Single Nucleotide Polymorphism Coverage Research Articles

Design and validation of high-density SNP array of goats and population stratification of Indian goat breeds

Goats are the supporting pillars of rural economy contributing significantly to meat and milk production in India. It is a species targeted for fulfilling the interdependent goals of poverty reduction and creation of employment for supporting the rural income. The increased demand for goat products necessitates their genetic characterization and improvement to augment the production of native breeds. Bi-allelic, genome wide, densely placed single nucleotide polymorphism (SNP) markers are most suitable for this purpose. This paper describes the design and validation of an Affymetrix Axiom-based high-density (HD) SNP chip for goats. The array was designed using a panel of 225 samples from 15 diverse goat breeds of India. In total, more than 38 million high quality SNPs were subjected to stringent filtering and 626,975 SNPs were finally tiled on the array. The average coverage of SNPs in our chip is one SNP per four kilobase (kb), providing a denser coverage of the goat genome than previously available arrays. The HD chip (Axiom_Cahi) was validated by genotyping 443 samples from 26 indigenous goat breeds/populations. The results revealed 95.83% markers to be highly informative and polymorphic in Indian goats. Multivariate analysis indicated population structuring, as 15 breeds could be segregated using the designed array. Phylogenetic analysis suggested stratification of breeds by geographic proximity. This HD SNP chip for goats is a valuable resource for genomic selection, genome wide association as well as population genetic studies in goats.

Exploring genetic diversity and population structure of a large grapevine (Vitis vinifera L.) germplasm collection in Türkiye.

Grapevine (Vitis Vinifera L.) has been one of the significant perennial crops in widespread temperate climate regions since its domestication around 6000 years ago. Grapevine and its products, particularly wine, table grapes, and raisins, have significant economic importance not only in grapevine-growing countries but also worldwide. Grapevine cultivation in Türkiye dates back to ancient times, and Anatolia is considered one of the main grapevine migration routes around the Mediterranean basin. Turkish germplasm collection, conserved at the Turkish Viticulture Research Institutes, includes cultivars and wild relatives mainly collected in Türkiye, breeding lines, rootstock varieties, and mutants, but also cultivars of international origin. Genotyping with high-throughput markers enables the investigation of genetic diversity, population structure, and linkage disequilibrium, which are crucial for applying genomic-assisted breeding. Here, we present the results of a high-throughput genotyping-by-sequencing (GBS) study of 341 genotypes from grapevine germplasm collection at Manisa Viticulture Research Institute. A total of 272,962 high-quality single nucleotide polymorphisms (SNP) markers on the nineteen chromosomes were identified using genotyping-by-sequencing (GBS) technology. The high-density coverage of SNPs resulted in an average of 14,366 markers per chromosome, an average polymorphism information content (PIC) value of 0.23 and an expected heterozygosity (He) value of 0.28 indicating the genetic diversity within 341 genotypes. LD decayed very fast when r2 was between 0.45 and 0.2 and became flat when r2 was 0.05. The average LD decay for the entire genome was 30 kb when r2=0.2. The PCA and structure analysis did not distinguish the grapevine genotypes based on different origins, highlighting the occurrence of gene flow and a high amount of admixture. Analysis of molecular variance (AMOVA) results indicated a high level of genetic differentiation within populations, while variation among populations was extremely low. This study provides comprehensive information on the genetic diversity and population structure of Turkish grapevine genotypes.

Abstract PL03-02: Somatic mutations, germline risk and ancestry in lung adenocarcinoma

Abstract Like most cancer types, lung cancer is caused predominantly by somatic genome alterations. In lung adenocarcinoma, the most common histological type of lung cancer, these alterations are known to occur in multiple pathways including the p53 pathway, the receptor tyrosine kinase (RTK)/Ras/Raf/MAP kinase (MAPK) pathway and PI3 kinase pathway, the Rb1/cell cycle pathway, the Swi/Snf pathway, the Myc pathway, and the telomerase pathway, among others. Genome-wide association studies comparing polymorphisms in germline DNA from patients with lung cancer and from unaffected control subjects have led to the identification of multiple germline risk alleles for lung adenocarcinoma, including the HLA locus, the telomerase catalytic subunit gene locus, and, notably, the nicotinic acetylcholine receptor locus, where polymorphisms appear to modulate individual propensity for smoking. The components of inherited lung cancer risk, particularly in nonsmokers, are not fully understood, but there appear to be variations in lung adenocarcinoma mutations in distinct ancestry groups, which may be related to inherited factors. In particular, the frequency of somatic EGFR and KRAS mutations in lung cancer varies by ethnicity. Somatic EGFR mutation rates are higher in lung cancers from patients with East Asian ancestry and lower in lung cancers from patients with European or African ancestry. Somatic KRAS and STK11 mutation rates show the opposite pattern, higher in lung cancers from patients with European or African ancestry and lower in lung cancers from patients with East Asian ancestry. In patients from Latin America, somatic lung cancer EGFR mutation frequencies vary by country, with higher frequencies in Peru, intermediate frequencies in Mexico, Colombia, Costa Rica and Brazil, and lower frequencies in Argentina. To explore the relationship between the somatic genome in lung cancer and ethnicity related germline risk, we performed cancer gene panel sequencing of DNA from over 1,000 lung cancers from Mexico and Colombia, countries with significant population admixture. We developed methods to infer ancestry from the tumor DNA sequence based on coverage of single nucleotide polymorphisms. This study revealed associations between ancestry and somatic lung cancer genomic alterations, including tumor mutational burden, and specific driver mutations in EGFR, KRAS, and STK11. A local ancestry score was more strongly correlated with EGFR mutation frequency compared with global ancestry correlation, suggesting that germline genetics, rather than environmental exposure, could underlie these disparities. Our study suggests that the variation in EGFR and KRAS somatic mutation frequency in lung cancer is associated with genetic ancestry in patients from Latin America, and suggests further studies to identify germline alleles that underpin this association. If we find a germline locus or loci that could impact the development of lung cancers with EGFR and/or KRAS mutation, this might help in improving lung cancer prevention and screening for populations of Latin American origin and others. Furthermore, multiple studies now highlight the importance of EGFR mutation screening and EGFR-directed targeted therapy for lung cancer patients in Latin America and with origins in Latin America. Citation Format: Matthew L. Meyerson. Somatic mutations, germline risk and ancestry in lung adenocarcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr PL03-02.

TagSNP-set selection for genotyping using integrated data

Single-nucleotide polymorphisms (SNPs) are vital in identifying genetic level variations in complex disease. It was found that the information of SNPs on adjacent or identical genes can be represented by a few tagSNPs (called tag SNP-set or tagSNP-set). In this work, we propose a novel method called TagSNP-set Selection by Optimal Iteration with Linkage Disequilibrium (TSOILD) and develop a quantificationally analytical tagSNP-set prediction method called Physical Distance-Linkage Disequilibrium Prediction Method (PDLDPM). To verify the validity of TSOILD method and PDLDPM, a large amount of test data is generated by simulation software HAPGEN2. According to the experimental results, the prediction accuracy of TSOILD is improved by 6.73%, 3.19%, 6.52% and 1.72% over the Random Sampling, Genetic Algorithm (GA) , Greedy Algorithm and TagSNP-Set Selection Method with Maximum Information (TSMI) respectively. In addition, PDLDPM, Linkage Coverage and selection of tag SNPs to maximize prediction accuracy (STAMPA) are used to evaluate the tagSNP-set selected by Random Sampling, GA, Greedy Algorithm and TSMI. Results show that the PDLDPM performs better than the other two methods. These methods provide effective assistance for the study of genetic level variation of complex diseases.

S890 NEW WHOLE GENOME ASSOCIATION SCANNING APPROACH FOR THE DISCOVERY OF HLA CLASS I‐RESTRICTED MINOR HISTOCOMPATIBILITY ANTIGENS

Background:Patients that undergo allogeneic stem cell transplantation (SCT) as treatment for hematological diseases face the risk of relapse as well as Graft‐versus‐Host Disease (GvHD). GvHD as well as the favorable Graft‐versus‐Leukemia effect are mediated by donor T cells. These T cells recognize minor histocompatibility antigens: polymorphic peptides, which are presented on the cell surface by HLA molecules and are caused by genetic differences in single nucleotide polymorphisms (SNPs) between patient and donor. Knowledge about mismatched minor histocompatibility antigens may enable a more directed donor search as well as better prediction and measurement of the Graft‐versus‐Leukemia effect and GvHD for personalized treatment after transplantation, thereby contributing to a better outcome for patients treated with allogeneic SCT.Aims:Identification of minor histocompatibility antigens has been a laborious process in the past. Therefore, whole genome association scanning was developed in our laboratory. However, this method was restricted to two HLAs and screening of one million SNPs. The aim of this study is to develop and use an optimized method to identify the dominant repertoire of minor histocompatibility antigens in common HLA class I alleles.Methods:Donor T‐cells isolated from patients after allogeneic SCT are tested for recognition of a new panel of 191 selected B‐cell lines, which are sequenced in the 1000 Genome Project. This panel enables the inclusion of seven common HLAs and increases SNP coverage to 12 million (MAF > 0.01). SNPs that strongly associate with T‐cell recognition are subsequently validated to encode minor histocompatibility antigens.Results:A total of 19 novel minor histocompatibility antigens have been identified that are presented in seven common HLA class I alleles, showing the potential of this optimized approach. Besides conventional antigens, cryptic peptides were found as well as peptides restricted to HLAs that were not primarily targeted.Summary/Conclusion:This improved approach for whole genome association scanning has been successfully applied in rapidly discovering new minor histocompatibility antigens. The new method surpasses previous methods in its rapidness and coverage of HLAs and SNPs across the human genome, which additionally allows for identification of cryptic peptides. With the increasing number of patients that are analyzed in this study, T‐cells recognizing known minor histocompatibility antigens are more often isolated, indicating that the repertoire of minor histocompatibility antigens is limited. Our optimized method is expected to discover the majority of unknown antigens in this repertoire, thereby contributing essential knowledge for new strategies to improve clinical outcome after allogeneic SCT.

Sequence imputation from low density single nucleotide polymorphism panel in a black poplar breeding population

BackgroundGenomic selection accuracy increases with the use of high SNP (single nucleotide polymorphism) coverage. However, such gains in coverage come at high costs, preventing their prompt operational implementation by breeders. Low density panels imputed to higher densities offer a cheaper alternative during the first stages of genomic resources development. Our study is the first to explore the imputation in a tree species: black poplar. About 1000 pure-breed Populus nigra trees from a breeding population were selected and genotyped with a 12K custom Infinium Bead-Chip. Forty-three of those individuals corresponding to nodal trees in the pedigree were fully sequenced (reference), while the remaining majority (target) was imputed from 8K to 1.4 million SNPs using FImpute. Each SNP and individual was evaluated for imputation errors by leave-one-out cross validation in the training sample of 43 sequenced trees. Some summary statistics such as Hardy-Weinberg Equilibrium exact test p-value, quality of sequencing, depth of sequencing per site and per individual, minor allele frequency, marker density ratio or SNP information redundancy were calculated. Principal component and Boruta analyses were used on all these parameters to rank the factors affecting the quality of imputation. Additionally, we characterize the impact of the relatedness between reference population and target population.ResultsDuring the imputation process, we used 7540 SNPs from the chip to impute 1,438,827 SNPs from sequences. At the individual level, imputation accuracy was high with a proportion of SNPs correctly imputed between 0.84 and 0.99. The variation in accuracies was mostly due to differences in relatedness between individuals. At a SNP level, the imputation quality depended on genotyped SNP density and on the original minor allele frequency. The imputation did not appear to result in an increase of linkage disequilibrium. The genotype densification not only brought a better distribution of markers all along the genome, but also we did not detect any substantial bias in annotation categories.ConclusionsThis study shows that it is possible to impute low-density marker panels to whole genome sequence with good accuracy under certain conditions that could be common to many breeding populations.

Development and evaluation of a transfusion medicine genome wide genotyping array.

Many aspects of transfusion medicine are affected by genetics. Current single-nucleotide polymorphism (SNP) arrays are limited in the number of targets that can be interrogated and cannot detect all variation of interest. We designed a transfusion medicine array (TM-Array) for study of both common and rare transfusion-relevant variations in genetically diverse donor and recipient populations. The array was designed by conducting extensive bioinformatics mining and consulting experts to identify genes and genetic variation related to a wide range of transfusion medicine clinical relevant and research-related topics. Copy number polymorphisms were added in the alpha globin, beta globin, and Rh gene clusters. The final array contains approximately 879,000 SNP and copy number polymorphism markers. Over 99% of SNPs were called reliably. Technical replication showed the array to be robust and reproducible, with an error rate less than 0.03%. The array also had a very low Mendelian error rate (average parent-child trio accuracy of 0.9997). Blood group results were in concordance with serology testing results, and the array accurately identifies rare variants (minor allele frequency of 0.5%). The array achieved high genome-wide imputation coverage for African-American (97.5%), Hispanic (96.1%), East Asian (94.6%), and white (96.1%) genomes at a minor allele frequency of 5%. A custom array for transfusion medicine research has been designed and evaluated. It gives wide coverage and accurate identification of rare SNPs in diverse populations. The TM-Array will be useful for future genetic studies in the diverse fields of transfusion medicine research.

Misidentification of runs of homozygosity islands in cattle caused by interference with copy number variation or large intermarker distances

BackgroundRuns of homozygosity (ROH) islands are stretches of homozygous sequence in the genome of a large proportion of individuals in a population. Algorithms for the detection of ROH depend on the similarity of haplotypes. Coverage gaps and copy number variants (CNV) may result in incorrect identification of such similarity, leading to the detection of ROH islands where none exists. Misidentified hemizygous regions will also appear as homozygous based on sequence variation alone. Our aim was to identify ROH islands influenced by marker coverage gaps or CNV, using Illumina BovineHD BeadChip (777 K) single nucleotide polymorphism (SNP) data for Austrian Brown Swiss, Tyrol Grey and Pinzgauer cattle.MethodsROH were detected using clustering, and ROH islands were determined from population inbreeding levels for each marker. CNV were detected using a multivariate copy number analysis method and a hidden Markov model. SNP coverage gaps were defined as genomic regions with intermarker distances on average longer than 9.24 kb. ROH islands that overlapped CNV regions (CNVR) or SNP coverage gaps were considered as potential artefacts. Permutation tests were used to determine if overlaps between CNVR with copy losses and ROH islands were due to chance. Diversity of the haplotypes in the ROH islands was assessed by haplotype analyses.ResultsIn Brown Swiss, Tyrol Grey and Pinzgauer, we identified 13, 22, and 24 ROH islands covering 26.6, 389.0 and 35.8 Mb, respectively, and we detected 30, 50 and 71 CNVR derived from CNV by using both algorithms, respectively. Overlaps between ROH islands, CNVR or coverage gaps occurred for 7, 14 and 16 ROH islands, respectively. About 37, 44 and 52% of the ROH islands coverage in Brown Swiss, Tyrol Grey and Pinzgauer, respectively, were affected by copy loss. Intersections between ROH islands and CNVR were small, but significantly larger compared to ROH islands at random locations across the genome, implying an association between ROH islands and CNVR. Haplotype diversity for reliable ROH islands was lower than for ROH islands that intersected with copy loss CNVR.ConclusionsOur findings show that a significant proportion of the ROH islands in the bovine genome are artefacts due to CNV or SNP coverage gaps.

Transethnic differences in GWAS signals: A simulation study.

Genome-wide association studies (GWASs) have allowed researchers to identify thousands of single nucleotide polymorphisms (SNPs) and other variants associated with particular complex traits. Previous studies have reported differences in the strength and even the direction of GWAS signals across different populations. These differences could be due to a combination of (1) lack of power, (2) allele frequency differences, (3) linkage disequilibrium (LD) differences, and (4) true differences in causal variant effect sizes. To determine whether properties (1)-(3) on their own might be sufficient to explain the patterns previously noted in strong GWAS signals, we simulated case-control data of European, Asian and African ancestry, applying realistic allele frequencies and LD from 1000 Genomes data but enforcing equal causal effect sizes across populations. Much of the observed differences in strong GWAS signals could indeed be accounted for by allele frequency and LD differences, enhanced by the Euro-centric SNP bias and lower SNP coverage found in older GWAS panels. While we cannot rule out a role for true transethnic effect size differences, our results suggest that strong causal effects may be largely shared among human populations, motivating the use of transethnic data for fine-mapping.

Conclusive evidence for hexasomic inheritance in chrysanthemum based on analysis of a 183\xa0k SNP array

BackgroundCultivated chrysanthemum is an outcrossing hexaploid (2n = 6× = 54) with a disputed mode of inheritance. In this paper, we present a single nucleotide polymorphism (SNP) selection pipeline that was used to design an Affymetrix Axiom array with 183 k SNPs from RNA sequencing data (1). With this array, we genotyped four bi-parental populations (with sizes of 405, 53, 76 and 37 offspring plants respectively), and a cultivar panel of 63 genotypes. Further, we present a method for dosage scoring in hexaploids from signal intensities of the array based on mixture models (2) and validation of selection steps in the SNP selection pipeline (3). The resulting genotypic data is used to draw conclusions on the mode of inheritance in chrysanthemum (4), and to make an inference on allelic expression bias (5).ResultsWith use of the mixture model approach, we successfully called the dosage of 73,936 out of 183,130 SNPs (40.4%) that segregated in any of the bi-parental populations. To investigate the mode of inheritance, we analysed markers that segregated in the large bi-parental population (n = 405). Analysis of segregation of duplex x nulliplex SNPs resulted in evidence for genome-wide hexasomic inheritance. This evidence was substantiated by the absence of strong linkage between markers in repulsion, which indicated absence of full disomic inheritance. We present the success rate of SNP discovery out of RNA sequencing data as affected by different selection steps, among which SNP coverage over genotypes and use of different types of sequence read mapping software. Genomic dosage highly correlated with relative allele coverage from the RNA sequencing data, indicating that most alleles are expressed according to their genomic dosage.ConclusionsThe large population, genotyped with a very large number of markers, is a unique framework for extensive genetic analyses in hexaploid chrysanthemum. As starting point, we show conclusive evidence for genome-wide hexasomic inheritance.

Proper joint analysis of summary association statistics requires the adjustment of heterogeneity in SNP coverage pattern.

As meta-analysis results published by consortia of genome-wide association studies (GWASs) become increasingly available, many association summary statistics-based multi-locus tests have been developed to jointly evaluate multiple single-nucleotide polymorphisms (SNPs) to reveal novel genetic architectures of various complex traits. The validity of these approaches relies on the accurate estimate of z-score correlations at considered SNPs, which in turn requires knowledge on the set of SNPs assessed by each study participating in the meta-analysis. However, this exact SNP coverage information is usually unavailable from the meta-analysis results published by GWAS consortia. In the absence of the coverage information, researchers typically estimate the z-score correlations by making oversimplified coverage assumptions. We show through real studies that such a practice can generate highly inflated type I errors, and we demonstrate the proper way to incorporate correct coverage information into multi-locus analyses. We advocate that consortia should make SNP coverage information available when posting their meta-analysis results, and that investigators who develop analytic tools for joint analyses based on summary data should pay attention to the variation in SNP coverage and adjust for it appropriately.

Single nucleotide polymorphism coverage and inference of N-acetyltransferase-2 acetylator phenotypes in wordwide population groups.

Several algorithms have been proposed to reduce the genotyping effort and cost, while retaining the accuracy of N-acetyltransferase-2 (NAT2) phenotype prediction. Data from the 1000 Genomes (1KG) project and an admixed cohort of Black Brazilians were used to assess the accuracy of NAT2 phenotype prediction using algorithms based on paired single nucleotide polymorphisms (SNPs) (rs1041983 and rs1801280) or a tag SNP (rs1495741). NAT2 haplotypes comprising SNPs rs1801279, rs1041983, rs1801280, rs1799929, rs1799930, rs1208 and rs1799931 were assigned according to the arylamine N-acetyltransferases database. Contingency tables were used to visualize the agreement between the NAT2 acetylator phenotypes on the basis of these haplotypes versus phenotypes inferred by the prediction algorithms. The paired and tag SNP algorithms provided more than 96% agreement with the 7-SNP derived phenotypes in Europeans, East Asians, South Asians and Admixed Americans, but discordance of phenotype prediction occurred in 30.2 and 24.8% 1KG Africans and in 14.4 and 18.6% Black Brazilians, respectively. Paired SNP panel misclassification occurs in carriers of NATs haplotypes *13A (282T alone), *12B (282T and 803G), *6B (590A alone) and *14A (191A alone), whereas haplotype *14, defined by the 191A allele, is the major culprit of misclassification by the tag allele. Both the paired SNP and the tag SNP algorithms may be used, with economy of scale, to infer NAT2 acetylator phenotypes, including the ultra-slow phenotype, in European, East Asian, South Asian and American populations represented in the 1KG cohort. Both algorithms, however, perform poorly in populations of predominant African descent, including admixed African-Americans, African Caribbeans and Black Brazilians.

41 - Detection of Exon-Centric Copy Number Changes and Mutations with Customizable Target Enrichment

Although targeted exome sequencing is a cost-effective method for identifying mutations in exons, high read depths from several neighboring regions away from exons are often required to provide confident copy number determination. There are significant limitations in exome sequencing to identify accurate aberration boundaries associated with potentially important regulatory regions outside of exons such as in introns or promoters. To enable higher resolution copy number calls in and around genes/exons of interest, we have augmented exonic tiling with custom target enrichment probes designed specifically to improve copy number variation (CNV) detection in these regions while maintaining exonic coverage of single nucleotide polymorphisms (SNPs), and insertions and deletions (INDELs). Herein we describe custom OneSeq, enabling higher resolution, exon-centric CNV detection in any genes of interest. When deployed in conjunction with existing exonic probes, they improve detection of biologically relevant CNVs in and near exons, while simultaneously detecting exonic SNPs and INDELs. The targeted CNV regions can be customized to address only a subset of genes, thus maximizing sequencing efficiency. We demonstrate that our approach improves detection of copy number changes with resolution often spanning just one or a few exons. Additionally, we identify aberrations in samples with either SNP/INDEL or CNV at a particular locus, and in some cases, compound heterozygotes with different aberrations in both alleles of the same locus. The addition of customizable, exon-centric OneSeq probes provides a means to detect exonic, intronic and intergenic CNVs, together with SNPs/ INDELs in a single assay. Conflict of Interest: All authors are employees of Agilent Technologies.

Genetic Susceptibility Loci for Childhood Acute Lymphoblastic Leukemia Among Japanese

Scrutiny of the human genome through evaluation of common genetic variants has revealed hundreds of disease susceptibility loci. In childhood acute lymphoblastic leukemia (ALL), six regions that have replicated in several populations are now considered known susceptibility loci (ARID5B, IKZF1, CEBPE, CDKN2A, PIP4K2A, and GATA3), but their effects have yet to be fully confirmed in populations of non-European ancestry. Targeted validation attempts based on the same SNPs originally identified in European ancestral populations have been performed in East Asians, but findings have been inconsistent. This may be due to differences in linkage disequilibrium patterns, allele frequency, and/or magnitude of effect between Europeans and East Asians; thus a comprehensive characterization of genetic variation across the targeted genetic loci is required for an appropriate validation attempt in different populations.Using a large network of hospitals within the Tokyo Children's Cancer Study Group, saliva samples from previously diagnosed childhood ALL patients (aged 0-19 years) were collected between December 2012 and May 2015. Genome-wide single nucleotide polymorphism (SNP) genotyping was performed and resulted in the inclusion of a total of 570 ALL patients, with genetic data available for up to about 500,000 SNPs after quality control exclusions. Control genome-wide data were available for 2,712 previously genotyped samples from the Nagahama Study Group and Aichi Cancer Center Study, Japan. SNP imputation was performed on the combined case-control dataset using ShapeIT and Minimac3, and the 1000 Genomes Project Phase I Version 3 as the reference population. Tests of association between childhood ALL and all available SNP genotypes across the six genes (mentioned above) implicated in previous genome-wide association studies was performed using logistic regression and assuming a log-additive model of inheritance.Of the six genomic regions examined, SNPs within the IKZF1, ARID5B, and PIP4K2A genes showed a statistically significant association with childhood ALL risk after Bonferroni correction. SNPs with the strongest evidence of association for these three genes included rs7090445 (ARID5B, OR=1.75, P =3.7x10-17), rs12533431 (IKZF1, OR=1.43, P =4.3x10-5), and rs11013045 (PIP4K2A, OR=0.76, P =9.5x10-5). Further examination of these regions indicated a second independently associated locus within ARID5B. Furthermore, we observed that the same previously reported primary ALL susceptibility SNPs for IKZF1 (e.g. rs4132601, rs11978267) and PIP4K2A (e.g. rs10828317, rs7088318) were not associated in Japanese. This highlights the importance of considering regional genetic variation comprehensively when testing the role of previously implicated candidate regions in a different racial/ethnic population. Characterization of the role of CEBPE, CDKN2A, and GATA3 genetic variation in Japanese may benefit from greater statistical power and potentially additional coverage of SNPs within these regions. DisclosuresNo relevant conflicts of interest to declare.

Japonica array: improved genotype imputation by designing a population-specific SNP array with 1070 Japanese individuals.

The Tohoku Medical Megabank Organization constructed the reference panel (referred to as the 1KJPN panel), which contains >20 million single nucleotide polymorphisms (SNPs), from whole-genome sequence data from 1070 Japanese individuals. The 1KJPN panel contains the largest number of haplotypes of Japanese ancestry to date. Here, from the 1KJPN panel, we designed a novel custom-made SNP array, named the Japonica array, which is suitable for whole-genome imputation of Japanese individuals. The array contains 659 253 SNPs, including tag SNPs for imputation, SNPs of Y chromosome and mitochondria, and SNPs related to previously reported genome-wide association studies and pharmacogenomics. The Japonica array provides better imputation performance for Japanese individuals than the existing commercially available SNP arrays with both the 1KJPN panel and the International 1000 genomes project panel. For common SNPs (minor allele frequency (MAF)>5%), the genomic coverage of the Japonica array (r2>0.8) was 96.9%, that is, almost all common SNPs were covered by this array. Nonetheless, the coverage of low-frequency SNPs (0.5%<MAF⩽5%) of the Japonica array reached 67.2%, which is higher than those of the existing arrays. In addition, we confirmed the high quality genotyping performance of the Japonica array using the 288 samples in 1KJPN; the average call rate 99.7% and the average concordance rate 99.7% to the genotypes obtained from high-throughput sequencer. As demonstrated in this study, the creation of custom-made SNP arrays based on a population-specific reference panel is a practical way to facilitate further association studies through genome-wide genotype imputations.

Association study of dopamine receptor genes polymorphism with cognitive functions in bipolar I disorder patients

ObjectiveTo determine the correlation among the polymorphisms of dopamine receptor genes, cognitive function of Bipolar disorder (BD) patients, and BD. MethodsTwenty-three Single Nucleotide Polymorphisms (SNPs) of dopamine receptor genes were genotyped using Illumina GoldenGate genotyping assay in 375 patients with bipolar I disorder (BD-I) (patients group) and 475 healthy controls (control group). Cognitive function tests were performed in 158 patients who were clinically stable and 307 healthy controls who were matched with the patients in age, sex, and education. ResultsThe allele frequencies of rs3758653 in the promoter region of the DRD4 gene were significantly different between patients group and control group (χ2=9.386, Corrected P=0.046). This significant difference was also observed between BD-I patients with psychotic symptoms and healthy controls (χ2=9.27, Corrected P=0.049). Patients with BD-I performed significantly worse than healthy controls in all cognitive domains (p<0.01) except TMTA errors and illegal time. Significant interactions between polymorphisms of rs5326 in DRD1 gene and phenotype (affected or unaffected with BD-I) were found in non-perseverative errors (β=3.20 and Corrected P=0.0034) on the Wisconsin Card Sorting Test (WCST). The allele of this SNP denoted the positive effect on the WCST non-perseverative errors in BD-I patients group (β=2.80 and Corrected P=0.017). The genotypic association analyses also supported the findings (F=4.24 and P=0.007), but this effect was not found in controls. LimitationsThe sample size was relatively small and the SNP coverage was limited, making it very important to be cautious when drawing a conclusion. ConclusionsDRD4 gene may play an important role in psychotic symptomatology rather than in unique diagnosis, BD, for example. A genetic association exists between DRD1 gene and impaired cognition in BD.

HLA-DRB1*15:01 allele protects from asthma susceptibility

HLA-DRB1*15:01 allele protects from asthma susceptibility

Rapid Identification of Alleles at the Soybean Maturity Gene E3 using genotyping by Sequencing and a Haplotype‐Based Approach

In eastern Canada, earliness is an important trait for soybean given the short growing season. The aim of this work was to develop tools for breeders to rapidly identify alleles present in their germplasm at the recently cloned maturity locus E3 (GmPhyA3). The tremendous throughput of modern DNA sequencing technology has allowed the use of genotyping by sequencing (GBS) approaches to identify and genotype thousands of single nucleotide polymorphisms (SNPs) across the entire genome. We have used a GBS protocol and SNP‐calling pipeline optimized for soybean to characterize 53 near‐isogenic lines (NILs) contrasting for maturity loci. Results obtained clearly showed the suitability of GBS to provide a dense SNP coverage and very accurate information on the location and size of introgressed regions. We then developed a GBS haplotype method to characterize 91 plant introductions (PIs) as well as a set of 305 lines representative of the Eastern Canadian germplasm for their allelic status at the GmPhyA3 gene. Six distinct haplotypes in and around the E3 locus were observed. Subsequent tests on two genotypes per haplotype (PCR test for a previously reported allele, sequencing entire gene), and validation on a subset of lines, allowed to determine that each of these corresponded to a different allele of this gene. We found that the functional allele E3Ha and the loss of function allele e3‐tr were the two most prevalent in the Eastern Canadian germplasm, while the e3‐fs allele was found at low frequency and e3‐ns was absent. These results show that this approach is a powerful method for rapid allelic characterization, and its application to other maturity genes will be useful for breeding purposes.

Assignment of SNP allelic configuration in polyploids using competitive allele-specific PCR: application to citrus triploid progeny

Polyploidy is a major component of eukaryote evolution. Estimation of allele copy numbers for molecular markers has long been considered a challenge for polyploid species, while this process is essential for most genetic research. With the increasing availability and whole-genome coverage of single nucleotide polymorphism (SNP) markers, it is essential to implement a versatile SNP genotyping method to assign allelic configuration efficiently in polyploids. This work evaluates the usefulness of the KASPar method, based on competitive allele-specific PCR, for the assignment of SNP allelic configuration. Citrus was chosen as a model because of its economic importance, the ongoing worldwide polyploidy manipulation projects for cultivar and rootstock breeding, and the increasing availability of SNP markers. Fifteen SNP markers were successfully designed that produced clear allele signals that were in agreement with previous genotyping results at the diploid level. The analysis of DNA mixes between two haploid lines (Clementine and pummelo) at 13 different ratios revealed a very high correlation (average = 0·9796; s.d. = 0·0094) between the allele ratio and two parameters [θ angle = tan(-1) (y/x) and y' = y/(x + y)] derived from the two normalized allele signals (x and y) provided by KASPar. Separated cluster analysis and analysis of variance (ANOVA) from mixed DNA simulating triploid and tetraploid hybrids provided 99·71 % correct allelic configuration. Moreover, triploid populations arising from 2n gametes and interploid crosses were easily genotyped and provided useful genetic information. This work demonstrates that the KASPar SNP genotyping technique is an efficient way to assign heterozygous allelic configurations within polyploid populations. This method is accurate, simple and cost-effective. Moreover, it may be useful for quantitative studies, such as relative allele-specific expression analysis and bulk segregant analysis.

Human genome epidemiology, progress and future

Human genome epidemiology, progress and future