Genomic regions underlying uniformity of yearling weight in Nellore cattle evaluated under different response variables

Abstract

BackgroundIn livestock, residual variance has been studied because of the interest to improve uniformity of production. Several studies have provided evidence that residual variance is partially under genetic control; however, few investigations have elucidated genes that control it. The aim of this study was to identify genomic regions associated with within-family residual variance of yearling weight (YW; N = 423) in Nellore bulls with high density SNP data, using different response variables. For this, solutions from double hierarchical generalized linear models (DHGLM) were used to provide the response variables, as follows: a DGHLM assuming non-null genetic correlation between mean and residual variance (rmv ≠ 0) to obtain deregressed EBV for mean (dEBVm) and residual variance (dEBVv); and a DHGLM assuming rmv = 0 to obtain two alternative response variables for residual variance, dEBVv_r0 and log-transformed variance of estimated residuals (ln_).ResultsThe dEBVm and dEBVv were highly correlated, resulting in common regions associated with mean and residual variance of YW. However, higher effects on variance than the mean showed that these regions had effects on the variance beyond scale effects. More independent association results between mean and residual variance were obtained when null rmv was assumed. While 13 and 4 single nucleotide polymorphisms (SNPs) showed a strong association (Bayes Factor > 20) with dEBVv and ln_, respectively, only suggestive signals were found for dEBVv_r0. All overlapping 1-Mb windows among top 20 between dEBVm and dEBVv were previously associated with growth traits. The potential candidate genes for uniformity are involved in metabolism, stress, inflammatory and immune responses, mineralization, neuronal activity and bone formation.ConclusionsIt is necessary to use a strategy like assuming null rmv to obtain genomic regions associated with uniformity that are not associated with the mean. Genes involved not only in metabolism, but also stress, inflammatory and immune responses, mineralization, neuronal activity and bone formation were the most promising biological candidates for uniformity of YW. Although no clear evidence of using a specific response variable was found, we recommend consider different response variables to study uniformity to increase evidence on candidate regions and biological mechanisms behind it.Electronic supplementary materialThe online version of this article (10.1186/s12864-018-5003-4) contains supplementary material, which is available to authorized users.

Genetics and genomics of uniformity and resilience in livestock and aquaculture species: A review

“…Promising genes were identified in the statistically significant genomic regions. Genes belonging to biological processes such as inflammatory and immune responses, neuronal activity and stress were found in these investigations (Iung et al, 2018;Sell-Kubiak, Duijvesteijn, et al, 2015). Among the stress-related genes, some members of the heat shock protein family were found by Sell-Kubiak, Duijvesteijn, et al (2015) and Iung et al (2018), increasing the evidence that these proteins may play a role in micro-environmental sensitivity of livestock as previously observed in non-livestock species such Drosophila and Arabidopsis (Queitsch, Sangster, & Lindquist, 2002;Rutherford, Hirate, & Swalla, 2007;Sangster et al, 2008).…”

“…Genes belonging to biological processes such as inflammatory and immune responses, neuronal activity and stress were found in these investigations (Iung et al, ; Sell‐Kubiak, Duijvesteijn, et al, ). Among the stress‐related genes, some members of the heat shock protein family were found by Sell‐Kubiak, Duijvesteijn, et al () and Iung et al (), increasing the evidence that these proteins may play a role in micro‐environmental sensitivity of livestock as previously observed in non‐livestock species such Drosophila and Arabidopsis (Queitsch, Sangster, & Lindquist, ; Rutherford, Hirate, & Swalla, ; Sangster et al, ). Heat shock proteins are molecular chaperones that play a role in maintenance of cellular homeostasis in response to stressful situations (see Jee, ; Zabinsky, Mason, Queitsch, & Jarosz, for review).…”

“…For instance, the estimate of residual variance may be on offspring, while the genotypes are available on sires. Recently, a GWAS for residual variance of yearling weight in Nellore cattle compared different response variables, including dEBV and log‐transformed variance of estimated residuals obtained from previous DHGLM analysis assuming null and non‐null r mv (Iung, Mulder, Neves, & Carvalheiro, ). The authors found no clear evidence on the most appropriate response variable and recommended considering multiple response variables to increase evidence on candidate regions and mechanisms regulating residual variance.…”

Genome and chromosome wide association studies for growth traits in Simmental and Simbrah cattle

“…PENK has been associated as a candidate gene for growth traits along with RB1 inducible coiled-coil 1 ( RB1CC1 ), neuropeptides B and W receptor 1 ( NPBWR1 ), and pleiomorphic adenoma gene 1 ( PLAG1 ) in Nellore cattle, according to these studies, PLAG1 seems to be the major gene due to its role in regulating insulin-like growth factors, and RB1CC1 , NPBWR1 , and PENK are also involved in processes that can contribute to determining the uniformity of growth traits, like YW [ 27 ]. COL4A1 is related to developmental biology, protein digestion, and protein absorption have been indicated as a candidate gene for weaning weight and YW [ 28 ].…”

Evaluation of the phenotypic and genomic background of variability based on litter size of Large White pigs

“…[ 60 ] Dairy cows Somatic cell score (SCS) Nelson et al . [ 20 ] S. cerevisiae strains Expression traits in different treatments Sell-Kubiak et al [ 25 ] Pigs Litter size Ek et al [ 61 ] Human Variation in DNA methylation levels Wang et al [ 62 ]; Wang et al [ 63 ] Pigs Birth weight Iung et al [ 64 ] Nellore cattle Yearling weight Hussain et al [ 65 ] Bread wheat Cadmium levels …”