Combination analysis of genome-wide association and transcriptome sequencing of residual feed intake in quality chickens
文献类型: 外文期刊
第一作者: Xu, Zhenqiang
作者: Xu, Zhenqiang;Zhang, Zhe;Nie, Qinghua;Xu, Jiguo;Zhang, Dexiang;Zhang, Xiquan;Xu, Zhenqiang;Zhang, Zhe;Nie, Qinghua;Xu, Jiguo;Zhang, Dexiang;Zhang, Xiquan;Xu, Zhenqiang;Ji, Congliang;Zhang, Yan;Zhang, Dexiang
作者机构:
关键词: Residual feed intake;Genome-wide association study;RNA-sequencing;Quality chickens
期刊名称:BMC GENOMICS ( 影响因子:3.969; 五年影响因子:4.478 )
ISSN: 1471-2164
年卷期: 2016 年 17 卷
页码:
收录情况: SCI
摘要: Background: Residual feed intake (RFI) is a powerful indicator for energy utilization efficiency and responds to selection. Low RFI selection enables a reduction in feed intake without affecting growth performance. However, the effective variants or major genes dedicated to phenotypic differences in RFI in quality chickens are unclear. Therefore, a genome-wide association study (GWAS) and RNA sequencing were performed on RFI to identify genetic variants and potential candidate genes associated with energy improvement. Results: A lower average daily feed intake was found in low-RFI birds compared to high-RFI birds. The heritability of RFI measured from 44 to 83 d of age was 0.35. GWAS showed that 32 of the significant single nucleotide polymorphisms (SNPs) associated with the RFI (P < 10(-4)) accounted for 53.01 % of the additive genetic variance. More than half of the effective SNPs were located in a 1 Mb region (16.3-17.3 Mb) of chicken (Gallus gallus) chromosome (GGA) 12. Thus, focusing on this region should enable a deeper understanding of energy utilization. RNA sequencing was performed to profile the liver transcriptomes of four male chickens selected from the high and low tails of the RFI. One hundred and sixteen unique genes were identified as differentially expressed genes (DEGs). Some of these genes were relevant to appetite, cell activities, and fat metabolism, such as CCKAR, HSP90B1, and PCK1. Some potential genes within the 500 Kb flanking region of the significant RFI-related SNPs detected in GWAS (i.e., MGP, HIST1H110, HIST1H2A4L3, OC3, NR0B2, PER2, ST6GALNAC2, and G0S2) were also identified as DEGs in chickens with divergent RFIs. Conclusions: The GWAS findings showed that the 1 Mb narrow region of GGA12 should be important because it contained genes involved in energy-consuming processes, such as lipogenesis, social behavior, and immunity. Similar results were obtained in the transcriptome sequencing experiments. In general, low-RFI birds seemed to optimize energy employment by reducing energy expenditure in cell activities, immune responses, and physical activity compared to eating.
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