# Identification of single nucleotide polymorphisms (SNPs) potentially associated with residual feed intake in Qinchuan beef cattle by hypothalamus and duodenum RNA-Seq data

## TL;DR

This study identifies SNPs linked to residual feed intake in beef cattle by analyzing RNA-Seq data from brain and gut tissues.

## Contribution

The study provides new insights into SNPs and gene pathways associated with energy metabolism in beef cattle related to feed intake.

## Key findings

- 270,410 and 255,120 SNPs were identified in high and low RFI groups, respectively, with most in intronic regions.
- Genes like ND4, ND5, and ND6 were significantly enriched in mitochondrial and thermogenic pathways.
- Candidate genes such as ATP1A2 and SLC9A4 were linked to RFI energy metabolism.

## Abstract

The regulation of residual feed intake (RFI) in beef cattle involves brain-gut mechanisms due to the interaction between neural signals in the brain and hunger or satiety in the gut. RNA-Seq data contain an extensive resource of untapped SNPs. Therefore, hypothalamic and duodenal tissues from ten extreme RFI individuals were collected, and transcriptome sequenced in this study. All the alignment data were combined according to RFI, and the SNPs in the same group were identified. A total of 270,410 SNPs were found in the high RFI group, and 255,120 SNPs were found in the low RFI group. Most SNPs were detected in the intronic region, followed by the intergenic region, and the exon region accounts for 1.11% and 1.38% in the high and low RFI groups, respectively. Prediction of high-impact SNPs and annotation of the genes in which they are located yielded 83 and 97 genes in the high-RFI and low-RFI groups, respectively. GO enrichment analysis of these genes revealed multiple NADH/NADPH-related pathways, with ND4, ND5, and ND6 significantly enriched as core subunits of NADH dehydrogenase (complex I), and is closely related to mitochondrial function. KEGG enrichment analysis of ND4, ND5, and ND6 genes was enriched in the thermogenic pathway. Multiple genes, such as ATP1A2, SLC9A4, and PLA2G5, were reported to be associated with RFI energy metabolism in the concurrent enrichment analysis. Protein-protein interaction analysis identified multiple potential candidate genes related to energy metabolism that were hypothesized to be potentially associated with the RFI phenotype. The results of this study will help to increase our understanding of identifying SNPs with significant genetic effects and their potential biological functions.