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Genetic Association Analysis for Relative Growths of Body Compositions and Metabolic Traits to Body Weights in Broilers.

ABSTRACT: In animal breeding, body components and metabolic traits always fall behind body weights in genetic improvement, which leads to the decline in standards and qualities of animal products. Phenotypically, the relative growth of multiple body components and metabolic traits relative to body weights are characterized by using joint allometric scaling models, and then random regression models (RRMs) are constructed to map quantitative trait loci (QTLs) for relative grwoth allometries of body compositions and metabolic traits in chicken. Referred to as real joint allometric scaling models, statistical utility of the so-called LASSO-RRM mapping method is given a demonstration by computer simulation analysis. Using the F2 population by crossing broiler × Fayoumi, we formulated optimal joint allometric scaling models of fat, shank weight (shank-w) and liver as well as thyroxine (T4) and glucose (GLC) to body weights. For body compositions, a total of 9 QTLs, including 4 additive and 5 dominant QTLs, were detected to control the allometric scalings of fat, shank-w, and liver to body weights; while a total of 10 QTLs of which 6 were dominant, were mapped to govern the allometries of T4 and GLC to body weights. We characterized relative growths of body compositions and metabolic traits to body weights in broilers with joint allometric scaling models and detected QTLs for the allometry scalings of the relative growths by using RRMs. The identified QTLs, including their highly linked genetic markers, could be used to order relative growths of the body components or metabolic traits to body weights in marker-assisted breeding programs for improving the standard and quality of broiler meat products.

SUBMITTER: Zhang Y

PROVIDER: S-EPMC7916405 | biostudies-literature | 2021 Feb

REPOSITORIES: biostudies-literature

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Genetic Association Analysis for Relative Growths of Body Compositions and Metabolic Traits to Body Weights in Broilers.

Zhang Ying Y Zhang Hengyu H Zhao Yunfeng Y Zhou Xiaojing X Du Jie J Yang Runqing R

Animals : an open access journal from MDPI 20210210 2

In animal breeding, body components and metabolic traits always fall behind body weights in genetic improvement, which leads to the decline in standards and qualities of animal products. Phenotypically, the relative growth of multiple body components and metabolic traits relative to body weights are characterized by using joint allometric scaling models, and then random regression models (RRMs) are constructed to map quantitative trait loci (QTLs) for relative grwoth allometries of body composit ...[more]

PMID: 33578694

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Project description:BackgroundThe musculoskeletal system participates in the pathology of metabolic disorders. Several studies have focused on body composition changes; however, the adipose tissue between muscle bundles with different metabolic statuses has rarely been studied. This study sought to explore the association between body compositions and metabolic disorders in Asians, and identify whether these body compositions can be used to detect metabolic disorders with different waist circumferences (WCs) by computed tomography (CT).MethodsA total of 116 subjects were included in the study and categorized into the following four groups according to WC and metabolic syndrome (MS): (I) the healthy control group; (II) the normal WC with metabolic disorder group; (III) the normal WC with MS group; and (IV) the larger WC with MS group. The International Diabetes Federation (IDF) criteria based on WC, laboratory tests, body mass index (BMI), and medical history was used to diagnose MS. Body composition parameters, such as muscle attenuation, the cross-sectional area of subcutaneous adipose tissue (SAT), muscle, extramyocellular lipid (EMCL), visceral adipose tissue (VAT), and the ratios between different compositions [e.g., the SMR (SAT/muscle), EMR (EMCL/muscle), and VMR (VAT/muscle)] were calculated for the thigh and abdomen. The areas under the curve (AUCs) of the receiver operating characteristic (ROC) curves adjusted for multiple comparisons were used to discriminate among metabolic disorders.ResultsThe groups with metabolic disorders had more SAT (P=0.001) and EMCL (P=0.040) in the thigh, and more VAT (P=0.001) and a higher SMR (P<0.001) in the abdomen. EMCL and muscle attenuation in the thigh (AUCs =0.790 and 0.791), and the VMR and SMR in the abdomen were better able to diagnose metabolic disorders (AUCs =0.752 and 0.746) than other body composition parameters. While SAT and EMCL in the thigh (AUCs =0.768 and 0.760), and VAT and the VMR in the abdomen (AUCs =0.788 and 0.775) were better able to diagnose MS than other parameters.ConclusionsBody composition parameters for the thigh and abdomen could assist in detecting patients with an increased risk of MS.

Dataset Information

Genetic Association Analysis for Relative Growths of Body Compositions and Metabolic Traits to Body Weights in Broilers.

Publications

Genetic Association Analysis for Relative Growths of Body Compositions and Metabolic Traits to Body Weights in Broilers.

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