scholarly journals Gene expression networks in the Drosophila Genetic Reference Panel

2020 ◽  
Vol 30 (3) ◽  
pp. 485-496 ◽  
Author(s):  
Logan J. Everett ◽  
Wen Huang ◽  
Shanshan Zhou ◽  
Mary Anna Carbone ◽  
Richard F. Lyman ◽  
...  
2019 ◽  
Author(s):  
Logan J. Everett ◽  
Wen Huang ◽  
Shanshan Zhou ◽  
Mary Anna Carbone ◽  
Richard F. Lyman ◽  
...  

SummaryA major challenge in modern biology is to understand how naturally occurring variation in DNA sequences affects complex organismal traits through networks of intermediate molecular phenotypes. Here, we performed deep RNA sequencing of 200 Drosophila Genetic Reference Panel inbred lines with complete genome sequences, and mapped expression quantitative trait loci for annotated genes, novel transcribed regions (most of which are long noncoding RNAs), transposable elements and microbial species. We identified host variants that affect expression of transposable elements, independent of their copy number, as well as microbiome composition. We constructed sex-specific expression quantitative trait locus regulatory networks. These networks are enriched for novel transcribed regions and target genes in heterochromatin and euchromatic regions of reduced recombination, and genes regulating transposable element expression. This study provides new insights regarding the role of natural genetic variation in regulating gene expression and generates testable hypotheses for future functional analyses.


2020 ◽  
Vol 156 (1) ◽  
pp. 6-12 ◽  
Author(s):  
Paulette Mhawech-Fauceglia ◽  
Iyare Izevbaye ◽  
Tassja Spindler ◽  
Guisong Wang ◽  
Helena Hwang ◽  
...  

Genetics ◽  
2021 ◽  
Author(s):  
Jacinta Davis ◽  
Claire Da Silva Santos ◽  
Narda Caudillo Zavala ◽  
Nicholas Gans ◽  
Daniel Patracuolla ◽  
...  

Abstract Parkinson’s Disease (PD) is primarily characterized by the loss of dopaminergic (DA) neurons in the brain. However, little is known about why DA neurons are selectively vulnerable to PD. To identify genes that are associated with DA neuron loss, we screened through 201 wild-caught populations of Drosophila melanogaster as part of the Drosophila Genetic Reference Panel (DGRP). Here we identify the top associated genes containing SNPs that render DA neurons vulnerable. These genes were further analyzed by using mutant analysis and tissue-specific knockdown for functional validation. We found that this loss of DA neurons caused progressive locomotor dysfunction in mutants and gene knockdown analysis. The identification of genes associated with the progressive loss of DA neurons should help to uncover factors that render these neurons vulnerable in PD, and possibly develop strategies to make these neurons more resilient.


Genes ◽  
2021 ◽  
Vol 12 (7) ◽  
pp. 1049
Author(s):  
Jia Wen ◽  
Munan Xie ◽  
Bryce Rowland ◽  
Jonathan D. Rosen ◽  
Quan Sun ◽  
...  

Background: Thousands of genetic variants have been associated with hematological traits, though target genes remain unknown at most loci. Moreover, limited analyses have been conducted in African ancestry and Hispanic/Latino populations; hematological trait associated variants more common in these populations have likely been missed. Methods: To derive gene expression prediction models, we used ancestry-stratified datasets from the Multi-Ethnic Study of Atherosclerosis (MESA, including n = 229 African American and n = 381 Hispanic/Latino participants, monocytes) and the Depression Genes and Networks study (DGN, n = 922 European ancestry participants, whole blood). We then performed a transcriptome-wide association study (TWAS) for platelet count, hemoglobin, hematocrit, and white blood cell count in African (n = 27,955) and Hispanic/Latino (n = 28,324) ancestry participants. Results: Our results revealed 24 suggestive signals (p < 1 × 10−4) that were conditionally distinct from known GWAS identified variants and successfully replicated these signals in European ancestry subjects from UK Biobank. We found modestly improved correlation of predicted and measured gene expression in an independent African American cohort (the Genetic Epidemiology Network of Arteriopathy (GENOA) study (n = 802), lymphoblastoid cell lines) using the larger DGN reference panel; however, some genes were well predicted using MESA but not DGN. Conclusions: These analyses demonstrate the importance of performing TWAS and other genetic analyses across diverse populations and of balancing sample size and ancestry background matching when selecting a TWAS reference panel.


Author(s):  
Jia Wen ◽  
Munan Xie ◽  
Bryce Rowland ◽  
Jonathan D. Rosen ◽  
Quan Sun ◽  
...  

Background: Thousands of genetic variants have been associated with hematological traits, though target genes remain unknown at most loci. Also, limited analyses have been conducted in African ancestry and Hispanic/Latino populations; hematological trait associated variants more common in these populations have likely been missed. Methods: To derive gene expression prediction models, we used ancestry-stratified datasets from the Multi-Ethnic Study of Atherosclerosis (MESA, including N=229 African American and N=381 Hispanic/Latino participants, monocytes) and the Depression Genes and Networks study (DGN, N = 922 European ancestry participants, whole blood). We then performed a transcriptome-wide association study (TWAS) for platelet count, hemoglobin, hematocrit, and white blood cell count in African (N = 27,955) and Hispanic/Latino (N = 28,324) ancestry participants. Results: Our results revealed 24 suggestive signals (p &lt; 1&times;10^(-4)) that were conditionally distinct from known GWAS identified variants and successfully replicated these signals in European ancestry subjects from UK Biobank. We found modestly improved correlation of predicted and measured gene expression in an independent African American cohort (the Genetic Epidemiology Network of Arteriopathy (GENOA) study (N=802), lymphoblastoid cell lines) using the larger DGN reference panel; however, some genes were well predicted using MESA but not DGN. Conclusions: These analyses demonstrate the importance of performing TWAS and other genetic analyses across diverse populations and of balancing sample size and ancestry background matching when selecting a TWAS reference panel.


2015 ◽  
Author(s):  
John E Pool

North American populations of Drosophila melanogaster are thought to derive from both European and African source populations, but despite their importance for genetic research, patterns of admixture along their genomes are essentially undocumented. Here, I infer geographic ancestry along genomes of the Drosophila Genetic Reference Panel (DGRP) and the D. melanogaster reference genome. Overall, the proportion of African ancestry was estimated to be 20% for the DGRP and 9% for the reference genome. Based on the size of admixture tracts and the approximate timing of admixture, I estimate that the DGRP population underwent roughly 13.9 generations per year. Notably, ancestry levels varied strikingly among genomic regions, with significantly less African introgression on the X chromosome, in regions of high recombination, and at genes involved in specific processes such as circadian rhythm. An important role for natural selection during the admixture process was further supported by a genome-wide signal of ancestry disequilibrium, in that many between-chromosome pairs of loci showed a deficiency of Africa-Europe allele combinations. These results support the hypothesis that admixture between partially genetically isolated Drosophila populations led to natural selection against incompatible genetic variants, and that this process is ongoing. The ancestry blocks inferred here may be relevant for the performance of reference alignment in this species, and may bolster the design and interpretation of many population genetic and association mapping studies.


2020 ◽  
Vol 21 (1) ◽  
Author(s):  
Michael V. Frochaux ◽  
Maroun Bou Sleiman ◽  
Vincent Gardeux ◽  
Riccardo Dainese ◽  
Brian Hollis ◽  
...  

2019 ◽  
Vol 1 (12) ◽  
pp. 1226-1242 ◽  
Author(s):  
Roel P. J. Bevers ◽  
Maria Litovchenko ◽  
Adamandia Kapopoulou ◽  
Virginie S. Braman ◽  
Matthew R. Robinson ◽  
...  

2020 ◽  
Author(s):  
Jie Yuan ◽  
Ben Lai ◽  
Itsik Pe’er

1AbstractTranscriptome-Wide Association Studies discover SNP effects mediated by gene expression through a two-stage process: a typically small reference panel is used to infer SNP-expression effects, and then these are applied to discover associations between imputed expression and phenotypes. We investigate whether the accuracy of SNP-expression and expression-phenotype associations can be increased by performing inference on both the reference panel and independent GWAS cohorts simultaneously. We develop EMBER (Estimation of Mediated Binary Effects in Regression) to re-estimate these effects using a liability threshold model with an adjustment to variance components accounting for imputed expression from GWAS data. In simulated data with only gene-mediated effects, EMBER more than doubles the performance of SNP-expression linear regression, increasing mean r2 from 0.3 to 0.65 with a gene-mediated variance explained of 0.01. EMBER also improves estimation accuracy when the fraction of cis-SNP variance mediated by genes is as low as 30%. We apply EMBER to genotype and gene expression data in schizophrenia by combining 512 samples from the CommonMind Consortium and 56,081 samples from the Psychiatric Genomic Consortium. We evaluate performance of EMBER in 36 genes suggested by TWAS by concordance of inferred effects with effects reported independently for frontal cortex expression. Applying the EMBER framework to a baseline linear regression model increases performance in 26 out of 36 genes (sign test p-value .0020) with an increase in mean r2 from 0.200 to 0.235.


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