scholarly journals Understanding human genetic variation in the era of high‐throughput sequencing

EMBO Reports ◽  
2010 ◽  
Vol 11 (9) ◽  
pp. 650-652 ◽  
Author(s):  
Julian C. Knight
Keyword(s):  
Genetic Variation ◽  
High Throughput ◽  
High Throughput Sequencing ◽  
Human Genetic Variation

scholarly journals Alu elements: at the crossroads between disease and evolution

2013 ◽  
Vol 41 (6) ◽  
pp. 1532-1535 ◽  
Author(s):  
Jernej Ule
Keyword(s):  
Genetic Variation ◽  
Personalized Medicine ◽  
High Throughput ◽  
High Throughput Sequencing ◽  
Rapid Progress ◽  
Functional Elements ◽  
Alu Elements ◽  
Gradual Evolution ◽  
Major Increase ◽  
The Cost

The cost of DNA sequencing is decreasing year by year, and the era of personalized medicine and the $1000 genome seems to be just around the corner. In order to link genetic variation to gene function, however, we need to learn more about the function of the non-coding genomic elements. The advance of high-throughput sequencing enabled rapid progress in mapping the functional elements in our genome. In the present article, I discuss how intronic mutations acting at Alu elements enable formation of new exons. I review the mutations that cause disease when promoting a major increase in the inclusion of Alu exon into mature transcripts. Moreover, I present the mechanism that represses such a major inclusion of Alu exons and instead enables a gradual evolution of Alu elements into new exons.

scholarly journals Impact of Genetic Variation in Gene Regulatory Sequences: A Population Genomics Perspective

2021 ◽  
Vol 12 ◽  
Author(s):  
Manas Joshi ◽  
Adamandia Kapopoulou ◽  
Stefan Laurent
Keyword(s):  
Gene Expression ◽  
Genetic Variation ◽  
High Throughput ◽  
High Throughput Sequencing ◽  
Population Genomics ◽  
Natural Populations ◽  
Regulatory Elements ◽  
Regulatory Sequences ◽  
Coding Sequences ◽  
The Impact

The unprecedented rise of high-throughput sequencing and assay technologies has provided a detailed insight into the non-coding sequences and their potential role as gene expression regulators. These regulatory non-coding sequences are also referred to as cis-regulatory elements (CREs). Genetic variants occurring within CREs have been shown to be associated with altered gene expression and phenotypic changes. Such variants are known to occur spontaneously and ultimately get fixed, due to selection and genetic drift, in natural populations and, in some cases, pave the way for speciation. Hence, the study of genetic variation at CREs has improved our overall understanding of the processes of local adaptation and evolution. Recent advances in high-throughput sequencing and better annotations of CREs have enabled the evaluation of the impact of such variation on gene expression, phenotypic alteration and fitness. Here, we review recent research on the evolution of CREs and concentrate on studies that have investigated genetic variation occurring in these regulatory sequences within the context of population genetics.

scholarly journals Genetic structure of the American ginseng (Panax quinquefolius L.) in Eastern Canada using reduced-representation high-throughput sequencing

Botany ◽  
2017 ◽  
Vol 95 (4) ◽  
pp. 429-434 ◽  
Author(s):  
Simon Joly ◽  
Annie Archambault ◽  
Stéphanie Pellerin ◽  
Andrée Nault
Keyword(s):  
Genetic Variation ◽  
Genetic Structure ◽  
High Throughput ◽  
High Throughput Sequencing ◽  
Natural Populations ◽  
American Ginseng ◽  
Panax Quinquefolius ◽  
Eastern Canada ◽  
Reduced Representation ◽  
Wide Range

The American ginseng (Panax quinquefolius L.) has been used for a wide range of medicinal purposes for more than 300 years, and is at risk in most of its range because of harvesting in natural populations, herbivory, and habitat loss. Its genetic structure is largely unknown in the previously glaciated areas of Eastern Canada, although such information could provide useful information for restoration strategies. We generated and analysed data from a reduced-representation high-throughput sequencing approach with a BAMOVA population model to partition the genetic variation within and among six natural populations of American ginseng in Eastern Canada. We found that an important and significant fraction of the genetic variation was structured among populations ([Formula: see text] = 42%; FST = 34%) at the geographical scale of the study (<250 km). No clear evidence of isolation-by-distance was observed. This important genetic structure observed among American ginseng populations from a region that was covered by ice during the last glaciations is similar to what had been found in previous studies on southern populations or throughout the species range.

scholarly journals seqCAT: a Bioconductor R-package for variant analysis of high throughput sequencing data

F1000Research ◽  
2018 ◽  
Vol 7 ◽  
pp. 1466 ◽  
Author(s):  
Erik Fasterius ◽  
Cristina Al-Khalili Szigyarto
Keyword(s):  
Genetic Variation ◽  
Liver Cancer ◽  
High Throughput ◽  
High Throughput Sequencing ◽  
R Package ◽  
Ease Of Use ◽  
Sequencing Data ◽  
Dna And Rna ◽  
High Throughput Sequencing Data ◽  
Wide Range

High throughput sequencing technologies are flourishing in the biological sciences, enabling unprecedented insights into e.g. genetic variation, but require extensive bioinformatic expertise for the analysis. There is thus a need for simple yet effective software that can analyse both existing and novel data, providing interpretable biological results with little bioinformatic prowess. We present seqCAT, a Bioconductor toolkit for analysing genetic variation in high throughput sequencing data. It is a highly accessible, easy-to-use and well-documented R-package that enables a wide range of researchers to analyse their own and publicly available data, providing biologically relevant conclusions and publication-ready figures. SeqCAT can provide information regarding genetic similarities between an arbitrary number of samples, validate specific variants as well as define functionally similar variant groups for further downstream analyses. Its ease of use, installation, complete data-to-conclusions functionality and the inherent flexibility of the R programming language make seqCAT a powerful tool for variant analyses compared to already existing solutions. A publicly available dataset of liver cancer-derived organoids is analysed herein using the seqCAT package, demonstrating that the organoids are genetically stable. A previously known liver cancer-related mutation is additionally shown to be present in a sample though it was not listed in the original publication. Differences between DNA- and RNA-based variant calls in this dataset are also analysed revealing a high median concordance of 97.5%.

Exploring Human Genetic Variation – Scientific and Ethical Challenges

2018 ◽  
Author(s):  
Paula Dobosz ◽  
Jakub Zawiła-Niedźwiecki
Keyword(s):  
Genetic Variation ◽  
High Throughput Sequencing ◽  
Current Knowledge ◽  
Human Genetic Variation ◽  
Ethical Challenges ◽  
New Techniques ◽  
Public And Private ◽  
Sequencing Technologies ◽  
Health And Disease ◽  
And Storage

Since the genomic era is a reality nowadays, we need deeper understanding and consideration upon the benefits and challenges it brings. Apart from all the enthusiasm, there are also concerns related to genomics, specifically to the use and storage of personal genetic information as well as concerns regarding, for instance, so-called incidental findings, and right not to know. It started with Mendel&rsquo;s simple experiments, but led to high-throughput sequencing technologies, resulting complex genomic data is constantly poured into public and private databases, inevitably changing our current knowledge. With the advent of new techniques and methods, like CRISPR/Cas9 engineering, researchers are provided with improved and expanded repertoire of research tools to analyse an organism in health and disease. This paper is aimed at providing examples of the applications and challenges, both practical and theoretical, in exploring human genetic variation.

scholarly journals Performance of High-Throughput Sequencing for the Discovery of Genetic Variation Across the Complete Size Spectrum

2013 ◽  
Vol 4 (1) ◽  
pp. 63-65 ◽  
Author(s):  
Andy Wing Chun Pang ◽  
Jeffrey R. MacDonald ◽  
Ryan K. C. Yuen ◽  
Vanessa M. Hayes ◽  
Stephen W. Scherer
Keyword(s):  
Genetic Variation ◽  
High Throughput ◽  
High Throughput Sequencing ◽  
Size Spectrum

scholarly journals A 'Variant Viewer' for investigating population-level variation in Arabidopsis thaliana

2021 ◽  
Author(s):  
Matthew Cumming ◽  
Eddi Esteban ◽  
Vincent Lau ◽  
Asher Pasha ◽  
Nicholas J. Provart
Keyword(s):  
Arabidopsis Thaliana ◽  
Genetic Variation ◽  
High Throughput ◽  
Web Application ◽  
High Throughput Sequencing ◽  
Population Level ◽  
Gene Families ◽  
Level Variation ◽  
Splice Isoforms ◽  
Large Populations

High throughput sequencing has opened the doors for investigators to probe genetic variation present in large populations of organisms. In plants, the 1001 Genomes Project (1001genomes.org) is one such effort that sought to characterize the extant worldwide variation in Arabidopsis thaliana for future analyses to compare and draw upon. We developed a web application that accesses the 1001 Genomes database called The Variant Viewer, for investigators to view variants in any A. thaliana gene and within gene families. These variants may be visualized in the context of alignments of queried genes, across splice isoforms of these genes and in relation to conserved domains.

scholarly journals seqCAT: a Bioconductor R-package for variant analysis of high throughput sequencing data

F1000Research ◽  
2019 ◽  
Vol 7 ◽  
pp. 1466 ◽  
Author(s):  
Erik Fasterius ◽  
Cristina Al-Khalili Szigyarto
Keyword(s):  
Genetic Variation ◽  
Liver Cancer ◽  
High Throughput ◽  
High Throughput Sequencing ◽  
R Package ◽  
Ease Of Use ◽  
Sequencing Data ◽  
Dna And Rna ◽  
High Throughput Sequencing Data ◽  
Wide Range

High throughput sequencing technologies are flourishing in the biological sciences, enabling unprecedented insights into e.g. genetic variation, but require extensive bioinformatic expertise for the analysis. There is thus a need for simple yet effective software that can analyse both existing and novel data, providing interpretable biological results with little bioinformatic prowess. We present seqCAT, a Bioconductor toolkit for analysing genetic variation in high throughput sequencing data. It is a highly accessible, easy-to-use and well-documented R-package that enables a wide range of researchers to analyse their own and publicly available data, providing biologically relevant conclusions and publication-ready figures. SeqCAT can provide information regarding genetic similarities between an arbitrary number of samples, validate specific variants as well as define functionally similar variant groups for further downstream analyses. Its ease of use, installation, complete data-to-conclusions functionality and the inherent flexibility of the R programming language make seqCAT a powerful tool for variant analyses compared to already existing solutions. A publicly available dataset of liver cancer-derived organoids is analysed herein using the seqCAT package, corroborating the original authors' conclusions that the organoids are genetically stable. A previously known liver cancer-related mutation is additionally shown to be present in a sample though it was not listed in the original publication. Differences between DNA- and RNA-based variant calls in this dataset are also analysed revealing a high median concordance of 97.5%. SeqCAT is an open source software under a MIT licence available at https://bioconductor.org/packages/release/bioc/html/seqCAT.html.

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