AUTHOR=Ye Shaopan , Chen Zi-Tao , Zheng Rongrong , Diao Shuqi , Teng Jinyan , Yuan Xiaolong , Zhang Hao , Chen Zanmou , Zhang Xiquan , Li Jiaqi , Zhang Zhe 

TITLE=New Insights From Imputed Whole-Genome Sequence-Based Genome-Wide Association Analysis and Transcriptome Analysis: The Genetic Mechanisms Underlying Residual Feed Intake in Chickens

JOURNAL=Frontiers in Genetics

VOLUME=Volume 11 - 2020

YEAR=2020

URL=https://www.frontiersin.org/journals/genetics/articles/10.3389/fgene.2020.00243

DOI=10.3389/fgene.2020.00243

ISSN=1664-8021

ABSTRACT=Poultry feed occupies the largest cost of poultry production, which is estimated up to 70%. Moreover, it is pressure on the agricultural industry to reduce emissions and improve its environmental footprint, simultaneously increasing output to meet the growing demand for protein worldwide. Therefore, improving feed efficiency (FE) play an important role to improve profits and their environmental footprint in broiler production. In this study, using imputed whole genome sequencing (WGS) data, genome-wide association analysis (GWAS) was performed to identify SNPs and genes associated with residual feed intake (RFI) and its component traits. Furthermore, transcriptomic analysis between high- and low-RFI groups was performed to validate candidate genes from GWAS. Results showed that heritability estimates of average daily gain (ADG), average daily feed intake (ADFI), and RFI were 0.29 (0.004), 0.37 (0.005), and 0.38 (0.004), respectively. Using imputed sequence-based GWAS, we identified seven significant SNPs and five candidate genes (MTSS I-BAR domain containing 1, MTSS1; folliculin, FLCN; COP9 signalosome subunit 3, COPS3; 5',3'-nucleotidase, mitochondrial, NT5M; and gametocyte specific factor 1, GTSF1) associated with RFI, twenty significant SNPs and one candidate gene (inositol polyphosphate multikinase, IPMK) associated with ADG, and one significant SNP and one candidate gene (coatomer protein complex subunit alpha, COPA) associated with ADFI. After performing transcriptomic analysis between high- and low-RFI groups, both 38 up-regulated and 26 down-regulated genes were identified in high-RFI group. Furthermore, integrating regional conditional GWAS and transcriptome analysis, ras related dexamethasone induced 1 (RASD1) was the only one overlapped gene associated with RFI, which also suggested that the region (GGA14: 4767015 -4882318) is a new quantitative trait locus (QTL) associated with RFI. In conclusions, using imputed sequence-based GWAS is an efficient method to identify significant SNPs and candidate genes in chicken. Our results provide valuable insights into the genetic mechanisms of RFI and component traits, which would further improve the genetic gain of feed efficiency rapidly and cost-effectively in the context of marker-assisted breeding selection.