Discovery Of Alleles Research Articles

Novel HLA-DQB1, DQA1, DPA1 and DPB1 alleles identified in the Australian New South Wales tissue typing laboratory

Introduction of NGS into clinical histocompatibility laboratories has greatly increased the frequency of novel HLA allele discovery. We identified 9 DQA1, 7 DQB1, 8 DPA1 and 2 DPB1 novel alleles over the last 2 years. 92% (24 of 26) differed from their closest allele by single nucleotide substitutions detected in coding regions and 84% (22 of 26) contained polymorphism outside of exon 2. Identification of novel alleles in non-coding intronic regions were restricted to splice sites. Two novel alleles arising from nucleotide substitution affecting splicing were identified and named with questionable expression status. Novel alleles with polymorphism detected only in non-coding regions (introns and UTRs) were not reported. 21 additional DQA1, DQB1 and DPA1 alleles detected in multiple individuals as novel at the time of testing, were also detected in other laboratories. The number of novel alleles detected further emphasises the role of NGS in novel allele discovery.

Ultrasensitive allele inference from immune repertoire sequencing data with MiXCR.

Allelic variability in the adaptive immune receptor loci, which harbor the gene segments that encode B cell and T cell receptors (BCR/TCR), is of critical importance for immune responses to pathogens and vaccines. Adaptive immune receptor repertoire sequencing (AIRR-seq) has become widespread in immunology research making it the most readily available source of information about allelic diversity in immunoglobulin (IG) and T cell receptor (TR) loci. Here we present a novel algorithm for extra-sensitive and specific variable (V) and joining (J) gene allele inference, allowing reconstruction of individual high-quality gene segment libraries. The approach can be applied for inferring allelic variants from peripheral blood lymphocyte BCR and TCR repertoire sequencing data, including hypermutated isotype-switched BCR sequences, thus allowing high-throughput novel allele discovery from a wide variety of existing datasets. The developed algorithm is a part of the MiXCR software. We demonstrate the accuracy of this approach using AIRR-seq paired with long-read genomic sequencing data, comparing it to a widely used algorithm, TIgGER. We applied the algorithm to a large set of IG heavy chain (IGH) AIRR-seq data from 450 donors of ancestrally diverse population groups, and to the largest reported full-length TCR alpha and beta chain (TRA; TRB) AIRR-seq dataset, representing 134 individuals. This allowed us to assess the genetic diversity within the IGH, TRA and TRB loci in different populations and to establish a database of alleles of V and J genes inferred from AIRR-seq data and their population frequencies with free public access through an online database.

CannSeek? Yes we Can! Anopen-source single nucleotide polymorphism database and analysis portal for Cannabis sativa.

The CannSeek portal is available at https://icgrc.info/cannseek, https://icgrc.info/genotype_viewer.

The cacao gene atlas: a transcriptome developmental atlas reveals highly tissue-specific and dynamically-regulated gene networks in Theobroma cacao L

BackgroundTheobroma cacao, the cocoa tree, is a tropical crop grown for its highly valuable cocoa solids and fat which are the basis of a 200-billion-dollar annual chocolate industry. However, the long generation time and difficulties associated with breeding a tropical tree crop have limited the progress of breeders to develop high-yielding disease-resistant varieties. Development of marker-assisted breeding methods for cacao requires discovery of genomic regions and specific alleles of genes encoding important traits of interest. To accelerate gene discovery, we developed a gene atlas composed of a large dataset of replicated transcriptomes with the long-term goal of progressing breeding towards developing high-yielding elite varieties of cacao.ResultsWe describe the creation of the Cacao Transcriptome Atlas, its global characterization and define sets of genes co-regulated in highly organ- and temporally-specific manners. RNAs were extracted and transcriptomes sequenced from 123 different tissues and stages of development representing major organs and developmental stages of the cacao lifecycle. In addition, several experimental treatments and time courses were performed to measure gene expression in tissues responding to biotic and abiotic stressors. Samples were collected in replicates (3–5) to enable statistical analysis of gene expression levels for a total of 390 transcriptomes. To promote wide use of these data, all raw sequencing data, expression read mapping matrices, scripts, and other information used to create the resource are freely available online. We verified our atlas by analyzing the expression of genes with known functions and expression patterns in Arabidopsis (ACT7, LEA19, AGL16, TIP13, LHY, MYB2) and found their expression profiles to be generally similar between both species. We also successfully identified tissue-specific genes at two thresholds in many tissue types represented and a set of genes highly conserved across all tissues.ConclusionThe Cacao Gene Atlas consists of a gene expression browser with graphical user interface and open access to raw sequencing data files as well as the unnormalized and CPM normalized read count data mapped to several cacao genomes. The gene atlas is a publicly available resource to allow rapid mining of cacao gene expression profiles. We hope this resource will be used to help accelerate the discovery of important genes for key cacao traits such as disease resistance and contribute to the breeding of elite varieties to help farmers increase yields.

Haplotype-resolved T2T genome assemblies and pangenome graph of pear reveal diverse patterns of allele-specific expression and the genomic basis of fruit quality traits

Hybrid crops often exhibit increased yield and greater resilience, yet the genomic mechanism(s) underlying hybrid vigor or heterosis remain unclear, hindering our ability to predict the expression of phenotypic traits in hybrid breeding. Here, we generated haplotype-resolved T2T genome assemblies of two pear hybrid varieties, ‘Yuluxiang’ (YLX) and ‘Hongxiangsu’ (HXS), which share the same maternal parent but differ in their paternal parents. We then used these assemblies to explore the genome-scale landscape of allele-specific expression (ASE) and create a pangenome graph for pear. ASE was observed for close to 6000 genes in both hybrid cultivars. A subset of ASE genes related to aspects of fruit quality such as sugars, organic acids, and cuticular wax were identified, suggesting their important contributions to heterosis. Specifically, Ma1, a gene regulating fruit acidity, is absent in the paternal haplotypes of HXS and YLX. A pangenome graph was built based on our assemblies and seven published pear genomes. Resequencing data for 139 cultivated pear genotypes (including 97 genotypes sequenced here) were subsequently aligned to the pangenome graph, revealing numerous structural variant hotspots and selective sweeps during pear diversification. As predicted, the Ma1 allele was found to be absent in varieties with low organic acid content, and this association was functionally validated by Ma1 overexpression in pear fruit and calli. Overall, these results reveal the contributions of ASE to fruit-quality heterosis and provide a robust pangenome reference for high-resolution allele discovery and association mapping.

Identification and analysis of novel recessive alleles for Tan1 and Tan2 in sorghum.

The identification and analysis of allelic variation are important bases for crop diversity research, trait domestication and molecular marker development. Grain tannin content is a very important quality trait in sorghum. Higher tannin levels in sorghum grains are usually required when breeding varieties resistant to bird damage or those used for brewing liquor. Non-tannin-producing or low-tannin-producing sorghum accessions are commonly used for food and forage. Tan1 and Tan2, two important cloned genes, regulate tannin biosynthesis in sorghum, and mutations in one or two genes will result in low or no tannin content in sorghum grains. Even if sorghum accessions contain dominant Tan1 and Tan2, the tannin contents are distributed from low to high, and there must be other new alleles of the known regulatory genes or new unknown genes contributing to tannin production. The two parents 8R306 and 8R191 did not have any known recessive alleles for Tan1 and Tan2, and it was speculated that they probably both had dominant Tan1 and Tan2 genotypes. However, the phenotypes of two parents were different; 8R306 had tannins and 8R191 had non-tannins in the grains, so these two parents were constructed as a RIL population. Bulked segregant analysis (BSA) was used to determine other new alleles of Tan1 and Tan2 or new Tannin locus. Tan1 and Tan2 full-length sequences and tannin contents were detected in wild sorghum resources, landraces and cultivars. We identified two novel recessive tan1-d and tan1-e alleles and four recessive Tan2 alleles, named as tan2-d, tan2-e, tan2-f, and tan2-g. These recessive alleles led to loss of function of Tan1 and Tan2, and low or no tannin content in sorghum grains. The loss-of-function alleles of tan1-e and tan2-e were only found in Chinese landraces, and other alleles were found in landraces and cultivars grown all around the world. tan1-a and tan1-b were detected in foreign landraces, Chinese cultivars and foreign cultivars, but not in Chinese landraces. These results implied that Tan1 and Tan2 recessive alleles had different geographically distribution in the worldwide, but not all recessive alleles had been used in breeding. The discovery of these new alleles provided new germplasm resources for breeding sorghum cultivars for food and feed, and for developing molecular markers for low-tannin or non-tannin cultivar-assisted breeding in sorghum.

Assessing myBaits Target Capture Sequencing Methodology Using Short-Read Sequencing for Variant Detection in Oat Genomics and Breeding.

The integration of target capture systems with next-generation sequencing has emerged as an efficient tool for exploring specific genetic regions with a high resolution and facilitating the rapid discovery of novel alleles. Despite these advancements, the application of targeted sequencing methodologies, such as the myBaits technology, in polyploid oat species remains relatively unexplored. In this study, we utilized the myBaits target capture method offered by Daicel Arbor Biosciences to detect variants and assess their reliability for variant detection in oat genomics and breeding. Ten oat genotypes were carefully chosen for targeted sequencing, focusing on specific regions on chromosome 2A to detect variants. The selected region harbors 98 genes. Precisely designed baits targeting the genes within these regions were employed for the target capture sequencing. We employed various mappers and variant callers to identify variants. After the identification of variants, we focused on the variants identified via all variants callers to assess the applicability of the myBaits sequencing methodology in oat breeding. In our efforts to validate the identified variants, we focused on two SNPs, one deletion and one insertion identified via all variant callers in the genotypes KF-318 and NOS 819111-70 but absent in the remaining eight genotypes. The Sanger sequencing of targeted SNPs failed to reproduce target capture data obtained through the myBaits technology. Similarly, the validation of deletion and insertion variants via high-resolution melting (HRM) curve analysis also failed to reproduce target capture data, again suggesting limitations in the reliability of the myBaits target capture sequencing using short-read sequencing for variant detection in the oat genome. This study shed light on the importance of exercising caution when employing the myBaits target capture strategy for variant detection in oats. This study provides valuable insights for breeders seeking to advance oat breeding efforts and marker development using myBaits target capture sequencing, emphasizing the significance of methodological sequencing considerations in oat genomics research.

Detection of novel HLA alleles by Next-Generation Sequencing in the Croatian population.

The introduction of Next-Generation Sequencing (NGS) methodology in the histocompatibility testing for both allo-HSCT and solid organ transplantation enables the sequencing of all HLA genes, which in turn leads to the discovery of many new HLA alleles. Over the last 3 years, we have identified 28 novel alleles (HLA-A*02:1079, A*03:01:01:112, A*11:01:01:83, A*11:01:01:87, A*24:595, A*68:01:01:15, B*07:02:01:107, B*08:01:01:67, B*08:01:01:69, B*13:02:01:25, B*15:01:82, B*15:18:08, B*18:01:01:76, B*27:02:06, B*27:05:02:34, B*40:06:01:17, B*40:517, C*04:01:01:173, C*04:477, C*05:276, C*07:01:01:130, C*12:03:80, C*12:03:01:62, DQA1*05:01:01:10, DPB1*13:01:07, DPB1*1146:01, DPB1*1456:01 and DPB1*1514:01) using the NGS method. The presented data emphasises the benefits gained by the utilisation of the NGS-based techniques in HLA genotyping but also provides new insight on the HLA polymorphism in the Croatian population.

Discovery of New Genomic Configuration of Mating-Type Loci in the Largest Lineage of Lichen-Forming Fungi.

The genetic architecture of mating-type loci in lichen-forming fungi has been characterized in very few taxa. Despite the limited data, and in contrast to all other major fungal lineages, arrangements that have both mating-type alleles in a single haploid genome have been hypothesized to be absent from the largest lineage of lichen-forming fungi, the Lecanoromycetes. We report the discovery of both mating-type alleles from the haploid genomes of three species within this group. Our results demonstrate that Lecanoromycetes are not an outlier among Ascomycetes.

Complex Polyploids: Origins, Genomic Composition, and Role of Introgressed Alleles.

Introgression allows polyploid species to acquire new genomic content from diploid progenitors or from other unrelated diploid or polyploid lineages, contributing to genetic diversity and facilitating adaptive allele discovery. In some cases, high levels of introgression elicit the replacement of large numbers of alleles inherited from the polyploid's ancestral species, profoundly reshaping the polyploid's genomic composition. In such complex polyploids, it is often difficult to determine which taxa were the progenitor species and which taxa provided additional introgressive blocks through subsequent hybridization. Here, we use population-level genomic data to reconstruct the phylogenetic history of Betula pubescens (downy birch), a tetraploid species often assumed to be of allopolyploid origin and which is known to hybridize with at least four other birch species. This was achieved by modeling polyploidization and introgression events under the multispecies coalescent and then using an approximate Bayesian computation rejection algorithm to evaluate and compare competing polyploidization models. We provide evidence that B. pubescens is the outcome of an autoploid genome doubling event in the common ancestor of B. pendula and its extant sister species, B. platyphylla, that took place approximately 178,000-188,000 generations ago. Extensive hybridization with B. pendula, B. nana, and B. humilis followed in the aftermath of autopolyploidization, with the relative contribution of each of these species to the B. pubescens genome varying markedly across the species' range. Functional analysis of B. pubescens loci containing alleles introgressed from B. nana identified multiple genes involved in climate adaptation, while loci containing alleles derived from B. humilis revealed several genes involved in the regulation of meiotic stability and pollen viability in plant species.

Into the Wild: A novel wild-derived inbred strain resource expands the genomic and phenotypic diversity of laboratory mouse models.

The laboratory mouse has served as the premier animal model system for both basic and preclinical investigations for over a century. However, laboratory mice capture only a subset of the genetic variation found in wild mouse populations, ultimately limiting the potential of classical inbred strains to uncover phenotype-associated variants and pathways. Wild mouse populations are reservoirs of genetic diversity that could facilitate the discovery of new functional and disease-associated alleles, but the scarcity of commercially available, well-characterized wild mouse strains limits their broader adoption in biomedical research. To overcome this barrier, we have recently developed, sequenced, and phenotyped a set of 11 inbred strains derived from wild-caught Mus musculus domesticus. Each of these "Nachman strains" immortalizes a unique wild haplotype sampled from one of five environmentally distinct locations across North and South America. Whole genome sequence analysis reveals that each strain carries between 4.73-6.54 million single nucleotide differences relative to the GRCm39 mouse reference, with 42.5% of variants in the Nachman strain genomes absent from current classical inbred mouse strain panels. We phenotyped the Nachman strains on a customized pipeline to assess the scope of disease-relevant neurobehavioral, biochemical, physiological, metabolic, and morphological trait variation. The Nachman strains exhibit significant inter-strain variation in >90% of 1119 surveyed traits and expand the range of phenotypic diversity captured in classical inbred strain panels. These novel wild-derived inbred mouse strain resources are set to empower new discoveries in both basic and preclinical research.

Enhancing genomic association studies in slash pine through close-range UAV-based morphological phenotyping.

In forestry genetics and industry, tree morphological traits such as height, crown size, and shape are critical for understanding growth dynamics and productivity. Traditional methods for measuring these traits are limited in efficiency, scalability, and accuracy, posing challenges for large-scale forest assessments. This study focuses on integrating unmanned aerial vehicle (UAV) technology with GWAS to improve genomic association studies in slash pine (Pinus elliottii). Seven key morphological traits have been identified (canopy area (CA), crown base height (CBH), crown length (CL), canopy volume (CV), crown width (CW), crown width height (CWH), and tree height (H)) through advanced UAV-based phenotyping. These associations account for a remarkable range of heritability in slash pine, with traits such as CBH, CL, CV, and H showing relatively high heritability across both Single nucleotide polymorphisms (SNP) and pedigree methods, indicating strong genetic influence, while traits such as CWH show lower heritability, suggesting greater environmental influence or non-additive genetic variance. The GWAS identified 28 associations, including 22 different SNPs localized to 16 candidate genes, that were significantly associated with the morphological traits of Slash Pine. Notably, two of these candidate genes, annotated as putative DEAD-like helicase and ethylene-responsive element binding factor (ERF), were present at different mutation sites and were significantly associated with CW and CA traits, respectively. These results demonstrate that the UAV imaging enables a comprehensive analysis of the Morphological growth response of slash pine and can facilitate the discovery of informative alleles to elucidate the genetic structure underlying complex phenotypic variation in conifers.

Pathogen-driven nucleotide overload triggers mitochondria-centered cell death in phagocytes.

Staphylococcus aureus is a dangerous pathogen that evolved refined immuno-evasive strategies to antagonize host immune responses. This involves the biogenesis of death-effector deoxyribonucleosides, which kill infectious foci-penetrating macrophages. However, the exact mechanisms whereby staphylococcal death-effector deoxyribonucleosides and coupled imbalances of intracellular deoxyribonucleotide species provoke immune cell death remain elusive. Here, we report that S. aureus systematically promotes an overload of deoxyribonucleotides to trigger mitochondrial rupture in macrophages, a fatal event that induces assembly of the caspase-9-processing apoptosome and subsequent activation of the intrinsic pathway of apoptosis. Remarkably, genetic disruption of this cascade not only helps macrophages coping with death-effector deoxyribonucleoside-mediated cytotoxicity but also enhances their infiltration into abscesses thereby ameliorating pathogen control and infectious disease outcomes in laboratory animals. Combined with the discovery of protective alleles in human CASP9, these data highlight the role of mitochondria-centered apoptosis during S. aureus infection and suggest that gene polymorphisms may shape human susceptibility toward a predominant pathogen.

Rapid Identification by Resequencing-Based QTL Mapping of a Novel Allele RGA1-FH Decreasing Grain Length in a Rice Restorer Line ‘Fuhui212’

Grain size is one of the most frequently selected traits during domestication and modern breeding. The continued discovery and characterization of new genes and alleles in controlling grain size are important in safeguarding the food supply for the world’s growing population. Previously, a small grain size was observed in a rice restorer line ‘Fuhui212’, while the underlying genetic factors controlling this trait were unknown. In this study, by combining QTL mapping, variant effect prediction, and complementation experiments, we recovered a novel allele RGA1-FH that explains most of the phenotypic changes. The RGA1-FH allele contains an A-to-T splicing site variant that disrupts the normal function of RGA1. While population analysis suggests extremely strong artificial selection in maintaining a functional allele of RGA1, our study is the first, to the best of our knowledge, to prove that a dysfunctional RGA1 allele can also be beneficial in real agricultural production. Future breeding programs would benefit from paying more attention to the rational utilization of those overlooked ‘unfavored’ alleles.

Resolution of structural variation in diverse mouse genomes reveals chromatin remodeling due to transposable elements

Diverse inbred mouse strains are important biomedical research models, yet genome characterization of many strains is fundamentally lacking in comparison with humans. In particular, catalogs of structural variants (SVs) (variants ≥ 50bp) are incomplete, limiting the discovery of causative alleles for phenotypic variation. Here, we resolve genome-wide SVs in 20 genetically distinct inbred mice with long-read sequencing. We report 413,758 site-specific SVs affecting 13% (356 Mbp) of the mouse reference assembly, including 510 previously unannotated coding variants. We substantially improve the Mus musculus transposable element (TE) callset, and we find that TEs comprise 39% of SVs and account for 75% of altered bases. We further utilize this callset to investigate how TE heterogeneity affects mouse embryonic stem cells and find multiple TE classes that influence chromatin accessibility. Our work provides a comprehensive analysis of SVs found in diverse mouse genomes and illustrates the role of TEs in epigenetic differences.

The Allele Catalog Tool: a web-based interactive tool for allele discovery and analysis

BackgroundThe advancement of sequencing technologies today has made a plethora of whole-genome re-sequenced (WGRS) data publicly available. However, research utilizing the WGRS data without further configuration is nearly impossible. To solve this problem, our research group has developed an interactive Allele Catalog Tool to enable researchers to explore the coding region allelic variation present in over 1,000 re-sequenced accessions each for soybean, Arabidopsis, and maize.ResultsThe Allele Catalog Tool was designed originally with soybean genomic data and resources. The Allele Catalog datasets were generated using our variant calling pipeline (SnakyVC) and the Allele Catalog pipeline (AlleleCatalog). The variant calling pipeline is developed to parallelly process raw sequencing reads to generate the Variant Call Format (VCF) files, and the Allele Catalog pipeline takes VCF files to perform imputations, functional effect predictions, and assemble alleles for each gene to generate curated Allele Catalog datasets. Both pipelines were utilized to generate the data panels (VCF files and Allele Catalog files) in which the accessions of the WGRS datasets were collected from various sources, currently representing over 1,000 diverse accessions for soybean, Arabidopsis, and maize individually. The main features of the Allele Catalog Tool include data query, visualization of results, categorical filtering, and download functions. Queries are performed from user input, and results are a tabular format of summary results by categorical description and genotype results of the alleles for each gene. The categorical information is specific to each species; additionally, available detailed meta-information is provided in modal popups. The genotypic information contains the variant positions, reference or alternate genotypes, the functional effect classes, and the amino-acid changes of each accession. Besides that, the results can also be downloaded for other research purposes.ConclusionsThe Allele Catalog Tool is a web-based tool that currently supports three species: soybean, Arabidopsis, and maize. The Soybean Allele Catalog Tool is hosted on the SoyKB website (https://soykb.org/SoybeanAlleleCatalogTool/), while the Allele Catalog Tool for Arabidopsis and maize is hosted on the KBCommons website (https://kbcommons.org/system/tools/AlleleCatalogTool/Zmays and https://kbcommons.org/system/tools/AlleleCatalogTool/Athaliana). Researchers can use this tool to connect variant alleles of genes with meta-information of species.

Increasing plant group productivity through latent genetic variation for cooperation.

Historic yield advances in the major crops have, to a large extent, been achieved by selection for improved productivity of groups of plant individuals such as high-density stands. Research suggests that such improved group productivity depends on "cooperative" traits (e.g., erect leaves, short stems) that-while beneficial to the group-decrease individual fitness under competition. This poses a problem for some traditional breeding approaches, especially when selection occurs at the level of individuals, because "selfish" traits will be selected for and reduce yield in high-density monocultures. One approach, therefore, has been to select individuals based on ideotypes with traits expected to promote group productivity. However, this approach is limited to architectural and physiological traits whose effects on growth and competition are relatively easy to anticipate. Here, we developed a general and simple method for the discovery of alleles promoting cooperation in plant stands. Our method is based on the game-theoretical premise that alleles increasing cooperation benefit the monoculture group but are disadvantageous to the individual when facing noncooperative neighbors. Testing the approach using the model plant Arabidopsis thaliana, we found a major effect locus where the rarer allele was associated with increased cooperation and productivity in high-density stands. The allele likely affects a pleiotropic gene, since we find that it is also associated with reduced root competition but higher resistance against disease. Thus, even though cooperation is considered evolutionarily unstable except under special circumstances, conflicting selective forces acting on a pleiotropic gene might maintain latent genetic variation for cooperation in nature. Such variation, once identified in a crop, could rapidly be leveraged in modern breeding programs and provide efficient routes to increase yields.

ApoE Modifier Alleles for Alzheimer's Disease Discovered by Information Theory Dependency Measures: MIST Software Package.

Information theory-based measures of variable dependency (previously published) have been implemented into a software package, MIST. The design of the software and its potential uses are described, and a demonstration is presented in the discovery of modifier alleles of the ApoE gene in affecting Alzheimer's disease (AD) by analyzing the UK Biobank dataset. The modifier genes uncovered overlap strongly with genes found to be associated with AD. Others include many known to influence AD. We discuss a range of uses of the dependency calculations using MIST that can uncover additional genetic effects in similar complex datasets, like higher degrees of interaction and phenotypic pleiotropy.

Whole genome sequence analysis of blood lipid levels in >66,000 individuals

Blood lipids are heritable modifiable causal factors for coronary artery disease. Despite well-described monogenic and polygenic bases of dyslipidemia, limitations remain in discovery of lipid-associated alleles using whole genome sequencing (WGS), partly due to limited sample sizes, ancestral diversity, and interpretation of clinical significance. Among 66,329 ancestrally diverse (56% non-European) participants, we associate 428M variants from deep-coverage WGS with lipid levels; ~400M variants were not assessed in prior lipids genetic analyses. We find multiple lipid-related genes strongly associated with blood lipids through analysis of common and rare coding variants. We discover several associated rare non-coding variants, largely at Mendelian lipid genes. Notably, we observe rare LDLR intronic variants associated with markedly increased LDL-C, similar to rare LDLR exonic variants. In conclusion, we conducted a systematic whole genome scan for blood lipids expanding the alleles linked to lipids for multiple ancestries and characterize a clinically-relevant rare non-coding variant model for lipids.

Sequencing individual genomes with recurrent genomic disorder deletions: an approach to characterize genes for autosomal recessive rare disease traits

BackgroundIn medical genetics, discovery and characterization of disease trait contributory genes and alleles depends on genetic reasoning, study design, and patient ascertainment; we suggest a segmental haploid genetics approach to enhance gene discovery and molecular diagnostics.MethodsWe constructed a genome-wide map for nonallelic homologous recombination (NAHR)-mediated recurrent genomic deletions and used this map to estimate population frequencies of NAHR deletions based on large-scale population cohorts and region-specific studies. We calculated recessive disease carrier burden using high-quality pathogenic or likely pathogenic variants from ClinVar and gnomAD. We developed a NIRD (NAHR deletion Impact to Recessive Disease) score for recessive disorders by quantifying the contribution of NAHR deletion to the overall allele load that enumerated all pairwise combinations of disease-causing alleles; we used a Punnett square approach based on an assumption of random mating. Literature mining was conducted to identify all reported patients with defects in a gene with a high NIRD score; meta-analysis was performed on these patients to estimate the representation of NAHR deletions in recessive traits from contemporary human genomics studies. Retrospective analyses of extant clinical exome sequencing (cES) were performed for novel rare recessive disease trait gene and allele discovery from individuals with NAHR deletions.ResultsWe present novel genomic insights regarding the genome-wide impact of NAHR recurrent segmental variants on recessive disease burden; we demonstrate the utility of NAHR recurrent deletions to enhance discovery in the challenging context of autosomal recessive (AR) traits and biallelic variation. Computational results demonstrate new mutations mediated by NAHR, involving recurrent deletions at 30 genomic regions, likely drive recessive disease burden for over 74% of loci within these segmental deletions or at least 2% of loci genome-wide. Meta-analyses on 170 literature-reported patients implicate that NAHR deletions are depleted from the ascertained pool of AR trait alleles. Exome reanalysis of personal genomes from subjects harboring recurrent deletions uncovered new disease-contributing variants in genes including COX10, ERCC6, PRRT2, and OTUD7A.ConclusionsOur results demonstrate that genomic sequencing of personal genomes with NAHR deletions could dramatically improve allele and gene discovery and enhance clinical molecular diagnosis. Moreover, results suggest NAHR events could potentially enable human haploid genetic screens as an approach to experimental inquiry into disease biology.