Genome-wide association and genomic selection in animal breeding

Results from genome-wide association studies in livestock, and humans, has lead to the conclusion that the effect of individual quantitative trait loci (QTL) on complex traits, such as yield, are likely to be small; therefore, a large number of QTL are necessary to explain genetic variation in these traits. Given this genetic architecture, gains from marker-assisted selection (MAS) programs using only a small number of DNA markers to trace a limited number of QTL is likely to be small. This has lead to the development of alternative technology for using the available dense single nucleotide polymorphism (SNP) information, called genomic selection. Genomic selection uses a genome-wide panel of dense markers so that all QTL are likely to be in linkage disequilibrium with at least one SNP. The genomic breeding values are predicted to be the sum of the effect of these SNPs across the entire genome. In dairy cattle breeding, the accuracy of genomic estimated breeding values (GEBV) that can be achieved and the fact that these are available early in life have lead to rapid adoption of the technology. Here, we discuss the design of experiments necessary to achieve accurate prediction of GEBV in future generations in terms of the number of markers necessary and the size of the reference population where marker effects are estimated. We also present a simple method for implementing genomic selection using a genomic relationship matrix. Future challenges discussed include using whole genome sequence data to improve the accuracy of genomic selection and management of inbreeding through genomic relationships.     

Genome-wide association mapping of fruit-quality traits using genotyping-by-sequencing approach in citrus landraces,modern cultivars,and breeding lines in Japan

Association mapping is an attractive method to identify QTLs in perennial horticultural crops such as citrus, as it does not need a designed cross between parental genotypes and can save time and labor to construct a segregating population. It usually requires more genetic markers than linkage-based QTL mapping owing to a lower degree of linkage disequilibrium (LD). However, recent advances in next-generation sequencing offer high-throughput, cost-effective methods, including genotyping-by-sequencing (GBS), for genotyping massive amounts of single nucleotide polymorphisms (SNPs). In this study, we performed a genome-wide association study (GWAS) of fruit-quality traits in citrus using SNPs obtained by GBS. We evaluated 110 citrus accessions, including landraces, modern cultivars, and breeding lines, for eight fruit-quality traits (fruit weight, fruit skin color, fruit surface texture, peelability, pulp firmness, segment firmness, sugar content, and acid content) during 2005 to 2012 (except 2007). GBS found 2309 SNPs, which we anchored to the clementine reference genome. We evaluated LD in the 110 accessions and confirmed that GBS gave enough SNPs to conduct GWAS. We identified seven QTLs, including four novel ones, comprising four significant QTLs for fruit weight and one QTL each for fruit skin color, pulp firmness, and segment firmness. These QTLs offer promise for use in citrus crossbreeding.     

A genome‐wide association study to detect genetic variation for postpartum dysgalactia syndrome in five commercial pig breeding lines

Postpartum dysgalactia syndrome (PDS) in sows is an important disease after parturition with a relevant economic impact, affecting the health and welfare of both sows and piglets. The genetic background of this disease has been discussed and its heritability estimated, but further genetic analyses are lacking in detail. The aim of the current study was to detect loci affecting the susceptibility to PDS through a genome‐wide association approach. The study was designed as a family‐based association study with matched sampling of affected sows and healthy half‐ or full‐sib control sows on six farms. For the study, 597 sows (322 affected vs. 275 healthy control sows) were genotyped on 62 163 single nucleotide polymorphisms (SNPs) using the Illumina PorcineSNP60 BeadChip. After quality control, 585 sows (314 affected vs. 271 healthy control sows) and 49 740 SNPs remained for further analysis. Statistics were performed mainly with the r package genabel and included a principal component analysis. A statistically significant genome‐wide associated SNP was identified on porcine chromosome (SSC) 17. Further promising results with moderate significance were detected on SSC 13 and on an unplaced scaffold with an older annotation on SSC 15. The PRICKLE2 and NRP2 genes were identified as candidate genes near associated SNPs. Several quantitative trait loci (QTL) have been previously described in these genomic regions, including QTL for mammary gland condition, as teat number and non‐functional nipples QTL, as well as QTL for body temperature and gestation length.     

Genome-wide association analyses reveal significant loci and strong candidate genes for growth and fatness traits in two pig populations

Background

Recently, genome-wide association studies (GWAS) have been reported on various pig traits. We performed a GWAS to analyze 22 traits related to growth and fatness on two pig populations: a White Duroc × Erhualian F₂ intercross population and a Chinese Sutai half-sib population.

Results

We identified 14 and 39 loci that displayed significant associations with growth and fatness traits at the genome-wide level and chromosome-wide level, respectively. The strongest association was between a 750 kb region on SSC7 (SSC for Sus scrofa) and backfat thickness at the first rib. This region had pleiotropic effects on both fatness and growth traits in F₂ animals and contained a promising candidate gene HMGA1 (high mobility group AT-hook 1). Unexpectedly, population genetic analysis revealed that the allele at this locus that reduces fatness and increases growth is derived from Chinese indigenous pigs and segregates in multiple Chinese breeds. The second strongest association was between the region around 82.85 Mb on SSC4 and average backfat thickness. PLAG1 (pleiomorphic adenoma gene 1), a gene under strong selection in European domestic pigs, is proximal to the top SNP and stands out as a strong candidate gene. On SSC2, a locus that significantly affects fatness traits mapped to the region around the IGF2 (insulin-like growth factor 2) gene but its non-imprinting inheritance excluded IGF2 as a candidate gene. A significant locus was also detected within a recombination cold spot that spans more than 30 Mb on SSCX, which hampered the identification of plausible candidate genes. Notably, no genome-wide significant locus was shared by the two experimental populations; different loci were observed that had both constant and time-specific effects on growth traits at different stages, which illustrates the complex genetic architecture of these traits.

Conclusions

We confirm several previously reported QTL and provide a list of novel loci for porcine growth and fatness traits in two experimental populations with Chinese Taihu and Western pigs as common founders. We showed that distinct loci exist for these traits in the two populations and identified HMGA1 and PLAG1 as strong candidate genes on SSC7 and SSC4, respectively.

Electronic supplementary material

The online version of this article (doi:10.1186/s12711-015-0089-5) contains supplementary material, which is available to authorized users.     

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.     

Genome-wide association study (GWAS) of salt tolerance in worldwide soybean germplasm lines

Salt is a severe abiotic stress causing soybean yield loss in saline soils and irrigated fields. Marker-assisted selection (MAS) is a powerful genomic tool for improving the efficiency of breeding salt-tolerant soybean varieties. The objectives of this study were to uncover novel single-nucleotide polymorphisms (SNPs) and quantitative trait loci (QTLs) associated with salt tolerance and to confirm the previously identified genomic regions and SNPs for salt tolerance. A total of 283 diverse soybean plant introductions (PIs) were screened for salt tolerance in the greenhouse based on leaf chloride concentrations and leaf chlorophyll concentrations after 12–18 days of 120-mM NaCl treatment. A total of 33,009 SNPs across 283 genotypes from the Illumina Infinium SoySNP50K BeadChip database were employed in the association analysis with leaf chloride concentrations and leaf chlorophyll concentrations. Genome-wide association mapping showed that 45 SNPs representing nine genomic regions on chromosomes (Chr.) 2, 3, 7, 8, 10, 13, 14, 16, and 20 were significantly associated with both leaf chloride concentrations and leaf chlorophyll concentrations in 2014, 2015, and combined years. A total of 31 SNPs on Chr. 3 were mapped at or near the previously reported major salt tolerance QTL. The significant SNP on Chr. 2 was also in proximity to the previously reported SNP for salt tolerance. The other significant SNPs represent seven putative novel QTLs for salt tolerance. The significant SNP markers on Chr. 2, 3, 14, 16, and 20, which were identified in both general linear model and mixed linear model, were highly recommended for MAS in breeding salt-tolerant soybean varieties.     

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.     

Genome-wide association study of reproductive traits in Nellore heifers using Bayesian inference

Background

An important goal of Zebu breeding programs is to improve reproductive performance. A major problem faced with the genetic improvement of reproductive traits is that recording the time for an animal to reach sexual maturity is costly. Another issue is that accurate estimates of breeding values are obtained only a long time after the young bulls have gone through selection. An alternative to overcome these problems is to use traits that are indicators of the reproductive efficiency of the herd and are easier to measure, such as age at first calving. Another problem is that heifers that have conceived once may fail to conceive in the next breeding season, which increases production costs. Thus, increasing heifer’s rebreeding rates should improve the economic efficiency of the herd. Response to selection for these traits tends to be slow, since they have a low heritability and phenotypic information is provided only later in the life of the animal. Genome-wide association studies (GWAS) are useful to investigate the genetic mechanisms that underlie these traits by identifying the genes and metabolic pathways involved.

Results

Data from 1853 females belonging to the Agricultural Jacarezinho LTDA were used. Genotyping was performed using the BovineHD BeadChip (777 962 single nucleotide polymorphisms (SNPs)) according to the protocol of Illumina - Infinium Assay II ® Multi-Sample HiScan with the unit SQ ™ System. After quality control, 305 348 SNPs were used for GWAS. Forty-two and 19 SNPs had a Bayes factor greater than 150 for heifer rebreeding and age at first calving, respectively. All significant SNPs for age at first calving were significant for heifer rebreeding. These 42 SNPs were next or within 35 genes that were distributed over 18 chromosomes and comprised 27 protein-encoding genes, six pseudogenes and two miscellaneous noncoding RNAs.

Conclusions

The use of Bayes factor to determine the significance of SNPs allowed us to identify two sets of 42 and 19 significant SNPs for heifer rebreeding and age at first calving, respectively, which explain 11.35 % and 6.42 % of their phenotypic variance, respectively. These SNPs provide relevant information to help elucidate which genes affect these traits.     

Genome-wide association study of insect bite hypersensitivity in two horse populations in the Netherlands

Background

Insect bite hypersensitivity is a common allergic disease in horse populations worldwide. Insect bite hypersensitivity is affected by both environmental and genetic factors. However, little is known about genes contributing to the genetic variance associated with insect bite hypersensitivity. Therefore, the aim of our study was to identify and quantify genomic associations with insect bite hypersensitivity in Shetland pony mares and Icelandic horses in the Netherlands.

Methods

Data on 200 Shetland pony mares and 146 Icelandic horses were collected according to a matched case–control design. Cases and controls were matched on various factors (e.g. region, sire) to minimize effects of population stratification. Breed-specific genome-wide association studies were performed using 70 k single nucleotide polymorphisms genotypes. Bayesian variable selection method Bayes-C with a threshold model implemented in GenSel software was applied. A 1 Mb non-overlapping window approach that accumulated contributions of adjacent single nucleotide polymorphisms was used to identify associated genomic regions.

Results

The percentage of variance explained by all single nucleotide polymorphisms was 13% in Shetland pony mares and 28% in Icelandic horses. The 20 non-overlapping windows explaining the largest percentages of genetic variance were found on nine chromosomes in Shetland pony mares and on 14 chromosomes in Icelandic horses. Overlap in identified associated genomic regions between breeds would suggest interesting candidate regions to follow-up on. Such regions common to both breeds (within 15 Mb) were found on chromosomes 3, 7, 11, 20 and 23. Positional candidate genes within 2 Mb from the associated windows were identified on chromosome 20 in both breeds. Candidate genes are within the equine lymphocyte antigen class II region, which evokes an immune response by recognizing many foreign molecules.

Conclusions

The genome-wide association study identified several genomic regions associated with insect bite hypersensitivity in Shetland pony mares and Icelandic horses. On chromosome 20, associated genomic regions in both breeds were within 2 Mb from the equine lymphocyte antigen class II region. Increased knowledge on insect bite hypersensitivity associated genes will contribute to our understanding of its biology, enabling more efficient selection, therapy and prevention to decrease insect bite hypersensitivity prevalence.     

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 stochastic simulation study on using different models for prediction of breeding values while changing the breeding goal

In a stochastic simulation study the effect of simultaneously changing the model for prediction of breeding values and changing the breeding goal was studied. A population of 100 000 cows with registrations on seven traits was simulated in two steps. In the first step of 15 years the population was selected for production and mastitis occurrence using a univariate model for prediction of breeding values for production and a trivariate model using information on mastitis treatments, udder depth and somatic cell score for prediction of breeding values for mastitis occurrence. In the second step six different scenarios were set up and simulated for 15 years combining two different breeding goals and three different models for prediction of breeding values in 20 replicates. Breeding goal 1 had relative economic value per genetic standard deviation on production (19.4) and mastitis occurrence ( − 50) whereas breeding goal 2 had a economic value on production (19.4), udder depth (4.2), mastitis occurrence ( − 50), non return rate (13.0) and days open ( − 16.75). Model 1 was a model similar to the one used in the first 15 years. Model 2 was an approximate multitrait model where solutions for fixed effects from a model corresponding to model 1 were subtracted from the phenotypes and a multitrait model with an overall mean, a year effect, an additive genetic and a residual effect were applied. Model 3 was a full multitrait model. Average genetic trends for total merit and each individual trait over 20 replicates were compared for each scenario. With the number of replicates the genetic responses using model 2 and 3 were not significant different. With a broad breeding goal using, model 2 or model 3 gave a significantly higher response in total merit than using model 1. Using a narrow breeding goal there was no significant difference between models used for prediction of breeding values. Results showed that with a breeding goal with a lot of emphasis on low heritable traits with a high economic value using a multitrait methodology for prediction of breeding values will redistribute the genetic progress in the total merit index. More gain will come from the low heritable traits in the breeding goal and less from traits with higher heritability. With a broad breeding goal and exploiting the available information in the data the inbreeding coefficient increased though not significantly.     

Genome-wide association study for longevity in the Holstein cattle population

Longevity is one of the most important traits determining dairy cow profitability. In the last decades dairy cows suffered a lowering in the age at culling. With the aim to identify the genes involved in longevity, dates of birth, yields, dates of calving during lifespan and culling dates were collected for 946 culled cows which had been genotyped with the Bovine High Density panel. Using the GenABEL package in R, genome-wide association analysis was performed on three potential traits of longevity: (1) ‘days in production,’ (2) ‘days in herd,’ (3) number of calvings over lifespan.’ Five genome-wide significant single nucleotide polymorphisms (SNPs) associated with all three longevity traits were detected. Several consecutive SNPs identified on chromosomes 16 and 30 indicated the presence of two suggestive quantitative trait loci (QTL). The genes comprised in the QTL regions had biological functions related to fertility, reproductive disorders, heat stress and welfare of cows. These findings might contribute to improving breeding strategies to improve longevity.     

Genome-wide association study for growth and fatness traits in Chinese Sujiang pigs

Growth and fatness traits are complex and economically important traits in the pig industry. The molecular basis underlying porcine growth and fatness traits remains largely unknown. To uncover genetic loci and candidate genes for these traits, we explored the GeneSeek GGP Porcine 80K SNP chip to perform a GWAS for seven growth and fatness traits in 365 individuals from the Sujiang pig, a recently developed breed in China. We identified two, 17, one and 11 SNPs surpassing the suggestively significant threshold (P < 1.86 × 10⁻⁵) for body weight, chest circumference, chest width and backfat thickness respectively. Of these SNPs, 20 represent novel genetic loci, and five and four SNPs were respectively associated with chest circumference and backfat thickness at a genome-wide significant threshold (P < 9.31 × 10⁻⁷). Eight SNPs had a pleiotropic effect on both chest circumference and backfat thickness. The most remarkable locus resided in a region between 72.95 and 76.27 Mb on pig chromosome 4, harboring a number of previously reported quantitative trait loci related to backfat deposition. In addition to two reported genes (PLAG1 and TAS2R38), we identified four genes including GABRB3, ZNF106, XKR4 and MGAM as novel candidates for body weight and backfat thickness at the mapped loci. Our findings provide insights into the genetic architecture of porcine growth and fatness traits and potential markers for selective breeding of Chinese Sujiang pigs.     

Genome-wide association study for atopy and allergic rhinitis in a Singapore Chinese population

Allergic rhinitis (AR) is an atopic disease which affects about 600 million people worldwide and results from a complex interplay between genetic and environmental factors. However genetic association studies on known candidate genes yielded variable results. The aim of this study is to identify the genetic variants that influence predisposition towards allergic rhinitis in an ethnic Chinese population in Singapore using a genome-wide association study (GWAS) approach. A total of 4461 ethnic Chinese volunteers were recruited in Singapore and classified according to their allergic disease status. The GWAS included a discovery stage comparing 515 atopic cases (including 456 AR cases) and 486 non-allergic non-rhinitis (NANR) controls. The top SNPs were then validated in a replication cohort consisting of a separate 2323 atopic cases (including 676 AR cases) and 511 NANR controls. Two SNPs showed consistent association in both discovery and replication phases; MRPL4 SNP rs8111930 on 19q13.2 (OR = 0.69, P_combined = 4.46×10⁻⁰⁵) and BCAP SNP rs505010 on chromosome 10q24.1 (OR = 0.64, P_combined = 1.10×10⁻⁰⁴). In addition, we also replicated multiple associations within known candidates regions such as HLA-DQ and NPSR1 locus in the discovery phase. Our study suggests that MRPL4 and BCAP, key components of the HIF-1α and PI3K/Akt signaling pathways respectively, are two novel candidate genes for atopy and allergic rhinitis. Further study on these molecules and their signaling pathways would help in understanding of the pathogenesis of allergic rhinitis and identification of targets for new therapeutic intervention.     

Stress neuroendocrine profiles in five pig breeding lines and the relationship with carcass composition

Stress neuroendocrine systems (hypothalamic–pituitary–adrenal axis and sympathetic nervous system) were studied in 100 female pigs from each of the five main genetic lines used in Europe for pork production: Piétrain, Large White, Landrace, Duroc and Meishan. Levels of cortisol and catecholamines were measured in urine collected at the farm, after transportation to the slaughterhouse and the next morning before slaughter. With the exception of the Piétrain line that showed intermediate levels of cortisol despite its extreme leanness, a significant positive relationship was found between basal cortisol levels and fatness, both across and within (except in Piétrain and Duroc) lines. Basal cortisol levels were 2.46-fold higher in Meishan (20.46 ng/mg creatinine) than in Large White pigs (8.30 ng/mg creatinine), the two extreme breeds. Post-transportation levels were highest but proportional to basal levels, suggesting that the adrenal reactivity to adrenocorticotropic hormone is a major source of variability between lines. Levels of catecholamines were less variable between lines but correlated also with fatness, partlyviapartial correlations with cortisol levels. In serum collected at exsanguination, creatine kinase activity was correlated with muscularity across the five breeds. However, this was due to a much larger activity than expected in Piétrain pigs, although all animals were negative for the allele of the ryanodine receptor gene responsible for stress sensitivity. Serum glucose levels were inversely related to fatness. These data show that the differences between breeds or lines can be utilised by cross-breeding and that this can lead to changes in stress hormones and in turn to some degree of changes in carcass traits.     

Genome-wide association study identifies candidate genes for male fertility traits in humans

Despite the fact that hundreds of genes are known to affect fertility in animal models, relatively little is known about genes that influence natural fertility in humans. To broadly survey genes contributing to variation in male fertility, we conducted a genome-wide association study (GWAS) of two fertility traits (family size and birth rate) in 269 married men who are members of a founder population of European descent that proscribes contraception and has large family sizes. Associations between ～250,000 autosomal SNPs and the fertility traits were examined. A total of 41 SNPs with p ≤ 1 × 10(-4) for either trait were taken forward to a validation study of 123 ethnically diverse men from Chicago who had previously undergone semen analyses. Nine (22%) of the SNPs associated with reduced fertility in the GWAS were also associated with one or more of the ten measures of reduced sperm quantity and/or function, yielding 27 associations with p values < 0.05 and seven with p values < 0.01 in the validation study. On the basis of 5,000 permutations of our data, the probabilities of observing this many or more small p values were 0.0014 and 5.6 × 10(-4), respectively. Among the nine associated loci, outstanding candidates for male fertility genes include USP8, an essential deubiquitinating enzyme that has a role in acrosome assembly; UBD and EPSTI1, which have potential roles in innate immunity; and LRRC32, which encodes a latent transforming growth factor β (TGF-β) receptor on regulatory T cells. We suggest that mutations in these genes that are more severe may account for some of the unexplained infertility (or subfertility) in the general population.     

Genome-wide association study for soybean mosaic virus SC3 resistance in soybean

Molecular Breeding - Meloidogyne graminicola is one of the most important plant-parasitic nematodes in rice. Breeding for natural resistance and tolerance is considered one of the most economical...     

Genome-wide association study for oat (Avena sativa L.) beta-glucan concentration using germplasm of worldwide origin

Detection of quantitative trait loci (QTL) controlling complex traits followed by selection has become a common approach for selection in crop plants. The QTL are most often identified by linkage mapping using experimental F₂, backcross, advanced inbred, or doubled haploid families. An alternative approach for QTL detection are genome-wide association studies (GWAS) that use pre-existing lines such as those found in breeding programs. We explored the implementation of GWAS in oat (Avena sativa L.) to identify QTL affecting β-glucan concentration, a soluble dietary fiber with several human health benefits when consumed as a whole grain. A total of 431 lines of worldwide origin were tested over 2?years and genotyped using Diversity Array Technology (DArT) markers. A mixed model approach was used where both population structure fixed effects and pair-wise kinship random effects were included. Various mixed models that differed with respect to population structure and kinship were tested for their ability to control for false positives. As expected, given the level of population structure previously described in oat, population structure did not play a large role in controlling for false positives. Three independent markers were significantly associated with β-glucan concentration. Significant marker sequences were compared with rice and one of the three showed sequence homology to genes localized on rice chromosome seven adjacent to the CslF gene family, known to have β-glucan synthase function. Results indicate that GWAS in oat can be a successful option for QTL detection, more so with future development of higher-density markers.