» Articles » PMID: 31931702

Genetic Architecture of Quantitative Traits in Beef Cattle Revealed by Genome Wide Association Studies of Imputed Whole Genome Sequence Variants: I: Feed Efficiency and Component Traits

Overview
Journal BMC Genomics
Publisher Biomed Central
Specialty Genetics
Date 2020 Jan 15
PMID 31931702
Citations 35
Authors
Affiliations
Soon will be listed here.
Abstract

Background: Genome wide association studies (GWAS) on residual feed intake (RFI) and its component traits including daily dry matter intake (DMI), average daily gain (ADG), and metabolic body weight (MWT) were conducted in a population of 7573 animals from multiple beef cattle breeds based on 7,853,211 imputed whole genome sequence variants. The GWAS results were used to elucidate genetic architectures of the feed efficiency related traits in beef cattle.

Results: The DNA variant allele substitution effects approximated a bell-shaped distribution for all the traits while the distribution of additive genetic variances explained by single DNA variants followed a scaled inverse chi-squared distribution to a greater extent. With a threshold of P-value < 1.00E-05, 16, 72, 88, and 116 lead DNA variants on multiple chromosomes were significantly associated with RFI, DMI, ADG, and MWT, respectively. In addition, lead DNA variants with potentially large pleiotropic effects on DMI, ADG, and MWT were found on chromosomes 6, 14 and 20. On average, missense, 3'UTR, 5'UTR, and other regulatory region variants exhibited larger allele substitution effects in comparison to other functional classes. Intergenic and intron variants captured smaller proportions of additive genetic variance per DNA variant. Instead 3'UTR and synonymous variants explained a greater amount of genetic variance per DNA variant for all the traits examined while missense, 5'UTR and other regulatory region variants accounted for relatively more additive genetic variance per sequence variant for RFI and ADG, respectively. In total, 25 to 27 enriched cellular and molecular functions were identified with lipid metabolism and carbohydrate metabolism being the most significant for the feed efficiency traits.

Conclusions: RFI is controlled by many DNA variants with relatively small effects whereas DMI, ADG, and MWT are influenced by a few DNA variants with large effects and many DNA variants with small effects. Nucleotide polymorphisms in regulatory region and synonymous functional classes play a more important role per sequence variant in determining variation of the feed efficiency traits. The genetic architecture as revealed by the GWAS of the imputed 7,853,211 DNA variants will improve our understanding on the genetic control of feed efficiency traits in beef cattle.

Citing Articles

Variations in rumen microbiota and host genome impacted feed efficiency in goat breeds.

Rabee A, Abou-Souliman I, Yousif A, Lamara M, El-Sherbieny M, Elwakeel E Front Microbiol. 2025; 16:1492742.

PMID: 39944650 PMC: 11813914. DOI: 10.3389/fmicb.2025.1492742.


Assessment of genome complementarity in three beef-on-dairy crossbreds reveals sire-specific effects on production traits with comparable rates of genomic inbreeding reduction.

Lindtke D, Lerch S, Morel I, Neuditschko M BMC Genomics. 2024; 25(1):1118.

PMID: 39567870 PMC: 11577664. DOI: 10.1186/s12864-024-11029-z.


LCoRL Regulates Growth and Metabolism.

Wyler S, Gahlot S, Bideyan L, Yip C, Dushime J, Chen B Endocrinology. 2024; 165(12).

PMID: 39467326 PMC: 11538781. DOI: 10.1210/endocr/bqae146.


Scans for Signatures of Selection in Genomes of Wagyu and Buryat Cattle Breeds Reveal Candidate Genes and Genetic Variants for Adaptive Phenotypes and Production Traits.

Igoshin A, Romashov G, Yurchenko A, Yudin N, Larkin D Animals (Basel). 2024; 14(14).

PMID: 39061521 PMC: 11274160. DOI: 10.3390/ani14142059.


Polymorphism rs2327430 in TCF21 predicts the risk and prognosis of gastric cancer by affecting the binding between TFAP2A and TCF21.

Zhou X, Shen K, Cao S, Li P, Xiao J, Dong J Cancer Cell Int. 2024; 24(1):159.

PMID: 38714991 PMC: 11075239. DOI: 10.1186/s12935-024-03343-z.


References
1.
Lee S, Wray N, Goddard M, Visscher P . Estimating missing heritability for disease from genome-wide association studies. Am J Hum Genet. 2011; 88(3):294-305. PMC: 3059431. DOI: 10.1016/j.ajhg.2011.02.002. View

2.
Kita Y, Mimori K, Iwatsuki M, Yokobori T, Ieta K, Tanaka F . STC2: a predictive marker for lymph node metastasis in esophageal squamous-cell carcinoma. Ann Surg Oncol. 2010; 18(1):261-72. DOI: 10.1245/s10434-010-1271-1. View

3.
Zhang W, Li J, Guo Y, Zhang L, Xu L, Gao X . Multi-strategy genome-wide association studies identify the DCAF16-NCAPG region as a susceptibility locus for average daily gain in cattle. Sci Rep. 2016; 6:38073. PMC: 5125095. DOI: 10.1038/srep38073. View

4.
Hu Z, Park C, Reecy J . Building a livestock genetic and genomic information knowledgebase through integrative developments of Animal QTLdb and CorrDB. Nucleic Acids Res. 2018; 47(D1):D701-D710. PMC: 6323967. DOI: 10.1093/nar/gky1084. View

5.
Lai E . Micro RNAs are complementary to 3' UTR sequence motifs that mediate negative post-transcriptional regulation. Nat Genet. 2002; 30(4):363-4. DOI: 10.1038/ng865. View