Studies are being conducted on the applicability of genomic data to improve the accuracy of the selection process in livestock, and genome-wide association studies (GWAS) provide valuable information to enhance the understanding on the genetics of complex traits. The aim of this study was to identify genomic regions and genes that play roles in birth weight (BW), weaning weight adjusted for 210 days of age (WW), and long-yearling weight adjusted for 420 days of age (LYW) in Canchim cattle. GWAS were performed by means of the Generalized Quasi-Likelihood Score (GQLS) method using genotypes from the BovineHD BeadChip and estimated breeding values for BW, WW, and LYW. Data consisted of 285 animals from the Canchim breed and 114 from the MA genetic group (derived from crossings between Charolais sires and ½ Canchim + ½ Zebu dams). After applying a false discovery rate correction at a 10% significance level, a total of 4, 12, and 10 SNPs were significantly associated with BW, WW, and LYW, respectively. These SNPs were surveyed to their corresponding genes or to surrounding genes within a distance of 250 kb. The genes DPP6 (dipeptidyl-peptidase 6) and CLEC3B (C-type lectin domain family 3 member B) were highlighted, considering its functions on the development of the brain and skeletal system, respectively. The GQLS method identified regions on chromosome associated with birth weight, weaning weight, and long-yearling weight in Canchim and MA animals. New candidate regions for body weight traits were detected and some of them have interesting biological functions, of which most have not been previously reported. The observation of QTL reports for body weight traits, covering areas surrounding the genes (SNPs) herein identified provides more evidence for these associations. Future studies targeting these areas could provide further knowledge to uncover the genetic architecture underlying growth traits in Canchim cattle.

BackgroundThe development of linkage disequilibrium (LD) maps and the characterization of haplotype block structure at the population level are useful parameters for guiding genome wide association (GWA) studies, and for understanding the nature of non-linear association between phenotypes and genes. The elucidation of haplotype block structure can reduce the information of several single nucleotide polymorphisms (SNP) into the information of a haplotype block, reducing the number of SNPs in a coherent way for consideration in GWA and genomic selection studies.ResultsThe maximum average LD, measured by r2 varied between 0.33 to 0.40 at a distance of < 2.5 kb, and the minimum average values of r2 varied between 0.05 to 0.07 at distances ranging from 400 to 500 kb, clearly showing that the average r2 reduced with the increase in SNP pair distances. The persistence of LD phase showed higher values at shorter genomic distances, decreasing with the increase in physical distance, varying from 0.96 at a distance of < 2.5 kb to 0.66 at a distance from 400 to 500 kb. A total of 78% of all SNPs were clustered into haplotype blocks, covering 1,57 Mb of the total autosomal genome size.ConclusionsThis study presented the first high density linkage disequilibrium map and haplotype block structure for a composite beef cattle population, and indicates that the high density SNP panel over 700 k can be used for genomic selection implementation and GWA studies for Canchim beef cattle.

BackgroundBeef cattle breeding programs in Brazil have placed greater emphasis on the genomic study of reproductive traits of males and females due to their economic importance. In this study, genome-wide associations were assessed for scrotal circumference at 210 d of age, scrotal circumference at 420 d of age, age at first calving, and age at second calving, in Canchim beef cattle. Data quality control was conducted resulting in 672,778 SNPs and 392 animals.ResultsAssociated SNPs were observed for scrotal circumference at 420 d of age (435 SNPs), followed by scrotal circumference at 210 d of age (12 SNPs), age at first calving (six SNPs), and age at second calving (four SNPs). We investigated whether significant SNPs were within genic or surrounding regions. Biological processes of genes were associated with immune system, multicellular organismal process, response to stimulus, apoptotic process, cellular component organization or biogenesis, biological adhesion, and reproduction.ConclusionsFew associations were observed for scrotal circumference at 210 d of age, age at first calving, and age at second calving, reinforcing their polygenic inheritance and the complexity of understanding the genetic architecture of reproductive traits. Finding many associations for scrotal circumference at 420 d of age in various regions of the Canchim genome also reveals the difficulty of targeting specific candidate genes that could act on fertility; nonetheless, the high linkage disequilibrium between loci herein estimated could aid to overcome this issue. Therefore, all relevant information about genomic regions influencing reproductive traits may contribute to target candidate genes for further investigation of causal mutations and aid in future genomic studies in Canchim cattle to improve the breeding program.Electronic supplementary materialThe online version of this article (doi:10.1186/s40104-017-0199-8) contains supplementary material, which is available to authorized users.

BackgroundNelore is the major beef cattle breed in Brazil with more than 130 million heads. Genome-wide association studies (GWAS) are often used to associate markers and genomic regions to growth and meat quality traits that can be used to assist selection programs. An alternative methodology to traditional GWAS that involves the construction of gene network interactions, derived from results of several GWAS is the AWM (Association Weight Matrices)/PCIT (Partial Correlation and Information Theory). With the aim of evaluating the genetic architecture of Brazilian Nelore cattle, we used high-density SNP genotyping data (~770,000 SNP) from 780 Nelore animals comprising 34 half-sibling families derived from highly disseminated and unrelated sires from across Brazil. The AWM/PCIT methodology was employed to evaluate the genes that participate in a series of eight phenotypes related to growth and meat quality obtained from this Nelore sample.ResultsOur results indicate a lack of structuring between the individuals studied since principal component analyses were not able to differentiate families by its sires or by its ancestral lineages. The application of the AWM/PCIT methodology revealed a trio of transcription factors (comprising VDR, LHX9 and ZEB1) which in combination connected 66 genes through 359 edges and whose biological functions were inspected, some revealing to participate in biological growth processes in literature searches.ConclusionsThe diversity of the Nelore sample studied is not high enough to differentiate among families neither by sires nor by using the available ancestral lineage information. The gene networks constructed from the AWM/PCIT methodology were a useful alternative in characterizing genes and gene networks that were allegedly influential in growth and meat quality traits in Nelore cattle.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-016-2535-3) contains supplementary material, which is available to authorized users.

BackgroundGenotype imputation has been used to increase genomic information, allow more animals in genome-wide analyses, and reduce genotyping costs. In Brazilian beef cattle production, many animals are resulting from crossbreeding and such an event may alter linkage disequilibrium patterns. Thus, the challenge is to obtain accurately imputed genotypes in crossbred animals. The objective of this study was to evaluate the best fitting and most accurate imputation strategy on the MA genetic group (the progeny of a Charolais sire mated with crossbred Canchim X Zebu cows) and Canchim cattle. The data set contained 400 animals (born between 1999 and 2005) genotyped with the Illumina BovineHD panel. Imputation accuracy of genotypes from the Illumina-Bovine3K (3K), Illumina-BovineLD (6K), GeneSeek-Genomic-Profiler (GGP) BeefLD (GGP9K), GGP-IndicusLD (GGP20Ki), Illumina-BovineSNP50 (50K), GGP-IndicusHD (GGP75Ki), and GGP-BeefHD (GGP80K) to Illumina-BovineHD (HD) SNP panels were investigated. Seven scenarios for reference and target populations were tested; the animals were grouped according with birth year (S1), genetic groups (S2 and S3), genetic groups and birth year (S4 and S5), gender (S6), and gender and birth year (S7). Analyses were performed using FImpute and BEAGLE software and computation run-time was recorded. Genotype imputation accuracy was measured by concordance rate (CR) and allelic R square (R2).ResultsThe highest imputation accuracy scenario consisted of a reference population with males and females and a target population with young females. Among the SNP panels in the tested scenarios, from the 50K, GGP75Ki and GGP80K were the most adequate to impute to HD in Canchim cattle. FImpute reduced computation run-time to impute genotypes from 20 to 100 times when compared to BEAGLE.ConclusionThe genotyping panels possessing at least 50 thousands markers are suitable for genotype imputation to HD with acceptable accuracy. The FImpute algorithm demonstrated a higher efficiency of imputed markers, especially in lower density panels. These considerations may assist to increase genotypic information, reduce genotyping costs, and aid in genomic selection evaluations in crossbred animals.Electronic supplementary materialThe online version of this article (doi:10.1186/s12863-015-0251-7) contains supplementary material, which is available to authorized users.