Characterization of zinc finger protein 536, a neuroendocrine regulator, using pan-cancer analysis.

BACKGROUND: Previous studies suggested that zinc finger protein 536 (ZNF536) was abundant in the central brain and regulated neuronal differentiation. However, the role of ZNF536 in cancer has remained unclear. METHODS: ZNF536 mutation, copy number alteration, DNA methylation, and RNA expression were explored using public portals. Data from The Cancer Genome Atlas (TCGA) were utilized to analyze pathways and tumor microenvironment (TME), with a focus on prognosis in both TCGA and immunotherapy pan-cancer cohorts. Methylated ZNF536 from small cell lung cancer (SCLC) cell lines were utilized to train with probes for conducting enrichment analysis. Single-cell RNA profile demonstrated the sublocalization and co-expression of ZNF536, and validated its targets by qPCR. RESULTS: Genetic alterations in ZNF536 were found to be high-frequency and a single sample could harbor different variations. ZNF536 at chromosome 19q12 exerted a bypass effect on CCNE1, supported by CRISPR data. For lung cancer, ZNF536 mutation was associated with longer survival in primary lung adenocarcinoma (LUAD), but its prognosis was poor in metastatic LUAD and SCLC. Importantly, ZNF536 mutation and amplification had opposite prognoses in Stand Up To Cancer-Mark Foundation (SU2C-MARK) LUAD cohort. ZNF536 mutation altered the patterns of genomic alterations in tumors, and had distinct impacts on the signaling pathways and TME compared to ZNF536 amplification. Additionally, ZNF536 expression was predominantly in endocrine tumors and brain tissues. High-dimensional analysis supported this finding and further revealed regulators of ZNF536. Considering that the methylation of ZNF536 was involved in the synaptic pathway associated with neuroendocrine neoplasms, demonstrating both diagnostic and prognostic value. Moreover, we experimentally verified ZNF536 upregulated neuroendocrine markers. CONCLUSIONS: Our results showed that ZNF536 alterations in cancer, including variations in copy number, mutation, and methylation. We proved the involvement of ZNF536 in neuroendocrine regulation, and identified highly altered ZNF536 as a potential biomarker for immunotherapy.

Mutation of SIVA, a candidate metastasis gene identified from clonally related bilateral breast cancers, promotes breast cancer cell spread in vitro and in vivo.

Metastasis is the most dreaded outcome after a breast cancer diagnosis, and little is known regarding what triggers or promotes breast cancer to spread distally, or how to prevent or eradicate metastasis effectively. Bilateral breast cancers are an uncommon form of breast cancers. In our study, a percentage of bilateral breast cancers were clonally related based on copy number variation profiling. Whole exome sequencing and comparative sequence analysis revealed that a limited number of somatic mutations were acquired in this "breast-to-breast" metastasis that might promote breast cancer distant spread. One somatic mutation acquired was SIVA-D160N that displayed pro-metastatic phenotypes in vivo and in vitro. Over-expression of SIVA-D160N promoted migration and invasion of human MB-MDA-231 breast cancer cells in vitro, consistent with a dominant negative interfering function. When introduced via tail vein injection, 231 cells over-expressing SIVA-D160N displayed enhanced distant spread on IVIS imaging. Over-expression of SIVA-D160N promoted invasion and anchorage independent growth of mouse 4T1 breast cancer cells in vitro. When introduced orthotopically via mammary fat pad injection in syngeneic Balb/c mice, over-expression of SIVA-D160N in 4T1 cells increased orthotopically implanted mammary gland tumor growth as well as liver metastasis. Clonally related bilateral breast cancers represented a novel system to investigate metastasis and revealed a role of SIVA-D160N in breast cancer metastasis. Further characterization and understanding of SIVA function, and that of its interacting proteins, may elucidate mechanisms of breast cancer metastasis, providing clinically useful biomarkers and therapeutic targets.

Prediction of anticancer drug sensitivity using an interpretable model guided by deep learning.

BACKGROUND: The prediction of drug sensitivity plays a crucial role in improving the therapeutic effect of drugs. However, testing the effectiveness of drugs is challenging due to the complex mechanism of drug reactions and the lack of interpretability in most machine learning and deep learning methods. Therefore, it is imperative to establish an interpretable model that receives various cell line and drug feature data to learn drug response mechanisms and achieve stable predictions between available datasets. RESULTS: This study proposes a new and interpretable deep learning model, DrugGene, which integrates gene expression, gene mutation, gene copy number variation of cancer cells, and chemical characteristics of anticancer drugs to predict their sensitivity. This model comprises two different branches of neural networks, where the first involves a hierarchical structure of biological subsystems that uses the biological processes of human cells to form a visual neural network (VNN) and an interpretable deep neural network for human cancer cells. DrugGene receives genotype input from the cell line and detects changes in the subsystem states. We also employ a traditional artificial neural network (ANN) to capture the chemical structural features of drugs. DrugGene generates final drug response predictions by combining VNN and ANN and integrating their outputs into a fully connected layer. The experimental results using drug sensitivity data extracted from the Cancer Drug Sensitivity Genome Database and the Cancer Treatment Response Portal v2 reveal that the proposed model is better than existing prediction methods. Therefore, our model achieves higher accuracy, learns the reaction mechanisms between anticancer drugs and cell lines from various features, and interprets the model's predicted results. CONCLUSIONS: Our method utilizes biological pathways to construct neural networks, which can use genotypes to monitor changes in the state of network subsystems, thereby interpreting the prediction results in the model and achieving satisfactory prediction accuracy. This will help explore new directions in cancer treatment. More available code resources can be downloaded for free from GitHub ( https://github.com/pangweixiong/DrugGene ).

Investigation of ENO2 as a promising novel marker for the progression of colorectal cancer with microsatellite instability-high.

BACKGROUND: Microsatellite instability-high (MSI-H) has emerged as a significant biological characteristic of colorectal cancer (CRC). Studies reported that MSI-H CRC generally had a better prognosis than microsatellite stable (MSS)/microsatellite instability-low (MSI-L) CRC, but some MSI-H CRC patients exhibited distinctive molecular characteristics and experienced a less favorable prognosis. In this study, our objective was to explore the metabolic transcript-related subtypes of MSI-H CRC and identify a biomarker for predicting survival outcomes. METHODS: Single-cell RNA sequencing (scRNA-seq) data of MSI-H CRC patients were obtained from the Gene Expression Omnibus (GEO) database. By utilizing the copy number variation (CNV) score, a malignant cell subpopulation was identified at the single-cell level. The metabolic landscape of various cell types was examined using metabolic pathway gene sets. Subsequently, functional experiments were conducted to investigate the biological significance of the hub gene in MSI-H CRC. Finally, the predictive potential of the hub gene was assessed using a nomogram. RESULTS: This study revealed a malignant tumor cell subpopulation from the single-cell RNA sequencing (scRNA-seq) data. MSI-H CRC was clustered into two subtypes based on the expression profiles of metabolism-related genes, and ENO2 was identified as a hub gene. Functional experiments with ENO2 knockdown and overexpression demonstrated its role in promoting CRC cell migration, invasion, glycolysis, and epithelial-mesenchymal transition (EMT) in vitro. High expression of ENO2 in MSI-H CRC patients was associated with worse clinical outcomes, including increased tumor invasion depth (p = 0.007) and greater likelihood of perineural invasion (p = 0.015). Furthermore, the nomogram and calibration curves based on ENO2 showed potential prognosis predictive performance. CONCLUSION: Our findings suggest that ENO2 serves as a novel prognostic biomarker and is associated with the progression of MSI-H CRC.

Three concurrent mechanisms generate gene copy number variation and transient antibiotic heteroresistance.

Heteroresistance is a medically relevant phenotype where small antibiotic-resistant subpopulations coexist within predominantly susceptible bacterial populations. Heteroresistance reduces treatment efficacy across diverse bacterial species and antibiotic classes, yet its genetic and physiological mechanisms remain poorly understood. Here, we investigated a multi-resistant Klebsiella pneumoniae isolate and identified three primary drivers of gene dosage-dependent heteroresistance for several antibiotic classes: tandem amplification, increased plasmid copy number, and transposition of resistance genes onto cryptic plasmids. All three mechanisms imposed fitness costs and were genetically unstable, leading to fast reversion to susceptibility in the absence of antibiotics. We used a mouse gut colonization model to show that heteroresistance due to elevated resistance-gene dosage can result in antibiotic treatment failures. Importantly, we observed that the three mechanisms are prevalent among Escherichia coli bloodstream isolates. Our findings underscore the necessity for treatment strategies that address the complex interplay between plasmids, resistance cassettes, and transposons in bacterial populations.

Copy number variation and elevated genetic diversity at immune trait loci in Atlantic and Pacific herring.

BACKGROUND: Genome-wide comparisons of populations are widely used to explore the patterns of nucleotide diversity and sequence divergence to provide knowledge on how natural selection and genetic drift affect the genome. In this study we have compared whole-genome sequencing data from Atlantic and Pacific herring, two sister species that diverged about 2 million years ago, to explore the pattern of genetic differentiation between the two species. RESULTS: The genome comparison of the two species revealed high genome-wide differentiation but with islands of remarkably low genetic differentiation, as measured by an FST analysis. However, the low FST observed in these islands is not caused by low interspecies sequence divergence (dxy) but rather by exceptionally high estimated intraspecies nucleotide diversity (π). These regions of low differentiation and elevated nucleotide diversity, termed high-diversity regions in this study, are not enriched for repeats but are highly enriched for immune-related genes. This enrichment includes genes from both the adaptive immune system, such as immunoglobulin, T-cell receptor and major histocompatibility complex genes, as well as a substantial number of genes with a role in the innate immune system, e.g. novel immune-type receptor, tripartite motif and tumor necrosis factor receptor genes. Analysis of long-read based assemblies from two Atlantic herring individuals revealed extensive copy number variation in these genomic regions, indicating that the elevated intraspecies nucleotide diversities were partially due to the cross-mapping of short reads. CONCLUSIONS: This study demonstrates that copy number variation is a characteristic feature of immune trait loci in herring. Another important implication is that these loci are blind spots in classical genome-wide screens for genetic differentiation using short-read data, not only in herring, likely also in other species harboring qualitatively similar variation at immune trait loci. These loci stood out in this study because of the relatively high genome-wide baseline for FST values between Atlantic and Pacific herring.

Development, validation and application of single molecule molecular inversion probe based novel integrated genetic screening method for 29 common lysosomal storage disorders in India.

BACKGROUND: Current clinical diagnosis pathway for lysosomal storage disorders (LSDs) involves sequential biochemical enzymatic tests followed by DNA sequencing, which is iterative, has low diagnostic yield and is costly due to overlapping clinical presentations. Here, we describe a novel low-cost and high-throughput sequencing assay using single-molecule molecular inversion probes (smMIPs) to screen for causative single nucleotide variants (SNVs) and copy number variants (CNVs) in genes associated with 29 common LSDs in India. RESULTS: 903 smMIPs were designed to target exon and exon-intron boundaries of targeted genes (n = 23; 53.7 kb of the human genome) and were equimolarly pooled to create a sequencing library. After extensive validation in a cohort of 50 patients, we screened 300 patients with either biochemical diagnosis (n = 187) or clinical suspicion (n = 113) of LSDs. A diagnostic yield of 83.4% was observed in patients with prior biochemical diagnosis of LSD. Furthermore, diagnostic yield of 73.9% (n = 54/73) was observed in patients with high clinical suspicion of LSD in contrast with 2.4% (n = 1/40) in patients with low clinical suspicion of LSD. In addition to detecting SNVs, the assay could detect single and multi-exon copy number variants with high confidence. Critically, Niemann-Pick disease type C and neuronal ceroid lipofuscinosis-6 diseases for which biochemical testing is unavailable, could be diagnosed using our assay. Lastly, we observed a non-inferior performance of the assay in DNA extracted from dried blood spots in comparison with whole blood. CONCLUSION: We developed a flexible and scalable assay to reliably detect genetic causes of 29 common LSDs in India. The assay consolidates the detection of multiple variant types in multiple sample types while having improved diagnostic yield at same or lower cost compared to current clinical paradigm.

PRKDC-Mediated NHEJ May Play a Crucial Role in Aneuploidy of Chromosome 8-Driven Progression of Ovarian Cancer.

High malignancy is a prominent characteristic of epithelial ovarian cancer (EOC), emphasizing the necessity for further elucidation of the potential mechanisms underlying cancer progression. Aneuploidy and copy number variation (CNV) partially contribute to the heightened malignancy observed in EOC; however, the precise features of aneuploidy and their underlying molecular patterns, as well as the relationship between CNV and aneuploidy in EOC, remain unclear. In this study, we employed single-cell sequencing data along with The Cancer Genome Atlas (TCGA) to investigate aneuploidy and CNV in EOC. The technique of fluorescence in situ hybridization (FISH) was employed using specific probes. The copy number variation within the genomic region of chromosome 8 (42754568-47889815) was assessed and utilized as a representative measure for the ploidy status of individual cells in chromosome 8. Differential expression analysis was performed between different subgroups based on chromosome 8 ploidy. Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), protein-protein interaction (PPI), and hub-gene analyses were subsequently utilized to identify crucial genes involved. By classifying enriched tumor cells into distinct subtypes based on chromosome 8 ploidy combined with TCGA data integration, we identified key genes driving chromosome 8 aneuploidy in EOC, revealing that PRKDC gene involvement through the mediated non-homologous end-joining pathway may play a pivotal role in disease progression. Further validation through analysis of the GEO and TCGA database and survival assessment, considering both mRNA expression levels and CNV status of PRKDC, has confirmed its involvement in the progression of EOC. Further functional analysis revealed an upregulation of PRKDC in both ovarian EOC cells and tissues, with its expression showing a significant correlation with the extent of copy number variation (CNV) on chromosome 8. Taken together, CNV amplification and aneuploidy of chromosome 8 are important characteristics of EOC. PRKDC and the mediated NHEJ pathway may play a crucial role in driving aneuploidy on chromosome 8 during the progression of EOC.

The genomic landscape of Vk*MYC myeloma highlights shared pathways of transformation between mice and humans.

Multiple myeloma (MM) is a heterogeneous disease characterized by frequent MYC translocations. Sporadic MYC activation in the germinal center of genetically engineered Vk*MYC mice is sufficient to induce plasma cell tumors in which a variety of secondary mutations are spontaneously acquired and selected over time. Analysis of 119 Vk*MYC myeloma reveals recurrent copy number alterations, structural variations, chromothripsis, driver mutations, apolipoprotein B mRNA-editing enzyme, catalytic polypeptide (APOBEC) mutational activity, and a progressive decrease in immunoglobulin transcription that inversely correlates with proliferation. Moreover, we identify frequent insertional mutagenesis by endogenous retro-elements as a murine specific mechanism to activate NF-kB and IL6 signaling pathways shared with human MM. Despite the increased genomic complexity associated with progression, advanced tumors remain dependent on MYC. In summary, here we credential the Vk*MYC mouse as a unique resource to explore MM genomic evolution and describe a fully annotated collection of diverse and immortalized murine MM tumors.

Genomic landscape and distinct molecular subtypes of primary testicular lymphoma.

Primary testicular lymphoma (PTL) is a rare lymphoma predominantly occurring in the elderly male population. It is characterized by a limited response to treatment and a heightened tendency towards relapse. Histologically, approximately 90% of PTL cases are classified as diffuse large B-cell lymphomas (DLBCL). Genetic features of PTL were delineated in a limited scope within several independent studies. Some of the articles which analyzed the genetic characterization of DLBCL have incorporated PTL samples, but these have been constrained by small sample sizes. In addition, there have been an absence of independent molecular typing studies of PTL. This report summarizes the common mutational features, copy number variations (CNVs) and molecular typing of PTL patients, based on whole-exome sequencing (WES) conducted on a cohort of 25 PTL patients. Among them, HLA, CDKN2A and MYD88 had a high mutation frequency. In addition, we found two core mutational characteristics in PTL including mutation in genes linked to genomic instability (TP53 and CDKN2A) and mutation in immune-related genes (HLA, MYD88, CD79B). We performed molecular typing of 25 PTL patients into C1 subtype with predominantly TP53 mutations and C2 subtype with predominantly HLA mutations. Notably, mutations in the TP53 gene predicted a poor outcome in most types of lymphomas. However, the C1 subtype, dominated by TP53 mutations, had a better prognosis compared to the C2 subtype in PTL. C2 subtype exhibited a worse prognosis, aligning with our finding that the mechanism of immune escape in PTL was primarily the deletions of HLA rather than PD-L1/PD-L2 alterations, a contrast to other DLBCLs. Moreover, we calculated the tumor mutation burden (TMB) and identified that TMB can predict prognosis and recurrence rate in PTL. Our study underscores the significance of molecular typing in PTL based on mutational characteristics, which plays a crucial role in prognostication and guiding therapeutic strategies for patients.

Lung cancer clustering by identification of similarities and discrepancies of DNA copy numbers using maximal information coefficient.

Lung cancer is the second most diagnosed cancer and the first cause of cancer related death for men and women in the United States. Early detection is essential as patient survival is not optimal and recurrence rate is high. Copy number (CN) changes in cancer populations have been broadly investigated to identify CN gains and deletions associated with the cancer. In this research, the similarities between cancer and paired peripheral blood samples are identified using maximal information coefficient (MIC) and the spatial locations with substantially high MIC scores in each chromosome are used for clustering analysis. The results showed that a sizable reduction of feature set can be obtained using only a subset of locations with high MIC values. The clustering performance was evaluated using both true rate and normalized mutual information (NMI). Clustering results using the reduced feature set outperformed the performance of clustering using entire feature set in several chromosomes that are highly associated with lung cancer with several identified oncogenes.

PanDepth, an ultrafast and efficient genomic tool for coverage calculation.

Coverage quantification is required in many sequencing datasets within the field of genomics research. However, most existing tools fail to provide comprehensive statistical results and exhibit limited performance gains from multithreading. Here, we present PanDepth, an ultra-fast and efficient tool for calculating coverage and depth from sequencing alignments. PanDepth outperforms other tools in computation time and memory efficiency for both BAM and CRAM-format alignment files from sequencing data, regardless of read length. It employs chromosome parallel computation and optimized data structures, resulting in ultrafast computation speeds and memory efficiency. It accepts sorted or unsorted BAM and CRAM-format alignment files as well as GTF, GFF and BED-formatted interval files or a specific window size. When provided with a reference genome sequence and the option to enable GC content calculation, PanDepth includes GC content statistics, enhancing the accuracy and reliability of copy number variation analysis. Overall, PanDepth is a powerful tool that accelerates scientific discovery in genomics research.

Multimodal analysis of cfDNA methylomes for early detecting esophageal squamous cell carcinoma and precancerous lesions.

Detecting early-stage esophageal squamous cell carcinoma (ESCC) and precancerous lesions is critical for improving survival. Here, we conduct whole-genome bisulfite sequencing (WGBS) on 460 cfDNA samples from patients with non-metastatic ESCC or precancerous lesions and matched healthy controls. We develop an expanded multimodal analysis (EMMA) framework to simultaneously identify cfDNA methylation, copy number variants (CNVs), and fragmentation markers in cfDNA WGBS data. cfDNA methylation markers are the earliest and most sensitive, detectable in 70% of ESCCs and 50% of precancerous lesions, and associated with molecular subtypes and tumor microenvironments. CNVs and fragmentation features show high specificity but are linked to late-stage disease. EMMA significantly improves detection rates, increasing AUCs from 0.90 to 0.99, and detects 87% of ESCCs and 62% of precancerous lesions with >95% specificity in validation cohorts. Our findings demonstrate the potential of multimodal analysis of cfDNA methylome for early detection and monitoring of molecular characteristics in ESCC.

A human neural crest model reveals the developmental impact of neuroblastoma-associated chromosomal aberrations.

Early childhood tumours arise from transformed embryonic cells, which often carry large copy number alterations (CNA). However, it remains unclear how CNAs contribute to embryonic tumourigenesis due to a lack of suitable models. Here we employ female human embryonic stem cell (hESC) differentiation and single-cell transcriptome and epigenome analysis to assess the effects of chromosome 17q/1q gains, which are prevalent in the embryonal tumour neuroblastoma (NB). We show that CNAs impair the specification of trunk neural crest (NC) cells and their sympathoadrenal derivatives, the putative cells-of-origin of NB. This effect is exacerbated upon overexpression of MYCN, whose amplification co-occurs with CNAs in NB. Moreover, CNAs potentiate the pro-tumourigenic effects of MYCN and mutant NC cells resemble NB cells in tumours. These changes correlate with a stepwise aberration of developmental transcription factor networks. Together, our results sketch a mechanistic framework for the CNA-driven initiation of embryonal tumours.

Prenatal diagnosis of a trisomy 7 mosaic case: CMA, CNV-seq, karyotyping, interphase FISH, and MS-MLPA, which technique to choose?

OBJECTIVE: This study aims to perform a prenatal genetic diagnosis of a high-risk fetus with trisomy 7 identified by noninvasive prenatal testing (NIPT) and to evaluate the efficacy of different genetic testing techniques for prenatal diagnosis of trisomy mosaicism. METHODS: For prenatal diagnosis of a pregnant woman with a high risk of trisomy 7 suggested by NIPT, karyotyping and chromosomal microarray analysis (CMA) were performed on an amniotic fluid sample. Low-depth whole-genome copy number variation sequencing (CNV-seq) and fluorescence in situ hybridization (FISH) were used to clarify the results further. In addition, methylation-specific multiplex ligation-dependent probe amplification (MS-MLPA) was performed to analyze the possibility of uniparental disomy(UPD). RESULTS: Amniotic fluid karyotype analysis revealed a 46, XX result. Approximately 20% mosaic trisomy 7 was detected according to the CMA result. About 16% and 4% of mosaicism was detected by CNV-seq and FISH, respectively. MS-MLPA showed no methylation abnormalities. The fetal ultrasound did not show any detectable abnormalities except for mild intrauterine growth retardation seen at 39 weeks of gestation. After receiving genetic counseling, the expectant mother decided to continue the pregnancy, and follow-up within three months of delivery was normal. CONCLUSION: In high-risk NIPT diagnosis, a combination of cytogenetic and molecular genetic techniques proves fruitful in detecting low-level mosaicism. Furthermore, the exclusion of UPD on chromosome 7 remains crucial when NIPT indicates a positive prenatal diagnosis of trisomy 7.

Mediation of mitochondrial DNA copy number and oxidative stress in fluoride-related bone mineral density alteration in Chinese farmers.

Excessive fluoride can adversely affect bone mineral density (BMD). Oxidative stress and mitochondrial dysfunction are crucial mechanisms of health damage induced by fluoride. Here, a cross-sectional survey involving 907 Chinese farmers (aged 18-60) was carried out in Tongxu County in 2017, aiming to investigate the significance of mitochondrial DNA copy number (mtDNAcn) and oxidative stress in fluoride-related BMD change. Concentrations of urinary fluoride (UF), serum oxidative stress biomarkers, including total antioxidant capacity (T-AOC), total superoxide dismutase (T-SOD), glutathione peroxidase (GSH-Px), and malondialdehyde (MDA), as well as relative mtDNAcn in peripheral blood were determined. The multivariable linear model and mediation analysis were performed to assess associations between UF, oxidative stress, and relative mtDNAcn with BMD. Results showed that GSH-Px levels increased by 6.98 U/mL [95% confidence interval (CI) 3.41-10.56)] with each 1.0 mg/L increment of UF. After stratification, the T-AOC, relative mtDNAcn, and BMD decreased by 0.04 mmol/L (-0.08 ~ -0.01), 0.29-unit (-0.55 ~ -0.04), and 0.18-unit (-0.33 ~ -0.03) with every 1.0 mg/L elevation of UF in the excessive fluoride group (EFG, adults with UF > 1.6 mg/L), respectively. Furthermore, T-AOC and relative mtDNAcn were favorably related to the BMD in the EFG (ß = 0.82, 95%CI 0.16-1.48 for T-AOC; ß = 0.11, 95%CI 0.02-0.19 for relative mtDNAcn). Mediation analysis showed that relative mtDNAcn and T-AOC mediated 15.4% and 17.1% of the connection between excessive fluoride and reduced BMD, respectively. Findings suggested that excessive fluoride was related to lower BMD in adults, and the decrement of T-AOC and relative mtDNAcn partially mediate this relationship.

Whole-exome-based single nucleotide variants and copy number analysis for prenatal diagnosis of compound heterozygosity of SMPD4.

BACKGROUND: Biallelic loss-of-function variants in SMPD4 cause a rare and severe neurodevelopmental disorder. These variants have been identified in a group of children with neurodevelopmental disorders with microcephaly, arthrogryposis, and structural brain anomalies. SMPD4 encodes a sphingomyelinase that hydrolyzes sphingomyelin into ceramide at neutral pH and can thereby affect membrane lipid homeostasis. SMPD4 localizes to the membranes of the endoplasmic reticulum and nuclear envelope and interacts with nuclear pore complexes. MATERIALS AND METHODS: For the efficient prenatal diagnosis of rare and undiagnosed diseases, the parallel detection of copy number variants (CNVs) and single nucleotide variants using whole-exome analysis is required. A physical examination of the parents was performed. Karyotype and whole-exome analysis were performed for the fetus and the parents. RESULTS: A fetus with microcephaly and arthrogryposis; biallelic null variants (c.387-1G>A; Chr2[GRCh38]: g.130142742_130202459del) were detected by whole-exome sequencing (WES). We have reported for the first time the biallelic loss-of-function mutations in SMPD4 in patients born to unrelated parents in China. CONCLUSION: WES could replace chromosomal microarray analysis and copy number variation sequencing as a more cost-effective genetic test for detecting CNVs and diagnosing highly heterogeneous conditions.

SPAST Intragenic CNVs Lead to Hereditary Spastic Paraplegia via a Haploinsufficiency Mechanism.

The most common form of hereditary spastic paraplegia (HSP), SPG4 is caused by single nucleotide variants and microrearrangements in the SPAST gene. The high percentage of multi-exonic deletions or duplications observed in SPG4 patients is predisposed by the presence of a high frequency of Alu sequences in the gene sequence. In the present study, we analyzed DNA and RNA samples collected from patients with different microrearrangements in SPAST to map gene breakpoints and evaluate the mutation mechanism. The study group consisted of 69 individuals, including 50 SPG4 patients and 19 healthy relatives from 18 families. Affected family members from 17 families carried varying ranges of microrearrangements in the SPAST gene, while one individual had a single nucleotide variant in the 5'UTR of SPAST. To detect the breakpoints of the SPAST gene, long-range PCR followed by sequencing was performed. The breakpoint sequence was detected for five different intragenic SPAST deletions and one duplication, revealing Alu-mediated microhomology at breakpoint junctions resulting from non-allelic homologous recombination in these patients. Furthermore, SPAST gene expression analysis was performed using patient RNA samples extracted from whole blood. Quantitative real-time PCR tests performed in 14 patients suggest no expression of transcripts with microrearrangements in 5 of them. The obtained data indicate that nonsense-mediated decay degradation is not the only mechanism of hereditary spastic paraplegia in patients with SPAST microrearrangements.

Hfq-Antisense RNA I Binding Regulates RNase E-Dependent RNA Stability and ColE1 Plasmid Copy Number.

The mechanisms and consequences of gene regulation by Hfq on trans-encoded small RNAs (sRNAs) have been well studied and documented. Recent employment of Genomic SELEX to search for Hfq-binding motifs has indicated that Hfq might frequently regulate gene expression controlled by cis-antisense RNAs. Here, we use the classic ColE1 plasmid antisense RNA-based regulation model (i.e., RNA I) to study the role of Hfq in controlling antisense regulatory functions. We show that Hfq exhibits a high binding affinity for RNA I and that binding limits RNase E cleavage, thereby stabilizing RNA I and reducing the plasmid copy number. Full-length RNA I displays a binding affinity for Hfq in the sub-micromolar range. In vivo overexpression of Hfq prolongs RNA I stability and reduces the ColE1 plasmid copy number, whereas deletion of hfq reduces RNA I stability and increases the plasmid copy number. RNA I predominantly binds to the proximal face of Hfq and exhibits competitive ability against a chromosome-borne proximal face-bound sRNA (DsrA) for Hfq binding. Through its strong promoter and high gene dosage features, plasmid-encoded antisense RNA I results in high RNA I expression, so it may antagonize the effects of trans-encoded RNAs in controlling target gene expression.

CopyVAE: a variational autoencoder-based approach for copy number variation inference using single-cell transcriptomics.

MOTIVATION: Copy number variations (CNVs) are common genetic alterations in tumour cells. The delineation of CNVs holds promise for enhancing our comprehension of cancer progression. Moreover, accurate inference of CNVs from single-cell sequencing data is essential for unravelling intratumoral heterogeneity. However, existing inference methods face limitations in resolution and sensitivity. RESULTS: To address these challenges, we present CopyVAE, a deep learning framework based on a variational autoencoder architecture. Through experiments, we demonstrated that CopyVAE can accurately and reliably detect CNVs from data obtained using single-cell RNA sequencing. CopyVAE surpasses existing methods in terms of sensitivity and specificity. We also discussed CopyVAE's potential to advance our understanding of genetic alterations and their impact on disease advancement. AVAILABILITY AND IMPLEMENTATION: CopyVAE is implemented and freely available under MIT license at https://github.com/kurtsemih/copyVAE.