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Heat stress imposes a challenge to the dairy industry, even in northern latitudes. In this study, publicly available weather station data were combined with test-day records for milk, fat, and protein yields to identify the temperature–humidity index (THI) thresholds at which heat load starts affecting milk production traits in Canadian Holstein cows. Production loss per THI unit above the threshold for each trait was estimated. Test-day records from 2010 to 2019 from 166,749 cows raised in Ontario and from 221,214 cows raised in Quebec were analyzed. Annual economic losses (EL) due to heat stress were estimated from the average losses of fat and protein yields based on the annual average of 156 d with THI exceeding the calculated thresholds. Average thresholds for the daily maximum (THImax) and daily average (THIavg) THI estimated across lactations in both provinces were THImax (THIavg) 68 (64), 57 (50), and 60 (58) for milk, fat, and protein yield, respectively, indicating that milk components are more sensitive to heat stress. An EL of about $34.5 million per year was estimated. Our findings contribute to an initial investigation into the impact of heat stress on the Canadian dairy industry and provide a basis for genetic studies on heat tolerance.

Selecting for lower methane (CH4) emitting animals is one of the best approaches to reduce CH4 given that genetic progress is permanent and cumulative over generations. As genetic selection requires a large number of animals with records and few countries actively record CH4, combining data from different countries could help to expedite accurate genetic parameters for CH4 traits and build a future genomic reference population. Additionally, if we want to include CH4 in the breeding goal, it is important to know the genetic correlations of CH4 traits with other economically important traits. Therefore, the aim of this study was first to estimate genetic parameters of 7 suggested methane traits, as well as genetic correlations between methane traits and production, maintenance, and efficiency traits using a multicountry database. The second aim was to estimate genetic correlations within parities and stages of lactation for CH4. The third aim was to evaluate the expected response of economically important traits by including CH4 traits in the breeding goal. A total of 15,320 methane production (MeP, g/d) records from 2,990 cows belonging to 4 countries (Canada, Australia, Switzerland, and Denmark) were analyzed. Records on dry matter intake (DMI), body weight (BW), body condition score, and milk yield (MY) were also available. Additional traits such as methane yield (MeY; g/kg DMI), methane intensity (MeI; g/kg energy-corrected milk), a genetic standardized methane production, and 3 definitions of residual methane production (g/d), residual feed intake, metabolic BW (MBW), BW change, and energy-corrected milk were calculated. The estimated heritability of MeP was 0.21, whereas heritability estimates for MeY and MeI were 0.30 and 0.38, and for the residual methane traits heritability ranged from 0.13 to 0.16. Genetic correlations between different methane traits were moderate to high (0.41 to 0.97). Genetic correlations between MeP and economically important traits ranged from 0.29 (MY) to 0.65 (BW and MBW), being 0.41 for DMI. Selection index calculations showed that residual methane had the most potential for inclusion in the breeding goal when compared with MeP, MeY, and MeI, as residual methane allows for selection of low methane emitting animals without compromising other economically important traits. Inclusion of residual feed intake in the breeding goal could further reduce methane, as the correlation with residual methane is moderate and elicits a favorable correlated response. Adding a negative economic value for methane could facilitate a substantial reduction in methane emissions while maintaining an increase in milk production.

Made available in DSpace on 2021-06-25T15:03:23Z (GMT). No. of bitstreams: 0 Previous issue date: 2021-04-27 Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) Context. Indicine breeds are the main source of beef products in tropical and subtropical regions. However, genetic improvement for carcass- and meat-quality traits in zebu cattle have been limited and genomics studies concerning structural variations that influence these traits are essential. Aim. The aim of this study was to perform a genome-wide association study between copy number variation regions (CNVRs) and carcass- and meat quality-traits in Nellore cattle. Methods. In total, 3794 animals, males and females included, were genotyped using a 777 962 single-nucleotide polymorphism platform of BovineHD BeadChip (777k; Illumina Inc.). Of these, 1751 Nellore bulls were slaughtered at 24 months of age for further carcass beef analysis. The following traits were studied: beef tenderness, marbling, rib-eye area, backfat thickness and meat colour (lightness, redness and yellowness). The CNV detection was conducted through PennCNV software. The association analyses were performed using CNVRuler software. Key results. Several identified genomic regions were linked to quantitative trait loci associated with fat deposition (FABP7) and lipid metabolism (PPARA; PLA2 family; BCHE), extracellular matrix (INS; COL10A1), contraction (SLC34A3; TRDN) and muscle development (CAPZP). The gene-enrichment analyses highlighted biological mechanisms directly related to the metabolism and synthesis of lipids and fatty acids. Conclusions. The large number of potential candidate genes identified within the CNVRs, as well as the functions and pathways identified, should help better elucidate the genetic mechanisms involved in the expression of beef and carcass traits in Nellore cattle. Several CNVRs harboured genes that might have a functional impact to improve the beef and carcass traits. Implications. The results obtained contribute to upgrade the sensorial and organoleptic attributes of Nellore cattle and make feasible the genetic improvement of carcass- and meat-quality traits. Univ Estadual Paulista, Dept Zootecnia, Fac Ciencias Agr & Vet, Via Acesso Prof Paulo Donato Castellane, BR-14884900 Jaboticabal, SP, Brazil Univ Guelph, Ctr Genet Improvement Livestock, 50 Stone Rd East,Bldg 70, Guelph, ON N1G 2W1, Canada Univ Sao Paulo, Fac Zootecnia & Engn Alimentos, Rua Duque Caxias Norte 225, BR-13635900 Pirassununga, SP, Brazil USDA ARS, ANRI, Bovine Funct Genom Lab, Beltsville, MD 20705 USA Univ Maryland, Dept Anim & Avian Sci, College Pk, MD 20742 USA Univ Estadual Paulista, Dept Zootecnia, Fac Ciencias Agr & Vet, Via Acesso Prof Paulo Donato Castellane, BR-14884900 Jaboticabal, SP, Brazil FAPESP: 2009/16118-5 CAPES: 001

Mastitis is one of the most common diseases in dairy cattle, causing severe economic losses to dairy farmers. Mastitis usually occurs due to intramammary infection (IMI) caused by a variety of pathogenic bacteria. Although good progress has been made in understanding genetics of pathogen-specific clinical mastitis, studies involving genetic analysis of pathogen-specific IMI are scarce. The overall objective of this study was, therefore, to assess genetic variation of overall and pathogen-specific IMI in nonclinical primiparous and multiparous cows using bacterial culture. Data and milk samples were collected over a 2-yr interval as part of the Canadian Bovine Mastitis Research Network. The final data set contained records of 46,900 quarter milk samples from 3,382 clinically healthy primiparous and multiparous Holstein cows from 84 dairy herds. For the genetic analysis, we considered the following 7 traits: overall IMI, non-aureus staphylococci (NAS) IMI, contagious pathogen IMI, environmental pathogen IMI, major pathogen IMI, minor pathogen IMI and somatic cell score (SCS). Data were analyzed at the quarter level using a threshold-probit model via Gibbs sampling in BLUPF90. Prevalence of IMI traits at the quarter level in multiparous cow from 0 to 400 DIM ranged from 6.8 to 45.5%. Posterior mean of quarter heritability estimates (on the underlying scale, posterior SD in brackets) of overall IMI and pathogen-specific IMI traits ranged from 0.017 to 0.073 (±0.009 to 0.030). Weak to strong genetic correlations [ranging from 0.18 to 0.97 (±0.01 to 0.29)] among pathogen-specific IMI traits and with overall IMI indicated that not all of these traits were genetically similar. Weak to moderate Spearman rank correlations between estimated breeding values for overall IMI and pathogen-specific IMI traits (from 0.31 to 0.87) indicated possible substantial reranking of sires. The percentage of daughters with IMI caused by various pathogen groups ranged from 13 to 80% and from 38 to 94% for the best (10% decile) and worst sires (90% decile) according to their IMI trait-specific estimated breeding values, respectively. Pathogen-specific IMI traits and overall IMI had weak to moderate positive genetic correlations [ranging from 0.11 to 0.81 (±0.11 to 0.22)] with SCS. Therefore, selection for lower SCS will improve resistance to IMI. However, based on the observed weak to moderate rank correlations (0.04 to 0.47) between pathogen-specific IMI traits and SCS, selection for lower SCC will not improve resistance to IMI from every pathogen-specific IMI group in the same manner. Therefore, despite low heritability estimates, there was sizeable genetic variation for pathogen-specific IMI traits, indicating that long-term direct genetic selection for pathogen-specific IMI can improve pathogen-specific IMI resistance.

A variety of measures are currently used to evaluate feed efficiency in livestock, with some of the most popular being the linear regression of nutrient intake on the various energy sinks of the cohort being evaluated. The adoption of novel on-farm technologies has greatly increased the breadth and depth of data being collected on a daily basis, which creates the opportunity for the implementation of more advanced feed efficiency models. The objectives of the current study were to leverage data collected using high-throughput biometric technologies to evaluate changes of early-lactation feed efficiency on a daily basis and to develop a novel measure of feed efficiency based on the NRC net energy model. Daily records of nutrient intake, fat- and protein-corrected milk yield, body weight, and body condition score were used to model 7 different indices of feed efficiency (gross feed efficiency, return over feed costs, residual feed intake, residual net energy intake, and net energy efficiencies of lactation, maintenance, and body reserve flux) in primiparous Holstein heifers (n = 40) from 0 to 150 d in milk. We observed that feed efficiency was dynamic and fluctuated over the course of the experimental period regardless of the efficiency measure used, but most measures followed similar trends in changes of efficiency on a day-to-day basis. Of the measures evaluated, return over feed costs would be most suited for management purposes due to practicality and simplicity, whereas other measures, such as the efficiency of net energy flux to and from body reserves, present potential targets for inclusion in breeding goals. Net energy efficiency of lactation was estimated to have higher repeatability compared with residual feed or energy intake, which may reduce the time required to estimate whole-lactation efficiency. Because decreased net energy balance was strongly correlated with increased efficiency for all indices evaluated, future work investigating the associations of feed efficiency with the magnitude and duration of negative energy balance is warranted.

We performed genome-wide association analyses for milk, fat, and protein yields and somatic cell score based on lactation stages in the first 3 parities of Canadian Ayrshire, Holstein, and Jersey cattle. The genome-wide association analyses were performed considering 3 different lactation stages for each trait and parity: from 5 to 95, from 96 to 215, and from 216 to 305 d in milk. Effects of single nucleotide polymorphisms (SNP) for each lactation stage, trait, parity, and breed were estimated by back-solving the direct breeding values estimated using the genomic best linear unbiased predictor and single-trait random regression test-day models containing only the fixed population average curve and the random genomic curves. To identify important genomic regions related to the analyzed lactation stages, traits, parities and breeds, moving windows (SNP-by-SNP) of 20 adjacent SNP explaining more than 0.30% of total genetic variance were selected for further analyses of candidate genes. A lower number of genomic windows with a relatively higher proportion of the explained genetic variance was found in the Holstein breed compared with the Ayrshire and Jersey breeds. Genomic regions associated with the analyzed traits were located on 12, 8, and 15 chromosomes for the Ayrshire, Holstein, and Jersey breeds, respectively. Especially for the Holstein breed, many of the identified candidate genes supported previous reports in the literature. However, well-known genes with major effects on milk production traits (e.g., diacylglycerol O-acyltransferase 1) showed contrasting results among lactation stages, traits, and parities of different breeds. Therefore, our results suggest evidence of differential sets of candidate genes underlying the phenotypic expression of the analyzed traits across breeds, parities, and lactation stages. Further functional studies are needed to validate our findings in independent populations.

Simple Summary With the increasing cost of production, increasing global population, and a greater focus on sustainability, methods to improve cow efficiency are becoming critical for the dairy industry. An efficient cow is the one that produces the same amount of milk and milk solids while consuming less feed and remaining healthy and fertile; thus, allowing for a reduction of costs without reduced production. This simulation showed that directly selecting on feed conversion efficiency allowed for an economically advantageous and more balanced response to selection than indirect selection on feed intake. If too much selection pressure is placed on feed efficiency, there are negative implications for other traits within the selection index. Further work is required to optimize the methods for including feed efficiency in a selection index. Abstract The inclusion of feed efficiency in the breeding goal for dairy cattle has been discussed for many years. The effects of incorporating feed efficiency into a selection index were assessed by indirect selection (dry matter intake) and direct selection (residual feed intake) using deterministic modeling. Both traits were investigated in three ways: (1) restricting the trait genetic gain to zero, (2) applying negative selection pressure, and (3) applying positive selection pressure. Changes in response to selection from economic and genetic gain perspectives were used to evaluate the impact of including feed efficiency with direct or indirect selection in an index. Improving feed efficiency through direct selection on residual feed intake was the best scenario analyzed, with the highest overall economic response including favorable responses to selection for production and feed efficiency. Over time, the response to selection is cumulative, with the potential for animals to reduce consumption by 0.16 kg to 2.7 kg of dry matter per day while maintaining production. As the selection pressure increased on residual feed intake, the response to selection for production, health, and fertility traits and body condition score became increasingly less favorable. This work provides insight into the potential long-term effects of selecting for feed efficiency as residual feed intake.

Genetically selecting animals that are heat tolerant can help to maintain production efficiency of the dairy industry under thermal challenges. During the summer months in Canada, dairy cows could be under thermal stress. For instance, in Ontario, cows are expected to be 105 days under thermal stress. The objective of this study was to estimate genetic parameters for milk production traits under heat stress in Canadian Holstein cows. A total of 604,050 test-day records for milk, fat, and protein yields from 78,516 first-lactation Holstein cows were used in this study. The production data was combined with daily maximum temperature-humidity index (THI; ranging from 30 to 83) calculated based on meteorological records from public weather stations. In total, 58 weather stations were located within a maximum distance of 20 km from each of the 1,284 herds included in this study. Single-trait random regressions on THI, fitting linear splines to describe the random additive genetic and permanent environmental effects, were used in the genetic analyses. Based on preliminary analyses, the knots of the spline functions were set to THI = 70, 57, and 58 for milk, fat, and protein yields, respectively. Therefore, the models assumed a linear effect of heat stress beyond the THI threshold, allowing to estimate the additive genetic effect under thermal comfort and at different levels of heat stress. The genetic correlations estimated between thermal comfort and heat stress were -0.09, -0.33, and -0.21 for milk, fat, and protein yields, respectively. This indicates an antagonistic relationship between level of production and heat tolerance. However, small differences in heritability estimates were observed above the THI thresholds (they ranged from 0.20 to 0.22 for milk, 0.18 to 0.15 for fat, and 0.14 to 0.15 for protein yields). This study demonstrates the possibility of genetically selecting for more heat-tolerant animals in Canada.

Genetic selection for improved feed efficiency in dairy cattle has received renewed attention over the last decade to address the needs of a growing global population. As milk yield is a critical component of feed efficiency metrics in dairy animals, our objective was to evaluate the associations between feed efficiency in primiparous Holstein cattle and parameters of a mathematical model describing individual lactation curves. The Dijkstra lactation curve model was fit to individual lactation records from 34 Holstein heifers with previously estimated measures of feed efficiency. We found that the optimal fit of the Dijkstra model was achieved using daily milk yield records up to 21 d in milk to capture the rise to peak milk yield and using monthly dairy herd improvement records for the remainder of lactation to accurately characterize lactation persistency. In the period of lactation before peak milk yield, improved feed efficiency was associated with a faster increase in daily milk yield over a shorter period of time at the expense of increased mobilization of body reserves; this serves to reinforce the concept that dairy cattle are primarily capital breeders versus income breeders. Feed efficiency in the period following peak lactation, as measured by gross feed efficiency, return over feed costs, and net energy efficiency of lactation, was positively associated with higher peak milk yield. The findings in early lactation suggest that estimates of feed efficiency could be improved by evaluating feed efficiency relative to conception, rather than parturition and lactation, to better account for the energy stored and released from body reserves in capital breeding.

Genome-wide association studies based on SNP have been completed for multiple traits in dairy cattle; however, copy number variants (CNV) could add genomic information that has yet to be harnessed. The objectives of this study were to identify CNV in genotyped Holstein animals and assess their association with hoof health traits using deregressed estimated breeding values as pseudophenotypes. A total of 23,256 CNV comprising 1,645 genomic regions were identified in 5,845 animals. Fourteen genomic regions harboring structural variations, including 9 deletions and 5 duplications, were associated with at least 1 of the studied hoof health traits. This group of traits included digital dermatitis, interdigital dermatitis, heel horn erosion, sole ulcer, white line lesion, sole hemorrhage, and interdigital hyperplasia; no regions were associated with toe ulcer. Twenty candidate genes overlapped with the regions associated with these traits including SCART1, NRXN2, KIF26A, GPHN, and OR7A17. In this study, an effect on infectious hoof lesions could be attributed to the PRAME (Preferentially Expressed Antigen in Melanoma) gene. Almost all genes detected in association with noninfectious hoof lesions could be linked to known metabolic disorders. The knowledge obtained considering information of associated CNV to the traits of interest in this study could improve the accuracy of estimated breeding values. This may further increase the genetic gain for these traits in the Canadian Holstein population, thus reducing the involuntary animal losses due to lameness.

The economic importance of genetically improving feed efficiency has been recognized by cattle producers worldwide. It has the potential to considerably reduce costs, minimize environmental impact, optimize land and resource use efficiency, and improve the overall cattle industry’s profitability. Feed efficiency is a genetically complex trait that can be described as units of product output (e.g., milk yield) per unit of feed input. The main objective of this review paper is to present an overview of the main genetic and physiological mechanisms underlying feed utilization in ruminants and the process towards implementation of genomic selection for feed efficiency in dairy cattle. In summary, feed efficiency can be improved via numerous metabolic pathways and biological mechanisms through genetic selection. Various studies have indicated that feed efficiency is heritable, and genomic selection can be successfully implemented in dairy cattle with a large enough training population. In this context, some organizations have worked collaboratively to do research and develop training populations for successful implementation of joint international genomic evaluations. The integration of “-omics” technologies, further investments in high-throughput phenotyping, and identification of novel indicator traits will also be paramount in maximizing the rates of genetic progress for feed efficiency in dairy cattle worldwide.

Methane is a greenhouse gas of high interest to the dairy industry, with 57% of Australia's dairy emissions attributed to enteric methane. Enteric methane emissions also constitute a loss of approximately 6.5% of ingested energy. Genetic selection offers a unique mitigation strategy to decrease the methane emissions of dairy cattle, while simultaneously improving their energy efficiency. Breeding objectives should focus on improving the overall sustainability of dairy cattle by reducing methane emissions without negatively affecting important economic traits. Common definitions for methane production, methane yield, and methane intensity are widely accepted, but there is not yet consensus for the most appropriate method to calculate residual methane production, as the different methods have not been compared. In this study, we examined 9 definitions of residual methane production. Records of individual cow methane, dry matter intake (DMI), and energy corrected milk (ECM) were obtained from 379 animals and measured over a 5-d period from 12 batches across 5 yr using the SF6 tracer method and an electronic feed recording system, respectively. The 9 methods of calculating residual methane involved genetic and phenotypic regression of methane production on a combination of DMI and ECM corrected for days in milk, parity, and experimental batch using phenotypes or direct genomic values. As direct genomic values (DGV) for DMI are not routinely evaluated in Australia at this time, DGV for FeedSaved, which is derived from DGV for residual feed intake and estimated breeding value for bodyweight, were used. Heritability estimates were calculated using univariate models, and correlations were estimated using bivariate models corrected for the fixed effects of year-batch, days in milk, and lactation number, and fitted using a genomic relationship matrix. Residual methane production candidate traits had low to moderate heritability (0.10 ± 0.09 to 0.21 ± 0.10), with residual methane production corrected for ECM being the highest. All definitions of residual methane were highly correlated phenotypically (>0.87) and genetically (>0.79) with one another and moderately to highly with other methane candidate traits (>0.59), with high standard errors. The results suggest that direct selection for a residual methane production trait would result in indirect, favorable improvement in all other methane traits. The high standard errors highlight the importance of expanding data sets by measuring more animals for their methane emissions and DMI, or through exploration of proxy traits and combining data via international collaboration.

Made available in DSpace on 2020-12-12T01:50:02Z (GMT). No. of bitstreams: 0 Previous issue date: 2020-02-01 Genomic evaluations are useful for crossbred as well as purebred populations when selection is applied to commercial herds. Dairy farmers had already spent more than $1 million to genotype over 32,000 crossbred animals before US genomic evaluations became available for those animals. Thus, new tools were needed to provide accurate genomic predictions for crossbreds. Genotypes for crossbreds are imputed more accurately when the imputation reference population includes purebreds. Therefore, genotypes of 6,296 crossbred animals were imputed from lower-density chips by including either 3,119 ancestors or 834,367 genotyped animals in the reference population. Crossbreds in the imputation study included 733 Jersey × Holstein F1 animals, 55 Brown Swiss × Holstein F1 animals, 2,300 Holstein backcrosses, 2,026 Jersey backcrosses, 27 Brown Swiss backcrosses, and 502 other crossbreds of various breed combinations. Another 653 animals appeared to be purebreds that owners had miscoded as a different breed. Genomic breed composition was estimated from 60,671 markers using the known breed identities for purebred, progeny-tested Holstein, Jersey, Brown Swiss, Ayrshire, and Guernsey bulls as the 5 traits (breed fractions) to be predicted. Estimates of breed composition were adjusted so that no percentages were negative or exceeded 100%, and breed percentages summed to 100%. Another adjustment set percentages above 93.5% equal to 100%, and the resulting value was termed breed base representation (BBR). Larger percentages of missing alleles were imputed by using a crossbred reference population rather than only the closest purebred reference population. Crossbred predictions were averages of genomic predictions computed using marker effects for each pure breed, which were weighted by the animal's BBR. Marker and polygenic effects were estimated separately for each breed on the all-breed scale instead of within-breed scales. For crossbreds, genomic predictions weighted by BBR were more accurate than the average of parents' breeding values and slightly more accurate than predictions using only the predominant breed. For purebreds, single-trait predictions using only within-breed data were as accurate as multi-trait predictions with allele effects in different breeds treated as correlated effects. Crossbred genomic predicted transmitting abilities were implemented by the Council on Dairy Cattle Breeding in April 2019 and will aid producers in managing their breeding programs and selecting replacement heifers. USDA Agricultural Research Service Animal Genomics and Improvement Laboratory Departamento de Ciências Exatas Universidade Estadual Paulista (Unesp) Faculdade de Ciências Agrárias e Veterinárias, Jaboticabal Council on Dairy Cattle Breeding Departamento de Ciências Exatas Universidade Estadual Paulista (Unesp) Faculdade de Ciências Agrárias e Veterinárias, Jaboticabal

Multiple methods to detect copy number variants (CNV) relying on different types of data have been developed and CNV have been shown to have an impact on phenotypes of numerous traits of economic importance in cattle, such as reproduction and immunity. Further improvements in CNV detection are still needed in regard to the trade-off between high-true and low-false positive variant identification rates. Instead of improving single CNV detection methods, variants can be identified in silico with high confidence when multiple methods and datasets are combined. Here, CNV were identified from whole-genome sequences (WGS) and genotype array (GEN) data on 96 Holstein animals. After CNV detection, two sets of high confidence CNV regions (CNVR) were created that contained variants found in both WGS and GEN data following an animal-based (n = 52) and a population-based (n = 36) pipeline. Furthermore, the change in false positive CNV identification rates using different GEN marker densities was evaluated. The population-based approach characterized CNVR, which were more often shared among animals (average 40% more samples per CNVR) and were more often linked to putative functions (48 vs 56% of CNVR) than CNV identified with the animal-based approach. Moreover, false positive identification rates up to 22% were estimated on GEN information. Further research using larger datasets should use a population-wide approach to identify high confidence CNVR.

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 CORR anim exceeded 0.96 (for 50K and 70K panels) when only Girolando animals were included in RPop (S1). We found smaller CORR anim 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 (CORR snp ) within each scenario. Crossbred animals (Girolando) must be included in the reference population to provide the best imputation accuracies.

Made available in DSpace on 2018-12-11T17:09:51Z (GMT). No. of bitstreams: 0 Previous issue date: 2017-04-01 The aim of this study was to estimate genetic parameters for scrotal circumference at 365 (SC365) and 450 (SC450) days of age, age at first calving (AFC), ribeye area (REA), backfat (BF) thickness, and rump fat (RF) thickness, in order to provide information on potential traits for Nelore cattle breeding program. Genetic parameters were estimated using the Average Information Restricted Maximum Likelihood method in single- and multitrait analyses. Four different animal models were tested for SC365, SC450, REA, BF, and RF in single-trait analyses. For SC365 and SC450, the maternal genetic effect was statistically significant (P

In dairy production, high fertility contributes to herd profitability by achieving greater production and maintaining short calving intervals. Improved management practices and genetic selection have contributed to reversing negative trends in dairy cow fertility, but further progress is still required. Phenotypes included in current genetic evaluations are largely interval and binary traits calculated from insemination and calving date records. Several indicator traits such as calving, health, variation in body condition score, and longevity traits also apply to genetic improvement of fertility. Several fertility traits are included in the selection indices of many countries, but for improved selection, the development of novel phenotypes that more closely describe the physiology of reproduction and limit management bias could be more effective. Progesterone-based phenotypes can be determined from milk samples to describe the heritable interval from calving to corpus luteum activity, as well as additional measures of cow cyclicity. A fundamental component of artificial insemination practices is the observation of estrus. Novel phenotypes collected on estrous activity could be used to select for cows clearly displaying heat, as those cows are more likely to be inseminated at the right time and therefore have greater fertility performance. On-farm technologies, including in-line milk testing and activity monitors, may allow for phenotyping novel traits on large numbers of animals. Additionally, selection for improved fertility using traditional traits could benefit from refined and accurate recording and implementation of parameters such as pregnancy confirmation and reproductive management strategy, to differentiate embryonic or fetal loss, and to ensure selection for reproductive capability without producer intervention. Opportunities exist to achieve genetic improvement of reproductive efficiency in cattle using novel phenotypes, which is required for long-term sustainability of the dairy cattle population and industry.

Feed efficiency has been widely studied in many areas of dairy science and is currently seeing renewed interest in the field of breeding and genetics. A critical part of determining how efficiently an animal utilizes feed is accurately measuring individual dry matter (DM) intake. Currently, multiple methods are used to measure feed intake or determine the DM content of that feed, resulting in different levels of accuracy of measurement. Furthermore, the scale at which data need to be collected for use in genetic analyses makes some methodologies impractical. This systematic review aims to provide an overview of the current methodologies used to measure both feed intake in ruminants and DM content of feedstuffs, current methods to predict individual DM intake, and applications of large-scale intake measurements. Overall, advances in milk spectral data analysis present a promising method of estimating individual DM intake on a herd scale with further validation of prediction models. Although measurements of individual feed intake rely on the same underlying principle, the methods selected are largely dictated by the costs of capital, labor, and necessary analyses. Finally, DM methodologies were synthesized into a comprehensive protocol for use in a variety of feedstuffs.

The Canadian dairy industry has been using invivo and invitro assisted reproductive technologies to produce embryos. Technological improvements have helped increase the number and quality of embryos produced, but genetic and genomic tools for improving these traits have yet to be assessed for the Canadian Holstein population. Genetic parameters and a genome-wide association study were performed in Canadian Holstein for the total number of embryos (NE) and the number of viable embryos (VE). Results showed potential for genetic selection for both NE and VE, with heritability estimates (± s.e.) of approximately 0.15±0.01. Genetic correlations between the number of embryos produced using different procedures (invivo and invitro) suggested that a similar number of embryos should be expected from a donor regardless of the procedure used. A region on chromosome 11 of the bovine genome was found to be significantly associated with the number of embryos, indicating a potential regulatory role of this region on embryo production. Overall, these findings are of interest for the Canadian dairy industry because they provide useful information for breeders that are interested in producing embryos from the elite donors in their herds or in the population using assisted reproductive technologies.

Genetically selecting for improved feed efficiency has been recognized by the dairy cattle industry as an important economic and environmental goal. Improved feed efficiency has the potential to significantly reduce costs, improving dairy farmers’ profitability and, at the same time, minimize environmental impact, for example by reducing nutrient loss in manure and methane emissions. Feed efficiency is recognized as a complex trait that may be define in different ways, but it generally describes units of product output per unit of feed required. An overview of genetic selection for improved feed efficiency and international initiatives to implement genomic selection for feed efficiency in dairy cattle is presented. In general, studies have indicated that feed efficiency, defined and assessed in alternative ways, is moderately heritable and genetic selection could be successfully implemented. Various initiatives around the world have worked collaboratively to carried out research and create reference datasets for joint genomic evaluations. An example is the large international Efficient Dairy Genome Project (EDGP) led by Canada. The EDGP database was developed in 2017 to allow data sharing among the international collaborators. Currently, the database contains genotypes and records on feed intake of 5,289 cows and on methane emissions of 1,337 cows from eight research herds in six countries (Australia, Canada, Denmark, Switzerland, United Kingdom and United States). Genetic parameters (heritability and genetic correlations) were estimated for dry matter intake, metabolic body weight and energy corrected milk at two time-periods: a) 5–60 DIM and b) 60–150 DIM. These parameters provide a basis for development of breeding value estimation procedures and subsequent selection index for feed efficiency, which will incorporate genomic information.

The aim of this study was to estimate genetic parameters for accumulated productivity (ACP), first calving interval (CI1), second calving interval (CI2), and mean calving interval (MCI) in Nelore beef cattle. The ACP trait is a reproduction index and comprises the total number of calves born per dam, weight of weaned calves, and age of the dam at calving. Genetic parameters were estimated by the average information restricted maximum likelihood method in two-trait analyses. The average heritability estimate for ACP was 0.17 (0.03). For CI1, CI2, and MCI, the heritability estimates were 0.02, 0.02, and 0.06, respectively. Genetic correlations between ACP with CI1, CI2, and MCI were -0.16 ± 0.47, -0.29 ± 0.53, and -0.40 ± 0.27, respectively. Despite of the low heritability estimates obtained in our study, reproduction traits should be further studied and their inclusion in the selection criteria must be evaluated in order to improve the performance of females because these traits are of great economic importance in beef cattle. Accumulated productivity could contribute to decrease the mean calving interval in Nelore cattle.

Made available in DSpace on 2018-12-11T16:49:24Z (GMT). No. of bitstreams: 0 Previous issue date: 2017-11-01 Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) The availability of large-scale SNP genotyping panels for horses has opened up new possibilities for genetic studies of the species. The first panel version contained around 54,000 SNPs (54k). The current second generation panel possesses approximately 65,000 SNPs (65k), which 19,000 of them are new markers and 45,000 were present in the first panel. The objectives of this study were to perform two-step genotype imputation between individuals in a relatively small population sample of racing Quarter Horses genotyped with the 54k or 65k panel and to evaluate the accuracy of imputation in a practical situation. Genotypes were imputed using 116 horses genotyped with the 54k SNP array and 233 animals genotyped with the 65k array. For the simulations, random samples were chosen to compose the imputed (about 50% samples) and reference populations in two scenarios. Scenario A simulated the genotype imputation in the first step (from 65k to 54k) and the scenario B in the second step (from 54k to 65k). For each scenario, the individuals genotyped with the same panel were considered as the reference population but that were included in the imputed group had their exclusive genotypes masked for subsequent evaluation of imputation accuracy. Thus, after quality control, the 54k and 65k panels contained 7,048 and 16,940 exclusive markers, respectively. The mean concordance rate was 0.9815 and 0.9751 for scenarios A and B, and the mean allelic r2 was 0.9791 and 0.974, respectively. No important influences of the genomic relationship coefficients on imputation accuracy were observed between the imputed and reference samples. Thus, two-step imputation of exclusive genotypes between the 54k and 65k equine panels resulted in a considerable increase of SNPs for all samples (12%–26%) without losses in the quality of information. Faculdade de Ciências Agrárias e Veterinárias Universidade Estadual Paulista (Unesp) Faculdade de Medicina Veterinária e Zootecnia Universidade Estadual Paulista (Unesp) Faculdade de Ciências Agrárias e Veterinárias Universidade Estadual Paulista (Unesp) Faculdade de Medicina Veterinária e Zootecnia Universidade Estadual Paulista (Unesp) FAPESP: 2014/20207-1

Made available in DSpace on 2018-12-11T17:14:06Z (GMT). No. of bitstreams: 0 Previous issue date: 2017-08-23 Background: Beef 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 210d of age, scrotal circumference at 420d 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. Results: Associated SNPs were observed for scrotal circumference at 420d of age (435 SNPs), followed by scrotal circumference at 210d 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. Conclusions: Few associations were observed for scrotal circumference at 210d 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 420d 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. Universidade Federal da Paraíba (UFPB) Departamento de Zootecnia Fast Genetics Beef Improvement Opportunities (BIO) University of Guelph Centre for Genetic Improvement of Livestock (CGIL) Department of Animal and Poultry Science Universidade Estadual Paulista (Unesp) Departamento de Ciências Exatas Faculdade de Ciências Agrárias e Veterinárias Universidade Estadual Paulista (Unesp) Departamento de Zootecnia Núcleo de Pesquisa e Conservação de Cervídeos Faculdade de Ciências Agrárias e Veterinárias Federal University of Lavras (UFLA) Department of Animal Science Federal University of São Carlos (UFSCar) Department of Genetics and Evolution Embrapa Agricultural Informatics Embrapa Dairy Cattle Embrapa Southeast Livestock Universidade Estadual Paulista (Unesp) Departamento de Ciências Exatas Faculdade de Ciências Agrárias e Veterinárias Universidade Estadual Paulista (Unesp) Departamento de Zootecnia Núcleo de Pesquisa e Conservação de Cervídeos Faculdade de Ciências Agrárias e Veterinárias

Made available in DSpace on 2018-11-28T07:23:20Z (GMT). No. of bitstreams: 0 Previous issue date: 2017-03-21 Embrapa (Brazil) Genomic Selection in Dairy Cattle in Brazil Embrapa (Brazil) National network for development of innovative genomic strategies applied to animal breeding, conservation and production (PI - ARC) Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) Fundação de Amparo à Pesquisa do Estado de Minas Gerais (FAPEMIG) Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) Whole-genome re-sequencing, alignment and annotation analyses were undertaken for 12 sires representing four important cattle breeds in Brazil: Guzerat (multi-purpose), Gyr, Girolando and Holstein (dairy production). A total of approximately 4.3 billion reads from an Illumina HiSeq 2000 sequencer generated for each animal 10.7 to 16.4-fold genome coverage. A total of 27,441,279 single nucleotide variations (SNVs) and 3,828,041 insertions/deletions (InDels) were detected in the samples, of which 2,557,670 SNVs and 883,219 InDels were novel. The submission of these genetic variants to the dbSNP database significantly increased the number of known variants, particularly for the indicine genome. The concordance rate between genotypes obtained using the Bovine HD BeadChip array and the same variants identified by sequencing was about 99.05%. The annotation of variants identified numerous non-synonymous SNVs and frameshift InDels which could affect phenotypic variation. Functional enrichment analysis was performed and revealed that variants in the olfactory transduction pathway was over represented in all four cattle breeds, while the ECM-receptor interaction pathway was over represented in Girolando and Guzerat breeds, the ABC transporters pathway was over represented only in Holstein breed, and the metabolic pathways was over represented only in Gyr breed. The genetic variants discovered here provide a rich resource to help identify potential genomic markers and their associated molecular mechanisms that impact economically important traits for Gyr, Girolando, Guzerat and Holstein breeding programs. Univ Estadual Paulista, Dept Ciencias Exatas, Fac Ciencias Agrarias & Vet, Sao Paulo, Brazil Embrapa Informat Agr, Campinas, SP, Brazil Embrapa Recursos Genet & Biotecnol, Brasilia, DF, Brazil Iowa State Univ, Dept Anim Sci, Ames, IA USA Embrapa Gado Leite, Juiz De Fora, MG, Brazil Univ Fed Minas Gerais, Dept Biol Geral, Belo Horizonte, MG, Brazil ARS, USDA, Anim Genom & Improvement Lab, Beltsville, MD USA Univ Estadual Paulista, Dept Ciencias Exatas, Fac Ciencias Agrarias & Vet, Sao Paulo, Brazil Embrapa (Brazil) Genomic Selection in Dairy Cattle in Brazil: SEG 02.09.07.008.00.00 Embrapa (Brazil) National network for development of innovative genomic strategies applied to animal breeding, conservation and production (PI - ARC): SEG 01.11.07.002.00.00 CNPq: PVE 407246/2013-4 FAPEMIG: CVZ PPM 00395/14 FAPESP: 15/08939-0

The aim of this study was to estimate variance and covariance components for gestation length (GL), birth weight (BW), weaning weight (WW), and accumulated productivity (ACP), and their respective genetic trends for Nellore cattle raised in Brazil. The ACP trait is a reproduction index developed by the National Association of Breeders and Researchers (ANCP) and comprises the total number of calves born per dam, weight of weaned calves, and age of the dam at calving. A total of 25,085, 46,911, 50,044, and 7351 observations were considered to analyze GL, BW, WW, and ACP. Genetic parameters were estimated by the Average Information Restricted Maximum Likelihood method in single and two-trait analyses. The average direct heritability estimates obtained in two-trait analyses were equal to 0.38±0.03 (GL), 0.25±0.02 (BW), 0.28±0.02 (WW), and 0.11±0.02 (ACP). The highest genetic correlation was found between BW and WW (0.36±0.05), followed by BW and ACP (0.20±0.09), and BW and GL (0.19±0.06). Significant direct genetic trends ( P

This study aimed to estimate genetic parameters for five traits related to performance and carcass in a terminal pig sire line using multitrait (MUV) and reduced rank animal models, and to analyze the relationship between the breeding values (EBVs) of the traits using genetic principal component analysis (PCA) applied directly on the mixed model equations (one-step PCA) and on the EBVs obtained using the MUV (two-step PCA). The heritabilities were very similar using both procedures ranged from 0.032 ± 0.014 for feed conversion to 0.102 ± 0.029 for lean meat. Except for some differences in the heritability for feed conversion ratio, the heritability estimates were remarkably similar using One-step PCA or MUV. The genetic correlations obtained using One-Step PCA were more reliable due to their lower standard errors compared to those obtained using MUV. The one-step PCA had better fit than MUV and could reduce the time computing due to the reduction of the additive genetic matrix.

Made available in DSpace on 2019-10-06T17:04:17Z (GMT). No. of bitstreams: 0 Previous issue date: 2019-02-01 Single nucleotide polymorphism (SNP) markers are used to study population structure and conservation genetics, which permits assessing similarities regarding the linkage disequilibrium and information about the relationship among individuals. To investigate the population genomic structure of 300 females and 25 males from a commercial maternal pig line we analyzed linkage disequilibrium extent, inbreeding coefficients using genomic and conventional pedigree data, and population stratification. The average linkage disequilibrium (r2) was 0.291 ± 0.312 for all adjacent SNPs, distancing less than 100 Kb (kilobase) between markers. The average inbreeding coefficients obtained from runs of homozygosity (ROH) and pedigree analyses were 0.119 and 0.0001, respectively. Low correlation was observed between the inbreeding coefficients possibly as a result of genetic recombination effect accounted for the ROH estimates or caused by pedigree identification errors. A large number of long ROHs might indicate recent inbreeding events in the studied population. A total of 36 homozygous segments were found in more than 30% of the population and these ROH harbor genes associated with reproductive traits. The population stratification analysis indicated that this population was possibly originated from two distinct populations, which is a result from crossings between the eastern and western breeds used in the formation of the line. Our findings provide support to understand the genetic structure of swine populations and may assist breeding companies to avoid a high level of inbreeding coefficients to maintain genetic diversity, showing the effectiveness of using genomewide SNP information for quantifying inbreeding when the pedigree was incomplete or incorrect. Departamento de Ciências Exatas Faculdade de Ciências Agrá Rias E Veteriná Rias Universidade Estadual Paulista (Unesp) Departamento de Zootecnia Universidade Federal da Paraíba (UFPB) Universidade de Passo Fundo (UPF) Embrapa Suínos e Aves Departamento de Zootecnia E Desenvolvimento Rural Centro de Ciências Agrá Rias Universidade Federal de Santa Catarina (UFSC) Departamento de Ciências Exatas Faculdade de Ciências Agrá Rias E Veteriná Rias Universidade Estadual Paulista (Unesp)

Submitted by Vitor Silverio Rodrigues (vitorsrodrigues@reitoria.unesp.br) on 2014-05-27T11:29:49Z No. of bitstreams: 0 Made available in DSpace on 2014-05-27T11:29:49Z (GMT). No. of bitstreams: 0 Previous issue date: 2013-07-01 The objective of this study was to estimate genetic parameters for female mature weight (FMW), age at first calving (AFC), weight gain from birth to 120 days (WG_B_120), from 210 to 365 days (WG_210_365), rib eye area (REA), back fat thickness (BF), rump fat (RF) and body weight at scanning date (BWS) using single and multiple-trait animal models by the REML method from Nellore cattle data. The estimates of heritability ranged from 0.163±0.011 for WG_210_365 to 0.309±0.028 for RF using the single-trait model and from 0.163±0.010 for WG_210_365 to 0.382±0.025 for BWS using the multiple-trait model. The estimates of genetic correlations ranged from -0.35±0.08 between AFC with BF to 0.69±0.04 between WG_B_120 with BWS. Selection for weights gains, REA, and BWS can improve FMW. © 2013 Elsevier B.V. Departamento de Ciências Exatas Faculdade de Ciências Agrárias e Veterinárias Universidade Estadual Paulista, 14884-900 Jaboticabal, São Paulo Associação Nacional de Criadores e Pesquisadores (ANCP), 14020-230 Ribeirão Preto, São Paulo Departamento de Ciências Exatas Faculdade de Ciências Agrárias e Veterinárias Universidade Estadual Paulista, 14884-900 Jaboticabal, São Paulo

Made available in DSpace on 2018-12-11T17:31:25Z (GMT). No. of bitstreams: 0 Previous issue date: 2017-02-01 Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) The aim of this study was to evaluate the level of introgression of breeds in the Canchim (CA: 62.5% Charolais-37.5% Zebu) and MA genetic group (MA: 65.6% Charolais-34.4% Zebu) cattle using genomic information on Charolais (CH), Nelore (NE), and Indubrasil (IB) breeds. The number of animals used was 395 (CA and MA), 763 (NE), 338 (CH), and 37 (IB). The Bovine 50SNP BeadChip from Illumina panel was used to estimate the levels of introgression of breeds considering the Maximum likelihood, Bayesian, and Single Regression method. After genotype quality control, 32,308 SNPs were considered in the analysis. Furthermore, three thresholds to prune out SNPs in linkage disequilibrium higher than 0.10, 0.05, and 0.01 were considered, resulting in 15,286, 7,652, and 1,582 SNPs, respectively. For k = 2, the proportion of taurine and indicine varied from the expected proportion based on pedigree for all methods studied. For k = 3, the Regression method was able to differentiate the animals in three main clusters assigned to each purebred breed, showing more reasonable according to its biological viewpoint. Analyzing the data considering k = 2 seems to be more appropriate for Canchim-MA animals due to its biological interpretation. The usage of 32,308 SNPs in the analyses resulted in similar findings between the estimated and expected breed proportions. Using the Regression approach, a contribution of Indubrasil was observed in Canchim-MA when k = 3 was considered. Genetic parameter estimation could account for this breed composition information as a source of variation in order to improve the accuracy of genetic models. Our findings may help assemble appropriate reference populations for genomic prediction for Canchim-MA in order to improve prediction accuracy. Using the information on the level of introgression in each individual could also be useful in breeding or crossing design to improve individual heterosis in crossbred cattle. Departamento de Ci�ncias Exatas Universidade Estadual Paulista (Unesp) Faculdade de Ci�ncias Agrarias e Veterinarias Beef Improvement Opportunities (BIO) Departamento de Ci�ncias Basicas Universidade de S�o Paulo (USP) Faculdade de Zootecnia e Engenharia de Alimentos (FZEA) Departamento de Zootecnia Universidade Estadual Paulista (Unesp) Faculdade de Ci�ncias Agrarias e Veterinarias Embrapa Southeast Livestock Embrapa Agricultural Informatics Faculdade de Agronomia e Medicina Veterin�ria Universidade de Passo Fundo Embrapa Dairy Cattle Department of Agricultural Food and Nutritional Science University of Alberta Lacombe Research and Development Centre Agriculture and Agri-Food Canada, 6000 C and E Trail Department of Animal and Poultry Science University of Guelph Centre for Genetic Improvement of Livestock (CGIL) Departamento de Ci�ncias Exatas Universidade Estadual Paulista (Unesp) Faculdade de Ci�ncias Agrarias e Veterinarias Departamento de Zootecnia Universidade Estadual Paulista (Unesp) Faculdade de Ci�ncias Agrarias e Veterinarias CAPES: 02663/09-0 CNPq: 449564/2014-2

Made available in DSpace on 2018-12-11T17:02:41Z (GMT). No. of bitstreams: 0 Previous issue date: 2016-05-05 Background: Recent technological advances in genomics have allowed the genotyping of cattle through single nucleotide polymorphism (SNP) panels. High-density SNP panels possess greater genome coverage and are useful for the identification of conserved regions of the genome due to selection, known as selection signatures (SS). The SS are detectable by different methods, such as the extended haplotype homozygosity (EHH); and the integrated haplotype score (iHS), which is derived from the EHH. The aim of this study was to identify SS regions in Canchim cattle (composite breed), genotyped with high-density SNP panel. Results: A total of 687,655 SNP markers and 396 samples remained for SS analysis after the genotype quality control. The iHS statistic for each marker was transformed into piHS for better interpretation of the results. Chromosomes BTA5 and BTA14 showed piHS > 5, with 39 and nine statistically significant SNPs (P < 0.00001), respectively. For the candidate selection regions, iHS values were computed across the genome and averaged within non-overlapping windows of 500 Kb. We have identified genes that play an important role in metabolism, melanin biosynthesis (pigmentation), and embryonic and bone development. Conclusions: The observation of SS indicates that the selection processes performed in Canchim, as well as in the founder breeds (i.e. Charolais), are maintaining specific genomic regions, particularly on BTA5 and BTA14. These selection signatures regions could be associated with Canchim characterization. Univ Estadual Paulista Faculdade de Ciências Agrárias e Veterinárias Departamento de Ciências Exatas UNESP - Univ Estadual Paulista Faculdade de Ciências Agrárias e Veterinárias Departamento de Tecnologia Embrapa Agricultural Informatics Embrapa Southeast Livestock Univ Estadual Paulista Faculdade de Ciências Agrárias e Veterinárias Departamento de Ciências Exatas UNESP - Univ Estadual Paulista Faculdade de Ciências Agrárias e Veterinárias Departamento de Tecnologia

Made available in DSpace on 2015-12-07T15:36:49Z (GMT). No. of bitstreams: 0 Previous issue date: 2015-08-07. Added 1 bitstream(s) on 2015-12-07T15:54:24Z : No. of bitstreams: 1 PMC4527250.pdf: 1497402 bytes, checksum: 788681d54c019d5a0a161c2a7d7c043a (MD5) Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) Genotype 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 (R(2)). The 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. The 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. Departamento de Ciências Exatas, Faculdade de Ciências Agrárias e Veterinárias (FCAV), Universidade Estadual Paulista (UNESP), Jaboticabal, SP, Brasil Beef Improvement Opportunities, Guelph, ON, Canada University of Guelph, Guelph, ON, Canada Departamento de Zootecnia, Faculdade de Ciências Agrárias e Veterinárias (FCAV), Universidade Estadual Paulista (UNESP), Jaboticabal, SP, Brasil Embrapa Southeast Livestock - Brazilian Corporation of Agricultural Research, São Carlos, SP, Brasil Embrapa Dairy Cattle - Brazilian Corporation of Agricultural Research, Juiz de Fora, MG, Brasil Departamento de Genética e Evolução, Universidade Federal de São Carlos (UFSCar), São Carlos, SP, Brasil Universidade Estadual Paulista, Departamento de Ciências Exatas, Faculdade de Ciências Agrárias e Veterinárias de Jaboticabal Universidade Estadual Paulista, Departamento de Zootecnia, Faculdade de Ciências Agrárias e Veterinárias de Jaboticabal FAPESP: 2012/21891-8 FAPESP: 2013/19335-2

Selection among broilers for performance traits is resulting in locomotion problems and bone disorders, once skeletal structure is not strong enough to support body weight in broilers with high growth rates. In this study, genetic parameters were estimated for body weight at 42 days of age (BW42), and tibia traits (length, width, and weight) in a population of broiler chickens. Quantitative trait loci (QTL) were identified for tibia traits to expand our knowledge of the genetic architecture of the broiler population. Genetic correlations ranged from 0.56 +/- 0.18 (between tibia length and BW42) to 0.89 +/- 0.06 (between tibia width and weight), suggesting that these traits are either controlled by pleiotropic genes or by genes that are in linkage disequilibrium. For QTL mapping, the genome was scanned with 127 microsatellites, representing a coverage of 2630 cM. Eight QTL were mapped on Gallus gallus chromosomes (GGA): GGA1, GGA4, GGA6, GGA13, and GGA24. The QTL regions for tibia length and weight were mapped on GGA1, between LEI0079 and MCW145 markers. The gene DACH1 is located in this region; this gene acts to form the apical ectodermal ridge, responsible for limb development. Body weight at 42 days of age was included in the model as a covariate for selection effect of bone traits. Two QTL were found for tibia weight on GGA2 and GGA4, and one for tibia width on GGA3. Information originating from these QTL will assist in the search for candidate genes for these bone traits in future studies.

Submitted by Vitor Silverio Rodrigues (vitorsrodrigues@reitoria.unesp.br) on 2014-05-27T11:29:30Z No. of bitstreams: 0 Made available in DSpace on 2014-05-27T11:29:30Z (GMT). No. of bitstreams: 0 Previous issue date: 2013-05-14 The objectives of this study were to estimate genetic parameters involving yearling weight (Ps), carcass weight (Pc), hip height (Ag) and the scores of conformation (C), precocity (P) and musculature (M) and carcass yield (Rd) and finishing score (Ac) in Nellore cattle in order to define criteria for selection in this breed. The data of the 20 732 animals were obtained from Agrope-cuária Jacarezinho, SP. Data were analyzed by restricted maximum likelihood using animal model multi-trait analysis, which included fixed effects of contemporary groups (animals born at the same month and slaughtered on the same day) and the covariate age at slaughter (linear) for carcass traits, and contemporary groups (animals of the same farm, age, sex and management group at weaning and yearling) and yearling age (linear) for growth and as random, the additive effects and residual effects. Estimates ranged from 0.13 (Ac and Rd) to 0.36 (Ag) for heritability and from -0.59 ± 0.62 (Rd with Ac) to 0.71 ± 0.17 (Pc with C) for genetic correlations. Selection for Pc, C, P, M, Ag or Ps may be efficient because their heritability estimates are of magnitude moderate. Selection for Ps and C can favor heavier Pc, considering their positive and high genetic correlation. Departamento de Zootecnia FCAV/UNESP, Jaboticabal, SP Departamento de Ciências Exatas FCAV/UNESP, Jaboticabal, SP Departamento de Melhoramento e Nutrição Animal FMVZ/UNESP, Botucatu, SP Departamento de Zootecnia FCAV/UNESP, Jaboticabal, SP Departamento de Ciências Exatas FCAV/UNESP, Jaboticabal, SP Departamento de Melhoramento e Nutrição Animal FMVZ/UNESP, Botucatu, SP

In this study, the objective was to estimate genetic parameters of body weight at 210 (BW210) and 365 (BW365) days of age in relation to rib eye area (REA), subcutaneous back fat thickness (BF) and rump fat (RF), and their respective genetic trends, in Nelore beef cattle. Estimates of genetic parameters and breeding values for the studied traits were obtained using the REML method. The direct and maternal heritability estimates were respectively: 0.25 ± 0.02 and 0.21 ± 0.01, for BW210, and 0.29 ± 0.02 and 0.09 ± 0.01, for BW365. The heritability estimates for transformed REA, BF and RF were 0.29 ± 0.03, 0.21 ± 0.02 and 0.23 ± 0.03, respectively. There were genetic associations between BW210 and REA, BW365 and REA, and BF and RF, while the other correlations were low. The selection process that was conducted at the farms participating in the breeding program, taking the proposed selection index into consideration, caused genetic changes to these traits.