Highlights d Novel ovine SNPs of the male-specific region of Y chromosome were developed d Y chromosome of domestic sheep contains four different paternal lineages d Lineages C and B predominate in breeds of primitive traits and fat tail, respectively d Expansions of sheep correlate with various phenotypic traits and breeding goals

Rumen microbiota play a key role in the digestion and utilization of plant materials by the ruminant species, which have important implications for greenhouse gas emission. Yet, little is known about the key taxa and potential gene functions involved in the digestion process. Here, we performed a genome-centric analysis of rumen microbiota attached to six different lignocellulosic biomasses in rumen-fistulated cattle. Our metagenome sequencing provided novel genomic insights into functional potential of 523 uncultured bacteria and 15 mostly uncultured archaea in the rumen. The assembled genomes belonged mainly to Bacteroidota, Firmicutes, Verrucomicrobiota, and Fibrobacterota and were enriched for genes related to the degradation of lignocellulosic polymers and the fermentation of degraded products into short chain volatile fatty acids. We also found a shift from copiotrophic to oligotrophic taxa during the course of rumen fermentation, potentially important for the digestion of recalcitrant lignocellulosic substrates in the physiochemically complex and varying environment of the rumen. Differential colonization of forages (the incubated lignocellulosic materials) by rumen microbiota suggests that taxonomic and metabolic diversification is an evolutionary adaptation to diverse lignocellulosic substrates constituting a major component of the cattle’s diet. Our data also provide novel insights into the key role of unique microbial diversity and associated gene functions in the degradation of recalcitrant lignocellulosic materials in the rumen.

Single nucleotide polymorphisms (SNPs) are among the most common types of genetic variation in complex genetic disorders. A growing number of studies link the functional role of SNPs with the networks and pathways mediated by the disease-associated genes. For example, many non-synonymous missense SNPs (nsSNPs) have been found near or inside the protein-protein interaction (PPI) interfaces. Determining whether such nsSNP will disrupt or preserve a PPI is a challenging task to address, both experimentally and computationally. Here, we present this task as three related classification problems, and develop a new computational method, called the SNP-IN tool (non-synonymous SNP INteraction effect predictor). Our method predicts the effects of nsSNPs on PPIs, given the interaction's structure. It leverages supervised and semi-supervised feature-based classifiers, including our new Random Forest self-learning protocol. The classifiers are trained based on a dataset of comprehensive mutagenesis studies for 151 PPI complexes, with experimentally determined binding affinities of the mutant and wild-type interactions. Three classification problems were considered: (1) a 2-class problem (strengthening/weakening PPI mutations), (2) another 2-class problem (mutations that disrupt/preserve a PPI), and (3) a 3-class classification (detrimental/neutral/beneficial mutation effects). In total, 11 different supervised and semi-supervised classifiers were trained and assessed resulting in a promising performance, with the weighted f-measure ranging from 0.87 for Problem 1 to 0.70 for the most challenging Problem 3. By integrating prediction results of the 2-class classifiers into the 3-class classifier, we further improved its performance for Problem 3. To demonstrate the utility of SNP-IN tool, it was applied to study the nsSNP-induced rewiring of two disease-centered networks. The accurate and balanced performance of SNP-IN tool makes it readily available to study the rewiring of large-scale protein-protein interaction networks, and can be useful for functional annotation of disease-associated SNPs. SNIP-IN tool is freely accessible as a web-server at http://korkinlab.org/snpintool/.