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Genetical Genomics of Behavior: A Novel Chicken Genomic Model for Anxiety Behavior.

ABSTRACT: The identification of genetic variants responsible for behavioral variation is an enduring goal in biology, with wide-scale ramifications, ranging from medical research to evolutionary theory on personality syndromes. Here, we use for the first time a large-scale genetical genomics analysis in the brains of chickens to identify genes affecting anxiety as measured by an open field test. We combine quantitative trait locus (QTL) analysis in 572 individuals and expression QTL (eQTL) analysis in 129 individuals from an advanced intercross between domestic chickens and Red Junglefowl. We identify 10 putative quantitative trait genes affecting anxiety behavior. These genes were tested for an association in the mouse Heterogeneous Stock anxiety (open field) data set and human GWAS data sets for bipolar disorder, major depressive disorder, and schizophrenia. Although comparisons between species are complex, associations were observed for four of the candidate genes in mice and three of the candidate genes in humans. Using a multimodel approach we have therefore identified a number of putative quantitative trait genes affecting anxiety behavior, principally in chickens but also with some potentially translational effects as well. This study demonstrates that chickens are an excellent model organism for the genetic dissection of behavior.

SUBMITTER: Johnsson M

PROVIDER: S-EPMC4701096 | biostudies-literature | 2016 Jan

REPOSITORIES: biostudies-literature

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Genetical Genomics of Behavior: A Novel Chicken Genomic Model for Anxiety Behavior.

Johnsson Martin M Williams Michael J MJ Jensen Per P Wright Dominic D

Genetics 20160101 1

The identification of genetic variants responsible for behavioral variation is an enduring goal in biology, with wide-scale ramifications, ranging from medical research to evolutionary theory on personality syndromes. Here, we use for the first time a large-scale genetical genomics analysis in the brains of chickens to identify genes affecting anxiety as measured by an open field test. We combine quantitative trait locus (QTL) analysis in 572 individuals and expression QTL (eQTL) analysis in 129 ...[more]

PMID: 26733665

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Project description:BackgroundLeaf morphology varies extensively among plant species and is under strong genetic control. Mutagenic screens in model systems have identified genes and established molecular mechanisms regulating leaf initiation, development, and shape. However, it is not known whether this diversity across plant species is related to naturally occurring variation at these genes. Quantitative trait locus (QTL) analysis has revealed a polygenic control for leaf shape variation in different species suggesting that loci discovered by mutagenesis may only explain part of the naturally occurring variation in leaf shape. Here we undertook a genetical genomics study in a poplar intersectional pseudo-backcross pedigree to identify genetic factors controlling leaf shape. The approach combined QTL discovery in a genetic linkage map anchored to the Populus trichocarpa reference genome sequence and transcriptome analysis.ResultsA major QTL for leaf lamina width and length:width ratio was identified in multiple experiments that confirmed its stability. A transcriptome analysis of expanding leaf tissue contrasted gene expression between individuals with alternative QTL alleles, and identified an ADP-ribosylation factor (ARF) GTPase (PtARF1) as a candidate gene for regulating leaf morphology in this pedigree. ARF GTPases are critical elements in the vesicular trafficking machinery. Disruption of the vesicular trafficking function of ARF by the pharmacological agent Brefeldin A (BFA) altered leaf lateral growth in the narrow-leaf P. trichocarpa suggesting a molecular mechanism of leaf shape determination. Inhibition of the vesicular trafficking processes by BFA interferes with cycling of PIN proteins and causes their accumulation in intercellular compartments abolishing polar localization and disrupting normal auxin flux with potential effects on leaf expansion.ConclusionsIn other model systems, ARF proteins have been shown to control the localization of auxin efflux carriers, which function to establish auxin gradients and apical-basal cell polarity in developing plant organs. Our results support a model where PtARF1 transcript abundance changes the dynamics of endocytosis-mediated PIN localization in leaf cells, thus affecting lateral auxin flux and subsequently lamina leaf expansion. This suggests that evolution of differential cellular polarity plays a significant role in leaf morphological variation observed in subgenera of genus Populus.

Project description:CD4(+) T-cells mediate inflammation in atherosclerosis, but additive genetic effects on associated pathways of Th1 and Th2 immune response have not been described. We sought to characterize heritability, pleiotropy, and QTL effects on the expression of genes implicated in Th1 and Th2 immune response in a baboon model of risk factors for atherosclerosis.We employed a maximum likelihood-based variance decomposition approach to estimate additive genetic effects on transcript levels generated from a gene expression profile of lymphocytes in 499 pedigreed baboons maintained on a basal diet. Transcript levels for 57 genes implicated in Th1 and Th2 immune response were selected for analysis based on significant heritability in this profile. Multipoint whole genome scans were conducted on heritable transcript levels to localize QTLs influencing these measures. To evaluate pleiotropic effects on transcript levels, we estimated genetic and phenotypic correlations among transcript measures, and assessed their correspondence using a Mantel test. Network analysis using GeneGo's MetaCore™ software was conducted to characterize known interaction among coded proteins.Heritabilities for candidate gene transcript levels ranged from 0.092-0.786 (median h(2)=0.278, P=4.72×10(-4)). Linkage analyses yielded significant evidence (LOD?2.73) for 14 eQTLs (LOD score range 2.76-14.87, genome-wide P=4.9×10(-2)-1.03×10(-14)). Estimates of genetic correlation supported shared additive genetic effects incorporating all 57 transcripts (null hypothesis of ?(G)=0 rejected at FDR?0.05 for 522 of 1596 estimates), and accounted for most of the observed phenotypic correlation among transcripts (Mantel test, r([?P],)([?G])=0.781, P<0.0001). Network analysis revealed direct interactions among 54 of the 57 coded proteins.We conclude that major genetic effects influence expression levels of multiple genes implicated in Th1 and Th2 immune response. Additionally, we find that expression levels of these candidate genes are characterized by extensive pleiotropy, consistent with known interaction among their coded proteins, many of which are independently associated with atherosclerosis.

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Genetical Genomics of Behavior: A Novel Chicken Genomic Model for Anxiety Behavior.

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Genetical Genomics of Behavior: A Novel Chicken Genomic Model for Anxiety Behavior.

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