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Riquet, J.

Publications and source records attributed to Riquet, J..

3 recordsLinked to original sources

Discovering genomic regions associated with the phenotypic differentiation of European local pig breeds

BackgroundIntensive selection of modern pig breeds resulted in genetic improvement of productive traits while local pig breeds remained less performant. As they have been bred in extensive systems, they have adapted to specifical environmental conditions resulting in a rich genotypic and phenotypic diversity. This study is based on European local pig breeds genetically characterized using DNA-pool sequencing data and phenotypically characterized using breed level phenotypes related to stature, fatness, growth and reproductive performance traits. These data were analyzed using a dedicated approach to detect selection signatures linked to phenotypic traits in order to uncover potential candidate genes that may be under adaptation to specific environments. ResultsGenetic data analysis of European pig breeds revealed four main axes of genetic variation represented by Iberian and modern breeds (i.e. Large White, Landrace, and Duroc). In addition, breeds clustered according to their geographical origin, for example French Gascon and Basque breeds, Italian Apulo Calabrese and Casertana breeds, Spanish Iberian and Portuguese Alentejano breeds. Principal component analysis of phenotypic data distinguished between larger and leaner breeds with better growth potential and reproductive performance on one hand and breeds that were smaller, fatter, and had low growth and reproductive efficiency on the other hand. Linking selection signatures with phenotype identified 16 significant genomic regions associated with stature, 24 with fatness, 2 with growth and 192 with reproduction. Among them, several regions contained candidate genes with possible biological effect on stature, fatness, growth and reproduction performance traits. For example, strong associations were found for stature in two regions containing the ANXA4 and ANTXR1 genes, for fatness containing the DNMT3A and POMC genes and for reproductive performance containing the HSD17B7 gene. ConclusionsThe present study on European local pig breeds used a dedicated approach for searching selection signatures supported by phenotypic data at the breed level to identify potential candidate genes that may have adapted to different living environments and production systems. Results can be useful to define conservation programs of local pig breeds.

genetics↗

A genome-wide epistatic network underlies the molecular architecture of continuous color variation of body extremities: a rabbit model

Deciphering the molecular architecture of coat coloration for a better understanding of the biological mechanisms underlying pigmentation still remains a challenge. We took advantage of a rabbit French experimental population in which both a pattern and a gradient of coloration from white to brown segregated within the himalayan phenotype. The whole experimental design was genotyped using the high density Affymetrix(R) AxiomOrcun SNP Array and phenotyped into 6 different groups ordered from the lighter to the darker. Genome-wide association analyses pinpointed an oligogenic determinism, under recessive and additive inheritance, involving genes already known in melanogenesis (ASIP, KIT, MC1R, TYR), and likely processed pseudogenes linked to ribosomal function, RPS20 and RPS14. We also identified (i) gene-gene interactions through ASIP:MC1R affecting light cream/beige phenotypes while KIT:RPS responsible of dark chocolate/brown colors and (ii) a genome-wide epistatic network involving several others coloration genes such as POT1 or HPS5. Finally, we determined the recessive inheritance of the English spotting phenotype likely involving a copy number variation affecting at least the end of the coding sequence of the KIT gene. Our analyses of coloration as a continuous trait allowed us to go beyond much of the established knowledge through the detection of additional genes and gene-gene interactions that may contribute to the molecular architecture of the coloration phenotype. Moreover, the characterization of a network including genes that contribute to melanogenesis and pigmentation, two processes affected in various human disorders, shows the potential interest of our rabbit model for transversal studies.

genetics↗

Identification of genomic regions affecting production traits in pigs divergently selected for feed efficiency

BackgroundFeed efficiency is a major driver of the sustainability of pig production systems. Understanding biological mechanisms underlying these agronomic traits is an important issue whether for environment and farms economy. This study aimed at identifying genomic regions affecting residual feed intake (RFI) and other production traits in two pig lines divergently selected for RFI during 9 generations (LRFI, low RFI; HRFI, high RFI). ResultsWe built a whole dataset of 570,447 single nucleotide polymorphisms (SNPs) in 2,426 pigs with records for 24 production traits after both imputation and prediction of genotypes using pedigree information. Genome-wide association studies (GWAS) were performed including both lines (Global-GWAS) or each line independently (LRFI-GWAS and HRFI-GWAS). A total of 54 chromosomic regions were detected with the Global-GWAS, whereas 37 and 61 regions were detected in LRFI-GWAS and HRFI-GWAS, respectively. Among those, only 15 regions were shared between at least two analyses, and only one was common between the three GWAS but affecting different traits. Among the 12 QTL detected for RFI, some were close to QTL detected for meat quality traits and 9 pinpointed novel genomic regions for some harbored candidate genes involved in cell proliferation and differentiation processes of gastrointestinal tissues or lipid metabolism-related signaling pathways. Detection of mostly different QTL regions between the three designs suggests the strong impact of the dataset on the detection power, which could be due to the changes of allelic frequencies during the line selection. ConclusionsBesides efficiently detecting known and new QTL regions for feed efficiency, the combination of GWAS carried out per line or simultaneously using all individuals highlighted the identification of chromosomic regions under selection that affect various production traits.

genetics↗