Autozygosity islands and ROH patterns in Nellore lineages: evidence of selection for functionally important traits.

BACKGROUND: The aim of this study was to assess genome-wide autozygosity in a Nellore cattle population and to characterize ROH patterns and autozygosity islands that may have occurred due to selection within its lineages. It attempts also to compare estimates of inbreeding calculated from ROH (FROH), genomic relationship matrix (FGRM), and pedigree-based coefficient (FPED). RESULTS: The average number of ROH per animal was 55.15 ± 13.01 with an average size of 3.24 Mb. The Nellore genome is composed mostly by a high number of shorter segments accounting for 78% of all ROH, although the proportion of the genome covered by them was relatively small. The genome autozygosity proportion indicates moderate to high inbreeding levels for classical standards, with an average value of 7.15% (178.70 Mb). The average of FPED and FROH, and their correlations (- 0.05 to 0.26) were low. Estimates of correlation between FGRM-FPED was zero, while the correlation (- 0.01 to - 0.07) between FGRM-FROH decreased as a function of ROH length, except for FROH > 8Mb (- 0.03). Overall, inbreeding coefficients were not high for the genotyped animals. Autozygosity islands were evident across the genome (n = 62) and their genomic location did not largely differ within lineages. Enriched terms (p < 0.01) associated with defense response to bacteria (GO:0042742), immune complex reaction (GO:0045647), pregnancy-associated glycoproteins genes (GO:0030163), and organism growth (GO:0040014) were described within the autozygotic islands. CONCLUSIONS: Low FPED-FROH correlation estimates indicate that FPED is not the most suitable method for capturing ancient inbreeding when the pedigree does not extend back many generations and FROH should be used instead. Enriched terms (p < 0.01) suggest a strong selection for immune response. Non-overlapping islands within the lineages greatly explain the mechanism underlying selection for functionally important traits in Nellore cattle.

Genotype imputation in a tropical crossbred dairy cattle population.

The objective of this study was to investigate different strategies for genotype imputation in a population of crossbred Girolando (Gyr × Holstein) dairy cattle. The data set consisted of 478 Girolando, 583 Gyr, and 1,198 Holstein sires genotyped at high density with the Illumina BovineHD (Illumina, San Diego, CA) panel, which includes ∼777K markers. The accuracy of imputation from low (20K) and medium densities (50K and 70K) to the HD panel density and from low to 50K density were investigated. Seven scenarios using different reference populations (RPop) considering Girolando, Gyr, and Holstein breeds separately or combinations of animals of these breeds were tested for imputing genotypes of 166 randomly chosen Girolando animals. The population genotype imputation were performed using FImpute. Imputation accuracy was measured as the correlation between observed and imputed genotypes (CORR) and also as the proportion of genotypes that were imputed correctly (CR). This is the first paper on imputation accuracy in a Girolando population. The sample-specific imputation accuracies ranged from 0.38 to 0.97 (CORR) and from 0.49 to 0.96 (CR) imputing from low and medium densities to HD, and 0.41 to 0.95 (CORR) and from 0.50 to 0.94 (CR) for imputation from 20K to 50K. The CORRanim exceeded 0.96 (for 50K and 70K panels) when only Girolando animals were included in RPop (S1). We found smaller CORRanim when Gyr (S2) was used instead of Holstein (S3) as RPop. The same behavior was observed between S4 (Gyr + Girolando) and S5 (Holstein + Girolando) because the target animals were more related to the Holstein population than to the Gyr population. The highest imputation accuracies were observed for scenarios including Girolando animals in the reference population, whereas using only Gyr animals resulted in low imputation accuracies, suggesting that the haplotypes segregating in the Girolando population had a greater effect on accuracy than the purebred haplotypes. All chromosomes had similar imputation accuracies (CORRsnp) within each scenario. Crossbred animals (Girolando) must be included in the reference population to provide the best imputation accuracies.

Kernel-based variance component estimation and whole-genome prediction of pre-corrected phenotypes and progeny tests for dairy cow health traits.

Prediction of complex trait phenotypes in the presence of unknown gene action is an ongoing challenge in animals, plants, and humans. Development of flexible predictive models that perform well irrespective of genetic and environmental architectures is desirable. Methods that can address non-additive variation in a non-explicit manner are gaining attention for this purpose and, in particular, semi-parametric kernel-based methods have been applied to diverse datasets, mostly providing encouraging results. On the other hand, the gains obtained from these methods have been smaller when smoothed values such as estimated breeding value (EBV) have been used as response variables. However, less emphasis has been placed on the choice of phenotypes to be used in kernel-based whole-genome prediction. This study aimed to evaluate differences between semi-parametric and parametric approaches using two types of response variables and molecular markers as inputs. Pre-corrected phenotypes (PCP) and EBV obtained for dairy cow health traits were used for this comparison. We observed that non-additive genetic variances were major contributors to total genetic variances in PCP, whereas additivity was the largest contributor to variability of EBV, as expected. Within the kernels evaluated, non-parametric methods yielded slightly better predictive performance across traits relative to their additive counterparts regardless of the type of response variable used. This reinforces the view that non-parametric kernels aiming to capture non-linear relationships between a panel of SNPs and phenotypes are appealing for complex trait prediction. However, like past studies, the gain in predictive correlation was not large for either PCP or EBV. We conclude that capturing non-additive genetic variation, especially epistatic variation, in a cross-validation framework remains a significant challenge even when it is important, as seems to be the case for health traits in dairy cows.

Fine mapping of copy number variations on two cattle genome assemblies using high density SNP array.

BACKGROUND: Btau_4.0 and UMD3.1 are two distinct cattle reference genome assemblies. In our previous study using the low density BovineSNP50 array, we reported a copy number variation (CNV) analysis on Btau_4.0 with 521 animals of 21 cattle breeds, yielding 682 CNV regions with a total length of 139.8 megabases. RESULTS: In this study using the high density BovineHD SNP array, we performed high resolution CNV analyses on both Btau_4.0 and UMD3.1 with 674 animals of 27 cattle breeds. We first compared CNV results derived from these two different SNP array platforms on Btau_4.0. With two thirds of the animals shared between studies, on Btau_4.0 we identified 3,346 candidate CNV regions representing 142.7 megabases (~4.70%) of the genome. With a similar total length but 5 times more event counts, the average CNVR length of current Btau_4.0 dataset is significantly shorter than the previous one (42.7 kb vs. 205 kb). Although subsets of these two results overlapped, 64% (91.6 megabases) of current dataset was not present in the previous study. We also performed similar analyses on UMD3.1 using these BovineHD SNP array results. Approximately 50% more and 20% longer CNVs were called on UMD3.1 as compared to those on Btau_4.0. However, a comparable result of CNVRs (3,438 regions with a total length 146.9 megabases) was obtained. We suspect that these results are due to the UMD3.1 assembly's efforts of placing unplaced contigs and removing unmerged alleles. Selected CNVs were further experimentally validated, achieving a 73% PCR validation rate, which is considerably higher than the previous validation rate. About 20-45% of CNV regions overlapped with cattle RefSeq genes and Ensembl genes. Panther and IPA analyses indicated that these genes provide a wide spectrum of biological processes involving immune system, lipid metabolism, cell, organism and system development. CONCLUSION: We present a comprehensive result of cattle CNVs at a higher resolution and sensitivity. We identified over 3,000 candidate CNV regions on both Btau_4.0 and UMD3.1, further compared current datasets with previous results, and examined the impacts of genome assemblies on CNV calling.

Development of a nomenclature system for a canine STR multiplex reagent kit.

Despite the popularity of dogs in US households, canine DNA evidence remains largely untapped in forensic investigations partially because of the absence of well-defined forensic short tandem repeats (STRs), lack of standardized and validated PCR protocols, STR reagent kits, and poorly developed nomenclature. A nomenclature system was established based on internationally recognized recommendations for human forensic STRs for a recently developed canine STR reagent kit. Representative alleles were sequenced from each of the 18 STRs and the sex-typing marker included in the kit. This study also reflects on the impact of point mutations, insertions, and deletions within and outside the STR core repeat structures. An understanding of the STRs' sequence and repeat structures will enable development of a robust and reliable allele nomenclature and improve the accuracy and precision of allele fragment sizing in canine forensic profiling. The expected allele sizes have been calculated, and their repeat stuctures defined based on sequence information.

Canine population data generated from a multiplex STR kit for use in forensic casework.

Canine biological specimens are often part of the physical evidence from crime scenes. Until now, there have been no validated canine-specific forensic reagent kits available. A multiplex genotyping system, comprising 18 short tandem repeats (STRs) and a sex-linked zinc finger locus for gender determination, was developed for generating population genetic data assessing the weight of canine forensic DNA profiles. Allele frequencies were estimated for 236 pedigreed and 431 mixed breed dogs residing in the U.S. Average random match probability is 1 in 2 x 10(33) using the regional database and 1 in 4 x 10(39) using the breed dataset. Each pedigreed population was genetically distinct and could be differentiated from the mixed breed dog population but genetic variation was not significantly correlated with geographic transition. Results herein support the use of the allele frequency data with the canine STR multiplex for conveying the significance of identity testing for forensic casework, parentage testing, and breed assignments.

Developmental validation of short tandem repeat reagent kit for forensic DNA profiling of canine biological material.

AIM: To develop a reagent kit that enables multiplex polymerase chain reaction (PCR) amplification of 18 short tandem repeats (STR) and the canine sex-determining Zinc Finger marker. METHODS: Validation studies to determine the robustness and reliability in forensic DNA typing of this multiplex assay included sensitivity testing, reproducibility studies, intra- and inter-locus color balance studies, annealing temperature and cycle number studies, peak height ratio determination, characterization of artifacts such as stutter percentages and dye blobs, mixture analyses, species-specificity, case type samples analyses and population studies. RESULTS: The kit robustly amplified domesticated dog samples and consistently generated full 19-locus profiles from as little as 125 pg of dog DNA. In addition, wolf DNA samples could be analyzed with the kit. CONCLUSION: The kit, which produces robust, reliable, and reproducible results, will be made available for the forensic research community after modifications based on this study's evaluation to comply with the quality standards expected for forensic casework.

Thermoregulatory responses of Holstein and Brown Swiss heat-stressed dairy cows to two different cooling systems.

Thirty-seven Holstein and 26 Brown Swiss dairy cows were used to evaluate the effect of two different cooling systems on physiological and hormonal responses during the summer. A control group of cows had access only to shade (C). A second group was cooled with spray and fans (S/F) and the third group was under an evaporative cooling system called Korral Kool (KK). The maximum temperature humidity index during the trial was from 73 to 85. Rectal temperatures and respiration rates of the C group were higher (P<0.05) than those of the S/F and KK groups in both Holstein and Brown Swiss cows. Triiodothyronine levels in milk were higher (P<0.05) in the KK group than in the S/F and C groups, while cortisol levels were lower (P<0.05) in the C group than in S/F and KK. There was no significant difference in the hormonal response of the two breeds. These results demonstrate that both cooling systems may be used increase the comfort of Holstein and Brown Swiss cows during summer in hot, dry climates.