Three novel quantitative trait loci for skin thickness in swine identified by linkage and genome‐wide association studies

Skin is the largest organ in the pig body and plays a key role in protecting the body against pathogens and excessive water loss. Deciphering the genetic basis of swine skin thickness would enrich our knowledge about the skin. To identify the loci for porcine skin thickness, we first performed a genome scan with 194 microsatellite markers in a White Duroc × Erhualian F₂ intercross. We identified three genome‐wide significant QTL on pig chromosomes (SSC) 4, 7 and 15 using linkage analysis. The most significant QTL was found on SSC7 with a small confidence interval of ~5 cM, explaining 23.9 percent of phenotypic variance. Further, we conducted a genome‐wide association study (GWAS) using Illumina PorcineSNP60 Beadchips for the F₂ pedigree and a population of Chinese Sutai pigs. We confirmed significant QTL in the F₂ pedigree and replicated QTL on SSC15 in Chinese Sutai pigs. A meta‐analysis of GWASs on both populations detected a genomic region associated with skin thickness on SSC4. GWAS results were generally consistent with QTL mapping. Identical‐by‐descent analysis defined QTL on SSC7 in a 683‐kb region harboring an interesting candidate gene: HMGA1. On SSC15, the linkage disequilibrium analysis showed a haplotype block of 2.20 Mb that likely harbors the gene responsible for skin thickness. Our findings provide novel insights into the genetic basis of swine skin thickness, which would benefit further understanding of porcine skin function.     

Genome‐wide association studies for hematological traits in swine

Improving immune capacity may increase the profitability of animal production if it enables animals to better cope with infections. Hematological traits play pivotal roles in animal immune capacity and disease resistance. Thus far, few studies have been conducted using a high‐density swine SNP chip panel to unravel the genetic mechanism of the immune capability in domestic animals. In this study, using mixed model‐based single‐locus regression analyses, we carried out genome‐wide association studies, using the Porcine SNP60 BeadChip, for immune responses in piglets for 18 hematological traits (seven leukocyte traits, seven erythrocyte traits, and four platelet traits) after being immunized with classical swine fever vaccine. After adjusting for multiple testing based on permutations, 10, 24, and 77 chromosome‐wise significant SNPs were identified for the leukocyte traits, erythrocyte traits, and platelet traits respectively, of which 10 reached genome‐wise significance level. Among the 53 SNPs for mean platelet volume, 29 are located in a linkage disequilibrium block between 32.77 and 40.59 Mb on SSC6. Four genes of interest are located within the block, providing genetic evidence that this genomic segment may be considered a candidate region relevant to the platelet traits. Other candidate genes of interest for red blood cell, hemoglobin, and red blood cell volume distribution width also have been found near the significant SNPs. Our genome‐wide association study provides a list of significant SNPs and candidate genes that offer valuable information for future dissection of molecular mechanisms regulating hematological traits.     

Pleiotropy informed adaptive association test of multiple traits using genome‐wide association study summary data

Genetic variants associated with disease outcomes can be used to develop personalized treatment. To reach this precision medicine goal, hundreds of large‐scale genome‐wide association studies (GWAS) have been conducted in the past decade to search for promising genetic variants associated with various traits. They have successfully identified tens of thousands of disease‐related variants. However, in total these identified variants explain only part of the variation for most complex traits. There remain many genetic variants with small effect sizes to be discovered, which calls for the development of (a) GWAS with more samples and more comprehensively genotyped variants, for example, the NHLBI Trans‐Omics for Precision Medicine (TOPMed) Program is planning to conduct whole genome sequencing on over 100 000 individuals; and (b) novel and more powerful statistical analysis methods. The current dominating GWAS analysis approach is the “single trait” association test, despite the fact that many GWAS are conducted in deeply phenotyped cohorts including many correlated and well‐characterized outcomes, which can help improve the power to detect novel variants if properly analyzed, as suggested by increasing evidence that pleiotropy, where a genetic variant affects multiple traits, is the norm in genome‐phenome associations. We aim to develop pleiotropy informed powerful association test methods across multiple traits for GWAS. Since it is generally very hard to access individual‐level GWAS phenotype and genotype data for those existing GWAS, due to privacy concerns and various logistical considerations, we develop rigorous statistical methods for pleiotropy informed adaptive multitrait association test methods that need only summary association statistics publicly available from most GWAS. We first develop a pleiotropy test, which has powerful performance for truly pleiotropic variants but is sensitive to the pleiotropy assumption. We then develop a pleiotropy informed adaptive test that has robust and powerful performance under various genetic models. We develop accurate and efficient numerical algorithms to compute the analytical P‐value for the proposed adaptive test without the need of resampling or permutation. We illustrate the performance of proposed methods through application to joint association test of GWAS meta‐analysis summary data for several glycemic traits. Our proposed adaptive test identified several novel loci missed by individual trait based GWAS meta‐analysis. All the proposed methods are implemented in a publicly available R package.     

Meta‐analysis of genome‐wide association from genomic prediction models

Genome‐wide association (GWA) studies based on GBLUP models are a common practice in animal breeding. However, effect sizes of GWA tests are small, requiring larger sample sizes to enhance power of detection of rare variants. Because of difficulties in increasing sample size in animal populations, one alternative is to implement a meta‐analysis (MA), combining information and results from independent GWA studies. Although this methodology has been used widely in human genetics, implementation in animal breeding has been limited. Thus, we present methods to implement a MA of GWA, describing the proper approach to compute weights derived from multiple genomic evaluations based on animal‐centric GBLUP models. Application to real datasets shows that MA increases power of detection of associations in comparison with population‐level GWA, allowing for population structure and heterogeneity of variance components across populations to be accounted for. Another advantage of MA is that it does not require access to genotype data that is required for a joint analysis. Scripts related to the implementation of this approach, which consider the strength of association as well as the sign, are distributed and thus account for heterogeneity in association phase between QTL and SNPs. Thus, MA of GWA is an attractive alternative to summarizing results from multiple genomic studies, avoiding restrictions with genotype data sharing, definition of fixed effects and different scales of measurement of evaluated traits.     

A genome‐wide association study suggests new candidate genes for milk production traits in Chinese Holstein cattle

A genome‐wide association study (GWAS) was conducted on 15 milk production traits in Chinese Holstein. The experimental population consisted of 445 cattle, each genotyped by the GGP (GeneSeek genomic profiling)‐BovineLD V3 SNP chip, which had 26 151 public SNPs in its manifest file. After data cleaning, 20 326 SNPs were retained for the GWAS. The phenotypes were estimated breeding values of traits, provided by a public dairy herd improvement program center that had been collected once a month for 3 years. Two statistical models, a fixed‐effect linear regression model and a mixed‐effect linear model, were used to estimate the association effects of SNPs on each of the phenotypes. Genome‐wide significant and suggestive thresholds were set at 2.46E‐06 and 4.95E‐05 respectively. The two statistical models concurrently identified two genome‐wide significant (P < 0.05) SNPs on milk production traits in this Chinese Holstein population. The positional candidate genes, which were the ones closest to these two identified SNPs, were EEF2K (eukaryotic elongation factor 2 kinase) and KLHL1 (kelch like family member 1). These two genes could serve as new candidate genes for milk yield and lactation persistence, yet their roles need to be verified in further function studies.     

Genetic‐based dissection of arsenic accumulation in maize using a genome‐wide association analysis method

Understanding the mechanism of arsenic (As) accumulation in plants is important in reducing As's toxicity to plants and its potential risks to human health. Here, we performed a genome‐wide association study to dissect the genetic basis of the As contents of different maize tissues in Xixian, which was irrigated with As‐rich surface water, and Changge using an association population consisting of 230 representative maize inbred lines. Phenotypic data revealed a wide normal distribution and high repeatability for the As contents in maize tissues. The As concentrations in maize tissues followed the same trend in the two locations: kernels < axes < stems < bracts < leaves. In total, 15, 16 and 15 non‐redundant quantitative trait loci (QTL s) associated with As concentrations were identified (P  ≤ 2.04 × 10^?6) in five tissues from Xixian, Changge, and the combination of the locations, respectively, explaining 9.70%–24.65% of the phenotypic variation for each QTL , on average. Additionally, four QTL s [involving 15 single nucleotide polymorphisms (SNP s)] were detected in the single and the combined locations, indicating that these loci/SNP s might be stable across different environments. The candidate genes associated with these four loci were predicted. In addition, four non‐redundant QTL s (6 SNP s), including a QTL that was detected in multiple locations according to the genome‐wide association study, were found to co‐localize with four previously reported QTL intervals. These results are valuable to understand the genetic architecture of As mechanism in maize and facilitate the genetic improvement of varieties without As toxicity.     

A genome‐wide association study using selective DNA pooling identifies candidate markers for fertility in Holstein cattle

The decline in the reproductive efficiency of dairy cows, especially those with high producing potential, has become a challenging problem. In this study, a selective DNA pooling approach was applied to a cow population whose oocytes were fertilized and cultured to obtain phenotypic records of fertilization rate and blastocyst rate. Using a stringent 5% genome‐wide significance level, 22 and five single nucleotide polymorphisms (SNPs) were found to be associated with fertilization rate and blastocyst rate, respectively. SNPs that showed significant association in selective DNA pooling were further evaluated by individual genotyping. Interestingly, the majority of the SNP associations were confirmed by individual genotyping, testifying to the effectiveness of selective DNA pooling using a high‐density SNP genotyping array. This study is the first application of the selective DNA pooling approach using the BovineSNP50 array in cattle.     

A genome‐wide scan for copy number variations using high‐density single nucleotide polymorphism array in Simmental cattle

Copy number variations (CNVs) have recently been identified as promising sources of genetic variation, complementary to single nucleotide polymorphisms (SNPs). As a result, detection of CNVs has attracted a great deal of attention. In this study, we performed genome‐wide CNV detection using Illumina Bovine HD BeadChip (770k) data on 792 Simmental cattle. A total of 263 CNV regions (CNVRs) were identified, which included 137 losses, 102 gains and 24 regions classified as both loss and gain, covering 35.48 Mb (1.41%) of the bovine genome. The length of these CNVRs ranged from 10.18 kb to 1.76 Mb, with an average length of 134.78 kb and a median length of 61.95 kb. In 136 of these regions, a total of 313 genes were identified related to biological functions such as transmembrane activity and olfactory transduction activity. To validate the results, we performed quantitative PCR to detect nine randomly selected CNVRs and successfully confirmed seven (77.6%) of them. Our results present a map of cattle CNVs derived from high‐density SNP data, which expands the current CNV map of the cattle genome and provides useful information for investigation of genomic structural variation in cattle.     

A genome‐wide association study of coping behaviors suggests FBXO45 is associated with emotional expression

Individuals use coping behaviors to deal with unpleasant daily events. Such behaviors can moderate or mediate the pathway between psychosocial stress and health‐related outcomes. However, few studies have examined the associations between coping behaviors and genetic variants. We conducted a genome‐wide association study (GWAS) on coping behaviors in 14088 participants aged 35 to 69 years as part of the Japan Multi‐Institutional Collaborative Cohort Study. Five coping behaviors (emotional expression, emotional support seeking, positive reappraisal, problem solving and disengagement) were measured and analyzed. A GWAS analysis was performed using a mixed linear model adjusted for study area, age and sex. Variants with suggestive significance in the discovery phase (N = 6403) were further examined in the replication phase (N = 7685). We then combined variant‐level association evidence into gene‐level evidence using a gene‐based analysis. The results showed a significant genetic contribution to emotional expression and disengagement, with an estimation that the 19.5% and 6.6% variance in the liability‐scale was explained by common variants. In the discovery phase, 12 variants met suggestive significance (P < 1 × 10^?6) for association with the coping behaviors and perceived stress. However, none of these associations were confirmed in the replication stage. In gene‐based analysis, FBXO45, a gene with regulatory roles in synapse maturation, was significantly associated with emotional expression after multiple corrections (P < 3.1 × 10^?6). In conclusion, our results showed the existence of up to 20% genetic contribution to coping behaviors. Moreover, our gene‐based analysis using GWAS data suggests that genetic variations in FBXO45 are associated with emotional expression.     

A genome‐wide association study identifies a region strongly associated with symmetrical onychomadesis on chromosome 12 in dogs

Symmetrical onychomadesis causes periodic loss of claws in otherwise healthy dogs. Genome‐wide association analysis in 225 Gordon Setters identified a single region associated with symmetrical onychomadesis on chromosome 12 (spanning about 3.3 mb). A meta‐analysis including also English Setters indicated that this genomic region predisposes for symmetrical onychomadesis in English Setters as well. The associated region spans most of the major histocompatibility complex and nearly 1 Mb downstream. Like many other autoimmune diseases, associations of symmetrical onychomadesis with DLA class II alleles have been reported. In this study, no associated markers were revealed within any of the DLA‐DRB1, ‐DQA1 or ‐DQB1 genes, and the odds for symmetrical onychomadesis in the Gordon Setters were much higher, carrying significant single nucleotide polymorphisms compared to the odds of any of the recorded DLA‐DRB1/DQA1/DQB1 haplotypes. We noticed that some of the associated DLA haplotypes were different between the English Setters and the Gordon Setters. Interestingly, associated SNP chip markers showed a more consistent pattern of allelic variants related to cases or controls regardless of breed. In conclusion, the associated genetic markers identified in this study hold the potential to aid in selection of breeding animals to reduce the frequency of symmetrical onychomadesis in the dog.     

A genome‐wide association analysis for carcass traits in a commercial Duroc pig population

We performed a genome‐wide association study to map the genetic determinants of carcass traits in 350 Duroc pigs typed with the Porcine SNP60 BeadChip. Association analyses were carried out using the gemma software. The proportion of phenotypic variance explained by the SNPs ranged between negligible to moderate (= 0.01–0.30) depending on the trait under consideration. At the genome‐wide level, we detected one significant association between backfat thickness between the 3^rd and 4^th ribs and six SNPs mapping to SSC12 (37–40 Mb). We also identified several chromosome‐wide significant associations for ham weight (SSC11: 51–53 Mb, three SNPs; 67–68 Mb, two SNPs), carcass weight (SSC11: 66–68 Mb, two SNPs), backfat thickness between the 3^rd and 4^th ribs (SSC12: 21 Mb, one SNP; 33–40 Mb, 17 SNPs; 51–58 Mb, two SNPs), backfat thickness in the last rib (SSC12: 37 Mb, one SNP; 40–41 Mb, nine SNPs) and lean meat content (SSC13: 34 Mb, three SNPs and SSC16: 45.1 Mb, one SNP; 62–63 Mb, 10 SNPs; 71–75 Mb, nine SNPs). The ham weight trait‐associated region on SSC11 contains two genes (UCHL3 and LMO7) related to muscle development. In addition, the ACACA gene, which encodes an enzyme for the catalysis of fatty acid synthesis, maps to the SSC12 (37–41 Mb) region harbouring trait‐associated regions for backfat thickness traits. Sequencing of these candidate genes may help to uncover the causal mutations responsible for the associations found in the present study.     

Metabolome‐genome‐wide association study dissects genetic architecture for generating natural variation in rice secondary metabolism

Plants produce structurally diverse secondary (specialized) metabolites to increase their fitness for survival under adverse environments. Several bioactive compounds for new drugs have been identified through screening of plant extracts. In this study, genome‐wide association studies (GWAS) were conducted to investigate the genetic architecture behind the natural variation of rice secondary metabolites. GWAS using the metabolome data of 175 rice accessions successfully identified 323 associations among 143 single nucleotide polymorphisms (SNPs) and 89 metabolites. The data analysis highlighted that levels of many metabolites are tightly associated with a small number of strong quantitative trait loci (QTLs). The tight association may be a mechanism generating strains with distinct metabolic composition through the crossing of two different strains. The results indicate that one plant species produces more diverse phytochemicals than previously expected, and plants still contain many useful compounds for human applications.     

Pathway analysis of genome‐wide association datasets of personality traits

Although several genome‐wide association (GWA) studies of human personality have been recently published, genetic variants that are highly associated with certain personality traits remain unknown, due to difficulty reproducing results. To further investigate these genetic variants, we assessed biological pathways using GWA datasets. Pathway analysis using GWA data was performed on 1089 Korean women whose personality traits were measured with the Revised NEO Personality Inventory for the 5‐factor model of personality. A total of 1042 pathways containing 8297 genes were included in our study. Of these, 14 pathways were highly enriched with association signals that were validated in 1490 independent samples. These pathways include association of: Neuroticism with axon guidance [L1 cell adhesion molecule (L1CAM) interactions]; Extraversion with neuronal system and voltage‐gated potassium channels; Agreeableness with L1CAM interaction, neurotransmitter receptor binding and downstream transmission in postsynaptic cells; and Conscientiousness with the interferon‐gamma and platelet‐derived growth factor receptor beta polypeptide pathways. Several genes that contribute to top‐ranked pathways in this study were previously identified in GWA studies or by pathway analysis in schizophrenia or other neuropsychiatric disorders. Here we report the first pathway analysis of all five personality traits. Importantly, our analysis identified novel pathways that contribute to understanding the etiology of personality traits.     

Genome‐wide association study identifies variants in the CAPN9 gene associated with umbilical hernia in pigs

Pig umbilical hernia (UH) affects pig welfare and brings considerable economic loss to the pig industry. To date, the molecular mechanisms underlying pig UH are still poorly understood. To identify potential loci for susceptibility to this disease, we performed a genome‐wide association study in an Erhualian × Shaziling F₂ intercross population. A total of 45 animals were genotyped using Illumina Porcine SNP60 BeadChips. We observed a SNP (rs80993347) located in the calpain‐9 (CAPN9) gene on Sus scrofa chromosome 14 that was significantly associated with UH (P = 1.97 × 10^?10). Then, we identified a synonymous mutation rs321865883 (g.20164T>C) in exon 10 of the CAPN9 gene that distinguished two affected individuals (CC) from their normal full‐sibs (TC). Finally, quantitative polymerase chain reaction was explored to investigate the mRNA expression profile of the CAPN9 gene in 12 tissues in Yorkshire pigs at different developmental stages (3, 90 and 180 days). CAPN9 showed high expression levels in the gastrointestinal tract at these three growth stages. The results of this study indicate that the CAPN9 gene might be implicated in UH. Further studies are required to establish a role of CAPN9 in pig UH.     

Metabolite‐based genome‐wide association study enables dissection of the flavonoid decoration pathway of wheat kernels

The marriage of metabolomic approaches with genetic design has proven a powerful tool in dissecting diversity in the metabolome and has additionally enhanced our understanding of complex traits. That said, such studies have rarely been carried out in wheat. In this study, we detected 805 metabolites from wheat kernels and profiled their relative contents among 182 wheat accessions, conducting a metabolite‐based genome‐wide association study (mGWAS) utilizing 14 646 previously described polymorphic SNP markers. A total of 1098 mGWAS associations were detected with large effects, within which 26 candidate genes were tentatively designated for 42 loci. Enzymatic assay of two candidates indicated they could catalyse glucosylation and subsequent malonylation of various flavonoids and thereby the major flavonoid decoration pathway of wheat kernel was dissected. Moreover, numerous high‐confidence genes associated with metabolite contents have been provided, as well as more subdivided metabolite networks which are yet to be explored within our data. These combined efforts presented the first step towards realizing metabolomics‐associated breeding of wheat.     

A genome‐wide association study of bipolar disorder and comorbid migraine

Both migraine and bipolar affective disorder (BPAD) are complex phenotypes with significant genetic and nongenetic components. Epidemiological and clinical studies have showed a high degree of comorbidity between migraine and BPAD, and overlapping regions of linkage have been shown in numerous genome‐wide linkage studies. To identify susceptibility factors for the BPAD/migraine phenotype, we conducted a genome‐wide association study (GWAS) in 1001 cases with bipolar disorder collected through the NIMH Genetics Initiative for Bipolar Disorder and genotyped at 1 m single‐nucleotide polymorphisms (SNPs) as part of the Genetic Association Information Network (GAIN). We compared BPAD patients without any headache (n = 699) with BPAD patients with doctor diagnosed migraine (n = 56). The strongest evidence for association was found for several SNPs in a 317‐kb region encompassing the uncharacterized geneKIAA0564 {e.g. rs9566845 [OR = 4.98 (95% CI: 2.6–9.48), P = 7.7 × 10^?8] and rs9566867 (P = 8.2 × 10^?8)}. Although the level of signficance was significantly reduced when using the Fisher's exact test (as a result of the low count of cases with migraine), rs9566845 P = 1.4 × 10^?5 and rs9566867 P = 1.5 × 10^?5, this region remained the most prominent finding. Furthermore, marker rs9566845 was genotyped and found associated with migraine in an independent Norwegian sample of adult attention deficit hyperactivity disorder (ADHD) patients with and without comorbid migraine (n = 131 and n = 324, respectively), OR = 2.42 (1.18–4.97), P = 0.013. This is the first GWAS examining patients with bipolar disorder and comorbid migraine. These data suggest that genetic variants in the KIAA0564 gene region may predispose to migraine headaches in subgroups of patients with both BPAD and ADHD.     

A genome‐wide association study for gestation length in swine

Selection for increased litter size in swine has potentially resulted in a correlated increase in preweaning mortality. Additional selection criteria should be considered when selecting for increased litter size to account for associated decreases in piglet quality, specifically piglet survival, initial weight and growth. Traits such as gestation length (GL), which have been associated with piglet performance, could be utilized to improve piglet development and survivability. The objective of this study was to conduct a genome‐wide association study to identify genomic regions associated with GL in differing parities in swine (n = 831) from the University of Nebraska–Lincoln reproductive longevity project. Gestation length was calculated as the number of days between last insemination administered and farrowing. Sows were genotyped with the Illumina SNP60 BeadArray, and the data were analyzed using Bayesian mixture models for GL at parity 1, 2, 3 and 4 (GL1, GL2, GL3 and GL4 respectively). Means (SD) for GL1–GL4 were 113 (1.4), 114 (1.2), 114 (1.3) and 115 (1.2) respectively. Posterior mean heritability estimates (PSD) for GL1, GL2, GL3 and GL4 were 0.33 (0.06), 0.34 (0.07), 0.32 (0.08) and 0.20 (0.08) respectively. Rank correlations between genomic estimated breeding values between GL1 and GL2, GL3 and GL4 respectively were moderate: 0.67, 0.65 and 0.60. The top SNP (ASGA0017859, SSC4, 7.8 Mb), located in the top common genomic region associated with GL1, GL2 and GL3, was associated with a difference of 1.1 days in GL1 between homozygote genotypes (P < 0.0001). The results of this study suggest that GL is a largely polygenic trait with relatively minor contributions from multiple genomic regions.