In this study, protein domains with cellulase activity in goat rumen microbes were investigated using metagenomic and bioinformatic analyses. After the complete genome of goat rumen microbes was obtained using a shotgun sequencing method, 217, 892, 109 pair reads were filtered, including only those with 70% identity, 100-bp matches, and thresholds below E−10 using METAIDBA. These filtered contigs were assembled and annotated using blastN against the NCBI nucleotide database. As a result, a microbial community structure with 1431 species was analyzed, among which Prevotella ruminicola 23 bacteria and Butyrivibrio proteoclasticus B316 were the dominant groups. In parallel, 201 sequences related with cellulase activities (EC.3.2.1.4) were obtained through blast searches using the enzyme.dat file provided by the NCBI database. After translating the nucleotide sequence into a protein sequence using Interproscan, 28 protein domains with cellulase activity were identified using the HMMER package with threshold E values below 10−5. Cellulase activity protein domain profiling showed that the major protein domains such as lipase GDSL, cellulase, and Glyco hydro 10 were present in bacterial species with strong cellulase activities. Furthermore, correlation plots clearly displayed the strong positive correlation between some protein domain groups, which was indicative of microbial adaption in the goat rumen based on feeding habits. This is the first metagenomic analysis of cellulase activity protein domains using bioinformatics from the goat rumen.

The modern horse (Equus caballus) is the product of over 50 million yrs of evolution. The athletic abilities of the horse have been enhanced during the past 6000 yrs under domestication. Therefore, the horse serves as a valuable model to understand the physiology and molecular mechanisms of adaptive responses to exercise. The structure and function of skeletal muscle show remarkable plasticity to the physical and metabolic challenges following exercise. Here, we reveal an evolutionary layer of responsiveness to exercise-stress in the skeletal muscle of the racing horse. We analysed differentially expressed genes and their co-expression networks in a large-scale RNA-sequence dataset comparing expression before and after exercise. By estimating genome-wide dN/dS ratios using six mammalian genomes, and FST and iHS using re-sequencing data derived from 20 horses, we were able to peel back the evolutionary layers of adaptations to exercise-stress in the horse. We found that the oldest and thickest layer (dN/dS) consists of system-wide tissue and organ adaptations. We further find that, during the period of horse domestication, the older layer (FST) is mainly responsible for adaptations to inflammation and energy metabolism, and the most recent layer (iHS) for neurological system process, cell adhesion, and proteolysis.