Feet and legs malformation in Nellore cattle: genetic analysis and prioritization of GWAS results

Beef cattle affected by feet and legs malformations (FLM) cannot perform their productive and reproductive functions satisfactorily, resulting in significant economic losses. Accelerated weight gain in young animals due to increased fat deposition can lead to ligaments, tendon and joint strain and promote gene expression patterns that lead to changes in the normal architecture of the feet and legs. The possible correlated response in the FLM due to yearling weight (YW) selection suggest that this second trait could be used as an indirect selection criterion. Therefore, FLM breeding values and the genetic correlation between FLM and yearling weight (YW) were estimated for 295,031 Nellore animals by fitting a linear-threshold model in a Bayesian approach. A genome-wide association study was performed to identify genomic windows and positional candidate genes associated with FLM. The effects of single nucleotide polymorphisms (SNPs) on FLM phenotypes (affected or unaffected) were estimated using the weighted single-step genomic BLUP method, based on genotypes of 12,537 animals for 461,057 SNPs. Twelve non-overlapping windows of 20 adjacent SNPs explaining more than 1% of the additive genetic variance were selected for candidate gene annotation. Functional and gene prioritization analysis of candidate genes identified six genes (ATG7, EXT1, ITGA1, PPARD, SCUBE3, and SHOX) that may play a role in FLM expression due to their known role in skeletal muscle development, aberrant bone growth, lipid metabolism, intramuscular fat deposition and skeletogenesis. Identifying genes linked to foot and leg malformations enables selective breeding for healthier herds by reducing the occurrence of these conditions. Genetic markers can be used to develop tests that identify carriers of these mutations, assisting breeders in making informed breeding decisions to minimize the incidence of malformations in future generations, resulting in greater productivity and animal welfare

Association of Copy Number Variation at Intron 3 of HMGA2 With Navel Length in Bos indicus

Navel injuries caused by friction against the pasture can promote infection, reproductive problems and costly treatments in beef cattle raised in extensive systems. A haplotype-based genome-wide association study (GWAS) was performed for visual scores of navel length at yearling in Nellore cattle (Bos indicus) using data from 2,016 animals and 503,088 single nucleotide polymorphism (SNP) markers. The strongest signal (p = 1.01 × 10-9) was found on chromosome 5 spanning positions 47.9–48.2 Mbp. This region contains introns 3 and 4 and exons 4 and 5 of the high mobility group AT-hook 2 gene (HMGA2). Further inspection of the region with whole genome sequence data of 21 Nellore bulls revealed correlations between counts of the significant haplotype and copy number gains of a ∼6.2 kbp segment of intron 3 of HMGA2. Analysis of genome sequences from five African B. indicus and four European Bos taurus breeds revealed that the copy number variant (CNV) is indicine-specific. This intronic CNV was then validated through quantitative polymerase chain reaction (qPCR) using Angus animals as copy neutral controls. Importantly, the CNV was not detectable by means of conventional SNP-based GWAS or SNP probe intensity analyses. Given that HMGA2 affects the expression of the insulin-like growth factor 2 gene (IGF2) together with the pleomorphic adenoma gene 1 (PLAG1), and that the latter has been repeatedly shown to be associated with quantitative traits of economic importance in cattle, these findings highlight the emerging role of variants impacting the insulin-like growth factor pathway to cattle breeding

Strategies to improve the efficiency of genomic selection in animal breeding programs

Esta tese compreende quatro diferentes estudos conduzidos a fim de avaliar estratégias alternativas para aumentar a eficiência de seleção genômica (GS) em programas de melhoramento animal. Um primeiro estudo foi desenvolvido com a finalidade de avaliar a performance preditiva de diferentes métodos estatísticos com base na informação de painéis de marcadores densamente distribuídos ao longo do genoma. Cinco diferentes características de uma população real de camundongos foram analisadas. Verificou-se que métodos com grandes diferenças conceituais apresentaram performance preditiva similar em algumas situações, também havendo variação na performance relativa dos métodos em função da característica analisada. O uso de diferentes variáveis resposta (pseudo-fenótipos) para estimação de efeitos de marcadores foi avaliado num segundo estudo, por meio da simulação de uma grande população de bovinos de corte, para a qual predições genômicas foram obtidas usando um procedimento de múltiplas etapas. Houve evidência de que provas desregredidas (dEBV) são mais apropriadas do que valores genéticos preditos (EBV) e médias ajustadas de desempenho da progênie (PYD), tanto para o treinamento de modelos quanto para a validação de predições genômicas. No terceiro estudo, procurou-se avaliar consequências em longo-prazo da aplicação de GS numa população de bovinos de corte sob seleção. Verificou-se grande benefício da aplicação de GS em cenários simulando seleção para características de qualidade de carne e reprodução de fêmeas. Houve evidência de que pode-se esperar maior benefício para GS, quando comparada à seleção por BLUP, no caso de características oligogênicas. Também foi possível inferir que em aplicações de GS, o uso de um critério de seleção em que se atribui maior peso a alelos favoráveis de menor frequência poderia proporcionar...Improvements in production levels and product quality are needed in livestock systems to meet the growing world demand for animal-source foods. Besides this increasing demand, the productive sector must deal with constraints related to competition for land, greenhouse gas emissions and also due to hardening legislation in the fields of environment and animal welfare (FAO, 2011). In this context, animal breeding has played and will continue to play an important role to improve the efficiency of such production systems, especially in terms of competitiveness, safety, sustainability and biodiversity conservation (Harlizius et al., 2004). The main objective of animal breeding programs is to improve the performance of the next generations, through identification and reproduction of the animals with better genetic pool to efficiently produce in a specific environment (herein, superior animals). In the last decades, animal breeders succeeded in achieving this goal, mostly through the application of statistical tools grounded in quantitative genetics theory, what could be called as 'classical animal breeding'. In this case, the traditional prediction of the genetic merit of individuals (estimated breeding values, EBV) is obtained based on information of pedigree and phenotypes (own records and measures on relatives). With the advent of dense molecular marker panels, the implementation and design of breeding programs, especially in dairy cattle, had changed dramatically as a consequence of incorporating this new information to identify superior animals earlier and more precisely. Pioneer simulation studies drew attention of animal breeders to the possibility of making accurate predictions of the genetic merit of individuals by using genotypic information from dense marker panels, a process known as genomic selection (GS) (Nejati-Javaremi et al., 1997; Meuwissen et al., 2001). Other influential work ..

Critérios de seleção para incremento de uniformidade de produção em bovinos de corte

O objetivo deste estudo foi investigar a existência de variabilidade genética aditiva sobre a variância residual do ganho de peso do nascimento à desmama (GND) de bovinos Nelore e as perspectivas de se explorar diferenças entre genótipos para variância residual para a obtenção de maior uniformidade de produção, por meio de seleção. Diferentes abordagens, implementadas em dois passos, foram estudadas: Inicialmente, avaliaram-se três modelos para análise de medidas de dispersão dos resíduos associados às observações de GND da progênie de touros Nelore. O modelo considerado mais promissor foi empregado em estudo subsequente, em que foi investigado o impacto do tamanho de progênie dos touros nas estimativas obtidas para variância aditiva sobre a dispersão residual e estimadores de dispersão em diferentes escalas foram comparados. A confiabilidade de tal abordagem foi verificada por meio de simulação de Monte Carlo. Um último estudo avaliou a possibilidade de se considerarem, simultaneamente, efeitos aditivos e ambientais sobre a variância residual de GND, empregando-se diferentes modelos para análise do logaritmo natural do quadrado do resíduo associado a cada observação. Concluiu-se que, ao se considerar famílias de grande tamanho, seria possível obter predições acuradas do mérito genético dos touros para a variância residual e alguma resposta em termos de uniformidade de produção, sendo a abordagem do último estudo considerada a mais adequada para este fim. Desconsiderar efeitos ambientais sobre a variância residual no segundo passo das análises pode levar a superestimação da variância aditiva sobre a dispersão residual, bem como da resposta esperada à seleçãoThis study was carried out to investigate the existence of genetic variability on residual variance of beef cattle production traits and to evaluate the opportunity for improvement in uniformity of such traits by selecting for lower residual variance. Different two-step approaches were studied to address these questions: Firstly, three models were employed to analyze different measures associated with residual dispersion of weight gain from birth to weaning (GND) in the progeny of Nellore sires. The model that performed best was employed in a subsequent study to access the impact of progeny size on estimates of additive variance for residual dispersion, also aiming to compare dispersion estimators of different scales and to predict selection response in each situation. Reliability of this approach was verified by Monte Carlo simulation. The possibility of considering, simultaneously, additive and environmental effects on residual variance of GND was investigated by analyzing log squared residuals associated with each observation according to different models. It was concluded that, by considering large sire families, accurate estimates of genetic merit of sires for residual variance could be obtained as well as some improvement in uniformity of GND. Analyzing log squared residuals associated with each observation was considered the most promising approach for this task. Ignoring environmental effects at the level of residual variance could lead to inflated estimates of additive variance of residual dispersion, therefore implying in overestimation of response to selectionCoordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP

Genomic regions underlying uniformity of yearling weight in Nellore cattle evaluated under different response variables

Background In livestock, residual variance has been studied because of the interest to improve uniformity of production. Several studies have provided evidence that residual variance is partially under genetic control; however, few investigations have elucidated genes that control it. The aim of this study was to identify genomic regions associated with within-family residual variance of yearling weight (YW; N = 423) in Nellore bulls with high density SNP data, using different response variables. For this, solutions from double hierarchical generalized linear models (DHGLM) were used to provide the response variables, as follows: a DGHLM assuming non-null genetic correlation between mean and residual variance (rmv ≠ 0) to obtain deregressed EBV for mean (dEBVm) and residual variance (dEBVv); and a DHGLM assuming rmv = 0 to obtain two alternative response variables for residual variance, dEBVv_r0 and log-transformed variance of estimated residuals (ln_ σ e ̂ 2 {\upsigma}_{\widehat{\mathrm{e}}}^2 ). Results The dEBVm and dEBVv were highly correlated, resulting in common regions associated with mean and residual variance of YW. However, higher effects on variance than the mean showed that these regions had effects on the variance beyond scale effects. More independent association results between mean and residual variance were obtained when null rmv was assumed. While 13 and 4 single nucleotide polymorphisms (SNPs) showed a strong association (Bayes Factor > 20) with dEBVv and ln_ σ e ̂ 2 {\upsigma}_{\widehat{\mathrm{e}}}^2 , respectively, only suggestive signals were found for dEBVv_r0. All overlapping 1-Mb windows among top 20 between dEBVm and dEBVv were previously associated with growth traits. The potential candidate genes for uniformity are involved in metabolism, stress, inflammatory and immune responses, mineralization, neuronal activity and bone formation. Conclusions It is necessary to use a strategy like assuming null rmv to obtain genomic regions associated with uniformity that are not associated with the mean. Genes involved not only in metabolism, but also stress, inflammatory and immune responses, mineralization, neuronal activity and bone formation were the most promising biological candidates for uniformity of YW. Although no clear evidence of using a specific response variable was found, we recommend consider different response variables to study uniformity to increase evidence on candidate regions and biological mechanisms behind it

Uso combinado de sêmen sexado e acasalamento dirigido sobre uma população de bovinos de corte submetida a seleção: estudo de simulação

Desenvolveu-se um estudo de simulação estocástica com o objetivo de verificar as consequências do uso combinado de acasalamento dirigido e sêmen sexado em uma população de bovinos de corte sob seleção. Simularam-se seis gerações de seleção para três cenários de acasalamento e uso de sêmen sexado. O primeiro cenário foi caracterizado por acasalamento aleatório e uso exclusivo de sêmen convencional. O segundo cenário caracterizou-se pelo uso de acasalamento associativo positivo nas 40% melhores vacas e acasalamento associativo negativo nas demais, sem uso de sêmen sexado. O terceiro cenário seguiu o mesmo procedimento de acasalamento do segundo, combinando-o com uso de sêmen sexado nas vacas submetidas a acasalamento associativo positivo. O acasalamento associativo positivo teve maior impacto no progresso genético que o uso de sêmen sexado, apesar de ter aumentado a incidência de endogamia na população. O uso de acasalamento associativo negativo foi ineficiente em reduzir a variabilidade dos animais destinados ao abate. O uso combinado de acasalmento associativo positivo e sêmen sexado aumentou a produção de animais geneticamente superiores.Stochastic simulation was carried out to access the consequences of combined use of assortative mating and sexed semen in a beef cattle population under selection. Six generations of selection were simulated under three different scenarios of mating strategy and sexed semen use. The first was characterized by random mating and no use of sexed semen. The second was simulated using positive assortative mating (PAM) for the 40% top dams and negative assortative mating (NAM) for the remainder, with no use of sexed semen. The third followed the mating procedure of the second combined with use of sexed semen for dams under positive assortative mating. Positive assortative mating had more impact on the genetic progress than sexed semen, although it increased inbreeding incidence in the population. The combined use of negative assortative mating breeding was not efficient in reducing genetic variability of inferior offspring. The combined use of positive assortative mating and sexed semen improved production of genetically outstanding animals

Genomic regions underlying uniformity of yearling weight in Nellore cattle evaluated under different response variables

Background: In livestock, residual variance has been studied because of the interest to improve uniformity of production. Several studies have provided evidence that residual variance is partially under genetic control; however, few investigations have elucidated genes that control it. The aim of this study was to identify genomic regions associated with within-family residual variance of yearling weight (YW; N=423) in Nellore bulls with high density SNP data, using different response variables. For this, solutions from double hierarchical generalized linear models (DHGLM) were used to provide the response variables, as follows: a DGHLM assuming non-null genetic correlation between mean and residual variance (rmv0) to obtain deregressed EBV for mean (dEBVm) and residual variance (dEBVv); and a DHGLM assuming rmv=0 to obtain two alternative response variables for residual variance, dEBVv_r0 and log-transformed variance of estimated residuals (ln_ σ ě 2 (\upsigma)_(\widehat(\mathrm(e)))^2 ). Results: The dEBVm and dEBVv were highly correlated, resulting in common regions associated with mean and residual variance of YW. However, higher effects on variance than the mean showed that these regions had effects on the variance beyond scale effects. More independent association results between mean and residual variance were obtained when null rmv was assumed. While 13 and 4 single nucleotide polymorphisms (SNPs) showed a strong association (Bayes Factor>20) with dEBVv and ln_ σ ě 2 (\upsigma)_(\widehat(\mathrm(e)))^2 , respectively, only suggestive signals were found for dEBVv_r0. All overlapping 1-Mb windows among top 20 between dEBVm and dEBVv were previously associated with growth traits. The potential candidate genes for uniformity are involved in metabolism, stress, inflammatory and immune responses, mineralization, neuronal activity and bone formation. Conclusions: It is necessary to use a strategy like assuming null rmv to obtain genomic regions associated with uniformity that are not associated with the mean. Genes involved not only in metabolism, but also stress, inflammatory and immune responses, mineralization, neuronal activity and bone formation were the most promising biological candidates for uniformity of YW. Although no clear evidence of using a specific response variable was found, we recommend consider different response variables to study uniformity to increase evidence on candidate regions and biological mechanisms behind it.</p

Genetics and genomics of uniformity and resilience in livestock and aquaculture species: A review

Genetic control of residual variance offers opportunities to increase uniformity and resilience of livestock and aquaculture species. Improving uniformity and resilience of animals will improve health and welfare of animals and lead to more homogenous products. Our aims in this review were to summarize the current models and methods to study genetic control of residual variance, genetic parameters and genomic results for residual variance and discuss future research directions. Typically, the genetic coefficient of variation is high (median = 0.27; range 0–0.86) and the heritability of residual variance is low (median = 0.01; range 0–0.10). Higher heritabilities can be achieved when increasing the number of records per animal. Divergent selection experiments have supported the feasibility of selecting for high or low residual variance. Genomic studies have revealed associations in regions related to stress, including those from the heat shock protein family. Although the number of studies is growing, genetic control of residual variance is still poorly understood, but big data and genomics offer great opportunities.</p