Targeted imputation of sequence variants and gene expression profiling identifies twelve candidate genes associated with lactation volume, composition and calving interval in dairy cattle.

Dairy cattle are an interesting model for gaining insights into the genes responsible for the large variation between and within mammalian species in the protein and fat content of their milk and their milk volume. Large numbers of phenotypes for these traits are available, as well as full genome sequence of key founders of modern dairy cattle populations. In twenty target QTL regions affecting milk production traits, we imputed full genome sequence variant genotypes into a population of 16,721 Holstein and Jersey cattle with excellent phenotypes.

SRST2: Rapid genomic surveillance for public health and hospital microbiology labs.

Rapid molecular typing of bacterial pathogens is critical for public health epidemiology, surveillance and infection control, yet routine use of whole genome sequencing (WGS) for these purposes poses significant challenges. Here we present SRST2, a read mapping-based tool for fast and accurate detection of genes, alleles and multi-locus sequence types (MLST) from WGS data. Using >900 genomes from common pathogens, we show SRST2 is highly accurate and outperforms assembly-based methods in terms of both gene detection and allele assignment.

Genetic variants in mammary development, prolactin signalling and involution pathways explain considerable variation in bovine milk production and milk composition.

Background: The maintenance of lactation in mammals is the result of a balance between competing signals from mammary development, prolactin signalling and involution pathways. Dairy cattle are an interesting case study to investigate the effect of polymorphisms that affect the function of genes in these pathways. In dairy cattle, lactation yields and milk composition (for example protein percentage and fat percentage) are routinely recorded, and these vary greatly between individuals.

Multibreed genome wide association can improve precision of mapping causative variants underlying milk production in dairy cattle.

Background: Genome wide association studies (GWAS) in most cattle breeds result in large genomic intervals of significant associations making it difficult to identify causal mutations. This is due to the extensive, low-level linkage disequilibrium within a cattle breed. As there is less linkage disequilibrium across breeds, multibreed GWAS may improve precision of causal variant mapping.

Genes of the RNASE5 pathway contain SNP associated with milk production traits in dairy cattle.

Background: Identification of the processes and mutations responsible for the large genetic variation in milk production among dairy cattle has proved challenging. One approach is to identify a biological process potentially involved in milk production and to determine the genetic influence of all the genes included in the process or pathway. Angiogenin encoded by angiogenin, ribonuclease, RNase A family 5 (RNASE5) is relatively abundant in milk, and has been shown to regulate protein synthesis and act as a growth factor in epithelial cells in vitro.