Genomic selection of purebred animals for crossbred performance in the presence of dominant gene action

Background

Genomic selection is an appealing method to select purebreds for crossbred performance. In the case of crossbred records, single nucleotide polymorphism (SNP) effects can be estimated using an additive model or a breed-specific allele model. In most studies, additive gene action is assumed. However, dominance is the likely genetic basis of heterosis. Advantages of incorporating dominance in genomic selection were investigated in a two-way crossbreeding program for a trait with different magnitudes of dominance. Training was carried out only once in the simulation.

Results

When the dominance variance and heterosis were large and overdominance was present, a dominance model including both additive and dominance SNP effects gave substantially greater cumulative response to selection than the additive model. Extra response was the result of an increase in heterosis but at a cost of reduced purebred performance. When the dominance variance and heterosis were realistic but with overdominance, the advantage of the dominance model decreased but was still significant. When overdominance was absent, the dominance model was slightly favored over the additive model, but the difference in response between the models increased as the number of quantitative trait loci increased. This reveals the importance of exploiting dominance even in the absence of overdominance. When there was no dominance, response to selection for the dominance model was as high as for the additive model, indicating robustness of the dominance model. The breed-specific allele model was inferior to the dominance model in all cases and to the additive model except when the dominance variance and heterosis were large and with overdominance. However, the advantage of the dominance model over the breed-specific allele model may decrease as differences in linkage disequilibrium between the breeds increase. Retraining is expected to reduce the advantage of the dominance model over the alternatives, because in general, the advantage becomes important only after five or six generations post-training.

Conclusion

Under dominance and without retraining, genomic selection based on the dominance model is superior to the additive model and the breed-specific allele model to maximize crossbred performance through purebred selection.     

Genomic analysis of dominance effects on milk production and conformation traits in Fleckvieh cattle

Background

Estimates of dominance variance in dairy cattle based on pedigree data vary considerably across traits and amount to up to 50% of the total genetic variance for conformation traits and up to 43% for milk production traits. Using bovine SNP (single nucleotide polymorphism) genotypes, dominance variance can be estimated both at the marker level and at the animal level using genomic dominance effect relationship matrices. Yield deviations of high-density genotyped Fleckvieh cows were used to assess cross-validation accuracy of genomic predictions with additive and dominance models. The potential use of dominance variance in planned matings was also investigated.

Results

Variance components of nine milk production and conformation traits were estimated with additive and dominance models using yield deviations of 1996 Fleckvieh cows and ranged from 3.3% to 50.5% of the total genetic variance. REML and Gibbs sampling estimates showed good concordance. Although standard errors of estimates of dominance variance were rather large, estimates of dominance variance for milk, fat and protein yields, somatic cell score and milkability were significantly different from 0. Cross-validation accuracy of predicted breeding values was higher with genomic models than with the pedigree model. Inclusion of dominance effects did not increase the accuracy of the predicted breeding and total genetic values. Additive and dominance SNP effects for milk yield and protein yield were estimated with a BLUP (best linear unbiased prediction) model and used to calculate expectations of breeding values and total genetic values for putative offspring. Selection on total genetic value instead of breeding value would result in a larger expected total genetic superiority in progeny, i.e. 14.8% for milk yield and 27.8% for protein yield and reduce the expected additive genetic gain only by 4.5% for milk yield and 2.6% for protein yield.

Conclusions

Estimated dominance variance was substantial for most of the analyzed traits. Due to small dominance effect relationships between cows, predictions of individual dominance deviations were very inaccurate and including dominance in the model did not improve prediction accuracy in the cross-validation study. Exploitation of dominance variance in assortative matings was promising and did not appear to severely compromise additive genetic gain.     

GVCBLUP: a computer package for genomic prediction and variance component estimation of additive and dominance effects

Background

Dominance effect may play an important role in genetic variation of complex traits. Full featured and easy-to-use computing tools for genomic prediction and variance component estimation of additive and dominance effects using genome-wide single nucleotide polymorphism (SNP) markers are necessary to understand dominance contribution to a complex trait and to utilize dominance for selecting individuals with favorable genetic potential.

Results

The GVCBLUP package is a shared memory parallel computing tool for genomic prediction and variance component estimation of additive and dominance effects using genome-wide SNP markers. This package currently has three main programs (GREML_CE, GREML_QM, and GCORRMX) and a graphical user interface (GUI) that integrates the three main programs with an existing program for the graphical viewing of SNP additive and dominance effects (GVCeasy). The GREML_CE and GREML_QM programs offer complementary computing advantages with identical results for genomic prediction of breeding values, dominance deviations and genotypic values, and for genomic estimation of additive and dominance variances and heritabilities using a combination of expectation-maximization (EM) algorithm and average information restricted maximum likelihood (AI-REML) algorithm. GREML_CE is designed for large numbers of SNP markers and GREML_QM for large numbers of individuals. Test results showed that GREML_CE could analyze 50,000 individuals with 400 K SNP markers and GREML_QM could analyze 100,000 individuals with 50K SNP markers. GCORRMX calculates genomic additive and dominance relationship matrices using SNP markers. GVCeasy is the GUI for GVCBLUP integrated with an existing software tool for the graphical viewing of SNP effects and a function for editing the parameter files for the three main programs.

Conclusion

The GVCBLUP package is a powerful and versatile computing tool for assessing the type and magnitude of genetic effects affecting a phenotype by estimating whole-genome additive and dominance heritabilities, for genomic prediction of breeding values, dominance deviations and genotypic values, for calculating genomic relationships, and for research and education in genomic prediction and estimation.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2105-15-270) contains supplementary material, which is available to authorized users.     

Non-additive genetic variation in growth,carcass and fertility traits of beef cattle

Background

A better understanding of non-additive variance could lead to increased knowledge on the genetic control and physiology of quantitative traits, and to improved prediction of the genetic value and phenotype of individuals. Genome-wide panels of single nucleotide polymorphisms (SNPs) have been mainly used to map additive effects for quantitative traits, but they can also be used to investigate non-additive effects. We estimated dominance and epistatic effects of SNPs on various traits in beef cattle and the variance explained by dominance, and quantified the increase in accuracy of phenotype prediction by including dominance deviations in its estimation.

Methods

Genotype data (729 068 real or imputed SNPs) and phenotypes on up to 16 traits of 10 191 individuals from Bos taurus, Bos indicus and composite breeds were used. A genome-wide association study was performed by fitting the additive and dominance effects of single SNPs. The dominance variance was estimated by fitting a dominance relationship matrix constructed from the 729 068 SNPs. The accuracy of predicted phenotypic values was evaluated by best linear unbiased prediction using the additive and dominance relationship matrices. Epistatic interactions (additive × additive) were tested between each of the 28 SNPs that are known to have additive effects on multiple traits, and each of the other remaining 729 067 SNPs.

Results

The number of significant dominance effects was greater than expected by chance and most of them were in the direction that is presumed to increase fitness and in the opposite direction to inbreeding depression. Estimates of dominance variance explained by SNPs varied widely between traits, but had large standard errors. The median dominance variance across the 16 traits was equal to 5% of the phenotypic variance. Including a dominance deviation in the prediction did not significantly increase its accuracy for any of the phenotypes. The number of additive × additive epistatic effects that were statistically significant was greater than expected by chance.

Conclusions

Significant dominance and epistatic effects occur for growth, carcass and fertility traits in beef cattle but they are difficult to estimate precisely and including them in phenotype prediction does not increase its accuracy.     

The consequences of including non-additive effects on the genetic evaluation of harvest body weight in Coho salmon (Oncorhynchus kisutch)

Background

In this study, we used different animal models to estimate genetic and environmental variance components on harvest weight in two populations of Oncorhynchus kisutch, forming two classes i.e. odd- and even-year spawners.

Methods

The models used were: additive, with and without inbreeding as a covariable (A + F and A respectively); additive plus common environmental due to full-sib families and inbreeding (A + C + F); additive plus parental dominance and inbreeding (A + D + F); and a full model (A + C + D + F). Genetic parameters and breeding values obtained by different models were compared to evaluate the consequences of including non-additive effects on genetic evaluation.

Results

Including inbreeding as a covariable did not affect the estimation of genetic parameters, but heritability was reduced when dominance or common environmental effects were included. A high heritability for harvest weight was estimated in both populations (even = 0.46 and odd = 0.50) when simple additive models (A + F and A) were used. Heritabilities decreased to 0.21 (even) and 0.37 (odd) when the full model was used (A + C + D + F). In this full model, the magnitude of the dominance variance was 0.19 (even) and 0.06 (odd), while the magnitude of the common environmental effect was lower than 0.01 in both populations. The correlation between breeding values estimated with different models was very high in all cases (i.e. higher than 0.98). However, ranking of the 30 best males and the 100 best females per generation changed when a high dominance variance was estimated, as was the case in one of the two populations (even).

Conclusions

Dominance and common environmental variance may be important components of variance in harvest weight in O. kisutch, thus not including them may produce an overestimation of the predicted response; furthermore, genetic evaluation was seen to be partially affected, since the ranking of selected animals changed with the inclusion of non-additive effects in the animal model.     

Association of selected SNP with carcass and taste panel assessed meat quality traits in a commercial population of Aberdeen Angus-sired beef cattle

Background

The purpose of this study was to evaluate the effects of eight single nucleotide polymorphisms (SNP), previously associated with meat and milk quality traits in cattle, in a population of 443 commercial Aberdeen Angus-cross beef cattle. The eight SNP, which were located within five genes: μ-calpain (CAPN1), calpastatin (CAST), leptin (LEP), growth hormone receptor (GHR) and acylCoA:diacylglycerol acyltransferase 1 (DGAT1), are included in various commercial tests for tenderness, fatness, carcass composition and milk yield/quality.

Methods

A total of 27 traits were examined, 19 relating to carcass quality, such as carcass weight and fatness, one mechanical measure of tenderness, and the remaining seven were sensory traits, such as flavour and tenderness, assessed by a taste panel.

Results

An SNP in the CAPN1 gene, CAPN316, was significantly associated with tenderness measured by both the tenderometer and the taste panel as well as the weight of the hindquarter, where animals inheriting the CC genotype had more tender meat and heavier hindquarters. An SNP in the leptin gene, UASMS2, significantly affected overall liking, where animals with the TT genotype were assigned higher scores by the panellists. The SNP in the GHR gene was significantly associated with odour, where animals inheriting the AA genotype produced steaks with an intense odour when compared with the other genotypes. Finally, the SNP in the DGAT1 gene was associated with sirloin weight after maturation and fat depth surrounding the sirloin, with animals inheriting the AA genotype having heavier sirloins and more fat.

Conclusion

The results of this study confirm some previously documented associations. Furthermore, novel associations have been identified which, following validation in other populations, could be incorporated into breeding programmes to improve meat quality.     

Effects on production traits of haplotypes among casein genes in Norwegian goats and evidence for a site of preferential recombination

In goat milk the most abundant proteins are the casein genes, CSN1S1, CSN2, CSN1S2, and CSN3. Mutations have been identified within these genes affecting the level of gene expression, and effects on milk production traits have been reported. The aim of this study was to detect polymorphisms (SNPs) in the casein genes of Norwegian goats, resolve haplotype structures within the loci, and assess the effect of these haplotypes on milk production traits. Four hundred thirty-six Norwegian bucks were genotyped for 39 polymorphic sites across the four loci. The numbers of unique haplotypes present in each locus were 10, 6, 4, and 8 for CSN1S1, CSN2, CSN1S2, and CSN3, respectively. The effects of the CSN1S1 haplotypes on protein percentage and fat kilograms were significant, as were the effects of CSN3 haplotypes on fat percentage and protein percentage. A deletion in exon 12 of CSN1S1, unique to the Norwegian goat population, explained the effects of CSN1S1 haplotypes on fat kilograms, but not protein percentage. Investigation of linkage disequilibrium between all possible pairs of SNPs revealed higher levels of linkage disequilbrium for SNP pairs within casein loci than for SNP pairs between casein loci, likely reflecting low levels of intragenic recombination. Further, there was evidence for a site of preferential recombination between CSN2 and CSN1S2. The value of the haplotypes for haplotype-assisted selection (HAS) is discussed.     

Reference genome of wild goat (capra aegagrus) and sequencing of goat breeds provide insight into genic basis of goat domestication

Background

Domestic goats (Capra hircus) have been selected to play an essential role in agricultural production systems, since being domesticated from their wild progenitor, bezoar (Capra aegagrus). A detailed understanding of the genetic consequences imparted by the domestication process remains a key goal of evolutionary genomics.

Results

We constructed the reference genome of bezoar and sequenced representative breeds of domestic goats to search for genomic changes that likely have accompanied goat domestication and breed formation. Thirteen copy number variation genes associated with coat color were identified in domestic goats, among which ASIP gene duplication contributes to the generation of light coat-color phenotype in domestic goats. Analysis of rapidly evolving genes identified genic changes underlying behavior-related traits, immune response and production-related traits.

Conclusion

Based on the comparison studies of copy number variation genes and rapidly evolving genes between wild and domestic goat, our findings and methodology shed light on the genetic mechanism of animal domestication and will facilitate future goat breeding.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1606-1) contains supplementary material, which is available to authorized users.     

Cardiac myosin binding protein C and MAP-kinase activating death domain-containing gene polymorphisms and diastolic heart failure

Objective

Myosin binding protein C (MYBPC3) plays a role in ventricular relaxation. The aim of the study was to investigate the association between cardiac myosin binding protein C (MYBPC3) gene polymorphisms and diastolic heart failure (DHF) in a human case-control study.

Methods

A total of 352 participants of 1752 consecutive patients from the National Taiwan University Hospital and its affiliated hospital were enrolled. 176 patients diagnosed with DHF confirmed by echocardiography were recruited. Controls were matched 1-to-1 by age, sex, hypertension, diabetes, renal function and medication use. We genotyped 12 single nucleotide polymorphisms (SNPs) according to HapMap Han Chinese Beijing databank across a 40 kb genetic region containing the MYBPC3 gene and the neighboring DNA sequences to capture 100% of haplotype variance in all SNPs with minor allele frequencies ≧5%. We also analyzed associations of these tagging SNPs and haplotypes with DHF and linkage disequilibrium (LD) structure of the MYBPC3 gene.

Results

In a single locus analysis, SNP rs2290149 was associated with DHF (allele-specific p = 0.004; permuted p = 0.031). The SNP with a minor allele frequency of 9.4%, had an odds ratio 2.14 (95% CI 1.25–3.66; p = 0.004) for the additive model and 2.06 for the autosomal dominant model (GG+GA : AA, 95% CI 1.17–3.63; p = 0.013), corresponding to a population attributable risk fraction of 12.02%. The haplotypes in a LD block of rs2290149 (C-C-G-C) was also significantly associated with DHF (odds ratio 2.10 (1.53–2.89); permuted p = 0.029).

Conclusions

We identified a SNP (rs2290149) among the tagging SNP set that was significantly associated with early DHF in a Chinese population.     

Using the realized relationship matrix to disentangle confounding factors for the estimation of genetic variance components of complex traits

Background

In the analysis of complex traits, genetic effects can be confounded with non-genetic effects, especially when using full-sib families. Dominance and epistatic effects are typically confounded with additive genetic and non-genetic effects. This confounding may cause the estimated genetic variance components to be inaccurate and biased.

Methods

In this study, we constructed genetic covariance structures from whole-genome marker data, and thus used realized relationship matrices to estimate variance components in a heterogenous population of ~ 2200 mice for which four complex traits were investigated. These mice were genotyped for more than 10,000 single nucleotide polymorphisms (SNP) and the variances due to family, cage and genetic effects were estimated by models based on pedigree information only, aggregate SNP information, and model selection for specific SNP effects.

Results and conclusions

We show that the use of genome-wide SNP information can disentangle confounding factors to estimate genetic variances by separating genetic and non-genetic effects. The estimated variance components using realized relationship were more accurate and less biased, compared to those based on pedigree information only. Models that allow the selection of individual SNP in addition to fitting a relationship matrix are more efficient for traits with a significant dominance variance.     

Detection of quantitative trait loci in Bos indicus and Bos taurus cattle using genome-wide association studies

Background

The apparent effect of a single nucleotide polymorphism (SNP) on phenotype depends on the linkage disequilibrium (LD) between the SNP and a quantitative trait locus (QTL). However, the phase of LD between a SNP and a QTL may differ between Bos indicus and Bos taurus because they diverged at least one hundred thousand years ago. Here, we test the hypothesis that the apparent effect of a SNP on a quantitative trait depends on whether the SNP allele is inherited from a Bos taurus or Bos indicus ancestor.

Methods

Phenotype data on one or more traits and SNP genotype data for 10 181 cattle from Bos taurus, Bos indicus and composite breeds were used. All animals had genotypes for 729 068 SNPs (real or imputed). Chromosome segments were classified as originating from B. indicus or B. taurus on the basis of the haplotype of SNP alleles they contained. Consequently, SNP alleles were classified according to their sub-species origin. Three models were used for the association study: (1) conventional GWAS (genome-wide association study), fitting a single SNP effect regardless of subspecies origin, (2) interaction GWAS, fitting an interaction between SNP and subspecies-origin, and (3) best variable GWAS, fitting the most significant combination of SNP and sub-species origin.

Results

Fitting an interaction between SNP and subspecies origin resulted in more significant SNPs (i.e. more power) than a conventional GWAS. Thus, the effect of a SNP depends on the subspecies that the allele originates from. Also, most QTL segregated in only one subspecies, suggesting that many mutations that affect the traits studied occurred after divergence of the subspecies or the mutation became fixed or was lost in one of the subspecies.

Conclusions

The results imply that GWAS and genomic selection could gain power by distinguishing SNP alleles based on their subspecies origin, and that only few QTL segregate in both B. indicus and B. taurus cattle. Thus, the QTL that segregate in current populations likely resulted from mutations that occurred in one of the subspecies and can have both positive and negative effects on the traits. There was no evidence that selection has increased the frequency of alleles that increase body weight.     

Mapping of a milk production quantitative trait locus to a 1.056 Mb region on bovine chromosome 5 in the Fleckvieh dual purpose cattle breed

Background

In a previous study in the Fleckvieh dual purpose cattle breed, we mapped a quantitative trait locus (QTL) affecting milk yield (MY1), milk protein yield (PY1) and milk fat yield (FY1) during first lactation to the distal part of bovine chromosome 5 (BTA5), but the confidence interval was too large for positional cloning of the causal gene. Our objective here was to refine the position of this QTL and to define the candidate region for high-throughput sequencing.

Methods

In addition to those previously studied, new Fleckvieh families were genotyped, in order to increase the number of recombination events. Twelve new microsatellites and 240 SNP markers covering the most likely QTL region on BTA5 were analysed. Based on haplotype analysis performed in this complex pedigree, families segregating for the low frequency allele of this QTL (minor allele) were selected. Single- and multiple-QTL analyses using combined linkage and linkage disequilibrium methods were performed.

Results

Single nucleotide polymorphism haplotype analyses on representative family sires and their ancestors revealed that the haplotype carrying the minor QTL allele is rare and most probably originates from a unique ancestor in the mapping population. Analyses of different subsets of families, created according to the results of haplotype analysis and availability of SNP and microsatellite data, refined the previously detected QTL affecting MY1 and PY1 to a region ranging from 117.962 Mb to 119.018 Mb (1.056 Mb) on BTA5. However, the possibility of a second QTL affecting only PY1 at 122.115 Mb was not ruled out.

Conclusion

This study demonstrates that targeting families segregating for a less frequent QTL allele is a useful method. It improves the mapping resolution of the QTL, which is due to the division of the mapping population based on the results of the haplotype analysis and to the increased frequency of the minor allele in the families. Consequently, we succeeded in refining the region containing the previously detected QTL to 1 Mb on BTA5. This candidate region contains 27 genes with unknown or partially known function(s) and is small enough for high-throughput sequencing, which will allow future detailed analyses of candidate genes.     

The Polymorphism of YWHAE,a Gene Encoding 14-3-3Epsilon,and Brain Morphology in Schizophrenia: A Voxel-Based Morphometric Study

Background

YWHAE is a possible susceptibility gene for schizophrenia that encodes 14-3-3epsilon, a Disrupted-in-Schizophrenia 1 (DISC1)-interacting molecule, but the effect of variation in its genotype on brain morphology remains largely unknown.

Methods

In this voxel-based morphometric magnetic resonance imaging study, we conducted whole-brain analyses regarding the effects of YWHAE single-nucleotide polymorphisms (SNPs) (rs28365859, rs11655548, and rs9393) and DISC1 SNP (rs821616) on gray matter volume in a Japanese sample of 72 schizophrenia patients and 86 healthy controls. On the basis of a previous animal study, we also examined the effect of rs28365859 genotype specifically on hippocampal volume.

Results

Whole-brain analyses showed no significant genotype effect of these SNPs on gray matter volume in all subjects, but we found significant genotype-by-diagnosis interaction for rs28365859 in the left insula and right putamen. The protective C allele carriers of rs28365859 had a significantly larger left insula than the G homozygotes only for schizophrenia patients, while the controls with G allele homozygosity had a significantly larger right putamen than the C allele carriers. The C allele carriers had a larger right hippocampus than the G allele homozygotes in schizophrenia patients, but not in healthy controls. No significant interaction was found between rs28365859 and DISC1 SNP on gray matter volume.

Conclusions

These different effects of the YWHAE (rs28365859) genotype on brain morphology in schizophrenia and healthy controls suggest that variation in its genotype might be, at least partly, related to the abnormal neurodevelopment, including in the limbic regions, reported in schizophrenia. Our results also suggest its specific role among YWHAE SNPs in the pathophysiology of schizophrenia.     

Evidence for Positive Selection on the Osteogenin (BMP3) Gene in Human Populations

Background

Human skeletal system has evolved rapidly since the dispersal of modern humans from Africa, potentially driven by selection and adaptation. Osteogenin (BMP3) plays an important role in skeletal development and bone osteogenesis as an antagonist of the osteogenic bone morphogenetic proteins, and negatively regulates bone mineral density.

Methodology/Principal Findings

Here, we resequenced the BMP3 gene from individuals in four geographically separated modern human populations. Features supportive of positive selection in the BMP3 gene were found including the presence of an excess of nonsynonymous mutations in modern humans, and a significantly lower genetic diversity that deviates from neutrality. The prevalent haplotypes of the first exon region in Europeans demonstrated features of long-range haplotype homogeneity. In contrast with findings in European, the derived allele SNP Arg192Gln shows higher extended haplotype homozygosity in East Asian. The worldwide allele frequency distribution of SNP shows not only a high-derived allele frequency in Asians, but also in Americans, which is suggestive of functional adaptation.

Conclusions/Significance

In conclusion, we provide evidence for recent positive selection operating upon a crucial gene in skeletal development, which may provide new insight into the evolution of the skeletal system and bone development.     

Epigenetic-genetic chromosome dosage approach for fetal trisomy 21 detection using an autosomal genetic reference marker

Background

The putative promoter of the holocarboxylase synthetase (HLCS) gene on chromosome 21 is hypermethylated in placental tissues and could be detected as a fetal-specific DNA marker in maternal plasma. Detection of fetal trisomy 21 (T21) has been demonstrated by an epigenetic-genetic chromosome dosage approach where the amount of hypermethylated HLCS in maternal plasma is normalized using a fetal genetic marker on the Y chromosome as a chromosome dosage reference marker. We explore if this method can be applied on both male and female fetuses with the use of a paternally-inherited fetal single nucleotide polymorphism (SNP) allele on a reference chromosome for chromosome dosage normalization.

Methodology

We quantified hypermethylated HLCS molecules using methylation-sensitive restriction endonuclease digestion followed by real-time or digital PCR analyses. For chromosome dosage analysis, we compared the amount of digestion-resistant HLCS to that of a SNP allele (rs6636, a C/G SNP) that the fetus has inherited from the father but absent in the pregnant mother.

Principal Findings

Using a fetal-specific SNP allele on a reference chromosome, we analyzed 20 euploid and nine T21 placental tissue samples. All samples with the fetal-specific C allele were correctly classified. One sample from each of the euploid and T21 groups were misclassified when the fetal-specific G allele was used as the reference marker. We then analyzed 33 euploid and 14 T21 maternal plasma samples. All but one sample from each of the euploid and T21 groups were correctly classified using the fetal-specific C allele, while correct classification was achieved for all samples using the fetal-specific G allele as the reference marker.

Conclusions

As a proof-of-concept study, we have demonstrated that the epigenetic-genetic chromosome dosage approach can be applied to the prenatal diagnosis of trisomy 21 for both male and female fetuses.     

SNP identification and marker assay development for high-throughput selection of soybean cyst nematode resistance

Background

Soybean cyst nematode (SCN) is the most economically devastating pathogen of soybean. Two resistance loci, Rhg1 and Rhg4 primarily contribute resistance to SCN race 3 in soybean. Peking and PI 88788 are the two major sources of SCN resistance with Peking requiring both Rhg1 and Rhg4 alleles and PI 88788 only the Rhg1 allele. Although simple sequence repeat (SSR) markers have been reported for both loci, they are linked markers and limited to be applied in breeding programs due to accuracy, throughput and cost of detection methods. The objectives of this study were to develop robust functional marker assays for high-throughput selection of SCN resistance and to differentiate the sources of resistance.

Results

Based on the genomic DNA sequences of 27 soybean lines with known SCN phenotypes, we have developed Kompetitive Allele Specific PCR (KASP) assays for two Single nucleotide polymorphisms (SNPs) from Glyma08g11490 for the selection of the Rhg4 resistance allele. Moreover, the genomic DNA of Glyma18g02590 at the Rhg1 locus from 11 soybean lines and cDNA of Forrest, Essex, Williams 82 and PI 88788 were fully sequenced. Pairwise sequence alignment revealed seven SNPs/insertion/deletions (InDels), five in the 6th exon and two in the last exon. Using the same 27 soybean lines, we identified one SNP that can be used to select the Rhg1 resistance allele and another SNP that can be employed to differentiate Peking and PI 88788-type resistance. These SNP markers have been validated and a strong correlation was observed between the SNP genotypes and reactions to SCN race 3 using a panel of 153 soybean lines, as well as a bi-parental population, F₅–derived recombinant inbred lines (RILs) from G00-3213 x LG04-6000.

Conclusions

Three functional SNP markers (two for Rhg1 locus and one for Rhg4 locus) were identified that could provide genotype information for the selection of SCN resistance and differentiate Peking from PI 88788 source for most germplasm lines. The robust KASP SNP marker assays were developed. In most contexts, use of one or two of these markers is sufficient for high-throughput marker-assisted selection of plants that will exhibit SCN resistance.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1531-3) contains supplementary material, which is available to authorized users.     

A Single Nucleotide Polymorphism in cBIM Is Associated with a Slower Achievement of Major Molecular Response in Chronic Myeloid Leukaemia Treated with Imatinib

Purpose

BIM is essential for the response to tyrosine-kinase inhibitors (TKI) in chronic myeloid leukaemia (CML) patients. Recently, a deletion polymorphism in intron 2 of the BIM gene was demonstrated to confer an intrinsic TKI resistance in Asian patients. The present study aimed at identifying mutations in the BIM sequence that could lead to imatinib resistance independently of BCR-ABL mutations.

Experimental Design

BIM coding sequence analysis was performed in 72 imatinib-treated CML patients from a French population of our centre and in 29 healthy controls (reference population) as a case-control study. Real-time quantitative PCR (RT qPCR) was performed to assess Bim expression in our reference population.

Results

No mutation with amino-acid change was found in the BIM coding sequence. However, we observed a silent single nucleotide polymorphism (SNP) c465C>T (rs724710). A strong statistical link was found between the presence of the T allele and the high Sokal risk group (p = 0.0065). T allele frequency was higher in non responsive patients than in the reference population (p = 0.0049). Similarly, this T allele was associated with the mutation frequency on the tyrosine kinase domain of BCR-ABL (p<0.001) and the presence of the T allele significantly lengthened the time to achieve a major molecular response (MMR). Finally, the presence of the T allele was related to a decreased basal expression of the Bim mRNA in the circulating mononuclear cells of healthy controls.

Conclusion

These results suggest that the analysis of the c465C>T SNP of BIM could be useful for predicting the outcome of imatinib-treated CML patients.     

The SNP rs3128965 of HLA-DPB1 as a Genetic Marker of the AERD Phenotype

Background

Two common clinical syndromes of acetylsalicylic acid (aspirin) hypersensitivity, aspirin-exacerbated respiratory disease (AERD) and aspirin-exacerbated cutaneous disease (AECD), were subjected to a genome-wide association study to identify strong genetic markers for aspirin hypersensitivity in a Korean population.

Methods

A comparison of SNP genotype frequencies on an Affymetrix Genome-Wide Human SNP array of 179 AERD patients and 1989 healthy normal control subjects (NC) revealed SNPs on chromosome 6 that were associated with AERD, but not AECD. To validate the association, we enrolled a second cohort comprising AERD (n = 264), NC (n = 238) and disease-control (aspirin tolerant asthma; ATA, n = 387) groups.

Results

The minor genotype frequency (AG or AA) of a particular SNP, rs3128965, in the HLA-DPB1 region was higher in the AERD group compared to the ATA or NC group (P = 0.001, P = 0.002, in a co-dominant analysis model, respectively). Comparison of rs3128965 alleles with the clinical features of asthmatics revealed that patients harboring the A allele had increased bronchial hyperresponsiveness to inhaled aspirin and methacholine, and higher 15-HETE levels, than those without the A allele (P = 0.039, 0.037, and 0.004, respectively).

Conclusions

This implies the potential of rs3128965 as a genetic marker for diagnosis and prediction of the AERD phenotype.