Genetic structure analysis in several populations of cattle using SNP genotypes.

Parameters such as effective population size (Ne), runs of homozygosity (ROH), and inbreeding based on ROH (FROH) can give new insight into the level of genetic diversity for the population under selection. This research aimed to measure the extent of linkage disequilibrium (LD), effective population size (Ne), Haplotype Block Structure, and runs of homozygosity (ROHs) in several populations of cattle using SNP genotypes. In this study, that the average r2 decreased with the increasing distance of SNP pairs. A general decrease in Ne can be seen for all four populations, indicating a loss of genetic diversity. The Iranian Holstein had the lowest level of genomic inbreeding at an ROH of 1, 5, 10 Mb, while the French Holstein had the highest. The maximum number of ROH is seen at a distance of less than 1 Mb, and the lowest number of ROH is seen at a distance of 10 Mb. The number of ROH decreases with increasing distance due to the increased recombination rate. This is a concern as an increase in inbreeding leads to a reduction in the effective population size, which was also evident in the study populations.

Genome-wide scan for selective sweeps identifies novel loci associated with resistance to mastitis in German Holstein cattle.

Domestication and selection significantly changed phenotypic and behavioural traits in modern domestic animals. In this study, to identify the genomic regions associated with mastitis, genomic data of German Holstein dairy cattle were analysed. The samples were genotyped using the Bovine 50 K SNP chip. For each defined healthy and sick group, 133 samples from 13,276 genotyped dairy cows were selected based on mastitis random residual effects. Grouping was done to infer selection signatures based on XP-EHH statistic. The results revealed that for the top 0.01 percentile of the obtained XP-EHH values, five genomic regions on chromosomes 8, 11, 12, 14 and 26 of the control group, and four regions on chromosomes 3, 4 (two regions) and 22 of the case group, have been under selection. Also, consideration of the top 0.1 percentile of the XP-EHH values, clarified 21 and 15 selective sweeps in the control and case group, respectively. This study identified some genomic regions containing potential candidate genes associated with resistance and susceptibility to mastitis, immune system and inflammation, milk traits, udder morphology and different types of cancers. In addition, these regions overlap with some quantitative trait loci linked to clinical mastitis, immunoglobulin levels, somatic cell score, udder traits, milk fat and protein, milk yield, milking speed and veterinary treatments. It is noteworthy that we found two regions in the healthy group (on chromosomes 12 and 14) with strong signals, which were not described previously. It is likely that future research could link these identified genomic regions to mastitis. The results of the current study contribute to the identification of causal mutations, genomic regions and genes affecting mastitis incidence in dairy cows.

Hitchhiking Mapping of Candidate Regions Associated with Fat Deposition in Iranian Thin and Fat Tail Sheep Breeds Suggests New Insights into Molecular Aspects of Fat Tail Selection.

The fat tail is a phenotype that divides indigenous Iranian sheep genetic resources into two major groups. The objective of the present study is to refine the map location of candidate regions associated with fat deposition, obtained via two separate whole genome scans contrasting thin and fat tail breeds, and to determine the nature of the selection occurring in these regions using a hitchhiking approach. Zel (thin tail) and Lori-Bakhtiari (fat tail) breed samples that had previously been run on the Illumina Ovine 50 k BeadChip, were genotyped with a denser set of SNPs in the three candidate regions using a Sequenom Mass ARRAY platform. Statistical tests were then performed using different and complementary methods based on either site frequency (FST and Median homozygosity) or haplotype (iHS and XP-EHH). The results from candidate regions on chromosome 5 and X revealed clear evidence of selection with the derived haplotypes that was consistent with selection to near fixation for the haplotypes affecting fat tail size in the fat tail breed. An analysis of the candidate region on chromosome 7 indicated that selection differentiated the beneficial alleles between breeds and homozygosity has increased in the thin tail breed which also had the ancestral haplotype. These results enabled us to confirm the signature of selection in these regions and refine the critical intervals from 113 kb, 201 kb, and 2831 kb to 28 kb, 142 kb, and 1006 kb on chromosome 5, 7, and X respectively. These regions contain several genes associated with fat metabolism or developmental processes consisting of TCF7 and PPP2CA (OAR5), PTGDR and NID2 (OAR7), AR, EBP, CACNA1F, HSD17B10,SLC35A2, BMP15, WDR13, and RBM3 (OAR X), and each of which could potentially be the actual target of selection. The study of core haplotypes alleles in our regions of interest also supported the hypothesis that the first domesticated sheep were thin tailed, and that fat tail animals were developed later. Overall, our results provide a comprehensive assessment of how and where selection has affected the patterns of variation in candidate regions associated with fat deposition in thin and fat tail sheep breeds.

Genomic comparisons of Persian Kurdish, Persian Arabian and American Thoroughbred horse populations.

The present research aimed to characterize the Persian Kurdish horse population relative to the Persian Arabian and American Thoroughbred populations using genome-wide SNP data. Fifty-eight Kurdish, 38 Persian Arabian and 83 Thoroughbred horses were genotyped across 670,796 markers. After quality control and pruning to eliminate linkage disequilibrium between loci which resulted in 13,554 SNPs in 52 Kurdish, 24 Persian Arabian and 58 Thoroughbred horses, the Kurdish horses were generally distinguished from the Persian Arabian samples by Principal Component Analyses, cluster analyses and calculation of pairwise FST. Both Persian breeds were discriminated from the Thoroughbred. Pairwise FST between the two Persian samples (0.013) was significantly greater than zero and several fold less than those found between the Thoroughbred and Kurdish (0.052) or Thoroughbred and Persian Arabian (0.057). Cluster analysis assuming three genetic clusters assigned the Kurdish horse and Thoroughbred to distinct clusters (0.942 in cluster 2 and 0.953 in cluster 3 respectively); the Persian Arabian was not in a distinct cluster (0.519 in cluster 1), demonstrating shared ancestry or recent admixture with the Kurdish breed. Diversity as quantified by expected heterozygosity was the highest in the Kurdish horse (0.342), followed by the Persian Arabian (0.328) and the Thoroughbred (0.326). Analysis of Molecular Variance showed that 4.47% of the genetic variation was present among populations (P<0.001). Population-specific inbreeding indices (FIS) were not significantly different from zero in any of the populations. Analysis of individual inbreeding based on runs of homozygosity using a larger SNP set suggested greater diversity in both the Kurdish and Persian Arabian than in the Thoroughbred. These results have implications for developing conservation strategies to achieve sound breeding goals while maintaining genetic diversity.

Genome-wide association studies for methane emission and ruminal volatile fatty acids using Holstein cattle sequence data.

BACKGROUND: Methane emission by ruminants has contributed considerably to the global warming and understanding the genomic architecture of methane production may help livestock producers to reduce the methane emission from the livestock production system. The goal of our study was to identify genomic regions affecting the predicted methane emission (PME) from volatile fatty acids (VFAs) indicators and VFA traits using imputed whole-genome sequence data in Iranian Holstein cattle. RESULTS: Based on the significant-association threshold (p < 5 × 10- 8), 33 single nucleotide polymorphisms (SNPs) were detected for PME per kg milk (n = 2), PME per kg fat (n = 14), and valeric acid (n = 17). Besides, 69 genes were identified for valeric acid (n = 18), PME per kg milk (n = 4) and PME per kg fat (n = 47) that were located within 1 Mb of significant SNPs. Based on the gene ontology (GO) term analysis, six promising candidate genes were significantly clustered in organelle organization (GO:0004984, p = 3.9 × 10- 2) for valeric acid, and 17 candidate genes significantly clustered in olfactory receptors activity (GO:0004984, p = 4 × 10- 10) for PME traits. Annotation results revealed 31 quantitative trait loci (QTLs) for milk yield and its components, body weight, and residual feed intake within 1 Mb of significant SNPs. CONCLUSIONS: Our results identified 33 SNPs associated with PME and valeric acid traits, as well as 17 olfactory receptors activity genes for PME traits related to feed intake and preference. Identified SNPs were close to 31 QTLs for milk yield and its components, body weight, and residual feed intake traits. In addition, these traits had high correlations with PME trait. Overall, our findings suggest that marker-assisted and genomic selection could be used to improve the difficult and expensive-to-measure phenotypes such as PME. Moreover, prediction of methane emission by VFA indicators could be useful for increasing the size of reference population required in genome-wide association studies and genomic selection.

Exploring novel single nucleotide polymorphisms and haplotypes of the diacylglycerol O-acyltransferase 1 (DGAT1) gene and their effects on protein structure in Iranian buffalo.

BACKGROUND: Diacylglycerol O-acyltransferase 1 (DGAT1) plays a key role in the synthesis of triglycerides. Recent studies have shown that a transition mutation resulting in substitutions of guanine by adenine in the DGAT1 gene in cattle has considerable effects on milk yield and composition. Currently, there is no systematic research reporting on the utilization of this gene segment in Iranian buffalo (Bubalus bubalis). OBJECTIVE: In this study, the genetic differentiation of three indigenous Iranian buffalo populations was investigated in the region spanning exon 3 to exon 17 of the DGAT1 gene. METHODS: A total of 200 buffaloes were genotyped, all the samples were sequenced directly in both directions with forward and reverse sequencing primers. RESULTS: Sequence analysis showed novel SNPs compared to the reference GenBank sequence (DQ886485) at nucleotide positions g.6097A>G, g.7036C>T, g.7338G>A, g.7710C>T, g.8087C>T, g.8259G>A, g.8275G>A, g.8367C>T, and g.8426C>T. No polymorphisms were found within exon 8. Therefore, the K232A position was thought to be a conserved and fixed region for high milk fat content (K allele) in Bos indicus and all buffalo breeds. Comparison with Indian buffalo revealed three exonic SNPs, one of which was nonsynonymous. A unique 22 bp insertion was observed in intron 10 of DGAT1. Linkage disequilibrium analysis allowed the identification of nine haplotypes among the sampled animals. To our knowledge, this is the first report of sequencing analysis of the DGAT1 gene in Iranian buffalo. CONCLUSION: Our results suggest that genetic diversity exists and could be useful in examining the association between the DGAT1 gene and milk production traits in buffalo.

Large-scale gene co-expression network as a source of functional annotation for cattle genes.

BACKGROUND: Genome sequencing and subsequent gene annotation of genomes has led to the elucidation of many genes, but in vertebrates the actual number of protein coding genes are very consistent across species (~20,000). Seven years after sequencing the cattle genome, there are still genes that have limited annotation and the function of many genes are still not understood, or partly understood at best. Based on the assumption that genes with similar patterns of expression across a vast array of tissues and experimental conditions are likely to encode proteins with related functions or participate within a given pathway, we constructed a genome-wide Cattle Gene Co-expression Network (CGCN) using 72 microarray datasets that contained a total of 1470 Affymetrix Genechip Bovine Genome Arrays that were retrieved from either NCBI GEO or EBI ArrayExpress. RESULTS: The total of 16,607 probe sets, which represented 11,397 genes, with unique Entrez ID were consolidated into 32 co-expression modules that contained between 29 and 2569 probe sets. All of the identified modules showed strong functional enrichment for gene ontology (GO) terms and Reactome pathways. For example, modules with important biological functions such as response to virus, response to bacteria, energy metabolism, cell signaling and cell cycle have been identified. Moreover, gene co-expression networks using "guilt-by-association" principle have been used to predict the potential function of 132 genes with no functional annotation. Four unknown Hub genes were identified in modules highly enriched for GO terms related to leukocyte activation (LOC509513), RNA processing (LOC100848208), nucleic acid metabolic process (LOC100850151) and organic-acid metabolic process (MGC137211). Such highly connected genes should be investigated more closely as they likely to have key regulatory roles. CONCLUSIONS: We have demonstrated that the CGCN and its corresponding regulons provides rich information for experimental biologists to design experiments, interpret experimental results, and develop novel hypothesis on gene function in this poorly annotated genome. The network is publicly accessible at http://www.animalgenome.org/cgi-bin/host/reecylab/d .

Random Regression Models Using Legendre Polynomials to Estimate Genetic Parameters for Test-day Milk Protein Yields in Iranian Holstein Dairy Cattle.

The objective of this study was to estimate the genetic parameters of milk protein yields in Iranian Holstein dairy cattle. A total of 1,112,082 test-day milk protein yield records of 167,269 first lactation Holstein cows, calved from 1990 to 2010, were analyzed. Estimates of the variance components, heritability, and genetic correlations for milk protein yields were obtained using a random regression test-day model. Milking times, herd, age of recording, year, and month of recording were included as fixed effects in the model. Additive genetic and permanent environmental random effects for the lactation curve were taken into account by applying orthogonal Legendre polynomials of the fourth order in the model. The lowest and highest additive genetic variances were estimated at the beginning and end of lactation, respectively. Permanent environmental variance was higher at both extremes. Residual variance was lowest at the middle of the lactation and contrarily, heritability increased during this period. Maximum heritability was found during the 12th lactation stage (0.213±0.007). Genetic, permanent, and phenotypic correlations among test-days decreased as the interval between consecutive test-days increased. A relatively large data set was used in this study; therefore, the estimated (co)variance components for random regression coefficients could be used for national genetic evaluation of dairy cattle in Iran.

Effect of ethanol induced mild stress on post-thawed bull sperm quality.

This study was performed to investigate the effect of sub-lethal exposure of bull semen to ethanol on the post-thaw spermatozoa quality. Semen samples (n=24, 6 ejaculates/bull) from 4 Holstein bulls were collected and pooled. Pooled samples were divided into 4 equal parts and each part was frozen after being diluted with Optidyl® extender containing 0 (O-E0), 0.03 (O-E3), 0.09 (O-E9) and 0.15 (O-E15) % (v/v) absolute ethanol. Sperm motility and velocity, plasma membrane integrity and functionality, mitochondrial activity, malondialdehyde concentration, and apoptosis status were evaluated after thawing. A higher percentage of total motility was observed in the O-E9 group as compared to the O-E0, O-E3 and O-E15 groups (p<0.05). Also, plasma membrane integrity was higher (p<0.05) in the O-E9 group compared to the O-E3, and O-E15 groups. However, the difference between the O-E9 and O-E0 groups was not significant (p>0.05). In terms of the proportion of sperm abnormality and plasma membrane functionality no differences (p>0.05) were observed between the groups. Our results revealed that malondialdehyde level was lower in ethanol treated (O-E3, O-E9 and O-E15) groups compared to the O-E0 group (p<0.05). Furthermore, the percentage of live spermatozoa with active mitochondria was higher in the O-E9 and O-E15 groups compared to the O-E0 and O-E3 groups (p<0.05). The O-E3 and O-E9 groups resulted in the highest and lowest percentage of apoptotic spermatozoa, respectively (p<0.05). The results of this study demonstrate that supplementation of semen extender with sub-lethal concentration of ethanol influences post-thawed bull sperm quality in a dose dependent manner.

Fertility subindex for improving fertility performance in Iranian Holstein cows.

Different fertility indices were constructed for improving fertility performance in Iranian Holstein dairy cows. Number of inseminations per conception and days from calving to first insemination, each weighted by its economic value, were included as breeding goals in the aggregate genotype definition. Different fertility indices (FI) were constructed with different combinations of available fertility traits: number of inseminations to conception (INS), days from calving to first service (DFS), interval between first and last insemination (IFL), and days open (DO). The fertility index (FI1) that included INS and DFS had the greatest genetic gain for INS (-0.39 insemination), DFS (-7.47 days), and profit ($4.3) per generation. Genetic gain for profit, DFS, and INS including only DO showed slight differences regarding FI1. A selection index that included only INS (DFS) presented the larger (smaller) genetic gains for INS and smaller (larger) for DFS, which were -0.40 (-0.034) and -0.975 (-11.18) inseminations and days, respectively. The result of this study showed that recording INS and DFS are preferable traits for including in a fertility subindex. DO can be used in the absence of other fertility traits.

The relation between the genetic architecture of quantitative traits and long-term genetic response.

The genetic architecture of a quantitative trait refers to the number of genetic variants, allele frequencies, and effect sizes of variants that affect a trait and their mode of gene action. This study was conducted to investigate the effect of four shapes of allelic frequency distributions (constant, uniform, L-shaped and U-shaped) and different number of trait-affecting loci (50, 100, 200, 500) on allelic frequency changes, long term genetic response, and maintaining genetic variance. To this end, a population of 440 individuals composed of 40 males and 400 females as well as a genome of 200 cM consisting of two chromosomes and with a mutation rate of 2.5 × 10(-5) per locus was simulated. Selection of superior animals was done using best linear unbiased prediction (BLUP) with assumption of infinitesimal model. Selection intensity was constant over 30 generations of selection. The highest genetic progress obtained when the allelic frequency had L-shaped distribution and number of trait-affecting loci was high (500). Although quantitative genetic theories predict the extinction of genetic variance due to artificial selection in long time, our results showed that under L- and U-shapped allelic frequency distributions, the additive genetic variance is persistent after 30 generations of selection. Further, presence or absence of selection limit can be an indication of low (<50) or high (>100) number of trait-affecting loci, respectively. It was concluded that the genetic architecture of complex traits is an important subject which should be considered in studies concerning long-term response to selection.

Genomic scan of selective sweeps in thin and fat tail sheep breeds for identifying of candidate regions associated with fat deposition.

BACKGROUND: Identification of genomic regions that have been targets of selection for phenotypic traits is one of the most important and challenging areas of research in animal genetics. However, currently there are relatively few genomic regions identified that have been subject to positive selection. In this study, a genome-wide scan using ~50,000 Single Nucleotide Polymorphisms (SNPs) was performed in an attempt to identify genomic regions associated with fat deposition in fat-tail breeds. This trait and its modification are very important in those countries grazing these breeds. RESULTS: Two independent experiments using either Iranian or Ovine HapMap genotyping data contrasted thin and fat tail breeds. Population differentiation using FST in Iranian thin and fat tail breeds revealed seven genomic regions. Almost all of these regions overlapped with QTLs that had previously been identified as affecting fat and carcass yield traits in beef and dairy cattle. Study of selection sweep signatures using FST in thin and fat tail breeds sampled from the Ovine HapMap project confirmed three of these regions located on Chromosomes 5, 7 and X. We found increased homozygosity in these regions in favour of fat tail breeds on chromosome 5 and X and in favour of thin tail breeds on chromosome 7. CONCLUSIONS: In this study, we were able to identify three novel regions associated with fat deposition in thin and fat tail sheep breeds. Two of these were associated with an increase of homozygosity in the fat tail breeds which would be consistent with selection for mutations affecting fat tail size several thousand years after domestication.

Estimation of genetic parameters for body weight and egg production traits in Mazandaran native chicken.

Native chicken breeding station of Mazandaran was established in 1988 with two main objectives: genetic improvement through selection programs and dissemination of indigenous Mazandarani birds. (Co)variance components and genetic parameters for economically important traits were estimated using (bi) univariate animal models with ASREML procedure in Mazandarani native chicken. The data were from 18 generations of selection (1988-2009). Heritability estimates for body weight at different ages [at hatch (bw1), 8 (bw8), 12 (bw12) weeks of ages and sex maturation (wsm)] ranged from 0.24 ± 0.00 to 0.47 ± 0.01. Heritability for reproductive traits including age at sex maturation (asm); egg number (en); weight of first egg (ew1); average egg weight at 28 (ew28), 30 (ew30), and 32 (ew32) weeks of age; their averages (av); average egg weight for the first 12 weeks of production (ew12); egg mass (em); and egg intensity (eint) varied from 0.16 ± 0.01 to 0.43 ± 0.01. Generally, the magnitudes of heritability for the investigated traits were moderate. However, egg production traits showed smaller heritability compared with growth traits. Genetic correlations among egg weight at different ages were mostly higher than 0.8. On the one hand, body weight at different ages showed positive and relatively moderate genetic correlations with egg weight traits (ew1, ew28, ew30, ew32, ew12, and av) and varied from 0.30 ± 0.03 to 0.59 ± 0.02. On the other hand, low negative genetic correlations were obtained between body weight traits (bw1, bw8, bw12, and wsm) and egg number (en). Also, there is low negative genetic correlation (-24 ± 0.04 to -29 ± 0.05) between egg number and egg weight. Therefore, during simultaneous selection process for both growth and egg production traits, probable reduction in egg production due to low reduction in egg number may be compensated by increases in egg weight.

Bio-economic evaluation of the use of sexed semen at different conception rates and herd sizes in Holstein populations.

A stochastic bio-economic model was used to determine the effects of applying artificial insemination (AI) with conventional or sexed semen at different conception rates and herd sizes on the genetic progress of productive trait and net profit over a 15-year period. The genetic means of the cattle population was predicted to increase over the years and the rate of genetic progress in the population program using sexed semen was significantly greater than the rate of progress in the population using conventional semen. The theoretical genetic gain was greater than the realized genetic gain for milk yield for all the AI scenarios. In addition, the genetic means for milk yield in the expanding herds were greater than in the fixed sized herds. The trend in net profit generated by using AI strategies with conventional semen over the time horizon was greater when herds were expanding(P < 0.01). The trend in net profit for fixed sized herds was generally negative, however,expanding herds experienced positive net profits over the years. Also, the net profit of using AI strategies with sexed semen was greater when dairy herds were expanding. On the other hand, the net profit of using AI with sexed semen was greater than that of AI with conventional semen at the end of the time horizon. The results of sensitivity analyses indicated that a 20% increase or decrease in milk sales income and feed costs have significantly modified the net profit of AI strategies using either sexed or conventional semen.

Effect of the threshold nature of traits on heritability estimates obtained by linear model.

In this research we used stochastic method to simulate litter size data under assumption that the phenotype of the trait of interest is categorically distributed with a liability of normally distributed background effect. For the phenotypic categorical measurements, normal distribution of liability was assumed. Analysis was conducted by DFREML for phenotypic categorical data set. In the simulation process, we applied different true background heritabilities in combination with different threshold points. The points with the lowest heritability had the lowest variation in estimated heritability and those with the highest heritability had the highest variation. Results clearly show that by moving threshold points from the population mean towards the two tails of the distribution and also by increasing the true heritability, the differences between estimated heritability and true heritability increases. The linear model has always underestimated true heritabilities. It is possible to use our estimates to obtain a confidence range for true heritability when we have information about approximate location of threshold and estimates of heritability obtained by linear model.