SVDF: enhancing structural variation detect from long-read sequencing via automatic filtering strategies.

Structural variation (SV) is an important form of genomic variation that influences gene function and expression by altering the structure of the genome. Although long-read data have been proven to better characterize SVs, SVs detected from noisy long-read data still include a considerable portion of false-positive calls. To accurately detect SVs in long-read data, we present SVDF, a method that employs a learning-based noise filtering strategy and an SV signature-adaptive clustering algorithm, for effectively reducing the likelihood of false-positive events. Benchmarking results from multiple orthogonal experiments demonstrate that, across different sequencing platforms and depths, SVDF achieves higher calling accuracy for each sample compared to several existing general SV calling tools. We believe that, with its meticulous and sensitive SV detection capability, SVDF can bring new opportunities and advancements to cutting-edge genomic research.

Benchmarking short and long read polishing tools for nanopore assemblies: achieving near-perfect genomes for outbreak isolates.

BACKGROUND: Oxford Nanopore provides high throughput sequencing platforms able to reconstruct complete bacterial genomes with 99.95% accuracy. However, even small levels of error can obscure the phylogenetic relationships between closely related isolates. Polishing tools have been developed to correct these errors, but it is uncertain if they obtain the accuracy needed for the high-resolution source tracking of foodborne illness outbreaks. RESULTS: We tested 132 combinations of assembly and short- and long-read polishing tools to assess their accuracy for reconstructing the genome sequences of 15 highly similar Salmonella enterica serovar Newport isolates from a 2020 onion outbreak. While long-read polishing alone improved accuracy, near perfect accuracy (99.9999% accuracy or ~ 5 nucleotide errors across the 4.8 Mbp genome, excluding low confidence regions) was only obtained by pipelines that combined both long- and short-read polishing tools. Notably, medaka was a more accurate and efficient long-read polisher than Racon. Among short-read polishers, NextPolish showed the highest accuracy, but Pilon, Polypolish, and POLCA performed similarly. Among the 5 best performing pipelines, polishing with medaka followed by NextPolish was the most common combination. Importantly, the order of polishing tools mattered i.e., using less accurate tools after more accurate ones introduced errors. Indels in homopolymers and repetitive regions, where the short reads could not be uniquely mapped, remained the most challenging errors to correct. CONCLUSIONS: Short reads are still needed to correct errors in nanopore sequenced assemblies to obtain the accuracy required for source tracking investigations. Our granular assessment of the performance of the polishing pipelines allowed us to suggest best practices for tool users and areas for improvement for tool developers.

Whole genome sequence data of the multidrug-resistant Proteus mirabilis-MN029, a model bacterial strain for the evaluation of antibacterial activity from selected native plant extracts.

Antimicrobial resistance remains a significant global and One Health threat, owing to the diminishing effectiveness of antibiotics against rapidly evolving multidrug-resistant bacteria, and the limited innovative research towards the development of new antibiotic therapeutics. In this article, we present the whole-genome sequence data of Proteus mirabilis-MN029 obtained from highly accurate long-read PacBioⓇ HiFi technology. The antibacterial activities of the selected African native plant species were also evaluated using the disk diffusion method. Acquired antibiotic resistance genes and chromosomal mutations corresponding to antibiotics of clinical importance were identified from genomic data. Using ethlyl acetate as solvent, Pterocarpus angolensis leaf extracts showed the most promising antibacterial effects against Proteus mirabilis-MN029. These datasets will be useful for future experimental research aimed at designing new antibacterial drugs from plant extracts that are effective alone or in combination with existing antibiotics to overcome multidrug-resistance mechanisms.

Unveiling novel genetic variants in 370 challenging medically relevant genes using the long read sequencing data of 41 samples from 19 global populations.

BACKGROUND: A large number of challenging medically relevant genes (CMRGs) are situated in complex or highly repetitive regions of the human genome, hindering comprehensive characterization of genetic variants using next-generation sequencing technologies. In this study, we employed long-read sequencing technology, extensively utilized in studying complex genomic regions, to characterize genetic alterations, including short variants (single nucleotide variants and short insertions and deletions) and copy number variations, in 370 CMRGs across 41 individuals from 19 global populations. RESULTS: Our analysis revealed high levels of genetic variants in CMRGs, with 68.73% exhibiting copy number variations and 65.20% containing short variants that may disrupt protein function across individuals. Such variants can influence pharmacogenomics, genetic disease susceptibility, and other clinical outcomes. We observed significant differences in CMRG variation across populations, with individuals of African ancestry harboring the highest number of copy number variants and short variants compared to samples from other continents. Notably, 15.79% to 33.96% of short variants were exclusively detectable through long-read sequencing. While the T2T-CHM13 reference genome significantly improved the assembly of CMRG regions, thereby facilitating variant detection in these regions, some regions still lacked resolution. CONCLUSION: Our results provide an important reference for future clinical and pharmacogenetic studies, highlighting the need for a comprehensive representation of global genetic diversity in the reference genome and improved variant calling techniques to fully resolve medically relevant genes.

Full-length direct RNA sequencing reveals extensive remodeling of RNA expression, processing and modification in aging Caenorhabditis elegans.

Organismal aging is marked by decline in cellular function and anatomy, ultimately resulting in death. To inform our understanding of the mechanisms underlying this degeneration, we performed standard RNA sequencing and Nanopore direct RNA sequencing over an adult time course in Caenorhabditis elegans. Long reads allowed for identification of hundreds of novel isoforms and age-associated differential isoform accumulation, resulting from alternative splicing and terminal exon choice. Genome-wide analysis reveals a decline in RNA processing fidelity and a rise in inosine and pseudouridine editing events in transcripts from older animals. In this first map of pseudouridine modifications for C. elegans, we find that they largely reside in coding sequences and that the number of genes with this modification increases with age. Collectively, this analysis discovers transcriptomic signatures associated with age and is a valuable resource to understand the many processes that dictate altered gene expression patterns and post-transcriptional regulation in aging.

Prevalence and diversity of TAL effector-like proteins in fungal endosymbiotic Mycetohabitans spp.

Endofungal Mycetohabitans (formerly Burkholderia) spp. rely on a type III secretion system to deliver mostly unidentified effector proteins when colonizing their host fungus, Rhizopus microsporus. The one known secreted effector family from Mycetohabitans consists of homologues of transcription activator-like (TAL) effectors, which are used by plant pathogenic Xanthomonas and Ralstonia spp. to activate host genes that promote disease. These 'Burkholderia TAL-like (Btl)' proteins bind corresponding specific DNA sequences in a predictable manner, but their genomic target(s) and impact on transcription in the fungus are unknown. Recent phenotyping of Btl mutants of two Mycetohabitans strains revealed that the single Btl in one Mycetohabitans endofungorum strain enhances fungal membrane stress tolerance, while others in a Mycetohabitans rhizoxinica strain promote bacterial colonization of the fungus. The phenotypic diversity underscores the need to assess the sequence diversity and, given that sequence diversity translates to DNA targeting specificity, the functional diversity of Btl proteins. Using a dual approach to maximize capture of Btl protein sequences for our analysis, we sequenced and assembled nine Mycetohabitans spp. genomes using long-read PacBio technology and also mined available short-read Illumina fungal-bacterial metagenomes. We show that btl genes are present across diverse Mycetohabitans strains from Mucoromycota fungal hosts yet vary in sequences and predicted DNA binding specificity. Phylogenetic analysis revealed distinct clades of Btl proteins and suggested that Mycetohabitans might contain more species than previously recognized. Within our data set, Btl proteins were more conserved across M. rhizoxinica strains than across M. endofungorum, but there was also evidence of greater overall strain diversity within the latter clade. Overall, the results suggest that Btl proteins contribute to bacterial-fungal symbioses in myriad ways.

Molecular mechanisms of human overgrowth and use of omics in its diagnostics: chances and challenges.

Overgrowth disorders comprise a group of entities with a variable phenotypic spectrum ranging from tall stature to isolated or lateralized overgrowth of body parts and or organs. Depending on the underlying physiological pathway affected by pathogenic genetic alterations, overgrowth syndromes are associated with a broad spectrum of neoplasia predisposition, (cardio) vascular and neurodevelopmental anomalies, and dysmorphisms. Pathologic overgrowth may be of prenatal or postnatal onset. It either results from an increased number of cells (intrinsic cellular hyperplasia), hypertrophy of the normal number of cells, an increase in interstitial spaces, or from a combination of all of these. The underlying molecular causes comprise a growing number of genetic alterations affecting skeletal growth and Growth-relevant signaling cascades as major effectors, and they can affect the whole body or parts of it (mosaicism). Furthermore, epigenetic modifications play a critical role in the manifestation of some overgrowth diseases. The diagnosis of overgrowth syndromes as the prerequisite of a personalized clinical management can be challenging, due to their clinical and molecular heterogeneity. Physicians should consider molecular genetic testing as a first diagnostic step in overgrowth syndromes. In particular, the urgent need for a precise diagnosis in tumor predisposition syndromes has to be taken into account as the basis for an early monitoring and therapy. With the (future) implementation of next-generation sequencing approaches and further omic technologies, clinical diagnoses can not only be verified, but they also confirm the clinical and molecular spectrum of overgrowth disorders, including unexpected findings and identification of atypical cases. However, the limitations of the applied assays have to be considered, for each of the disorders of interest, the spectrum of possible types of genomic variants has to be considered as they might require different methodological strategies. Additionally, the integration of artificial intelligence (AI) in diagnostic workflows significantly contribute to the phenotype-driven selection and interpretation of molecular and physiological data.

Exploring early DNA methylation alterations in type 1 diabetes: implications of glycemic control.

Background: Prolonged hyperglycemia causes diabetes-related micro- and macrovascular complications, which combined represent a significant burden for individuals living with diabetes. The growing scope of evidence indicates that hyperglycemia affects the development of vascular complications through DNA methylation. Methods: A genome-wide differential DNA methylation analysis was performed on pooled peripheral blood DNA samples from individuals with type 1 diabetes (T1D) with direct DNA sequencing. Strict selection criteria were used to ensure two age- and sex-matched groups with no clinical signs of chronic complications according to persistent mean glycated hemoglobin (HbA1c) values over 5 years: HbA1c<7% (N=10) and HbA1c>8% (N=10). Results: Between the two groups, 8385 differentially methylated CpG sites, annotated to 1802 genes, were identified. Genes annotated to hypomethylated CpG sites were enriched in 48 signaling pathways. Further analysis of key CpG sites revealed four specific regions, two of which were hypermethylated and two hypomethylated, associated with long non-coding RNA and processed pseudogenes. Conclusions: Prolonged hyperglycemia in individuals with T1D, who have no clinical manifestation of diabetes-related complications, is associated with multiple differentially methylated CpG sites in crucial genes and pathways known to be linked to chronic complications in T1D.

CYP17A1 Pathogenic Variants in 26 Chinese Patients with 17α-Hydroxylase Deficiency by Targeted Long-read Sequencing.

BACKGROUND: 17α-hydroxylase/17,20-lyase deficiency (17-OHD) is a rare subtype of congenital adrenal hyperplasia (CAH) caused by homozygous or compound heterozygous pathogenic variants in the CYP17A1 gene. PURPOSE: This study aimed to identify and characterize pathogenic variants in individuals with 17-OHD, and to classify and validate the pathogenicity of novel variants. METHODS: Variants were identified via targeted long-read sequencing (TLRS) of the entire CYP17A1 gene in enrolled 17-OHD patients. The American College of Medical Genetics and Genomics guidelines were employed to assess the pathogenicity of novel variants. A minigene splicing assay was utilized to determine the impact of variants on RNA splicing. RESULTS: This study encompassed 26 patients with 17-OHD, detecting two trans pathogenic variants per patient using the TLRS method. A total of 20 pathogenic variants in the CYP17A1 were identified, with variant c.985_987delinsAA being the most frequent (28/52 alleles), followed by variant c.1459_1467del (4/52 alleles). Five novel variants including c.280T>C, c.470T>A, c.636_637del, c.866A>G, and c.1095del, were classified as pathogenic/likely pathogenic ones according to ACMG criteria. The minigene assay revealed c.866A>G in exon 5 causes a frameshift due to a 104 base pair deletion, while c.470T>A generates two transcripts, with vast majority spliced like the wild-type, and a small fraction lack 35 base pairs in the 5' flank of exon 3. CONCLUSION: The TLRS can determine the cis/trans orientation of two distant variants. Five novel pathogenic variants were reported, broadening the spectrum of CYP17A1 pathogenic variant. The variant c.866A>G, located deep in exon, affects gene function through mechanisms of aberrant splicing.

Long-read sequencing for brain tumors.

Brain tumors and genomics have a long-standing history given that glioblastoma was the first cancer studied by the cancer genome atlas. The numerous and continuous advances through the decades in sequencing technologies have aided in the advanced molecular characterization of brain tumors for diagnosis, prognosis, and treatment. Since the implementation of molecular biomarkers by the WHO CNS in 2016, the genomics of brain tumors has been integrated into diagnostic criteria. Long-read sequencing, also known as third generation sequencing, is an emerging technique that allows for the sequencing of longer DNA segments leading to improved detection of structural variants and epigenetics. These capabilities are opening a way for better characterization of brain tumors. Here, we present a comprehensive summary of the state of the art of third-generation sequencing in the application for brain tumor diagnosis, prognosis, and treatment. We discuss the advantages and potential new implementations of long-read sequencing into clinical paradigms for neuro-oncology patients.

Benchmarking short-, long- and hybrid-read assemblers for metagenome sequencing of complex microbial communities.

Metagenome community analyses, driven by the continued development in sequencing technology, is rapidly providing insights in many aspects of microbiology and becoming a cornerstone tool. Illumina, Oxford Nanopore Technologies (ONT) and Pacific Biosciences (PacBio) are the leading technologies, each with their own advantages and drawbacks. Illumina provides accurate reads at a low cost, but their length is too short to close bacterial genomes. Long reads overcome this limitation, but these technologies produce reads with lower accuracy (ONT) or with lower throughput (PacBio high-fidelity reads). In a critical first analysis step, reads are assembled to reconstruct genomes or individual genes within the community. However, to date, the performance of existing assemblers has never been challenged with a complex mock metagenome. Here, we evaluate the performance of current assemblers that use short, long or both read types on a complex mock metagenome consisting of 227 bacterial strains with varying degrees of relatedness. We show that many of the current assemblers are not suited to handle such a complex metagenome. In addition, hybrid assemblies do not fulfil their potential. We conclude that ONT reads assembled with CANU and Illumina reads assembled with SPAdes offer the best value for reconstructing genomes and individual genes of complex metagenomes, respectively.

Machine learning and related approaches in transcriptomics.

Data acquisition for transcriptomic studies used to be the bottleneck in the transcriptomic analytical pipeline. However, recent developments in transcriptome profiling technologies have increased researchers' ability to obtain data, resulting in a shift in focus to data analysis. Incorporating machine learning to traditional analytical methods allows the possibility of handling larger volumes of complex data more efficiently. Many bioinformaticians, especially those unfamiliar with ML in the study of human transcriptomics and complex biological systems, face a significant barrier stemming from their limited awareness of the current landscape of ML utilisation in this field. To address this gap, this review endeavours to introduce those individuals to the general types of ML, followed by a comprehensive range of more specific techniques, demonstrated through examples of their incorporation into analytical pipelines for human transcriptome investigations. Important computational aspects such as data pre-processing, task formulation, results (performance of ML models), and validation methods are encompassed. In hope of better practical relevance, there is a strong focus on studies published within the last five years, almost exclusively examining human transcriptomes, with outcomes compared with standard non-ML tools.

Transcriptional determinism and stochasticity contribute to the complexity of autism-associated SHANK family genes.

Precision of transcription is critical because transcriptional dysregulation is disease causing. Traditional methods of transcriptional profiling are inadequate to elucidate the full spectrum of the transcriptome, particularly for longer and less abundant mRNAs. SHANK3 is one of the most common autism causative genes. Twenty-four Shank3-mutant animal lines have been developed for autism modeling. However, their preclinical validity has been questioned due to incomplete Shank3 transcript structure. We apply an integrative approach combining cDNA-capture and long-read sequencing to profile the SHANK3 transcriptome in humans and mice. We unexpectedly discover an extremely complex SHANK3 transcriptome. Specific SHANK3 transcripts are altered in Shank3-mutant mice and postmortem brain tissues from individuals with autism spectrum disorder. The enhanced SHANK3 transcriptome significantly improves the detection rate for potential deleterious variants from genomics studies of neuropsychiatric disorders. Our findings suggest that both deterministic and stochastic transcription of the genome is associated with SHANK family genes.

Comparative genomics of Giardia duodenalis sub-assemblage AI beaver (Be-2) and human (WB-C6) strains show remarkable homozygosity, sequence similarity, and conservation of VSP genes.

Giardia duodenalis, a major cause of waterborne infection, infects a wide range of mammalian hosts and is subdivided into eight genetically well-defined assemblages named A through H. However, fragmented genomes and a lack of comparative analysis within and between the assemblages render unclear the molecular mechanisms controlling host specificity and differential disease outcomes. To address this, we generated a near-complete de novo genome of AI assemblage using the Oxford Nanopore platform by sequencing the Be-2 genome. We generated 148,144 long-reads with quality scores of > 7. The final genome assembly consists of only nine contigs with an N50 of 3,045,186 bp. This assembly agrees closely with the assembly of another strain in the AI assemblage (WB-C6). However, a critical difference is that a region previously placed in the five-prime region of Chr5 belongs to Chr4 of Be-2. We find a high degree of conservation in the ploidy, homozygosity, and the presence of cysteine-rich variant-specific surface proteins (VSPs) within the AI assemblage. Our assembly provides a nearly complete genome of a member of the AI assemblage of G. duodenalis, aiding population genomic studies capable of elucidating Giardia transmission, host range, and pathogenicity.

Detection of four isomers of the human cytomegalovirus genome using nanopore long-read sequencing.

Human cytomegalovirus has a linear DNA genome with a total length of approximately 235 kb. This large genome is divided into two domains, "Long" and "Short". There are four isomers of the cytomegalovirus genome with different orientations of each domain. To confirm the presence of four types of isomers, it is necessary to identify the sequence of the junction between the domains. However, due to the presence of repeat sequences, it is difficult to determine the junction sequences by next-generation sequencing analysis. To solve this problem, long-read sequencing was performed using the Oxford Nanopore sequencer and the junctions were successfully identified in four isomers in strain Merin and ATCC-2011-3. Nanopore sequencing also revealed the presence of multiple copies of the "a" sequence (a-seq) in the junctions, indicating the diversity of the junction sequences. These results strongly suggest that long-read sequencing using the nanopore sequencer would be beneficial for identifying the complex structure of the cytomegalovirus genome.

Phenomics and genomic features of Enterococcus avium IRMC1622a isolated from a clinical sample of hospitalized patient.

BACKGROUND: Enterococcus avium (E. avium) is a Gram-positive nosocomial pathogen that is commonly isolated from the alimentary tract. The objective of this functional genomics study was to identify the resistant genes by analyzing the genome of E. avium IRMC1622a, a type of bacteria found in feces collected from a patient at a Saudi Arabian tertiary hospital. METHODS: The bacterial strain IRMC1622a was identified by 16 S rRNA sequencing as Enterococcus sp. The resistance phenomics were performed using VITEK® 2, and morphological analysis was achieved using a scanning electron microscope (SEM). Finally, the whole bacterial genome of the bacterial strain IRMC1622a was subjected to sequencing during October 2023 using Oxford Nanopore long-read sequencing technology, and mining for resistant genes. RESULTS: The results of antimicrobial resistant phenomics indicated that the IRMC1622a strain was sensitive to all tested antimicrobial agents except for erythromycin, and the same result was confirmed by genomic analysis in addition to other classes of antibiotics. SEM showed E. avium IRMC1622a is ovoid shape, in single cells (L 1.2797 ± 0.1490 µm), in pairs (L 1.7333 ± 0.1054 µm), and in chains (L 2.44033 ± 0.1978 µm). The E. avium IRMC1622a genome has 14 (in CARD) antimicrobial resistance genes that were identified with several mechanisms of antimicrobial resistance, such as the efflux pump and conferring antibiotic resistance. The present study revealed that the E. avium IRMC1622a genome contains a high number of genes associated with virulence factors, and 14 matched pathogenic protein families and predicted as human pathogen (probability score 0.855). We report two (ISEnfa4 and ISEfa5) mobile genetic elements for the first time in the E. avium genome. CONCLUSIONS: The study concludes that E. avium IRMC1622a is susceptible to all tested antibacterials except erythromycin. The IRMC1622a has 14 genes encoding antimicrobial resistance mechanisms, including the efflux pump and conferring antibiotic resistance. This could indicate a potential rise in E. avium resistance in healthcare facilities. These observations may raise concerns regarding E. avium resistance in healthcare. We need more research to understand the pathophysiology of E. avium, which leads to hospital-acquired infections.

Neotelomeres and telomere-spanning chromosomal arm fusions in cancer genomes revealed by long-read sequencing.

Alterations in the structure and location of telomeres are pivotal in cancer genome evolution. Here, we applied both long-read and short-read genome sequencing to assess telomere repeat-containing structures in cancers and cancer cell lines. Using long-read genome sequences that span telomeric repeats, we defined four types of telomere repeat variations in cancer cells: neotelomeres where telomere addition heals chromosome breaks, chromosomal arm fusions spanning telomere repeats, fusions of neotelomeres, and peri-centromeric fusions with adjoined telomere and centromere repeats. These results provide a framework for the systematic study of telomeric repeats in cancer genomes, which could serve as a model for understanding the somatic evolution of other repetitive genomic elements.

Glomerular basement membrane ultrastructural changes in a patient with COQ2 glomerulopathy: A case report.

Primary coenzyme Q10 deficiency-1, caused by COQ2 disease-causing variants, is an autosomal recessive disorder, and genetic testing is the gold standard for diagnosing this condition. A Chinese boy with steroid-resistant nephrotic syndrome, focal segmental glomerulosclerosis, and progressive kidney insufficiency was included in the study. Electron microscopy revealed the glomerular basement membrane with irregular thickness and lamellation with diffuse effacement of foot processes in the podocytes, and swollen mitochondria with abnormal cristae in the podocytes. Coenzyme Q10 supplementation started about 3 weeks after the onset of mild kidney dysfunction did not improve the proband's kidney outcome. Proband-only whole-exome sequencing and Sanger sequencing revealed two heteroallelic COQ2 variants: a maternally inherited novel variant c.1013G > A[p.(Gly338Glu)] in exon 6 and a variant of unknown origin c.1159C > T[p.(Arg387*)] in exon 7. Subsequent long-read sequencing demonstrated these two variants were located on different alleles. Our report extends the phenotypic and genotypic spectrum of COQ2 glomerulopathy.

GROND: a quality-checked and publicly available database of full-length 16S-ITS-23S rRNA operon sequences.

Sequence comparison of 16S rRNA PCR amplicons is an established approach to taxonomically identify bacterial isolates and profile complex microbial communities. One potential application of recent advances in long-read sequencing technologies is to sequence entire rRNA operons and capture significantly more phylogenetic information compared to sequencing of the 16S rRNA (or regions thereof) alone, with the potential to increase the proportion of amplicons that can be reliably classified to lower taxonomic ranks. Here we describe GROND (Genome-derived Ribosomal Operon Database), a publicly available database of quality-checked 16S-ITS-23S rRNA operons, accompanied by multiple taxonomic classifications. GROND will aid researchers in analysis of their data and act as a standardised database to allow comparison of results between studies.