Prospecting genes associated with navel length, coat and scrotal circumference traits in Canchim cattle

Romero, Andrea; Siqueira, F.; Santiago, G. G.; Regitano, Luciana Correia de Almeida; Júnior, Maury Dorta de Souza; Júnior, Roberto Augusto de Almeida Torres; Nascimento, André Vieira do; Barufatti, Alexéia

doi:10.1016/j.livsci.2018.02.004

Cited by 6 publications

(3 citation statements)

References 42 publications

(42 reference statements)

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“…The practicality of this and any GS approach depends on knowledge of the genetic architecture of the traits of interest, including heritability, the number of underlying causative mutations, and their effect sizes (Huang and Mackay, 2016). Given the wide variety of complexity of genetic architectures reported in recent studies (Campbell et al, 2017; Divilov et al, 2018; Muqaddasi et al, 2017; da Silva Romero et al, 2018), an RR‐BLUP model augmented with unpenalized fixed‐effect marker covariates could theoretically accelerate the breeding cycles of many crop and livestock species.…”

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confidence: 99%

Evaluation of RR‐BLUP Genomic Selection Models that Incorporate Peak Genome‐Wide Association Study Signals in Maize and Sorghum

Rice

Lipka

2019

The Plant Genome

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Core Ideas Augmenting RR‐BLUP models with peak GWAS markers can hypothetically boost prediction accuracy We conducted a simulation study in maize and sorghum to test the performance of such models For most of the simulated traits, we observed a decrease in prediction accuracy These augmented models tended to yield greater variability in prediction accuracy An increase of bias in predicted breeding values from these models was noted Certain agronomic crop traits are complex and thus governed by many small‐effect loci. Statistical models typically used in a genome‐wide association study (GWAS) and genomic selection (GS) quantify these signals by assessing genomic marker contributions in linkage disequilibrium (LD) with these loci to trait variation. These models have been used in separate quantitative genetics contexts until recently, when, in published studies, the predictive ability of GS models that include peak associated markers from a GWAS as fixed‐effect covariates was assessed. Previous work suggests that such models could be useful for predicting traits controlled by several large‐effect and many small‐effect genes. We expand this work by evaluating simulated traits from diversity panels in maize (Zea mays L.) and sorghum [Sorghum bicolor (L.) Moench] using ridge‐regression best linear unbiased prediction (RR‐BLUP) models that include fixed‐effect covariates tagging peak GWAS signals. The ability of such covariates to increase GS prediction accuracy in the RR‐BLUP model under a wide variety of genetic architectures and genomic backgrounds was quantified. Of the 216 genetic architectures that we simulated, we identified 60 where the addition of fixed‐effect covariates boosted prediction accuracy. However, for the majority of the simulated data, no increase or a decrease in prediction accuracy was observed. We also noted several instances where the inclusion of fixed‐effect covariates increased both the variability of prediction accuracies and the bias of the genomic estimated breeding values. We therefore recommend that the performance of such a GS model be explored on a trait‐by‐trait basis prior to its implementation into a breeding program.

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confidence: 99%

Evaluation of RR‐BLUP Genomic Selection Models that Incorporate Peak Genome‐Wide Association Study Signals in Maize and Sorghum

Rice

Lipka

2019

The Plant Genome

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“…Local ancestry tracts may integrate linkage disequilibrium patterns which are crucial in association studies (e.g. Shriner, 2017; Li, Kemppainen, Rastas, & Merilä, 2018). The nine groups include the two hatchery samples (Atlantic, Mediterranean), then seven distinct samples of wild-caught trout.…”

Section: Methodsmentioning

confidence: 99%

Spotting genome-wide pigmentation variation in a brown trout admixture context

Valette¹,

Leitwein

Lascaux³

et al. 2020

Preprint

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Colour and pigmentation variation attracted fish biologists for a while, but high-throughput genomic studies investigating the molecular basis of body pigmentation remain still limited to few species and conservation biology issues ignored. Using 75,684 SNPs, we investigated the genomic basis of pigmentation pattern variation among individuals of the Atlantic and Mediterranean clades of the brown trout (Salmo trutta), a polytypic species in which Atlantic hatchery individuals are commonly used to supplement local wild populations. Using redundancy analyses and genome-wide association studies, a set of 384 “colour patterning loci” (CPL) significantly correlated with pigmentation traits such as the number of red and black spots on flanks, but also the presence of a large black stain on the opercular bone was identified. CPLs map onto 35 out of 40 brown trout linkage groups indicating a polygenic basis to pigmentation patterns. They are mostly located in coding regions (43.4%) of 223 candidate genes, and correspond to GO-terms known to be involved in pigmentation (e.g. calcium and ion-binding, cell adhesion). Annotated genes especially include 24 candidates with known pigmentation effects (e.g. SOX10, PEML, SLC45A2), but also the Gap-junction Δ2 (GJD2) gene that was previously showed be differentially expressed in trout skin. Patterns of admixture were found significantly distinct when using either the full SNP data set or the set of CPLs, indicating that pigmentation patterns accessible to practitioners are not a reliable proxy of genome-wide admixture. Consequences for management are discussed.

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“…Some visual assessment methods of Zebu breeds also attribute navel and breed quality (BQ) scores. The size and shape of the navel are important traits, especially for animals raised on pastures with shrubs because males with pendulous navels are more susceptible to injuries, reducing their use or making them unsuitable for breeding (Bignardi et al , 2011; Holroyd & McGowan, 2014; Boligon et al , 2016; Abreu, Mota et al, 2018; Romero et al, 2018). In contrast, all items observed in the breed standard are included in the BQ score, which is a negotiation tool in the market, particularly in elite herds (Faria et al , 2009; Boligon et al , 2016; Abreu, Mota et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

Genetic analysis of growth, visual scores, height, and carcass traits in Nelore cattle

Silveira

Schmidt

Campos

et al. 2021

Animal Science Journal

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Covariance components were estimated for growth traits (BW, birth weight; WW, weaning weight; YW, yearling weight), visual scores (BQ, breed quality; CS, conformation; MS, muscling; NS, navel; PS, finishing precocity), hip height (HH), and carcass traits (BF, backfat thickness; LMA, longissimus muscle area) measured at yearling. Genetic gains were obtained and validation models on direct and maternal effects for BW and WW were fitted. Genetic correlations of growth traits with CS, PS, MS, and HH ranged from 0.20 AE 0.01 to 0.94 AE 0.01 and were positive and low with NS (0.11 AE 0.01 to 0.20 AE 0.01) and favorable with BQ (0.14 AE 0.02 to 0.37 AE 0.02). Null to moderate genetic correlations were obtained between growth and carcass traits. Genetic gains were positive and significant, except for BW. An increase of 0.76 and 0.72 kg is expected for BW and WW, respectively, per unit increase in estimated breeding value (EBV) for direct effect and an additional 0.74 and 1.43, respectively, kg per unit increase in EBV for the maternal effect.Monitoring genetic gains for HH and NS is relevant to maintain an adequate body size and a navel morphological correction, if necessary. Simultaneous selection for growth, morphological, and carcass traits in line with improve maternal performance is a feasible strategy to increase herd productivity.

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Prospecting genes associated with navel length, coat and scrotal circumference traits in Canchim cattle

Cited by 6 publications

References 42 publications

Evaluation of RR‐BLUP Genomic Selection Models that Incorporate Peak Genome‐Wide Association Study Signals in Maize and Sorghum

Evaluation of RR‐BLUP Genomic Selection Models that Incorporate Peak Genome‐Wide Association Study Signals in Maize and Sorghum

Spotting genome-wide pigmentation variation in a brown trout admixture context

Genetic analysis of growth, visual scores, height, and carcass traits in Nelore cattle

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