Analyzes of genome-wide association follow-up study for calving traits in dairy cattle

ABSTRACT: BACKGROUND: There is often a pronounced disagreement between results obtained from different genome-wide association studies in cattle. There are multiple reasons for this disagreement. Particularly the presence of false positives leads to a need to validate detected QTL before they are optimally incorporated or weighted in selection decisions or further studied for causal gene. In dairy cattle progeny testing scheme new data is routinely accumulated which can be used to validate previously discovered associations. However, the data is not an independent sample and the sample size may not be sufficient to have enough power to validate previous discoveries. Here we compared two strategies to validate previously detected QTL when new data is added from the same study population. We compare analyzing a combined dataset (COMB) including all data presently available to only analyzing a validation dataset (VAL) i.e. a new dataset not previously analyzed as an independent replication. Secondly, we confirm SNP detected in the Reference population (REF) (i.e. previously analyzed dataset consists of older bulls) in the VAL dataset. RESULTS: Clearly the results from the combined (COMB) dataset which had nearly twice the sample size of other two subsets allowed the detection of far more significant associations than the two smaller subsets. The number of significant SNPs in REF (older bulls) was about four times higher compare to VAL (younger bulls) though both had similar sample sizes, 2,219 and 2,039 respectively. A total of 424 SNP-trait combinations on 22 chromosomes showed genome-wide significant association involving 284 unique SNPs in the COMB dataset. In the REF data set 101 associations (73 unique SNPs) and in the VAL 24 associations (18 unique SNPs) were found genome-wide significant.Sixty-eight percent of the SNPs in the REF dataset could be confirmed in the VAL dataset. Out of 469 unique SNPs showing chromosome-wide significant association with calving traits in the REF dataset 321 could be confirmed in the VAL dataset at P < 0.05. CONCLUSIONS: The follow-up study for GWAS in cattle will depend on the aim of the study. If the aim is to discover novel QTL, analyses of the COMB dataset is recommended, while in case of identification of the causal mutation underlying a QTL, confirmation of the discovered SNPs are necessary to avoid following a false positive.     

奶牛重要经济性状全基因组关联分析研究进展

产奶性状是奶牛最重要的生产性状,随着平衡育种理念的提出和发展,繁殖性状、体型性状、健康性状和长寿性等功能性状也逐渐被重视并纳入育种规划中。鉴定产奶性状和功能性状主效基因或遗传标记并将之应用于奶牛标记辅助选择可望加快遗传进展。随着高密度SNP标记的高通量检测技术的发展,全基因组关联分析已成为鉴定畜禽重要经济性状基因的重要途径。文章对奶牛产奶性状和功能性状全基因组关联分析研究进展进行综述。     

奶牛重要经济性状全基因组关联分析研究进展

产奶性状是奶牛最重要的生产性状, 随着平衡育种理念的提出和发展, 繁殖性状、体型性状、健康性状和长寿性等功能性状也逐渐被重视并纳入育种规划中。鉴定产奶性状和功能性状主效基因或遗传标记并将之应用于奶牛标记辅助选择可望加快遗传进展。随着高密度SNP标记的高通量检测技术的发展, 全基因组关联分析已成为鉴定畜禽重要经济性状基因的重要途径。文章对奶牛产奶性状和功能性状全基因组关联分析研究进展进行综述。     

Genome-wide association study for calving performance using high-density genotypes in dairy and beef cattle

Background

Calving difficulty and perinatal mortality are prevalent in modern-day cattle production systems. It is well-established that there is a genetic component to both traits, yet little is known about their underlying genomic architecture, particularly in beef breeds. Therefore, we performed a genome-wide association study using high-density genotypes to elucidate the genomic architecture of these traits and to identify regions of the bovine genome associated with them.

Results

Genomic regions associated with calving difficulty (direct and maternal) and perinatal mortality were detected using two statistical approaches: (1) single-SNP (single nucleotide polymorphism) regression and (2) a Bayesian approach. Data included high-density genotypes on 770 Holstein-Friesian, 927 Charolais and 963 Limousin bulls. Several novel or previously identified genomic regions were detected but associations differed by breed. For example, two genomic associations, one each on chromosomes 18 and 2 explained 2.49 % and 3.13 % of the genetic variance in direct calving difficulty in the Holstein-Friesian and Charolais populations, respectively. Imputed Holstein-Friesian sequence data was used to refine the genomic regions responsible for significant associations. Several candidate genes on chromosome 18 were identified and four highly significant missense variants were detected within three of these genes (SIGLEC12, CTU1, and ZNF615). Nevertheless, only CTU1 contained a missense variant with a putative impact on direct calving difficulty based on SIFT (0.06) and Polyphen (0.95) scores. Using imputed sequence data, we refined a genomic region on chromosome 4 associated with maternal calving difficulty in the Holstein-Friesian population and found the strongest association with an intronic variant in the PCLO gene. A meta-analysis was performed across the three breeds for each calving performance trait to identify common variants associated with these traits in the three breeds. Our results suggest that a portion of the genetic variation in calving performance is common to all three breeds.

Conclusion

The genomic architecture of calving performance is complex and mainly influenced by many polymorphisms of small effect. We identified several associations of moderate effect size but the majority were breed-specific, indicating that breed-specific alleles exist for calving performance or that the linkage phase between genotyped allele and causal mutation varies between breeds.

Electronic supplementary material

The online version of this article (doi:10.1186/s12711-015-0126-4) contains supplementary material, which is available to authorized users.     

A genome-wide association study of immune response traits in Canadian Holstein cattle

Background

Breeding for enhanced immune response (IR) has been suggested as a tool to improve inherent animal health. Dairy cows with superior antibody-mediated (AMIR) and cell-mediated immune responses (CMIR) have been demonstrated to have a lower occurrence of many diseases including mastitis. Adaptive immune response traits are heritable, and it is, therefore, possible to breed for improved IR, decreasing the occurrence of disease. The objective of this study was to perform genome-wide association studies to determine differences in genetic profiles among Holstein cows classified as High or Low for AMIR and CMIR. From a total of 680 cows with immune response phenotypes, 163 cows for AMIR (81 High and 82 Low) and 140 for CMIR (75 High and 65 Low) were selectively genotyped using the Illumina Bovine SNP50 BeadChip. Results were validated using an unrelated population of 164 Holstein bulls IR phenotyped for AMIR and 146 for CMIR.

Results

A generalized quasi likelihood score method was used to determine single nucleotide polymorphisms (SNP) and chromosomal regions associated with immune response. After applying a 5% chromosomal false discovery rate, 186 SNPs were significantly associated with AMIR. The majority (93%) of significant markers were on chromosome 23, with a similar peak found in the bull population. For CMIR, 21 SNP markers remained significant. Candidate genes within 250,000 base pairs of significant SNPs were identified to determine biological pathways associated with AMIR and CMIR. Various pathways were identified, including the antigen processing and presentation pathway, important in host defense. Candidate genes included those within the bovine Major Histocompatability Complex such as BoLA-DQ, BoLA-DR and the non-classical BoLA-NC1 for AMIR and BoLA-DQ for CMIR, the complement system including C2 and C4 for AMIR and C1q for CMIR, and cytokines including IL-17A, IL17F for AMIR and IL-17RA for CMIR and tumor necrosis factor for both AMIR and CMIR. Additional genes associated with CMIR included galectins 1, 2 and 3, BCL2 and β-defensin.

Conclusions

The significant genetic variation associated with AMIR and CMIR in this study may imply feasibility to include immune response in genomic breeding indices as an approach to improve inherent animal health.     

Genome-wide association study identifies two major loci affecting calving ease and growth-related traits in cattle

Identifying quantitative trait loci (QTL) underlying complex, low-heritability traits is notoriously difficult. Prototypical for such traits, calving ease is an important breeding objective of cattle (Bos taurus)-improving programs. To identify QTL underlying calving ease, we performed a genome-wide association study using estimated breeding values (EBVs) as highly heritable phenotypes for paternal calving ease (pCE) and related traits. The massively structured study population consisted of 1800 bulls of the German Fleckvieh (FV) breed. Two pCE-associated regions on bovine chromosomes (BTA) 14 and 21 (P = 5.72 × 10(-15) and P = 2.27 × 10(-8), respectively) were identified using principal components analysis to correct for population stratification. The two most significantly associated SNPs explain 10% of the EBV variation. Since marker alleles with negative effect on pCE have positive effects on growth-related traits, the QTL may exert their effects on the birthing process through fetal growth traits. The QTL region on BTA14 corresponds to a human chromosome (HSA) region that is associated with growth characteristics. The HSA region corresponding to the BTA21 pCE QTL is maternally imprinted and involved in the Prader-Willi and Angelman syndromes. Resequencing of positional candidate genes on BTA14 revealed a highly significantly (P = 1.96 × 10(-14)) associated polymorphism ablating a polyadenylation signal of the gene encoding ribosomal protein S20 (RPS20). Our study demonstrates the leverage potential of EBVs in unraveling the genetic architecture of lowly heritable traits.     

A genome-wide association study for quantitative traits in schizophrenia in China

Few genome-wide association studies (GWAS) of schizophrenia have included Chinese populations, and verification of positive genetic findings from other ethnic groups is rare in Chinese groups. We used fluid intelligence as the quantitative trait reflecting schizophrenia dysfunction in Chinese populations, and determined the impact of genetic variation on fluid intelligence phenotypic patterns to identify genetic influences in schizophrenia. The study sample comprised 98 patients with schizophrenia and 60 healthy controls. The general fluid intelligence of participants was assessed with Cattell's Culture-Free Intelligence Test (CCFIT). Subjects were genotyped using the Illumina HumanHap 660 beadchip. We identified the methionine sulfoxide reductase A (MSRA) gene on chromosome 8 as having an association with fluid intelligence. However, only CCFIT subtest 1 (series score) demonstrated a significant result for the interaction term using the criteria of the quantitative trait (QT) analysis of 10(-5) for at least three SNPs. There were 15 haplotype blocks of MSRA gene SNPs identified using Haploview 4.2 with solid spine D' > 0.80. The strongest QT interaction was noted in Block 3, with the most common haplotypes being AAACAGCAG and CGCAGAAGA. In conclusion, we report data from a GWAS with quantitative traits design from Chinese first-episode schizophrenia patients and matched controls. Although the gene identified requires confirmation in an independent sample, the MSRA gene located on chromosome 8 was found to be associated with the phenotype of schizophrenia.     

Genome-wide association study for growth traits in Nelore cattle

The objective of this study was to investigate the association of single nucleotide polymorphisms (SNPs) with birth weight, weight gain from birth to weaning and from weaning to yearling, yearling height and cow weight in Nelore cattle. Data from 5064 animals participating in the DeltaGen and PAINT breeding programs were used. The animals were genotyped with a panel of 777 962 SNPs (Illumina BovineHD BeadChip) and 412 993 SNPs remained after quality control analysis of the genomic data. A genome-wide association study was performed using a single-step methodology. The analyses were processed with the BLUPF90 family of programs. When applied to a genome-wide association studies, the single-step GBLUP methodology is an iterative process that estimates weights for the SNPs. The weights of SNPs were included in all analyses by iteratively applying the single-step GBLUP methodology and repeated twice so that the effect of the SNP and the effect of the animal were recalculated in order to increase the weight of SNPs with large effects and to reduce the weight of those with small effects. The genome-wide association results are reported based on the proportion of variance explained by windows of 50 adjacent SNPs. Considering the two iterations, only windows with an additive genetic variance >1.5% were presented in the results. Associations were observed with birth weight on BTA 14, with weight gain from birth to weaning on BTA 5 and 29, with weight gain from weaning to yearling on BTA 11, and with yearling height on BTA 8, showing the genes TMEM68 (transmembrane protein 8B) associated with birth weight and yearling height, XKR4 (XK, Kell blood group complex subunit-related family, member 4) associated with birth weight, NPR2 (natriuretic peptide receptor B) associated with yearling height, and REG3G (regenerating islet-derived 3-gamma) associated with weight gain from weaning to yearling. These genes play an important role in feed intake, weight gain and the regulation of skeletal growth.     

Evaluating alternate models to estimate genetic parameters of calving traits in United Kingdom Holstein-Friesian dairy cattle

Background

The focus in dairy cattle breeding is gradually shifting from production to functional traits and genetic parameters of calving traits are estimated more frequently. However, across countries, various statistical models are used to estimate these parameters. This study evaluates different models for calving ease and stillbirth in United Kingdom Holstein-Friesian cattle.

Methods

Data from first and later parity records were used. Genetic parameters for calving ease, stillbirth and gestation length were estimated using the restricted maximum likelihood method, considering different models i.e. sire (−maternal grandsire), animal, univariate and bivariate models. Gestation length was fitted as a correlated indicator trait and, for all three traits, genetic correlations between first and later parities were estimated. Potential bias in estimates was avoided by acknowledging a possible environmental direct-maternal covariance. The total heritable variance was estimated for each trait to discuss its theoretical importance and practical value. Prediction error variances and accuracies were calculated to compare the models.

Results and discussion

On average, direct and maternal heritabilities for calving traits were low, except for direct gestation length. Calving ease in first parity had a significant and negative direct-maternal genetic correlation. Gestation length was maternally correlated to stillbirth in first parity and directly correlated to calving ease in later parities. Multi-trait models had a slightly greater predictive ability than univariate models, especially for the lowly heritable traits. The computation time needed for sire (−maternal grandsire) models was much smaller than for animal models with only small differences in accuracy. The sire (−maternal grandsire) model was robust when additional genetic components were estimated, while the equivalent animal model had difficulties reaching convergence.

Conclusions

For the evaluation of calving traits, multi-trait models show a slight advantage over univariate models. Extended sire models (−maternal grandsire) are more practical and robust than animal models. Estimated genetic parameters for calving traits of UK Holstein cattle are consistent with literature. Calculating an aggregate estimated breeding value including direct and maternal values should encourage breeders to consider both direct and maternal effects in selection decisions.     

Bayesian genome-wide association study of nut traits in Japanese chestnut

Japanese chestnut (Castanea crenata Sieb. et Zucc.) has a long juvenile phase, so breeders have to wait many years to evaluate nut traits. Molecular markers associated with genes of interest would accelerate selection in chestnut breeding programs. We evaluated five nut traits (nut harvest date, nut weight, pericarp splitting, insect infestation, and specific gravity) in 99 Japanese chestnut cultivars and selections. A wide range of phenotypic variation was observed for each of the traits, suggesting that the collection harbored sufficient genetic diversity for breeding. A Bayesian genome-wide association study was conducted using 162 simple sequence repeat markers and 741 single nucleotide polymorphism markers. To evaluate the potential of marker-assisted selection, we examined 12 molecular markers found to be associated with nut traits: 4 for nut harvest date, 4 for nut weight, 1 for pericarp splitting, and 3 for insect infestation. The percentages of phenotypic variance explained ranged from 4.8 to 37.1%. Although insect infestation showed only medium heritability (0.672), we obtained two quantitative trait loci (QTLs) with extremely high posterior probabilities (0.93 and 1.00). Out of the 12 molecular markers, 3 of the 4 markers for nut harvest time could be validated in a breeding population. Accuracies of genomic selection were extremely high for nut harvest date (0.841) and moderate for insect infestation (0.604), suggesting that genomic selection based on Bayesian regression would reduce the cost of phenotypic evaluation of these traits and possibly others.     

Integrating genome-wide association study and pathway analysis reveals physiological aspects affecting heifer early calving defined at different ages in Nelore cattle

Heifer early calving (HC) plays a key role in beef cattle herds' economic sustainability and profitability by reducing production costs and generation intervals. However, the genetic basis of HC in Nelore heifers at different ages remains to be well understood. In this study, we aimed to perform a multi-trait weighted single-step genome-wide association (MT w-ssGWAS) to uncover the genetic mechanism involved in HC at 24 (HC24), 26 (HC26), 28 (HC28), and 30 (HC30) months of age in Nelore heifers. The MT w-ssGWAS pointed out four shared windows regions for HC24, HC26, HC28, and HC30 on BTA 5, 6, 14, and 16, explaining a larger proportion of genetic variation from 9.2% for HC30 to 10.6% for HC28. The shared regions harbored candidate genes related with the major gatekeeper for early puberty onset by controlling metabolic aspects related to homeostasis, reproductive, and growth (IGF1, PARPBP, PMCH, GNRHR, LYN, TMEM68, PLAG1, CHCHD7, KISS1, GOLT1A, and PPP1R15B). The MT w-ssGWAS and pathway analysis highlighted differences in physiological processes that support complex interactions between the gonadotropic axes, growth aspects, and sexual precocity in Nelore heifers, providing useful information for genetic improvement and management strategies.     

A genome-wide association study on obesity and obesity-related traits

Large-scale genome-wide association studies (GWAS) have identified many loci associated with body mass index (BMI), but few studies focused on obesity as a binary trait. Here we report the results of a GWAS and candidate SNP genotyping study of obesity, including extremely obese cases and never overweight controls as well as families segregating extreme obesity and thinness. We first performed a GWAS on 520 cases (BMI>35 kg/m(2)) and 540 control subjects (BMI<25 kg/m(2)), on measures of obesity and obesity-related traits. We subsequently followed up obesity-associated signals by genotyping the top ～500 SNPs from GWAS in the combined sample of cases, controls and family members totaling 2,256 individuals. For the binary trait of obesity, we found 16 genome-wide significant signals within the FTO gene (strongest signal at rs17817449, P = 2.5 × 10(-12)). We next examined obesity-related quantitative traits (such as total body weight, waist circumference and waist to hip ratio), and detected genome-wide significant signals between waist to hip ratio and NRXN3 (rs11624704, P = 2.67 × 10(-9)), previously associated with body weight and fat distribution. Our study demonstrated how a relatively small sample ascertained through extreme phenotypes can detect genuine associations in a GWAS.     

A genome-wide association study for feed efficiency-related traits in a crossbred pig population

Feed efficiency (FE) is one of the most important traits in pig production. However, it is difficult and costly to measure it, limiting the collection of large amount of data for an accurate selection for better FE. Therefore, the identification of single-nucleotide polymorphisms (SNPs) associated with FE-related traits to be used in the genetic evaluation is of great interest of pig breeding programs for increasing the prediction accuracy and the genetic progress of these traits. The objective of this study was to identify SNPs significantly associated with FE-related traits: average daily gain (ADG), average daily feed intake (ADFI) and feed conversion ratio (FCR). We also aimed to identify potential candidate genes for these traits. Phenotypic information recorded on a population of 2386 three-way crossbreed pigs that were genotyped for 51 468 SNPs was used. We identified three loci of quantitative trait (QTL) regions associated with ADG and three QTL regions associated with ADFI; however, no significant association was found for FCR. A false discovery rate (FDR) ≤ 0.005 was used as the threshold for declaring an association as significant. The QTL regions associated with ADG on Sus scrofa chromosome (SSC) 1 were located between 177.01 and 185.47 Mb, which overlaps with the QTL regions for ADFI on SSC1 (173.26 and 185.47 Mb). The other QTL region for ADG was located on SSC12 (2.87 and 3.22 Mb). The most significant SNPs in these QTL regions explained up to 3.26% of the phenotypic variance of these traits. The non-identification of genomic regions associated with FCR can be explained by the complexity of this trait, which is a ratio between ADG and ADFI. Finally, the genes CDH19, CDH7, RNF152, MC4R, PMAIP1, FEM1B and GAA were the candidate genes found in the 1 Mb window around the QTL regions identified in this study. Among them, the MC4R gene (SSC1) has a well-known function related to ADG and ADFI. In this study, we identified three QTL regions for ADG (SSC1 and SSC12) and three for ADFI (SSC1). These regions were previously described in purebred pig populations; however, to our knowledge, this is the first study to confirm the relevance of these QTL regions in a crossbred pig population. The potential use of the SNPs and genes identified in this study in prediction models that combine genomic selection and marker-assisted selection should be evaluated for increasing the prediction accuracy of these traits in this population.     

An imputation-based genome-wide association study for growth and fatness traits in Sujiang pigs

Sujiang pigs are a synthetic breed derived from Jiangquhai, Fengjing, and Duroc pigs. In this study, we sequenced the genome of 62 pigs with a coverage depth of 10× to 20×, including 27 Sujiang and 35 founder breed pigs, and we collected 360 global pigs’ genome sequence data from public databases including 39 Duroc pigs. We obtained a high-quality variant dataset of 365 Sujiang pigs by imputing the porcine 80 K single nucleotide polymorphism (SNP) Beadchip to the whole-genome scale with a total of 422 pigs as a reference panel. A dataset of 365 imputated Sujiang pigs was used to perform single-trait genome-wide association study (GWAS) and meta-analyses for growth and fatness traits. Single-trait GWAS identified 1 907, 18, and 14 SNPs surpassing the suggestively significant threshold for backfat thickness, chest circumference, and chest width, respectively. Meta-analyses identified 2 400 genome-wide significant SNPs and 520 suggestively significant SNPs for backfat thickness and chest circumference, and 719 genome-wide significant SNPs and 1 225 suggestively significant SNPs for all seven traits. According to the meta-analysis of backfat thickness and chest circumference, a remarkable region of 2.69 Mb on Sus scrofa chromosome 4 containing FAM110B, IMPAD1, LYN, MOS, PENK, PLAG1, SDR16C5 and XKR4 was identified as a candidate region. The haplotype heat map of the 2.69 Mb region verified that Sujiang pigs were derived from Duroc and Chinese indigenous pigs, especially Jiangquhai pigs. The Kruskal-Wallis test showed that haplotypes of the 2.69 Mb region significantly affected backfat thickness and chest circumference traits. We then focused on PLAG1, an important growth-related gene, and identified two synonymous SNPs with obvious differences among different breeds in the PLAG1 gene. We then performed genotyping of 365 Sujiang, 150 Duroc, 95 Jiangquhai, and 100 Fengjing pigs to confirm the above result and verified that the two variants significantly affected phenotypes of growth and fatness traits. Our findings not only provide insights into the genetic architecture of porcine growth and fatness traits but also provide potential markers for selective breeding of these traits in Sujiang pigs.     

A genome-wide association study of wheat yield and quality-related traits in southwest China

Wheat (Triticum aestivum L.) is one of the most productive and important crops and its yield potential and quality characteristics are tightly linked with the global food security. In this study, genome-wide association study (GWAS) was conducted for yield and quality-related traits. Based on the high-density wheat 90K Illumina iSelect SNP Array, 192 bread wheat lines from southwest China, including 25 synthetic hexaploid wheat lines, 80 landraces, and 87 cultivars were analyzed. Association analysis results indicated that there were 57, 27, 30, and 34 SNPs associated with plant height (PH), grain protein content (GPC), thousand kernel weight (TKW), and SDS sedimentation volume (SSV) have been detected, respectively. Then, integrating RNA-Seq with bioinformatics analysis, 246 candidate genes (102 for GPC, 52 for TKW, and 92 for SSV) were found. Further analysis indicated that one up-regulated and two down-regulated expression genes affect GPC. Additionally, two haplotypes significantly affecting PH were detected in a 2.2-Mb genome region encompassing a gene which encoded an ubiquitin-specific protease, TaUBP24. The functional markers of TaUBP24 have been developed, which could be used for marker-assisted selection to improve wheat quality and yield.     

京海黄鸡体重性状全基因组关联分析

体重性状是肉鸡重要的经济性状。为了寻找可用于京海黄鸡体重性状遗传改良的分子标记及候选基因,本文以400只京海黄鸡核心群母鸡为基础,测定了0~14周龄体重,利用简化基因组测序技术(Specific-locus amplified fragment sequencing, SLAF-seq)对京海黄鸡体重性状进行全基因组关联研究(Genome-wide association stndy, GWAS),筛选与京海黄鸡体重性状相关的SNPs位点。结果共检测到100个与京海黄鸡体重相关的SNPs位点,其中15个位点效应达到全基因组显著水平(P<1.87E-06),85个位点效应达到全基因组潜在显著水平(P<3.73E-05)。通过筛选每个显著SNP周围1 Mb区域内的基因,共找到9个可能的候选基因,其中FAM124A(Family with sequence similarity 124A)、QDPR(Quinoid dihydropteridine reductase)、WDR1(WD repeat domain 1)和SLC2A9(Solute carrier family 2 (facilitated glucose transporter), member 9) 4个基因可能是影响体重性状的重要候选基因。同时还发现,4号染色体75.6~80.7 Mb区域集中了大部分与京海黄鸡中后期体重性状显著相关的SNPs位点,该区域可能是影响京海黄鸡中后期生长体重的重要候选区域。     

Genome-wide association study identifies candidate markers for bull fertility in Holstein dairy cattle

The decline in the reproductive efficiency of dairy cattle has become a challenging problem worldwide. Female fertility is now taken into account in breeding goals while generally less attention is given to male fertility. The objective of this study was to perform a genome-wide association study in Holstein bulls to identify genetic variants significantly related to sire conception rate (SCR), a new phenotypic evaluation of bull fertility. The analysis included 1755 sires with SCR data and 38,650 single nucleotide polymorphisms (SNPs) spanning the entire bovine genome. Associations between SNPs and SCR were analyzed using a mixed linear model that included a random polygenic effect and SNP genotype either as a linear covariate or as a categorical variable. A multiple testing correction approach was used to account for the correlation between SNPs because of linkage disequilibrium. After genome-wide correction, eight SNPs showed significant association with SCR. Some of these SNPs are located close to or in the middle of genes with functions related to male fertility, such as the sperm acrosome reaction, chromatin remodeling during the spermatogenesis, and the meiotic process during male germ cell maturation. Some SNPs showed marked dominance effects, which provide more evidence for the relevance of non-additive effects in traits closely related to fitness such as fertility. The results could contribute to the identification of genes and pathways associated with male fertility in dairy cattle.     

A genome-wide association study follow-up suggests a possible role for PPARG in systemic sclerosis susceptibility

Introduction

A recent genome-wide association study (GWAS) comprising a French cohort of systemic sclerosis (SSc) reported several non-HLA single-nucleotide polymorphisms (SNPs) showing a nominal association in the discovery phase. We aimed to identify previously overlooked susceptibility variants by using a follow-up strategy.

Methods

Sixty-six non-HLA SNPs showing a P value <10^-4 in the discovery phase of the French SSc GWAS were analyzed in the first step of this study, performing a meta-analysis that combined data from the two published SSc GWASs. A total of 2,921 SSc patients and 6,963 healthy controls were included in this first phase. Two SNPs, PPARG rs310746 and CHRNA9 rs6832151, were selected for genotyping in the replication cohort (1,068 SSc patients and 6,762 healthy controls) based on the results of the first step. Genotyping was performed by using TaqMan SNP genotyping assays.

Results

We observed nominal associations for both PPARG rs310746 (P_MH = 1.90 × 10^-6, OR, 1.28) and CHRNA9 rs6832151 (P_MH = 4.30 × 10^-6, OR, 1.17) genetic variants with SSc in the first step of our study. In the replication phase, we observed a trend of association for PPARG rs310746 (P value = 0.066; OR, 1.17). The combined overall Mantel-Haenszel meta-analysis of all the cohorts included in the present study revealed that PPARG rs310746 remained associated with SSc with a nominal non-genome-wide significant P value (P_MH = 5.00 × 10^-7; OR, 1.25). No evidence of association was observed for CHRNA9 rs6832151 either in the replication phase or in the overall pooled analysis.

Conclusion

Our results suggest a role of PPARG gene in the development of SSc.     

Beef cattle body temperature during climatic stress: a genome-wide association study

Cattle are reared in diverse environments and collecting phenotypic body temperature (BT) measurements to characterize BT variation across diverse environments is difficult and expensive. To better understand the genetic basis of BT regulation, a genome-wide association study was conducted utilizing crossbred steers and heifers totaling 239 animals of unknown pedigree and breed fraction. During predicted extreme heat and cold stress events, hourly tympanic and vaginal BT devices were placed in steers and heifers, respectively. Individuals were genotyped with the BovineSNP50K_v2 assay and data analyzed using Bayesian models for area under the curve (AUC), a measure of BT over time, using hourly BT observations summed across 5-days (AUC summer 5-day (AUCS5D) and AUC winter 5-day (AUCW5D)). Posterior heritability estimates were moderate to high and were estimated to be 0.68 and 0.21 for AUCS5D and AUCW5D, respectively. Moderately positive correlations between direct genomic values for AUCS5D and AUCW5D (0.40) were found, although a small percentage of the top 5 % 1-Mb windows were in common. Different sets of genes were associated with BT during winter and summer, thus simultaneous selection for animals tolerant to both heat and cold appears possible.