Literature DB >> 33458906

Genomic imprinting variances of beef carcass traits and physiochemical characteristics in Japanese Black cattle.

Keiichi Inoue1, Yoshinobu Inoue2, Toshiaki Oe3, Masami Nishimura2.   

Abstract

The objective of this study was to estimate variance components related to imprinting for carcass traits and physiochemical characteristics in Japanese Black cattle. The carcass records obtained from 4,220 Japanese Black feedlot cattle included carcass weight (CW), rib eye area (REA), rib thickness, subcutaneous fat thickness, and beef marbling score (BMS), and the physiochemical characteristics were fat, moisture, glycogen per proportion of moisture content, oleic acid, and monounsaturated fatty acids (MUFA). To detect gametic effects, an imprinting model was fitted. High additive heritabilities were estimated for all traits (from 0.516 for glycogen to 0.853 for fat) and were reduced in Mendelian heritability. The range of the differences was from 0.002 (CW) to 0.331 (fat and moisture), and the reductions were due to their imprinting variances. The ratio of the imprinting variance to the total additive genetic variance for REA (0.374), BMS (0.291), fat (0.387), moisture (0.388), and MUFA (0.337) were large (p < 0.05). These imprinting variances were due to the maternal contribution and suggested the existence of maternally expressed genomic imprinting effects on the traits in Japanese Black cattle. Therefore, maternal gametic effects should be considered in breeding programs for Japanese Black cattle.
© 2021 Japanese Society of Animal Science.

Entities:  

Keywords:  Japanese Black cattle; carcass trait; fatty acid composition; genomic imprinting; glycogen

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Year:  2021        PMID: 33458906     DOI: 10.1111/asj.13504

Source DB:  PubMed          Journal:  Anim Sci J        ISSN: 1344-3941            Impact factor:   1.749


  2 in total

1.  Detection of Genomic Imprinting for Carcass Traits in Cattle Using Imputed High-Density Genotype Data.

Authors:  David Kenny; Roy D Sleator; Craig P Murphy; Ross D Evans; Donagh P Berry
Journal:  Front Genet       Date:  2022-07-15       Impact factor: 4.772

2.  Blood Transcriptome Analysis of Beef Cow with Different Parity Revealed Candidate Genes and Gene Networks Regulating the Postpartum Diseases.

Authors:  Yanda Yang; Chencheng Chang; Batu Baiyin; Zaixia Liu; Lili Guo; Le Zhou; Bin Liu; Caixia Shi; Wenguang Zhang
Journal:  Genes (Basel)       Date:  2022-09-19       Impact factor: 4.141

  2 in total

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