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Analysis of natural variation reveals neurogenetic networks for Drosophila olfactory behavior

机译:对自然变异的分析揭示了果蝇嗅觉行为的神经遗传网络

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摘要

Understanding the relationship between genetic variation and phenotypic variation for quantitative traits is necessary for predicting responses to natural and artificial selection and disease risk in human populations, but is challenging because of large sample sizes required to detect and validate loci with small effects. Here, we used the inbred, sequenced, wild-derived lines of the Drosophila melanogaster Genetic Reference Panel (DGRP) to perform three complementary genome-wide association (GWA) studies for natural variation in olfactory behavior. The first GWA focused on single nucleotide polymorphisms (SNPs) associated with mean differences in olfactory behavior in the DGRP, the second was an extreme quantitative trait locus GWA on an outbred advanced intercross population derived from extreme DGRP lines, and the third was for SNPs affecting the variance among DGRP lines. No individual SNP in any analysis was associated with variation in olfactory behavior by using a strict threshold accounting for multiple tests, and no SNP overlapped among the analyses. However, combining the top SNPs from all three analyses revealed a statistically enriched network of genes involved in cellular signaling and neural development. We used mu-tational and gene expression analyses to validate both candidate genes and network connectivity at a high rate. The lack of replication between the GWA analyses, small marginal SNP effects, and convergence on common cellular networks were likely attributable to epistasis. These results suggest that fully understanding the ge-notype-phenotype relationship requires a paradigm shift from a focus on single SNPs to pathway associations.
机译:了解数量变异性的遗传变异和表型变异之间的关系对于预测人类对自然选择和人工选择的反应以及疾病风险是必要的,但由于检测和验证基因座所需的样本量较大且影响较小,因此具有挑战性。在这里,我们使用果蝇果蝇遗传参考小组(DGRP)的近交,测序,野生来源品系进行三个互补的全基因组关联(GWA)研究,以研究嗅觉行为的自然变化。第一个GWA专注于与DGRP中嗅觉行为的平均差异相关的单核苷酸多态性(SNP),第二个是源自极端DGRP系的远交远交杂交群体的极端数量性状基因座GWA,第三个是针对影响SNP的DGRP线之间的差异。通过对多个测试使用严格的阈值,在任何分析中没有单个SNP与嗅觉行为的变化相关,并且在分析之间没有SNP重叠。但是,将所有这三个分析的最高SNP组合在一起,揭示了一个统计丰富的网络基因,参与了细胞信号传导和神经发育。我们使用突变和基因表达分析来高效率地验证候选基因和网络连接性。 GWA分析之间缺乏重复性,SNP的边际效应较小,以及常见细胞网络的趋同性很可能归因于上位性。这些结果表明,全面了解ge-notype-phenotype关系需要从关注单个SNP到途径关联的范式转变。

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  • 作者单位

    Departments of Genetics North Carolina State University, Raleigh, NC 27695-7614,Departments of W. M. Keck Center for Behavioral Biology, North Carolina State University, Raleigh, NC 27695-7614,Genome Biology Team, Monsanto Company, Chesterfield, MO 63017;

    Departments of Genetics North Carolina State University, Raleigh, NC 27695-7614,Departments of W. M. Keck Center for Behavioral Biology, North Carolina State University, Raleigh, NC 27695-7614;

    Departments of Genetics North Carolina State University, Raleigh, NC 27695-7614,Departments of W. M. Keck Center for Behavioral Biology, North Carolina State University, Raleigh, NC 27695-7614;

    Departments of Genetics North Carolina State University, Raleigh, NC 27695-7614,Departments of W. M. Keck Center for Behavioral Biology, North Carolina State University, Raleigh, NC 27695-7614;

  • 收录信息 美国《科学引文索引》(SCI);美国《生物学医学文摘》(MEDLINE);美国《化学文摘》(CA);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    genetic architecture; chemosensation; behavioral genetics;

    机译:基因结构化学感觉行为遗传学;
  • 入库时间 2022-08-18 00:39:52

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