Using transcriptome profiling to characterize QTL regions on chicken chromosome 5

Mignon, Guillaume Le; Désert, Colette; Pitel, Frédérique; Leroux, Sophie; Demeure, Olivier; Guernec, Grégory; Abasht, Behnam; Douaire, Madeleine; Roy, Pascale Le; Lagarrigue, Sandrine

doi:10.1186/1471-2164-10-575

Cited by 18 publications

(34 citation statements)

References 47 publications

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“…a focus on genomic variation and a focus on expression of causal pathways) are likely to identify common, but also unique sets of genes involved in regulation of heritable quantitative traits (e.g. Le Mignon et al 2009). For instance, there may be no genomic variation in some of the genes that play a crucial role in the pathway.…”

Section: Different Perspectivesmentioning

confidence: 99%

Phenology, seasonal timing and circannual rhythms: towards a unified framework

Visser

Samuel

Oers

et al. 2010

Phil. Trans. R. Soc. B

290

291

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Phenology refers to the periodic appearance of life-cycle events and currently receives abundant attention as the effects of global change on phenology are so apparent. Phenology as a discipline observes these events and relates their annual variation to variation in climate. But phenology is also studied in other disciplines, each with their own perspective. Evolutionary ecologists study variation in seasonal timing and its fitness consequences, whereas chronobiologists emphasize the periodic nature of life-cycle stages and their underlying timing programmes (e.g. circannual rhythms). The (neuro-) endocrine processes underlying these life-cycle events are studied by physiologists and need to be linked to genes that are explored by molecular geneticists. In order to fully understand variation in phenology, we need to integrate these different perspectives, in particular by combining evolutionary and mechanistic approaches. We use avian research to characterize different perspectives and to highlight integration that has already been achieved. Building on this work, we outline a route towards uniting the different disciplines in a single framework, which may be used to better understand and, more importantly, to forecast climate change impacts on phenology.

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Section: Different Perspectivesmentioning

confidence: 99%

Phenology, seasonal timing and circannual rhythms: towards a unified framework

Visser

Samuel

Oers

et al. 2010

Phil. Trans. R. Soc. B

290

291

View full text Add to dashboard Cite

show abstract

“…In these studies, eQTL were mapped using linkage analysis in which the locus affecting gene expression was traced by segregation through genetic crosses in experimental organisms, human families, or livestock species (Kruglyak 2008;Le Mignon et al 2009;van Nas et al 2010). A weakness of such studies in the case of mammals is that the mapping resolution was poor, generally in the range of tens to hundreds of genes.…”

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confidence: 99%

Analysis of Allele-Specific Expression in Mouse Liver by RNA-Seq: A Comparison With Cis-eQTL Identified Using Genetic Linkage

et al. 2013

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We report an analysis of allele-specific expression (ASE) and parent-of-origin expression in adult mouse liver using next generation sequencing (RNA-Seq) of reciprocal crosses of heterozygous F 1 mice from the parental strains C57BL/6J and DBA/2J. We found a 60% overlap between genes exhibiting ASE and putative cis-acting expression quantitative trait loci (cis-eQTL) identified in an intercross between the same strains. We discuss the various biological and technical factors that contribute to the differences. We also identify genes exhibiting parental imprinting and complex expression patterns. Our study demonstrates the importance of biological replicates to limit the number of false positives with RNA-Seq data.

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“…As indicated in Figure 2B, the majority of analyses gave the same LRT curves with the expected AF QTL located around 168 cM on the chromosome 5 [12]. However, after removing the lean subtype called lean2, a new significant QTL (p-value < 0.05) was detected on a proximal chromosome 5 locus around 100 cM with an effect of 1.19 phenotypic standard deviation.…”

Section: Resultsmentioning

confidence: 74%

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

et al. 2011

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BackgroundIntegrative 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.ResultsUsing 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.ConclusionOur 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.

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Using transcriptome profiling to characterize QTL regions on chicken chromosome 5

Cited by 18 publications

References 47 publications

Phenology, seasonal timing and circannual rhythms: towards a unified framework

Phenology, seasonal timing and circannual rhythms: towards a unified framework

Analysis of Allele-Specific Expression in Mouse Liver by RNA-Seq: A Comparison With Cis-eQTL Identified Using Genetic Linkage

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

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