Mehdi Sargolzaei

QMSim: A large scale genome simulator for livestock

SUMMARY QMSim was designed to simulate large-scale genotyping data in multiple and complex livestock pedigrees. The simulation is basically carried out in two steps. In the first step, a historical population is simulated to establish mutation-drift equilibrium, and in the second step, recent population structures are generated, which can be very complex. A wide variety of genome architectures, ranging from infinitesimal model to single-locus model, can be simulated. The program is efficient in terms of computing time and memory requirements. AVAILABILITY Executable versions of QMSim for Windows and Linux are freely available at http://www.aps.uoguelph.ca/~msargol/qmsim/.

A Genome Scan to Detect Quantitative Trait Loci for Economically Important Traits in Holstein Cattle Using Two Methods and a Dense Single Nucleotide Polymorphism Map

Genome scans for detection of bovine quantitative trait loci (QTL) were performed via variance component linkage analysis and linkage disequilibrium single-locus regression (LDRM). Four hundred eighty-four Holstein sires, of which 427 were from 10 grandsire families, were genotyped for 9,919 single nucleotide polymorphisms (SNP) using the Affymetrix MegAllele GeneChip Bovine Mapping 10K SNP array. A hybrid of the grand-daughter and selective genotyping designs was applied. Four thousand eight hundred fifty-six of the 9,919 SNP were located to chromosomes in base-pairs and formed the basis for the analyses. The mean polymorphism information content of the SNP was 0.25. The SNP centimorgan position was interpolated from their base-pair position using a microsatellite framework map. Estimated breeding values were used as observations, and the following traits were analyzed: 305-d lactation milk, fat, and protein yield; somatic cell score; herd life; interval of calving to first service; and age at first service. The variance component linkage analysis detected 102 potential QTL, whereas LDRM analysis found 144 significant SNP associations after accounting for a 5% false discovery rate. Twenty potential QTL and 49 significant SNP associations were in close proximity to QTL cited in the literature. Both methods found significant regions on Bos taurus autosome (BTA) 3, 5, and 16 for milk yield; BTA 14 and 19 for fat yield; BTA 1, 3, 16, and 28 for protein yield; BTA 2 and 13 for calving to first service; and BTA 14 for age at first service. Both approaches were effective in detecting potential QTL with a dense SNP map. The LDRM was well suited for a first genome scan due to its approximately 8 times lower computational demands. Further fine mapping should be applied on the chromosomal regions of interest found in this study.

Genomic imputation and evaluation using high-density Holstein genotypes

Genomic evaluations for 161,341 Holsteins were computed by using 311,725 of 777,962 markers on the Illumina BovineHD Genotyping BeadChip (HD). Initial edits with 1,741 HD genotypes from 5 breeds revealed that 636,967 markers were usable but that half were redundant. Holstein genotypes were from 1,510 animals with HD markers, 82,358 animals with 45,187 (50K) markers, 1,797 animals with 8,031 (8K) markers, 20,177 animals with 6,836 (6K) markers, 52,270 animals with 2,683 (3K) markers, and 3,229 nongenotyped dams (0K) with >90% of haplotypes imputable because they had 4 or more genotyped progeny. The Holstein HD genotypes were from 1,142 US, Canadian, British, and Italian sires, 196 other sires, 138 cows in a US Department of Agriculture research herd (Beltsville, MD), and 34 other females. Percentages of correctly imputed genotypes were tested by applying the programs findhap and FImpute to a simulated chromosome for an earlier population that had only 1,112 animals with HD genotypes and none with 8K genotypes. For each chip, 1% of the genotypes were missing and 0.02% were incorrect initially. After imputation of missing markers with findhap, percentages of genotypes correct were 99.9% from HD, 99.0% from 50K, 94.6% from 6K, 90.5% from 3K, and 93.5% from 0K. With FImpute, 99.96% were correct from HD, 99.3% from 50K, 94.7% from 6K, 91.1% from 3K, and 95.1% from 0K genotypes. Accuracy for the 3K and 6K genotypes further improved by approximately 2 percentage points if imputed first to 50K and then to HD instead of imputing all genotypes directly to HD. Evaluations were tested by using imputed actual genotypes and August 2008 phenotypes to predict deregressed evaluations of US bulls proven after August 2008. For 28 traits tested, the estimated genomic reliability averaged 61.1% when using 311,725 markers vs. 60.7% when using 45,187 markers vs. 29.6% from the traditional parent average. Squared correlations with future data were slightly greater for 16 traits and slightly less for 12 with HD than with 50K evaluations. The observed 0.4 percentage point average increase in reliability was less favorable than the 0.9 expected from simulation but was similar to actual gains from other HD studies. The largest HD and 50K marker effects were often located at very similar positions. The single-breed evaluation tested here and previous single-breed or multibreed evaluations have not produced large gains. Increasing the number of HD genotypes used for imputation above 1,074 did not improve the reliability of Holstein genomic evaluations.

Genome-Wide Association for Growth Traits in Canchim Beef Cattle

Studies are being conducted on the applicability of genomic data to improve the accuracy of the selection process in livestock, and genome-wide association studies (GWAS) provide valuable information to enhance the understanding on the genetics of complex traits. The aim of this study was to identify genomic regions and genes that play roles in birth weight (BW), weaning weight adjusted for 210 days of age (WW), and long-yearling weight adjusted for 420 days of age (LYW) in Canchim cattle. GWAS were performed by means of the Generalized Quasi-Likelihood Score (GQLS) method using genotypes from the BovineHD BeadChip and estimated breeding values for BW, WW, and LYW. Data consisted of 285 animals from the Canchim breed and 114 from the MA genetic group (derived from crossings between Charolais sires and ½ Canchim + ½ Zebu dams). After applying a false discovery rate correction at a 10% significance level, a total of 4, 12, and 10 SNPs were significantly associated with BW, WW, and LYW, respectively. These SNPs were surveyed to their corresponding genes or to surrounding genes within a distance of 250 kb. The genes DPP6 (dipeptidyl-peptidase 6) and CLEC3B (C-type lectin domain family 3 member B) were highlighted, considering its functions on the development of the brain and skeletal system, respectively. The GQLS method identified regions on chromosome associated with birth weight, weaning weight, and long-yearling weight in Canchim and MA animals. New candidate regions for body weight traits were detected and some of them have interesting biological functions, of which most have not been previously reported. The observation of QTL reports for body weight traits, covering areas surrounding the genes (SNPs) herein identified provides more evidence for these associations. Future studies targeting these areas could provide further knowledge to uncover the genetic architecture underlying growth traits in Canchim cattle.

Mixed Model Association Mapping for Fusarium Head Blight Resistance in Tunisian-Derived Durum Wheat Populations

Sources of resistance to Fusarium head blight (FHB) in wheat are mostly restricted to Chinese hexaploid genotypes. The effort to incorporate the resistance from hexaploid wheat or wild relatives to cultivated durum wheat (Triticum turgidum L. var. durum Desf.) have not been successful in providing resistance to the level of the donor parents. In this study, we used 171 BC1F6 and 169 BC1F7 lines derived from crossing of four Tunisian tetraploid sources of resistance (Tun7, Tun18, Tun34, Tun36) with durum cultivars ‘Ben,’ ‘Maier,’ ‘Lebsock,’ and ‘Mountrail’ for association studies. The Tun18 and Tun7 FHB resistances were found to be comparable to the best hexaploid wheat sources. A new significant QTL for FHB resistance was identified on the long arm of chromosome 5B (Qfhs.ndsu-5BL) with both association and classical QTL mapping analysis. Linkage disequilibrium (LD) blocks extending up to 40 cM were evident in these populations. The linear mixed model considering the structure (Q or P) and the kinship matrix (KT) estimated by restricted maximum likelihood (REML) was identified as the best for association studies in a mixture of wheat populations from a breeding program. The results of association mapping analysis also demonstrated a region on the short arm of chromosome 3B as potentially linked to FHB resistance. This region is in proximity of major FHB resistance gene fhb1 reported in hexaploid wheat. A possibility of having susceptibility or suppressor of resistance gene(s) on durum wheat chromosome 2A was further confirmed in this material, explaining the problem in developing resistant genotypes without counter selection against this region.

Rates of inbreeding and genetic diversity in Canadian Holstein and Jersey cattle

The accumulation of inbreeding and the loss of genetic diversity is a potential problem in the modern dairy cattle breeds. Therefore, the purpose of this study was to analyze the pedigrees of Canadian Holstein and Jersey cattle to estimate the past and current rates of inbreeding and genetic diversity, and to identify the main causes of diversity loss. Completeness and depth of the pedigrees were good for both breeds. For Holsteins, the average rates of inbreeding per generation showed a decreasing trend in recent years when compared with the 1990s. The estimated current effective population size was about 115 for Holsteins and is not expected to significantly change in the near future if generation intervals stay at current value, as rates of increase in inbreeding and coancestry showed decreasing trends. For Jerseys, the estimated effective population size was about 55 and it is expected to decrease in the near future due to the observed increasing rates of coancestry and inbreeding. Ancestors with the highest marginal genetic contributions to the gene pool in current years and with the highest contributions to inbreeding were identified. The 2 most heavily used and represented ancestors in the Holstein pedigree (i.e., Round Oak Rag Apple Elevation and his son Hanoverhill Starbuck), accounted for 30% of inbreeding. Analyses revealed that the most important cause of genetic diversity loss in both breeds was genetic drift accumulated over nonfounder generations, which occurred due to small effective population size. Therefore, a need exists in both breeds, particularly in Jerseys, for managing selection and mating decisions to control future coancestry and inbreeding, which would lead to better handling of the effective population size.

Linkage disequilibrium in Angus, Charolais, and Crossbred beef cattle

Linkage disequilibrium (LD) and the persistence of its phase across populations are important for genomic selection as well as fine scale mapping of quantitative trait loci (QTL). However, knowledge of LD in beef cattle, as well as the persistence of LD phase between crossbreds (C) and purebreds, is limited. The objective of this study was to understand the patterns of LD in Angus (AN), Charolais (CH), and C beef cattle based on 31,073, 32,088, and 33,286 SNP in each population, respectively. Amount of LD decreased rapidly from 0.29 to 0.23 to 0.19 in AN, 0.22 to 0.16 to 0.12 in CH, 0.21 to 0.15 to 0.11 in C, when the distance range between markers changed from 0–30 kb to 30–70 kb and then to 70–100 kb, respectively. Breeds and chromosomes had significant effects (P < 0.001) on LD decay. There was significant interaction between breeds and chromosomes (P < 0.001). Correlations of LD phase were high between C and AN (0.84), C and CH (0.81), as well as between AN and CH (0.77) for distances less than or equal to 70 kb. These dropped when the distance increased. Estimated effective population sizes for AN and CH were 207 and 285, respectively, for 10 generations ago. Given a useful LD of at least 0.3 between pairs of SNPs, the LD phase between any pair of the three breed groups was highly persistent. The current SNP density would allow the capture of approximately 49% of useful LD between SNP and marker QTL in AN, and 38% in CH. A higher density SNP panel or redesign of the current panel is needed to achieve more of useful LD for the purpose of genomic selection beef cattle.

Linkage disequilibrium and haplotype block structure in a composite beef cattle breed.

BackgroundThe development of linkage disequilibrium (LD) maps and the characterization of haplotype block structure at the population level are useful parameters for guiding genome wide association (GWA) studies, and for understanding the nature of non-linear association between phenotypes and genes. The elucidation of haplotype block structure can reduce the information of several single nucleotide polymorphisms (SNP) into the information of a haplotype block, reducing the number of SNPs in a coherent way for consideration in GWA and genomic selection studies.ResultsThe maximum average LD, measured by r2 varied between 0.33 to 0.40 at a distance of < 2.5 kb, and the minimum average values of r2 varied between 0.05 to 0.07 at distances ranging from 400 to 500 kb, clearly showing that the average r2 reduced with the increase in SNP pair distances. The persistence of LD phase showed higher values at shorter genomic distances, decreasing with the increase in physical distance, varying from 0.96 at a distance of < 2.5 kb to 0.66 at a distance from 400 to 500 kb. A total of 78% of all SNPs were clustered into haplotype blocks, covering 1,57 Mb of the total autosomal genome size.ConclusionsThis study presented the first high density linkage disequilibrium map and haplotype block structure for a composite beef cattle population, and indicates that the high density SNP panel over 700 k can be used for genomic selection implementation and GWA studies for Canchim beef cattle.

Genome-wide association analyses for growth and feed efficiency traits in beef cattle.

A genome-wide association study using the Illumina 50K BeadChip included 38,745 SNP on 29 BTA analyzed on 751 animals, including 33 purebreds and 718 crossbred cattle. Genotypes and 6 production traits: birth weight (BWT), weaning weight (WWT), ADG, DMI, midtest metabolic BW (MMWT), and residual feed intake (RFI), were used to estimate effects of individual SNP on the traits. At the genome-wide level false discovery rate (FDR < 10%), 41 and 5 SNP were found significantly associated with BWT and WWT, respectively. Thirty-three of them were located on BTA6. At a less stringent significance level (P < 0.001), 277 and 27 SNP were in association with single traits and multiple traits, respectively. Seventy-three SNP on BTA6 and were mostly associated with BW-related traits, and heavily located around 30 to 50Mb. Markers that significantly affected multiple traits appeared to impact them in same direction. In terms of the size of SNP effect, the significant SNP (P < 0.001) explained between 0.26 and 8.06% of the phenotypic variation in the traits. Pairs of traits with low genetic correlation, such as ADG vs. RFI or DMI vs. BWT, appeared to be controlled by 2 groups of SNP; 1 of them affected the traits in same direction, the other worked in opposite direction. This study provides useful information to further assist the identification of chromosome regions and subsequently genes affecting growth and feed efficiency traits in beef cattle.

Accuracy of genomic selection in simulated populations mimicking the extent of linkage disequilibrium in beef cattle

BackgroundThe success of genomic selection depends mainly on the extent of linkage disequilibrium (LD) between markers and quantitative trait loci (QTL), the number of animals in the training set (TS) and the heritability (h2) of the trait. The extent of LD depends on the genetic structure of the population and the density of markers. The aim of this study was to calculate accuracy of direct genomic estimated breeding values (DGEBV) using best linear unbiased genomic prediction (GBLUP) for different marker densities, heritabilities and sizes of the TS in simulated populations that mimicked previously reported extent and pattern of LD in beef cattle.ResultsThe accuracy of DGEBV increased significantly (p < 0.05) with the increase in the number of bulls in the TS (480, 960 or 1920), trait h2 (0.10, 0.25 or 0.40) and marker densities (40 k or 800 k). Increasing the number of animals in the TS by 4-fold and using their phenotypes to estimate marker effects was not sufficient to maintain or increase the accuracy of DGEBV obtained using estimated breeding values (EBVs) when the trait h2 was lower than 0.40 for both marker densities. Comparing to expected accuracies of parent average (PA), the gains by using DGEBV would be of 27%, 13% and 10% for trait h2 equal to 0.10, 0.25 and 0.40, respectively, considering the scenario with 40 k markers and 1920 bulls in TS.ConclusionsAs reported in dairy cattle, the size of the TS and the extent of LD have major impact on the accuracy of DGEBV. Based on the findings of this simulation study, large TS, as well as dense marker panels, aiming to increase the level of LD between markers and QTL, will likely be needed in beef cattle for successful implementation of genomic selection.