Pair Of Alleles Research Articles

Transcripts of wheat at a target locus on chromosome 6B associated with increased yield, leaf mass and chlorophyll index under combined drought and heat stress.

Drought and heat stress constrain wheat (Triticum aestivum L.) yields globally. To identify putative mechanisms and candidate genes associated with combined drought and heat stress tolerance, we developed bread wheat near-isogenic lines (NILs) targeting a quantitative trait locus (QTL) on chromosome 6B which was previously associated with combined drought and heat stress tolerance in a diverse panel of wheats. Genotyping-by-sequencing was used to identify additional regions that segregated in allelic pairs between the recurrent and the introduced exotic parent, genome-wide. NILs were phenotyped in a gravimetric platform with precision irrigation and exposed to either drought or to combined drought and heat stress from three days after anthesis. An increase in grain weight in NILs carrying the exotic allele at 6B locus was associated with thicker, greener leaves, higher photosynthetic capacity and increased water use index after re-watering. RNA sequencing of developing grains at early and later stages of treatment revealed 75 genes that were differentially expressed between NILs across both treatments and timepoints. Differentially expressed genes coincided with the targeted QTL on chromosome 6B and regions of genetic segregation on chromosomes 1B and 7A. Pathway enrichment analysis showed the involvement of these genes in cell and gene regulation, metabolism of amino acids and transport of carbohydrates. The majority of these genes have not been characterized previously under drought or heat stress and they might serve as candidate genes for improved abiotic stress tolerance.

Abstract S03-02: Sequence-based prediction of SARS-CoV-2 vaccine targets using a mass spectrometry-based bioinformatics predictor identifies immunogenic T-cell epitopes

Abstract The ongoing COVID-19 pandemic has created an urgency to identify novel vaccine targets for protective immunity against SARS-CoV-2. Consistent with observations for the closely related SARS-CoV, early reports identify a protective role for both humoral and cell-mediated immunity for SARS-CoV-2. In this study, we leveraged our bioinformatics binding prediction tools for human leukocyte antigen (HLA)-I and HLA-II alleles that cover nearly the entire population and were developed using mass spectrometry-based profiling of 74 individual HLA-I and 83 individual HLA-II alleles. We applied these binding predictors, initially developed to predict tumor neoantigen presentation, to identify T-cell epitopes from SARS-CoV-2 proteins. To determine the ability of our tools to identify viral T-cell epitopes, we validated HLA-I and HLA-II predictions on Coronaviridae family epitopes deposited in the Virus Pathogen Database and Analysis Resource (ViPR) database. We then applied our HLA-I and HLA-II predictors to 13 open reading frames (ORFs) of SARS-CoV-2 and identified 11,897 HLA-I and 8,046 HLA-II candidate peptides that were highly ranked for binding. From our SARS-CoV-2 predicted peptide-HLA-I allele pairs, 374 pairs identically matched previously reported pairs in the ViPR database, originating from other coronaviruses with homologous sequences. Of these pairs, 333 (89 %) had a positive HLA-binding assay result, reinforcing the validity of our predictions. Furthermore, we assayed a subset of epitopes with highly predicted binding scores for their ability to be recognized by specific CD8+ T cell in human donor PBMCs. These epitopes were chosen from four structural proteins (S, N, M, E) and one nonstructural protein (ORF1ab) from SARS-CoV-2, and epitopes from all five proteins were found to be immunogenic. Finally, it was important to address the expression of SARS-CoV-2 proteins within cells since their subsequent processing is necessary for MHC presentation and the generation of specific epitopes. We utilized publicly available proteomic data to infer the relative expression of SARS-CoV-2 proteins from infected cell lines and determined that the different proteins vary significantly in their expression levels, with the nucleocapsid being the most highly expressed viral protein across these studies. Our predictions identify few epitopes from each SARS-CoV-2 protein, which are predicted to bind multiple HLA-I or HLA-II alleles, potentially covering over 99% of the USA, European, and Asian populations. Finally, using our bioinformatic platform, we identify multiple putative epitopes that are potential targets for CD4+ and CD8+ T cells whose predicted HLA binding properties cover nearly the entire population. We further propose that when considering the protein expression levels of these epitopes and their ability to elicit a T-cell response, these epitopes may be effective when included in vaccines against SARS-CoV-2 to induce broad cellular immunity. Citation Format: Asaf Poran, Dewi Harjanto, Matt Malloy, Christina M. Arieta, Daniel A. Rothenberg, Divya Lenkala, Marit M. van Buuren, Terri A. Addona, Michael S. Rooney, Lakshmi Srinivasan, Richard B. Gaynor. Sequence-based prediction of SARS-CoV-2 vaccine targets using a mass spectrometry-based bioinformatics predictor identifies immunogenic T-cell epitopes [abstract]. In: Proceedings of the AACR Virtual Meeting: COVID-19 and Cancer; 2020 Jul 20-22. Philadelphia (PA): AACR; Clin Cancer Res 2020;26(18_Suppl):Abstract nr S03-02.

Sequence-based prediction of SARS-CoV-2 vaccine targets using a mass spectrometry-based bioinformatics predictor identifies immunogenic T cell epitopes

BackgroundThe ongoing COVID-19 pandemic has created an urgency to identify novel vaccine targets for protective immunity against SARS-CoV-2. Early reports identify protective roles for both humoral and cell-mediated immunity for SARS-CoV-2.MethodsWe leveraged our bioinformatics binding prediction tools for human leukocyte antigen (HLA)-I and HLA-II alleles that were developed using mass spectrometry-based profiling of individual HLA-I and HLA-II alleles to predict peptide binding to diverse allele sets. We applied these binding predictors to viral genomes from the Coronaviridae family and specifically focused on T cell epitopes from SARS-CoV-2 proteins. We assayed a subset of these epitopes in a T cell induction assay for their ability to elicit CD8+ T cell responses.ResultsWe first validated HLA-I and HLA-II predictions on Coronaviridae family epitopes deposited in the Virus Pathogen Database and Analysis Resource (ViPR) database. We then utilized our HLA-I and HLA-II predictors to identify 11,897 HLA-I and 8046 HLA-II candidate peptides which were highly ranked for binding across 13 open reading frames (ORFs) of SARS-CoV-2. These peptides are predicted to provide over 99% allele coverage for the US, European, and Asian populations. From our SARS-CoV-2-predicted peptide-HLA-I allele pairs, 374 pairs identically matched what was previously reported in the ViPR database, originating from other coronaviruses with identical sequences. Of these pairs, 333 (89%) had a positive HLA binding assay result, reinforcing the validity of our predictions. We then demonstrated that a subset of these highly predicted epitopes were immunogenic based on their recognition by specific CD8+ T cells in healthy human donor peripheral blood mononuclear cells (PBMCs). Finally, we characterized the expression of SARS-CoV-2 proteins in virally infected cells to prioritize those which could be potential targets for T cell immunity.ConclusionsUsing our bioinformatics platform, we identify multiple putative epitopes that are potential targets for CD4+ and CD8+ T cells, whose HLA binding properties cover nearly the entire population. We also confirm that our binding predictors can predict epitopes eliciting CD8+ T cell responses from multiple SARS-CoV-2 proteins. Protein expression and population HLA allele coverage, combined with the ability to identify T cell epitopes, should be considered in SARS-CoV-2 vaccine design strategies and immune monitoring.

The Role of Brain-Derived Neurotrophic Factor and Serotonin Polymorphisms in Stress-Related Personality and Psychiatric Symptoms

Background: Diathesis-stress perspectives of cardiovascular (CV) health and disease have long identified the important role of a host of mental health risk and protective factors in both illness course and recovery. Few studies, however, have investigated these factors within the same sample of healthy people. Aims and Objectives: Accordingly, we focused on the inter-relationships among well-established CV mental health risk factors, specifically childhood adversity, stress-related adult personality traits and psychiatric symptoms, and naturally occurring genetic polymorphisms. Materials and Methods: Here 100 college students completed the NEO Five Factor Model of personality in conjunction with measures of childhood adversity, psychiatric symptoms as well as genetic variables derived from assays of the serotonin transporter (5-HTTLPR) and the brain-derived neurotrophic factor (BDNF). Results: Single gene comparisons pointed to lower CV risk, as reflected in personality and psychiatric symptom measures for BDNF Met versus Val/Val carriers. In addition, polygenic comparisons revealed a significant BDNF x 5-HTTLPR interactional effect, suggesting that this particular allelic combination may moderate the phenotypic expression of key personality traits, namely neuroticism and extraversion, as well as psychiatric symptoms, all linked to cardiovascular health. In fact, the data showed across personality and symptom measures, evidence of stress-resistance, resilience and protection for carriers of the allelic pair, BDNF Met and 5-HTTLPR-S. Conclusions: The findings suggested the Met variant of the BDNF gene had a risk-reducing and health-promoting effect when paired with the short serotonin allele, arguably reversing the commonly reported 5-HTTLPR-S association with stress vulnerability.

Effect of TRF1 rs3863242 polymorphism on telomere length in omethoate-exposed workers

Telomere length was found to be associated with omethoate exposure and polymorphisms in certain genes among occupational workers. However, whether the polymorphisms in telomere-binding protein genes influence telomere length remains unclear. To explore the correlation between telomere length and polymorphisms in telomere-binding protein genes, telomere length in peripheral blood leukocytes was determined by real-time quantitative polymerase chain reaction in 180 omethoate-exposed workers and 115 healthy controls. Polymorphisms in 10 pairs of alleles were detected using flight mass spectrometry or polymerase chain reaction–restriction fragment length polymorphism technique. The results showed that individuals with GG genotype in TRF1 rs3863242 had longer telomere lengths than those with AG + AA genotype in the control group (p = 0.005). The multiple regression analysis suggested that both omethoate exposure (b = 0.526, p < 0.001) and TRF1 rs3863242 GG (b = 0.220, p = 0.002) were related to a longer telomere length. In conclusion, GG genotype in TRF1 rs3863242 is linked to prolongation of telomere length, and individuals with GG genotype are recommended to strengthen health protection in a Chinese occupational omethoate-exposed population.

Differential Gene Expression between Fungal Mating Types Is Associated with Sequence Degeneration.

Degenerative mutations in non-recombining regions, such as in sex chromosomes, may lead to differential expression between alleles if mutations occur stochastically in one or the other allele. Reduced allelic expression due to degeneration has indeed been suggested to occur in various sex-chromosome systems. However, whether an association occurs between specific signatures of degeneration and differential expression between alleles has not been extensively tested, and sexual antagonism can also cause differential expression on sex chromosomes. The anther-smut fungus Microbotryum lychnidis-dioicae is ideal for testing associations between specific degenerative signatures and differential expression because 1) there are multiple evolutionary strata on the mating-type chromosomes, reflecting successive recombination suppression linked to mating-type loci; 2) separate haploid cultures of opposite mating types help identify differential expression between alleles; and 3) there is no sexual antagonism as a confounding factor accounting for differential expression. We found that differentially expressed genes were enriched in the four oldest evolutionary strata compared with other genomic compartments, and that, within compartments, several signatures of sequence degeneration were greater for differentially expressed than non-differentially expressed genes. Two particular degenerative signatures were significantly associated with lower expression levels within differentially expressed allele pairs: upstream insertion of transposable elements and mutations truncating the protein length. Other degenerative mutations associated with differential expression included nonsynonymous substitutions and altered intron or GC content. The association between differential expression and allele degeneration is relevant for a broad range of taxa where mating compatibility or sex is determined by genes located in large regions where recombination is suppressed.

MINERVA: Learning the Rules of HLA Class I Peptide Presentation in Tumors with Convolutional Neural Networks and Transfer Learning

Neoantigens act as surrogates for T cell immunoreactivity and have been shown to correlate with patients’ response to immune checkpoint inhibitors (ICI). Here, we have developed a multi-allele convolutional neural network-based model, MINERVA, for predicting HLA class I (HLA-I) presentation of tumor antigenic peptides using transfer learning with immunopeptidome data from cancer patients. We show that MINERVA recapitulates physicochemical properties of naturally presented peptides that are relevant to tumor biology and is more sensitive to tumor-derived HLA presented peptides than existing algorithms. Without a priori knowledge provided to MINERVA, the model was able to learn the determinants of peptide-HLA presentation and we utilized the learnt features to understand the impact of mutations on neoantigen presentation. Furthermore, we show that the diversity of tumor peptides being presented by a pair of alleles are significantly correlated with HLA sequence divergence. In conclusion, MINERVA is an open source software that can greatly facilitate tumor neoantigen discovery and guide cancer immunotherapies.

Paircounting

X inactivation presents two longstanding puzzles: the counting and choice of X chromosomes. Here, we consider counting and choice in the context of pairing, both of the X and of the autosomes.

A Comparative Genome-Wide Analysis of the R2R3-MYB Gene Family Among Four Gossypium Species and Their Sequence Variation and Association With Fiber Quality Traits in an Interspecific G. hirsutum × G. barbadense Population.

Cotton (Gossypium spp.) is the most important natural fiber crop in the world. The R2R3-MYB gene family is a large gene family involved in many plant functions including cotton fiber development. Although previous studies have reported its phylogenetic relationships, gene structures, and expression patterns in tetraploid G. hirsutum and diploid G. raimondii, little is known about the sequence variation of the members between G. hirsutum and G. barbadense and their involvement in the natural quantitative variation in fiber quality and yield. In this study, a comprehensive genome-wide comparative analysis was performed among the four Gossypium species using whole genome sequences, i.e., tetraploid G. hirsutum (AD1) and G. barbadense (AD2) as well as their likely ancestral diploid extants G. raimondii (D5) and G. arboreum (A2), leading to the identification of 406, 393, 216, and 213 R2R3-MYB genes, respectively. To elucidate whether the R2R3-MYB genes are genetically associated with fiber quality traits, 86 R2R3-MYB genes were co-localized with quantitative trait loci (QTL) hotspots for fiber quality and yield, including 42 genes localized within the fiber length QTL hotspots, in interspecific G. hirsutum × G. barbadense populations. There were 20 interspecific nonsynonymous single-nucleotide polymorphism (SNP) sites between the two tetraploid cultivated species, of which 16 developed from 11 R2R3-MYB genes were significantly correlated with fiber quality and yield in a backcross inbred population (BIL) of G. hirsutum × G. barbadense in at least one of the four field tests. Taken together, these results indicate that the sequence variation in these 11 R2R3-MYB genes is associated with the natural variation (i.e., QTL) in fiber quality and yield. Moreover, the functional SNPs of five R2R3-MYB allele pairs from the AD1 and AD2 genomes were significantly correlated with the gene expression related to fiber quality in fiber development. The results will be useful in further elucidating the role of the R2R3-MYB genes during fiber development.

Designing Allele-Specific Inhibitors of Spastin, a Microtubule-Severing AAA Protein.

The bump-hole approach is a powerful chemical biology strategy to specifically probe the functions of closely related proteins. However, for many protein families, such as the ATPases associated with diverse cellular activities (AAA), we lack structural data for inhibitor-protein complexes to design allele-specific chemical probes. Here we report the X-ray structure of a pyrazolylaminoquinazoline-based inhibitor bound to spastin, a microtubule-severing AAA protein, and characterize the residues involved in inhibitor binding. We show that an inhibitor analogue with a single-atom hydrogen-to-fluorine modification can selectively target a spastin allele with an engineered cysteine mutation in its active site. We also report an X-ray structure of the fluoro analogue bound to the spastin mutant. Furthermore, analyses of other mutant alleles suggest how the stereoelectronics of the fluorine-cysteine interaction, rather than sterics alone, contribute to the inhibitor-allele selectivity. This approach could be used to design allele-specific probes for studying cellular functions of spastin isoforms. Our data also suggest how tuning stereoelectronics can lead to specific inhibitor-allele pairs for the AAA superfamily.

Characterization of Non-heading Mutation in Heading Chinese Cabbage (Brassica rapa L. ssp. pekinensis).

Heading is a key agronomic trait of Chinese cabbage. A non-heading mutant with flat growth of heading leaves (fg-1) was isolated from an EMS-induced mutant population of the heading Chinese cabbage inbred line A03. In fg-1 mutant plants, the heading leaves are flat similar to rosette leaves. The epidermal cells on the adaxial surface of these leaves are significantly smaller, while those on the abaxial surface are much larger than in A03 plants. The segregation of the heading phenotype in the F2 and BC1 population suggests that the mutant trait is controlled by a pair of recessive alleles. Phytohormone analysis at the early heading stage showed significant decreases in IAA, ABA, JA and SA, with increases in methyl IAA and trans-Zeatin levels, suggesting they may coordinate leaf adaxial-abaxial polarity, development and morphology in fg-1. RNA-sequencing analysis at the early heading stage showed a decrease in expression levels of several auxin transport (BrAUX1, BrLAXs, and BrPINs) and responsive genes. Transcript levels of important ABA responsive genes, including BrABF3, were up-regulated in mid-leaf sections suggesting that both auxin and ABA signaling pathways play important roles in regulating leaf heading. In addition, a significant reduction in BrIAMT1 transcripts in fg-1 might contribute to leaf epinastic growth. The expression profiles of 19 genes with known roles in leaf polarity were significantly different in fg-1 leaves compared to wild type, suggesting that these genes might also regulate leaf heading in Chinese cabbage. In conclusion, leaf heading in Chinese cabbage is controlled through a complex network of hormone signaling and abaxial-adaxial patterning pathways. These findings increase our understanding of the molecular basis of head formation in Chinese cabbage.

High‐resolution characterization of 12 classical and non‐classical HLA loci in Southern Brazilians

The human leukocyte antigen (HLA) are the most polymorphic genes in the human genome. Because of their importance for antigen recognition, HLA molecules play a central role in host defense and graft rejection upon transplantation. The aim of this study was to characterize allelic diversity of the classical HLA genes HLA-A, -B, -C, -DRA, -DRB1, -DQA1, -DQB1, -DPA1, -DPB1, and the non-classical class I genes HLA-E, -F and -G at high-resolution for a population of predominantly European ancestry from Curitiba, Brazil. Genotyping of 108 individuals was performed by next-generation sequencing on the MiSeq platform and also by Sanger sequencing. The genotype distributions of all loci were in accordance with Hardy-Weinberg equilibrium (P > 0.05) and a total of 202 HLA variants at second field resolution were observed for the 12 loci. The strongest linkage disequilibrium (r2 = 1.0, P < 10-5 ) was observed for the following pairs of alleles: HLA-B*42:01:01 ~ HLA-DRB1*03:02:01; HLA-B*14:02:01 ~ HLA-C*08:02:01; B*42:01:01 ~ HLA-C*17:01:01; HLA-DRB1*03:01:01 ~ HLA-DQB1*02:01:01 ~ DRB1*03:01:01 ~ HLA-DQB1*02:01:01; DRB1*13:01:01~ HLA-DQB1*06:03:01 and HLA-DRB1*09:01:02 ~ HLA-DQA1*03:02. This is the first study to characterize all 12 HLA genes at high resolution in a single population. On the basis of the allelic frequencies of worldwide populations and principal component analysis, we confirmed the similarity of the study population to European and other Euro-descendant populations.

Application of SSR markers for assessment of genetic differentiation of silver fir (Abies alba Mill.) originating from Javor mountain

The process of plant breeding and conservation of gene pool among other things depends on the knowledge of the level of genetic differentiation. The aim of research in this paper was to determine the genetic differentiation of silver fir (Abies alba Mill.) populations of regular type and atypical genotypes with pyramidal crown that can be found on Javor mountain, at the site Ogorijevac. The genetic differentiation of silver fir was determined using SSR (Simple Sequence Repeat) markers. Nine SSR pairs of primers gave 29 alleles, while the average number of alleles was 3.2. The primer NFH15 gave the smallest number of alleles (two), while the primer SF78 gave the greatest number of alleles (five). Dice coefficient of the genetic similarity was used to obtain a dendrogram by UPMGA analysis using NTSYSpc statistical program. The genetic similarity recorded among the individuals P1 and P2 was the largest (0.89), while the populations VI and individual P2 showed the lowest similarity (0.61). Based on the cluster analysis it can be concluded that the studied populations and genotypes of silver fir with different types of crown are clearly differentiated. The basic insight into the level of the genetic diversity of the natural populations of silver fir with the various types of crown has been provided using selected SSR markers. The obtained results can be used for creating further strategy for the conservation of the available gene pool and the regeneration of silver fir forests in Serbia.

MOLECULAR CHARACTERIZATION OF GENES FOR QUALITY TRAITS IN MACEDONIAN WHEAT GENOTYPES (Triticum aestivum L.)

The main goal of this study was to characterize glutenin subunits with high molecular weight (HMW-GS) in Macedonian wheat genotypes by using DNA markers and to analyse the polymorphism of the Glu-A1 and Glu-D1 loci, influencing wheat bread-making quality. Polymorphysm and allelic variations in the Glu-A1 loci were determined through characterization of Ax-null, Ax1 and Ax2* alleles, and in Glu-D1 loci through characterization of Dx2+Dy12 and Dx5+Dy10 alleles. Ax null, that has a negative influence on bread-making quality, was detected in 77.66% of the genotypes. The allelic pair Dx5+Dy10 was present in 68.09% of the genotypes. Only 8.51% of the analysed genotypes had the allele Ax1. According to the identified alleles in the Glu A1 and Glu D1 loci, the genotypes were grouped in two main clusters, 64 in the first and 30 genotypes in the second cluster. Both clusters consisted of three subclusters, comprising different number of genotypes. The most of the genotypes belonged to the subgroups 1a (presence of Dx5+Dy10) and 2a (presence of Dx2+Dy12). Genotypes in the 2a subgroup had Ах-null in Glu-A1 locus and Dx2+Dy12 in Glu-D1 locus, negatively influencing the wheat bread-making quality. These genotypes are not recommended to be used in a breeding program for improving wheat bread-making quality. Genotypes from the subgroups 1b and 1c possessed the alleles Аx2* and Ax1 in Glu-A1 locus and Dx5+Dy10 in Glu-D1 locus, indicating good bread-making quality. The superior breeding lines with improved quality, good agronomic characteristics and high yield have to be evaluated for their adaptability and stability. The lines with a complex of positive characteristics may be submitted for registration of new varieties. Further investigations of the material are needed for the other loci influencing the wheat bread-making quality.

Accurate Prediction of RH Genotypes Using Whole Genome Sequencing Data

IntroductionRBC alloimmunization is common in patients with sickle cell disease (SCD). Despite serological matching RBCs for major Rh antigens, Rh alloimmunization remains problematic. The Rh blood group is encoded by two genes RHD and RHCE, which exhibit extensive nucleotide polymorphism and chromosome structural changes, resulting in the formation of Rh variant antigens. Rh variants can result in loss of protein epitopes or expression of neo-epitopes, and are common in SCD patients. Hence SCD patients harboring Rh variants can be predisposed to Rh alloimmunization. Given the limitation of traditional serologic antigen typing for detection of Rh variants, molecular genotyping has become required. A DNA microarray-based platform, BioArray RHCE and RHD BeadChip (Immuncor) is available for RH genotyping. However, it detects the most common, but not all, variants. Whole exome sequence data have been used for prediction of Rh variants (Chou, et. al, Blood Adv., 2017), offer some advantages, including detection of rare variants, structural rearrangements and copy number variation. However, whole genome sequence (WGS) analysis of RHD/RHCE is challenging due to difficulties in mapping next generation sequencing (NGS) reads to this duplicated gene family. We developed a computational algorithm to identify RH variants using WGS data.MethodsThe pipeline included three major components, RH allele database construction, RH variant calling, and classification of Rh blood group according the identified variants. The RH allele database was built based on NCBI Blood Group Antigen Gene Mutation (BGMUT) and International Society of Blood Transfusion (ISBT) database. Since the alleles in the BGMUT and ISBT databases were specified according to conventional RH genes (RHD, L08429; RHCE, DQ322275) that are different from those on reference human genome, we first called the variations based on the reference human genome. The positions of the identified variations were subsequently corrected to match with the BGMUT and ISBT annotation system. Next, the NGS reads with low base quality and/or mapping quality were discarded during the variation calling step. Synonymous and non-synonymous amino acid changes were characterized for each polymorphism. Haplotypes were constructed for the segments with NGS read support. Gene sequencing coverage was calculated to determine gene deletions or amplifications. Lastly, we implemented an algorithm to predict RH genotypes based on a selection of candidate alleles by read-mapping profile which considers both sequence variations and sequence consistency followed by a likelihood-based ranking of all pairwise combinations of the selected alleles. The allele combination with the highest likelihood is considered the most likely pair of alleles at a given locus. Patient specimens used in this study were from participants of the Sickle Cell Clinical Research and Intervention Program (SCCRIP, Hankins et al. Pediatr Blood Cancer. 2018).ResultsWe validated our method in a cohort of 58 SCD patients whose RH genotypes had been determined by BioArray RhCE and RhD BeadChip and supplementary molecular tests that identify the most common variants among individuals of African descent. In this validation cohort including a total of 11 RHD and 13 RHCE alleles, our approach achieved a concordance rate of 85.85% (91 of 106 alleles) for RHD and 83.02% (88 of 106 alleles) for RHCE genotyping. WGS was highly sensitive in distinguishing homozygosity from heterozygosity of genes. By comparing the numbers of NGS reads on RH regions and whole genome average coverage, heterozygous deletion can be determined. Since WGS provides comprehensive genotyping, our analysis identified single nucleotide polymorphisms that were not identified by the BeadChip and supplemental molecular testing. The final source of discordance was likely due to the short read length of NGS such that haplotype phases cannot be correctly predicted if the variations are separated by thousands of base pairs, for which long read DNA sequencing or RNA/cDNA sequencing are required. Evaluation of the identified discrepancies is ongoing.ConclusionsWe developed and validated a diagnostic method for RH genotyping that leveraged the accuracy and flexibility of RH genotyping based on WGS data. With further optimization of our method, this may be useful for RBC genotype matching sickle cell patients to blood donors in the future. DisclosuresHankins:Novartis: Research Funding; Global Blood Therapeutics: Research Funding; NCQA: Consultancy; bluebird bio: Consultancy.

P071 Limited exon sequence mismatches outside the antigen recognition domain in a cohort of 4646 high resolution 10/10 HLA-matched donor and recipient

Aim In hematopoietic stem cell transplantation (HCT), HLA allele matching between donor and recipient has traditionally focused on the polymorphic antigen recognition domain (ARD). Mismatching at the ARD is known to influence outcomes. This study investigated the genetic differences in the non-ARD regions among ARD-matched donor-recipient pairs to determine possible association with the transplant outcomes. Methods We compared the full-length HLA Class I allele sequences (HLA-A, -B, -C) and partial-length (partial intron 1 through partial intron 3) Class II allele sequences (HLA-DRB1, DQB1) for 4646 high-resolution 10/10 HLA-matched HCT donor-recipient pairs. We developed a comprehensive HLA allele sequence comparison pipeline, which identifies and annotates the mismatched positions between two alleles by their functional region and their protein sequence differences using IMGT/HLA Database (v3.31.0). Results For HLA Class I alleles, 95.4% of the ARD matched alleles have identical sequences outside the ARD, including introns and non-ARD exons. 0.3% of the mismatches were synonymous variants from the ARD region while 0.2% and 0.1% of mismatches found from non-ARD exons were synonymous and nonsynonymous variants, respectively. The intronic variation accounted for 4.2% of the mismatches. Similarly, for HLA Class II alleles, 0.3% of mismatches were synonymous ARD variants, and the mismatches in the non-ARD exons were also very rare (synonymous: 0.3%; nonsynonymous: 0.2%). However, a high degree of polymorphism was observed in the intronic regions of the Class II genes with only 77.3% of the allele pairs having identical sequences. 0.2% and 4.6% of Class I and Class II allele pairs, respectively, showed both exonic and intronic mismatches. Conclusions HCT donor/recipient pairs matched at high resolution for HLA-A, B, C, DRB1 and DQB1 have limited coding variation outside of the ARD. Intronic variation was observed at a higher rate for HLA Class II in our study compared to prior publications (17.3% vs.

Development of a new S locus haplotyping system based on three tightly linked genes in the S locus controlling self-incompatibility in radish (Raphanus sativus L.)

To develop an efficient and reliable haplotype identification system of the S locus controlling self-incompatibility (SI) in radish (Raphanus sativus L.), polymorphic sequences of the SLL2 and SP6 genes, which were located at each border of the S core regions, were used together with those of the SRK gene, the female determinant of SI. Partial sequences of the SP6 and SRK genes were isolated from 35 diverse breeding lines that showed differential self-incompatibility responses. A total of 25 SP6 and 29 SRK alleles were isolated in this study, and 29 SLL2 alleles isolated from the previous study were included for the S haplotyping. Whereas the phylogenetic tree of the SP6 alleles showed species-specific clustering patterns, the phylogenetic tree of the SRK alleles revealed intergeneric pairing of some SRK alleles, although the others showed species-specific clustering. Among 35 breeding lines, 13 had combinations of the unique SLL2, SRK, and SP6 alleles, but the others shared a common allele of either SLL2 or SP6 genes. Except for two breeding lines that contained the same SLL2, SRK, and SP6 alleles, all breeding lines were shown to harbor unique haplotypes that consisted of different combinations of SLL2, SRK, and SP6 alleles. When 73 additional diverse breeding lines were analyzed by this new S locus haplotyping system, the haplotypes of all breeding lines were clearly identified. In addition, eight new combinations that contained different combinations of the SLL2, SRK, and SP6 alleles were identified.

Massively parallel and multiplex blood group genotyping using next-generation-sequencing

ObjectivesThirty-six blood group systems are listed by the International Society of Blood Transfusion, containing almost 350 antigens. Most of these result from a single nucleotide polymorphism (SNP). Serology is the standard method for blood group typing. However, this technique has some limitations and cannot respond to the growing demand of blood product typing for a large number of antigens. Here we describe a blood group genotyping assay directly from whole blood samples using Next-Generation Sequencing (NGS), allowing the simultaneous identification of 15 SNPs associated with the blood group systems of 95 patients in a single run. Design and methodAfter an automated DNA extraction, targets are amplified by multiplex polymerase chain reaction (PCRm). Two panels addressing 9 groups have been developed (MNS, Lutheran, Kell, Duffy, Kidd, Diego, Yt, Dombrock, and Colton), one for 8 SNPs, the other for 7 SNPs. For each sample, both panels corresponding to 14 amplicons (1 amplicon containing 2 SNPs) are pooled. Then a dual-indexed library is generated from each pool by linking Illumina adaptors directly onto amplicons, followed by sequencing using the MiSeq platform (Illumina). ResultsIn a single experiment, 95 blood donor samples have been sequenced for the genes of interest. Among the 1425 targeted single nucleotide polymorphisms, 1420 were identified by sequencing, reflecting a coverage of 99.65%. The obtained data shows a good correlation (99% for all SNPs) with other blood group typing methods. Depending on the allele pairs analyzed, correlations vary between 97.12 and 100%.Conclusion: Next-Generation sequencing would supplement serological and molecular techniques and, in the near future, could replace it with complete and fast results acquisition for pre-screening and identification of rare blood bags.

Inheritance of fruit neck, rind and seed coat hardness, and seed coat colour in bottle gourd

Bottle gourd (Lagenaria siceraria (Molina) Standl.) is an edible, medicinal and decorative plant exhibiting wide genetic variation for fruit and seed characters, but it remains under-researched. This study assessed inheritance of fruit neck, fruit rind hardness, seed coat hardness and seed coat colour in bottle gourd, by crossing the egusi type with the calabash type. Results indicated that fruit neck is controlled by two genes, each with two alleles (N/n and R/r), with complementary gene action. Neckless fruit plants could be nnR−, N−rr or nnrr. A pair of alleles control each of fruit rind hardness (Hf /hf), seed coat hardness (Hs /hs) and seed coat colour (Y/y). Complete dominance of hard over soft was observed for fruit rind and seed coat hardness, whereas codominance of dark brown and yellow was observed for seed coat colour. These findings can hasten the efficiency of breeding and development of improved cultivars in L. siceraria.

Association of the CSN1S1 gene polymorphism with milk composition traits in Jamunapari goat

The genetic polymorphism of the CSN1S1 (casein alpha-s1) locus was investigated in Jamunapari goat breed by Sodium Dodicyle Sulphate – Poly Acrylamide Gel Electrophoresis (SDS-PAGE) and Polymerase Chain Reaction – Restriction Fragment Length Polymorphism (PCR-RFLP). A total of 122 milk and blood samples were collected. The SDS-PAGE pattern revealed the presence of four variants of CSN1S1 locus namely, A, B, E and F. The A allele of a-s1 – casein was observed in the majority of goats. The genotypic frequency of the AA, BB, BE, AF and FF genotypes of CSN1S1 locus were 0.437, 0.175, 0.250, 0.125 and 0.012, respectively. The PCR-RFLP was performed, six different variant groups of F allele (224)bp, the B/E allelic pair (161+63) bp, A/0 allelic pair (150+63) bp, AD allelic pair (212+150+63) bp, AF allelic pair (224+150+63) bp and BF allelic pair (224+160+63) were obtained after restriction digestion with XmnI. The genotypic frequency of AA, AD, AF, BB, BE, BF and BC genotypes were 0.274, 0.114, 0.147, 0.098, 0.163, 0.081 and 0.163, respectively. The allelic frequency of A, B, C, D, E and F were 0.360, 0.303, 0.081, 0.057, 0.081 and 0.114, respectively. The present study showed that AA genotype had significant effect on total protein content on the milk and AD genotype had significant effect on 90 day milk yield in Jamunapari goat. Thus the CSN1S1 genotype information in Jamunapari could be utilised in selection strategies, in order to select genetic stock for the production of goat milk with higher protein content in marker assisted selection to increase the rate of genetic gain.