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Over the past decades, daughter designs, including genotyped sires and their genotyped daughters, have been used as an approach to identify QTL related to economic traits. The aim of this study was to identify genomic regions inherited by Gir sire families and genes associated with number of viable oocytes (VO), total number of oocytes (TO), and number of embryos (EMBR) based on a daughter design approach. In total, 15 Gir sire families were selected. The number of daughters per family ranged from 26 to 395, which were genotyped with different SNP panels and imputed to the Illumina BovineHD BeadChip (777K) and had phenotypes for oocyte and embryo production. Daughters had phenotypic data for VO, TO, and EMBR. The search for QTL was performed through GWAS based on GBLUP. The QTL were found for each trait among and within families based on the top 10 genomic windows with the greatest genetic variance. For EMBR, genomic windows identified among families were located on BTA4, BTA5, BTA6, BTA7, BTA8, BTA13, BTA16, and BTA17, and they were most frequent on BTA7 within families. For VO, genomic windows were located on BTA2, BTA4, BTA5, BTA7, BTA17, BTA21, BTA22, BTA23, and BTA27 among families, being most frequent on BTA8 within families. For TO, the top 10 genomic windows were identified on BTA2, BTA4, BTA5, BTA7, BTA17, BTA21, BTA22, BTA26, and BTA27, being most frequent on BTA7 and BTA8 within families. Considering all results, the greatest number of genomic windows was found on BTA7, where the VCAN, XRCC4, TRNAC-ACA, HAPLN1, and EDIL3 genes were identified in the common regions. In conclusion, 15 Gir sire families with 26 to 395 daughters per family with phenotypes for oocyte and embryo production helped to identify the inheritance of several genomic regions, especially on BTA7, where the EDIL3, HAPLN1, and VCAN candidate genes were associated with number of oocytes and embryos in Gir cattle families., (The Authors. Published by Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).)

Milk production is economically important to the Brazilian agribusiness, and the majority of the country's milk production derives from Girolando (Gir × Holstein) cows. This study aimed to identify quantitative trait loci (QTL) and candidate genes associated with 305-d milk yield (305MY) in Girolando cattle. In addition, we investigated the SNP-specific variances for Holstein and Gir breeds of origin within the sequence of candidate genes. A single-step genomic BLUP procedure was used to identify QTL associated with 305MY, and the most likely candidate genes were identified through follow-up analyses. Genomic breeding values specific for Holstein and Gir were estimated in the Girolando animals using a model that uses breed-specific partial relationship matrices, which were converted to breed of origin SNP effects. Differences between breed of origin were evaluated by comparing estimated SNP variances between breeds. From 10 genome regions explaining most additive genetic variance for 305MY in Girolando cattle, 7 candidate genes were identified on chromosomes 1, 4, 6, and 26. Within the sequence of these 7 candidate genes, Gir breed of origin SNP alleles showed the highest genetic variance. These results indicated QTL regions that could be further explored in genomic selection panels and which may also help in understanding the gene mechanisms involved in milk production in the Girolando breed., (Copyright © 2020 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.)

Heat stress is an important issue in the global dairy industry. In tropical areas, an alternative to overcome heat stress is the use of crossbred animals or synthetic breeds, such as the Girolando. In this study, we performed a genome-wide association study (GWAS) and post-GWAS analyses for heat stress in an experimental Gir × Holstein F 2 population. Rectal temperature (RT) was measured in heat-stressed F 2 animals, and the variation between 2 consecutive RT measurements (ΔRT) was used as the dependent variable. Illumina BovineSNP50v1 BeadChip (Illumina Inc., San Diego, CA) and single-SNP approach were used for GWAS. Post-GWAS analyses were performed by gene ontology terms enrichment and gene-transcription factor (TF) networks, generated from enriched TF. The breed origin of marker alleles in the F 2 population was assigned using the breed of origin of alleles (BOA) approach. Heritability and repeatability estimates (± standard error) for ΔRT were 0.13 ± 0.08 and 0.29 ± 0.06, respectively. Association analysis revealed 6 SNP significantly associated with ΔRT. Genes involved with biological processes in response to heat stress effects (LIF, OSM, TXNRD2, and DGCR8) were identified as putative candidate genes. After performing the BOA approach, the 10% of F 2 animals with the lowest breeding values for ΔRT were classified as low-ΔRT, and the 10% with the highest breeding values for ΔRT were classified as high-ΔRT. On average, 49.4% of low-ΔRT animals had 2 alleles from the Holstein breed (HH), and 39% had both alleles from the Gir breed (GG). In high-ΔRT animals, the average proportion of animals for HH and GG were 1.4 and 50.2%, respectively. This study allowed the identification of candidate genes for ΔRT in Gir × Holstein crossbred animals. According to the BOA approach, Holstein breed alleles could be associated with better response to heat stress effects, which could be explained by the fact that Holstein animals are more affected by heat stress than Gir animals and thus require a genetic architecture to defend the body from the deleterious effects of heat stress. Future studies can provide further knowledge to uncover the genetic architecture underlying heat stress in crossbred cattle., (Copyright © 2019 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.)

Rhipicephalus (Boophilus) microplus is the main cattle ectoparasite in tropical areas. Gir × Holstein crossbred cows are well adapted to different production systems in Brazil. In this context, we performed genome-wide association study (GWAS) and post-GWAS analyses for R. microplus resistance in an experimental Gir × Holstein F 2 population. Single nucleotide polymorphisms (SNP) identified in GWAS were used to build gene networks and to investigate the breed of origin for its alleles. Tick artificial infestations were performed during the dry and rainy seasons. Illumina BovineSNP50 BeadChip (Illumina Inc., San Diego, CA) and single-step BLUP procedure was used for GWAS. Post-GWAS analyses were performed by gene ontology terms enrichment and gene transcription factors networks, generated from enriched transcription factors, identified from the promoter sequences of selected gene sets. The genetic origin of marker alleles in the F 2 population was assigned using the breed of origin of alleles approach. Heritability estimates for tick counts were 0.40 ± 0.11 in the rainy season and 0.54 ± 0.11 in the dry season. The top ten 0.5-Mbp windows with the highest percentage of genetic variance explained by SNP markers were found in chromosomes 10 and 23 for both the dry and rainy seasons. Gene network analyses allowed the identification of genes involved with biological processes relevant to immune system functions (TREM1, TREM2, and CD83). Gene-transcription factors network allowed the identification of genes involved with immune functions (MYO5A, TREML1, and PRSS16). In resistant animals, the average proportion of animals showing significant SNPs with paternal and maternal alleles originated from Gir breed was 44.8% whereas the proportion of animals with both paternal and maternal alleles originated from Holstein breed was 11.3%. Susceptible animals showing both paternal and maternal alleles originated from Holstein breed represented 44.6% on average, whereas both paternal and maternal alleles originated from Gir breed animals represented 9.3%. This study allowed us to identify candidate genes for tick resistance in Gir × Holstein crossbreds in both rainy and dry seasons. According to the origin of alleles analysis, we found that most animals classified as resistant showed 2 alleles from Gir breed, while the susceptible ones showed alleles from Holstein. Based on these results, the identified genes may be thoroughly investigated in additional experiments aiming to validate their effects on tick resistance phenotype in cattle., (Copyright © 2018 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.)

Genomic selection may accelerate genetic progress in breeding programs of indicine breeds when compared with traditional selection methods. We present results of genomic predictions in Gyr (Bos indicus) dairy cattle of Brazil for milk yield (MY), fat yield (FY), protein yield (PY), and age at first calving using information from bulls and cows. Four different single nucleotide polymorphism (SNP) chips were studied. Additionally, the effect of the use of imputed data on genomic prediction accuracy was studied. A total of 474 bulls and 1,688 cows were genotyped with the Illumina BovineHD (HD; San Diego, CA) and BovineSNP50 (50K) chip, respectively. Genotypes of cows were imputed to HD using FImpute v2.2. After quality check of data, 496,606 markers remained. The HD markers present on the GeneSeek SGGP-20Ki (15,727; Lincoln, NE), 50K (22,152), and GeneSeek GGP-75Ki (65,018) were subset and used to assess the effect of lower SNP density on accuracy of prediction. Deregressed breeding values were used as pseudophenotypes for model training. Data were split into reference and validation to mimic a forward prediction scheme. The reference population consisted of animals whose birth year was ≤2004 and consisted of either only bulls (TR1) or a combination of bulls and dams (TR2), whereas the validation set consisted of younger bulls (born after 2004). Genomic BLUP was used to estimate genomic breeding values (GEBV) and reliability of GEBV (R 2 PEV ) was based on the prediction error variance approach. Reliability of GEBV ranged from ∼0.46 (FY and PY) to 0.56 (MY) with TR1 and from 0.51 (PY) to 0.65 (MY) with TR2. When averaged across all traits, R 2 PEV were substantially higher (R 2 PEV of TR1 = 0.50 and TR2 = 0.57) compared with reliabilities of parent averages (0.35) computed from pedigree data and based on diagonals of the coefficient matrix (prediction error variance approach). Reliability was similar for all the 4 marker panels using either TR1 or TR2, except that imputed HD cow data set led to an inflation of reliability. Reliability of GEBV could be increased by enlarging the limited bull reference population with cow information. A reduced panel of ∼15K markers resulted in reliabilities similar to using HD markers. Reliability of GEBV could be increased by enlarging the limited bull reference population with cow information., (Copyright © 2017 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.)