Analysis of stop-gain and frameshift variants in human innate immunity genes

An integrative framework for clinical diagnosis and knowledge discovery from exome sequencing data

Non-silent single nucleotide genetic variants, like nonsense changes and insertion-deletion variants, that affect protein function and length substantially are prevalent and are frequently misclassified. The low sensitivity and specificity of existing variant effect predictors for nonsense and indel variations restrict their use in clinical applications. We propose the Pathogenic Mutation Prediction (PMPred) method to predict the pathogenicity of single nucleotide variations, which impair protein function by prematurely terminating a protein's elongation during its synthesis. The prediction starts by monitoring functional effects (Gene Ontology annotation changes) of the change in sequence, using an existing ensemble machine learning model (UniGOPred). This, in turn, reveals the mutations that significantly deviate functionally from the wild-type sequence. We have identified novel harmful mutations in patient data and present them as motivating case studies. We also show that our method has increased sensitivity and specificity compared to state-of-the-art, especially in single nucleotide variations that produce large functional changes in the final protein. As further validation, we have done a comparative docking study on such a variation that is misclassified by existing methods and, using the altered binding affinities, show how PMPred can correctly predict the pathogenicity when other tools miss it. PMPred is freely accessible as a web service at https://pmpred.kansil.org/, and the related code is available at https://github.com/kansil/PMPred.

An FGFR2 mutation as the potential cause of a new phenotype including early-onset osteoporosis and bone fractures: a case report

Osteoporosis is a systemic, multifactorial disorder of bone mineralization. Many factors contributing to the development of osteoporosis have been identified so far, including gender, age, nutrition, lifestyle, exercise, drug use, as well as a range of comorbidities. In addition to environmental and lifestyle factors, molecular genetic factors account for 50-85% of osteoporosis cases. For example, the vitamin D receptor (VDR), collagen type I (COL1), estrogen receptor (ER), apolypoprotein Е (ApoE), bone morphogenetic protein (BMP), and Low-density lipoprotein receptor-related protein 5 (LRP5) are all involved in the pathogenesis of osteoporosis. Among the candidate genes, the pathogenic variants in which are involved in the pathogenesis of osteoporosis is FGFR2. Additionally, FGFs/FGFRs-dependent signaling has been shown to regulate skeletal development and has been linked to a plethora of heritable disorders of the musculoskeletal system. In this study we present the clinical, biochemical and radiological findings, as well as results of molecular genetic testing of a 13-year-old male proband with heritable osteoporosis, arthralgia and multiple fractures and a family history of abnormal bone mineralization and fractures. Whole exome sequencing found a heterozygous previously undescribed variant in the FGFR2 gene (NM_000141.5) (GRCh37.p13 ENSG00000066468.16: g.123298133dup; ENST00000358487.5:c.722dup; ENSP00000351276.5:p.Asn241LysfsTer43). The same variant was found in two affected relatives. These data lead us to believe that the variant in FGFR2 found in our proband and his relatives could be related to their phenotype. Therefore, modern methods of molecular genetic testing can allow us to differentiate between osteogenesis imperfecta and other bone mineralization disorders.

Common protein-coding variants influence the racing phenotype in galloping racehorse breeds

Selection for system-wide morphological, physiological, and metabolic adaptations has led to extreme athletic phenotypes among geographically diverse horse breeds. Here, we identify genes contributing to exercise adaptation in racehorses by applying genomics approaches for racing performance, an end-point athletic phenotype. Using an integrative genomics strategy to first combine population genomics results with skeletal muscle exercise and training transcriptomic data, followed by whole-genome resequencing of Asian horses, we identify protein-coding variants in genes of interest in galloping racehorse breeds (Arabian, Mongolian and Thoroughbred). A core set of genes, G6PC2, HDAC9, KTN1, MYLK2, NTM, SLC16A1 and SYNDIG1, with central roles in muscle, metabolism, and neurobiology, are key drivers of the racing phenotype. Although racing potential is a multifactorial trait, the genomic architecture shaping the common athletic phenotype in horse populations bred for racing provides evidence for the influence of protein-coding variants in fundamental exercise-relevant genes. Variation in these genes may therefore be exploited for genetic improvement of horse populations towards specific types of racing.

X-CAP improves pathogenicity prediction of stopgain variants

Stopgain substitutions are the third-largest class of monogenic human disease mutations and often examined first in patient exomes. Existing computational stopgain pathogenicity predictors, however, exhibit poor performance at the high sensitivity required for clinical use. Here, we introduce a new classifier, termed X-CAP, which uses a novel training methodology and unique feature set to improve the AUROC by 18% and decrease the false-positive rate 4-fold on large variant databases. In patient exomes, X-CAP prioritizes causal stopgains better than existing methods do, further illustrating its clinical utility. X-CAP is available at https://github.com/bejerano-lab/X-CAP .

PARD3 gene variation as candidate cause of nonsyndromic cleft palate only

Nonsyndromic cleft palate only (NSCP) is a common congenital malformation worldwide. In this study, we report a three‐generation pedigree with NSCP following the autosomal‐dominant pattern. Whole‐exome sequencing and Sanger sequencing revealed that only the frameshift variant c.1012dupG [p. E338Gfs*26] in PARD3 cosegregated with the disease. In zebrafish embryos, ethmoid plate patterning defects were observed with PARD3 ortholog disruption or expression of patient‐derived N‐terminal truncating PARD3 (c.1012dupG), which implicated PARD3 in ethmoid plate morphogenesis. PARD3 plays vital roles in determining cellular polarity. Compared with the apical distribution of wild‐type PARD3, PARD3‐p. E338Gfs*26 mainly localized to the basal membrane in 3D‐cultured MCF‐10A epithelial cells. The interaction between PARD3‐p. E338Gfs*26 and endogenous PARD3 was identified by LC–MS/MS and validated by co‐IP. Immunofluorescence analysis showed that PARD3‐p. E338Gfs*26 substantially altered the localization of endogenous PARD3 to the basement membrane in 3D‐cultured MCF‐10A cells. Furthermore, seven variants, including one nonsense variant and six missense variants, were identified in the coding region of PARD3 in sporadic cases with NSCP. Subsequent analysis showed that PARD3‐p. R133*, like the insertion variant of c.1012dupG, also changed the localization of endogenous full‐length PARD3 and that its expression induced abnormal ethmoid plate morphogenesis in zebrafish. Based on these data, we reveal PARD3 gene variation as a novel candidate cause of nonsyndromic cleft palate only.

Less Is More, Natural Loss-of-Function Mutation Is a Strategy for Adaptation

Gene gain and loss are crucial factors that shape the evolutionary success of diverse organisms. In the past two decades, more attention has been paid to the significance of gene gain through gene duplication or de novo genes. However, gene loss through natural loss-of-function (LoF) mutations, which is prevalent in the genomes of diverse organisms, has been largely ignored. With the development of sequencing techniques, many genomes have been sequenced across diverse species and can be used to study the evolutionary patterns of gene loss. In this review, we summarize recent advances in research on various aspects of LoF mutations, including their identification, evolutionary dynamics in natural populations, and functional effects. In particular, we discuss how LoF mutations can provide insights into the minimum gene set (or the essential gene set) of an organism. Furthermore, we emphasize their potential impact on adaptation. At the genome level, although most LoF mutations are neutral or deleterious, at least some of them are under positive selection and may contribute to biodiversity and adaptation. Overall, we highlight the importance of natural LoF mutations as a robust framework for understanding biological questions in general.

Common homozygosity for predicted loss-of-function variants reveals both redundant and advantageous effects of dispensable human genes

Humans homozygous or hemizygous for variants predicted to cause a loss of function (LoF) of the corresponding protein do not necessarily present with overt clinical phenotypes. We report here 190 autosomal genes with 207 predicted LoF variants, for which the frequency of homozygous individuals exceeds 1% in at least one human population from five major ancestry groups. No such genes were identified on the X and Y chromosomes. Manual curation revealed that 28 variants (15%) had been misannotated as LoF. Of the 179 remaining variants in 166 genes, only 11 alleles in 11 genes had previously been confirmed experimentally to be LoF. The set of 166 dispensable genes was enriched in olfactory receptor genes (41 genes). The 41 dispensable olfactory receptor genes displayed a relaxation of selective constraints similar to that observed for other olfactory receptor genes. The 125 dispensable nonolfactory receptor genes also displayed a relaxation of selective constraints consistent with greater redundancy. Sixty-two of these 125 genes were found to be dispensable in at least three human populations, suggesting possible evolution toward pseudogenes. Of the 179 LoF variants, 68 could be tested for two neutrality statistics, and 8 displayed robust signals of positive selection. These latter variants included a known FUT2 variant that confers resistance to intestinal viruses, and an APOL3 variant involved in resistance to parasitic infections. Overall, the identification of 166 genes for which a sizeable proportion of humans are homozygous for predicted LoF alleles reveals both redundancies and advantages of such deficiencies for human survival.

Detection of homozygous genotypes for a putatively lethal recessive mutation in the porcine argininosuccinate synthase 1 (ASS1) gene

The sequencing of the pig genome revealed the existence of homozygous individuals for a nonsense mutation in the argininosuccinate synthase 1 (ASS1) gene (rs81212146, c.944T>A, L315X). Paradoxically, an AA homozygous genotype for this polymorphism is expected to abolish the function of the ASS1 enzyme that participates in the urea cycle, leading to citrullinemia, hyperammonemia, coma and death. Sequencing of five Duroc boars that sired a population of 350 Duroc barrows revealed the segregation of the c.944T>A polymorphism, so we aimed to investigate its phenotypic consequences. Genotyping of this mutation in the 350 Duroc barrows revealed the existence of seven individuals homozygous (AA) for the nonsense mutation. These AA pigs had a normal weight despite the fact that mild citrullinemia often involves impaired growth. Sequencing of the region surrounding the mutation in TT, TA and AA individuals revealed that the A substitution in the second position of the codon (c.944T>A) is in complete linkage disequilibrium with a C replacement (c.943T>C) in the first position of the codon. This second mutation would compensate for the potentially damaging effect of the c.944T>A replacement. In fact, this is the most probable reason why pigs with homozygous AA genotypes at the 944 site of the ASS1 coding region are alive. Our results illustrate the complexities of predicting the consequences of nonsense mutations on gene function and phenotypes, not only because of annotation issues but also owing to the existence of genetic mechanisms that sometimes limit the penetrance of highly harmful mutations.

NCBoost classifies pathogenic non-coding variants in Mendelian diseases through supervised learning on purifying selection signals in humans

State-of-the-art methods assessing pathogenic non-coding variants have mostly been characterized on common disease-associated polymorphisms, yet with modest accuracy and strong positional biases. In this study, we curated 737 high-confidence pathogenic non-coding variants associated with monogenic Mendelian diseases. In addition to interspecies conservation, a comprehensive set of recent and ongoing purifying selection signals in humans is explored, accounting for lineage-specific regulatory elements. Supervised learning using gradient tree boosting on such features achieves a high predictive performance and overcomes positional bias. NCBoost performs consistently across diverse learning and independent testing data sets and outperforms other existing reference methods.

Sequence variants in muscle tissue-related genes may determine the severity of muscle contractures in cerebral palsy

Muscle contractures are a common complication to cerebral palsy (CP). The purpose of this study was to evaluate whether individuals with CP carry specific gene variants of important structural genes that might explain the severity of muscle contractures. Next-generation-sequencing (NGS) of 96 candidate genes associated with muscle structure and metabolism were analyzed in 43 individuals with CP (Gross Motor Function classification system [GMFCS] I, n=10; GMFCS II, n=14; GMFCS III, n=19) and four control participants. In silico analysis of the identified variants was performed. The variants were classified into four categories ranging from likely benign (VUS0) to highly likely functional effect (VUS3). All individuals with CP were classified and grouped according to their GMFCS level: Statistical comparisons were made between GMFCS groups. Kruskal-Wallis tests showed significantly more VUS2 variants in the genes COL4 (GMFCS I-III; 1, 1, 5, respectively [p < .04]), COL5 (GMFCS I-III; 1, 1, 5 [p < .04]), COL6 (GMFCS I-III; 0, 4, 7 [p < .003]), and COL9 (GMFCS I-III; 1, 1, 5 [p < .04]), in individuals with CP within GMFCS Level III when compared to the other GMFCS levels. Furthermore, significantly more VUS3 variants in COL6 (GMFCS I-III; 0, 5, 2 [p < .01]) and COL7 (GMFCS I-III; 0, 3, 0 [p < .04]) were identified in the GMFCS II level when compared to the other GMFCS levels. The present results highlight several candidate gene variants in different collagen types with likely functional effects in individuals with CP.

Computational Methods for the Pharmacogenetic Interpretation of Next Generation Sequencing Data

Up to half of all patients do not respond to pharmacological treatment as intended. A substantial fraction of these inter-individual differences is due to heritable factors and a growing number of associations between genetic variations and drug response phenotypes have been identified. Importantly, the rapid progress in Next Generation Sequencing technologies in recent years unveiled the true complexity of the genetic landscape in pharmacogenes with tens of thousands of rare genetic variants. As each individual was found to harbor numerous such rare variants they are anticipated to be important contributors to the genetically encoded inter-individual variability in drug effects. The fundamental challenge however is their functional interpretation due to the sheer scale of the problem that renders systematic experimental characterization of these variants currently unfeasible. Here, we review concepts and important progress in the development of computational prediction methods that allow to evaluate the effect of amino acid sequence alterations in drug metabolizing enzymes and transporters. In addition, we discuss recent advances in the interpretation of functional effects of non-coding variants, such as variations in splice sites, regulatory regions and miRNA binding sites. We anticipate that these methodologies will provide a useful toolkit to facilitate the integration of the vast extent of rare genetic variability into drug response predictions in a precision medicine framework.

Association study of the three functional polymorphisms (TAS2R46G>A, OR4C16G>A, and OR4X1A>T) with recurrent pregnancy loss

This study was purposed to investigate whether genetic polymorphisms in the function of stop-gain are associated with a fetal or placental development play roles and a development of idiopathic recurrent pregnancy loss (RPL) in Korean females. Three stop-gain polymorphisms were selected using next-generation sequencing screening, which allows for the rigorous examination and discovery of previously uncharacterized stop-gain genes and stop-gain expression profiles. Accordingly, we investigated the association of stop-gain polymorphisms in Korean women with RPL. Three functional polymorphisms in the TAS2R46G>A (rs2708381), OR4C16G>A (rs1459101), and OR4X1A>T (rs10838851) genes were genotyped using polymerase chain reaction (PCR)-restriction fragment length polymorphism assays and real-time PCR analysis. We determined that the OR4C16G>A polymorphism was associated with idiopathic RPL in Korean women (Adjusted odds ratio [AOR] 1.782; 95% confidence interval [CI] 1.004-3.163; P = 0.048, and AOR 1.766; 95% CI 1.020-3.059; P = 0.042). In addition, the prevalence of RPL was increased in women with the OR4C16GA + AA genotype and blood coagulation measures of prothrombin time (PT) > 10.4 s (AOR 8.292; 95% CI 2.744-25.054). We suggest that the OR4C16G>A polymorphism might serve as a clinically useful biomarker for the development, prevention, and prognosis of RPL.

Cancer driver mutation prediction through Bayesian integration of multi-omic data

Identification of cancer driver mutations is critical for advancing cancer research and personalized medicine. Due to inter-tumor genetic heterogeneity, many driver mutations occur at low frequencies, which make it challenging to distinguish them from passenger mutations. Here, we show that a novel Bayesian hierarchical modeling approach, named rDriver can achieve enhanced prediction accuracy by identifying mutations that not only have high functional impact scores but also are associated with systemic variation in gene expression levels. In examining 3,080 tumor samples from 8 cancer types in The Cancer Genome Atlas, rDriver predicted 1,389 driver mutations. Compared with existing tools, rDriver identified more low frequency mutations associated with lineage specific functional properties, timing of occurrence and patient survival. Evaluation of rDriver predictions using engineered cell-line models resulted in a positive predictive value of 0.94 in PIK3CA genes. Our study highlights the importance of integrating multi-omic data in predicting cancer driver mutations and provides a statistically rigorous solution for cancer target discovery and development.

Using ALoFT to determine the impact of putative loss-of-function variants in protein-coding genes

Variants predicted to result in the loss of function of human genes have attracted interest because of their clinical impact and surprising prevalence in healthy individuals. Here, we present ALoFT (annotation of loss-of-function transcripts), a method to annotate and predict the disease-causing potential of loss-of-function variants. Using data from Mendelian disease-gene discovery projects, we show that ALoFT can distinguish between loss-of-function variants that are deleterious as heterozygotes and those causing disease only in the homozygous state. Investigation of variants discovered in healthy populations suggests that each individual carries at least two heterozygous premature stop alleles that could potentially lead to disease if present as homozygotes. When applied to de novo putative loss-of-function variants in autism-affected families, ALoFT distinguishes between deleterious variants in patients and benign variants in unaffected siblings. Finally, analysis of somatic variants in >6500 cancer exomes shows that putative loss-of-function variants predicted to be deleterious by ALoFT are enriched in known driver genes.Variants causing loss of function (LoF) of human genes have clinical implications. Here, the authors present a method to predict disease-causing potential of LoF variants, ALoFT (annotation of Loss-of-Function Transcripts) and show its application to interpreting LoF variants in different contexts.

When loss-of-function is loss of function: assessing mutational signatures and impact of loss-of-function genetic variants

MOTIVATION

Loss-of-function genetic variants are frequently associated with severe clinical phenotypes, yet many are present in the genomes of healthy individuals. The available methods to assess the impact of these variants rely primarily upon evolutionary conservation with little to no consideration of the structural and functional implications for the protein. They further do not provide information to the user regarding specific molecular alterations potentially causative of disease.

RESULTS

To address this, we investigate protein features underlying loss-of-function genetic variation and develop a machine learning method, MutPred-LOF, for the discrimination of pathogenic and tolerated variants that can also generate hypotheses on specific molecular events disrupted by the variant. We investigate a large set of human variants derived from the Human Gene Mutation Database, ClinVar and the Exome Aggregation Consortium. Our prediction method shows an area under the Receiver Operating Characteristic curve of 0.85 for all loss-of-function variants and 0.75 for proteins in which both pathogenic and neutral variants have been observed. We applied MutPred-LOF to a set of 1142 de novo vari3ants from neurodevelopmental disorders and find enrichment of pathogenic variants in affected individuals. Overall, our results highlight the potential of computational tools to elucidate causal mechanisms underlying loss of protein function in loss-of-function variants.

AVAILABILITY AND IMPLEMENTATION

http://mutpred.mutdb.org.

CONTACT

predrag@indiana.edu.

Primary immunodeficiencies suggest redundancy within the human immune system

Pathogen-driven evolution has shaped the complexity of the human immune system. Our genome contains at least 1854 gene products involved in immune responses. However, the redundancy and robustness of the immune system need further characterization. One way to examine this redundancy is through the study of monogenic primary immunodeficiencies (PIDs) associated with infections. Causal mutations affecting innate immunity genes are, in relative terms, close to seven times less frequent than those affecting adaptive immunity genes in PIDs. Loss-of-function mutations of innate immunity genes encoding pattern-recognition receptors (PRRs) and associated pathways rarely cause susceptibility to infections, which suggests that PRR pathways are partially redundant in the immune responses to infection. This dispensability has also been observed for constitutive products of the immune system, such as secretory immunoglobulin A, and for innate immune cells, such as natural killer and innate lymphoid cell subsets, which are not essential for viability. This Review discusses these findings in the context of their implications for the identification of previously unknown classes of PIDs and assessment of the susceptibility to infection associated with various targeted immunotherapies.

eMERGE Phenome-Wide Association Study (PheWAS) identifies clinical associations and pleiotropy for stop-gain variants

BACKGROUND

We explored premature stop-gain variants to test the hypothesis that variants, which are likely to have a consequence on protein structure and function, will reveal important insights with respect to the phenotypes associated with them. We performed a phenome-wide association study (PheWAS) exploring the association between a selected list of functional stop-gain genetic variants (variation resulting in truncated proteins or in nonsense-mediated decay) and an extensive group of diagnoses to identify novel associations and uncover potential pleiotropy.

RESULTS

In this study, we selected 25 stop-gain variants: 5 stop-gain variants with previously reported phenotypic associations, and a set of 20 putative stop-gain variants identified using dbSNP. For the PheWAS, we used data from the electronic MEdical Records and GEnomics (eMERGE) Network across 9 sites with a total of 41,057 unrelated patients. We divided all these samples into two datasets by equal proportion of eMERGE site, sex, race, and genotyping platform. We calculated single effect associations between these 25 stop-gain variants and ICD-9 defined case-control diagnoses. We also performed stratified analyses for samples of European and African ancestry. Associations were adjusted for sex, site, genotyping platform and the first three principal components to account for global ancestry. We identified previously known associations, such as variants in LPL associated with hyperglyceridemia indicating that our approach was robust. We also found a total of three significant associations with p < 0.01 in both datasets, with the most significant replicating result being LPL SNP rs328 and ICD-9 code 272.1 "Disorder of Lipoid metabolism" (pdiscovery = 2.59x10-6, preplicating = 2.7x10-4). The other two significant replicated associations identified by this study are: variant rs1137617 in KCNH2 gene associated with ICD-9 code category 244 "Acquired Hypothyroidism" (pdiscovery = 5.31x103, preplicating = 1.15x10-3) and variant rs12060879 in DPT gene associated with ICD-9 code category 996 "Complications peculiar to certain specified procedures" (pdiscovery = 8.65x103, preplicating = 4.16x10-3).

CONCLUSION

In conclusion, this PheWAS revealed novel associations of stop-gained variants with interesting phenotypes (ICD-9 codes) along with pleiotropic effects.

Identification of Siglec-1 null individuals infected with HIV-1

Siglec-1/CD169 is a myeloid-cell surface receptor critical for HIV-1 capture and infection of bystander target cells. To dissect the role of SIGLEC1 in natura, we scan a large population genetic database and identify a loss-of-function variant (Glu88Ter) that is found in ∼1% of healthy people. Exome analysis and direct genotyping of 4,233 HIV-1-infected individuals reveals two Glu88Ter homozygous and 97 heterozygous subjects, allowing the analysis of ex vivo and in vivo consequences of SIGLEC1 loss-of-function. Cells from these individuals are functionally null or haploinsufficient for Siglec-1 activity in HIV-1 capture and trans-infection ex vivo. However, Siglec-1 protein truncation does not have a measurable impact on HIV-1 acquisition or AIDS outcomes in vivo. This result contrasts with the known in vitro functional role of Siglec-1 in HIV-1 trans-infection. Thus, it provides evidence that the classical HIV-1 infectious routes may compensate for the lack of Siglec-1 in fuelling HIV-1 dissemination within infected individuals.

Whole-exome sequencing to analyze population structure, parental inbreeding, and familial linkage

Principal component analysis (PCA), homozygosity rate estimations, and linkage studies in humans are classically conducted through genome-wide single-nucleotide variant arrays (GWSA). We compared whole-exome sequencing (WES) and GWSA for this purpose. We analyzed 110 subjects originating from different regions of the world, including North Africa and the Middle East, which are poorly covered by public databases and have high consanguinity rates. We tested and applied a number of quality control (QC) filters. Compared with GWSA, we found that WES provided an accurate prediction of population substructure using variants with a minor allele frequency > 2% (correlation = 0.89 with the PCA coordinates obtained by GWSA). WES also yielded highly reliable estimates of homozygosity rates using runs of homozygosity with a 1,000-kb window (correlation = 0.94 with the estimates provided by GWSA). Finally, homozygosity mapping analyses in 15 families including a single offspring with high homozygosity rates showed that WES provided 51% less genome-wide linkage information than GWSA overall but 97% more information for the coding regions. At the genome-wide scale, 76.3% of linked regions were found by both GWSA and WES, 17.7% were found by GWSA only, and 6.0% were found by WES only. For coding regions, the corresponding percentages were 83.5%, 7.4%, and 9.1%, respectively. With appropriate QC filters, WES can be used for PCA and adjustment for population substructure, estimating homozygosity rates in individuals, and powerful linkage analyses, particularly in coding regions.

Screening of whole genome sequences identified high-impact variants for stallion fertility

Background

Stallion fertility is an economically important trait due to the increase of artificial insemination in horses. The availability of whole genome sequence data facilitates identification of rare high-impact variants contributing to stallion fertility. The aim of our study was to genotype rare high-impact variants retrieved from next-generation sequencing (NGS)-data of 11 horses in order to unravel harmful genetic variants in large samples of stallions.

Methods

Gene ontology (GO) terms and search results from public databases were used to obtain a comprehensive list of human und mice genes predicted to participate in the regulation of male reproduction. The corresponding equine orthologous genes were searched in whole genome sequence data of seven stallions and four mares and filtered for high-impact genetic variants using SnpEFF, SIFT and Polyphen 2 software. All genetic variants with the missing homozygous mutant genotype were genotyped on 337 fertile stallions of 19 breeds using KASP genotyping assays or PCR-RFLP. Mixed linear model analysis was employed for an association analysis with de-regressed estimated breeding values of the paternal component of the pregnancy rate per estrus (EBV-PAT).

Results

We screened next generation sequenced data of whole genomes from 11 horses for equine genetic variants in 1194 human and mice genes involved in male fertility and linked through common gene ontology (GO) with male reproductive processes. Variants were filtered for high-impact on protein structure and validated through SIFT and Polyphen 2. Only those genetic variants were followed up when the homozygote mutant genotype was missing in the detection sample comprising 11 horses. After this filtering process, 17 single nucleotide polymorphism (SNPs) were left. These SNPs were genotyped in 337 fertile stallions of 19 breeds using KASP genotyping assays or PCR-RFLP. An association analysis in 216 Hanoverian stallions revealed a significant association of the splice-site disruption variant g.37455302G>A in NOTCH1 with the de-regressed estimated breeding values of the paternal component of the pregnancy rate per estrus (EBV-PAT). For 9 high-impact variants within the genes CFTR, OVGP1, FBXO43, TSSK6, PKD1, FOXP1, TCP11, SPATA31E1 and NOTCH1 (g.37453246G>C) absence of the homozygous mutant genotype in the validation sample of all 337 fertile stallions was obvious. Therefore, these variants were considered as potentially deleterious factors for stallion fertility.

Conclusions

In conclusion, this study revealed 17 genetic variants with a predicted high damaging effect on protein structure and missing homozygous mutant genotype. The g.37455302G>A NOTCH1 variant was identified as a significant stallion fertility locus in Hanoverian stallions and further 9 candidate fertility loci with missing homozygous mutant genotypes were validated in a panel including 19 horse breeds. To our knowledge this is the first study in horses using next generation sequencing data to uncover strong candidate factors for stallion fertility.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-016-2608-3) contains supplementary material, which is available to authorized users.

High-Throughput Sequencing Reveals Single Nucleotide Variants in Longer-Kernel Bread Wheat

The transcriptomes of bread wheat Yunong 201 and its ethyl methanesulfonate derivative Yunong 3114 were obtained by next-sequencing technology. Single nucleotide variants (SNVs) in the wheat strains were explored and compared. A total of 5907 and 6287 non-synonymous SNVs were acquired for Yunong 201 and 3114, respectively. A total of 4021 genes with SNVs were obtained. The genes that underwent non-synonymous SNVs were significantly involved in ATP binding, protein phosphorylation, and cellular protein metabolic process. The heat map analysis also indicated that most of these mutant genes were significantly differentially expressed at different developmental stages. The SNVs in these genes possibly contribute to the longer kernel length of Yunong 3114. Our data provide useful information on wheat transcriptome for future studies on wheat functional genomics. This study could also help in illustrating the gene functions of the non-synonymous SNVs of Yunong 201 and 3114.

The Characteristics of Heterozygous Protein Truncating Variants in the Human Genome

Sequencing projects have identified large numbers of rare stop-gain and frameshift variants in the human genome. As most of these are observed in the heterozygous state, they test a gene’s tolerance to haploinsufficiency and dominant loss of function. We analyzed the distribution of truncating variants across 16,260 autosomal protein coding genes in 11,546 individuals. We observed 39,893 truncating variants affecting 12,062 genes, which significantly differed from an expectation of 12,916 genes under a model of neutral de novo mutation (p<10⁻⁴). Extrapolating this to increasing numbers of sequenced individuals, we estimate that 10.8% of human genes do not tolerate heterozygous truncating variants. An additional 10 to 15% of truncated genes may be rescued by incomplete penetrance or compensatory mutations, or because the truncating variants are of limited functional impact. The study of protein truncating variants delineates the essential genome and, more generally, identifies rare heterozygous variants as an unexplored source of diversity of phenotypic traits and diseases.

Genome sequencing provides evidence for large numbers of putative protein truncating variants in humans. Most truncating variants are only observed in few individuals but are collectively prevalent and widely distributed across the coding genome. Most of the truncating variants are so rare that they are only observed in heterozygosis. The current study identifies 10% of genes where heterozygous truncations are not observed and describes their biological characteristics. In addition, for genes where rare truncations are observed, we argue that these are an unexplored source of diversity of phenotypic traits and diseases.

Secondary findings and carrier test frequencies in a large multiethnic sample

BACKGROUND

Besides its growing importance in clinical diagnostics and understanding the genetic basis of Mendelian and complex diseases, whole exome sequencing (WES) is a rich source of additional information of potential clinical utility for physicians, patients and their families. We analyzed the frequency and nature of single nucleotide variants (SNVs) considered secondary findings and recessive disease allele carrier status in the exomes of 8554 individuals from a large, randomly sampled cohort study and 2514 patients from a study of presumed Mendelian disease having undergone WES.

METHODS

We used the same sequencing platform and data processing pipeline to analyze all samples and characterized the distributions of reported pathogenic (ClinVar, Human Gene Mutation Database (HGMD)) and predicted deleterious variants in the pre-specified American College of Medical Genetics and Genomics (ACMG) secondary findings and recessive disease genes in different ethnic groups.

RESULTS

In the 56 ACMG secondary findings genes, the average number of predicted deleterious variants per individual was 0.74, and the mean number of ClinVar reported pathogenic variants was 0.06. We observed an average of 10 deleterious and 0.78 ClinVar reported pathogenic variants per individual in 1423 autosomal recessive disease genes. By repeatedly sampling pairs of exomes, 0.5 % of the randomly generated couples were at 25 % risk of having an affected offspring for an autosomal recessive disorder based on the ClinVar variants.

CONCLUSIONS

By investigating reported pathogenic and novel, predicted deleterious variants we estimated the lower and upper limits of the population fraction for which exome sequencing may reveal additional medically relevant information. We suggest that the observed wide range for the lower and upper limits of these frequency numbers will be gradually reduced due to improvement in classification databases and prediction algorithms.

Alternatively Spliced Homologous Exons Have Ancient Origins and Are Highly Expressed at the Protein Level

Alternative splicing of messenger RNA can generate a wide variety of mature RNA transcripts, and these transcripts may produce protein isoforms with diverse cellular functions. While there is much supporting evidence for the expression of alternative transcripts, the same is not true for the alternatively spliced protein products. Large-scale mass spectroscopy experiments have identified evidence of alternative splicing at the protein level, but with conflicting results. Here we carried out a rigorous analysis of the peptide evidence from eight large-scale proteomics experiments to assess the scale of alternative splicing that is detectable by high-resolution mass spectroscopy. We find fewer splice events than would be expected: we identified peptides for almost 64% of human protein coding genes, but detected just 282 splice events. This data suggests that most genes have a single dominant isoform at the protein level. Many of the alternative isoforms that we could identify were only subtly different from the main splice isoform. Very few of the splice events identified at the protein level disrupted functional domains, in stark contrast to the two thirds of splice events annotated in the human genome that would lead to the loss or damage of functional domains. The most striking result was that more than 20% of the splice isoforms we identified were generated by substituting one homologous exon for another. This is significantly more than would be expected from the frequency of these events in the genome. These homologous exon substitution events were remarkably conserved—all the homologous exons we identified evolved over 460 million years ago—and eight of the fourteen tissue-specific splice isoforms we identified were generated from homologous exons. The combination of proteomics evidence, ancient origin and tissue-specific splicing indicates that isoforms generated from homologous exons may have important cellular roles.

Alternative splicing is thought to be one means for generating the protein diversity necessary for the whole range of cellular functions. While the presence of alternatively spliced transcripts in the cell has been amply demonstrated, the same cannot be said for alternatively spliced proteins. The quest for alternative protein isoforms has focused primarily on the analysis of peptides from large-scale mass spectroscopy experiments, but evidence for alternative isoforms has been patchy and contradictory. A careful analysis of the peptide evidence is needed to fully understand the scale of alternative splicing detectable at the protein level. Here we analysed peptides from eight large-scale data sets, identifying just 282 splice events among 12,716 genes. This suggests that most genes have a single dominant isoform. Many of the alternative isoforms that we identified were only subtly different from the main splice variant, and one in five was generated by substitution of homologous exons by swapping one related exon for another. Remarkably, the alternative isoforms generated from homologous exons were highly conserved, first appearing 460 million years ago, and several appear to have tissue-specific roles in the brain and heart. Our results suggest that these particular isoforms are likely to have important cellular roles.