Literature DB >> 17468416

Genetic and phenotypic relationships of serum leptin concentration with performance, efficiency of gain, and carcass merit of feedlot cattle.

J D Nkrumah1, D H Keisler, D H Crews, J A Basarab, Z Wang, C Li, M A Price, E K Okine, S S Moore.   

Abstract

Leptin is the hormone product of the obese gene that is synthesized and predominantly expressed by adipocytes. This study estimated the genetic variation in serum leptin concentration and evaluated the genetic and phenotypic relationships of serum leptin concentration with performance, efficiency of gain, and carcass merit. There were 464 steers with records for serum leptin concentration, performance, and efficiency of gain and 381 steers with records for carcass traits. The analyses included a total of 813 steers, including those without phenotypic records. Phenotypic and genetic parameter estimates were obtained using SAS and ASREML, respectively. Serum leptin concentration was moderately heritable (h2 = 0.34 +/- 0.13) and averaged 13.91 (SD = 5.74) ng/mL. Sire breed differences in serum leptin concentration correlated well with breed differences in body composition. Specifically, the serum leptin concentration was 20% greater in Angus-sired steers compared with Charolais-sired steers (P < 0.001). Consequently, ultrasound backfat (27%), carcass 12th-rib fat (31%), ultrasound marbling (14%), and carcass marbling (15%) were less in Charolais- than Angus-sired steers (P < 0.001). Conversely, carcass LM area (P = 0.05) and carcass lean meat yield (P < 0.001) were greater in Charolais- compared with Angus-sired steers. Steers with greater serum leptin concentration also had greater DMI (P < 0.001), greater residual feed intake (P = 0.04), and partial efficiency of growth (P = 0.01), but did not differ in feed conversion ratio (P > 0.10). Serum leptin concentration was correlated phenotypically with ultrasound backfat (r = 0.41; P < 0.001), carcass 12th-rib fat (r = 0.42; P < 0.001), ultrasound marbling (r = 0.25; P < 0.01), carcass marbling (r = 0.28; P < 0.01), ultrasound LM area (r = -0.19; P < 0.01), carcass LM area (r = -0.17; P < 0.05), lean meat yield (r = -0.38; P < 0.001), and yield grade (r = 0.32; P < 0.001). The corresponding genetic correlations were generally greater than the phenotypic correlations and included ultrasound backfat (r = 0.76 +/- 0.19), carcass 12th-rib fat (r = 0.54 +/- 0.23), ultrasound marbling (r = 0.27 +/- 0.22), carcass marbling (r = 0.76 +/- 0.21), ultrasound LM area (r = -0.71 +/- 0.19), carcass LM area (r = -0.75 +/- 0.20), lean meat yield (r = -0.59 +/- 0.22), and yield grade (r = 0.39 +/- 0.26). Serum leptin concentration can be a valuable tool that can be incorporated into appropriate selection programs to favorably improve the carcass merit of cattle.

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Year:  2007        PMID: 17468416     DOI: 10.2527/jas.2006-764

Source DB:  PubMed          Journal:  J Anim Sci        ISSN: 0021-8812            Impact factor:   3.159


  11 in total

1.  Adipose depots differ in cellularity, adipokines produced, gene expression, and cell systems.

Authors:  Michael V Dodson; Min Du; Songbo Wang; Werner G Bergen; Melinda Fernyhough-Culver; Urmila Basu; Sylvia P Poulos; Gary J Hausman
Journal:  Adipocyte       Date:  2014-12-10       Impact factor: 4.534

2.  Genetic and phenotypic associations of feed efficiency with growth and carcass traits in Australian Angus cattle.

Authors:  José Antonio Torres-Vázquez; Julius H J van der Werf; Samuel A Clark
Journal:  J Anim Sci       Date:  2018-11-21       Impact factor: 3.159

3.  Phenotypic and genetic correlations of fatty acid composition in subcutaneous adipose tissue with carcass merit and meat tenderness traits in Canadian beef cattle.

Authors:  C Ekine-Dzivenu; M Vinsky; J A Basarab; J L Aalhus; M E R Dugan; C Li
Journal:  J Anim Sci       Date:  2017-12       Impact factor: 3.159

4.  Evaluation of Bovine chemerin (RARRES2) Gene Variation on Beef Cattle Production Traits.

Authors:  Amanda K Lindholm-Perry; Larry A Kuehn; Lea A Rempel; Timothy P L Smith; Robert A Cushman; Tara G McDaneld; Tommy L Wheeler; Steven D Shackelford; David A King; Harvey C Freetly
Journal:  Front Genet       Date:  2012-03-29       Impact factor: 4.599

5.  Systems biology analysis merging phenotype, metabolomic and genomic data identifies Non-SMC Condensin I Complex, Subunit G (NCAPG) and cellular maintenance processes as major contributors to genetic variability in bovine feed efficiency.

Authors:  Philipp Widmann; Antonio Reverter; Rosemarie Weikard; Karsten Suhre; Harald M Hammon; Elke Albrecht; Christa Kuehn
Journal:  PLoS One       Date:  2015-04-15       Impact factor: 3.240

6.  The non-synonymous mutation in bovine SPP1 gene influences carcass weight.

Authors:  Hirokazu Matsumoto; Ryosuke Kohara; Makoto Sugi; Azumi Usui; Kenji Oyama; Hideyuki Mannen; Shinji Sasazaki
Journal:  Heliyon       Date:  2019-12-13

7.  Integrative analyses of genomic and metabolomic data reveal genetic mechanisms associated with carcass merit traits in beef cattle.

Authors:  Jiyuan Li; Yining Wang; Robert Mukiibi; Brian Karisa; Graham S Plastow; Changxi Li
Journal:  Sci Rep       Date:  2022-03-01       Impact factor: 4.379

8.  Circulating leptin and its muscle gene expression in Nellore cattle with divergent feed efficiency.

Authors:  Lúcio Flávio Macedo Mota; Cristina Moreira Bonafé; Pâmela Almeida Alexandre; Miguel Henrique Santana; Francisco José Novais; Erika Toriyama; Aldrin Vieira Pires; Saulo da Luz Silva; Paulo Roberto Leme; José Bento Sterman Ferraz; Heidge Fukumasu
Journal:  J Anim Sci Biotechnol       Date:  2017-09-01

9.  Association of residual feed intake with growth and slaughtering performance, blood metabolism, and body composition in growing lambs.

Authors:  Xiaoxue Zhang; Weimin Wang; Futao Mo; Yongfu La; Chong Li; Fadi Li
Journal:  Sci Rep       Date:  2017-10-04       Impact factor: 4.379

10.  Exploring the Regulatory Potential of Long Non-Coding RNA in Feed Efficiency of Indicine Cattle.

Authors:  Pâmela A Alexandre; Antonio Reverter; Roberta B Berezin; Laercio R Porto-Neto; Gabriela Ribeiro; Miguel H A Santana; José Bento S Ferraz; Heidge Fukumasu
Journal:  Genes (Basel)       Date:  2020-08-25       Impact factor: 4.096

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