Genome-Wide Association Study on Reproductive Traits Using Imputation-Based Whole-Genome Sequence Data in Yorkshire Pigs.
Jingchun SunJinhong XiaoYifan JiangYaxin WangMinghao CaoJialin WeiTaiyong YuXiangdong DingGong-She YangPublished in: Genes (2023)
Reproductive traits have a key impact on production efficiency in the pig industry. It is necessary to identify the genetic structure of potential genes that influence reproductive traits. In this study, a genome-wide association study (GWAS) based on chip and imputed data of five reproductive traits, namely, total number born (TNB), number born alive (NBA), litter birth weight (LBW), gestation length (GL), and number of weaned (NW), was performed in Yorkshire pigs. In total, 272 of 2844 pigs with reproductive records were genotyped using KPS Porcine Breeding SNP Chips, and then chip data were imputed to sequencing data using two online software programs: the Pig Haplotype Reference Panel (PHARP v2) and Swine Imputation Server (SWIM 1.0). After quality control, we performed GWAS based on chip data and the two different imputation databases by using fixed and random model circulating probability unification (FarmCPU) models. We discovered 71 genome-wide significant SNPs and 25 potential candidate genes (e.g., SMAD4 , RPS6KA2 , CAMK2A , NDST1 , and ADCY5 ). Functional enrichment analysis revealed that these genes are mainly enriched in the calcium signaling pathway, ovarian steroidogenesis, and GnRH signaling pathways. In conclusion, our results help to clarify the genetic basis of porcine reproductive traits and provide molecular markers for genomic selection in pig breeding.
Keyphrases
- genome wide
- dna methylation
- genome wide association study
- copy number
- electronic health record
- signaling pathway
- big data
- gestational age
- high throughput
- birth weight
- data analysis
- quality control
- epithelial mesenchymal transition
- preterm infants
- social media
- gene expression
- low birth weight
- machine learning
- healthcare
- pi k akt
- deep learning
- physical activity
- preterm birth
- cell proliferation
- public health
- transcription factor
- induced apoptosis
- human health
- artificial intelligence
- single molecule
- amino acid