Papers by Ignacio Aguilar
Animals, 2021
Intense selection for milk yield has increased environmental sensitivity in animals, and currentl... more Intense selection for milk yield has increased environmental sensitivity in animals, and currently, heat stress is an expensive problem in dairy farming. The objectives were to identify the best model for characterizing environmental sensitivity in Holstein cattle, using the test-day milk yield (TDMY) combined with the temperature–humidity index (THI), and identify sires genetically superior for heat-stress (HS) tolerance and milk yield, through random regression. The data comprised 94,549 TDMYs of 11,294 first-parity Holstein cows in Brazil, collected from 1997 to 2013. The yield data were fitted to Legendre orthogonal polynomials, linear splines and the Wilmink function. The THI (the average of two days before the dairy control) was used as an environmental gradient. An animal model that fitted production using a Legendre polynomials of quartic order for the days in milk and quadratic equations for the THI presented a better quality of fit (Akaike’s information criterion (AIC) and...
Journal of Animal Science, 2015
Predictive ability of genomic EBV when using single-step genomic BLUP 1 (ssGBLUP) in Angus cattle... more Predictive ability of genomic EBV when using single-step genomic BLUP 1 (ssGBLUP) in Angus cattle was investigated. Over 6 million records were available on birth 2 weight (BW) and weaning weight (WW), almost 3.4 million on post-weaning gain (PWG), and 3 over 1.3 million on calving ease (CE). Genomic information was available on at most 51,883 4 animals, which included high and low EBV accuracy animals. Traditional EBV was computed 5 by BLUP and genomic EBV by ssGBLUP and indirect prediction based on SNP effects derived 6 from ssGBLUP; SNP effects were calculated based on the following reference populations: 7 ref_2k (high EBV accuracy sires and cows), ref_8k (ref_2k, plus all genotyped ancestors of 8 validation animals), and ref_33k (ref_8k, plus all remaining genotyped animals not in the 9 validation). Indirect prediction was obtained as direct genomic value (DGV) or as an index of 10 DGV and parent average (PA). Additionally, runs with ssGBLUP used the inverse of the 11 genomic relationship matrix calculated by an algorithm for proven and young animals (APY) 12 that uses recursions on a small subset of reference animals. An extra reference subset included 13 3872 genotyped parents of genotyped animals (ref_4k). Cross-validation was used to assess 14 predictive ability on a validation population of 18,721 animals born in 2013. Computations for 15 growth traits used multiple-trait linear model, and for CE, a bivariate CE-BW threshold-linear 16 model. With BLUP, predictivities were 0.29, 0.34, 0.23, and 0.12 for BW, WW, PWG, and CE, 17 respectively. With ssGBLUP and ref_2k (ref_33k), predictivities were 0.34, 0.35, 0.27, and 0.13 18 (0.39, 0.38, 0.29, and 0.13), respectively. Low predictivity for CE was due to low incidence rate 19 of difficult calving. Indirect predictions with ref_33k were as accurate as with full ssGBLUP. 20 Using APY and recursions on ref_4k (ref_8k) gave 88% (97%) gains of full ssGBLUP. 21 Genomic evaluation in beef cattle with ssGBLUP is feasible while keeping the models (maternal, 22 multiple trait, threshold) already used in regular BLUP. Gains in predictivity are dependent on 23
A single-step GBLUP (ssGBLUP) is a procedure that calculates GEBVs based on combined pedigree, ge... more A single-step GBLUP (ssGBLUP) is a procedure that calculates GEBVs based on combined pedigree, genomic and phenotypic information. The procedure achieves these goals by blending traditional pedigree relationships with those derived from genetic markers. In practical applications involving national data sets in cattle, pigs, chicken and sheep, ssGBLUP exhibited superior accuracy with simplicity of application and inexpensive computing. However, the applications pointed to general problems of genomic predictions where GEBV of particular group of animals may be biased upwards or downwards depending on properties of the genomic relationship matrix (GRM). Biases are minimized or removed when such a matrix accounts for admixed populations and the genetic distance of the genotyped population to the base population. ssGBLUP can be modified for genome-wide association analysis (GWAS). For GWAS, GEBVs are computed initially using a GRM derived assuming equal weight per SNP. Then GEBVs are con...
Recent use of genomic (marker-based) relationships shows that relationships exist within and acro... more Recent use of genomic (marker-based) relationships shows that relationships exist within and across base population (breeds or lines). However, current treatment of pedigree relationships is unable to consider relationships within or across base populations, although such relationships must exist due to finite size of the ancestral population and connections between populations. This complicates the conciliation of both approaches and, in particular, combining pedigree with genomic relationships. We present a coherent theoretical framework to consider base population in pedigree relationships. We suggest a conceptual framework that considers each ancestral population as a finite-sized pool of gametes. This generates across-individual relationships and contrasts with the classical view which each population is considered as an infinite, unrelated pool. Several ancestral populations may be connected and therefore related. Each ancestral population can be represented as a "metafounder," a pseudo-individual included as founder of the pedigree and similar to an "unknown parent group." Metafounders have self-and across relationships according to a set of parameters, which measure ancestral relationships, i.e., homozygozities within populations and relationships across populations. These parameters can be estimated from existing pedigree and marker genotypes using maximum likelihood or a method based on summary statistics, for arbitrarily complex pedigrees. Equivalences of genetic variance and variance components between the classical and this new parameterization are shown. Segregation variance on crosses of populations is modeled. Efficient algorithms for computation of relationship matrices, their inverses, and inbreeding coefficients are presented. Use of metafounders leads to compatibility of genomic and pedigree relationship matrices and to simple computing algorithms. Examples and code are given.
This study aimed to compare results of genome-wide associations obtained from various methodologi... more This study aimed to compare results of genome-wide associations obtained from various methodologies for GWAS when applied to two lines of broiler chicken. Each line contained >250k birds with up to 3 traits and ~5k genotypes with a 60k SNP chip. Methods included single-step GWAS, single marker model and BayesB. Manhattan plots were based on variances of 20-SNP segments, as shorter segments produced noisy plots. Only a few segments explained >1% of the additive variance. One segment explained >20% variance in BayesB but 3% with ssGWAS and <1% with a single marker model. In two lines, no major segment overlapped for any trait. When analyses used slices of generations (1-3,2-4,3-5,1-5), variances for the same segment varied greatly. The plots were more distinct with a new data set that included >16k genotypes, but no segment explained >1.5% of the variance. Strength of associations strongly depends on methodologies and details of implementations.
Abstract Text: The objective of this study was to compare a conventional genomic model (GBLUP) an... more Abstract Text: The objective of this study was to compare a conventional genomic model (GBLUP) and its extension to a linear reaction norm model (GLRNM) specifying genotype by environment interaction (G*E) for tick resistance in Brazilian cattle. Tick counts (TC) from 4,363 Hereford and Braford cattle from 146 contemporary groups (CG) were available of which 3,591 animals had BovineSNP50 Illumina v2 BeadChip genotypes. The reaction norm covariate was based on CG estimates of TC from a first-step model. Analysis was conducted based on adapting the single step GBLUP/REML procedure. Five-fold cross validation based on K-means and random partitioning was used to compare the fit of the two models. Cross validation correlations were strong and not significantly different between models for either partitioning strategy. Nevertheless, it seems apparent that G*E for tick infestation exists and can captured by GLRNM models. Keywords: Cross validation Single-step Tick counts
Resumen. El consumo de alimento y características de calidad de canal no han podido ser incluidas... more Resumen. El consumo de alimento y características de calidad de canal no han podido ser incluidas en programas de mejora genética a pesar de su relevancia económica debido a la dificultad y alto costo de medición. La selección genómica surge como una oportunidad para mejorar estas características. El objetivo de este proyecto es el establecimiento de una población de entrenamiento conformada por 1000 animales entre toros y novillos Hereford. Esta población será genotipada con paneles de miles de marcadores moleculares y contará con registros de consumo individual de alimento y características de calidad de canal en el caso de novillos. Integrando ésta información, será posible generar ecuaciones de predicción que serán usadas en la estimación del valor genómico de cada animal para cada característica, incluso de los que no disponen de registros. Análisis preliminares demuestran la existencia de variación individual para consumo residual de alimento, lo que alienta a pensar en la pos...
Introducción La determinación o confirmación de las relaciones de parentesco entre animales es im... more Introducción La determinación o confirmación de las relaciones de parentesco entre animales es importante desde el punto de vista del mejoramiento genético porque los errores en la genealogía tienen un efecto negativo en la tasa de progreso genético (Van Vleck, 1970; Israel and Weller, 2000), y además por permitir la asignación de paternidades en sistemas de apareamiento con múltiples toros (Van Eenennaam et al., 2007). Ya en la década de 1990 se diseñaron paneles de microsatélites como herramientas moleculares para la determinación de parentesco, siendo el método oficial avalado por la Asociación Internacional para la Genética Animal (ISAG, por su sigla en inglés). Más recientemente, la identificación de numerosos SNP distribuidos en todo el genoma y el salto tecnológico dado por el genotipado masivo de SNP (del inglés, Single Nucleotide Polymorphism), con tiempos y costos decrecientes, han hecho posible el uso de estos marcadores para asignar o verificar parentesco. Marcadores del...
Abstract Text: Datasets of US and Israeli Holsteins, and pigs from PIC were used to evaluate the ... more Abstract Text: Datasets of US and Israeli Holsteins, and pigs from PIC were used to evaluate the impact of different number of generations on ability to predict GEBV of young genotyped animals. The inclusion of only two generations of ancestors (A2) or all ancestors (Af) was also evaluated. A total of 34,506 US and 1,305 Israeli Holsteins bulls, and 5,236 pigs were genotyped. The evaluations were computed by traditional BLUP and single-step GBLUP, with respective computing performance recorded. For the two Holstein datasets, coefficients of determination and regression of deregressed evaluations from a full dataset with records up to 2011 on EBV or GEBV from the reduced dataset (up to 2006 for Israeli and 2007 for US) and truncations were computed. The thresholds for old data deletion were based on generation intervals of 5 years. For the PIC dataset, correlations between corrected phenotypes and EBV or GEBV were used to evaluate the predictive ability on young animals born in 2010 ...
Abstract Text: Our objective was to conduct a genome-wide association study on cow mortality and ... more Abstract Text: Our objective was to conduct a genome-wide association study on cow mortality and 305-d milk yield for three lactations and determine if there were differences in the genetic architecture in three US regions. Genomic EBV of mortality and milk yield were estimated with a single-step genomic BLUP using a threshold-linear model. Genomic information was included on 34,506 bulls. Data consisted of the entire US data and three regions SE: southeast, SW: southwest, and NE: northeast for first three lactation cows calving from 1999 to 2008. As expected, a segment on chromosome 14 was significantly associated with milk production in all regions. Chromosome 14 showed a strong association with the first parity mortality for the entire US, with NE showing a strong association for all three parities. Within SE and SW regions, no single region stood out for mortality on chromosomes for three parities. Keywords: GWAS Cow mortality Region
Abstract Text: The purpose of this study was to determine whether the top SNP windows that explai... more Abstract Text: The purpose of this study was to determine whether the top SNP windows that explain the most variance are stable over multiple generations of selection in a GWAS analysis using single-step GBLUP. Phenotypes were available for five generations of a pure line of broiler chicken for body weight, breast meat, and leg score. Pedigrees included 297,017 animals, of which 294,632 had phenotypic records over 5 generations. Genotypes of 57,635 SNP were available for 4,922 animals. After quality checks, 41,036 SNP and 4,866 animals remained in the genomic file. SNP effects were calculated by a GWAS type analysis using single-step GBLUP approach. In each run, the generations were grouped from 1-3, 2-4, 3-5, and 1-5. The evaluation model included sex and contemporary group as fixed effects, animal additive and maternal permanent environmental as random. In GWAS by single-step GBLUP, genomic breeding values (GEBV) are converted to SNP effects. Variances of SNP effects were derived ...
Genetics, selection, evolution : GSE, 2015
As more and more genotypes become available, accuracy of genomic evaluations can potentially incr... more As more and more genotypes become available, accuracy of genomic evaluations can potentially increase. However, the impact of genotype data on accuracy depends on the structure of the genotyped cohort. For populations such as dairy cattle, the greatest benefit has come from genotyping sires with high accuracy, whereas the benefit due to adding genotypes from cows was smaller. In broiler chicken breeding programs, males have less progeny than dairy bulls, females have more progeny than dairy cows, and most production traits are recorded for both sexes. Consequently, genotyping both sexes in broiler chickens may be more advantageous than in dairy cattle. We studied the contribution of genotypes from males and females using a real dataset with genotypes on 15 723 broiler chickens. Genomic evaluations used three training sets that included only males (4648), only females (8100), and both sexes (12 748). Realized accuracies of genomic estimated breeding values (GEBV) were used to evaluat...
Journal of dairy science, 2015
The purpose of this study was to evaluate the accuracy of genomic selection in single-step genomi... more The purpose of this study was to evaluate the accuracy of genomic selection in single-step genomic BLUP (ssGBLUP) when the inverse of the genomic relationship matrix (G) is derived by the "algorithm for proven and young animals" (APY). This algorithm implements genomic recursions on a subset of "proven" animals. Only a relationship matrix for animals treated as "proven" needs to be inverted, and the extra costs of adding animals treated as "young" are linear. Analyses involved 10,102,702 final scores on 6,930,618 Holstein cows. Final score, which is a composite of type traits, is popular trait in the United States and was easily available for this study. A total of 100,000 animals with genotypes were used in the analyses and included 23,000 sires (16,000 with >5 progeny), 27,000 cows, and 50,000 young animals. Genomic EBV (GEBV) were calculated with a regular inverse of G, and with the G inverse approximated by APY. Animals in the proven su...
Journal of animal breeding and genetics = Zeitschrift fur Tierzuchtung und Zuchtungsbiologie, Jan 10, 2015
The purpose of this study was to examine accuracy of genomic selection via single-step genomic BL... more The purpose of this study was to examine accuracy of genomic selection via single-step genomic BLUP (ssGBLUP) when the direct inverse of the genomic relationship matrix (G) is replaced by an approximation of G(-1) based on recursions for young genotyped animals conditioned on a subset of proven animals, termed algorithm for proven and young animals (APY). With the efficient implementation, this algorithm has a cubic cost with proven animals and linear with young animals. Ten duplicate data sets mimicking a dairy cattle population were simulated. In a first scenario, genomic information for 20k genotyped bulls, divided in 7k proven and 13k young bulls, was generated for each replicate. In a second scenario, 5k genotyped cows with phenotypes were included in the analysis as young animals. Accuracies (average for the 10 replicates) in regular EBV were 0.72 and 0.34 for proven and young animals, respectively. When genomic information was included, they increased to 0.75 and 0.50. No dif...
The objective of this study was to examine the feasibility of using random regression, spline (RR... more The objective of this study was to examine the feasibility of using random regression, spline (RR-spline) models for fitting growth traits in a multibreed beef cattle population. To meet the objective, the evaluation results from the RR-spline model were compared to the multi-trait (MT) model when both were fit to a data set (1.8 million records and 1.1 million animals)
Plant and Animal Genome XX Conference (January 14 …, 2012
... W593 Tools for Genomic Analyses Using Single-Step Methodology. ... The last modifications all... more ... W593 Tools for Genomic Analyses Using Single-Step Methodology. ... The last modifications allows for differential weightings of SNP. For GWAS, GEBVs are computed initially using a genomic relationship matrix (GRM) derived assuming equal weight per SNP. ...
Journal of dairy science, 2010
The first national single-step, full-information (phenotype, pedigree, and marker genotype) genet... more The first national single-step, full-information (phenotype, pedigree, and marker genotype) genetic evaluation was developed for final score of US Holsteins. Data included final scores recorded from 1955 to 2009 for 6,232,548 Holsteins cows. BovineSNP50 (Illumina, San Diego, CA) genotypes from the Cooperative Dairy DNA Repository (Beltsville, MD) were available for 6,508 bulls. Three analyses used a repeatability animal model as currently used for the national US evaluation. The first 2 analyses used final scores recorded up to 2004. The first analysis used only a pedigree-based relationship matrix. The second analysis used a relationship matrix based on both pedigree and genomic information (single-step approach). The third analysis used the complete data set and only the pedigree-based relationship matrix. The fourth analysis used predictions from the first analysis (final scores up to 2004 and only a pedigree-based relationship matrix) and prediction using a genomic based matrix ...
athens 30602 † instituto Nacional de investigación agropecuaria, las Brujas 90200, uruguay aBStra... more athens 30602 † instituto Nacional de investigación agropecuaria, las Brujas 90200, uruguay aBStraCt Data included 585,119 test-day records for milk, fat, and protein yields from the first, second, and third parities of 38,608 Holsteins in Georgia. Daily temperature-humidity indexes (THI) were available from public weather stations. Models included a repeatability test-day model with a random regression on a function of THI and a test-day random regression model using linear splines with knots at 5, 50, 200, and 305 d in milk and a function of THI. Random effects were additive genetic and permanent environmental in the repeatability model and additive genetic, permanent environmental, and herd year in the random regression model. Additionally, models included fixed effects for herd test day, calving age, milking frequency, and lactation stage. Phenotypic variance increased by 50 to 60% from the first to second parity for all yield traits with the repeatability model and by 12 to 15% from the second to third parity. General additive genetic variance increased by 25 to 35% from the first to second parity for all yield traits but decreased slightly from the second to third parity for milk and protein yields. Genetic variance for heat tolerance doubled from the first to second parity and increased by 20 to 100% from the second to third parity. Genetic correlations among general additive effects were lowest between the first and second parities (0.84 to 0.88) and were highest between the second and third parities (0.96 to 0.98). Genetic correlations among parities for the effect of heat tolerance ranged from 0.56 to 0.79. Genetic correlations between general and heat-tolerance effects across parities and yield traits ranged from −0.30 to −0.50. With the random regression model, genetic variance for heat tolerance for milk yield was approximately one-half that of the repeatability model. For milk yield, the most negative genetic correlation (approximately −0.45) between general and heat-tolerance effects was between 50 and 200 d in milk for the first parity and between 200 and 305 d in milk for the second and third parities. The genetic variance of heat tolerance increased substantially from the first to third parity. Genetic estimates of heat tolerance may be inflated with the repeatability model because of timing of lactations to avoid peak yield during hot seasons.
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Papers by Ignacio Aguilar