Limits...
Using microarrays to identify positional candidate genes for QTL: the case study of ACTH response in pigs.

Jouffe V, Rowe S, Liaubet L, Buitenhuis B, Hornshøj H, Sancristobal M, Mormède P, de Koning DJ - BMC Proc (2009)

Bottom Line: A further step to explore links between DE genes and QTL at the pathway level was largely unsuccessful due to the lack of annotation of the pig genome.This could be improved by further comparative mapping analyses but this would be time consuming.The results illustrate the challenges that must be addressed but also provide a roadmap for future work that is applicable to other non-model species.

View Article: PubMed Central - HTML - PubMed

Affiliation: Laboratoire PsyNuGen, INRA UMR1286, CNRS UMR5226, Université de Bordeaux 2, 146 rue Léo-Saignat, F-33076 Bordeaux, France. VJouffe@bordeaux.inra.fr

ABSTRACT

Background: Microarray studies can supplement QTL studies by suggesting potential candidate genes in the QTL regions, which by themselves are too large to provide a limited selection of candidate genes. Here we provide a case study where we explore ways to integrate QTL data and microarray data for the pig, which has only a partial genome sequence. We outline various procedures to localize differentially expressed genes on the pig genome and link this with information on published QTL. The starting point is a set of 237 differentially expressed cDNA clones in adrenal tissue from two pig breeds, before and after treatment with adrenocorticotropic hormone (ACTH).

Results: Different approaches to localize the differentially expressed (DE) genes to the pig genome showed different levels of success and a clear lack of concordance for some genes between the various approaches. For a focused analysis on 12 genes, overlapping QTL from the public domain were presented. Also, differentially expressed genes underlying QTL for ACTH response were described. Using the latest version of the draft sequence, the differentially expressed genes were mapped to the pig genome. This enabled co-location of DE genes and previously studied QTL regions, but the draft genome sequence is still incomplete and will contain many errors. A further step to explore links between DE genes and QTL at the pathway level was largely unsuccessful due to the lack of annotation of the pig genome. This could be improved by further comparative mapping analyses but this would be time consuming.

Conclusion: This paper provides a case study for the integration of QTL data and microarray data for a species with limited genome sequence information and annotation. The results illustrate the challenges that must be addressed but also provide a roadmap for future work that is applicable to other non-model species.

No MeSH data available.


Inferred locations of differentially expressed genes and ACTH response related QTL on the porcine genome. Positions are given in Mb derived from the draft assembly of the pig genome (version 7). Black gene symbol denotes genes positioned by SJR using blast against pig genome sequence build 7, brown gene symbol denotes best position for a gene although not significant in the blast output (e-value < 0.0001). Pink are genes positioned in common by both build 6 and build 7 of the pig genome sequence, dark blue are genes positioned differently by build 6, orange are genes positioned by version 6 and human orthologues, green are genes that could not be positioned by human orthologues or build 6. Red bars denote confidence intervals for QTL associated with glucose, cortisol and ACTH from analyses by Desautes et al., 2002.
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Figure 2: Inferred locations of differentially expressed genes and ACTH response related QTL on the porcine genome. Positions are given in Mb derived from the draft assembly of the pig genome (version 7). Black gene symbol denotes genes positioned by SJR using blast against pig genome sequence build 7, brown gene symbol denotes best position for a gene although not significant in the blast output (e-value < 0.0001). Pink are genes positioned in common by both build 6 and build 7 of the pig genome sequence, dark blue are genes positioned differently by build 6, orange are genes positioned by version 6 and human orthologues, green are genes that could not be positioned by human orthologues or build 6. Red bars denote confidence intervals for QTL associated with glucose, cortisol and ACTH from analyses by Desautes et al., 2002.

Mentions: The localization of the twelve differentially expressed genes on the pig genome has been realised by two different methods. First, the genes have been aligned to the human genome then mapped on the pig chromosomes by synteny using the comparative map [7]. Second, the genes have been directly aligned to the draft pig genome sequence. The different results are compared in Table 1. The Eif1b, Crem, A2m and Rnf2 genes have been mapped on chromosomes 13, 10, 5 and 1, respectively by both methods. Cited1 has been localized on the pig chromosome X and the human chromosome X. The Pig RH map – human comparative map is not available for X/Y chromosomes [7]. Nevertheless, the comparative tool from the Rat Genome Database [15] showed similarities between the X chromosomes from human, rat and mouse genomes, thus it can be hypothesized that the X chromosomes from the human and the pig genomes are conserved. The Ckb gene has been mapped on chromosome X by alignment against the pig genome and on chromosome 7 by alignment on a human genome region that in syntenic with porcine chromosome 7. Anpep and Cd83 have only been mapped on chromosome 7 by alignment against pig genome. The Gadd45b, Ldlr, Star and Acox1 genes have only been mapped on chromosomes 2, 2, 15 and 12, respectively by synteny after alignment against human genome. The comparative map [7] showed syntenic blocks. According to the "synteny blocks" definition from Pevzner and Tesler [16], the Anpep, Gadd45b, Ckb, Ldlr, Star, Acox1 and Cd83 genes should be mapped on dissimilar regions. The consensus location of all 12 genes is highlighted in Figure 2, including the 4 genes that could not initially be mapped to the porcine sequence but were successfully mapped to version 7 of the draft genome (Roslin).


Using microarrays to identify positional candidate genes for QTL: the case study of ACTH response in pigs.

Jouffe V, Rowe S, Liaubet L, Buitenhuis B, Hornshøj H, Sancristobal M, Mormède P, de Koning DJ - BMC Proc (2009)

Inferred locations of differentially expressed genes and ACTH response related QTL on the porcine genome. Positions are given in Mb derived from the draft assembly of the pig genome (version 7). Black gene symbol denotes genes positioned by SJR using blast against pig genome sequence build 7, brown gene symbol denotes best position for a gene although not significant in the blast output (e-value < 0.0001). Pink are genes positioned in common by both build 6 and build 7 of the pig genome sequence, dark blue are genes positioned differently by build 6, orange are genes positioned by version 6 and human orthologues, green are genes that could not be positioned by human orthologues or build 6. Red bars denote confidence intervals for QTL associated with glucose, cortisol and ACTH from analyses by Desautes et al., 2002.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2712744&req=5

Figure 2: Inferred locations of differentially expressed genes and ACTH response related QTL on the porcine genome. Positions are given in Mb derived from the draft assembly of the pig genome (version 7). Black gene symbol denotes genes positioned by SJR using blast against pig genome sequence build 7, brown gene symbol denotes best position for a gene although not significant in the blast output (e-value < 0.0001). Pink are genes positioned in common by both build 6 and build 7 of the pig genome sequence, dark blue are genes positioned differently by build 6, orange are genes positioned by version 6 and human orthologues, green are genes that could not be positioned by human orthologues or build 6. Red bars denote confidence intervals for QTL associated with glucose, cortisol and ACTH from analyses by Desautes et al., 2002.
Mentions: The localization of the twelve differentially expressed genes on the pig genome has been realised by two different methods. First, the genes have been aligned to the human genome then mapped on the pig chromosomes by synteny using the comparative map [7]. Second, the genes have been directly aligned to the draft pig genome sequence. The different results are compared in Table 1. The Eif1b, Crem, A2m and Rnf2 genes have been mapped on chromosomes 13, 10, 5 and 1, respectively by both methods. Cited1 has been localized on the pig chromosome X and the human chromosome X. The Pig RH map – human comparative map is not available for X/Y chromosomes [7]. Nevertheless, the comparative tool from the Rat Genome Database [15] showed similarities between the X chromosomes from human, rat and mouse genomes, thus it can be hypothesized that the X chromosomes from the human and the pig genomes are conserved. The Ckb gene has been mapped on chromosome X by alignment against the pig genome and on chromosome 7 by alignment on a human genome region that in syntenic with porcine chromosome 7. Anpep and Cd83 have only been mapped on chromosome 7 by alignment against pig genome. The Gadd45b, Ldlr, Star and Acox1 genes have only been mapped on chromosomes 2, 2, 15 and 12, respectively by synteny after alignment against human genome. The comparative map [7] showed syntenic blocks. According to the "synteny blocks" definition from Pevzner and Tesler [16], the Anpep, Gadd45b, Ckb, Ldlr, Star, Acox1 and Cd83 genes should be mapped on dissimilar regions. The consensus location of all 12 genes is highlighted in Figure 2, including the 4 genes that could not initially be mapped to the porcine sequence but were successfully mapped to version 7 of the draft genome (Roslin).

Bottom Line: A further step to explore links between DE genes and QTL at the pathway level was largely unsuccessful due to the lack of annotation of the pig genome.This could be improved by further comparative mapping analyses but this would be time consuming.The results illustrate the challenges that must be addressed but also provide a roadmap for future work that is applicable to other non-model species.

View Article: PubMed Central - HTML - PubMed

Affiliation: Laboratoire PsyNuGen, INRA UMR1286, CNRS UMR5226, Université de Bordeaux 2, 146 rue Léo-Saignat, F-33076 Bordeaux, France. VJouffe@bordeaux.inra.fr

ABSTRACT

Background: Microarray studies can supplement QTL studies by suggesting potential candidate genes in the QTL regions, which by themselves are too large to provide a limited selection of candidate genes. Here we provide a case study where we explore ways to integrate QTL data and microarray data for the pig, which has only a partial genome sequence. We outline various procedures to localize differentially expressed genes on the pig genome and link this with information on published QTL. The starting point is a set of 237 differentially expressed cDNA clones in adrenal tissue from two pig breeds, before and after treatment with adrenocorticotropic hormone (ACTH).

Results: Different approaches to localize the differentially expressed (DE) genes to the pig genome showed different levels of success and a clear lack of concordance for some genes between the various approaches. For a focused analysis on 12 genes, overlapping QTL from the public domain were presented. Also, differentially expressed genes underlying QTL for ACTH response were described. Using the latest version of the draft sequence, the differentially expressed genes were mapped to the pig genome. This enabled co-location of DE genes and previously studied QTL regions, but the draft genome sequence is still incomplete and will contain many errors. A further step to explore links between DE genes and QTL at the pathway level was largely unsuccessful due to the lack of annotation of the pig genome. This could be improved by further comparative mapping analyses but this would be time consuming.

Conclusion: This paper provides a case study for the integration of QTL data and microarray data for a species with limited genome sequence information and annotation. The results illustrate the challenges that must be addressed but also provide a roadmap for future work that is applicable to other non-model species.

No MeSH data available.