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1.
Nat Commun ; 13(1): 154, 2022 01 10.
Article in English | MEDLINE | ID: mdl-35013161

ABSTRACT

De novo mutations are known to play a prominent role in sporadic disorders with reduced fitness. We hypothesize that de novo mutations play an important role in severe male infertility and explain a portion of the genetic causes of this understudied disorder. To test this hypothesis, we utilize trio-based exome sequencing in a cohort of 185 infertile males and their unaffected parents. Following a systematic analysis, 29 of 145 rare (MAF < 0.1%) protein-altering de novo mutations are classified as possibly causative of the male infertility phenotype. We observed a significant enrichment of loss-of-function de novo mutations in loss-of-function-intolerant genes (p-value = 1.00 × 10-5) in infertile men compared to controls. Additionally, we detected a significant increase in predicted pathogenic de novo missense mutations affecting missense-intolerant genes (p-value = 5.01 × 10-4) in contrast to predicted benign de novo mutations. One gene we identify, RBM5, is an essential regulator of male germ cell pre-mRNA splicing and has been previously implicated in male infertility in mice. In a follow-up study, 6 rare pathogenic missense mutations affecting this gene are observed in a cohort of 2,506 infertile patients, whilst we find no such mutations in a cohort of 5,784 fertile men (p-value = 0.03). Our results provide evidence for the role of de novo mutations in severe male infertility and point to new candidate genes affecting fertility.


Subject(s)
Azoospermia/genetics , Cell Cycle Proteins/genetics , DNA-Binding Proteins/genetics , Genetic Predisposition to Disease , Loss of Function Mutation , Mutation, Missense , Oligospermia/genetics , RNA-Binding Proteins/genetics , Tumor Suppressor Proteins/genetics , Adult , Azoospermia/pathology , Case-Control Studies , Cell Cycle Proteins/deficiency , DNA-Binding Proteins/deficiency , Exome , Gene Expression , Gene Expression Profiling , Humans , Male , Oligospermia/pathology , Tumor Suppressor Proteins/deficiency , Exome Sequencing
3.
Andrology ; 3(6): 1140-9, 2015 Nov.
Article in English | MEDLINE | ID: mdl-26473511

ABSTRACT

Despite its great potential, high-throughput functional genomic data are rarely integrated and applied to characterizing the genomic basis of fertility. We obtained and reprocessed over 30 functional genomics datasets from human and mouse germ cells to perform genome-wide prediction of genes underlying various reproductive phenotypes in both species. Genes involved in male fertility are easier to predict than their female analogs. Of the multiple genomic data types examined, protein-protein interactions are by far the most informative for gene prediction, followed by gene expression, and then epigenetic marks. As an application of our predictions, we show that copy number variants (CNVs) disrupting predicted fertility genes are more strongly associated with gonadal dysfunction in male and female case-control cohorts when compared to all gene-disrupting CNVs (OR = 1.64, p < 1.64 × 10(-8) vs. OR = 1.25, p < 4 × 10(-6)). Using gender-specific fertility gene annotations further increased the observed associations (OR = 2.31, p < 2.2 × 10(-16)). We provide our gene predictions as a resource with this article.


Subject(s)
Fertility/genetics , Genetic Markers , Genomics/methods , High-Throughput Nucleotide Sequencing , Infertility, Female/genetics , Infertility, Male/genetics , Animals , Case-Control Studies , DNA Copy Number Variations , Databases, Genetic , Discriminant Analysis , Epigenesis, Genetic , Female , Gene Expression Regulation , Gene Regulatory Networks , Genetic Predisposition to Disease , Genome-Wide Association Study , Humans , Infertility, Female/physiopathology , Infertility, Male/physiopathology , Linear Models , Male , Mice , Models, Genetic , Odds Ratio , Phenotype , Predictive Value of Tests , Protein Interaction Maps , Risk Factors
4.
Andrology ; 3(5): 825-33, 2015 Sep.
Article in English | MEDLINE | ID: mdl-26139570

ABSTRACT

The double sex and mab-3-related transcription factor 1 (DMRT1) gene has long been linked to sex-determining pathways across vertebrates and is known to play an essential role in gonadal development and maintenance of spermatogenesis in mice. In humans, the genomic region harboring the DMRT gene cluster has been implicated in disorders of sex development and recently DMRT1 deletions were shown to be associated with non-obstructive azoospermia (NOA). In this work, we have employed different methods to screen a cohort of Portuguese NOA patients for DMRT1 exonic insertions and deletions [by multiplex ligation probe assay (MLPA); n = 68] and point mutations (by Sanger sequencing; n = 155). We have found three novel patient-specific non-coding variants in heterozygosity that were absent from 357 geographically matched controls. One of these is a complex variant with a putative regulatory role (c.-223_-219CGAAA>T), located in the promoter region within a conserved sequence involved in Dmrt1 repression. Moreover, while DMRT1 domains are highly conserved across vertebrates and show reduced levels of diversity in human populations, two rare synonymous substitutions (rs376518776 and rs34946058) and two rare non-coding variants that potentially affect DMRT1 expression and splicing (rs144122237 and rs200423545) were overrepresented in patients when compared with 376 Portuguese controls (301 fertile and 75 normozoospermic). Overall our previous and present results suggest a role of changes in DMRT1 dosage in NOA potentially also through a process of gene misregulation, even though DMRT1 deleterious variants seem to be rare.


Subject(s)
Azoospermia/genetics , Gene Dosage/genetics , Promoter Regions, Genetic/genetics , Spermatogenesis/genetics , Transcription Factors/genetics , Base Sequence , Gene Deletion , Genotype , Humans , Male , Molecular Sequence Data , Portugal , Sequence Alignment
5.
Nature ; 508(7497): 469-76, 2014 Apr 24.
Article in English | MEDLINE | ID: mdl-24759409

ABSTRACT

The discovery of rare genetic variants is accelerating, and clear guidelines for distinguishing disease-causing sequence variants from the many potentially functional variants present in any human genome are urgently needed. Without rigorous standards we risk an acceleration of false-positive reports of causality, which would impede the translation of genomic research findings into the clinical diagnostic setting and hinder biological understanding of disease. Here we discuss the key challenges of assessing sequence variants in human disease, integrating both gene-level and variant-level support for causality. We propose guidelines for summarizing confidence in variant pathogenicity and highlight several areas that require further resource development.


Subject(s)
Disease , Genetic Predisposition to Disease/genetics , Genetic Variation/genetics , Guidelines as Topic , False Positive Reactions , Genes/genetics , Humans , Information Dissemination , Publishing , Reproducibility of Results , Research Design , Translational Research, Biomedical/standards
6.
Ann Hum Genet ; 72(Pt 4): 535-46, 2008 Jul.
Article in English | MEDLINE | ID: mdl-18513279

ABSTRACT

When performing association studies in populations that have not been the focus of large-scale investigations of haplotype variation, it is often helpful to rely on genomic databases in other populations for study design and analysis - such as in the selection of tag SNPs and in the imputation of missing genotypes. One way of improving the use of these databases is to rely on a mixture of database samples that is similar to the population of interest, rather than using the single most similar database sample. We demonstrate the effectiveness of the mixture approach in the application of African, European, and East Asian HapMap samples for tag SNP selection in populations from India, a genetically intermediate region underrepresented in genomic studies of haplotype variation.


Subject(s)
Databases, Genetic , Linkage Disequilibrium , Population Groups/genetics , Databases, Genetic/standards , Genetics, Population , Genome, Human , Haplotypes , Humans , India , Polymorphism, Single Nucleotide , Research Design
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