A 44-kb deleted-type copy number variation is associated with decreasing complement component activity and calf mortality in Japanese Black cattle

Background Calf mortality generally occurs in calves prior to weaning, which is a serious problem in cattle breeding. Several causative variants of monogenic Mendelian disorders in calf mortality have been identified, whereas genetic factors affecting the susceptibility of calves to death are not well known. To identify variants associated with calf mortality in Japanese Black cattle, we evaluated calf mortality as a categorical trait with a threshold model and performed a genome-wide copy number variation (CNV) association study on calf mortality. Results We identified a 44-kb deleted-type CNV ranging from 103,317,687 to 103,361,802 bp on chromosome 5, which was associated with the mortality of 1–180-day-old calves. The CNV harbored C1RL, a pseudogene, and an IncRNA localized in the C1R and C1S gene cluster, which is a component of the classical complement activation pathway for immune complexes for infectious pathogens. The average complement activity in CNVR_221 homozygotes at postnatal day 7 was significantly lower than that of wild-type animals and heterozygotes. The frequency of the risk allele in dead calves suffering from diarrhea and pneumonia and in healthy cows was 0.35 and 0.28, respectively (odds ratio = 2.2, P = 0.016), suggesting that CNVR_221 was associated with the mortality of Japanese Black calves suffering from an infectious disease. Conclusions This study identified a deleted-type CNV associated with the mortality of 1–180-day-old calves. The complement activity in CNVR_221 homozygotes was significantly lower than that in heterozygotes and wild type animals. The frequency of the risk allele was higher in dead calves suffering from an infectious disease than in healthy cows. These results suggest that the existence of CNVR_221 in calves could be attributed to a reduction in complement activity, which in turn leads to susceptibility to infections. Thus, the risk allele could serve as a useful marker to reduce the mortality of infected Japanese Black calves.

Phenotypic and genomic relationships between vulva score categories and reproductive performance in first-parity sows

Background One of the biggest challenges in the swine industry is to increase female reproductive efficiency. Recently, vulva score categories (VSC), assessed prior to puberty, has been proposed as an indicator trait of efficient reproductive performance in sows. The objective of this study was to validate the use of VSC as an indicator trait for reproductive performance, and to perform genetic and genomic analyses for VSC. Methods The phenotypic relationship of VSC, using a three-point scale: small (VSC-S), medium (VSC-M), and large (VSC-L), on reproductive performance was evaluated on three farms. VSC was measured at 15 weeks of age, for farms 1 and 2, and at 14 weeks of age for farm 3 on 3981 Yorkshire gilts, in which 1083 had genotypes (~ 50 K SNPs). Genetic parameters for VSC with reproductive traits were estimated using ssGBLUP. A Genome-wide association study (GWAS) for VSC was performed using BayesB. Results For the phenotypic analysis of VSC across datasets, differences in performance were identified there was a significant effect (P ≤ 0.05) for the interaction between Farm and VSC for total number dead (TND), and a trend (P < 0.10) for total number born (TNB). There were significant (P ≤ 0.05) pre-defined contrasts of VSC-S versus VSC-M + L on TNB, number born alive (NBA), TND, number of stillborn (NSB), and number of mummies (MUM). Heritability estimates for VSC as a categorical trait (VSCc) and a quantitative trait (VSCq) were 0.40 ± 0.02 and 0.83 ± 0.02, respectively, for across farm, 0.13 ± 0.07 and 0.20 ± 0.10, respectively, for Farm1, 0.07 ± 0.07 and 0.09 ± 0.09, respectively, for Farm2, and 0.20 ± 0.03 and 0.34 ± 0.05, respectively, for Farm3. For across farms, favorable genetic correlations estimates were found for TNB (0.28 ± 0.19) and NBA (0.26 ± 0.17). Within farms, moderate genetic correlations between VSC with reproductive traits were found for TNB (0.61 ± 0.47) and MUM (0.69 ± 0.47) for farm 1, for number of services until first farrow (NS; 0.69 ± 0.38) and unique service with successful first farrow (SFS; − 0.71 ± 0.38) for farm 3. Multiple genomic regions associated with VSCc were identified. Of these, a QTL located on chromosome 3 at 33–34 Mb accounted for about 7.1% of the genetic variance for VSCc and VSCq. This region harbors the gene PRM1 that has been associated with early embryonic development in pigs. Conclusions The results support potential of VSC for improved reproductive efficiency on first-parity performance, but the results might depend on the interaction between environmental factors and VSC, as well as potentially additive genetics.

Preweaning Calf Survival of a Nellore Beef Cattle Population

The preweaning calf survival (SW) is one of the main economic bottlenecks of beef cattle rearing systems, however there is still few quantitative studies approaching this issue. Being a binary trait, genetic parameters for SW can be estimated considering continuous or categorical data under frequentist and Bayesian methods providing support for the selection and mating of animals in breeding programs. Therefore, the objectives in this study were to obtain and compare the variance component estimates for preweaning calf survival of calves in single-trait analyses and their correlations with a continuous trait in two-trait analyses. An amount of 25 218 data of the categorical trait of calf survival until weaning (SW) and the continuous trait of weaning weight (WW) were collected between the years of 2000 and 2012 in six herds of Nellore cattle. Methods III of Henderson, Maximum Restricted Likelihood (REML), Bayesian Inference and Generalized Linear Mixed Model (GLMM) were tested. Variance components obtained in one-trait analyses were similar to those obtained in two-trait analyses. Estimates of heritability (h2) obtained with different models for SW ranged from 0.0206 to 0.2644. The comparison between different estimation methods in single or two-trait analysis models allows the conclusion that the most appropriate method for SW analysis was the Bayesian estimation under an animal model and assuming linear distribution for phenotypes of SW trait.

Utilizing mutual information for detecting rare and common variants associated with a categorical trait

Background.Genome-wide association studies have succeeded in detecting novel common variants which associate with complex diseases. As a result of the fast changes in next generation sequencing technology, a large number of sequencing data are generated, which offers great opportunities to identify rare variants that could explain a larger proportion of missing heritability. Many effective and powerful methods are proposed, although they are usually limited to continuous, dichotomous or ordinal traits. Notice that traits having nominal categorical features are commonly observed in complex diseases, especially in mental disorders, which motivates the incorporation of the characteristics of the categorical trait into association studies with rare and common variants.Methods.We construct two simple and intuitive nonparametric tests, MIT and aMIT, based on mutual information for detecting association between genetic variants in a gene or region and a categorical trait. MIT and aMIT can gauge the difference among the distributions of rare and common variants across a region given every categorical trait value. If there is little association between variants and a categorical trait, MIT or aMIT approximately equals zero. The larger the difference in distributions, the greater values MIT and aMIT have. Therefore, MIT and aMIT have the potential for detecting functional variants.Results.We checked the validity of proposed statistics and compared them to the existing ones through extensive simulation studies with varied combinations of the numbers of variants of rare causal, rare non-causal, common causal, and common non-causal, deleterious and protective, various minor allele frequencies and different levels of linkage disequilibrium. The results show our methods have higher statistical power than conventional ones, including the likelihood based score test, in most cases: (1) there are multiple genetic variants in a gene or region; (2) both protective and deleterious variants are present; (3) there exist rare and common variants; and (4) more than half of the variants are neutral. The proposed tests are applied to the data from Collaborative Studies on Genetics of Alcoholism, and a competent performance is exhibited therein.Discussion.As a complementary to the existing methods mainly focusing on quantitative traits, this study provides the nonparametric tests MIT and aMIT for detecting variants associated with categorical trait. Furthermore, we plan to investigate the association between rare variants and multiple categorical traits.