Integration of a single-step genome-wide association study with a multi-tissue transcriptome analysis provides novel insights into the genetic basis of wool and weight traits in sheep

Authors: ZHAO, BINGRU - China Agricultural University; LUO, HANPENG - China Agricultural University; HUANG, XIXIA - Xinjiang Agricultural University; WEI, CHEN - Xinjiang Agricultural University; DI, JIANG - Xinjiang Agricultural University; TIAN, YUEZHEN - Xinjiang Agricultural University; FU, XUEFENG - Xinjiang Agricultural University; LI, BINGJIE - Sruc-Scotland'S Rural College; Liu, Ge - George; FANG, LINGZHAO - University Of Edinburgh; ZHANG, SHENGLI - China Agricultural University; TIAN, KECHUAN - Xinjiang Agricultural University

Submitted to: Genetic Selection Evolution
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 6/22/2021
Publication Date: 6/30/2021
Citation: Zhao, B., Luo, H., Huang, X., Wei, C., Di, J., Tian, Y., Fu, X., Li, B., Liu, G., Fang, L., Zhang, S., Tian, K. 2021. Integration of a single-step genome-wide association study with a multi-tissue transcriptome analysis provides novel insights into the genetic basis of wool and weight traits in sheep. Genetic Selection Evolution. 53:56. https://doi.org/10.1186/s12711-021-00649-8.
DOI: https://doi.org/10.1186/s12711-021-00649-8

Interpretive Summary: RNA sequencing generates a major source of genomic data. By performing integrative analyses of genome-wide association studies with RNA sequencing data in sheep, we detected tissue-specific genes and trait-relevant tissues and cell types. These results fill our knowledge gaps and provide the foundation for incorporating RNA sequencing data into the future animal breeding program. Farmers, scientist, and policy planners who need improve animal health and production based on genome-enable animal selection will benefit from this study.

Technical Abstract: Background: The genetic improvement of wool and growth traits is critical for sheep industry. Yet, the genetic architecture underlying such agronomic traits is elusive. Here, we conducted a weighted single-step genome-wide association study (WssGWAS) and then integrated the results with large-scale RNA-seq data for five wool and one live weight traits in Merino sheep, including mean fiber diameter (MFD), coefficient of variation of fiber diameter (CVFD), crimp number (CN), mean staple length (MSL), greasy fleece weight (GFW), and live weight (LW). Results: The dataset being analyzed consisted of 7,135 individuals at the age of 15 months with phenotypes, among which 1,216 with high-density genotypes (n = 372,534). The heritability of wool and live weight traits ranged from 0.05 (CVFD) to 0.36 (MFD), with genetic correlations ranging from -0.44 (CN vs. LW) to 0.77 (GFW vs. LW). By integrating GWAS signals with 500 RNA-seq data, representing 87 tissues, we detected tissues and cell types that were relevant with each of these six traits. For instance, liver, muscle and gastrointestinal tract were the top tissues for LW, while leukocytes and macrophage were the top cells for CN. We proposed 54 quantitative trait loci (QTLs) for all six traits, covering 81 candidate genes on 21 different Ovine autosomes. We found that multiple candidate genes showed strong tissue-specific expression. For instance, BNC1 (associated with MFD) and CHRNB1 (LW) were highly and specifically expressed in skin and muscle, respectively. By conducting phenome-wide association studies (PheWAS) in humans, we found that orthologues of several candidate genes were significantly (FDR < 0.05) associated with similar traits in humans. For instance, BNC1 was significantly associated with MFD in sheep and with hair color in humans, while CHRNB1 was significantly associated with LW in sheep and with body mass index in humans. Conclusions: Our current study provided novel insights into the biological and genetic mechanisms underlying wool and live weight traits, which will contribute to the genetic improvement in sheep and cross-species gene mapping of complex traits.