Annotating and prioritizing genomic variants using the Ensembl Variant Effect Predictor-A tutorial

Computational study of the potential impact of WHRN protein missense SNPs on WHRN-MYO15A protein complex interaction and their association with Usher syndrome

Usher syndrome is a rare genetic condition characterized by both hearing and vision impairment that occurs through mutations of multiple genes, including WHRN and MYO15A. In this computational work, we intend to explore how missense SNPs within the WHRN protein affect its interaction with the MYO15A protein, a crucial component of the Usher interactome. Therefore, the identification of missense SNPs that has a potential effect on the function of the WHRN protein was realized using various computational prediction tools, including VEP, SIFT, PolyPhen-2, CADD, REVEL, and Mutation Assessor. Further evaluation of the stability of mutated proteins was conducted through SDM2, MCSM, DeepDDG and CUP-SAT. We used ConSurf web server to identify conserved regions in the WHRN protein. Yasara and Haddock analysis tools were used to minimize the energy of protein 3D structures and to dock protein-protein complexes, respectively. and then the binding energy of the complexes was calculated through PRODIGY. Mutation pathogenicity prediction tools showed that in total, 18 missense SNPs, predicted as deleterious. However, a comprehensive analysis revealed that only SIX single nucleotide polymorphisms were predicted to be the most deleterious with high conservation and less stability. Furthermore, we conducted molecular dynamics analysis to fully comprehend the impact of these variations on the dynamic behavior of the WHRN-MYO15A protein complex, which revealed significant insights into the destabilizing effects of the deleterious SNPs impacting the protein's binding affinity and stability that occurs during the binding process of the WHRN-MYO15A protein complex.

Genomics and integrative clinical data machine learning scoring model to ascertain likely Lynch syndrome patients

BACKGROUND

Lynch syndrome (LS) screening methods include multistep molecular somatic tumor testing to distinguish likely-LS patients from sporadic cases, which can be costly and complex. Also, direct germline testing for LS for every diagnosed solid cancer patient is a challenge in resource limited settings. We developed a unique machine learning scoring model to ascertain likely-LS cases from a cohort of colorectal cancer (CRC) patients.

METHODS

We used CRC patients from the cBioPortal database (TCGA studies) with complete clinicopathologic and somatic genomics data. We determined the rate of pathogenic/likely pathogenic variants in five (5) LS genes (MLH1, MSH2, MSH6, PMS2, EPCAM), and the BRAF mutations using a pre-designed bioinformatic annotation pipeline. Annovar, Intervar, Variant Effect Predictor (VEP), and OncoKB software tools were used to functionally annotate and interpret somatic variants detected. The OncoKB precision oncology knowledge base was used to provide information on the effects of the identified variants. We scored the clinicopathologic and somatic genomics data automatically using a machine learning model to discriminate between likely-LS and sporadic CRC cases. The training and testing datasets comprised of 80% and 20% of the total CRC patients, respectively. Group regularisation methods in combination with 10-fold cross-validation were performed for feature selection on the training data.

RESULTS

Out of 4800 CRC patients frorm the TCGA datasets with clinicopathological and somatic genomics data, we ascertained 524 patients with complete data. The scoring model using both clinicopathological and genetic characteristics for likely-LS showed a sensitivity and specificity of 100%, and both had the maximum accuracy, area under the curve (AUC) and AUC for precision-recall (AUCPR) of 1. In a similar analysis, the training and testing models that only relied on clinical or pathological characteristics had a sensitivity of 0.88 and 0.50, specificity of 0.55 and 0.51, accuracy of 0.58 and 0.51, AUC of 0.74 and 0.61, and AUCPR of 0.21 and 0.19, respectively.

CONCLUSIONS

Simultaneous scoring of LS clinicopathological and somatic genomics data can improve prediction and ascertainment for likely-LS from all CRC cases. This approach can increase accuracy while reducing the reliance on expensive direct germline testing for all CRC patients, making LS screening more accessible and cost-effective, especially in resource-limited settings.

A Hitchhiker's Guide to long-read genomic analysis

Over the past decade, long-read sequencing has evolved into a pivotal technology for uncovering the hidden and complex regions of the genome. Significant cost efficiency, scalability, and accuracy advancements have driven this evolution. Concurrently, novel analytical methods have emerged to harness the full potential of long reads. These advancements have enabled milestones such as the first fully completed human genome, enhanced identification and understanding of complex genomic variants, and deeper insights into the interplay between epigenetics and genomic variation. This mini-review provides a comprehensive overview of the latest developments in long-read DNA sequencing analysis, encompassing reference-based and de novo assembly approaches. We explore the entire workflow, from initial data processing to variant calling and annotation, focusing on how these methods improve our ability to interpret a wide array of genomic variants. Additionally, we discuss the current challenges, limitations, and future directions in the field, offering a detailed examination of the state-of-the-art bioinformatics methods for long-read sequencing.

FDPSM: Feature-Driven Prediction Modeling of Pathogenic Synonymous Mutations

Synonymous mutations, once considered to be biologically neutral, are now recognized to affect protein expression and function by altering the RNA splicing, stability, or translation efficiency. These effects can contribute to disease, making the prediction of the pathogenicity a crucial task. Computational methods have been developed to analyze the sequence features and biological functions of synonymous mutations, but existing methods face limitations, including scarcity of labeled data, reliance on other prediction tools, and insufficient representation of feature interrelationships. Here, we present FDPSM, a novel prediction method specifically designed to predict pathogenic synonymous mutations. FDPSM was trained on a robust data set of 4251 positive and negative training samples to enhance predictive accuracy. The method leveraged a comprehensive set of features, including genomic context, conservation, splicing effects, functional effects, and epigenomics, without relying on prediction scores from other mutation pathogenicity tools. Recognizing that original features alone may not fully capture the distinctions between pathogenic and benign synonymous mutations, we enhanced the feature set by extracting effective information from the interactions and distribution of these features. The experimental results showed that FDPSM significantly outperformed existing methods in predicting the pathogenicity of synonymous mutations, offering a more accurate and reliable tool for this important task. FDPSM is available at https://github.com/xialab-ahu/FDPSM.

Novel Parkinson's Disease Genetic Risk Factors Within and Across European Populations

Introduction

We conducted a meta-analysis of Parkinson's disease genome-wide association study summary statistics, stratified by source (clinically-recruited case-control cohorts versus population biobanks) and by general European versus European isolate ancestries. This study included 63,555 cases, 17,700 proxy cases with a family history of Parkinson's disease, and 1,746,386 controls, making it the largest investigation of Parkinson's disease genetic risk to date.

Methods

Meta-analyses were performed using standard fixed and random effect models for the European sub-populations, the case-control studies, and the population biobanks separately. Finally, all of the European ancestries for all study types as well as proxy cases were combined in our final cross-European meta-analysis. We estimated heritable risk across ancestry groups, investigated tissue and cell-type enrichment, and prioritized risk genes using public data to facilitate functional follow-up efforts.

Results

The final combined cross-European meta-analysis identified 134 risk loci (59 novel), with a total of 157 independent signals, significantly expanding our understanding of Parkinson's disease risk. Multi-omic data integration revealed that expression of the nominated risk genes are highly enriched in brain tissues, particularly in neuronal and astrocyte cell types. Additionally, we prioritized 33 high-confidence genes across these 134 loci for future follow-up studies.

Conclusions

By integrating diverse European populations and leveraging harmonized data from the Global Parkinson's Genetics Program (GP2), we reveal new insight into the genetic architecture of Parkinson's disease. We identified a total of 134 risk loci, expanding the number of known loci associated with PD by approximately 24%. We also provided an initial layer of biological context to these results through follow-up analyses in an effort to facilitate follow-up studies and precision medicine efforts with the goal of advancing Parkinson's disease research.

RMRP variants inhibit the cell cycle checkpoints pathway in cartilage‑hair hypoplasia

Cartilage‑hair hypoplasia (CHH) is an autosomal recessive form of metaphyseal chondrodysplasia caused by RNA component of mitochondrial RNA processing endoribonuclease (RMRP) gene variants; however, its molecular etiology remains unclear. Whole‑exome sequencing was performed to detect possible pathogenic variants in a patient with a typical short stature and sparse hair. A co‑segregation analysis was also conducted and variants in the family members of the patient were confirmed by Sanger sequencing. A novel compound heterozygous variant in RMRP (NR_003051.4: n.‑21_‑2dup and n.197C>T) was identified in the affected patient. Data from 2 years and 4 months of follow‑up showed a positive effect of growth hormone (GH) therapy on height. Subsequently, two gene expression profiles associated with CHH were obtained from the EMBL‑EBI ENA and ArrayExpress databases. Differentially expressed genes between patients with CHH and healthy controls were selected using R software and were subjected to core analysis using ingenuity pathway analysis (IPA) software. IPA core analysis showed that the 'cell cycle checkpoints' was the most prominent canonical pathway, and the top enriched diseases and functions included various types of cancer, immunological diseases, development disorders and respiratory diseases. The integrative analysis displayed that RMRP can regulate the aberrant expression of downstream targets mainly via the transcription factor TP53, which results in the inhibition of 'cell cycle checkpoints'; eventually, functions associated with the CHH phenotype, such as 'growth failure or short stature' are activated. In conclusion, novel disease‑causing genetic variants of RMRP expand the genetic etiology of CHH, which must be clinically differentiated from achondroplasia. The findings of the present study provide new insights into the mechanisms underlying CHH.

Comparative analysis of the Mexico City Prospective Study and the UK Biobank identifies ancestry-specific effects on clonal hematopoiesis

The impact of genetic ancestry on the development of clonal hematopoiesis (CH) remains largely unexplored. Here, we compared CH in 136,401 participants from the Mexico City Prospective Study (MCPS) to 416,118 individuals from the UK Biobank (UKB) and observed CH to be significantly less common in MCPS compared to UKB (adjusted odds ratio = 0.59, 95% confidence interval (CI) = [0.57, 0.61], P = 7.31 × 10-185). Among MCPS participants, CH frequency was positively correlated with the percentage of European ancestry (adjusted beta = 0.84, 95% CI = [0.66, 1.03], P = 7.35 × 10-19). Genome-wide and exome-wide association analyses in MCPS identified ancestry-specific variants in the TCL1B locus with opposing effects on DNMT3A-CH versus non-DNMT3A-CH. Meta-analysis of MCPS and UKB identified five novel loci associated with CH, including polymorphisms at PARP11/CCND2, MEIS1 and MYCN. Our CH study, the largest in a non-European population to date, demonstrates the power of cross-ancestry comparisons to derive novel insights into CH pathogenesis.

Assessment of the functionality and usability of open-source rare variant analysis pipelines

Sequencing of increasingly larger cohorts has revealed many rare variants, presenting an opportunity to further unravel the genetic basis of complex traits. Compared with common variants, rare variants are more complex to analyze. Specialized computational tools for these analyses should be both flexible and user-friendly. However, an overview of the available rare variant analysis pipelines and their functionalities is currently lacking. Here, we provide a systematic review of the currently available rare variant analysis pipelines. We searched MEDLINE and Google Scholar until 27 November 2023, and included open-source rare variant pipelines that accepted genotype data from cohort and case-control studies and group variants into testing units. Eligible pipelines were assessed based on functionality and usability criteria. We identified 17 rare variant pipelines that collectively support various trait types, association tests, testing units, and variant weighting schemes. Currently, no single pipeline can handle all data types in a scalable and flexible manner. We recommend different tools to meet diverse analysis needs. STAARpipeline is suitable for newcomers and common applications owing to its built-in definitions for the testing units. REGENIE is highly scalable, actively maintained, regularly updated, and well documented. Ravages is suitable for analyzing multinomial variables, and OrdinalGWAS is tailored for analyzing ordinal variables. Opportunities remain for developing a user-friendly pipeline that provides high degrees of flexibility and scalability. Such a pipeline would enable researchers to exploit the potential of rare variant analyses to uncover the genetic basis of complex traits.

A Murine Database of Structural Variants Enables the Genetic Architecture of a Spontaneous Murine Lymphoma to be Characterized

A more complete map of the pattern of genetic variation among inbred mouse strains is essential for characterizing the genetic architecture of the many available mouse genetic models of important biomedical traits. Although structural variants (SVs) are a major component of genetic variation, they have not been adequately characterized among inbred strains due to methodological limitations. To address this, we generated high-quality long-read sequencing data for 40 inbred strains; and designed a pipeline to optimally identify and validate different types of SVs. This generated a database for 40 inbred strains with 573,191SVs, which included 10,815 duplications and 2,115 inversions, that also has 70 million SNPs and 7.5 million insertions/deletions. Analysis of this SV database led to the discovery of a novel bi-genic model for susceptibility to a B cell lymphoma that spontaneously develops in SJL mice, which was initially described 55 years ago. The first genetic factor is a previously identified endogenous retrovirus encoded protein that stimulates CD4 T cells to produce the cytokines required for lymphoma growth. The second genetic factor is a newly found deletion SV, which ablates a protein whose promotes B lymphoma development in SJL mice. Characterizing the genetic architecture of SJL lymphoma susceptibility could provide new insight into the pathogenesis of a human lymphoma that has similarities with this murine lymphoma.

Introduction to androgenetics: terminology, approaches, and impactful studies across 60 years

Across six decades, androgenetics has consistently concentrated on discovering genetic causes and enhancing the molecular diagnostics of male infertility, disorders of sex development, and their broader implications on health, such as cancer and other comorbidities. Despite vast clinical knowledge, the training of andrologists often lacks fundamental basics in medical genetics. This work, as part of the Special Issue of Andrology "Genetics in Andrology", provides the core terminology in medical genetics and technological advancements in genomics, required to understand the ever-progressing research in the field. It also gives an overview of study designs and approaches that have frequently led to discoveries in androgenetics. The rapid progress in the methodological toolbox in human genetics is illustrated by numerous examples of impactful androgenetic studies over 60 years, and their clinical implications.

Nanopore adaptive sampling accurately detects nucleotide variants and improves the characterization of large-scale rearrangement for the diagnosis of cancer predisposition

BACKGROUND

Molecular diagnosis has become highly significant for patient management in oncology.

METHODS

Here, 30 well-characterized clinical germline samples were studied with adaptive sampling to enrich the full sequence of 152 cancer predisposition genes. Sequencing was performed on Oxford Nanopore (ONT) R10.4.1 MinION flowcells with the Q20+ chemistry.

RESULTS

In our cohort, 11 samples had large-scale rearrangements (LSR), which were all detected with ONT sequencing. In addition to perfectly detecting the locus of the LSR, we found a known MLPA amplification of exon 13 in the BRCA1 (NM_7294) gene corresponded to a duplication in tandem of both exons 12 and 13 of the reference NM_7300. Similarly, in another sample with a known total deletion of the BRCA1 gene, ONT sequencing highlighted this complete deletion was the consequence of a large deletion of almost 140 000 bp carrying over five different genes. ONT sequencing was also able to detect all pathogenic nucleotide variants present in 16 samples at low coverage. As we analyzed complete genes and more genes than with short-read sequencing, we detected novel unknown variants. We randomly selected six new variants with a coverage larger than 10× and an average quality higher than 14, and confirmed all of them by Sanger sequencing, suggesting that variants detected with ONT (coverage >10× and quality score >14) could be considered as real variants.

CONCLUSIONS

We showed that ONT adaptive sampling sequencing is suitable for the analysis of germline alterations, improves characterization of LSR, and detects single nucleotide variations even at low coverage.

KEY POINTS

Adaptive sampling is suitable for the analysis of germline alterations. Improves the characterization of Large Scale Rearrangement and detects SNV at a minimum coverage of 10x. Allows flexibility of sequencing.

Clinically Significant BRCA1 and BRCA2 Germline Variants in Breast Cancer-A Single-Center Experience

BACKGROUND

Conditions associated with BRCA1/2 pathogenic (PVs) or likely pathogenic variants (LPVs) are often severe. The early detection of carrier status is ideal, as it provides options for effective case management.

MATERIALS AND METHODS

The study involved 58 patients with a personal and familial history of breast cancer (BC) who underwent genetic testing at the Regional Centre for Medical Genetics Dolj over a three-year period. An immunohistochemical panel (HER2, ER, PR, and Ki-67) was used to define the molecular subtypes of breast tumors. The AmpliSeq for Illumina BRCA Panel was used to evaluate germline variants in the BRCA1 and BRCA2 genes in patients with BC. The χ2 test and Fisher's exact test were used to compare the different parameters studied.

RESULTS

Our findings revealed that 15.5% of the patients carried either BRCA1 or BRCA2 PVs or LPVs. BRCA1 carriers had aggressive tumors whereas BRCA2 carriers had rather low-grade tumors.

CONCLUSIONS

The study revealed that PVs in both BRCA genes have a significant frequency among BC patients in our region, and BRCA1 carriers tend to develop more aggressive tumors than carriers of BRCA2 PVs and patients with no germline PVs in either of the two genes. These observations could provide new epidemiologic data for this disease in our region and contribute further to the development of national screening strategies.

An overview of key online resources for human genomics: a powerful and open toolbox for in silico research

Recent advances in high-throughput molecular methods have led to an extraordinary volume of genomics data. Simultaneously, the progress in the computational implementation of novel algorithms has facilitated the creation of hundreds of freely available online tools for their advanced analyses. However, a general overview of the most commonly used tools for the in silico analysis of genomics data is still missing. In the current article, we present an overview of commonly used online resources for genomics research, including over 50 tools. This selection will be helpful for scientists with basic or intermediate skills in the in silico analyses of genomics data, such as researchers and students from wet labs seeking to strengthen their computational competencies. In addition, we discuss current needs and future perspectives within this field.

Pharmacogenetic analysis of structural variation in the 1000 genomes project using whole genome sequences

While significant strides have been made in understanding pharmacogenetics (PGx) and gene-drug interactions, there remains limited characterization of population-level PGx variation. This study aims to comprehensively profile global star alleles (haplotype patterns) and phenotype frequencies in 58 pharmacogenes associated with drug absorption, distribution, metabolism, and excretion. PyPGx, a star-allele calling tool, was employed to identify star alleles within high-coverage whole genome sequencing (WGS) data from the 1000 Genomes Project (N = 2504; 26 global populations). This process involved detecting structural variants (SVs), such as gene deletions, duplications, hybrids, as well as single nucleotide variants and insertion-deletion variants. The majority of our PyPGx calls for star alleles and phenotype frequencies aligned with the Pharmacogenomics Knowledge Base, although notable population-specific frequencies differed at least twofold. Validation efforts confirmed known SVs while uncovering several novel SVs currently undefined as star alleles. Additionally, we identified 210 small nucleotide variants associated with severe functional consequences that are not defined as star alleles. The study serves as a valuable resource, providing updated population-level star allele and phenotype frequencies while incorporating SVs. It also highlights the burgeoning potential of cost-effective WGS for PGx genotyping, offering invaluable insights to improve tailored drug therapies across diverse populations.

Lack of a genetic risk continuum between pubertal timing in the general population and idiopathic hypogonadotropic hypogonadism

Pubertal timing is a highly heritable trait in the general population. Recently, a large-scale exome-wide association study has implicated rare variants in six genes (KDM4C, MC3R, MKRN3, PDE10A, TACR3, and ZNF483) as genetic determinants of pubertal timing within the general population. Two of the genes (TACR3, MKRN3) are already implicated in extreme disorders of pubertal timing. This observation suggests that there may be a pervasive "genetic risk continuum" wherein genes that govern pubertal timing in the general population, by extension, may also be causal for rare Mendelian disorders of pubertal timing. Hence, we hypothesized that the four novel genes linked to pubertal timing in the population will also contribute to idiopathic hypogonadotropic hypogonadism (IHH), a genetic disorder characterized by absent puberty. Exome sequencing data from 1322 unrelated IHH probands were reviewed for rare sequence variants (RSVs) (minor allele frequency bins: <1%; <0.1%; <0.01%) in the six genes linked to puberty in the general population. A gene-based rare variant association testing (RVAT) was performed between the IHH cohort and a reference public genomic sequences repository-the Genome Aggregation Database (gnomAD). As expected, RVAT analysis showed that RSVs in TACR3, a known IHH gene, were significantly enriched in the IHH cohort compared to gnomAD cohort across all three MAF bins. However, RVAT analysis of the remaining five genes failed to show any RSV enrichment in the IHH cohort across all MAF bins. Our findings argue strongly against a pervasive genetic risk continuum between pubertal timing in the general population and extreme pubertal phenotypes. The biologic basis of such distinct genetic architectures' merits further evaluation.

Large-scale copy number alterations are enriched for synthetic viability in BRCA1/BRCA2 tumors

BACKGROUND

Pathogenic BRCA1 or BRCA2 germline mutations contribute to hereditary breast, ovarian, prostate, and pancreatic cancer. Paradoxically, bi-allelic inactivation of BRCA1 or BRCA2 (bBRCA1/2) is embryonically lethal and decreases cellular proliferation. The compensatory mechanisms that facilitate oncogenesis in bBRCA1/2 tumors remain unclear.

METHODS

We identified recurrent genetic alterations enriched in human bBRCA1/2 tumors and experimentally validated if these improved proliferation in cellular models. We analyzed mutations and copy number alterations (CNAs) in bBRCA1/2 breast and ovarian cancer from the TCGA and ICGC. We used Fisher's exact test to identify CNAs enriched in bBRCA1/2 tumors compared to control tumors that lacked evidence of homologous recombination deficiency. Genes located in CNA regions enriched in bBRCA1/2 tumors were further screened by gene expression and their effects on proliferation in genome-wide CRISPR/Cas9 screens. A set of candidate genes was functionally validated with in vitro clonogenic survival and functional assays to validate their influence on proliferation in the setting of bBRCA1/2 mutations.

RESULTS

We found that bBRCA1/2 tumors harbor recurrent large-scale genomic deletions significantly more frequently than histologically matched controls (n = 238 cytobands in breast and ovarian cancers). Within the deleted regions, we identified 277 BRCA1-related genes and 218 BRCA2-related genes that had reduced expression and increased proliferation in bBRCA1/2 but not in wild-type cells in genome-wide CRISPR screens. In vitro validation of 20 candidate genes with clonogenic proliferation assays validated 9 genes, including RIC8A and ATMIN (ATM-Interacting protein). We identified loss of RIC8A, which occurs frequently in both bBRCA1/2 tumors and is synthetically viable with loss of both BRCA1 and BRCA2. Furthermore, we found that metastatic homologous recombination deficient cancers acquire loss-of-function mutations in RIC8A. Lastly, we identified that RIC8A does not rescue homologous recombination deficiency but may influence mitosis in bBRCA1/2 tumors, potentially leading to increased micronuclei formation.

CONCLUSIONS

This study provides a means to solve the tumor suppressor paradox by identifying synthetic viability interactions and causal driver genes affected by large-scale CNAs in human cancers.

Genome-wide association study and meta-analysis of phytosterols identifies a novel locus for serum levels of campesterol

Sitosterolemia is a rare inherited disorder caused by mutations in the ABCG5/ABCG8 genes. These genes encode proteins involved in the transport of plant sterols. Mutations in these genes lead to decreased excretion of phytosterols, which can accumulate in the body and lead to a variety of health problems, including premature coronary artery disease. We conducted the first genome-wide association study (GWAS) in the Middle East/North Africa population to identify genetic determinants of plant sterol levels in Qatari people. GWAS was performed on serum levels of β-sitosterol and campesterol using the Metabolon platform from Qatar Biobank (QBB) and genome sequence data provided by Qatar Genome Program. A trans-ancestry meta-analysis of data from our Qatari cohort with summary statistics from a previously published large cohort (9758 subjects) of European ancestry was conducted. Using conditional analysis, we identified two independent single nucleotide polymorphisms associated with β-sitosterol (rs145164937 and rs4299376), and two others with campesterol (rs7598542 and rs75901165) in the Qatari population in addition to previously reported variants. All of them map to the ABCG5/8 locus except rs75901165 which is located within the Intraflagellar Transport 43 (IFT43) gene. The meta-analysis replicated most of the reported variants, and our study provided significant support for the association of variants in SCARB1 and ABO with sitosterolemia. Evaluation of a polygenic risk score devised from European GWAS data showed moderate performance when applied to QBB (adjusted-R2 = 0.082). These findings provide new insights into the genetic architecture of phytosterol metabolism while showing the importance including under-represented populations in future GWAS studies.

T/myeloid mixed phenotype acute leukaemia harbouring TLX3::BCL11B with TLX3 activation

T/myeloid mixed phenotype acute leukaemia (MPAL) is a rare aggressive acute leukaemia with poorly understood pathogenesis. Herein, we report two cases of T/myeloid MPAL harbouring BCL11B-associated structural variants that activate TLX3 (TLX3::BCL11B-TLX3-activation) by genome sequencing and transcriptomic analyses. Both patients were young males with extramedullary involvement. Cooperative gene alterations characteristic of T/myeloid MPAL and T-lymphoblastic leukaemia (T-ALL) were detected. Both patients achieved initial remission following lineage-matched ALL-based therapy with one patient requiring a lineage-switched myeloid-based therapy. Our study is the first to demonstrate the clinicopathological and genomic features of TLX3::BCL11B-TLX3-activated T/myeloid MPAL and provide insights into leukaemogenesis.

Whole-Genome Resequencing Reveals Genetic Diversity and Growth Trait-Related Genes in Pinan Cattle

The breeding of high-quality beef cattle breeds is crucial for the development of animal husbandry, and whole-genome resequencing is widely applicated in the field of molecular breeding. Advantages in growth and reproductive traits exist in Pinan cattle compared with other cattle breeds, but there is limited research on its genomic mechanism. Using whole-genome resequencing, the genetic structure and genomic selection signatures in Pinan cattle were investigated in this study. Phylogenetic, cluster, and admixture analysis results indicated that Pinan cattle have a closer genetic relationship with Kholmogory cattle and China north cattle breeds. Through a selective sweep strategy, 207 and 54 candidate genes related to growth and reproduction and immunity, respectively, were identified in the Pinan cattle population. Given the crucial role of the glutamate-cysteine ligase catalytic (GCLC) gene in muscle antioxidative defense, the high frequency of allele T of the GCLC c.429 C>T locus in the Pinan cattle population might partially contribute to the advantages of Pinan cattle in growth performance. This study laid the foundation for the genetic improvement in Chinese local beef cattle and provide background for the studies on the growth and development of Pinan cattle.

Genetic analyses of inflammatory polyneuropathy and chronic inflammatory demyelinating polyradiculoneuropathy identified candidate genes

Chronic inflammatory demyelinating polyneuropathy (CIDP) is a rare, immune-mediated disorder in which an aberrant immune response causes demyelination and axonal damage of the peripheral nerves. Genetic contribution to CIDP is unclear and no genome-wide association study (GWAS) has been reported so far. In this study, we aimed to identify CIDP-related risk loci, genes, and pathways. We first focused on CIDP, and 516 CIDP cases and 403,545 controls were included in the GWAS analysis. We also investigated genetic risk for inflammatory polyneuropathy (IP), in which we performed a GWAS study using FinnGen data and combined the results with GWAS from the UK Biobank using a fixed-effect meta-analysis. A total of 1,261 IP cases and 823,730 controls were included in the analysis. Stratified analyses by gender were performed. Mendelian randomization (MR), colocalization, and transcriptome-wide association study (TWAS) analyses were performed to identify associated genes. Gene-set analyses were conducted to identify associated pathways. We identified one genome-wide significant locus at 20q13.33 for CIDP risk among women, the top variant located at the intron region of gene CDH4. Sex-combined MR, colocalization, and TWAS analyses identified three candidate pathogenic genes for CIDP and five genes for IP. MAGMA gene-set analyses identified a total of 18 pathways related to IP or CIDP. Sex-stratified analyses identified three genes for IP among males and two genes for IP among females. Our study identified suggestive risk genes and pathways for CIDP and IP. Functional analyses should be conducted to further confirm these associations.

Genome-wide association exploratory studies in individuals with ultra-high risk for schizophrenia in Chinese Han nationality in two years follow-up: A subpopulation study

BACKGROUND

Although ultra-high risk for schizophrenia (UHR) is related to both genetic and environment factors, the precise pathogenesis is still unknow. To date, few studies have explored the Genome-Wide Association Studies (GWAS) in UHR or HR individuals especially in Han population in China.

METHODS

In this study, a GWAS analysis for 36 participants with UHR and 43 with HR were performed, and all deletion variations in 22q11 region were also compared.

RESULTS

Sixteen individuals with UHR (44.4%) and none with HR converted into schizophrenia in follow-up after two years. Six loci including neurexin-1(NRXN1) (rs1045881), dopamine D1 receptor (DRD1) (rs686, rs4532), chitinase-3-like protein 1 (CHI3L1) (rs4950928), velocardiofacial syndrome (ARVCF) (rs165815), dopamine D2 receptor (DRD2) (rs1076560) were identified higher expression with significant difference in individuals converted into schizophrenia after two years. The Family with Sequence Similarity 230 Member H (FAM230H) gene in the 22q11 region were also found high expression in UHR group.

CONCLUSIONS

Further expansion of sample size and validation studies are needed to explore the pathogenesis of these risk loci in UHR conversion into schizophrenia in the future.

Deciphering the Impact of Rare Missense Variants in EGFR-TKI-Resistant Non-Small-Cell Lung Cancer through Whole Exome Sequencing: A Computational Approach

Targeted therapy revolutionizes the treatment of non-small-cell lung cancer (NSCLC), harboring molecular change. Epidermal growth factor receptor(EGFR) mutations play a crucial role in the development of NSCLC, serving as a pivotal factor in its pathogenesis. We elucidated the mechanisms of resistance and potential therapeutic strategies in NSCLC resistant to the EGFR-tyrosine kinase inhibitor (EGFR-TKI). This is achieved by identifying rare missense variants through whole exome sequencing (WES). The goal is to enhance our understanding, identify biomarkers, and lay the groundwork for targeted interventions, thereby offering hope for an improved NSCLC treatment landscape. We conducted WES analysis on 16 NSCLC samples with EGFR-TKI-resistant NSCLC obtained from SRA-NCBI (PRJEB50602) to reveal genomic profiles within the EGFR-TKI. Our findings showed that 48% of the variants were missense, and after filtering with the Ensembl variant effect predictor, 53 rare missense variants in 23 genes were identified as highly deleterious. Further examination using pathogenic tools like PredictSNP revealed 12 deleterious rare missense variants in 7 genes: ZNF717, PSPH, ESRRA, SEMA3G, PTPN7, CAVIN4, and MYBBP1A. Molecular dynamics simulation (MDS) suggested that the L385P variant alters the structural flexibility of ESRRA, potentially leading to unfolding of ERRα proteins. This could impact their function and alter ERRα expression. These insights from MDS enhance our understanding of the structural and dynamic consequences of the L385P ESRRA variant and provide valuable implications for subsequent therapeutic considerations and targeted interventions.

Genome-Wide Analysis of Exertional Rhabdomyolysis in Sickle Cell Trait Positive African Americans

Sickle cell trait (SCT), although generally a benign carrier state of hemoglobin S (HbAS), is a risk factor for exertional rhabdomyolysis (ERM), a rare but potentially fatal consequence of highly intense physical exercise, particularly among active-duty military personnel and high-performance athletes. The association between SCT and ERM is poorly understood. The objective of this study was to elucidate the genetic basis of ERM in an SCT-positive African American cohort. SCT-positive African Americans with a personal history of ERM (cases, n = 30) and without history of ERM (controls, n = 53) were enrolled in this study. Whole-genome sequencing was performed on DNA samples isolated from peripheral white blood cells. Participants' demographic, behavioral, and medical history information was obtained. An additional 131 controls were extracted from SCT-positive subjects of African descent from the 1000 Genomes Project. SCT carriers with ERM were characterized by myotoxicity features, significant muscle involvement dominated by muscle weakness, and severe pain and substantial increase in serum creatine kinase, with a mean value of 50,480 U/L. A distinctive feature of the SCT individuals with ERM was exertional collapse, which was reported in 53.3% of the cases in the study cohort. An important factor for the development of ERM was the duration and frequency of strenuous physical activity in the cases compared to the controls. Whole-genome sequencing identified 79,696 protein-coding variants. Genome-wide association analysis revealed that the p.C477R, rs115958260 variant in the SLC44A3 gene was significantly associated with ERM event in SCT-positive African Americans. The study results suggest that a combination of vigorous exercise and a genetic predisposing factor is involved in ERM.

A Comprehensive Analysis of the Effect of A>I(G) RNA-Editing Sites on Genotoxic Drug Response and Progression in Breast Cancer

Dysregulated A>I(G) RNA editing, which is mainly catalyzed by ADAR1 and is a type of post-transcriptional modification, has been linked to cancer. A low response to therapy in breast cancer (BC) is a significant contributor to mortality. However, it remains unclear if there is an association between A>I(G) RNA-edited sites and sensitivity to genotoxic drugs. To address this issue, we employed a stringent bioinformatics approach to identify differentially RNA-edited sites (DESs) associated with low or high sensitivity (FDR 0.1, log2 fold change 2.5) according to the IC50 of PARP inhibitors, anthracyclines, and alkylating agents using WGS/RNA-seq data in BC cell lines. We then validated these findings in patients with basal subtype BC. These DESs are mainly located in non-coding regions, but a lesser proportion in coding regions showed predicted deleterious consequences. Notably, some of these DESs are previously reported as oncogenic variants, and in genes related to DNA damage repair, drug metabolism, gene regulation, the cell cycle, and immune response. In patients with BC, we uncovered DESs predominantly in immune response genes, and a subset with a significant association (log-rank test p < 0.05) between RNA editing level in LSR, SMPDL3B, HTRA4, and LL22NC03-80A10.6 genes, and progression-free survival. Our findings provide a landscape of RNA-edited sites that may be involved in drug response mechanisms, highlighting the value of A>I(G) RNA editing in clinical outcomes for BC.

GwasWA: A GWAS one-stop analysis platform from WGS data to variant effect assessment

Using the accumulated whole-genome sequencing (WGS) data and assessing the functional effects of genetic variants, particularly non-coding variants, help identify new and rare variants and decipher the molecular mechanisms underlying diseases and traits but presents significant challenges. GwasWA is a comprehensive and efficient platform to identify causal variants and assess their functional effects based on WGS data. It covers the entire workflow from downloading and processing WGS data to detecting associated variants and assessing their functional effects with optimized configurations, standardized input/output formats, personalized analysis options, data visualization, and parallel processing capability that is crucial for large-scale studies. Applying GwasWA to real datasets identified three novel genes related to seed size and revealed the regulatory mechanism underlying the linkage between a human non-coding variant, rs80067372, and tumor necrosis factor levels. These results highlight the capability of GwasWA to detect novel variants based on WGS data and provide comprehensive insights into the molecular mechanisms underlying the association of variants with diseases and traits, thus contributing to medicine and biology. GwasWA and its documentation are freely available at https://github.com/unicorn-23/GwasWA.

Genome-wide association study analysis of disease severity in Acne reveals novel biological insights

Acne vulgaris is a common skin disease that affects >85% of teenage young adults among which >8% develop severe lesions that leaves permanent scars. Genetic heritability studies of acne in twin cohorts have estimated that the heritability for acne is 80%. Previous genome-wide association studies (GWAS) have identified 50 genetic loci associated with increased risk of developing acne when compared to healthy individuals. However only a few studies have investigated genetic association with disease severity. GWAS of disease progression may provide a more effective approach to unveil potential disease modifying therapeutic targets. Here, we performed a multi-ethnic GWAS analysis to capture disease severity in acne patients by using individuals with normal acne as a control. Our cohort consists of a total of 2,956 participants, including 290 severe acne cases and 930 normal acne controls from FinnGen, and 522 cases and 1,214 controls from BioVU. We also performed mendelian randomization (MR), colocalization analyses and transcriptome-wide association study (TWAS) to identify putative causal genes. Lastly, we performed gene-set enrichment analysis using MAGMA to implicate biological pathways that drive disease severity in Acne. We identified two new loci associated with acne severity at the genome-wide significance level, six novel associated genes by MR, colocalization and TWAS analyses, including genes CDC7, SLC7A1, ADAM23, TTLL10, CDK20 and DNAJA4 , and 5 novel pathways by MAGMA analyses. Our study suggests that the etiologies of acne susceptibility and severity have limited overlap, with only 26% of known acne risk loci presenting nominal association with acne severity and none of the novel severity associated genes reported as associated with acne risk in previous GWAS.

The status of the human gene catalogue

Scientists have been trying to identify every gene in the human genome since the initial draft was published in 2001. In the years since, much progress has been made in identifying protein-coding genes, currently estimated to number fewer than 20,000, with an ever-expanding number of distinct protein-coding isoforms. Here we review the status of the human gene catalogue and the efforts to complete it in recent years. Beside the ongoing annotation of protein-coding genes, their isoforms and pseudogenes, the invention of high-throughput RNA sequencing and other technological breakthroughs have led to a rapid growth in the number of reported non-coding RNA genes. For most of these non-coding RNAs, the functional relevance is currently unclear; we look at recent advances that offer paths forward to identifying their functions and towards eventually completing the human gene catalogue. Finally, we examine the need for a universal annotation standard that includes all medically significant genes and maintains their relationships with different reference genomes for the use of the human gene catalogue in clinical settings.

Genetic determinants of Vitamin D deficiency in the Middle Eastern Qatari population: a genome-wide association study

Introduction

Epidemiological studies have consistently revealed that Vitamin D deficiency is most prevalent in Middle Eastern countries. However, research on the impact of genetic loci and polygenic models related to Vitamin D has primarily focused on European populations.

Methods

We conducted the first genome-wide association study to identify genetic determinants of Vitamin D levels in Middle Easterners using a whole genome sequencing approach in 6,047 subjects from the Qatar Biobank (QBB) project. We performed a GWAS meta-analysis, combining the QBB cohort with recent European GWAS data from the UK Biobank (involving 345,923 individuals). Additionally, we evaluated the performance of European-derived polygenic risk scores using UK Biobank data in the QBB cohort.

Results

Our study identified an association between a variant in a known locus for the group-specific component gene (GC), specifically rs2298850 (p-value = 1.71 × 10-08, Beta = -0.1285), and Vitamin D levels. Furthermore, our GWAS meta-analysis identified two novel variants at a known locus on chromosome 11, rs67609747 and rs1945603, that reached the GWAS significance threshold. Notably, we observed a moderately high heritability of Vitamin D, estimated at 18%, compared to Europeans. Despite the lower predictive performance of Vitamin D levels in Qataris compared to Europeans, the European-derived polygenic risk scores exhibited significant links to Vitamin D deficiency risk within the QBB cohort.

Conclusion

This novel study reveals the genetic architecture contributing to Vitamin D deficiency in the Qatari population, emphasizing the genetic heterogeneity across different populations.

aenmd: annotating escape from nonsense-mediated decay for transcripts with protein-truncating variants

SUMMARY

DNA changes that cause premature termination codons (PTCs) represent a large fraction of clinically relevant pathogenic genomic variation. Typically, PTCs induce transcript degradation by nonsense-mediated mRNA decay (NMD) and render such changes loss-of-function alleles. However, certain PTC-containing transcripts escape NMD and can exert dominant-negative or gain-of-function (DN/GOF) effects. Therefore, systematic identification of human PTC-causing variants and their susceptibility to NMD contributes to the investigation of the role of DN/GOF alleles in human disease. Here we present aenmd, a software for annotating PTC-containing transcript-variant pairs for predicted escape from NMD. aenmd is user-friendly and self-contained. It offers functionality not currently available in other methods and is based on established and experimentally validated rules for NMD escape; the software is designed to work at scale, and to integrate seamlessly with existing analysis workflows. We applied aenmd to variants in the gnomAD, Clinvar, and GWAS catalog databases and report the prevalence of human PTC-causing variants in these databases, and the subset of these variants that could exert DN/GOF effects via NMD escape.

AVAILABILITY AND IMPLEMENTATION

aenmd is implemented in the R programming language. Code is available on GitHub as an R-package (github.com/kostkalab/aenmd.git), and as a containerized command-line interface (github.com/kostkalab/aenmd_cli.git).

Leveraging decagonal in-silico strategies for uncovering IL-6 inhibitors with precision

Interleukin-6 upregulation leads to various acute phase reactions such as local inflammation and systemic inflammation in many diseases like cancer, multiple sclerosis, rheumatoid arthritis, anemia, and Alzheimer's disease stimulating JAK/STAT3, Ras/MAPK, PI3K-PKB/Akt pathogenic pathways. Since no small molecules are available in the market against IL-6 till now, we have designed a class of small bioactive 1,3 - indanedione (IDC) molecules for inhibiting IL-6 using a decagonal approach computational studies. The IL-6 mutations were mapped in the IL-6 protein (PDB ID: 1ALU) from thorough pharmacogenomic and proteomics studies. The protein-drug interaction networking analysis for 2637 FFDA-approved drugs with IL-6 protein using Cytoscape software showed that 14 drugs have prominent interactions with IL-6. Molecular docking studies showed that the designed compound IDC-24 (-11.8 kcal/mol) and methotrexate (-5.20) bound most strongly to the 1ALU south asian population mutated protein. MMGBSA results indicated that IDC-24 (-41.78 kcal/mol) and methotrexate (-36.81 kcal/mol) had the highest binding energy when compared to the standard molecules LMT-28 (-35.87 kcal/mol) and MDL-A (-26.18 kcal/mol). These results we substantiated by the molecular dynamic studies in which the compound IDC-24 and the methotrexate had the highest stability. Further, the MMPBSA computations produced energies of -28 kcal/mol and -14.69 kcal/mol for IDC-24 and LMT-28. KDeep absolute binding affinity computations revealed energies of -5.81 kcal/mol and -4.74 kcal/mol for IDC-24 and LMT-28 respectively. Finally, our decagonal approach established the compound IDC-24 from the designed 1,3-indanedione library and methotrexate from protein drug interaction networking as suitable HITs against IL-6.

The Genetic Architecture of Vitamin D Deficiency among an Elderly Lebanese Middle Eastern Population: An Exome-Wide Association Study

The Middle East region experiences a high prevalence of vitamin D deficiency, yet most genetic studies on vitamin D have focused on European populations. Furthermore, there is a lack of research on the genomic risk factors affecting elderly people, who are more susceptible to health burdens. We investigated the genetic determinants of 25-hydroxyvitamin D concentrations in elderly Lebanese individuals (n = 199) through a whole-exome-based genome-wide association study. Novel genomic loci displaying suggestive evidence of association with 25-hydroxyvitamin D levels were identified in our study, including rs141064014 in the MGAM (p-value of 4.40 × 10^-6) and rs7036592 in PHF2 (p-value of 8.43 × 10^-6). A meta-analysis of the Lebanese data and the largest European genome-wide association study confirmed consistency replication of numerous variants, including rs2725405 in SLC38A10 (p-value of 3.73 × 10^-8). Although the polygenic risk score model derived from European populations exhibited lower performance than European estimations, it still effectively predicted vitamin D deficiency among our cohort. Our discoveries offer novel perspectives on the genetic mechanisms underlying vitamin D deficiency among elderly Middle Eastern populations, facilitating the development of personalized approaches for more effective management of vitamin D deficiency. Additionally, we demonstrated that whole-exome-based genome-wide association study is an effective method for identifying genetic components associated with phenotypes.

Homozygosity mapping in the Kazakh national dog breed Tazy

The Tazy is a breed of sighthound common in Kazakhstan. The identification of runs of homozygosity (ROH) is an informative approach to assessing the history and possible patterns of directional selection pressure. To our knowledge, the present study is the first to provide an overview of the ROH pattern in the Tazy dogs from a genome-wide perspective. The ROH of the Tazy was found to be mainly composed of shorter segments (1-2 Mb), accounting for approximately 67% of the total ROH. The estimated ROH-based inbreeding coefficients (F_ROH) ranged from 0.028 to 0.058 with a mean of 0.057. Five genomic regions under positive selection were identified on chromosomes 18, 22, and 25. The regions on chromosomes 18 and 22 may be breed specific, while the region on chromosome 22 overlaps with regions of hunting traits in other hunting dog breeds. Among the 12 candidate genes located in these regions, the gene CAB39L may be a candidate that affects running speed and endurance of the Tazy dog. Eight genes could belong to an evolutionarily conserved complex as they were clustered in a large protein network with strong linkages. The results may enable effective interventions when incorporated into conservation planning and selection of the Tazy breed.

The AnnotSV webserver in 2023: updated visualization and ranking

Much of the human genetics variant repertoire is composed of single nucleotide variants (SNV) and small insertion/deletions (indel) but structural variants (SV) remain a major part of our modified DNA. SV detection has often been a complex question to answer either because of the necessity to use different technologies (array CGH, SNP array, Karyotype, Optical Genome Mapping…) to detect each category of SV or to get an appropriate resolution (Whole Genome Sequencing). Thanks to the deluge of pangenomic analysis, Human geneticists are accumulating SV and their interpretation remains time consuming and challenging. The AnnotSV webserver (https://www.lbgi.fr/AnnotSV/) aims at being an efficient tool to (i) annotate and interpret SV potential pathogenicity in the context of human diseases, (ii) recognize potential false positive variants from all the SV identified and (iii) visualize the patient variants repertoire. The most recent developments in the AnnotSV webserver are: (i) updated annotations sources and ranking, (ii) three novel output formats to allow diverse utilization (analysis, pipelines), as well as (iii) two novel user interfaces including an interactive circos view.

Robust identification of regulatory variants (eQTLs) using a differential expression framework developed for RNA-sequencing

BACKGROUND

A gap currently exists between genetic variants and the underlying cell and tissue biology of a trait, and expression quantitative trait loci (eQTL) studies provide important information to help close that gap. However, two concerns that arise with eQTL analyses using RNA-sequencing data are normalization of data across samples and the data not following a normal distribution. Multiple pipelines have been suggested to address this. For instance, the most recent analysis of the human and farm Genotype-Tissue Expression (GTEx) project proposes using trimmed means of M-values (TMM) to normalize the data followed by an inverse normal transformation.

RESULTS

In this study, we reasoned that eQTL analysis could be carried out using the same framework used for differential gene expression (DGE), which uses a negative binomial model, a statistical test feasible for count data. Using the GTEx framework, we identified 35 significant eQTLs (P < 5 × 10^-8) following the ANOVA model and 39 significant eQTLs (P < 5 × 10^-8) following the additive model. Using a differential gene expression framework, we identified 930 and six significant eQTLs (P < 5 × 10^-8) following an analytical framework equivalent to the ANOVA and additive model, respectively. When we compared the two approaches, there was no overlap of significant eQTLs between the two frameworks. Because we defined specific contrasts, we identified trans eQTLs that more closely resembled what we expect from genetic variants showing complete dominance between alleles. Yet, these were not identified by the GTEx framework.

CONCLUSIONS

Our results show that transforming RNA-sequencing data to fit a normal distribution prior to eQTL analysis is not required when the DGE framework is employed. Our proposed approach detected biologically relevant variants that otherwise would not have been identified due to data transformation to fit a normal distribution.

The status of the human gene catalogue

Scientists have been trying to identify all of the genes in the human genome since the initial draft of the genome was published in 2001. Over the intervening years, much progress has been made in identifying protein-coding genes, and the estimated number has shrunk to fewer than 20,000, although the number of distinct protein-coding isoforms has expanded dramatically. The invention of high-throughput RNA sequencing and other technological breakthroughs have led to an explosion in the number of reported non-coding RNA genes, although most of them do not yet have any known function. A combination of recent advances offers a path forward to identifying these functions and towards eventually completing the human gene catalogue. However, much work remains to be done before we have a universal annotation standard that includes all medically significant genes, maintains their relationships with different reference genomes, and describes clinically relevant genetic variants.

aenmd: Annotating escape from nonsense-mediated decay for transcripts with protein-truncating variants

DNA changes that cause premature termination codons (PTCs) represent a large fraction of clinically relevant pathogenic genomic variation. Typically, PTCs induce a transcript's degradation by nonsense-mediated mRNA decay (NMD) and render such changes loss-of-function alleles. However, certain PTC-containing transcripts escape NMD and can exert dominant-negative or gain-of-function (DN/GOF) effects. Therefore, systematic identification of human PTC-causing variants and their susceptibility to NMD contributes to the investigation of the role of DN/GOF alleles in human disease. Here we present aenmd, a software for annotating PTC-containing transcript-variant pairs for predicted escape from NMD. aenmd is user-friendly and self-contained. It offers functionality not currently available in other methods and is based on established and experimentally validated rules for NMD escape; the software is designed to work at scale, and to integrate seamlessly with existing analysis workflows. We applied aenmd to variants in the gnomAD, Clinvar, and GWAS catalog databases and report the prevalence of human PTC-causing variants in these databases, and the subset of these that could exert DN/GOF effects via NMD escape. Availability and implementation: aenmd is implemented in the R programming language. Code is available on GitHub as an R package (github.com/kostkalab/aenmd.git), and as a containerized command-line interface (github.com/kostkalab/aenmd_cli.git).

Non-Syndromic Hearing Loss in a Romanian Population: Carrier Status and Frequent Variants in the GJB2 Gene

The genetic causes of autosomal recessive nonsyndromic hearing loss (ARNSHL) are heterogeneous and highly ethnic-specific. We describe GJB2 (connexin 26) variants and carrier frequencies as part of our study and summarize previously reported ones for the Romanian population. In total, 284 unrelated children with bilateral congenital NSHL were enrolled between 2009 and 2018 in northwestern Romania. A tiered diagnostic approach was used: all subjects were tested for c.35delG, c.71G>A and deletions in GJB6 (connexin 30) using PCR-based methods. Furthermore, 124 cases undiagnosed at this stage were analyzed by multiplex-ligation-dependent probe amplifications (MLPA), probe mix P163, and sequencing of GJB2 exon 2. Targeted allele-specific PCR/restriction fragment length polymorphism (RFLP) established definite ethio-pathogenical diagnosis for 72/284 (25.35%) of the cohort. Out of the 124 further analyzed, in 12 cases (9.67%), we found compound heterozygous point mutations in GJB2. We identified one case of deletion of exon 1 of the WFS1 (wolframin) gene. Carrier status evaluation used Illumina Infinium Global Screening Array (GSA) genotyping: the HINT cohort-416 individuals in northwest Romania, and the FUSE cohort-472 individuals in southwest Romania. GSA variants yielded a cumulated risk allele presence of 0.0284. A tiered diagnostic approach may be efficient in diagnosing ARNSHL. The summarized contributions to Romanian descriptive epidemiology of ARNSHL shows that pathogenic variants in the GJB2 gene are frequent among NSHL cases and have high carrier rates, especially for c.35delG and c.71G>A. These findings may serve in health strategy development.

Phenotype-aware prioritisation of rare Mendelian disease variants

A molecular diagnosis from the analysis of sequencing data in rare Mendelian diseases has a huge impact on the management of patients and their families. Numerous patient phenotype-aware variant prioritisation (VP) tools have been developed to help automate this process, and shorten the diagnostic odyssey, but performance statistics on real patient data are limited. Here we identify, assess, and compare the performance of all up-to-date, freely available, and programmatically accessible tools using a whole-exome, retinal disease dataset from 134 individuals with a molecular diagnosis. All tools were able to identify around two-thirds of the genetic diagnoses as the top-ranked candidate, with LIRICAL performing best overall. Finally, we discuss the challenges to overcome most cases remaining undiagnosed after current, state-of-the-art practices.

Using Genomic Variation to Distinguish Ovarian High-Grade Serous Carcinoma from Benign Fallopian Tubes

The preoperative diagnosis of pelvic masses has been elusive to date. Methods for characterization such as CA-125 have had limited specificity. We hypothesize that genomic variation can be used to create prediction models which accurately distinguish high grade serous ovarian cancer (HGSC) from benign tissue.

METHODS

In this retrospective, pilot study, we extracted DNA and RNA from HGSC specimens and from benign fallopian tubes. Then, we performed whole exome sequencing and RNA sequencing, and identified single nucleotide variants (SNV), copy number variants (CNV) and structural variants (SV). We used these variants to create prediction models to distinguish cancer from benign tissue. The models were then validated in independent datasets and with a machine learning platform.

RESULTS

The prediction model with SNV had an AUC of 1.00 (95% CI 1.00-1.00). The models with CNV and SV had AUC of 0.87 and 0.73, respectively. Validated models also had excellent performances.

CONCLUSIONS

Genomic variation of HGSC can be used to create prediction models which accurately discriminate cancer from benign tissue. Further refining of these models (early-stage samples, other tumor types) has the potential to lead to detection of ovarian cancer in blood with cell free DNA, even in early stage.

In silico identification of the rare-coding pathogenic mutations and structural modeling of human NNAT gene associated with anorexia nervosa

PURPOSE

Increased susceptibility towards anorexia nervosa (AN) was reported with reduced levels of neuronatin (NNAT) gene. We sought to investigate the most pathogenic rare-coding missense mutations, non-synonymous single-nucleotide polymorphisms (nsSNPs) of NNAT and their potential damaging impact on protein function through transcript level sequence and structure based in silico approaches.

METHODS

Gene sequence, single nucleotide polymorphisms (SNPs) of NNAT was retrieved from public databases and the putative post-translational modification (PTM) sites were analyzed. Distinctive in silico algorithms were recruited for transcript level SNPs analyses and to characterized high-risk rare-coding nsSNPs along with their impact on protein stability function. Ab initio 3D-modeling of wild-type, alternate model prediction for most deleterious nsSNP, validation and recognition of druggable binding pockets were also performed. AN 3D therapeutic compounds that followed rule of drug-likeness were docked with most pathogenic variant of NNAT to estimate the drugs' binding free energies.

RESULTS

Conclusively, 10 transcript (201-205)-based nsSNPs from 3 rare-coding missense variants, i.e., rs539681368, rs542858994, rs560845323 out of 840 exonic SNPs were identified. Transcript-based functional impact analyses predicted rs539681368 (C30Y) from NNAT-204 as the high-risk rare-coding pathogenic nsSNP, deviating protein functions. The 3D-modeling analysis of AN drugs' binding energies indicated lowest binding free energy (ΔG) and significant inhibition constant (K_i) with mutant models C30Y.

CONCLUSIONS

Mutant model (C30Y) exhibiting significant drug binding affinity and the commonest interaction observed at the acetylation site K59. Thus, based on these findings, we concluded that the identified nsSNP may serve as potential targets for various studies, diagnosis and therapeutic interventions.

LEVEL OF EVIDENCE

No level of evidence-open access bioinformatics research.

Genome-Wide Analysis Identifies Candidate Genes Encoding Feather Color in Ducks

Comparative population genomics and genome-wide association studies (GWAS) offer opportunities to discover human-driven detectable signatures within the genome. From the point of view of evolutionary biology, the identification of genes associated with the domestication of traits is of interest for the elucidation of the selection of these traits. To this end, an F2 population of ducks, consisting of 275 ducks, was genotyped using a whole genome re-sequence containing 12.6 Mb single nucleotide polymorphisms (SNPs) and four plumage colors. GWAS was used to identify the candidate and potential SNPs of four plumage colors in ducks (white, spot, grey, and black plumage). In addition, FST and genetic diversity (π ratio) were used to screen signals of the selective sweep, which relate to the four plumage colors. Major genomic regions associated with white, spotted, and black feathers overlapped with their candidate selection regions, whereas no such overlap was observed with grey plumage. In addition, MITF and EDNRB2 are functional candidate genes that contribute to white and black plumage due to their indirect involvement in the melanogenesis pathway. This study provides new insights into the genetic factors that may influence the diversity of plumage color.