scholarly journals Searching for causal networks involving latent variables in complex traits: Application to growth, carcass, and meat quality traits in pigs1

2015 ◽  
Vol 93 (10) ◽  
pp. 4617-4623 ◽  
Author(s):  
F. Peñagaricano ◽  
B. D. Valente ◽  
J. P. Steibel ◽  
R. O. Bates ◽  
C. W. Ernst ◽  
...  
2020 ◽  
Author(s):  
Piush Khanal ◽  
Christian Maltecca ◽  
Clint Schwab ◽  
Justin Fix ◽  
Francesco Tiezzi

Abstract BackgroundSwine gut microbiome constitutes a portion of the whole genome and has potential to affect different phenotypes. More recently, research is more directed towards association of gut microbiome and different traits in swine. However, the contribution of microbial composition to the phenotypic variation of meat quality and carcass composition traits in pigs has not been explored yet. The objectives of this study are to estimate the microbiabilities for different meat quality and carcass composition traits; to investigate the impact of intestinal microbiome on heritability estimates; to estimate the correlation between microbial diversity and meat quality and carcass composition traits; and to estimate the microbial correlation between the meat quality and carcass composition traits in a commercial swine population.ResultsThe contribution of the microbiome to carcass composition and meat quality traits was prominent although it varied over time, increasing from weaning to off test for most traits. Microbiability estimates of carcass composition traits were greater than that of meat quality traits. Among all of the traits analyzed, belly weight had higher microbiability estimate (0.29 ± 0.04). Adding microbiome information did not affect the estimates of genomic heritability of meat quality traits but affected the estimates of carcass composition traits. Fat depth had greater decrease (10%) in genomic heritability. High microbial correlations were found among several traits. This suggested that genomic correlation was partially contributed by genetic similarity of microbiome composition.ConclusionsResults indicate that better understanding of microbial composition could aid the improvement of complex traits, particularly the carcass composition traits in swine by inclusion of microbiome information in the genetic evaluation process.


2021 ◽  
Author(s):  
Frédéric Hérault ◽  
Annie Vincent ◽  
Ando Yoanne Randriamanantena ◽  
Marie Damon ◽  
Pierre Cherel ◽  
...  

Abstract Background: Many quantitative trait loci (QTLs) affecting pig meat and carcass quality traits have been reported. However, in most cases, the length of these phenotypic QTLs (pQTLs) is large. Hence, the identification of candidate genes and causative polymorphisms hidden behind those pQTLs remains a difficult task. Combining gene expression, phenotype and genotype data in an integrative genomics approach may help to identify regulatory networks and pathways underlying such complex traits. In the present study, we used genome-wide association study (GWAS) and linkage disequilibrium linkage analysis (LDLA) approaches to identify longissimus muscle (LM) and semimembranosus muscle (SM) expression QTLs (eQTLs). The locations of these eQTLs were compared to those of pQTLs previously mapped in the same population of commercial-type pigs. Colocalized eQTLs/pQTLs could help to identify candidate genes and pathways involved in pig carcass and meat quality trait determination. Results: Both approaches led us to identify 1,253 and 1,109 genome-wide significant eQTLs for LM and SM, respectively. We identified only one common eQTL between the two muscles and a few significant common eQTLs between methodologies : 16 in SM and 1 in LM. A total of 192 overlapping locations were identified between eQTLs and pQTLs. Colocalization highlighted some genes involved in muscle development, adipogenic processes or ion calcium homeostasis. These eQTLs allowed us to refine previously identified pQTLs related to carcass and meat quality traits. However, in most cases, the refined loci were still large and contained several coding and noncoding genes. Conclusions: Our results shed light on the muscle-specific genetic control governing mRNA expression and hence controlling the development of pig carcass and meat quality traits. Moreover, colocations between eQTLs and pQTLs implicated genes potentially involved in muscle development, adipogenic processes or ion calcium homeostasis in the pathways governing these traits. Finally, our results allowed us to refine QTLs controlling meat quality traits and to highlight the possible involvement of long noncoding RNAs in the architecture of regulatory networks governing complex traits such as pig carcass and meat quality traits.


Author(s):  
Hugo Teixeira Silva ◽  
José Teodoro Paiva ◽  
Margareth Evangelista Botelho ◽  
Eula Regina Carrara ◽  
Paulo Sávio Lopes ◽  
...  

2013 ◽  
Vol 38 (1) ◽  
pp. 64-68
Author(s):  
Ji ZHU ◽  
Jian LIU ◽  
Jian-bang SUN ◽  
Shi-liu YANG ◽  
Jing-ru LI ◽  
...  

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Simone Savoia ◽  
Andrea Albera ◽  
Alberto Brugiapaglia ◽  
Liliana Di Stasio ◽  
Alessio Cecchinato ◽  
...  

Abstract Background The possibility of assessing meat quality traits over the meat chain is strongly limited, especially in the context of selective breeding which requires a large number of phenotypes. The main objective of this study was to investigate the suitability of portable infrared spectrometers for phenotyping beef cattle aiming to genetically improving the quality of their meat. Meat quality traits (pH, color, water holding capacity, tenderness) were appraised on rib eye muscle samples of 1,327 Piemontese young bulls using traditional (i.e., reference/gold standard) laboratory analyses; the same traits were also predicted from spectra acquired at the abattoir on the intact muscle surface of the same animals 1 d after slaughtering. Genetic parameters were estimated for both laboratory measures of meat quality traits and their spectra-based predictions. Results The prediction performances of the calibration equations, assessed through external validation, were satisfactory for color traits (R2 from 0.52 to 0.80), low for pH and purge losses (R2 around 0.30), and very poor for cooking losses and tenderness (R2 below 0.20). Except for lightness and purge losses, the heritability estimates of most of the predicted traits were lower than those of the measured traits while the genetic correlations between measured and predicted traits were high (average value 0.81). Conclusions Results showed that NIRS predictions of color traits, pH, and purge losses could be used as indicator traits for the indirect genetic selection of the reference quality phenotypes. Results for cooking losses were less effective, while the NIR predictions of tenderness were affected by a relatively high uncertainty of estimate. Overall, genetic selection of some meat quality traits, whose direct phenotyping is difficult, can benefit of the application of infrared spectrometers technology.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Giovanni Bittante ◽  
Simone Savoia ◽  
Alessio Cecchinato ◽  
Sara Pegolo ◽  
Andrea Albera

AbstractSpectroscopic predictions can be used for the genetic improvement of meat quality traits in cattle. No information is however available on the genetics of meat absorbance spectra. This research investigated the phenotypic variation and the heritability of meat absorbance spectra at individual wavelengths in the ultraviolet–visible and near-infrared region (UV–Vis-NIR) obtained with portable spectrometers. Five spectra per instrument were taken on the ribeye surface of 1185 Piemontese young bulls from 93 farms (13,182 Herd-Book pedigree relatives). Linear animal model analyses of 1481 single-wavelengths from UV–Vis-NIRS and 125 from Micro-NIRS were carried out separately. In the overlapping regions, the proportions of phenotypic variance explained by batch/date of slaughter (14 ± 6% and 17 ± 7%,), rearing farm (6 ± 2% and 5 ± 3%), and the residual variances (72 ± 10% and 72 ± 5%) were similar for the UV–Vis-NIRS and Micro-NIRS, but additive genetics (7 ± 2% and 4 ± 2%) and heritability (8.3 ± 2.3% vs 5.1 ± 0.6%) were greater with the Micro-NIRS. Heritability was much greater for the visible fraction (25.2 ± 11.4%), especially the violet, blue and green colors, than for the NIR fraction (5.0 ± 8.0%). These results allow a better understanding of the possibility of using the absorbance of visible and infrared wavelengths correlated with meat quality traits for the genetic improvement in beef cattle.


2018 ◽  
Vol 96 (suppl_3) ◽  
pp. 84-84
Author(s):  
M Abo-Ismail ◽  
J Crowley ◽  
E Akanno ◽  
C Li ◽  
P Stothard ◽  
...  

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