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Delpuech, E.

Publications and source records attributed to Delpuech, E..

2 recordsLinked to original sources

Whole-genome sequencing identifies interferon induced protein IFI6 as a strong candidate gene for VNN resistance in European sea bass

BackgroundViral Nervous Necrosis (VNN) is major disease affecting of European sea bass. Understanding the biological mechanisms that underlie VNN resistance is thus important for the welfare of farmed fish and the sustainability of production systems. This study aimed at identifying key genomic regions and genes that determine VNN resistance in sea bass. ResultsWe generated a dataset of around 900,000 single nucleotide polymorphisms (SNPs) identified from whole-genome sequencing (WGS) in the parental generation in two different commercial populations (pop A and pop B) comprising 2371 and 3428 European sea bass with phenotypic records for binary survival in a VNN challenge. In each commercial population, three cohorts were submitted to the redspotted grouper nervous necrosis virus (RGNNV) challenge by immersion and genotyped on a 57K SNP chip. After imputation of WGS SNPs from their parents, QTL mapping was performed using a Bayesian Sparse Linear Mixed Model (BSLMM). We found several QTL regions on different linkage groups (LG), most of which are specific to a single population, but a QTL region on LG12 was shared by both commercial populations. This QTL region is only 127 kB wide, and we identified IFI6, an interferon induced protein at only 1.9 kB of the most significant SNP. An unrelated validation population with 4 large families was used to validate the effect of the QTL, for which the survival of the susceptible genotype ranges from 39.8 to 45.4%, while that of the resistant genotype ranges from 63.8 to 70.8%. ConclusionsWe could precisely locate the genomic region implied in the main resistance QTL at less than 1.9 kb of the interferon alpha inducible protein 6 (IFI6), which has already been identified as a key player for other viral infections such as hepatitis B and C. This will lead to major improvements for sea bass breeding programs, allowing for greater genetic gain by using marker-assisted genomic selection to obtain more resistant fish. Further functional analyses are needed to evaluate the impact of the variant on the expression of this gene.

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↗