Faculty Opinions recommendation of Whole-genome patterns of common DNA variation in three human populations.

2005 ◽  
Author(s):  
Magnus Nordborg
Keyword(s):  
Human Populations ◽  
Whole Genome ◽  
Dna Variation

scholarly journals A study of transposable element-associated structural variations (TASVs) using a de novo-assembled Korean genome

2021 ◽  
Author(s):  
Seyoung Mun ◽  
Songmi Kim ◽  
Wooseok Lee ◽  
Keunsoo Kang ◽  
Thomas J. Meyer ◽  
...  
Keyword(s):  
Genome Sequencing ◽  
Genome Assembly ◽  
De Novo ◽  
Personal Genome ◽  
Human Populations ◽  
Whole Genome ◽  
Structural Variations ◽  
Insert Size ◽  
Human Genomes ◽  
Next Generation Sequencing Ngs

AbstractAdvances in next-generation sequencing (NGS) technology have made personal genome sequencing possible, and indeed, many individual human genomes have now been sequenced. Comparisons of these individual genomes have revealed substantial genomic differences between human populations as well as between individuals from closely related ethnic groups. Transposable elements (TEs) are known to be one of the major sources of these variations and act through various mechanisms, including de novo insertion, insertion-mediated deletion, and TE–TE recombination-mediated deletion. In this study, we carried out de novo whole-genome sequencing of one Korean individual (KPGP9) via multiple insert-size libraries. The de novo whole-genome assembly resulted in 31,305 scaffolds with a scaffold N50 size of 13.23 Mb. Furthermore, through computational data analysis and experimental verification, we revealed that 182 TE-associated structural variation (TASV) insertions and 89 TASV deletions contributed 64,232 bp in sequence gain and 82,772 bp in sequence loss, respectively, in the KPGP9 genome relative to the hg19 reference genome. We also verified structural differences associated with TASVs by comparative analysis with TASVs in recent genomes (AK1 and TCGA genomes) and reported their details. Here, we constructed a new Korean de novo whole-genome assembly and provide the first study, to our knowledge, focused on the identification of TASVs in an individual Korean genome. Our findings again highlight the role of TEs as a major driver of structural variations in human individual genomes.

scholarly journals Whole genome sequences are required to fully resolve the linkage disequilibrium structure of human populations

BMC Genomics ◽  
2015 ◽  
Vol 16 (1) ◽  
Author(s):  
Reuben J. Pengelly ◽  
William Tapper ◽  
Jane Gibson ◽  
Marcin Knut ◽  
Rick Tearle ◽  
...  
Keyword(s):  
Linkage Disequilibrium ◽  
Human Populations ◽  
Whole Genome ◽  
Linkage Disequilibrium Structure ◽  
Genome Sequences

scholarly journals Identification of meiotic recombination through gamete genome reconstruction using whole genome linked-reads

2018 ◽  
Author(s):  
Peng Xu ◽  
Zechen Chong ◽  
Keyword(s):  
Meiotic Recombination ◽  
Haplotype Diversity ◽  
Genomic Analysis ◽  
Genomic Diversity ◽  
Pedigree Information ◽  
Human Populations ◽  
Whole Genome ◽  
Homologous Chromosomes ◽  
Template Strand ◽  
Recombination Hotspots

AbstractMeiotic recombination (MR), which transmits exchanged genetic materials between homologous chromosomes to offspring, plays a crucial role in shaping genomic diversity in eukaryotic organisms. In humans, thousands of meiotic recombination hotspots have been mapped by population genetics approaches. However, direct identification of MR events for individuals is still challenging due to the difficulty in resolving the haplotypes of homologous chromosomes and reconstructing the gamete genome. Whole genome linked-read sequencing (lrWGS) can generate haplotype sequences of mega-base pairs (N50 ~2.5Mb) after computational phasing. However, the haplotype information is still isolated in a large number of fragmented genomic regions and limited by switch errors, impeding its further application in the chromosome-scale analysis. In this study, we developed a tool MRLR (Meiotic Recombination identification by Linked-Read sequencing) for the analysis of individual MR events. By leveraging trio pedigree information with lrWGS haplotypes, our pipeline is sufficient to reconstruct the whole human gamete genome with 99.8% haplotyping accuracy. By analyzing the haplotype exchange between homologous chromosomes, MRLR identified 462 high-resolution MR events in 6 human trio samples from the Genome In A Bottle (GIAB) and the Human Genome Structural Variation Consortium (HGSVC). In three datasets of the HGSVC, our results recapitulated 149 (92%) previously identified high-confident MR events and discovered 85 novel events. About half (40) of the new events are supported by single-cell template strand sequencing (Strand-seq) results. We found that 332 (71.9%) MR events co-localize with recombination hotspots (>10 cM/Mb) in human populations, and MR breakpoint regions are enriched in PRDM9 and DMC1 binding sites. In addition, 48% (221) breakpoint regions were detected inside a gene, indicating these MRs can directly affect the haplotype diversity of genic regions. Taken together, our approach provides new opportunities in the haplotype-based genomic analysis of individual meiotic recombination. The MRLR software is implemented in Perl and is freely available at https://github.com/ChongLab/MRLR.

scholarly journals Whole-genome sequencing analysis of clozapine-induced myocarditis

2021 ◽  
Author(s):  
Ankita Narang ◽  
Paul Lacaze ◽  
Kathlyn Ronaldson ◽  
John McNeil ◽  
Mahesh Jayaram ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Genome Wide Association Study ◽  
Copy Number Variants ◽  
Whole Genome Sequencing Data ◽  
Whole Genome ◽  
Sequencing Analysis ◽  
Sequencing Data ◽  
Dna Variation ◽  
Rare Genetic Variants

One of the concerns limiting the use of clozapine in schizophrenia treatment is the risk of rare but potentially fatal myocarditis. Our previous genome-wide association study and human leucocyte antigen analyses identified putative loci associated with clozapine-induced myocarditis. However, the contribution of DNA variation in cytochrome P450 genes, copy number variants and rare deleterious variants have not been investigated. We explored these unexplored classes of DNA variation using whole-genome sequencing data from 25 cases with clozapine-induced myocarditis and 25 demographically-matched clozapine-tolerant control subjects. We identified 15 genes based on rare variant gene-burden analysis (MLLT6, CADPS, TACC2, L3MBTL4, NPY, SLC25A21, PARVB, GPR179, ACAD9, NOL8, C5orf33, FAM127A, AFDN, SLC6A11, PXDN) nominally associated (p<0.05) with clozapine-induced myocarditis. Of these genes, 13 were expressed in human myocardial tissue. Although independent replication of these findings is required, our study provides preliminary insights into the potential role of rare genetic variants in susceptibility to clozapine-induced myocarditis.

scholarly journals Tracking human population structure through time from whole genome sequences

2019 ◽  
Author(s):  
Ke Wang ◽  
Iain Mathieson ◽  
Jared O’Connell ◽  
Stephan Schiffels
Keyword(s):  
Population Structure ◽  
Gene Flow ◽  
Demographic History ◽  
Time Dependent ◽  
Human Populations ◽  
Whole Genome ◽  
Genome Sequences ◽  
Migration Model ◽  
Novel Approach ◽  
Different Populations

AbstractThe genetic diversity of humans, like many species, has been shaped by a complex pattern of population separations followed by isolation and subsequent admixture. This pattern, reaching at least as far back as the appearance of our species in the paleontological record, has left its traces in our genomes. Reconstructing a population’s history from these traces is a challenging problem. Here we present a novel approach based on the Multiple Sequentially Markovian Coalescent (MSMC) to analyse the population separation history. Our approach, called MSMC-IM, uses an improved implementation of the MSMC (MSMC2) to estimate coalescence rates within and across pairs of populations, and then fits a continuous Isolation-Migration model to these rates to obtain a time-dependent estimate of gene flow. We show, using simulations, that our method can identify complex demographic scenarios involving post-split admixture or archaic introgression. We apply MSMC-IM to whole genome sequences from 15 worldwide populations, tracking the process of human genetic diversification. We detect traces of extremely deep ancestry between some African populations, with around 1% of ancestry dating to divergences older than a million years ago.Author SummaryHuman demographic history is reflected in specific patterns of shared mutations between the genomes from different populations. Here we aim to unravel this pattern to infer population structure through time with a new approach, called MSMC-IM. Based on estimates of coalescence rates within and across populations, MSMC-IM fits a time-dependent migration model to the pairwise rate of coalescences. We implemented this approach as an extension to existing software (MSMC2), and tested it with simulations exhibiting different histories of admixture and gene flow. We then applied it to the genomes from 15 worldwide populations to reveal their pairwise separation history ranging from a few thousand up to several million years ago. Among other results, we find evidence for remarkably deep population structure in some African population pairs, suggesting that deep ancestry dating to one million years ago and older is still present in human populations in small amounts today.

scholarly journals A Likelihood Approach for Uncovering Selective Sweep Signatures from Haplotype Data

2020 ◽  
Vol 37 (10) ◽  
pp. 3023-3046
Author(s):  
Alexandre M Harris ◽  
Michael DeGiorgio
Keyword(s):  
Selective Sweep ◽  
Natural Populations ◽  
Haplotype Frequency ◽  
Human Populations ◽  
Ratio Test ◽  
Whole Genome ◽  
Selective Sweeps ◽  
Test Statistic ◽  
Haplotypic Diversity ◽  
Haplotype Data

Abstract Selective sweeps are frequent and varied signatures in the genomes of natural populations, and detecting them is consequently important in understanding mechanisms of adaptation by natural selection. Following a selective sweep, haplotypic diversity surrounding the site under selection decreases, and this deviation from the background pattern of variation can be applied to identify sweeps. Multiple methods exist to locate selective sweeps in the genome from haplotype data, but none leverages the power of a model-based approach to make their inference. Here, we propose a likelihood ratio test statistic T to probe whole-genome polymorphism data sets for selective sweep signatures. Our framework uses a simple but powerful model of haplotype frequency spectrum distortion to find sweeps and additionally make an inference on the number of presently sweeping haplotypes in a population. We found that the T statistic is suitable for detecting both hard and soft sweeps across a variety of demographic models, selection strengths, and ages of the beneficial allele. Accordingly, we applied the T statistic to variant calls from European and sub-Saharan African human populations, yielding primarily literature-supported candidates, including LCT, RSPH3, and ZNF211 in CEU, SYT1, RGS18, and NNT in YRI, and HLA genes in both populations. We also searched for sweep signatures in Drosophila melanogaster, finding expected candidates at Ace, Uhg1, and Pimet. Finally, we provide open-source software to compute the T statistic and the inferred number of presently sweeping haplotypes from whole-genome data.

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