In silico approach to calculate the transcript capacity.

We sought the novel concept, transcript capacity (TC) and analyzed TC. Our approach to estimate TC was through an in silico method. TC refers to the capacity that a transcript exerts in a cell as enzyme or protein function after translation. We used the genome-wide association study (GWAS) beta effect and transcription level in RNA-sequencing to estimate TC. The trait was body fat percent and the transcript reads were obtained from the human protein atlas. The assumption was that the GWAS beta effect is the gene's effect and TC was related to the corresponding gene effect and transcript reads. Further, we surveyed gene ontology (GO) in the highest TC and the lowest TC genes. The most frequent GOs with the highest TC were neuronal-related and cell projection organization related. The most frequent GOs with the lowest TC were wound-healing related and embryo development related. We expect that our analysis contributes to estimating TC in the diverse species and playing a benevolent role to the new bioinformatic analysis.

In silico approaches to discover the functional impact of non-synonymous single nucleotide polymorphisms in selective sweep regions of the Landrace genome.

OBJECTIVE: The aim of this study was to discover the functional impact of non-synonymous single nucleotide polymorphisms (nsSNPs) that were found in selective sweep regions of the Landrace genome. METHODS: Whole-genome re-sequencing data were obtained from 40 pigs, including 14 Landrace, 16 Yorkshire, and 10 wild boars, which were generated with the Illumina HiSeq 2000 platform. The nsSNPs in the selective sweep regions of the Landrace genome were identified, and the impacts of these variations on protein function were predicted to reveal their potential association with traits of the Landrace breed, such as reproductive capacity. RESULTS: Total of 53,998 nsSNPs in the mapped regions of pigs were identified, and among them, 345 nsSNPs were found in the selective sweep regions of the Landrace genome which were reported previously. The genes featuring these nsSNPs fell into various functional categories, such as reproductive capacity or growth and development during the perinatal period. The impacts of amino acid sequence changes by nsSNPs on protein function were predicted using two in silico SNP prediction algorithms, i.e., sorting intolerant from tolerant and polymorphism phenotyping v2, to reveal their potential roles in biological processes that might be associated with the reproductive capacity of the Landrace breed. CONCLUSION: The findings elucidated the domestication history of the Landrace breed and illustrated how Landrace domestication led to patterns of genetic variation related to superior reproductive capacity. Our novel findings will help understand the process of Landrace domestication at the genome level and provide SNPs that are informative for breeding.