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In silico prediction method for plant Nucleotide-binding leucine-rich repeat- and pathogen effector interactions.

Plant Nucleotide-binding leucine-rich repeat (NLR) proteins play a crucial role in effector recognition and activation of Effector triggered immunity following pathogen infection. Genome sequencing advancements have led to the identification of a myriad of NLRs in numerous agriculturally important plant species. However, deciphering which NLRs recognize specific pathogen effectors remains challenging. Predicting NLR-effector interactions in silico will provide a more targeted approach for experimental validation, critical for elucidating function, and advancing our understanding of NLR-triggered immunity. In this study, NLR-effector protein complex structures were predicted using AlphaFold2-Multimer for all experimentally validated NLR-effector interactions reported in literature. Binding affinities- and energies were predicted using 97 machine learning models from Area-Affinity. We show that AlphaFold2-Multimer predicted structures have acceptable accuracy and can be used to investigate NLR-effector interactions in silico. Binding affinities for 58 NLR-effector complexes ranged between -8.5 and -10.6 log(K), and binding energies between -11.8 and -14.4 kcal/mol-1, depending on the Area-Affinity model used. For 2427 "forced" NLR-effector complexes, these estimates showed larger variability, enabling identification of novel NLR-effector interactions with 99% accuracy using an Ensemble machine learning model. The narrow range of binding energies- and affinities for "true" interactions suggest a specific change in Gibbs free energy, and thus conformational change, is required for NLR activation. This is the first study to provide a method for predicting NLR-effector interactions, applicable to all pathosystems. Finally, the NLR-Effector Interaction Classification (NEIC) resource can streamline research efforts by identifying NLRs important for plant-pathogen resistance, advancing our understanding of plant immunity.

Plant Proteins

Beyond in silico prediction: multi-omics to identify a pathogenic deep intronic HNRNPK variant in Au-Kline syndrome.

Pathogenic variants in HNRNPK are associated with autosomal dominant Au-Kline syndrome (AKS, Au-Kline-Okamoto syndrome, OMIM #616580). This syndrome is characterized by developmental delay and intellectual disability, hypotonia, and distinctive facial features. Despite the use of whole-genome sequencing (WGS) as a powerful diagnostic tool, we nearly dismissed a novel intronic variant (NM_031263.4(HNRNPK):c.214-55 T > A) affecting HNRNPK splicing and function. Although commonly used bioinformatic splice prediction tools, including SpliceAI and PDIVAS, yielded inconclusive results, Face2Gene analysis indicated a high phenotypic similarity to AKS. Characteristic facial features described by Choufani et al. [1] supported the clinical diagnosis of AKS. Subsequent functional studies demonstrated aberrant splicing with intron retention, and DNA methylation profiling revealed a positive HNRNPK-specific episignature. These insights and the de novo status support an evaluation as likely pathogenic. This case report supports the relevance of facial analysis and comprehensive variant validation strategies, particularly for deep intronic variants with ambiguous in silico splicing predictions.

Journal Article

In silico prediction of the impact of genomic variations in the small conductance calcium activated potassium channel SK3 structure and function.

The small-conductance calcium-activated potassium channel SK3, encoded by the KCNN3 gene, plays a critical role in regulating dopaminergic neuron (DN) firing patterns by modulating after hyperpolarization currents. SK3 dysfunction has been implicated in neuropsychiatric and neurodegenerative disorders. We analyzed structural and functional consequences of KCNN3 splicing and genetic variation. Alternative splicing variants of the KCNN3 gene were retrieved from the Ensembl database and aligned using T-Coffee, manually inspected and curated. Protein domains were identified with Pfam 35.0, SMART 9.0, and InterPro 98.0, and visualized. An AlphaFold2 model of SK3 full-length protein (UniProt: Q9UGI6) used as reference and structural models of its splicing variants were predicted with ColabFold. Functional domains (S1-S6 transmembrane helices, H5 pore loop, and calmodulin-binding) were defined and superimposed onto the AlphaFold2 reference. Domain integrity was assessed based on completeness of all expected residue indices within each functional region. SNPs and CNVs across all coding KCNN3 splicing variants were analyzed, classified, and filtered to isolate pathogenic variants prioritizing non-synonymous amino acid substitutions. Differential variant impacts across splicing isoforms were assessed by mapping variant positions to individual transcript protein sequences and used to predict functional consequences. Two long and two short splicing variants are known. Short variants lack the motif required for potassium channels. Pathogenic variants result from missense mutations resulting in amino acid substitutions. In all cases, the consequential effects depend on the specific location and role of the amino acid being changed.

SK3 channels

Systematic functional evaluation of CNGA1 missense variants associated with retinitis pigmentosa.

BACKGROUND: Missense variants are frequently classified as variants of uncertain significance (VUS) according to the guidelines of the American College of Medical Genetics and Genomics and the Association of Molecular Pathology (ACMG/AMP). Consequently, disease relevance remains elusive, impeding molecular genetic diagnostics, patients` and family genetic counseling, and identification of patients eligible for clinical trials. Functional studies are critical for resolving the clinical significance of VUS. CNGA1 encodes the main subunit of the rod cyclic nucleotide-gated (CNG) channel, a vital component of the phototransduction cascade. Variants in CNGA1 are a rare cause of autosomal recessive retinitis pigmentosa and a phase I/II gene augmentation trial (NCT06291935) is currently ongoing highlighting the necessity to differentiate benign from pathogenic variants. METHODS: CNGA1 missense variants compiled from retinal disease patient cohorts, public databases and literature were functionally investigated using a medium-throughput aequorin-based assay and in vitro minigene splice assays for predicted exonic spliceogenic variants. Functional data were correlated with the in silico prediction of five variant effect predictors (VEPs) and applied to support or revise variants' ACMG/AMP classification. RESULTS: Data mining revealed 86 missense CNGA1 variants - including three novel - most of them lacking functional data; 65.1% of the variants were initially classified as VUS. The aequorin-based assay showed that 72.1% of tested variants significantly impaired CNG channel function and were classified as functionally abnormal, while 23.3% were functionally normal and 5% remained functionally uncertain. Correlation of the functional data with in silico predictions identified AlphaMissense and CPT-1 to be the most suitable tools for assessing CNGA1 missense variants. Using in vitro minigene splice assays, two putative missense variants were shown to induce missplicing. Based on the functional findings, 62.1% of the variants initially classified as VUS were re-categorized as likely pathogenic or likely benign. Furthermore, 93.3% of the variants initially classified as likely pathogenic showed an effect on CNGA1 channel function, confirming their disease relevance and supporting their reclassification as pathogenic. CONCLUSION: This study represents the first comprehensive functional assessment of disease-associated CNGA1 missense variants, thus significantly advancing the understanding of their disease relevance and improving molecular genetic diagnostics in patients.

Humans

Substitutions of nucleotides at the 3' ends of COL6A1/2/3 exons induce exon skipping associated with collagen VI-related muscular dystrophies and therapeutic strategies.

PURPOSE: Collagen VI-related muscular dystrophies, characterized by proximal muscle weakness and joint contractures, are caused by pathogenic variants in the genes, COL6A1 to COL6A3. A monoallelic variant at the last nucleotide of a COL6A1 exon was initially classified as a missense variant but acted as a splicing variant, resulting in exon skipping. Here, we evaluated whether single-nucleotide variants at the 3'-ends of COL6A1 to COL6A3 exons cause aberrant splicing. METHODS: Ten relevant variants were identified in patients from our repository or public databases, and their muscle COL6A1 to COL6A3 transcripts were analyzed. The effects of the variants on splicing were also analyzed by minigene assay and SpliceAI in silico prediction. RESULTS: Transcripts from muscles of individuals with suspected collagen VI-related phenotypes showed exon skipping (skipping rate >12%). Findings of minigene assay and in silico prediction experiments supported these findings. Two therapeutic approaches, splicing correction of pre-messenger RNA or gene silencing of mature messenger RNA were assessed. Among them, gene silencing using short interfering RNAs targeting the skipped transcripts proved to be effective in restoring collagen VI in cells containing the pathogenic variant. CONCLUSION: Single-nucleotide variants at the 3'-ends of exons can lead to aberrant splicing, and allele-specific gene silencing targeting such variants is a promising therapeutic strategy.

Humans

Deciphering the Role of LNX2 as a Potential Contributor to Neurodevelopmental Disorders.

BACKGROUND/OBJECTIVES: Attention-deficit/hyperactivity disorder (ADHD) is a common neurodevelopmental condition characterized by a complex and multifactorial genetic architecture. In this study, we report a male patient, born to non-consanguineous healthy parents, presenting with ADHD and oppositional defiant disorder (ODD). METHODS: Trio-based whole-exome sequencing (WES) was performed in the proband and both parents. Variant classification was performed according to American College of Medical Genetics and Genomics (ACMG) guidelines, and the potential pathogenicity of the identified variant was further assessed through multiple in silico prediction algorithms and protein structural analyses. RESULTS: WES identified a homozygous variant in the LNX2 gene (NM_153371.4: c.1165G>A, p.Ala389Thr), classified as a variant of uncertain significance (VUS) and supported by multiple in silico predictions. LNX2 is expressed during brain development and encodes an E3 ubiquitin ligase involved in neuronal differentiation and synaptic function. The identified variant is located within the PDZ2 domain, a functionally relevant region involved in protein-protein interactions. Although the variant is reported in population databases (gnomAD ID: rs148429804), it has not been associated with any clinical phenotype, and its presence in the homozygous state has been reported only once, remaining extremely rare and lacking clinical annotation. Structural modelling predicted localized rearrangement of the hydrogen-bonding network within the PDZ2 domain without major conformational changes. Integrative transcriptomic, and single-cell analyses further supported the biological relevance of LNX2 in neurodevelopment, highlighting its preferential association with neuronal projection-cell networks, synaptic vesicle trafficking pathways, and neuron-specific regulatory programs. CONCLUSION: Although the identified LNX2 variant cannot be considered causative for the patient's phenotype and a definitive disease-gene relationship cannot be established based on a single individual, the complementary genetic, structural, and transcriptomic findings support the biological plausibility of LNX2 as a candidate gene for neurodevelopmental disorders. Additional independent patients and functional studies will be required to clarify its contribution to human disease.

Child

Synthetic community Hi-C benchmarking provides a baseline for virus-host inferences.

Microbiomes influence diverse ecosystems, and viruses increasingly appear to impose key constraints. While viromics has expanded genomic catalogs, host identification for these viruses remains challenging due to the limitations in scaling cultivation-based approaches and the uncertain reliability and relative low resolution of in silico predictions - particularly for understudied viral taxa. Towards this, Hi-C proximity ligation uses sequenced, cross-linked virus and host genomic fragments to infer virus-host linkages and has now been applied in at least ten studies. However, its accuracy remains unknown. Here we assess Hi-C performance in recovering virus-host interactions using synthetic communities (SynComs) composed of four marine bacterial strains and nine phages with known interactions and then apply optimized bioinformatic protocols to natural soil samples. In SynComs, standard Hi-C sample preparations and analyses showed poor normalized contact score performance (26% specificity, 100% sensitivity, incorrect matches up to class level) that could be dramatically improved by Z-score filtering (Z ≥ 0.5, 99% specificity), though at reduced sensitivity (62% down from 100%). Detection limits were established as reproducibility was poor below minimal phage abundances of 105 PFU/mL. Applying optimized bioinformatic protocols to natural soil samples, we compared virus-host linkages inferred from proximity-ligated Hi-C sequencing with predictions generated by in silico homology-based and machine learning-based bioinformatic approaches. Prior to Z-score thresholding, agreement was relatively high at the phylum to family levels (72%), but not at the genus (43%) or species (15%) levels. Z-score thresholding reduced sensitivity (only 34% of predictions were retained), with only modest improvements in congruence with bioinformatic methods (48% or 18% at genus or species levels, respectively). Regardless, this led to 79 genus-level-congruent virus-host linkages and 293 new ones revealed by Hi-C alone - i.e., providing many new virus-host interactions to explore in already well-studied climate-critical soils. Overall, these findings provide empirical benchmarks and methodological guidelines to improve the accuracy and reliability of Hi-C for virus-host linkage studies in complex microbial communities.

Genomics

Benchmarking with synthetic communities provides a baseline for virus-host inferences from Hi-C proximity linking.

Microbiomes influence diverse ecosystems, and viruses increasingly appear to impose key constraints. While viromics has expanded genomic catalogs, host identification for these viruses remains challenging due to the limitations in scaling cultivation-based approaches and the uncertain reliability and relative low resolution of in silico predictions - particularly for understudied viral taxa. Towards this, Hi-C proximity ligation uses sequenced, cross-linked virus and host genomic fragments to infer virus-host linkages and has now been applied in at least 10 studies. However, its accuracy remains unknown. Here we assess Hi-C performance in recovering virus-host interactions using synthetic communities (SynComs) composed of four marine bacterial strains and nine phages with known interactions and then apply optimized bioinformatic protocols to natural soil samples. In SynComs, standard Hi-C sample preparations and analyses showed poor normalized contact score performance (26% specificity, 100% sensitivity, incorrect matches up to class level) that could be dramatically improved by Z-score filtering (Z ≥ 0.5, 99% specificity), though at reduced sensitivity (62% down from 100%). Detection limits were established as reproducibility was poor below minimal phage abundances of 105 PFU/mL. Applying optimized bioinformatic protocols to natural soil samples, we compared virus-host linkages inferred from proximity-ligated Hi-C sequencing with predictions generated by in silico homology-based and machine learning-based bioinformatic approaches. Prior to Z-score thresholding, agreement was relatively high at the phylum to family levels (72%), but not at the genus (43%) or species (15%) levels. Z-score thresholding reduced sensitivity (only 34% of predictions were retained), with only modest improvements in congruence with bioinformatic methods (48% or 18% at genus or species levels, respectively). Regardless, this led to 79 genus-level-congruent virus-host linkages and 293 new ones revealed by Hi-C alone, i.e., providing many new virus-host interactions to explore in already well-studied climate-critical soils. Overall, these findings provide empirical benchmarks and methodological guidelines to improve the accuracy and reliability of Hi-C for virus-host linkage studies in complex microbial communities.

Benchmarking

Identification of Potential Therapeutic Agents for Type I Interferonopathy Using iPSC-Based Disease Modeling.

PURPOSE: Type I interferonopathy encompasses disorders marked by systemic inflammation and neurological involvement, arising from genetic mutations that result in the upregulation of type I IFN signaling through various mechanisms. Currently, therapeutic options are limited, and no standard therapy exists. This study aims to develop a strategy for identifying new therapeutic targets for type I interferonopathy using induced pluripotent stem cells (iPSCs). METHODS: The IFIH1 R779H variant was introduced into iPSCs through genome editing. RNA sequencing of iPSC-derived dendritic cells (DCs) was performed, and differentially expressed genes (DEGs) were identified. IFN-α secretion, reactive oxygen species (ROS), and mitochondrial oxygen consumption rate (OCR) were analyzed in iPSC-derived DCs. An in silico prediction of compounds binding to the OAS-like domain was conducted. Candidate compounds were evaluated for their ability to inhibit IFN secretion from IFIH1 R779H-mutated iPSC-derived DCs. RESULTS: Transcriptome analysis indicated upregulation of the IFN-related and metabolic pathways. IFIH1 R779H-mutated iPSC-derived DCs exhibited increased OCR and ROS generation, and blocking mitochondrial metabolism significantly reduced excessive IFN-α secretion. Among the DEGs, PML was upregulated, and targeting this gene with arsenic trioxide (ATO), a PML antagonist, suppressed IFN-α secretion from IFIH1 R779H-mutated iPSC-derived DCs. Additionally, bisantrene, phthalylsulfathiazole and ganaplacide were predicted to bind to the RNA binding groove of OAS-like domain of human OASL in silico, effectively inhibiting IFN-α secretion from IFIH1 R779H-mutated DCs. CONCLUSION: Our iPSC-based disease modeling and drug investigation approach provides a robust platform for validating the efficacy and toxicity of candidate therapeutic agents for rare and intractable human diseases such as type I interferonopathy.

Humans

MNV-aware molecular characterization of a rare homozygous TTPA complex allele in ataxia with vitamin E deficiency.

Ataxia with vitamin E deficiency (AVED) is a rare autosomal-recessive neurological disorder caused by biallelic pathogenic variants in TTPA. Early vitamin E supplementation may prevent or limit irreversible neurological damage, but diagnosis is often delayed. Multi-nucleotide variants (MNVs) in TTPA have rarely been described and may be misinterpreted when adjacent substitutions are evaluated independently. We investigated a 34-year-old woman with childhood-onset progressive ataxia using clinical, biochemical, neuroimaging, and electrophysiological assessments. Serum vitamin E levels were measured longitudinally during supplementation. Whole-exome sequencing, read-level inspection, and Sanger sequencing were used to identify and confirm a homozygous TTPA complex allele, NM_000370.3:c. 296G > A;299 A > C, predicted to result in NP_000361.1:p. Gly99_Tyr100delinsAspSer, and to assess familial segregation. Population-database review, in silico prediction, and exploratory structure-based analysis were performed to evaluate its potential clinical relevance. The patient had markedly reduced baseline serum vitamin E levels of 0.8 µg/mL, which increased to 7.5 µg/mL after 12 months of supplementation. This biochemical correction was temporally accompanied by qualitatively observed improvements in gait stability, coordination, speech, and fine motor performance. Read-level analysis supported the presence of both substitutions on the same allele, and Sanger sequencing confirmed the homozygous complex allele in the patient and heterozygous carrier status in both parents. The affected residues are conserved and located within the CRAL-TRIO domain of α-tocopherol transfer protein. Exploratory structure-based analysis suggested altered local residue interactions; however, no functional assay was performed, and effects on protein stability, α-tocopherol binding, or transfer could not be established. This report expands the molecular spectrum of AVED by describing a homozygous TTPA complex allele and highlights the importance of MNV-aware interpretation of closely spaced substitutions. Vitamin E supplementation resulted in biochemical correction and was accompanied by possible partial clinical improvement despite initiation in adulthood. Functional studies are required to determine the precise effect of this allele on α-tocopherol transfer protein function.

Humans

Carafe enables high quality in silico spectral library generation for data-independent acquisition proteomics.

Data-independent acquisition (DIA)-based mass spectrometry is becoming an increasingly popular mass spectrometry acquisition strategy for carrying out quantitative proteomics experiments. Most of the popular DIA search engines make use of in silico generated spectral libraries. However, the generation of high-quality spectral libraries for DIA data analysis remains a challenge, particularly because most such libraries are generated directly from data-dependent acquisition (DDA) data or are from in silico prediction using models trained on DDA data. In this study, we developed Carafe, a tool that generates high-quality experiment-specific in silico spectral libraries by training deep learning models directly on DIA data. We demonstrate the performance of Carafe on a wide range of DIA datasets, where we observe improved fragment ion intensity prediction and peptide detection relative to existing pretrained DDA models. To make Carafe more accessible to the community, we have integrated Carafe into the widely used Skyline tool.

Journal Article

Identification of Rare Noncoding Variants in Familial Nonmedullary Thyroid Carcinoma.

BACKGROUND: Familial nonmedullary thyroid carcinoma (FNMTC) occurs when three or more family members are affected by usually papillary thyroid carcinoma (PTC), the most common form of NMTC. While the heritability to NMTC is among the highest of all cancers, the genetic determinants among NMTC families are not well understood. Here, we aim to understand the contribution of rare noncoding germline variants in the etiology of FNMTC. METHODS: We previously reported whole-genome sequencing (WGS) and linkage analysis in 17 PTC families and reported on 41 protein-coding variants in 40 genes that cosegregated with PTC in 11 of the families. Herein, we further leveraged our WGS data to include noncoding variants in our analysis for all 17 families. We hypothesized that most of the pathogenic noncoding variants would be located in theoretical or empirically determined regulatory regions that demonstrate at a minimum, basal thyroid expression, a positive family linkage score, and co-segregation among PTC-affected individuals. To test this hypothesis, we adopted a unique filtering strategy to identify variants that occurred in known DNA elements and transcription factor binding sites, near regions known to impact on gene expression or splicing in thyroid tissue, and/or in characterized thyroid enhancers. We annotated variants using two analyses (ENCODE and transcription factor binding site) within the BasePlayer software. We separately analyzed (1) expression quantitative trait loci, (2) splicing quantitative trait loci, and (3) thyroid enhancers. We then ranked variants according to predicted pathogenicity and performed Sanger sequencing in all individuals of each family. RESULTS: In total, 121 variants were selected based on in-silico prediction and our custom ranking analysis in each pedigree. Of these, 56 variants showed cosegregation among all PTC-affected individuals and were absent from unaffected individuals. This included candidate variants from five of the six PTC families for whom no protein-coding variants were previously found. CONCLUSION: Our data suggest that noncoding variants are important in the etiology of FNMTC and provide a framework for identifying noncoding germline variants using a novel approach. Further studies are needed to functionally characterize these variants to better understand the molecular mechanism of their pathogenicity.

Humans

Phenotypic pleiotropy of missense variants in human B cell confinement receptor P2RY8.

Missense variants can have pleiotropic effects on protein function, and predicting these effects can be difficult. We performed near-saturation deep mutational scanning of P2RY8, a G protein-coupled receptor that promotes germinal center B cell confinement. We assayed the effect of each variant on surface expression, migration, and proliferation. We delineated variants that affected both expression and function, affected function independently of expression, and discrepantly affected migration and proliferation. We also used cryo-electron microscopy to determine the structure of activated, ligand-bound P2RY8, providing structural insights into the effects of variants on ligand binding and signal transmission. We applied the deep mutational scanning results to both improve computational variant effect predictions and to characterize the phenotype of germline variants and lymphoma-associated variants. Together, our results demonstrate the power of integrating deep mutational scanning, structure determination, and in silico prediction to advance the understanding of a receptor important in human health.

Humans

Scalable approaches for functional analyses of whole-genome sequencing non-coding variants.

Non-coding genetic variants outside of protein-coding genome regions play an important role in genetic and epigenetic regulation. It has become increasingly important to understand their roles, as non-coding variants often make up the majority of top findings of genome-wide association studies (GWAS). In addition, the growing popularity of disease-specific whole-genome sequencing (WGS) efforts expands the library of and offers unique opportunities for investigating both common and rare non-coding variants, which are typically not detected in more limited GWAS approaches. However, the sheer size and breadth of WGS data introduce additional challenges to predicting functional impacts in terms of data analysis and interpretation. This review focuses on the recent approaches developed for efficient, at-scale annotation and prioritization of non-coding variants uncovered in WGS analyses. In particular, we review the latest scalable annotation tools, databases and functional genomic resources for interpreting the variant findings from WGS based on both experimental data and in silico predictive annotations. We also review machine learning-based predictive models for variant scoring and prioritization. We conclude with a discussion of future research directions which will enhance the data and tools necessary for the effective functional analyses of variants identified by WGS to improve our understanding of disease etiology.

Genome-Wide Association Study

The NmpRSTU multi-component signaling system of Myxococcus xanthus regulates expression of an oxygen utilization regulon.

UNLABELLED: Myxococcus xanthus has numerous two-component signaling systems (TCSs), many of which regulate the complex social behaviors of this soil bacterium. A subset of TCSs consists of NtrC-like response regulators (RRs) and their cognate histidine sensor kinases (SKs). We have previously demonstrated that a multi-component, phosphorelay TCS named NmpRSTU plays a role in M. xanthus social motility. NmpRSTU was discovered through a screen that identified mutations in nmp genes that restored Type-IV pili-dependent motility to a nonmotile strain. The Nmp pathway begins with the SK NmpU, which is predicted to be active in the presence of oxygen. NmpU phosphorylates another SK, NmpS, a hybrid kinase containing an RR domain and a HisKA-CA domain. These two kinases work in a reciprocal fashion: when NmpU is active, NmpS is inactive, and vice versa. Finally, the phosphorelay culminates in NmpS phosphorylating the NtrC-like RR NmpR. To better understand the role of NmpRSTU in M. xanthus physiology, we determined the NmpR regulon by combining in silico predictions of the NmpR consensus binding sequence with in vitro electromobility shift assays (EMSAs) and in vivo transcriptional reporters. We identified several NmpR-dependent, upregulated genes likely to be important in oxygen utilization. Additionally, we demonstrate NmpRSTU plays a role in fruiting body development, suggesting a role for oxygen sensing in this behavior. We propose that NmpRSTU senses oxygen-limiting conditions, and NmpR upregulates genes associated with optimal utilization of that oxygen. This may be necessary for M. xanthus physiology and behaviors in the highly dynamic soil where oxygen concentrations vary dramatically. IMPORTANCE: Bacteria use two-component signaling systems (TCSs) to respond to a multitude of environmental signals and subsequently regulate complex cellular physiology and behaviors. Myxococcus xanthus is a ubiquitous soil bacterium that encodes numerous two-component systems to respond to the conditions of its soil environment and coordinate multicellular behaviors such as coordinated motility, microbial predation, fruiting body development, and sporulation. To better understand how this bacterium uses a two-component system that has been linked to the sensing of oxygen concentrations, NmpRSTU, we determined the gene regulatory network of this system. We identified several genes regulated by NmpR that are likely important in oxygen utilization and for the M. xanthus response to varied oxygen concentrations in the dynamic soil environment.

Myxococcus xanthus

A Simplified Workflow for the Prediction of Putative Viral Reads Using NIPT Data.

OBJECTIVE: Non-invasive prenatal testing (NIPT) identifies fetal chromosomal abnormalities by sequencing cell-free fetal DNA (cffDNA). Recent studies suggest the prediction of viral sequences from NIPT data, but current methods lack cost-effectiveness for routine use. This study develops a straightforward workflow to investigate potential viral signatures in pregnant women using NIPT data from 888 Iranian participants. METHOD: Two bioinformatic workflows were compared for predicting viral reads: the traditional method involved mapping reads to the human genome, followed by mapping unmapped reads to viral references, and a direct mapping approach to viral genomes, as proposed in this research. RESULTS: While maintaining reproducibility comparable to the conventional method, the proposed workflow minimizes computational complexity and time usage for data processing. Ultimately, this analysis suggested viral DNA in 24.2% of samples, encompassing 29 distinct species, implying the diversity of the maternal virome. CONCLUSION: This study presents a computationally efficient workflow for the in silico prediction of viral-like sequences from routine NIPT data. Further experimental validation is essential to verify the presence, viability, or clinical relevance of these sequences.

Humans

Exome sequencing revealed a novel homozygous variant in TRMT61 A in a multiplex family with atypical Cornelia de Lange Syndrome from Rwanda.

BACKGROUND: In 30% of patients who exhibit the clinical profile of Cornelia de Lange Syndrome (CdLS), the genetic cause remains undetermined. This proportion tends to be higher in low-resource settings including Africa. We performed a molecular characterization of CdLS in a multiplex Rwandan family. METHODS: After a clinical evaluation of two affected siblings, DNA isolated from peripheral whole blood of the affected patients and their parents underwent Exome Sequencing (ES). Sanger sequencing validated the variant segregating with CdLS. In silico predictive tools, protein modelling, and cell-based experiments using HEK293T cells were used to investigate the pathogenicity of the variant found. RESULTS: We identified a family with two parents and their two offspring (male and female), who were referred for hearing impairment. The 17-year-old female presented bilateral profound hearing impairment with moderate hypertelorism, progressive visual impairment, and secondary amenorrhea. The 14-year-old male displayed intellectual disability and a bilateral profound hearing impairment with no noticeable facial dysmorphism. Following exome sequencing (ES) of DNA samples obtained from the four family members, we found that the siblings harbored a novel likely pathogenic homozygous missense variant in the TRMT61 A gene [NM_152307.3:c.665C > T p.(Ala222Val)] inherited from both heterozygous parents. In silico analysis suggested that the variant substitutes a highly conserved amino acid, and 2-D structure modelling revealed a significant decrease in the stability of the protein. Cell-based experiment in HEK293T showed that the variant significantly affected the TRMT61 A protein localization which is thought to impact the mitochondrial and cytosolic functions. CONCLUSION: We reported a novel biallelic variant in TRMT61 A, [NM_152307.3:c.665C > T p.(Ala222Val)], which is associated with autosomal recessive atypical CdLS in a multiplex Rwandan family, the first report from Africa, and the second globally. The study emphasizes the need to expand the availability of ES for molecular characterization of rare diseases for the understudied genetically diverse population of Africa.

Humans

[Genetic and functional characterization of a novel KIT splicing variant in a Chinese three-generation pedigree with piebaldism].

OBJECTIVES: To investigate the genetic etiology of a three-generation pedigree affected with piebaldism. METHODS: Next-generation sequencing and Sanger sequencing were employed to detect and verify gene variants. Bioinformatics tools were used to predict the effects of candidate variants on splicing and protein function. RT-PCR and Sanger sequencing were further performed to validate the impact of the variant on RNA splicing, and homology modeling was applied to predict its effect on the three-dimensional structure of the KIT protein. The pathogenicity of the variant was then classified according to the guidelines of the American College of Medical Genetics and Genomics (ACMG) and the UK Association for Clinical Genomic Science (ACGS). RESULTS: A heterozygous insertion variant near the splice site, c.1990+8_1990+9insTGCACCATTGGAGGTAAA, was identified in the KIT gene in the proband and was found to co-segregate with the phenotype within the family. RT-PCR and cDNA sequencing revealed that this variant led to aberrant splicing during transcription, resulting in a 21 bp in-frame insertion in the mRNA, which encodes an extra 7 amino acids within the tyrosine kinase domain and may thus affect protein function. In silico predictions, together with the experimental findings, supported classification of this variant as likely pathogenic according to relevant variant interpretation guidelines. CONCLUSIONS: The heterozygous splice-site insertion variant KIT:c.1990+8_1990+9insTGCACCATTGGAGGTAAA is the genetic cause of piebaldism in this pedigree.

Genetics diagnosis