Whole-genome sequencing identifies new candidate genes for nonobstructive azoospermia.

BACKGROUND: Genetic causes that lead to spermatogenetic failure in patients with nonobstructive azoospermia (NOA) have not been yet completely established. OBJECTIVE: To identify low-frequency NOA-associated single nucleotide variants (SNVs) using whole-genome sequencing (WGS). MATERIALS AND METHODS: Men with various types of NOA (n = 39), including samples that had been previously tested with whole-exome sequencing (WES; n = 6) and did not result in diagnostic conclusions. Variants were annotated using the Ensembl Variant Effect Predictor, utilizing frequencies from GnomAD and other databases to provide clinically relevant information (ClinVar), conservation scores (phyloP), and effect predictions (i.e., MutationTaster). Structural protein modeling was also performed. RESULTS: Using WGS, we revealed potential NOA-associated SNVs, such as: TKTL1, IGSF1, ZFPM2, VCX3A (novel disease causing variants), ESX1, TEX13A, TEX14, DNAH1, FANCM, QRICH2, FSIP2, USP9Y, PMFBP1, MEI1, PIWIL1, WDR66, ZFX, KCND1, KIAA1210, DHRSX, ZMYM3, FAM47C, FANCB, FAM50B (genes previously known to be associated with infertility) and ALG13, BEND2, BRWD3, DDX53, TAF4, FAM47B, FAM9B, FAM9C, MAGEB6, MAP3K15, RBMXL3, SSX3 and FMR1NB genes, which may be involved in spermatogenesis. DISCUSSION AND CONCLUSION: In this study, we identified novel potential candidate NOA-associated genes in 29 individuals out of 39 azoospermic males. Note that in 5 out of 6 patients subjected previously to WES analysis, which did not disclose potentially causative variants, the WGS analysis was successful with NOA-associated gene findings.

DBFE: distribution-based feature extraction from structural variants in whole-genome data.

MOTIVATION: Whole-genome sequencing has revolutionized biosciences by providing tools for constructing complete DNA sequences of individuals. With entire genomes at hand, scientists can pinpoint DNA fragments responsible for oncogenesis and predict patient responses to cancer treatments. Machine learning plays a paramount role in this process. However, the sheer volume of whole-genome data makes it difficult to encode the characteristics of genomic variants as features for learning algorithms. RESULTS: In this article, we propose three feature extraction methods that facilitate classifier learning from sets of genomic variants. The core contributions of this work include: (i) strategies for determining features using variant length binning, clustering and density estimation; (ii) a programing library for automating distribution-based feature extraction in machine learning pipelines. The proposed methods have been validated on five real-world datasets using four different classification algorithms and a clustering approach. Experiments on genomes of 219 ovarian, 61 lung and 929 breast cancer patients show that the proposed approaches automatically identify genomic biomarkers associated with cancer subtypes and clinical response to oncological treatment. Finally, we show that the extracted features can be used alongside unsupervised learning methods to analyze genomic samples. AVAILABILITY AND IMPLEMENTATION: The source code of the presented algorithms and reproducible experimental scripts are available on Github at https://github.com/MNMdiagnostics/dbfe. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

The Thousand Polish Genomes-A Database of Polish Variant Allele Frequencies.

Although Slavic populations account for over 4.5% of world inhabitants, no centralised, open-source reference database of genetic variation of any Slavic population exists to date. Such data are crucial for clinical genetics, biomedical research, as well as archeological and historical studies. The Polish population, which is homogenous and sedentary in its nature but influenced by many migrations of the past, is unique and could serve as a genetic reference for the Slavic nations. In this study, we analysed whole genomes of 1222 Poles to identify and genotype a wide spectrum of genomic variation, such as small and structural variants, runs of homozygosity, mitochondrial haplogroups, and de novo variants. Common variant analyses showed that the Polish cohort is highly homogenous and shares ancestry with other European populations. In rare variant analyses, we identified 32 autosomal-recessive genes with significantly different frequencies of pathogenic alleles in the Polish population as compared to the non-Finish Europeans, including C2, TGM5, NUP93, C19orf12, and PROP1. The allele frequencies for small and structural variants, calculated for 1076 unrelated individuals, are released publicly as The Thousand Polish Genomes database, and will contribute to the worldwide genomic resources available to researchers and clinicians.

The First Report of Biallelic Missense Mutations in the SFRP4 Gene Causing Pyle Disease in Two Siblings.

BACKGROUND: Pyle disease is a rare autosomal recessive bone dysplasia characterized by the broadening of metaphyses with generalized cortical thinning. Homozygous truncating mutations in secreted frizzled-related protein 4 (SFRP4) were, to date, the only known variants causative for this type of skeletal disorder. SFRP4 controls cortical and trabecular bone remodeling by differential regulation of the canonical and non-canonical WNT signaling in both bone compartments. Loss-of-function mutations in the SFRP4 gene lead to the protein deficiency causing skeletal phenotype typical for Pyle disease. RESULTS: Herein, we report on the first SFRP4 missense mutations that occurred in compound heterozygosity in two siblings affected by Pyle disease, and which we have identified using a whole-genome sequencing approach followed by a comprehensive in silico pathogenicity assessment. The variants we have found were extremely rare and evaluated to be disease-causing by several online available tools and software. CONCLUSION: With this paper, we have shown that Pyle disease may be related not only to SFRP4 truncating mutations but also to other loss-of-function alterations that possibly impair the protein capacity to bind WNT ligands. As we have expanded here, the range of deleterious variants underlying Pyle disease, we contribute to the knowledge on the pathogenesis of this rare skeletal disorder.