Advances in understanding the genetic architecture of antibody response to paratuberculosis in sheep by heritability estimate and LDLA mapping analyses and investigation of candidate regions using sequence-based data.

BACKGROUND: Paratuberculosis is a contagious and incurable disease that is caused by Mycobacterium avium subsp. paratuberculosis (MAP) with significant negative effects on animal welfare and farm profitability. Based on a large naturally infected flock over 12 years, we analyzed repeated enzyme-linked immunosorbent assay tests (ELISA), OvineSNP50 BeadChip genotypes and whole-genome sequences imputed from 56 influential animals. The main goals were to estimate the genetic parameters of proxy traits for resistance to MAP, identify genomic regions associated with the host's immune response against MAP and search for candidate genes and causative mutations through association and functional annotation analyses of polymorphisms identified by sequencing. RESULTS: Two variables were derived from ELISA tests. The first, a binary variable, assessed the infection status of each animal over the entire productive life, while the second considered the level of antibody recorded over time. Very similar results were obtained for both variables. Heritability estimates of about 0.20 were found and a significant region capturing 18% and 13% of the genetic variance was detected on ovine chromosome 20 by linkage disequilibrium and linkage analysis on OvineSNP50 positions. Functional annotation and association analyses on the imputed sequence polymorphisms that were identified in this region were carried out. No significant variants showed a functional effect on the genes that mapped to this region, most of which belong to the major histocompatibility complex class II (MHC II). However, the conditional analysis led to the identification of two significant polymorphisms that can explain the genetic variance associated with the investigated genomic region. CONCLUSIONS: Our results confirm the involvement of the host's genetics in susceptibility to MAP in sheep and suggest that selective breeding may be an option to limit the infection. The estimated heritability is moderate with a relevant portion being due to a highly significant region on ovine chromosome 20. The results of the combined use of sequence-based data and functional analyses suggest several genes belonging to the MHC II as the most likely candidates, although no mutations in their coding regions showed a significant association. Nevertheless, information from genotypes of two highly significant polymorphisms in the region can enhance the efficiency of selective breeding programs.

Association analysis and functional annotation of imputed sequence data within genomic regions influencing resistance to gastro-intestinal parasites detected by an LDLA approach in a nucleus flock of Sarda dairy sheep.

BACKGROUND: Gastroinestinal nematodes (GIN) are one of the major health problem in grazing sheep. Although genetic variability of the resistance to GIN has been documented, traditional selection is hampered by the difficulty of recording phenotypes, usually fecal egg count (FEC). To identify causative mutations or markers in linkage disequilibrium (LD) to be used for selection, the detection of quantitative trait loci (QTL) for FEC based on linkage disequilibrium-linkage analysis (LDLA) was performed on 4097 ewes (from 181 sires) all genotyped with the OvineSNP50 Beadchip. Identified QTL regions (QTLR) were imputed from whole-genome sequences of 56 target animals of the population. An association analysis and a functional annotation of imputed polymorphisms in the identified QTLR were performed to pinpoint functional variants with potential impact on candidate genes identified from ontological classification or differentially expressed in previous studies. RESULTS: After clustering close significant locations, ten QTLR were defined on nine Ovis aries chromosomes (OAR) by LDLA. The ratio between the ANOVA estimators of the QTL variance and the total phenotypic variance ranged from 0.0087 to 0.0176. QTL on OAR4, 12, 19, and 20 were the most significant. The combination of association analysis and functional annotation of sequence data did not highlight any putative causative mutations. None of the most significant SNPs showed a functional effect on genes' transcript. However, in the most significant QTLR, we identified genes that contained polymorphisms with a high or moderate impact, were differentially expressed in previous studies, contributed to enrich the most represented GO process (regulation of immune system process, defense response). Among these, the most likely candidate genes were: TNFRSF1B and SELE on OAR12, IL5RA on OAR19, IL17A, IL17F, TRIM26, TRIM38, TNFRSF21, LOC101118999, VEGFA, and TNF on OAR20. CONCLUSIONS: This study performed on a large experimental population provides a list of candidate genes and polymorphisms which could be used in further validation studies. The expected advancements in the quality of the annotation of the ovine genome and the use of experimental designs based on sequence data and phenotypes from multiple breeds that show different LD extents and gametic phases may help to identify causative mutations.

Mapping genomic regions affecting milk traits in Sarda sheep by using the OvineSNP50 Beadchip and principal components to perform combined linkage and linkage disequilibrium analysis.

BACKGROUND: The detection of regions that affect quantitative traits (QTL), to implement selection assisted by molecular information, remains of particular interest in dairy sheep for which genetic gain is constrained by the high costs of large-scale phenotype and pedigree recording. QTL detection based on the combination of linkage disequilibrium and linkage analysis (LDLA) is the most suitable approach in family-structured populations. The main issue in performing LDLA mapping is the handling of the identity-by-descent (IBD) probability matrix. Here, we propose the use of principal component analysis (PCA) to perform LDLA mapping for milk traits in Sarda dairy sheep. METHODS: A resource population of 3731 ewes belonging to 161 sire families and genotyped with the OvineSNP50 Beadchip was used to map genomic regions that affect five milk traits. The paternally and maternally inherited gametes of genotyped individuals were reconstructed and IBD probabilities between them were defined both at each SNP position and at the genome level. A QTL detection model fitting fixed effects of principal components that summarize IBD probabilities was tested at each SNP position. Genome-wide (GW) significance thresholds were determined by within-trait permutations. RESULTS: PCA resulted in substantial dimensionality reduction, in fact 137 and 32 (on average) principal components were able to capture 99% of the IBD variation at the locus and genome levels, respectively. Overall, 2563 positions exceeded the 0.05 GW significance threshold for at least one trait, which clustered into 75 QTL regions most of which affected more than one trait. The strongest signal was obtained for protein content on Ovis aries (OAR) chromosome 6 and overlapped with the region that harbours the casein gene cluster. Additional interesting positions were identified on OAR4 for fat content and on OAR11 for the three yield traits. CONCLUSIONS: PCA is a good strategy to summarize IBD probabilities. A large number of regions associated to milk traits were identified. The outputs provided by the proposed method are useful for the selection of candidate genes, which need to be further investigated to identify causative mutations or markers in strong LD with them for application in selection programs assisted by molecular information.