Natural genetic variation in transcriptome reflects network structure inferred with major effect mutations

Insulin/TOR and associated phenotypes in Drosophila melanogaster

Sergey V. Nuzhdin, Jennifer A. Brisson, Andrew Pickering, Marta L. Wayne, Lawrence G Harshman, Lauren M. McIntyre

Research output: Contribution to journalArticle

17 Citations (Scopus)

Abstract

Background: A molecular process based genotype-to-phenotype map will ultimately enable us to predict how genetic variation among individuals results in phenotypic alterations. Building such a map is, however, far from straightforward. It requires understanding how molecular variation re-shapes developmental and metabolic networks, and how the functional state of these networks modifies phenotypes in genotype specific way. We focus on the latter problem by describing genetic variation in transcript levels of genes in the InR/TOR pathway among 72 Drosophila melanogaster genotypes. Results: We observe tight co-variance in transcript levels of genes not known to influence each other through direct transcriptional control. We summarize transcriptome variation with factor analyses, and observe strong co-variance of gene expression within the dFOXO-branch and within the TOR-branch of the pathway. Finally, we investigate whether major axes of transcriptome variation shape phenotypes expected to be influenced through the InR/TOR pathway. We find limited evidence that transcript levels of individual upstream genes in the InR/TOR pathway predict fly phenotypes in expected ways. However, there is no evidence that these effects are mediated through the major axes of downstream transcriptome variation. Conclusion: In summary, our results question the assertion of the 'sparse' nature of genetic networks, while validating and extending candidate gene approaches in the analyses of complex traits.

Original languageEnglish (US)
Article number124
JournalBMC genomics
Volume10
DOIs
StatePublished - Mar 24 2009

Fingerprint

Drosophila melanogaster
Transcriptome
Insulin
Phenotype
Mutation
Genotype
Genes
Metabolic Networks and Pathways
Diptera
Statistical Factor Analysis
Gene Expression

ASJC Scopus subject areas

  • Biotechnology
  • Genetics

Cite this

Natural genetic variation in transcriptome reflects network structure inferred with major effect mutations : Insulin/TOR and associated phenotypes in Drosophila melanogaster. / Nuzhdin, Sergey V.; Brisson, Jennifer A.; Pickering, Andrew; Wayne, Marta L.; Harshman, Lawrence G; McIntyre, Lauren M.

In: BMC genomics, Vol. 10, 124, 24.03.2009.

Research output: Contribution to journalArticle

Nuzhdin, Sergey V. ; Brisson, Jennifer A. ; Pickering, Andrew ; Wayne, Marta L. ; Harshman, Lawrence G ; McIntyre, Lauren M. / Natural genetic variation in transcriptome reflects network structure inferred with major effect mutations : Insulin/TOR and associated phenotypes in Drosophila melanogaster. In: BMC genomics. 2009 ; Vol. 10.
@article{e1f5a8a88b584e08847af824774c654a,
title = "Natural genetic variation in transcriptome reflects network structure inferred with major effect mutations: Insulin/TOR and associated phenotypes in Drosophila melanogaster",
abstract = "Background: A molecular process based genotype-to-phenotype map will ultimately enable us to predict how genetic variation among individuals results in phenotypic alterations. Building such a map is, however, far from straightforward. It requires understanding how molecular variation re-shapes developmental and metabolic networks, and how the functional state of these networks modifies phenotypes in genotype specific way. We focus on the latter problem by describing genetic variation in transcript levels of genes in the InR/TOR pathway among 72 Drosophila melanogaster genotypes. Results: We observe tight co-variance in transcript levels of genes not known to influence each other through direct transcriptional control. We summarize transcriptome variation with factor analyses, and observe strong co-variance of gene expression within the dFOXO-branch and within the TOR-branch of the pathway. Finally, we investigate whether major axes of transcriptome variation shape phenotypes expected to be influenced through the InR/TOR pathway. We find limited evidence that transcript levels of individual upstream genes in the InR/TOR pathway predict fly phenotypes in expected ways. However, there is no evidence that these effects are mediated through the major axes of downstream transcriptome variation. Conclusion: In summary, our results question the assertion of the 'sparse' nature of genetic networks, while validating and extending candidate gene approaches in the analyses of complex traits.",
author = "Nuzhdin, {Sergey V.} and Brisson, {Jennifer A.} and Andrew Pickering and Wayne, {Marta L.} and Harshman, {Lawrence G} and McIntyre, {Lauren M.}",
year = "2009",
month = "3",
day = "24",
doi = "10.1186/1471-2164-10-124",
language = "English (US)",
volume = "10",
journal = "BMC Genomics",
issn = "1471-2164",
publisher = "BioMed Central",

}

TY - JOUR

T1 - Natural genetic variation in transcriptome reflects network structure inferred with major effect mutations

T2 - Insulin/TOR and associated phenotypes in Drosophila melanogaster

AU - Nuzhdin, Sergey V.

AU - Brisson, Jennifer A.

AU - Pickering, Andrew

AU - Wayne, Marta L.

AU - Harshman, Lawrence G

AU - McIntyre, Lauren M.

PY - 2009/3/24

Y1 - 2009/3/24

N2 - Background: A molecular process based genotype-to-phenotype map will ultimately enable us to predict how genetic variation among individuals results in phenotypic alterations. Building such a map is, however, far from straightforward. It requires understanding how molecular variation re-shapes developmental and metabolic networks, and how the functional state of these networks modifies phenotypes in genotype specific way. We focus on the latter problem by describing genetic variation in transcript levels of genes in the InR/TOR pathway among 72 Drosophila melanogaster genotypes. Results: We observe tight co-variance in transcript levels of genes not known to influence each other through direct transcriptional control. We summarize transcriptome variation with factor analyses, and observe strong co-variance of gene expression within the dFOXO-branch and within the TOR-branch of the pathway. Finally, we investigate whether major axes of transcriptome variation shape phenotypes expected to be influenced through the InR/TOR pathway. We find limited evidence that transcript levels of individual upstream genes in the InR/TOR pathway predict fly phenotypes in expected ways. However, there is no evidence that these effects are mediated through the major axes of downstream transcriptome variation. Conclusion: In summary, our results question the assertion of the 'sparse' nature of genetic networks, while validating and extending candidate gene approaches in the analyses of complex traits.

AB - Background: A molecular process based genotype-to-phenotype map will ultimately enable us to predict how genetic variation among individuals results in phenotypic alterations. Building such a map is, however, far from straightforward. It requires understanding how molecular variation re-shapes developmental and metabolic networks, and how the functional state of these networks modifies phenotypes in genotype specific way. We focus on the latter problem by describing genetic variation in transcript levels of genes in the InR/TOR pathway among 72 Drosophila melanogaster genotypes. Results: We observe tight co-variance in transcript levels of genes not known to influence each other through direct transcriptional control. We summarize transcriptome variation with factor analyses, and observe strong co-variance of gene expression within the dFOXO-branch and within the TOR-branch of the pathway. Finally, we investigate whether major axes of transcriptome variation shape phenotypes expected to be influenced through the InR/TOR pathway. We find limited evidence that transcript levels of individual upstream genes in the InR/TOR pathway predict fly phenotypes in expected ways. However, there is no evidence that these effects are mediated through the major axes of downstream transcriptome variation. Conclusion: In summary, our results question the assertion of the 'sparse' nature of genetic networks, while validating and extending candidate gene approaches in the analyses of complex traits.

UR - http://www.scopus.com/inward/record.url?scp=65349152442&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=65349152442&partnerID=8YFLogxK

U2 - 10.1186/1471-2164-10-124

DO - 10.1186/1471-2164-10-124

M3 - Article

VL - 10

JO - BMC Genomics

JF - BMC Genomics

SN - 1471-2164

M1 - 124

ER -