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Archive for the ‘Genome Biology’ Category


Individuals without angiographic CAD but with hiPRS remain at significantly elevated risk of mortality after cardiac catheterization

Reporter: Aviva Lev-Ari, PhD, RN

 

A genome-wide Polygenic risk scores (PRS) improves risk stratification when added to traditional risk factors and coronary angiography. Individuals without angiographic CAD but with hiPRS remain at significantly elevated risk of mortality.

 

Background:

Coronary artery disease (CAD) is influenced by genetic variation and traditional risk factors. Polygenic risk scores (PRS), which can be ascertained before the development of traditional risk factors, have been shown to identify individuals at elevated risk of CAD. Here, we demonstrate that a genome-wide PRS for CAD predicts all-cause mortality after accounting for not only traditional cardiovascular risk factors but also angiographic CAD itself.

Methods:

Individuals who underwent coronary angiography and were enrolled in an institutional biobank were included; those with prior myocardial infarction or heart transplant were excluded. Using a pruning-and-thresholding approach, a genome-wide PRS comprised of 139 239 variants was calculated for 1503 participants who underwent coronary angiography and genotyping. Individuals were categorized into high PRS (hiPRS) and low-PRS control groups using the maximally selected rank statistic. Stratified analysis based on angiographic findings was also performed. The primary outcome was all-cause mortality following the index coronary angiogram.

Results:

Individuals with hiPRS were younger than controls (66 years versus 69 years; P=2.1×10-5) but did not differ by sex, body mass index, or traditional risk-factor profiles. Individuals with hiPRS were at significantly increased risk of all-cause mortality after cardiac catheterization, adjusting for traditional risk factors and angiographic extent of CAD (hazard ratio, 1.6; 95% CI, 1.2–2.2; P=0.004). The strongest increase in risk of all-cause mortality conferred by hiPRS was seen among individuals without angiographic CAD (hazard ratio, 2.4; 95% CI, 1.1–5.5; P=0.04). In the overall cohort, adding hiPRS to traditional risk assessment improved prediction of 5-year all-cause mortality (area under the receiver-operating curve 0.70; 95% CI, 0.66–0.75 versus 0.66; 95% CI, 0.61–0.70; P=0.001).

Conclusions:

A genome-wide PRS improves risk stratification when added to traditional risk factors and coronary angiography. Individuals without angiographic CAD but with hiPRS remain at significantly elevated risk of mortality.

Footnotes

https://www.ahajournals.org/journal/circgen

*A list of all Regeneron Genetics Center members is given in the Data Supplement.

Guest Editor for this article was Christopher Semsarian, MBBS, PhD, MPH.

The Data Supplement is available at https://www.ahajournals.org/doi/suppl/10.1161/CIRCGEN.118.002352.

Scott M. Damrauer, MD, Department of Surgery, Hospital of the University of Pennsylvania, 3400 Spruce St, Silverstein 4, Philadelphia, PA 19104. Email 
SOURCE
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The HFE H63D variant confers an increased risk for hypertension, no increased risk for adverse cardiovascular events or substantial left ventricular remodeling

Reporter: Aviva Lev-Ari, PhD, RN

Conclusion:

The HFE H63D variant confers an increased risk for hypertension per allele and, given its frequency, accounts for a significant number of cases of hypertension. However, there was no increased risk for adverse cardiovascular events or substantial left ventricular remodeling.

 

HFE H63D Polymorphism and the Risk for Systemic Hypertension, Myocardial Remodeling, and Adverse Cardiovascular Events in the ARIC Study

Originally publishedHypertension. 2018;0:HYPERTENSIONAHA.118.11730

H63D has been identified as a novel locus associated with the development of hypertension. The quantitative risks for hypertension, cardiac remodeling, and adverse events are not well studied. We analyzed white participants from the ARIC study (Atherosclerosis Risk in Communities) with H63D genotyping (N=10 902). We related genotype status to prevalence of hypertension at each of 5 study visits and risk for adverse cardiovascular events. Among visit 5 participants (N=4507), we related genotype status to echocardiographic features. Frequencies of wild type (WT)/WT, H63D/WT, and H63D/H63D were 73%, 24.6%, and 2.4%. The average age at baseline was 54.9±5.7 years and 47% were men. Participants carrying the H63D variant had higher systolic blood pressure (P=0.004), diastolic blood pressure (0.012), and more frequently had hypertension (P<0.001). Compared with WT/WT, H63D/WT and H63D/H63D participants had a 2% to 4% and 4% to 7% absolute increase in hypertension risk at each visit, respectively. The population attributable risk of H63D for hypertension among individuals aged 45 to 64 was 3.2% (95% CI, 1.3–5.1%) and 1.3% (95% CI, 0.0–2.4%) among individuals >65 years. After 25 years of follow-up, there was no relationship between genotype status and any outcome (P>0.05). H63D/WT and H63D/H63D genotypes were associated with small differences in cardiac remodeling. In conclusion, the HFE H63D variant confers an increased risk for hypertension per allele and, given its frequency, accounts for a significant number of cases of hypertension. However, there was no increased risk for adverse cardiovascular events or substantial left ventricular remodeling.

Footnotes

The online-only Data Supplement is available with this article at https://www.ahajournals.org/doi/suppl/10.1161/HYPERTENSIONAHA.118.11730.

Correspondence to Scott D. Solomon, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, 75 Francis St, Boston, MA 02115. Email 

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Bioinformatics Tool Review: Genome Variant Analysis Tools

Curator: Stephen J. Williams, Ph.D.

 

The following post will be an ongoing curation of reviews of gene variant bioinformatic software.

 

The Ensembl Variant Effect Predictor.

McLaren W, Gil L, Hunt SE, Riat HS, Ritchie GR, Thormann A, Flicek P, Cunningham F.

Genome Biol. 2016 Jun 6;17(1):122. doi: 10.1186/s13059-016-0974-4.

Author information

1

European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK. wm2@ebi.ac.uk.

2

European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK.

3

European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK. fiona@ebi.ac.uk.

Abstract

The Ensembl Variant Effect Predictor is a powerful toolset for the analysis, annotation, and prioritization of genomic variants in coding and non-coding regions. It provides access to an extensive collection of genomic annotation, with a variety of interfaces to suit different requirements, and simple options for configuring and extending analysis. It is open source, free to use, and supports full reproducibility of results. The Ensembl Variant Effect Predictor can simplify and accelerate variant interpretation in a wide range of study designs.

 

Rare diseases can be difficult to diagnose due to low incidence and incomplete penetrance of implicated alleles however variant analysis of whole genome sequencing can identify underlying genetic events responsible for the disease (Nature, 2015).  However, a large cohort is required for many WGS association studies in order to produce enough statistical power for interpretation (see post and here).  To this effect major sequencing projects have been initiated worldwide including:

A more thorough curation of sequencing projects can be seen in the following post:

Icelandic Population Genomic Study Results by deCODE Genetics come to Fruition: Curation of Current genomic studies

 

And although sequencing costs have dramatically been reduced over the years, the costs to determine the functional consequences of such variants remains high, as thorough basic research studies must be conducted to validate the interpretation of variant data with respect to the underlying disease, as only a small fraction of variants from a genome sequencing project will encode for a functional protein.  Correct annotation of sequences and variants, identification of correct corresponding reference genes or transcripts in GENCODE or RefSeq respectively offer compelling challenges to the proper identification of sequenced variants as potential functional variants.

To this effect, the authors developed the Ensembl Variant Effect Predictor (VEP), which is a software suite that performs annotations and analysis of most types of genomic variation in coding and non-coding regions of the genome.

Summary of Features

  • Annotation: VEP can annotate two broad categories of genomic variants
    • Sequence variants with specific and defined changes: indels, base substitutions, SNVs, tandem repeats
    • Larger structural variants > 50 nucleotides
  • Species and assembly/genomic database support: VEP can analyze data from any species with assembled genome sequence and annotated gene set. VEP supports chromosome assemblies such as the latest GRCh38, FASTA, as well as transcripts from RefSeq as well as user-derived sequences
  • Transcript Annotation: VEP includes a wide variety of gene and transcript related information including NCBI Gene ID, Gene Symbol, Transcript ID, NCBI RefSeq ID, exon/intron information, and cross reference to other databases such as UniProt
  • Protein Annotation: Protein-related fields include Protein ID, RefSeq ID, SwissProt, UniParc ID, reference codons and amino acids, SIFT pathogenicity score, protein domains
  • Noncoding Annotation: VEP reports variants in noncoding regions including genomic regulatory regions, intronic regions, transcription binding motifs. Data from ENCODE, BLUEPRINT, and NIH Epigenetics RoadMap are used for primary annotation.  Plugins to the Perl coding are also available to link other databases which annotate noncoding sequence features.
  • Frequency, phenotype, and citation annotation: VEP searches Ensembl databases containing a large amount of germline variant information and checks variants against the dbSNP single nucleotide polymorphism database. VEP integrates with mutational databases such as COSMIC, the Human Gene Mutation Database, and structural and copy number variants from Database of Genomic Variants.  Allele Frequencies are reported from 1000 Genomes and NHLBI and integrates with PubMed for literature annotation.  Phenotype information is from OMIM, Orphanet, GWAS and clinical information of variants from ClinVar.
  • Flexible Input and Output Formats: VEP supports input data format called “variant call format” or VCP, a standard in next-gen sequencing. VEP has the ability to process variant identifiers from other database formats.  Output formats are tab deliminated and give the user choices in presentation of results (HTML or text based)
  • Choice of user interface
    • Online tool (VEP Web): simple point and click; incorporates Instant VEP Functionality and copy and paste features. Results can be stored online in cloud storage on Ensembl.
    • VEP script: VEP is available as a downloadable PERL script (see below for link) and can process large amounts of data rapidly. This interface is powerfully flexible with the ability to integrate multiple plugins available from Ensembl and GitHub.  The ability to alter the PERL code and add plugins and code functions allows the flexibility to modify any feature of VEP.
    • VEP REST API: provides robust computational access to any programming language and returns basic variant annotation. Can make use of external plugins.

 

 

Watch Video on VES Instructional Webinar: https://youtu.be/7Fs7MHfXjWk

Watch Video on VES Web Version training on How to Analyze Your Sequence in VEP

 

 

Availability of data and materials

The dataset supporting the conclusions of this article is available from Illumina’s Platinum Genomes [93] and using the Ensembl release 75 gene set. Pre-built data sets are available for all Ensembl and Ensembl Genomes species [94]. They can also be downloaded automatically during set up whilst installing the VEP.

 

References

Large-scale discovery of novel genetic causes of developmental disorders.

Deciphering Developmental Disorders Study.

Nature2015 Mar 12;519(7542):223-8. doi: 10.1038/nature14135. PMID:25533962

Other articles related to Genomics and Bioinformatics on this online Open Access Journal Include:

Finding the Genetic Links in Common Disease: Caveats of Whole Genome Sequencing Studies

 

Large-scale sequencing does not support the idea that lower-frequency variants have a major role in predisposition to type 2 diabetes

 

US Personalized Cancer Genome Sequencing Market Outlook 2018 –

 

Icelandic Population Genomic Study Results by deCODE Genetics come to Fruition: Curation of Current genomic studies

 

 

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Sickle Cell and Beta Thalassemia chosen for first human trial of the gene editing technology, CRISPR by sponsoring companies CRISPR Therapeutics and Vertex Pharmaceuticals, trial at a single site in Germany,

 

Reporter: Aviva Lev-Ari, PhD, RN

UPDATED on 9/13/2018

 

September 13, 2018

NIH launches initiative to accelerate genetic therapies to cure sickle cell disease

“Our scientific investments have brought us to a point where we have many tools available to correct or compensate for the defective gene that causes sickle cell disease. We are now ready to use these tools to speed up our quest for a cure,” said Gary H. Gibbons, M.D., director of NIH’s National Heart, Lung, and Blood Institute (NHLBI), which is leading the effort.

SOURCE

https://www.nih.gov/news-events/news-releases/nih-launches-initiative-accelerate-genetic-therapies-cure-sickle-cell-disease

 

 

Vertex licensed CTX001, an autologous gene-edited hematopoietic stem cell therapy, from CRISPR in December. It was the first CRISPR-based treatment to come out of a four-year, $105 million deal the pair struck in 2015. At the time, Vertex paid up $75 million in cash and took a $30 million stake in CRISPR Therapeutics in exchange for the right to license up to six gene-editing programs. CTX001 is being developed for the blood disorders sickle cell disease and beta thalassemia.

Both disorders are caused by mutations in the beta-globin gene, which codes for a part of hemoglobin, the oxygen-carrying component of red blood cells. This results in missing or defective hemoglobin. CTX001 was developed on the knowledge that fetal hemoglobin—found in newborn babies but later replaced by adult hemoglobin—can be protective in adults who have blood disorders.

CTX001 uses CRISPR gene-editing ex vivo—that is, outside the body. A patient’s cells are harvested and edited to increase fetal hemoglobin levels in the patient’s blood cells. The edited cells are then infused back into the patient where they are expected to produce blood cells with fetal hemoglobin and compensate for defective adult hemoglobin.

SOURCE

https://www.fiercebiotech.com/biotech/crispr-therapeutics-vertex-start-first-company-backed-human-crispr-trial?mkt_tok=eyJpIjoiTm1FMllXTmtOMlkwWkRNdyIsInQiOiJLMUEyeGtsT0ZMTVBuM1RtbVFjRFdMQUdRcDZkXC9yVHlXTWxIQmlvc3M0XC9LVFArdlFuaVVYY0lQXC81ak9cL3h1VjFHYnprZ3dqVlNlaWFldWxcLzA3QUphdExpc0w0Vk1TSGR3WVl0YXNqQlFRVHdvZmNycVNEWE9qdWQ2QmdacklSIn0%3D&mrkid=993697

Other 339 articles on GENE EDITING were published in this Open Access Online Scientific Journal, including the following articles:

https://pharmaceuticalintelligence.com/?s=Gene+Editing

On CRISPR/Cas9, there are 141 articles in the Journal:

https://pharmaceuticalintelligence.com/?s=CRISPR%2FCas9

Gene Therapy, there are 11 articles in the Journal:

https://pharmaceuticalintelligence.com/category/genome-biology/gene-therapy-gene-editing-development/

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Single-cell Genomics: Directions in Computational and Systems Biology – Contributions of Prof. Aviv Regev @Broad Institute of MIT and Harvard, Cochair, the Human Cell Atlas Organizing Committee with Sarah Teichmann of the Wellcome Trust Sanger Institute

 

Curator: Aviva Lev-Ari, PhD, RN

 

Dana Pe’er, PhD, now chair of computational and systems biology at the Sloan Kettering Institute at the Memorial Sloan Kettering Cancer Center and a member of the Human Cell Atlas Organizing Committee,

what really sets Regev apart is the elegance of her work. Regev, says Pe’er, “has a rare, innate ability of seeing complex biology and simplifying it and formalizing it into beautiful, abstract, describable principles.”

Dr. Aviv Regev, an MIT biology professor who is also chair of the faculty of the Broad and director of its Klarman Cell Observatory and Cell Circuits Program, was reviewing a newly published white paper detailing how the Human Cell Atlas is expected to change the way we diagnose, monitor, and treat disease at a gathering of international scientists at Israel’s Weizmann Institute of Science, 10/2017.

For Regev, the importance of the Human Cell Atlas goes beyond its promise to revolutionize biology and medicine. As she once put it, without an atlas of our cells, “we don’t really know what we’re made of.”

Regev, turned to a technique known as RNA interference (she now uses CRISPR), which allowed her to systematically shut genes down. Then she looked at which genes were expressed to determine how the cells’ response changed in each case. Her team singled out 100 different genes that were involved in regulating the response to the pathogens—some of which weren’t previously known to be involved in immune function. The study, published in Science, generated headlines.

The project, the Human Cell Atlas, aims to create a reference map that categorizes all the approximately 37 trillion cells that make up a human. The Human Cell Atlas is often compared to the Human Genome Project, the monumental scientific collaboration that gave us a complete readout of human DNA, or what might be considered the unabridged cookbook for human life. In a sense, the atlas is a continuation of that project’s work. But while the same DNA cookbook is found in every cell, each cell type reads only some of the recipes—that is, it expresses only certain genes, following their DNA instructions to produce the proteins that carry out a cell’s activities. The promise of the Human Cell Atlas is to reveal which specific genes are expressed in every cell type, and where the cells expressing those genes can be found.

Regev says,

The final product, will amount to nothing less than a “periodic table of our cells,” a tool that is designed not to answer one specific question but to make countless new discoveries possible.

Sequencing the RNA of the cells she’s studying can tell her only so much. To understand how the circuits change under different circumstances, Regev subjects cells to different stimuli, such as hormones or pathogens, to see how the resulting protein signals change.

“the modeling step”—creating algorithms that try to decipher the most likely sequence of molecular events following a stimulus. And just as someone might study a computer by cutting out circuits and seeing how that changes the machine’s operation, Regev tests her model by seeing if it can predict what will happen when she silences specific genes and then exposes the cells to the same stimulus.

By sequencing the RNA of individual cancer cells in recent years—“Every cell is an experiment now,” she says—she has found remarkable differences between the cells of a single tumor, even when they have the same mutations. (Last year that work led to Memorial Sloan Kettering’s Paul Marks Prize for Cancer Research.) She found that while some cancers are thought to develop resistance to therapy, a subset of melanoma cells were resistant from the start. And she discovered that two types of brain cancer, oligodendroglioma and astrocytoma, harbor the same cancer stem cells, which could have important implications for how they’re treated.

As a 2017 overview of the Human Cell Atlas by the project’s organizing committee noted, an atlas “is a map that aims to show the relationships among its elements.” Just as corresponding coastlines seen in an atlas of Earth offer visual evidence of continental drift, compiling all the data about our cells in one place could reveal relationships among cells, tissues, and organs, including some that are entirely unexpected. And just as the periodic table made it possible to predict the existence of elements yet to be observed, the Human Cell Atlas, Regev says, could help us predict the existence of cells that haven’t been found.

This year alone it will fund 85 Human Cell Atlas grants. Early results are already pouring in.

  • In March, Swedish researchers working on cells related to human development announced they had sequenced 250,000 individual cells.
  • In May, a team at the Broad made a data set of more than 500,000 immune cells available on a preview site.

The goal, Regev says, is for researchers everywhere to be able to use the open-source platform of the Human Cell Atlas to perform joint analyses.

Eric Lander, PhDthe founding director and president of the Broad Institute and a member of the Human Cell Atlas Organizing Committee, likens it to genomics.

“People thought at the beginning they might use genomics for this application or that application,” he says. “Nothing has failed to be transformed by genomics, and nothing will fail to be transformed by having a cell atlas.”

“How did we ever imagine we were going to solve a problem without single-cell resolution?”

SOURCE

https://www.technologyreview.com/s/611786/the-cartographer-of-cells/?utm_source=MIT+Technology+Review&utm_campaign=Alumni-Newsletter_Sep-Oct-2018&utm_medium=email

Other related articles published in this Open Access Online Scientific Journal include the following:

 

University of California Santa Cruz’s Genomics Institute will create a Map of Human Genetic Variations

Reporter: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2015/01/13/university-of-california-santa-cruzs-genomics-institute-will-create-a-map-of-human-genetic-variations/

 

Recognitions for Contributions in Genomics by Dan David Prize Awards

Reporter: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2017/07/31/recognitions-for-contributions-in-genomics-by-dan-david-prize-awards/

 

ENCODE (Encyclopedia of DNA Elements) program: ‘Tragic’ Sequestration Impact on NHGRI Programs

Reporter: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2013/09/18/encode-encyclopedia-of-dna-elements-program-tragic-sequestration-impact-on-nhgri-programs/

 

Single-cell Sequencing

Genomic Diagnostics: Three Techniques to Perform Single Cell Gene Expression and Genome Sequencing Single Molecule DNA Sequencing

Curator: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2017/07/04/genomic-diagnostics-three-techniques-to-perform-single-cell-gene-expression-and-genome-sequencing-single-molecule-dna-sequencing/

 

LIVE – Real Time – 16th Annual Cancer Research Symposium, Koch Institute, Friday, June 16, 9AM – 5PM, Kresge Auditorium, MIT – See, Aviv Regev

REAL TIME PRESS COVERAGE & Reporter: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2017/03/13/16th-annual-cancer-research-symposium-koch-institute-friday-june-16-9am-5pm-kresge-auditorium-mit/

 

LIVE 11/3/2015 1:30PM @The 15th Annual EmTech MIT – MIT Media Lab: Top 10 Breakthrough Technologies & 2015 Innovators Under 35 – See, Gilead Evrony

REAL TIME PRESS COVERAGE & Reporter: Aviva Lev-Ari, PhD, RN
https://pharmaceuticalintelligence.com/2015/11/03/live-1132015-130pm-the-15th-annual-emtech-mit-mit-media-lab-top-10-breakthrough-technologies-2015-innovators-under-35/

 

Cellular Guillotine Created for Studying Single-Cell Wound Repair

Reporter: Irina Robu, PhD

https://pharmaceuticalintelligence.com/2017/06/29/cellular-guillotine-created-for-studying-single-cell-wound-repair/

 

New subgroups of ILC immune cells discovered through single-cell RNA sequencing

Reporter: Stephen J Williams, PhD

https://pharmaceuticalintelligence.com/2016/02/17/new-subgroups-of-ilc-immune-cells-discovered-through-single-cell-rna-sequencing-from-karolinska-institute/

 

#JPM16: Illumina’s CEO on new genotyping array called Infinium XT and Bio-Rad Partnership for single-cell sequencing workflow

Reporter: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2016/01/12/jpm16-illuminas-ceo-on-new-genotyping-array-called-infinium-xt-and-bio-rad-partnership-for-single-cell-sequencing-workflow/

 

Juno Acquires AbVitro for $125M: high-throughput and single-cell sequencing capabilities for Immune-Oncology Drug Discovery

Reporter: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2016/01/12/juno-acquires-abvitro-for-125m-high-throughput-and-single-cell-sequencing-capabilities-for-immune-oncology-drug-discovery/

 

NIH to Award Up to $12M to Fund DNA, RNA Sequencing Research: single-cell genomics,  sample preparation,  transcriptomics and epigenomics, and  genome-wide functional analysis.

Reporter: Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2015/10/27/nih-to-award-up-to-12m-to-fund-dna-rna-sequencing-research-single-cell-genomics-sample-preparation-transcriptomics-and-epigenomics-and-genome-wide-functional-analysis/

 

Genome-wide Single-Cell Analysis of Recombination Activity and De Novo Mutation Rates in Human Sperm

Reporter and Curator: Dr. Sudipta Saha, Ph.D.

https://pharmaceuticalintelligence.com/2012/08/07/genome-wide-single-cell-analysis-of-recombination-activity-and-de-novo-mutation-rates-in-human-sperm/

REFERENCES to Original studies

In Science, 2018

Single-cell RNA-seq reveals new types of human blood dendritic cells, monocytes, and progenitors

 See all authors and affiliations

Science  21 Apr 2017:
Vol. 356, Issue 6335, eaah4573
DOI: 10.1126/science.aah4573
Single-cell reconstruction of developmental trajectories during zebrafish embryogenesis

See all authors and affiliations

Science  26 Apr 2018:
eaar3131
DOI: 10.1126/science.aar3131

In Nature, 2018 and 2017

How to build a human cell atlas

Aviv Regev is a maven of hard-core biological analyses. Now she is part of an effort to map every cell in the human body.

  1. Research | 

  2. Research | 

  3. Research | 

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  6. Amendments and Corrections | 

  7. Research |  | OPEN

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  9. Amendments and Corrections | 

  10. Comments and Opinion | 

  11. Research | 

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Reporter and Curator: Dr. Sudipta Saha, Ph.D.

 

Researchers have embraced CRISPR gene-editing as a method for altering genomes, but some have reported that unwanted DNA changes may slip by undetected. The tool can cause large DNA deletions and rearrangements near its target site on the genome. Such alterations can confuse the interpretation of experimental results and could complicate efforts to design therapies based on CRISPR. The finding is in line with previous results from not only CRISPR but also other gene-editing systems.

 

CRISPR -Cas9 gene editing relies on the Cas9 enzyme to cut DNA at a particular target site. The cell then attempts to reseal this break using its DNA repair mechanisms. These mechanisms do not always work perfectly, and sometimes segments of DNA will be deleted or rearranged, or unrelated bits of DNA will become incorporated into the chromosome.

 

Researchers often use CRISPR to generate small deletions in the hope of knocking out a gene’s function. But when examining CRISPR edits, researchers found large deletions (often several thousand nucleotides) and complicated rearrangements of DNA sequences in which previously distant DNA sequences were stitched together. Many researchers use a method for amplifying short snippets of DNA to test whether their edits have been made properly. But this approach might miss larger deletions and rearrangements.

 

These deletions and rearrangements occur only with gene-editing techniques that rely on DNA cutting and not with some other types of CRISPR modifications that avoid cutting DNA. Such as a modified CRISPR system to switch one nucleotide for another without cutting DNA and other systems use inactivated Cas9 fused to other enzymes to turn genes on or off, or to target RNA. Overall, these unwanted edits are a problem that deserves more attention, but this should not stop anyone from using CRISPR. Only when people use it, they need to do a more thorough analysis about the outcome.

 

References:

 

https://www.nature.com/articles/d41586-018-05736-3?utm_source=briefing-dy

 

https://www.ncbi.nlm.nih.gov/pubmed/28561021

 

https://www.ncbi.nlm.nih.gov/pubmed/30010673

 

https://www.ncbi.nlm.nih.gov/pubmed/24651067

 

https://www.ncbi.nlm.nih.gov/pubmed/25398350

 

https://www.ncbi.nlm.nih.gov/pubmed/24838573

 

https://www.ncbi.nlm.nih.gov/pubmed/25200087

 

https://www.ncbi.nlm.nih.gov/pubmed/25757625

 

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Reporter and Curator: Dr. Sudipta Saha, Ph.D.

 

Long interspersed nuclear elements 1 (LINE1) is repeated half a million times in the human genome, making up nearly a fifth of the DNA in every cell. But nobody cared to study it and may be the reason to call it junk DNA. LINE1, like other transposons (or “jumping genes”), has the unusual ability to copy and insert itself in random places in the genome. Many other research groups uncovered possible roles in early mouse embryos and in brain cells. But nobody quite established a proper report about the functions of LINE1.

 

Geneticists gave attention to LINE1 when it was found to cause cancer or genetic disorders like hemophilia. But researchers at University of California at San Francisco suspected there was more characteristics of LINE1. They suspected that if it can be most harmless then it can be worst harmful also.

 

Many reports showed that LINE1 is especially active inside developing embryos, which suggests that the segment actually plays a key role in coordinating the development of cells in an embryo. Researchers at University of California at San Francisco figured out how to turn LINE1 off in mouse embryos by blocking LINE1 RNA. As a result the embryos got stuck in the two-cell stage, right after a fertilized egg has first split. Without LINE1, embryos essentially stopped developing.

 

The researchers thought that LINE1 RNA particles act as molecular “glue,” bringing together a suite of molecules that switch off the two-cell stage and kick it into the next phase of development. In particular, it turns off a gene called Dux, which is active in the two-cell stage.

 

LINE1’s ability to copy itself, however, seems to have nothing to do with its role in embryonic development. When LINE1 was blocked from inserting itself into the genome, the embryonic stem cells remained unaffected. It’s possible that cells in embryos have a way of making LINE1 RNA while also preventing its potentially harmful “jumping” around in the genome. But it’s unlikely that every one of the thousands of copies of LINE1 is actually being used to regulate embryonic development.

 

LINE1 is abundant in the genomes of almost all mammals. Other transposons, also once considered junk DNA, have turned out to have critical roles in development in human cells too. There are differences between mice and humans, so, the next obvious step is to study LINE1 in human cells, where it makes up 17 percent of the genome.

 

References:

 

https://www-theatlantic-com.cdn.ampproject.org/c/s/www.theatlantic.com/amp/article/563354/

 

https://www.ncbi.nlm.nih.gov/pubmed/29937225

 

https://www.nature.com/scitable/topicpage/transposons-the-jumping-genes-518

 

https://www.sciencedaily.com/releases/2018/06/180621141038.htm

 

https://www.ncbi.nlm.nih.gov/pubmed/16015595

 

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