Transcriptome Sequencing from Diverse Human Populations Reveals Differentiated Regulatory Architecture
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{"title"=>"Transcriptome Sequencing from Diverse Human Populations Reveals Differentiated Regulatory Architecture", "type"=>"journal", "authors"=>[{"first_name"=>"Alicia R.", "last_name"=>"Martin", "scopus_author_id"=>"56090863600"}, {"first_name"=>"Helio A.", "last_name"=>"Costa", "scopus_author_id"=>"56954501200"}, {"first_name"=>"Tuuli", "last_name"=>"Lappalainen", "scopus_author_id"=>"14323311700"}, {"first_name"=>"Brenna M.", "last_name"=>"Henn", "scopus_author_id"=>"6508347528"}, {"first_name"=>"Jeffrey M.", "last_name"=>"Kidd", "scopus_author_id"=>"27171424500"}, {"first_name"=>"Muh Ching", "last_name"=>"Yee", "scopus_author_id"=>"7006098142"}, {"first_name"=>"Fabian", "last_name"=>"Grubert", "scopus_author_id"=>"17345891500"}, {"first_name"=>"Howard M.", "last_name"=>"Cann", "scopus_author_id"=>"7005847684"}, {"first_name"=>"Michael", "last_name"=>"Snyder", "scopus_author_id"=>"35355673100"}, {"first_name"=>"Stephen B.", "last_name"=>"Montgomery", "scopus_author_id"=>"8708455800"}, {"first_name"=>"Carlos D.", "last_name"=>"Bustamante", "scopus_author_id"=>"35228607000"}], "year"=>2014, "source"=>"PLoS Genetics", "identifiers"=>{"sgr"=>"84922296279", "pui"=>"607876021", "isbn"=>"10.1371/journal.pgen.1004549", "doi"=>"10.1371/journal.pgen.1004549", "issn"=>"15537404", "scopus"=>"2-s2.0-84922296279", "pmid"=>"25121757"}, "id"=>"b03be8bb-0615-38a7-b105-499b6f126325", "abstract"=>"Large-scale sequencing efforts have documented extensive genetic variation within the human genome. However, our understanding of the origins, global distribution, and functional consequences of this variation is far from complete. While regulatory variation influencing gene expression has been studied within a handful of populations, the breadth of transcriptome differences across diverse human populations has not been systematically analyzed. To better understand the spectrum of gene expression variation, alternative splicing, and the population genetics of regulatory variation in humans, we have sequenced the genomes, exomes, and transcriptomes of EBV transformed lymphoblastoid cell lines derived from 45 individuals in the Human Genome Diversity Panel (HGDP). The populations sampled span the geographic breadth of human migration history and include Namibian San, Mbuti Pygmies of the Democratic Republic of Congo, Algerian Mozabites, Pathan of Pakistan, Cambodians of East Asia, Yakut of Siberia, and Mayans of Mexico. We discover that approximately 25.0% of the variation in gene expression found amongst individuals can be attributed to population differences. However, we find few genes that are systematically differentially expressed among populations. Of this population-specific variation, 75.5% is due to expression rather than splicing variability, and we find few genes with strong evidence for differential splicing across populations. Allelic expression analyses indicate that previously mapped common regulatory variants identified in eight populations from the International Haplotype Map Phase 3 project have similar effects in our seven sampled HGDP populations, suggesting that the cellular effects of common variants are shared across diverse populations. Together, these results provide a resource for studies analyzing functional differences across populations by estimating the degree of shared gene expression, alternative splicing, and regulatory genetics across populations from the broadest points of human migration history yet sampled.", "link"=>"http://www.mendeley.com/research/transcriptome-sequencing-diverse-human-populations-reveals-differentiated-regulatory-architecture", "reader_count"=>112, "reader_count_by_academic_status"=>{"Professor > Associate Professor"=>11, "Researcher"=>26, "Student > Doctoral Student"=>2, "Student > Ph. D. Student"=>47, "Student > Postgraduate"=>3, "Student > Master"=>9, "Other"=>5, "Student > Bachelor"=>6, "Professor"=>3}, "reader_count_by_user_role"=>{"Professor > Associate Professor"=>11, "Researcher"=>26, "Student > Doctoral Student"=>2, "Student > Ph. D. Student"=>47, "Student > Postgraduate"=>3, "Student > Master"=>9, "Other"=>5, "Student > Bachelor"=>6, "Professor"=>3}, "reader_count_by_subject_area"=>{"Unspecified"=>2, "Biochemistry, Genetics and Molecular Biology"=>20, "Agricultural and Biological Sciences"=>86, "Medicine and Dentistry"=>2, "Physics and Astronomy"=>1, "Immunology and Microbiology"=>1}, "reader_count_by_subdiscipline"=>{"Medicine and Dentistry"=>{"Medicine and Dentistry"=>2}, "Physics and Astronomy"=>{"Physics and Astronomy"=>1}, "Immunology and Microbiology"=>{"Immunology and Microbiology"=>1}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>86}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>20}, "Unspecified"=>{"Unspecified"=>2}}, "reader_count_by_country"=>{"United States"=>4, "United Kingdom"=>3, "Spain"=>1, "Canada"=>1, "Netherlands"=>1, "Austria"=>1, "Sweden"=>1, "Brazil"=>2, "South Africa"=>1, "Mexico"=>1, "Italy"=>1, "France"=>1, "Germany"=>1}, "group_count"=>3}

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/1636851"], "description"=>"<p>A) Distribution of percent variance explained by population across n = 5,334 expressed genes with ≥2 transcripts expressed across all individuals. B) Empirical p-values for genes in part A. P-values were calculated by permuting population labels for individuals 100 times and comparing to true population labels. Dashed line indicates the uniform p-value distribution expected under the null hypothesis of no association between population label and expression. The output from the multiplicative model can be interpreted similarly to an R<sup>2</sup> coefficient of a linear model. C) The contribution of gene expression in the variance explained by the population.</p>", "links"=>[], "tags"=>["gene expression", "migration history", "Diverse Human Populations", "International Haplotype Map Phase 3 project", "Allelic expression analyses", "gene expression variation", "hgdp", "lymphoblastoid cell lines", "Human Genome Diversity Panel", "ebv"], "article_id"=>1139963, "categories"=>["Biological Sciences"], "users"=>["Alicia R. Martin", "Helio A. Costa", "Tuuli Lappalainen", "Brenna M. Henn", "Jeffrey M. Kidd", "Muh-Ching Yee", "Fabian Grubert", "Howard M. Cann", "Michael Snyder", "Stephen B. Montgomery", "Carlos D. Bustamante"], "doi"=>"https://dx.doi.org/10.1371/journal.pgen.1004549.g005", "stats"=>{"downloads"=>16, "page_views"=>18, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Analysis_of_variation_in_gene_expression_and_splicing_among_individuals_attributable_to_population_labels_/1139963", "title"=>"Analysis of variation in gene expression and splicing among individuals attributable to population labels.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-08-14 11:24:16"}
  • {"files"=>["https://ndownloader.figshare.com/files/1636865"], "description"=>"<p>Each sashimi plot shows the expression within an individual for a differentially spliced gene (ENSG00000183291.11, SEP15). The RNA-seq read densities supporting expression over the region as well as the inclusion and exclusion of exons are shown and line densities are proportional to reads supporting splicing events. The y-axis on each sashimi plot indicates the expression in log<sub>10</sub> reads per kilobase per million reads (log<sub>10</sub>(RPKM)). The plots on the bottom show the transcript structure within the gene.</p>", "links"=>[], "tags"=>["gene expression", "migration history", "Diverse Human Populations", "International Haplotype Map Phase 3 project", "Allelic expression analyses", "gene expression variation", "hgdp", "lymphoblastoid cell lines", "Human Genome Diversity Panel", "ebv"], "article_id"=>1139977, "categories"=>["Biological Sciences"], "users"=>["Alicia R. Martin", "Helio A. Costa", "Tuuli Lappalainen", "Brenna M. Henn", "Jeffrey M. Kidd", "Muh-Ching Yee", "Fabian Grubert", "Howard M. Cann", "Michael Snyder", "Stephen B. Montgomery", "Carlos D. Bustamante"], "doi"=>"https://dx.doi.org/10.1371/journal.pgen.1004549.g006", "stats"=>{"downloads"=>1, "page_views"=>44, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Splicing_variability_across_human_populations_/1139977", "title"=>"Splicing variability across human populations.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-08-14 11:24:16"}
  • {"files"=>["https://ndownloader.figshare.com/files/1636849"], "description"=>"<p>* indicates p<0.05, ** indicates p<0.01, *** indicates p<0.001. ρ<sup>2</sup> values in this dataset were filtered to the same minimum threshold as in the HapMap3 study for consistency.</p>", "links"=>[], "tags"=>["gene expression", "migration history", "Diverse Human Populations", "International Haplotype Map Phase 3 project", "Allelic expression analyses", "gene expression variation", "hgdp", "lymphoblastoid cell lines", "Human Genome Diversity Panel", "ebv"], "article_id"=>1139962, "categories"=>["Biological Sciences"], "users"=>["Alicia R. Martin", "Helio A. Costa", "Tuuli Lappalainen", "Brenna M. Henn", "Jeffrey M. Kidd", "Muh-Ching Yee", "Fabian Grubert", "Howard M. Cann", "Michael Snyder", "Stephen B. Montgomery", "Carlos D. Bustamante"], "doi"=>"https://dx.doi.org/10.1371/journal.pgen.1004549.g004", "stats"=>{"downloads"=>0, "page_views"=>20, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Comparison_between_eQTL_correlations_2_discovered_in_HapMap3_vs_replicated_in_HGDP_/1139962", "title"=>"Comparison between eQTL correlations (ρ<sup>2</sup>) discovered in HapMap3 vs replicated in HGDP.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-08-14 11:24:16"}
  • {"files"=>["https://ndownloader.figshare.com/files/1636833"], "description"=>"<p>A) F<sub>ST</sub> matrix with 100*F<sub>ST</sub> values shown in the upper half and B) tree generated via hierarchical clustering. C–F) Principal components analysis (PCA) of genetic (C and D) and expression (E and F) values. Genetic values are from exome variants, which were called from high coverage (96X) sequence data.</p>", "links"=>[], "tags"=>["gene expression", "migration history", "Diverse Human Populations", "International Haplotype Map Phase 3 project", "Allelic expression analyses", "gene expression variation", "hgdp", "lymphoblastoid cell lines", "Human Genome Diversity Panel", "ebv"], "article_id"=>1139944, "categories"=>["Biological Sciences"], "users"=>["Alicia R. Martin", "Helio A. Costa", "Tuuli Lappalainen", "Brenna M. Henn", "Jeffrey M. Kidd", "Muh-Ching Yee", "Fabian Grubert", "Howard M. Cann", "Michael Snyder", "Stephen B. Montgomery", "Carlos D. Bustamante"], "doi"=>"https://dx.doi.org/10.1371/journal.pgen.1004549.g002", "stats"=>{"downloads"=>0, "page_views"=>8, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Analysis_of_genetic_and_expression_divergence_among_individuals_and_populations_/1139944", "title"=>"Analysis of genetic and expression divergence among individuals and populations.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-08-14 11:24:16"}
  • {"files"=>["https://ndownloader.figshare.com/files/1636835"], "description"=>"<p>Bottom plots show exon positions indicated by rectangles to physical position scale. Red rectangles are differentially expressed exons. Upper plots show the median conditionally quantile normalized (CQN) expression values per population of each exon in horizontal lines. Diagonal lines connect each exon. Each exon corresponds one-to-one with the transcript structure shown below but have been scaled evenly to the width of the plot for ease of visualization. Population orders on the right correspond with the order of expression values of the last exon. A) Expression by population of the uc002yzh.3 transcript of MX1. B) Expression by population of the uc001lui.3 transcript of LSP1.</p>", "links"=>[], "tags"=>["gene expression", "migration history", "Diverse Human Populations", "International Haplotype Map Phase 3 project", "Allelic expression analyses", "gene expression variation", "hgdp", "lymphoblastoid cell lines", "Human Genome Diversity Panel", "ebv"], "article_id"=>1139947, "categories"=>["Biological Sciences"], "users"=>["Alicia R. Martin", "Helio A. Costa", "Tuuli Lappalainen", "Brenna M. Henn", "Jeffrey M. Kidd", "Muh-Ching Yee", "Fabian Grubert", "Howard M. Cann", "Michael Snyder", "Stephen B. Montgomery", "Carlos D. Bustamante"], "doi"=>"https://dx.doi.org/10.1371/journal.pgen.1004549.g003", "stats"=>{"downloads"=>0, "page_views"=>14, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Differential_expression_across_human_populations_/1139947", "title"=>"Differential expression across human populations.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-08-14 11:24:16"}
  • {"files"=>["https://ndownloader.figshare.com/files/1636866"], "description"=>"<p>RNA-sequencing summary.</p>", "links"=>[], "tags"=>["gene expression", "migration history", "Diverse Human Populations", "International Haplotype Map Phase 3 project", "Allelic expression analyses", "gene expression variation", "hgdp", "lymphoblastoid cell lines", "Human Genome Diversity Panel", "ebv"], "article_id"=>1139978, "categories"=>["Biological Sciences"], "users"=>["Alicia R. Martin", "Helio A. Costa", "Tuuli Lappalainen", "Brenna M. Henn", "Jeffrey M. Kidd", "Muh-Ching Yee", "Fabian Grubert", "Howard M. Cann", "Michael Snyder", "Stephen B. Montgomery", "Carlos D. Bustamante"], "doi"=>"https://dx.doi.org/10.1371/journal.pgen.1004549.t001", "stats"=>{"downloads"=>0, "page_views"=>14, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_RNA_sequencing_summary_/1139978", "title"=>"RNA-sequencing summary.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2014-08-14 11:24:16"}
  • {"files"=>["https://ndownloader.figshare.com/files/1636828"], "description"=>"<p>LCLs were immortalized from the populations highlighted above, as described previously <a href=\"http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1004549#pgen.1004549-Cann1\" target=\"_blank\">[21]</a>, and the genomes, exomes, and transcriptomes were sequenced. Founder effect and migration paths have been reproduced from <a href=\"http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1004549#pgen.1004549-Henn2\" target=\"_blank\">[53]</a> to highlight the breadth of human migration history across which these LCLs were sampled.</p>", "links"=>[], "tags"=>["gene expression", "migration history", "Diverse Human Populations", "International Haplotype Map Phase 3 project", "Allelic expression analyses", "gene expression variation", "hgdp", "lymphoblastoid cell lines", "Human Genome Diversity Panel", "ebv"], "article_id"=>1139940, "categories"=>["Biological Sciences"], "users"=>["Alicia R. Martin", "Helio A. Costa", "Tuuli Lappalainen", "Brenna M. Henn", "Jeffrey M. Kidd", "Muh-Ching Yee", "Fabian Grubert", "Howard M. Cann", "Michael Snyder", "Stephen B. Montgomery", "Carlos D. Bustamante"], "doi"=>"https://dx.doi.org/10.1371/journal.pgen.1004549.g001", "stats"=>{"downloads"=>0, "page_views"=>17, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Collection_sites_for_genome_exome_and_RNA_sequenced_human_lymphoblastoid_cell_lines_LCLs_/1139940", "title"=>"Collection sites for genome-, exome-, and RNA-sequenced human lymphoblastoid cell lines (LCLs).", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-08-14 11:24:16"}
  • {"files"=>["https://ndownloader.figshare.com/files/1636937", "https://ndownloader.figshare.com/files/1636938", "https://ndownloader.figshare.com/files/1636939", "https://ndownloader.figshare.com/files/1636940", "https://ndownloader.figshare.com/files/1636941", "https://ndownloader.figshare.com/files/1636942", "https://ndownloader.figshare.com/files/1636944", "https://ndownloader.figshare.com/files/1636945", "https://ndownloader.figshare.com/files/1636946", "https://ndownloader.figshare.com/files/1636947", "https://ndownloader.figshare.com/files/1636948", "https://ndownloader.figshare.com/files/1636949", "https://ndownloader.figshare.com/files/1636950", "https://ndownloader.figshare.com/files/1636951", "https://ndownloader.figshare.com/files/1636952", "https://ndownloader.figshare.com/files/1636953", "https://ndownloader.figshare.com/files/1636954", "https://ndownloader.figshare.com/files/1636955", "https://ndownloader.figshare.com/files/1636956", "https://ndownloader.figshare.com/files/1636957", "https://ndownloader.figshare.com/files/1636958", "https://ndownloader.figshare.com/files/1636960"], "description"=>"<div><p>Large-scale sequencing efforts have documented extensive genetic variation within the human genome. However, our understanding of the origins, global distribution, and functional consequences of this variation is far from complete. While regulatory variation influencing gene expression has been studied within a handful of populations, the breadth of transcriptome differences across diverse human populations has not been systematically analyzed. To better understand the spectrum of gene expression variation, alternative splicing, and the population genetics of regulatory variation in humans, we have sequenced the genomes, exomes, and transcriptomes of EBV transformed lymphoblastoid cell lines derived from 45 individuals in the Human Genome Diversity Panel (HGDP). The populations sampled span the geographic breadth of human migration history and include Namibian San, Mbuti Pygmies of the Democratic Republic of Congo, Algerian Mozabites, Pathan of Pakistan, Cambodians of East Asia, Yakut of Siberia, and Mayans of Mexico. We discover that approximately 25.0% of the variation in gene expression found amongst individuals can be attributed to population differences. However, we find few genes that are systematically differentially expressed among populations. Of this population-specific variation, 75.5% is due to expression rather than splicing variability, and we find few genes with strong evidence for differential splicing across populations. Allelic expression analyses indicate that previously mapped common regulatory variants identified in eight populations from the International Haplotype Map Phase 3 project have similar effects in our seven sampled HGDP populations, suggesting that the cellular effects of common variants are shared across diverse populations. Together, these results provide a resource for studies analyzing functional differences across populations by estimating the degree of shared gene expression, alternative splicing, and regulatory genetics across populations from the broadest points of human migration history yet sampled.</p></div>", "links"=>[], "tags"=>["gene expression", "migration history", "Diverse Human Populations", "International Haplotype Map Phase 3 project", "Allelic expression analyses", "gene expression variation", "hgdp", "lymphoblastoid cell lines", "Human Genome Diversity Panel", "ebv"], "article_id"=>1140018, "categories"=>["Biological Sciences"], "users"=>["Alicia R. Martin", "Helio A. Costa", "Tuuli Lappalainen", "Brenna M. Henn", "Jeffrey M. Kidd", "Muh-Ching Yee", "Fabian Grubert", "Howard M. Cann", "Michael Snyder", "Stephen B. Montgomery", "Carlos D. Bustamante"], "doi"=>["https://dx.doi.org/10.1371/journal.pgen.1004549.s001", "https://dx.doi.org/10.1371/journal.pgen.1004549.s002", "https://dx.doi.org/10.1371/journal.pgen.1004549.s003", "https://dx.doi.org/10.1371/journal.pgen.1004549.s004", "https://dx.doi.org/10.1371/journal.pgen.1004549.s005", "https://dx.doi.org/10.1371/journal.pgen.1004549.s006", "https://dx.doi.org/10.1371/journal.pgen.1004549.s007", "https://dx.doi.org/10.1371/journal.pgen.1004549.s008", "https://dx.doi.org/10.1371/journal.pgen.1004549.s009", "https://dx.doi.org/10.1371/journal.pgen.1004549.s010", "https://dx.doi.org/10.1371/journal.pgen.1004549.s011", "https://dx.doi.org/10.1371/journal.pgen.1004549.s012", "https://dx.doi.org/10.1371/journal.pgen.1004549.s013", "https://dx.doi.org/10.1371/journal.pgen.1004549.s014", "https://dx.doi.org/10.1371/journal.pgen.1004549.s015", "https://dx.doi.org/10.1371/journal.pgen.1004549.s016", "https://dx.doi.org/10.1371/journal.pgen.1004549.s017", "https://dx.doi.org/10.1371/journal.pgen.1004549.s018", "https://dx.doi.org/10.1371/journal.pgen.1004549.s019", "https://dx.doi.org/10.1371/journal.pgen.1004549.s020", "https://dx.doi.org/10.1371/journal.pgen.1004549.s021", "https://dx.doi.org/10.1371/journal.pgen.1004549.s022"], "stats"=>{"downloads"=>52, "page_views"=>21, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Transcriptome_Sequencing_from_Diverse_Human_Populations_Reveals_Differentiated_Regulatory_Architecture_/1140018", "title"=>"Transcriptome Sequencing from Diverse Human Populations Reveals Differentiated Regulatory Architecture", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2014-08-14 11:24:16"}

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