Genetic Variation and Signatures of Natural Selection in Diverse Africans
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ABSTRACT: Our study identified candidate regions of genome involved in adaptation and identified regions associated with selected phenotypes.
SECONDARY ACCESSION(S): PRJNA89683PRJNA157241
REPOSITORIES: dbGaP
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Project description:<p>Our study identified candidate regions of genome involved in adaptation and identified regions associated with selected phenotypes.</p>
| phs000449.v2.p1 | EGA
Project description:Deciphering the genetic architecture of human cardiac disorders is of fundamental importance but their underlying complexity is a major hurdle. We investigated the natural variation of cardiac performance in the sequenced inbred lines of the Drosophila Genetic Reference Panel (DGRP). Genome Wide Associations Studies (GWAS) identified genetic networks associated with natural variation of cardiac traits which were used to gain insights as to the molecular and cellular processes affected. Non-coding variants that we identified were used to map potential regulatory non-coding regions, which in turn were employed to predict Transcription Factors (TFs) binding sites. Cognate TFs, many of which themselves bear polymorphisms associated with variations of cardiac performance, were also validated by heart specific knockdown. Additionally, we showed that the natural variations associated with variability in cardiac performance affect a set of genes overlapping those associated with average traits but through different variants in the same genes. Furthermore, we showed that phenotypic variability was also associated with natural variation of gene regulatory networks. More importantly, we documented correlations between genes associated with cardiac phenotypes in both flies and humans, which supports a conserved genetic architecture regulating adult cardiac function from arthropods to mammals. Specifically, roles for PAX9 and EGR2 in the regulation of the cardiac rhythm were established in both models, illustrating that the characteristics of natural variations in cardiac function identified in Drosophila can accelerate discovery in humans.
2022-11-23 | GSE217655 | GEO
Project description:Metabolic homeostasis is sustained by complex biological networks that respond to nutrient availability. Genetic and environmental factors may disrupt this equilibrium leading to metabolic disorders, including obesity and type 2 diabetes. To identify the genetic factors controlling metabolism, we performed quantitative genetic analysis using a population of 199 recombinant inbred lines (RILs) in the nematode Caenorhabditis elegans. We focused on the genomic regions that control metabolite levels by measuring fatty acid (FA) and amino acid (AA) composition in the RILs using targeted metabolomics. The genetically diverse RILs showed a large variation in their FA and AA levels with a heritability ranging from 32-82%. We detected strongly co-correlated metabolite clusters and 36 significant metabolite QTL (mQTL). We focused on mQTL displaying highly significant linkage and heritability, including an mQTL for the FA C14:1 on Chromosome I, and another mQTL for the FA C18:2 on Chromosome IV. Using introgression lines (ILs) we were able to narrow down both mQTL to a 1.4 Mbp and a 3.6 Mbp region, respectively. RNAi-based screening focusing on the Chromosome I mQTL identified several candidate genes for the C14:1 mQTL, including lagr-1, Y87G2A.2, nhr-265, nhr-276, and nhr-81. Overall, this systems approach provides us with a powerful platform to study the genetic basis of C. elegans metabolism. Furthermore, it allows us to investigate interventions, such as nutrients and stresses that maintain or disturb the regulatory network controlling metabolic homeostasis, and identify gene-by-environment interactions.
2018-07-05 | ST000999 | MetabolomicsWorkbench
Project description:We report a novel high-throughput method to empirically quantify individual-specific regulatory element activity at the population scale. The approach combines targeted DNA capture with a high-throughput reporter-gene expression assay. As demonstration, we have measured the activity of more than 100 putative regulatory elements from 95 individuals in a single experiment. We found that, in agreement with previous reports, most genetic variants have weak effects on distal regulatory element activity. Because haplotypes are typically maintained within but not between assayed regulatory elements, the approach can be used to identify likely causal regulatory haplotypes that contribute to human phenotypes. Finally, we demonstrate the utility of the method to functionally fine map causal regulatory variants in regions of high linkage disequilibrium identified by expression quantitative trait loci (eQTL) analyses. 104 candidate regulatory elements from 95 individuals were resequenced using Illumina custom amplicon sequencing. We then cloned the resulting DNA fragments into a massively parallel reporter assay to quantify allele-specific regulatory activity from that population. SNP-fdr.txt contains output of significance evaluation haplotype.fasta.gz contains the reference used to generate alignment files
2015-06-15 | E-GEOD-68331 | biostudies-arrayexpress
Project description:We examine whether there are differences in gene expression between aggressive versus nonaggressive behavioral types of individuals within a natural population of male threespined sticklebacks (Gasterosteus aculeatus). We compared gene expression profiles of aggressive male sticklebacks to nonaggressive males in four regions of the brain (brainstem, cerebellum, diencephalon and telencephalon). We identified new candidate genes related to aggressiveness, including SLC38a, a solute carrier which has been linked to GABAergic neuron reuptake of glutamine.
2017-02-28 | GSE78861 | GEO
Project description:Complex traits, including common disease-related traits, are affected by many different genes that function in multiple pathways and networks. The apoptosis, MAPK, Notch and Wnt signalling pathways play important roles in development and disease progression. At the moment we have a poor understanding of how allelic variation affects gene expression in these pathways at the level of translation. Here we report the effect of natural genetic variation on transcript and protein abundance involved in developmental signalling pathways in Caenorhabditis elegans. We used selected reaction monitoring to analyse proteins from the abovementioned four pathways in a set of recombinant inbred lines (RILs) generated from the wild-type strains Bristol N2 and Hawaii CB4856 to enable quantitative trait loci (QTL) mapping. Variation in gene expression was greater in the RILs than in the parental lines, at the proteome as well as at the transcriptome levels. We detected a trans-QTL on the left arm of chromosome II that affected protein abundance of the phosphatidylserine receptor protein PSR-1, and two separate QTLs that influenced embryonic and ionizing radiation-induced apoptosis on chromosome IV. Our results demonstrate that natural variation in C. elegans is sufficient to cause significant changes in signalling pathways both at the gene expression (transcript and protein abundance) and phenotypic levels.
2016-02-16 | GSE77905 | GEO
Project description:Classical laboratory strains show limited genetic diversity and do not harness natural genetic variation. Mouse models relevant to Alzheimer’s disease (AD) have largely been developed using these classical laboratory strains, such as C57BL/6J (B6), and this has likely contributed to the failure of translation of findings from mice to the clinic. Therefore, here we test the potential for natural genetic variation to enhance the translatability of AD mouse models. Two widely used AD-relevant transgenes, APPswe and PS1de9 (APP/PS1), were backcrossed from B6 to three wild-derived strains CAST/EiJ, WSB/EiJ, PWK/PhJ, representative of three Mus musculus subspecies. These new AD strains were characterized using metabolic, functional, neuropathological and transcriptional assays. Strain-, sex- and genotype-specific differences were observed in cognitive ability, neurodegeneration, plaque load, cerebrovascular health and cerebral amyloid angiopathy. Analyses of brain transcriptional data showed strain was the greatest driver of variation. We identified significant variation in myeloid cell numbers in wild type mice of different strains as well as significant differences in plaque-associated myeloid responses in APP/PS1 mice between the strains. Collectively, these data support the use of wild-derived strains to better model the complexity of human AD.
2019-05-22 | GSE131659 | GEO
Project description:Complex traits, including common disease-related traits, are affected by many different genes that function in multiple pathways and networks. The apoptosis, MAPK, Notch and Wnt signalling pathways play important roles in development and disease progression. At the moment we have a poor understanding of how allelic variation affects gene expression in these pathways at the level of translation. Here we report the effect of natural genetic variation on transcript and protein abundance involved in developmental signalling pathways in Caenorhabditis elegans. We used selected reaction monitoring to analyse proteins from the abovementioned four pathways in a set of recombinant inbred lines (RILs) generated from the wild-type strains Bristol N2 and Hawaii CB4856 to enable quantitative trait loci (QTL) mapping. Variation in gene expression was greater in the RILs than in the parental lines, at the proteome as well as at the transcriptome levels. We detected a trans-QTL on the left arm of chromosome II that affected protein abundance of the phosphatidylserine receptor protein PSR-1, and two separate QTLs that influenced embryonic and ionizing radiation-induced apoptosis on chromosome IV. Our results demonstrate that natural variation in C. elegans is sufficient to cause significant changes in signalling pathways both at the gene expression (transcript and protein abundance) and phenotypic levels. Parental genotypes N2 (3x) and CB4856 (3x) and 47 RILs from (Li etal 2006; Vinuela etal 2010 and Elvin etal 2011)
2016-02-16 | E-GEOD-77905 | biostudies-arrayexpress
Project description:Anorexia nervosa (AN), bulimia nervosa (BN), and obsessive-compulsive disorder (OCD) are complex psychiatric disorders with shared obsessive features, thought to arise from the interaction of multiple genes of small effect with environmental factors. Potential candidate genes for AN, BN, and OCD have been identified through clinical association and neuroimaging studies; however, recent genome-wide association studies of eating disorders (ED) so far have failed to report significant findings. Additionally, few if any studies have interrogated postmortem brain tissue for evidence of eQTLs associated with candidate genes, which has particular promise as an approach to elucidating molecular mechanisms of association. We therefore selected single nucleotide polymorphisms (SNPs) based on candidate gene studies for AN, BN, and OCD from the literature, and examined the association of these SNPs with gene expression across the lifespan in prefrontal cortex of a non-psychiatric control cohort (N=268). Several risk-predisposing SNPs were significantly associated with gene expression among control subjects. We then measured gene expression in the prefrontal cortex of cases previously diagnosed with obsessive psychiatric disorders, e.g., eating disorders (ED; N=15), and obsessive-compulsive disorder/obsessive-compulsive personality disorder or tics (OCD/OCPD/Tic; N=16), and non-psychiatric controls (N=102) and identified 6 and 286 genes that were differentially expressed between ED compared to controls and OCD cases compared to controls, respectively (FDR < 5%). However, none of the clinical risk SNPs were among the eQTLs and none were significantly associated with gene expression within the broad obsessive cohort, suggesting larger sample sizes or other brain regions may be required to identify candidate molecular mechanisms of clinical association in postmortem brain datasets. Gene expression data from the dorsolateral prefrontal cortex (DLPFC) from postmortem tissue on 133 subjects - 15 eating disorder (ED) patients, 16 obessive compulsive disorder (OCD) patients, and 102 non-psychiatric controls - run on the Illumina HumanHT-12 v3 microarray
2014-08-08 | E-GEOD-60190 | biostudies-arrayexpress
Project description:A quantitative genetic analysis of the yeast replicative life span was carried out by sampling the natural genetic variation Genomic DNA was extracted from 39 recombinant lines from a cross between strains S96 and YJM 789.
2012-07-17 | E-GEOD-37590 | biostudies-arrayexpress