Cargando…

Complex trait subtypes identification using transcriptome profiling reveals an interaction between two QTL affecting adiposity in chicken

BACKGROUND: Integrative genomics approaches that combine genotyping and transcriptome profiling in segregating populations have been developed to dissect complex traits. The most common approach is to identify genes whose eQTL colocalize with QTL of interest, providing new functional hypothesis abou...

Descripción completa

Detalles Bibliográficos
Autores principales: Blum, Yuna, Le Mignon, Guillaume, Causeur, David, Filangi, Olivier, Désert, Colette, Demeure, Olivier, Le Roy, Pascale, Lagarrigue, Sandrine
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3276653/
https://www.ncbi.nlm.nih.gov/pubmed/22103296
http://dx.doi.org/10.1186/1471-2164-12-567
_version_ 1782223394587017216
author Blum, Yuna
Le Mignon, Guillaume
Causeur, David
Filangi, Olivier
Désert, Colette
Demeure, Olivier
Le Roy, Pascale
Lagarrigue, Sandrine
author_facet Blum, Yuna
Le Mignon, Guillaume
Causeur, David
Filangi, Olivier
Désert, Colette
Demeure, Olivier
Le Roy, Pascale
Lagarrigue, Sandrine
author_sort Blum, Yuna
collection PubMed
description BACKGROUND: Integrative genomics approaches that combine genotyping and transcriptome profiling in segregating populations have been developed to dissect complex traits. The most common approach is to identify genes whose eQTL colocalize with QTL of interest, providing new functional hypothesis about the causative mutation. Another approach includes defining subtypes for a complex trait using transcriptome profiles and then performing QTL mapping using some of these subtypes. This approach can refine some QTL and reveal new ones. In this paper we introduce Factor Analysis for Multiple Testing (FAMT) to define subtypes more accurately and reveal interaction between QTL affecting the same trait. The data used concern hepatic transcriptome profiles for 45 half sib male chicken of a sire known to be heterozygous for a QTL affecting abdominal fatness (AF) on chromosome 5 distal region around 168 cM. RESULTS: Using this methodology which accounts for hidden dependence structure among phenotypes, we identified 688 genes that are significantly correlated to the AF trait and we distinguished 5 subtypes for AF trait, which are not observed with gene lists obtained by classical approaches. After exclusion of one of the two lean bird subtypes, linkage analysis revealed a previously undetected QTL on chromosome 5 around 100 cM. Interestingly, the animals of this subtype presented the same q paternal haplotype at the 168 cM QTL. This result strongly suggests that the two QTL are in interaction. In other words, the "q configuration" at the 168 cM QTL could hide the QTL existence in the proximal region at 100 cM. We further show that the proximal QTL interacts with the previous one detected on the chromosome 5 distal region. CONCLUSION: Our results demonstrate that stratifying genetic population by molecular phenotypes followed by QTL analysis on various subtypes can lead to identification of novel and interacting QTL.
format Online
Article
Text
id pubmed-3276653
institution National Center for Biotechnology Information
language English
publishDate 2011
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-32766532012-02-10 Complex trait subtypes identification using transcriptome profiling reveals an interaction between two QTL affecting adiposity in chicken Blum, Yuna Le Mignon, Guillaume Causeur, David Filangi, Olivier Désert, Colette Demeure, Olivier Le Roy, Pascale Lagarrigue, Sandrine BMC Genomics Research Article BACKGROUND: Integrative genomics approaches that combine genotyping and transcriptome profiling in segregating populations have been developed to dissect complex traits. The most common approach is to identify genes whose eQTL colocalize with QTL of interest, providing new functional hypothesis about the causative mutation. Another approach includes defining subtypes for a complex trait using transcriptome profiles and then performing QTL mapping using some of these subtypes. This approach can refine some QTL and reveal new ones. In this paper we introduce Factor Analysis for Multiple Testing (FAMT) to define subtypes more accurately and reveal interaction between QTL affecting the same trait. The data used concern hepatic transcriptome profiles for 45 half sib male chicken of a sire known to be heterozygous for a QTL affecting abdominal fatness (AF) on chromosome 5 distal region around 168 cM. RESULTS: Using this methodology which accounts for hidden dependence structure among phenotypes, we identified 688 genes that are significantly correlated to the AF trait and we distinguished 5 subtypes for AF trait, which are not observed with gene lists obtained by classical approaches. After exclusion of one of the two lean bird subtypes, linkage analysis revealed a previously undetected QTL on chromosome 5 around 100 cM. Interestingly, the animals of this subtype presented the same q paternal haplotype at the 168 cM QTL. This result strongly suggests that the two QTL are in interaction. In other words, the "q configuration" at the 168 cM QTL could hide the QTL existence in the proximal region at 100 cM. We further show that the proximal QTL interacts with the previous one detected on the chromosome 5 distal region. CONCLUSION: Our results demonstrate that stratifying genetic population by molecular phenotypes followed by QTL analysis on various subtypes can lead to identification of novel and interacting QTL. BioMed Central 2011-11-21 /pmc/articles/PMC3276653/ /pubmed/22103296 http://dx.doi.org/10.1186/1471-2164-12-567 Text en Copyright ©2011 Blum et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Blum, Yuna
Le Mignon, Guillaume
Causeur, David
Filangi, Olivier
Désert, Colette
Demeure, Olivier
Le Roy, Pascale
Lagarrigue, Sandrine
Complex trait subtypes identification using transcriptome profiling reveals an interaction between two QTL affecting adiposity in chicken
title Complex trait subtypes identification using transcriptome profiling reveals an interaction between two QTL affecting adiposity in chicken
title_full Complex trait subtypes identification using transcriptome profiling reveals an interaction between two QTL affecting adiposity in chicken
title_fullStr Complex trait subtypes identification using transcriptome profiling reveals an interaction between two QTL affecting adiposity in chicken
title_full_unstemmed Complex trait subtypes identification using transcriptome profiling reveals an interaction between two QTL affecting adiposity in chicken
title_short Complex trait subtypes identification using transcriptome profiling reveals an interaction between two QTL affecting adiposity in chicken
title_sort complex trait subtypes identification using transcriptome profiling reveals an interaction between two qtl affecting adiposity in chicken
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3276653/
https://www.ncbi.nlm.nih.gov/pubmed/22103296
http://dx.doi.org/10.1186/1471-2164-12-567
work_keys_str_mv AT blumyuna complextraitsubtypesidentificationusingtranscriptomeprofilingrevealsaninteractionbetweentwoqtlaffectingadiposityinchicken
AT lemignonguillaume complextraitsubtypesidentificationusingtranscriptomeprofilingrevealsaninteractionbetweentwoqtlaffectingadiposityinchicken
AT causeurdavid complextraitsubtypesidentificationusingtranscriptomeprofilingrevealsaninteractionbetweentwoqtlaffectingadiposityinchicken
AT filangiolivier complextraitsubtypesidentificationusingtranscriptomeprofilingrevealsaninteractionbetweentwoqtlaffectingadiposityinchicken
AT desertcolette complextraitsubtypesidentificationusingtranscriptomeprofilingrevealsaninteractionbetweentwoqtlaffectingadiposityinchicken
AT demeureolivier complextraitsubtypesidentificationusingtranscriptomeprofilingrevealsaninteractionbetweentwoqtlaffectingadiposityinchicken
AT leroypascale complextraitsubtypesidentificationusingtranscriptomeprofilingrevealsaninteractionbetweentwoqtlaffectingadiposityinchicken
AT lagarriguesandrine complextraitsubtypesidentificationusingtranscriptomeprofilingrevealsaninteractionbetweentwoqtlaffectingadiposityinchicken