Genetic variants associated with two major bovine milk fatty acids offer opportunities to breed for altered milk fat composition.

BACKGROUND: Although bovine milk is regarded as healthy and nutritious, its high content of saturated fatty acids (FA) may be harmful to cardiovascular health. Palmitic acid (C16:0) is the predominant saturated FA in milk with adverse health effects that could be countered by substituting it with higher levels of unsaturated FA, such as oleic acid (C18:1cis-9). In this work, we performed genome-wide association analyses for milk fatty acids predicted from FTIR spectroscopy data using 1811 Norwegian Red cattle genotyped and imputed to a high-density 777k single nucleotide polymorphism (SNP)-array. In a follow-up analysis, we used imputed whole-genome sequence data to detect genetic variants that are involved in FTIR-predicted levels of C16:0 and C18:1cis-9 and explore the transcript profile and protein level of candidate genes. RESULTS: Genome-wise significant associations were detected for C16:0 on Bos taurus (BTA) autosomes 11, 16 and 27, and for C18:1cis-9 on BTA5, 13 and 19. Closer examination of a significant locus on BTA11 identified the PAEP gene, which encodes the milk protein ß-lactoglobulin, as a particularly attractive positional candidate gene. At this locus, we discovered a tightly linked cluster of genetic variants in coding and regulatory sequences that have opposing effects on the levels of C16:0 and C18:1cis-9. The favourable haplotype, linked to reduced levels of C16:0 and increased levels of C18:1cis-9 was also associated with a marked reduction in PAEP expression and ß-lactoglobulin protein levels. ß-lactoglobulin is the most abundant whey protein in milk and lower levels are associated with important dairy production parameters such as improved cheese yield. CONCLUSIONS: The genetic variants detected in this study may be used in breeding to produce milk with an improved FA health-profile and enhanced cheese-making properties.

Insertion of an endogenous Jaagsiekte sheep retrovirus element into the BCO2 - gene abolishes its function and leads to yellow discoloration of adipose tissue in Norwegian Spælsau (Ovis aries).

BACKGROUND: The accumulation of carotenoids in adipose tissue leading to yellow fat is, in sheep, a heritable recessive trait that can be attributed to a nonsense mutation in the beta-carotene oxygenase 2 (BCO2) gene. However, not all sheep breeds suffering from yellow fat have this nonsense mutation, meaning that other functional mechanisms must exist. We investigated one such breed, the Norwegian spælsau. RESULTS: In spælsau we detected an aberration in BCO2 mRNA. Nanopore sequencing of genomic DNA revealed the insertion of a 7.9 kb endogenous Jaagsiekte Sheep Retrovirus (enJSRV) sequence in the first intron of the BCO2 gene. Close examination of its cDNA revealed that the BCO2 genes first exon was spliced together with enJSRV-sequence immediately downstream of a potential -AG splice acceptor site at enJSRV position 415. The hybrid protein product consists of 29 amino acids coded by the BCO2 exon 1, one amino acid coded by the junction sequence, followed by 28 amino acids arbitrary coded for by the enJSRV-sequence, before a translation stop codon is reached. CONCLUSIONS: Considering that the functional BCO2 protein consists of 575 amino acids, it is unlikely that the 58 amino acid BCO2/enJSRV hybrid protein can display any enzymatic function. The existence of this novel BCO2 allele represents an alternative functional mechanism accounting for BCO2 inactivation and is a perfect example of the potential benefits for searching for structural variants using long-read sequencing data.

Genome-wide association mapping for milk fat composition and fine mapping of a QTL for de novo synthesis of milk fatty acids on bovine chromosome 13.

BACKGROUND: Bovine milk is widely regarded as a nutritious food source for humans, although the effects of individual fatty acids on human health is a subject of debate. Based on the assumption that genomic selection offers potential to improve milk fat composition, there is strong interest to understand more about the genetic factors that influence the biosynthesis of bovine milk and the molecular mechanisms that regulate milk fat synthesis and secretion. For this reason, the work reported here aimed at identifying genetic variants that affect milk fatty acid composition in Norwegian Red cattle. Milk fatty acid composition was predicted from the nation-wide recording scheme using Fourier transform infrared spectroscopy data and applied to estimate heritabilities for 36 individual and combined fatty acid traits. The recordings were used to generate daughter yield deviations that were first applied in a genome-wide association (GWAS) study with 17,343 markers to identify quantitative trait loci (QTL) affecting fatty acid composition, and next on high-density and sequence-level datasets to fine-map the most significant QTL on BTA13 (BTA for Bos taurus chromosome). RESULTS: The initial GWAS revealed 200 significant associations, with the strongest signals on BTA1, 13 and 15. The BTA13 QTL highlighted a strong functional candidate gene for de novo synthesis of short- and medium-chained saturated fatty acids; acyl-CoA synthetase short-chain family member 2. However, subsequent fine-mapping using single nucleotide polymorphisms (SNPs) from a high-density chip and variants detected by resequencing showed that the effect was more likely caused by a second nearby gene; nuclear receptor coactivator 6 (NCOA6). These findings were confirmed with results from haplotype studies. NCOA6 is a nuclear receptor that interacts with transcription factors such as PPARγ, which is a major regulator of bovine milk fat synthesis. CONCLUSIONS: An initial GWAS revealed a highly significant QTL for de novo-synthesized fatty acids on BTA13 and was followed by fine-mapping of the QTL within NCOA6. The most significant SNPs were either synonymous or situated in introns; more research is needed to uncover the underlying causal DNA variation(s).

Trans-Atlantic Distribution and Introgression as Inferred from Single Nucleotide Polymorphism: Mussels Mytilus and Environmental Factors.

Large-scale climate changes influence the geographic distribution of biodiversity. Many taxa have been reported to extend or reduce their geographic range, move poleward or displace other species. However, for closely related species that can hybridize in the natural environment, displacement is not the only effect of changes of environmental variables. Another option is subtler, hidden expansion, which can be found using genetic methods only. The marine blue mussels Mytilus are known to change their geographic distribution despite being sessile animals. In addition to natural dissemination at larval phase-enhanced by intentional or accidental introductions and rafting-they can spread through hybridization and introgression with local congeners, which can create mixed populations sustaining in environmental conditions that are marginal for pure taxa. The Mytilus species have a wide distribution in coastal regions of the Northern and Southern Hemisphere. In this study, we investigated the inter-regional genetic differentiation of the Mytilus species complex at 53 locations in the North Atlantic and adjacent Arctic waters and linked this genetic variability to key local environmental drivers. Of seventy-nine candidate single nucleotide polymorphisms (SNPs), all samples were successfully genotyped with a subset of 54 SNPs. There was a clear interregional separation of Mytilus species. However, all three Mytilus species hybridized in the contact area and created hybrid zones with mixed populations. Boosted regression trees (BRT) models showed that inter-regional variability was important in many allele models but did not prevail over variability in local environmental factors. Local environmental variables described over 40% of variability in about 30% of the allele frequencies of Mytilus spp. For the 30% of alleles, variability in their frequencies was only weakly coupled with local environmental conditions. For most studied alleles the linkages between environmental drivers and the genetic variability of Mytilus spp. were random in respect to "coding" and "non-coding" regions. An analysis of the subset of data involving functional genes only showed that two SNPs at Hsp70 and ATPase genes correlated with environmental variables. Total predictive ability of the highest performing models (r2 between 0.550 and 0.801) were for alleles that discriminated most effectively M.trossulus from M.edulis and M.galloprovincialis, whereas the best performing allele model (BM101A) did the best at discriminating M.galloprovincialis from M. edulis and M.trossulus. Among the local environmental variables, salinity, water temperature, ice cover and chlorophyll a concentration were by far the greatest predictors, but their predictive performance varied among different allele models. In most cases changes in the allele frequencies along these environmental gradients were abrupt and occurred at a very narrow range of environmental variables. In general, regions of change in allele frequencies for M.trossulus occurred at 8-11 psu, 0-10 C, 60%-70% of ice cover and 0-2 mg m-3 of chlorophyll a, M. edulis at 8-11 and 30-35 psu, 10-14 C and 60%-70% of ice cover and for M.galloprovincialis at 30-35 psu, 14-20 C.

SNP Arrays for Species Identification in Salmonids.

The use of SNP genotyping microarrays, developed in one species to analyze a closely related species for which genomic sequence information is scarce, enables the rapid development of a genomic resource (SNP information) without the need to develop new species-specific markers. Using large numbers of microarray SNPs offers the best chance to detect informative markers in nontarget species, markers that can very often be assayed using a lower throughput platform as is described in this paper.