicine. India should develop and indigenize its genome sequencing capabilities over the next 2-3 years, given that we may have to live with epidemics and pandemics on a more regular basis. Such capabilities and surveillance will be crucial in pre-empting the catastrophes and reducing the damage.

Surabhi Srivastava is the Research Coordinator for Genomics and Bioinformatics. Rakesh K Mishra is the former director and current Advisor for COVID-19 efforts at the CSIR-Centre for Cellular and Molecular Biology, Hyderabad.

Excerpt from:
Explainer: What is genome sequencing and surveillance? Why is it important? - Firstpost

Melbourne, Jun 10 (The Conversation) The release of the draft human genome sequence in 2001 was a seismic moment in our understanding of the human genome, and paved the way for advances in our understanding of the genomic basis of human biology and disease.

But sections were left unsequenced, and some sequence information was incorrect. Now, two decades later, we have a much more complete version, published as a preprint (which is yet to undergo peer review) by an international consortium of researchers.

Technological limitations meant the original draft human genome sequence covered just the euchromatic portion of the genome the 92% of our genome where most genes are found, and which is most active in making gene products such as RNA and proteins.

The newly updated sequence fills in most of the remaining gaps, providing the full 3.055 billion base pairs (letters) of our DNA code in its entirety. This data has been made publicly available, in the hope other researchers will use it to further their research.

Why did it take 20 years?

Much of the newly sequenced material is the heterochromatic part of the genome, which is more tightly packed than the euchromatic genome and contains many highly repetitive sequences that are very challenging to read accurately.

These regions were once thought not to contain any important genetic information but they are now known to contain genes that are involved in fundamentally important processes such as the formation of organs during embryonic development. Among the 200 million newly sequenced base pairs are an estimated 115 genes predicted to be involved in producing proteins.

Two key factors made the completion of the human genome possible:

1. Choosing a very special cell type

The newly published genome sequence was created using human cells derived from a very rare type of tissue called a complete hydatidiform mole, which occurs when a fertilised egg loses all the genetic material contributed to it by the mother.

Most cells contain two copies of each chromosome, one from each parent and each parent's chromosome contributing a different DNA sequence. A cell from a complete hydatidiform mole has two copies of the father's chromosomes only, and the genetic sequence of each pair of chromosomes is identical. This makes the full genome sequence much easier to piece together.

2. Advances in sequencing technology

After decades of glacial progress, the Human Genome Project achieved its 2001 breakthrough by pioneering a method called shotgun sequencing, which involved breaking the genome into very small fragments of about 200 base pairs, cloning them inside bacteria, deciphering their sequences, and then piecing them back together like a giant jigsaw.

This was the main reason the original draft covered only the euchromatic regions of the genome only these regions could be reliably sequenced using this method.

The latest sequence was deduced using two complementary new DNA-sequencing technologies. One was developed by PacBio, and allows longer DNA fragments to be sequenced with very high accuracy. The second, developed by Oxford Nanopore, produces ultra-long stretches of continuous DNA sequence. These new technologies allows the jigsaw pieces to be thousands or even millions of base pairs long, making it easier to assemble.

The new information has the potential to advance our understanding of human biology including how chromosomes function and maintain their structure. It is also going to improve our understanding of genetic conditions such as Down syndrome that have an underlying chromosomal abnormality.

Is the genome now completely sequenced?

Well, no. An obvious omission is the Y chromosome, because the complete hydatidiform mole cells used to compile this sequence contained two identical copies of the X chromosome. However, this work is underway and the researchers anticipate their method can also accurately sequence the Y chromosome, despite it having highly repetitive sequences.

Even though sequencing the (almost) complete genome of a human cell is an extremely impressive landmark, it is just one of several crucial steps towards fully understanding humans' genetic diversity.

The next job will be to study the genomes of diverse populations (the complete hydatidiform mole cells were European). Once the new technology has matured sufficiently to be used routinely to sequence many different human genomes, from different populations, it will be better positioned to make a more significant impact on our understanding of human history, biology and health.

Both care and technological development are needed to ensure this research is conducted with a full understanding of the diversity of the human genome to prevent exacerbation of health disparities by limiting discoveries to specific populations. (The Conversation)

(This is an unedited and auto-generated story from Syndicated News feed, LatestLY Staff may not have modified or edited the content body)

Originally posted here:
World News | Why It Took 20 Years to finish' the Human Genome and Why There's Still More to Do - LatestLY

This article was originally published here

Genomics Proteomics Bioinformatics. 2021 Jun 8:S1672-0229(21)00096-6. doi: 10.1016/j.gpb.2020.05.007. Online ahead of print.

ABSTRACT

Genomic studies of cancer cell alterations, such as mutations, copy number variations (CNVs), and translocations, greatly promote our understanding of the genesis and development of cancer. However, the 3D genome architecture of cancers remains less studied due to the complexity of cancer genomes and technical difficulties. To explore the 3D genome structure in clinical lung cancer, we performed Hi-C experiments using paired normal and tumor cells harvested from patients with lung cancer, combining with RNA-seq analysis. We demonstrated the feasibility of studying 3D genome of clinical lung cancer samples with a small number of cells (1 104), compared the genome architecture between clinical samples and cell lines of lung cancer, and identified conserved and changed spatial chromatin structures between normal and cancer samples. We also showed that Hi-C data can be used to infer CNVs and point mutations in cancer. By integrating those different types of cancer alterations, we showed significant associations between CNVs, 3D genome, and gene expression. We propose that 3D genome mediates the effects of cancer genomic alterations on gene expression through altering regulatory chromatin structures. Our study highlights the importance of analyzing 3D genomes of clinical cancer samples in addition to cancer cell lines and provides an integrative genomic analysis pipeline for future larger-scale studies in lung cancer and other cancers.

PMID:34116262 | DOI:10.1016/j.gpb.2020.05.007

More here:
Integrative Analysis of Genome, 3D Genome, and Transcriptome Alterations of Clinical Lung Cancer Samples - DocWire News

A spinout from the University of Oxford has found a new way to depict and analyze DNA with super-fine resolution, allowing them to peer into what they describe as the dark matter of the human genome and the molecular basis of many diseases.

Nucleome Therapeutics is working on a method known as micro-capture-C, or MCC, to provide a three-dimensional view of the famously twisting double-helix structure, with the ability to zoom in on individual base pairs.

Previous methods of determining the large-scale 3D genome structure within cells have been unable to resolve it much below 500 to 1,000 base pairs, said co-founder James Davies, who helped develop the technology at Oxfords MRC Weatherall Institute of Molecular Medicine alongside Danuta Jeziorska, who serves as Nucleomes CEO.

Nucleome plans to use its technique to identify the genes at play behind severe COVIDas well as find new drug targets for diseases such as rheumatoid arthritis and multiple sclerosiswith additional reports in the near future. Its latest work on 3D genome mapping was published this week in Nature.

RELATED: Google, Oxford study projects benefits to coronavirus-tracing smartphone apps, even at low levels of adoption

The researchers equate the process with looking at a citys skyline, representing the full strand of DNA within a cell. While before they could only make out the shape of small buildings from a distance, now they can see how its built up from individual brickswith all 6 billion of them representing a single letter of the genetic code.

3D genome analysis is key to understanding the largely untapped dark matter of the genome, Jeziorska said. Better resolution of 3D genome maps improves the accuracy and confidence of linking disease-relevant genetic changes to genes.

This could include the coronavirus pandemic and may help provide a better understanding of why some people require intensive care while others may show no symptoms at all.

RELATED: Oxford, Prenetics to take their COVID-19 rapid testing tech to other infectious diseases

For example, at the moment we know that there is a genetic variant which doubles the risk of being severely affected by COVID-19, Davies said. However, we do not know how the genetic variant makes people more vulnerable to COVID-19.

By providing a more detailed view into DNAs larger structure, drugs aimed at these genetic targets may have a better chance of making it through clinical trials, he added.

In the Nature publication, the researchers report that MCC could spot the physical interactions between gene-regulating proteins and the DNA code itself at base-pair resolutioneven though one targeted string may be controlled by genes located tens of thousands to millions of base pairs further along the chainor maybe a mile away, by bricks in a wall on the other side of the city.

Read more:
Oxford spinout spies the hidden mechanics of DNA and disease with single-pair resolution method - FierceBiotech

NEW YORK Quantum-Sisaid this week that it has completed itsplanned mergerwith special purpose acquisition firmHighCapeCapital Acquisition.

The business combination and private placement, approved byHighCape'sstockholders on June 9, provide the company with approximately $534 million in funding, prior to transaction fees, for further development and commercialization of its single-molecule, semiconductor chip-based protein sequencing and genomics technology. This includes approximately $109 millionincash held inHighCape'strust account and $425 million from private placementinvestors, includingForesiteCapital Management, Eldridge, accounts advised by ARK Invest, and Glenview Capital Management. Also, QSi's management team and existing stockholders have rolledall oftheir equity into the combined company.

Following the merger, thecombinedfirm was renamed Quantum-Si. Its Class A common stock and warrants will begin trading on the Nasdaq Global Market on June 11 under the symbols QSI and QSIAW, respectively. Former Quantum-Si stockholders exchanged their shares of capital stock for common stock of the combined company at an exchange ratio of 0.7975. Each share ofHighCapeClass A common stock and Class B common stock became one share of the combined company's Class A common stock.

The Translational Genomics Research Institute said this week that it has received a "substantial grant" from Taiwan Semiconductor Manufacturing to support SARS-CoV-2 variant tracking. Arizona-based TGen will use the funding to perform genomic sequencing of virus samples. The institute is under contract with the Arizona Department of Health Services and the Centers for Disease Control and Prevention to sequence samples from patients who have tested positive for SARS-CoV-2 in Arizona and to monitor for the emergence of mutations and variants. TSMC is building a chip manufacturing plant in north Phoenix that is expected to begin production in 2024.

The US Food and Drug Administration this week reissued a letter granting Emergency Use Authorization to the Yale School of Public Health for itsSalivaDirectSARS-CoV-2 test.

In its letter, the FDA authorized use of the test with additional thermocyclersABIStepOneReal-Time PCR System, ABI Prism 7000 Real-Time PCR System, ABIQuantStudioDx,UbiquitomeLiberty16, Roche Cobas Z480, and Analytik JenaqTower. Based on a post-authorization asymptomatic screening study, the agency also removed a limitation on serial testing for asymptomatic screening.

The FDAhadgranted EUAto Yale fortheSalivaDirecttestin August 2020.

OpGen announced this week that it has submitted an updated 510(k) summary document to the US Food and Drug Administration for its Acuitas AMR Gene Panel for Isolates. The updated document includes the agencys requested updates to documents such as the package insert, electronic user guide, and operator manual. The agency provided feedback on the documents by the end of May and told OpGen it intends to finish its review by August, but that it cant commit to a timeline. OpGen previously submitted its Acuitas panel to the FDAin May 2019,and the agency has twice requested more information.

ProPhase Labs this week announced the formation of two wholly owned subsidiaries, ProPhase Precision Medicine and ProPhase Global Healthcare. The precision medicine subsidiary will focus on genomic testing technologies and will look to acquire existing businesses and technologies or otherwise gain access to technologies used in whole-genome sequencing, the company said. The global healthcare business will expand the companys COVID-19 testing into other countries and will develop additional healthcare-related initiatives, ProPhase added. The company is also developing SARS-CoV-2 antigen and antibody tests to add to its offerings.

Yourgene said this week that it has entered into a license and supply agreement with an unnamed US precision medicine company for an initial term of three years, starting April 1, 2022. The agreement grants the precision medicine company a nonexclusive license to Yourgenes Flex Analysis Software and commits Yourgene to supplying sample preparation reagents and instrumentation to support the precision medicine companys planned launch of a new clinical reproductive health screening service across the US. The deal also allows for automatic annual renewals after the initial term. Financial terms werent disclosed.

India-based Core Diagnostics said this week that it has received accreditation from the College of American Pathologists for a range of tests, including cardiology, oncology, endocrinology, infectious diseases, gynecology, and nephrology. In the accreditation process, CAP inspectors examined the firm's clinical laboratory records and quality control procedures for the past two years. The inspectors also examined Core Diagnostics' laboratory staff qualifications, equipment, facilities, safety program and record, and overall management.

In Brief This Week is a selection of news items that may be of interest to our readers but had not previously appeared onGenomeWeb.

More:
In Brief This Week: Quantum-Si, TGen, Yale, and More - GenomeWeb

A species goes extinct when there are none of its kind left. In other words, extinction is about small numbers, so how does big data help us study extinction? Luckily for us, each individual of a species carries with it signatures of its past, information on how connected/ isolated it is today, and other information on what may predict its future, in its genome. The last fifteen years have witnessed a major change in how we can read genomes, and information from genomes of individuals and species can help better plan their conservation.

All life on Earth harbours genetic material. Often called the blueprint of life, this genetic material could be DNA or RNA. We all know what DNA is, but another way to think of DNA is as data. All mammals, for example harbour between 2 to 3.5 billion bits of data in every one of their cells. The entire string of DNA data is called the whole genome. Recent changes in technology allow us to read whole genomes. We read short 151 letter long information bits many, many times, and piece together the whole genome by comparing it to a known reference. This helps us figure out where each of these 151 letter long pieces go in the 3 billion letter long word. Once we have read each position on an average of 10 or 20 times, we can be confident about it. If each genome is sequenced even ten times and only ten individuals are sampled, for mammals each dataset would consist of 200 to 350 billion bits of data!

Over time, the genome changes because of mutation, or spelling errors that creep in. Such spelling errors create variation, or differences between individual genomes in a population (a set of animals or plants). Similarly, large populations with many individuals will hold a variety of spellings or high genetic variation. Since DNA is the genetic blueprint, changes in the environment can also get reflected in these DNA spellings, with individuals with certain words in their genome surviving better than others under certain conditions. Changes in population size often changes the variety of letters observed at a specific location in the genome, or variation at a specific genomic position. Migration or movement of animals into a population adds new letters and variation. Taking all these together, the history of a population can be understood by comparing the DNA sequences of individuals. The challenge lies in the fact that every population faces all of these effects: changes in population size, environmental selection, migration and mutation, all at once, and it is difficult to separate the effects of different factors. Here, the big data comes to the rescue.

Photo Credit: Dr Anubhab Khan

Genomic data has allowed us to understand how a population has been affected by changes in climate, and whether it has the necessary genomic variation to survive in the face of ongoing climate change. Or how specific human activities have impacted a population in the past. We can understand more about the origins of a population. How susceptible is a population to certain infections? Or whether the individuals in a population are related to each other. Some of these large datasets have helped identify if certain populations are identical and should be managed together or separately. All of these questions help in the management and conservation of a population.

We have worked on such big genomic datasets for tigers, and our research has helped us identify which populations of tigers have high genomic variation and are more connected to other populations. We have identified populations that are small and have low genomic variation, but also seem to have mis-spelled or badly spelled words, or a propensity of bad' mutations. We have identified unknown relationships between individuals within populations and have suggested strategies that could allow these isolated populations to recover their genomic variation. It has been amazing to peek into animals lives through these big data approaches, and we hope these types of genomic dataset will contribute to understanding how biodiversity can continue to survive on this Earth.

Uma Ramakrishnan is fascinated by unravelling the mysteries of nature using DNA as tool. Along with her lab colleagues, she has spent the last fifteen years studying endangered species in India.She hopes such understanding will contribute to their conservation. Uma is a professor at the National Centre for Biological Sciences.

Dr. Anubhab Khan is a wildlife genomics expert. He has researching genetics of small isolated populations for past several years and has created and analyzed large scale genome sequencing data of tigers, elephants and small cats among others. He keen about population genetics, wildlife conservation and genome sequencing technologies. He is passionate about ending technology disparity in the world by either making advanced technologies and expertise available or by developing techniques that are affordable and accessible to all.

This series is an initiative by the Nature Conservation Foundation (NCF), under their programme 'Nature Communications' to encourage nature content in all Indian languages. To know more about birds and nature, Join The Flock.

Read the original here:
What Does Big Data Have to Do With Wildlife Conservation? - Gadgets 360

The Genome Engineering Market research report provides detailed observation of several aspects, including the rate of growth, regional scope and recent developments by the primary market players. The report offers Porters Five Forces, PESTEL, and market analysis to provide a 360-degree research study on the global Genome Engineering market. The research study discusses about important market strategies, future plans, market share growth, and product portfolios of leading companies. The final report copy provides the impact analysis of novel COVID-19 pandemicon the Genome Engineering market as well as fluctuations during the forecast period.

Top Companies in the global Genome Engineering market areTransposagen Biopharmaceuticals, Inc. (U.S.), Genscript Biotech Corporation (U.S.), New England Biolabs, Inc. (U.S.), Sangamo Biosciences, Inc. (U.S.), Integrated DNA Technologies, Inc (U.S.), Merck KGAA (Germany), Horizon Discovery Group Plc (U.K.), Thermo Fisher Scientific, Inc. (U.S.), Origene Technologies, Inc. (U.S.), Lonza Group Ltd. (Switzerland) and Other.

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By types market is divided intoCRISPRTALENZFNAntisenseOther Technologies

By applications market is divided intoCell Line EngineeringAnimal Genetic EngineeringPlant Genetic EngineeringOther Applications

Regional Analysis:Asia-Pacific (China, India, Japan, South Korea, Australia, Indonesia, Malaysia, and Others), North America (United States, Canada, and Mexico), Central & South America (Brazil, and Rest of South America), Europe (Germany, France, UK, Italy, Russia, and Rest of Europe), Middle East & Africa (GCC Countries, Turkey, Egypt, South Africa and Other)

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The Genome Engineering market report highlights are A comprehensive evaluation of all opportunities and risks in the market. Genome Engineering market current developments and significant occasions. A deep study of business techniques for the development of the market-driving players. Conclusive study about the improvement plot of the market for approaching years. Top to bottom approach of market-express drivers, targets, and major littler scale markets.

Important Features that are under Offering and Key Highlights of the Reports: Potential and niche segments/regions exhibiting promising growth. Detailed overview of Market Changing market dynamics of the industry In-depth market segmentation by Type, Application, etc. Historical, current, and projected market size in terms of volume and value Recent industry trends and developments Competitive landscape of Market Strategies of key players and product offerings

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A potentially revolutionary step forward in biology which could lead to more reliable drug manufacture, new antibiotics or biodegradable plastics has been achieved at the MRC Laboratory of Molecular Biology in Cambridge.

Two years on from creating the biggest ever synthetic genome, the laboratory of Professor Jason Chin has now reprogrammed cells to make artificial polymers from building blocks not found in nature.

They were able to direct the cells by encoding instructions in their genes and they proved that their synthetic genome also made them entirely resistant to infection by viruses.

The research could lead to the creation of entirely new polymers large molecules made of many repeating units, as seen in proteins, plastics and many drugs.

Prof Chin said: This system allows us to write a gene that encodes the instructions to make polymers out of monomers that dont occur in nature.

These bacteria may be turned into renewable and programmable factories that produce a wide range of new molecules with novel properties, which could have benefits for biotechnology and medicine, including making new drugs, such as new antibiotics.

Wed like to use these bacteria to discover and build long synthetic polymers that fold up into structures and may form new classes of materials and medicines.

We will also investigate applications of this technology to develop novel polymers, such as biodegradable plastics, which could contribute to a circular bioeconomy.

It follows pioneering work, completed in 2019, which enabled the group to construct the entire genome of the bacterium Escherichia coli (E. coli) from scratch.

As the Cambridge Independent reported at the time, they had created a new lifeform that played by different biological rules to any other before it.

And they did so by answering a long-standing question about the way genetic code is read.

DNA is made up of four bases, which are represented by the letters A, T, C and G.

These are read by machinery in cells in threes, such as TCG, and each of these groups is called codon.

To build proteins, each codon tells the cell to add a specific amino acid to a chain via molecules called tRNA. And each codon has a specific tRNA that recognises it and adds the corresponding amino acid. The tRNA that recognises the codon TCG, for example, leads to the amino acid serine.

In all known life, there are 64 codons, or possible combinations, yet only 20 natural amino acids. This means there is redundancy in the system. For example, TCG, TCA, AGC and AGT all code for serine.

Other codons such as TAG and TAA send stop signals to tell a cell when to stop making a protein.

When they synthesised the entire genome of the commonly studied bacteria, E. coli, in 2019, Prof Chins group also simplified its genome, giving it just 61 codons.

Like a giant find and replace exercise, they removed every instance of TCG and TCA and replaced them with the synonyms AGC and AGT, while every instance of the stop codon TAG was replaced by another, TAA.

Their creation continued to synthesise all the normal proteins and the cells containing the synthetic genome thrived.

For the new work, they aimed to use their new techniques to make artificial polymers by exploiting cells natural protein-making processes.

They further modified the bacteria to remove the tRNA molecules that recognise the codons TCG and TCA.

It means that even if there are TCG or TCA codons in the genetic code, the cell no longer has the molecule that can read those codons.

And that is fatal for any virus that tries to infect the cell, as viruses replicate by injecting their genome into a cell and hijacking the cells machinery.

But when the machinery in the modified bacteria tries to read the virus genome, it fails every time it reaches a TCG, TCA or TAG codon.

The researchers infected their bacteria with viruses to test what happened. While the unmodified normal bacteria were killed, the modified bacteria were resistant to infection and survived.

This could be very useful in improving the reliability and cost of drug manufacture.

Medicines such as protein drugs, like insulin, and polysaccharide and protein subunit vaccines, are manufactured by growing bacteria that contain instructions to produce the drug.

If a virus gets into the vats of bacteria used to manufacture certain drugs then it can destroy the whole batch, said Prof Chin. Our modified bacterial cells could overcome this problem by being completely resistant to viruses. Because viruses use the full genetic code, the modified bacteria wont be able to read the viral genes.

Freeing up certain codons also means they are available for use for other purposes, such as coding for synthetic building blocks, called monomers.

The team engineered the bacteria to produce tRNAs coupled with artificial monomers that recognised the newly-available codons TCG and TAG.

Genetic sequences with strings of TCG and TAG codons were inserted into the bacterias DNA and read by the altered tRNAs.

This assembled chains of synthetic monomers in the order defined by the sequence of codons in the DNA.

They were able to programme the cells to string together monomers in different orders by changing the order of TCG and TAG codons in the genetic sequence. And they were able to create polymers composed of different monomers by changing which monomers were coupled to the tRNAs.

Polymers comprising up to eight monomers strung together were created.

The ends of these were joined to make macrocycles, which is a type of molecule that forms the basis of some drugs, including certain antibiotics and cancer drugs.

The synthetic monomers were linked using the same chemical bonds that join amino acids in protein, but the team is also exploring how to expand the range of linkages that could be used in the new polymers.

Dr Megan Dowie, head of molecular and cellular medicine at the Medical Research Council, which funded the study, said: Dr Chins pioneering work into genetic code expansion is a really exciting example of the value of our long-term commitment to discovery science. Research like this, in synthetic and engineering biology, clearly has huge potential for major impact in biopharma and other industrial settings.

The study, published in Science, was funded by the MRC and the European Research Council.

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Cells with synthetic genomes reprogrammed at MRC LMB - and could create new drugs or biodegradable plastics - Cambridge Independent