Whole Genome Sequencing Technologies Research Articles

First Data on WGS-Based Typing and Antimicrobial Resistance of Human Salmonella Enteritidis Isolates in Greece

Salmonella enterica subsp. enterica serotype Enteritidis (S. Enteritidis) is one of the major causes of foodborne infections and is responsible for many national and multi-country foodborne outbreaks worldwide. In Greece, human salmonellosis is a mandatory notifiable disease, with laboratory surveillance being on a voluntary basis. This study aims to provide the first insights into the genetic characteristics and antimicrobial resistance profiles of 47 S. Enteritidis human isolates using whole-genome sequencing (WGS) technology. The S. Enteritidis population was mainly resistant to fluoroquinolones due to gyrA point mutations, whereas one isolate presented a multi-resistant plasmid-mediated phenotype. ST11 was the most frequent sequence type, and phylogenetic analysis through the cgMLST and SNP methods revealed considerable genetic diversity. Regarding virulence factors, 8 out of the 24 known SPIs and C63PI were detected. Due to the observed variability between countries, it is of utmost importance to record the circulating S. Enteritidis strains’ structure and genomic epidemiology at the national level. WGS is a valuable tool that is revolutionizing our approach to Salmonella by providing a deeper understanding of these pathogens and their impact on human health.

The Whole Genome DNA Methylation Signatures of Hindlimb Muscles in Chinese Alligators during Hibernation and Active Periods.

Many ectotherms hibernate to increase their chances of survival during harsh winter conditions. The role of DNA methylation in regulating gene expression related to hibernation in ectotherms remains unclear. Here, we employed whole-genome bisulfite sequencing (WGBS) technology to construct a comprehensive genome-wide DNA methylation landscape of the hindlimb muscles in the Chinese alligator during hibernation and active periods. The results indicated that methylation modifications were most abundant at CG sites, identifying 9447 differentially methylated regions (DMRs) and 2329 differentially methylated genes (DMGs). KEGG pathway enrichment analysis of the DMGs revealed significant enrichment in major pathways such as the neurotrophin signaling pathway, the MAPK signaling pathway, the GnRH signaling pathway, the biosynthesis of amino acids, and the regulation of the actin cytoskeleton, which are closely related to lipid metabolism, energy metabolism, and amino acid metabolism. Among these, 412 differentially methylated genes were located in promoter regions, including genes related to energy metabolism such as ATP5F1C, ATP5MD, PDK3, ANGPTL1, and ANGPTL2, and genes related to ubiquitin-proteasome degradation such as FBXO28, FBXO43, KLHL40, and PSMD5. These findings suggest that methylation in promoter regions may play a significant role in regulating the adaptive hibernation mechanisms in the Chinese alligator. This study contributes to a further understanding of the epigenetic mechanisms behind the hibernation of the Chinese alligator.

Transposase-assisted tagmentation: an economical and scalable strategy for single-worm whole-genome sequencing.

AlphaMissense identifies 23 million human missense variants as likely pathogenic, but only 0.1% have been clinically classified. To experimentally validate these predictions, chemical mutagenesis presents a rapid, cost-effective method to produce billions of mutations in model organisms. However, the prohibitive costs and limitations in the throughput of whole-genome sequencing (WGS) technologies, crucial for variant identification, constrain its widespread application. Here, we introduce a Tn5 transposase-assisted tagmentation technique for conducting WGS in Caenorhabditis elegans, Escherichia coli, Saccharomyces cerevisiae, and Chlamydomonas reinhardtii. This method, demands merely 20 min of hands-on time for a single-worm or single-cell clones and incurs a cost below 10 US dollars. It effectively pinpoints causal mutations in mutants defective in cilia or neurotransmitter secretion and in mutants synthetically sterile with a variant analogous to the B-Raf Proto-oncogene, Serine/Threonine Kinase (BRAF) V600E mutation. Integrated with chemical mutagenesis, our approach can generate and identify missense variants economically and efficiently, facilitating experimental investigations of missense variants in diverse species.

ACMGA: a reference-free multiple-genome alignment pipeline for plant species

BackgroundThe short-read whole-genome sequencing (WGS) approach has been widely applied to investigate the genomic variation in the natural populations of many plant species. With the rapid advancements in long-read sequencing and genome assembly technologies, high-quality genome sequences are available for a group of varieties for many plant species. These genome sequences are expected to help researchers comprehensively investigate any type of genomic variants that are missed by the WGS technology. However, multiple genome alignment (MGA) tools designed by the human genome research community might be unsuitable for plant genomes.ResultsTo fill this gap, we developed the AnchorWave-Cactus Multiple Genome Alignment (ACMGA) pipeline, which improved the alignment of repeat elements and could identify long (> 50 bp) deletions or insertions (INDELs). We conducted MGA using ACMGA and Cactus for 8 Arabidopsis (Arabidopsis thaliana) and 26 Maize (Zea mays) de novo assembled genome sequences and compared them with the previously published short-read variant calling results. MGA identified more single nucleotide variants (SNVs) and long INDELs than did previously published WGS variant callings. Additionally, ACMGA detected significantly more SNVs and long INDELs in repetitive regions and the whole genome than did Cactus. Compared with the results of Cactus, the results of ACMGA were more similar to the previously published variants called using short-read. These two MGA pipelines identified numerous multi-allelic variants that were missed by the WGS variant calling pipeline.ConclusionsAligning denovo assembled genome sequences could identify more SNVs and INDELs than mapping short-read. ACMGA combines the advantages of AnchorWave and Cactus and offers a practical solution for plant MGA by integrating global alignment, a 2-piece-affine-gap cost strategy, and the progressive MGA algorithm.

Genomic analysis of multidrug-resistant Escherichia coli from Urban Environmental water sources in Accra, Ghana, Provides Insights into public health implications.

Wastewater discharge into the environment in resource-poor countries poses a threat to public health. Studies in this area within these countries are limited, and the use of high-throughput whole-genome sequencing technologies is lacking. Therefore, understanding of environmental impacts is inadequate. The present study investigated the antibiotic resistance profiles and diversity of beta-lactamases in Escherichia coli strains isolated from environmental water sources in Accra, Ghana. Microbiological analyses were conducted on wastewater samples from three hospitals, a sewage and wastewater treatment plant, and water samples from two urban surface water bodies. Confirmed isolates (N = 57) were selected for phenotypic antibiotic resistance profiles. Multi-drug-resistant isolates (n = 25) were genome sequenced using Illumina MiSeq sequencing technology and screened for sequence types, antibiotic resistance, virulence and beta-lactamase genes, and mobile genetic elements. Isolates were frequently resistant to ampicillin (63%), meropenem (47%), azithromycin (46%), and sulfamethoxazole-trimethoprim (42%). Twenty different sequence types (STs) were identified, including clinically relevant ones such as ST167 and ST21. Five isolates were assigned to novel STs: ST14531 (n = 2), ST14536, ST14537, and ST14538. The isolates belonged to phylogroups A (52%), B1 (44%), and B2 (4%) and carried β-lactamase (TEM-1B, TEM-1C, CTX-M-15, and blaDHA-1) and carbapenemase (OXA-1, OXA-181) resistance genes. Dominant plasmid replicons included Col440I (10.2%) and IncFIB (AP001918) (6.8%). Polluted urban environments in Accra are reservoirs for antibiotic-resistant bacteria, posing a substantial public health risk. The findings underscore the need for targeted public health interventions to mitigate the spread of antibiotic-resistant bacteria and protect public health.

Modulation of long noncoding RNAs by polyphenols as a novel potential therapeutic approach in lung cancer: A comprehensive review.

Lung cancer stands as a formidable global health challenge, necessitating innovative therapeutic strategies. Polyphenols, bioactive compounds synthesized by plants, have garnered attention for their diverse health benefits, particularly in combating various cancers, including lung cancer. The advent of whole-genome and transcriptome sequencing technologies has illuminated the pivotal roles of long noncoding RNAs (lncRNAs), operating at epigenetic, transcriptional, and posttranscriptional levels, in cancer progression. This review comprehensively explores the impact of polyphenols on both oncogenic and tumor-suppressive lncRNAs in lung cancer, elucidating on their intricate regulatory mechanisms. The comprehensive examination extends to the potential synergies when combining polyphenols with conventional treatments like chemotherapy, radiation, and immunotherapy. Recognizing the heterogeneity of lung cancer subtypes, the review emphasizes the need for the integration of nanotechnology for optimized polyphenol delivery and personalized therapeutic approaches. In conclusion, we collect the latest research, offering a holistic overview of the evolving landscape of polyphenol-mediated modulation of lncRNAs in lung cancer therapy. The integration of polyphenols and lncRNAs into multidimensional treatment strategies holds promise for enhancing therapeutic efficacy and navigating the challenges associated with lung cancer treatment.

Identification of methylation driver genes for predicting the prognosis of pancreatic cancer patients based on whole-genome DNA methylation sequencing technology

This study was based on the use of whole-genome DNA methylation sequencing technology to identify DNA methylation biomarkers in tumor tissue that can predict the prognosis of patients with pancreatic cancer (PCa). TCGA database was used to download PCa-related DNA methylation and transcriptome atlas data. Methylation driver genes (MDGs) were obtained using the MethylMix package. Candidate genes in the MDGs were screened for prognostic relevance to PCa patients by univariate Cox analysis, and a prognostic risk score model was constructed based on the key MDGs. ROC curve analysis was performed to assess the accuracy of the prognostic risk score model. The effects of PIK3C2B knockdown on malignant phenotypes of PCa cells were investigated in vitro. A total of 2737 differentially expressed genes were identified, with 649 upregulated and 2088 downregulated, using 178 PCa samples and 171 normal samples. MethylMix was employed to identify 71 methylation-driven genes (47 hypermethylated and 24 hypomethylated) from 185 TCGA PCa samples. Cox regression analyses identified eight key MDGs (LEF1, ZIC3, VAV3, TBC1D4, FABP4, MAP3K5, PIK3C2B, IGF1R) associated with prognosis in PCa. Seven of them were hypermethylated, while PIK3C2B was hypomethylated. A prognostic risk prediction model was constructed based on the eight key MDGs, which was found to accurately predict the prognosis of PCa patients. In addition, the malignant phenotypes of PANC-1 cells were decreased after the knockdown of PIK3C2B. Therefore, the prognostic risk prediction model based on the eight key MDGs could accurately predict the prognosis of PCa patients.

Towards a unified medical microbiome ecology of the OMU for metagenomes and the OTU for microbes

BackgroundMetagenomic sequencing technologies offered unprecedented opportunities and also challenges to microbiology and microbial ecology particularly. The technology has revolutionized the studies of microbes and enabled the high-profile human microbiome and earth microbiome projects. The terminology-change from microbes to microbiomes signals that our capability to count and classify microbes (microbiomes) has achieved the same or similar level as we can for the biomes (macrobiomes) of plants and animals (macrobes). While the traditional investigations of macrobiomes have usually been conducted through naturalists’ (Linnaeus & Darwin) naked eyes, and aerial and satellite images (remote-sensing), the large-scale investigations of microbiomes have been made possible by DNA-sequencing-based metagenomic technologies. Two major types of metagenomic sequencing technologies—amplicon sequencing and whole-genome (shotgun sequencing)—respectively generate two contrastingly different categories of metagenomic reads (data)—OTU (operational taxonomic unit) tables representing microorganisms and OMU (operational metagenomic unit), a new term coined in this article to represent various cluster units of metagenomic genes.ResultsThe ecological science of microbiomes based on the OTU representing microbes has been unified with the classic ecology of macrobes (macrobiomes), but the unification based on OMU representing metagenomes has been rather limited. In a previous series of studies, we have demonstrated the applications of several classic ecological theories (diversity, composition, heterogeneity, and biogeography) to the studies of metagenomes. Here I push the envelope for the unification of OTU and OMU again by demonstrating the applications of metacommunity assembly and ecological networks to the metagenomes of human gut microbiomes. Specifically, the neutral theory of biodiversity (Sloan’s near neutral model), Ning et al.stochasticity framework, core-periphery network, high-salience skeleton network, special trio-motif, and positive-to-negative ratio are applied to analyze the OMU tables from whole-genome sequencing technologies, and demonstrated with seven human gut metagenome datasets from the human microbiome project.ConclusionsAll of the ecological theories demonstrated previously and in this article, including diversity, composition, heterogeneity, stochasticity, and complex network analyses, are equally applicable to OMU metagenomic analyses, just as to OTU analyses. Consequently, I strongly advocate the unification of OTU/OMU (microbiomes) with classic ecology of plants and animals (macrobiomes) in the context of medical ecology.

Abstract 6250: The RNA editing landscape of lung cancer in never smokers

Abstract Adenosine-to-Inosine (A-to-I) editing represents a crucial RNA modification mechanism, holding the potential to drive carcinogenesis. This sophisticated post-transcriptional process is catalyzed by a series of ADAR (adenosine deaminase acting on RNA) family members, which can profoundly reshape the cellular epitranscriptomic landscape. While previous explorations have illuminated the important role of A-to-I editing in lung cancer tumorigenesis and prognosis, most studies have focused on lung cancer from smokers. To investigate the contribution on RNA-editing in lung cancers in never smokers (LCINS) , we embarked on a rigorous dissection of A-to-I RNA editing events in 603 LCINS. Harnessing transcriptome and whole-genome sequencing technologies, we identified 15,880 A-to-I sites, of which 75% were positively linked to the enzymatic activity of ADAR1. 92.80% of detected editing sites were located at Alu repetitive regions, with the remainder in non_Alu repeat (4.1%) and non-repeat regions (3.1%). The global RNA editing levels, measured as Alu Editing Index (AEI), were found to be significantly associated with ADAR1 expression, Tumor Mutational Burden, and Neoantigens Burden. A subtle correlation between global RNA editing levels and tumor stage was also noted. Delving into cancer-associated editing events, we identified 5,539 differentially edited sites in tumors compared with normal tissues, which were located at 823 genes, including several key tumor suppressors and oncogenes, like MDM2, BRAF, TP53, BRCA2, ATM, and VHL. Subsequent pathway analysis identified TGF-beta, Notch Signaling, and DNA Damage Response as the key pathways for cancer progression. Using the characterized A-to-I editing profiles, we built a prognostic risk stratification model, with high risk scores significantly linked to poor survival outcomes, even after adjusting for other clinical factors. Our study provides a comprehensive A-to-I editing landscape of lung cancer in never smokers, highlighting the potential roles of RNA modifications in the pathogenesis of this lethal disease. Citation Format: Jian Sang, Wei Zhao, Tongwu Zhang, Maria Teresa Landi. The RNA editing landscape of lung cancer in never smokers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6250.

Genotypes and Phylogenetic Analysis of Human Adenovirus in Hospitalized Pneumonia and Influenza-Like Illness Patients in Jiangsu Province, China (2013-2021).

Human adenovirus (HAdV) is common pathogens that cause various respiratory diseases. The genetic diversity of viruses caused by recombination is considered to be the main source of emerging outbreaks. The aim of this study is to explore the evolutionary relationship and recombination events of HAdV genome in respiratory tract infections in Jiangsu Province. Whole-genome sequencing (WGS) technology was used to sequence 66 patients with HAdV infection (37 patients with influenza-like illness (ILI) and 29 hospitalized patients with pneumonia) from Jiangsu Province. Epidemiological analysis was performed on hospitalized pneumonia and ILI patients infected with HAdV. Subsequently, phylogenetic, recombination, and nucleotide and amino acid identity analyses were performed. Epidemiological analysis of patients undergoing WGS showed that 75.7% of ILI patients were infected with the HAdVB strain and 69.0% of hospitalized pneumonia patients were infected with the HAdVC strain. Moreover, the hospitalized pneumonia and ILI patients infected with HAdV were different in region and time. The strains of HAdVB3 and HAdVB7 genotypes were mainly infected in 2015 and 2017, and the strains of HAdVC1 and HAdVC2 genotypes were mainly infected in 2020. The results of histogram analysis showed that the HAdV strain mainly infected children under 5 years old. In addition, 36 novel recombinant strains were identified. The discovery of these recombinant strains may contribute to understanding the epidemiology of HAdV and research on related vaccines. Furthermore, the percentage of nucleotide and amino acid identities revealed a high level of genetic conservation within isolates from HAdVB3, HAdVB7, HAdVC1, HAdVC2 and HAdVC5 genotypes. The WGS analysis reveals the evolutionary relationships and recombination events of HAdV strains in Jiangsu Province, which is helpful to deepen the understanding of HAdV epidemiology and evolution. In addition, it provides a basis for the formulation of public health strategies in Jiangsu Province.

A Review on Microbiological Source Attribution Methods of Human Salmonellosis: From Subtyping to Whole-Genome Sequencing.

Salmonella is one of the main causes of human foodborne illness. It is endemic worldwide, with different animals and animal-based food products as reservoirs and vehicles of infection. Identifying animal reservoirs and potential transmission pathways of Salmonella is essential for prevention and control. There are many approaches for source attribution, each using different statistical models and data streams. Some aim to identify the animal reservoir, while others aim to determine the point at which exposure occurred. With the advance of whole-genome sequencing (WGS) technologies, new source attribution models will greatly benefit from the discriminating power gained with WGS. This review discusses some key source attribution methods and their mathematical and statistical tools. We also highlight recent studies utilizing WGS for source attribution and discuss open questions and challenges in developing new WGS methods. We aim to provide a better understanding of the current state of these methodologies with application to Salmonella and other foodborne pathogens that are common sources of illness in the poultry and human sectors.

Molecular characterization of invasive Streptococcus pneumoniae clinical isolates from a tertiary children's hospital in eastern China.

Streptococcus pneumoniae is a common opportunistic pathogen that causes invasive pneumococcal disease (IPD), especially in children. This study aimed to determine the prevalence and molecular characteristics of S. pneumoniae isolated from children with IPD. A total of 78 S. pneumoniae isolates from aseptic body fluids of 70 IPD patients were collected at the Children's Hospital of Nanjing Medical University (Jiangsu Province, China) during 2017-2021. Whole-genome sequencing technology was used to analyze the serotype, sequence type (ST), virulence, and antibiotic resistance of the 78 invasive S. pneumoniae clinical isolates. Our results showed that the pneumococcal infection rate declined after the COVID-19 outbreak in 2019. Serotypes 19F, 14, 6A, 23F, 19A, and 6B were the most common strains. The pneumococcal conjugate vaccine (PCV) 13 serotype coverage rate was 87.1%. All isolates were classified by multi-locus sequence typing (MLST) analysis into 27 different STs, including 3 novel STs (ST17941, ST17942, and ST17944) and 1 novel allele [recP (558)]. The most predominant ST was ST271, followed by ST320 and ST876. All isolates carried the following virulence genes: cbpG, lytB, lytC, pce (cbpE), pavA, slrA, plr (gapA), hysA, nanA, eno, piuA, psaA, cppA, iga, htrA (degP), tig (ropA), zmpB, and ply. All isolates were multidrug resistant and had high levels of resistance to macrolides, tetracyclines, and sulfonamides. Taken together, this study revealed extensive genetic diversity among S. pneumoniae isolates from a single Chinese hospital. Wearing masks, universal infant vaccination with PCV13, and the launch of recombinant protein vaccine development programs could reduce the burden of IPD in children. IMPORTANCE Invasive pneumococcal disease (IPD) caused by Streptococcus pneumoniae in children remains a global burden and should be given more attention due to the fact that the pneumococcal vaccine is not fully covered globally. The molecular epidemiological characteristics of S. pneumoniae are not so clear, especially in these years of COVID-19. In this study, we collected S. pneumoniae isolates from the aseptic body fluid of children with IPD from 2017 to 2021 in a tertiary children's hospital in China and revealed the extensive genetic diversity of these isolates. Most importantly, we first found that the rate of pneumococcal infection has declined since the COVID-19 outbreak in 2019, which means that wearing masks could reduce the transmission of S. pneumoniae. In addition, it was shown that universal infant vaccination with PCV13 seems essential for reducing the burden of IPD in children.

Bioinformatics analysis of bovine immunodeficiency virus main genes (gag, env, pol) sequences

The sequences bioinformatic analysis results of the of the bovine immunodeficiency virus main genes (gag, env, pol), and updated data on the phylogenetic relationships of the pathogen are presented in the article. The existence of at least two genetic groups of BIV, which have a common origin from a common ancestor, has been established. In addition, the complexity of conducting a full-fledged and comprehensive sequence analysis for a complete understanding of the evolution and virus phylogenetic relationships was noted. It was determined that the lack of a single methodological approach to BIV sequencing in different world scientific communities complicates the analysis and interpretation of the obtained data. The application of whole-genome sequencing technologies is proposed to solve this issue

Alternative molecular and genomic strategies to provide a rapid response to alerts concerning the introduction of new emerging SARS-CoV-2 variants: the Omicron alert.

During the COVID-19 pandemic, several SARS-CoV-2 variants of concern (VOCs) of particular relevance emerged. Early detection of VOCs entering a country is essential to control spread. The alert triggered by the first suspected case of the Omicron variant in Spain in a traveler arriving from South Africa in November 2021 provided a unique opportunity to evaluate four different methodological strategies tailored to rapid identification of Omicron. The different approaches were designed to respond to the different technical resources available in different settings. First, we used melting probes in RT-PCR to determine the presence of four Omicron signatures (K417N, E484A, P681H, and absence of L452R): three probes showed deviations in temperature (Tm) values relative to the reference codons (E484K-15.8°C, P681H-5.2°C, and L452R-7.2°C) and one maintained the reference value (K417N). The deviation in Tm of P681H suggested the presence of the characteristic Omicron N679K mutation in the probe hybridization region; these data pointed to the presence of Omicron alleles. Second, the presence of 29 of the 33 characteristic single nucleotide polymorphisms (SNPs) in the Omicron variant S-gene was identified by Sanger sequencing of nine amplicons. The final two strategies involved identification of 47 of the 50 non-synonymous and indel mutations attributed to Omicron by rapid nanopore whole genome sequencing (WGS) and by Illumina WGS technology. These strategies enabled us to pre-assign the first Omicron case in Spain with high certainty 2 h after receipt of RNA and to confirm it genomically 3 h later, so that the Public Health authorities could be rapidly notified. IMPORTANCE The study presents different experimental alternatives to identify new variants of concern (VOCs) of SARS-CoV-2 entering a certain population. Early detection of a new VOC is crucial for surveillance and control of spread. The objective is to provide laboratories with tools adapted to their resource capabilities that offer a sufficient level of resolution to rule out, confirm, or pre-assign the presence of a suspected VOC. The study describes four different techniques that were applied simultaneously to the first suspected Omicron case in Spain, highlighting the level of resolution and response time achieved in each case. These techniques are based on the detection of mutations in the S-gene of the virus that can easily adapt to potential emerging variants. The results of the study allow any laboratory to prepare for new alerts of SARS-CoV-2 VOCs.

Evaluation of the clinical utility of extended non-invasive prenatal testing in the detection of chromosomal aneuploidy and microdeletion/microduplication

BackgroundWith the development of whole-genome sequencing technology, non-invasive prenatal testing (NIPT) has been applied gradually to screen chromosomal microdeletions and microduplications that cannot be detected by traditional karyotyping. However, in NIPT, some false positives and false negatives occur. This study aimed to investigate the applicability of extended NIPT (NIPT-PLUS) in the detection of chromosomal aneuploidy and microdeletion/microduplication syndrome (MMS).MethodsA total of 452 pregnancies that underwent prenatal diagnostic testing (amniocentesis or chorionic villus sampling) by chromosomal microarray analysis (CMA), were screened by NIPT-PLUS from the peripheral blood sample of the pregnant women. The results of the two tested items were compared and analysed.ResultsOf the 452 cases, 335 (74.12%) had positive CMA results, and 117 (25.88%) had no abnormal results. A total of 86 cases of trisomy 21, 18 and 13 and sex chromosome aneuploidy (SCA) were detected by CMA and NIPT-PLUS, with a detection rate of 96.51% (83/86). Among them, the detection rates of T18, T13; 47, XXY; 47, XXX and 47 XYY were 100%, and the detection rates of T21 and 45 XO were 96.55% and 90%, respectively. The detection sensitivity of rare chromosomal trisomy (RAT) was 80% (4/5). The positive predictive values of NIPT-PLUS for chromosome aneuploidy T21, T18 and T13 and for SCA and RAT were 90.32%, 87.50%, 25.00%, 88.89% and 50%, respectively. A total of 249 cases (74.32%) of chromosomal MMS were detected by CMA. The detection rate of NIPT-PLUS was 63.86% (159/249), and 90 cases (36.14%) were missed. The larger the MMS fragment, the higher the NIPT-PLUS detection sensitivity. In addition, most small fragments were of maternal origin.ConclusionThe comparison between the CMA and NIPT-PLUS techniques shows that NIPT-PLUS has high sensitivity for detecting chromosomal aneuploidy and chromosomal copy number variations (CNVs) with fragments > 5 M. However, the sensitivity of CNV for fragments < 5 M is low, and the missed detection rate is high. Additionally, confined placental mosaicism and foetal mosaicism are the key factors causing false negatives in NIPT-PLUS, while maternal chromosomal abnormalities and confined placental mosaicism are key contributors to false positives, so appropriate genetic counselling is especially important for pregnant women before and after NIPT-PLUS testing.

Chromothripsis detection with multiple myeloma patients based on deep graph learning.

Chromothripsis, associated with poor clinical outcomes, is prognostically vital in multiple myeloma. The catastrophic event is reported to be detectable prior to the progression of multiple myeloma. As a result, chromothripsis detection can contribute to risk estimation and early treatment guidelines for multiple myeloma patients. However, manual diagnosis remains the gold standard approach to detect chromothripsis events with the whole-genome sequencing technology to retrieve both copy number variation (CNV) and structural variation data. Meanwhile, CNV data are much easier to obtain than structural variation data. Hence, in order to reduce the reliance on human experts' efforts and structural variation data extraction, it is necessary to establish a reliable and accurate chromothripsis detection method based on CNV data. To address those issues, we propose a method to detect chromothripsis solely based on CNV data. With the help of structure learning, the intrinsic relationship-directed acyclic graph of CNV features is inferred to derive a CNV embedding graph (i.e. CNV-DAG). Subsequently, a neural network based on Graph Transformer, local feature extraction, and non-linear feature interaction, is proposed with the embedding graph as the input to distinguish whether the chromothripsis event occurs. Ablation experiments, clustering, and feature importance analysis are also conducted to enable the proposed model to be explained by capturing mechanistic insights. The source code and data are freely available at https://github.com/luvyfdawnYu/CNV_chromothripsis.

A revised SNP-based barcoding scheme for typing Mycobacterium tuberculosis complex isolates.

The development of whole-genome sequencing technologies is gradually leading to a more detailed description of the population structure of the Mycobacterium tuberculosis complex (MTBC). In this study, we correlated previously published classifications on a collection of more than 10,000 genomes and proposed a new, comprehensive nomenclature that unifies the existing ones. In total, we identified 169 lineages and sublineages of M. tuberculosis/M. africanum and 9 animal-adapted species. For the purpose of organizing these genotypes in a more streamlined manner, we stratified them into five hierarchical levels. To represent the classification and compare it with the reference, we compiled a confirmatory data set of 670 high-quality isolates, which includes all genotypes and species of MTBC, and this confirmatory data set can serve as a basis for further studies. We proposed a set of 213 robust barcoding single-nucleotide polymorphisms and a suitable workflow for reliable differentiation of genotypes and species within the complex. This work integrates the results of all the major systematized studies to date to provide an understanding of the global diversity of the MTBC population structure. The results of this work may ultimately help to reliably determine the pathogen genotype and associate it with traits that reflect its prevalence, virulence, vaccination, and treatment efficiency, as well as to reliably find natural features revealed during its spread. IMPORTANCE Through years of research into the Mycobacterium tuberculosis complex (MTBC), a number of ambiguous phylogenetic classifications have emerged, which often overlap with one another. In the present study, we have combined all major studies on MTBC classification and inferred a unified, most complete to date classification and accompanying SNP barcodes.

Genome-wide genetic variation and molecular surveillance of drug resistance in Plasmodium falciparum isolates from asymptomatic individuals in Ouélessébougou, Mali

Sequence analysis of Plasmodium falciparum parasites is informative in ensuring sustained success of malaria control programmes. Whole-genome sequencing technologies provide insights into the epidemiology and genome-wide variation of P. falciparum populations and can characterise geographical as well as temporal changes. This is particularly important to monitor the emergence and spread of drug resistant P. falciparum parasites which is threatening malaria control programmes world-wide. Here, we provide a detailed characterisation of genome-wide genetic variation and drug resistance profiles in asymptomatic individuals in South-Western Mali, where malaria transmission is intense and seasonal, and case numbers have recently increased. Samples collected from Ouélessébougou, Mali (2019–2020; n = 87) were sequenced and placed in the context of older Malian (2007–2017; n = 876) and African-wide (n = 711) P. falciparum isolates. Our analysis revealed high multiclonality and low relatedness between isolates, in addition to increased frequencies of molecular markers for sulfadoxine-pyrimethamine and lumefantrine resistance, compared to older Malian isolates. Furthermore, 21 genes under selective pressure were identified, including a transmission-blocking vaccine candidate (pfCelTOS) and an erythrocyte invasion locus (pfdblmsp2). Overall, our work provides the most recent assessment of P. falciparum genetic diversity in Mali, a country with the second highest burden of malaria in West Africa, thereby informing malaria control activities.

Integrating whole-genome sequencing and transcriptomic findings in the diagnosis and management of Coffin-Siris syndrome

IntroductionAlthough the whole-exome sequencing (WES) approach has been widely used in clinic, many rare diseases with syndromic and nonsyndromic neurological manifestations remain undiagnosed. Coffin-Siris syndrome (CSS) is a rare autosomal dominant genetic disease characterized by neurodevelopmental delay. A suspected diagnosis can be made based on the typical CSS clinical features; however, molecular genetic testing is necessary for a confirmed diagnosis. ObjectivesThree CSS-like patients with negative results in the WES and chromosomal microarray analysis (CMA) were recruited in this study. MethodsWe used whole-genome sequencing (WGS) technology to sequence the peripheral blood of the three families. To further explore the possible pathogenesis of CSS, we performed RNA-sequencing (RNA-seq). ResultsWGS identified the three CSS patients were carrying de novo copy number variants of the ARID1B gene, which have not been reported before. RNA-seq identified 184 differentially expressed genes (DEGs), with 116 up-regulated and 68 down-regulated. Functional annotation of DEGs showed that two biological processes (immune response, chemokine activity) and two signaling pathways (cytokine-cytokine receptor interaction, chemokine activity) were highlighted. We speculated that ARID1B deficiency might trigger abnormal immune responses, which may be involved in the pathophysiologic mechanisms of CSS. ConclusionOur research provided further support for WGS application in CSS diagnosis and made an investigational approach for the underlying mechanisms of CSS.

Genomic Innovation in Early Life Cardiovascular Disease Prevention and Treatment.

Cardiovascular disease (CVD) is a leading cause of morbidity and mortality globally. Although CVD events do not typically manifest until older adulthood, CVD develops gradually across the life-course, beginning with the elevation of risk factors observed as early as childhood or adolescence and the emergence of subclinical disease that can occur in young adulthood or midlife. Genomic background, which is determined at zygote formation, is among the earliest risk factors for CVD. With major advances in molecular technology, including the emergence of gene-editing techniques, along with deep whole-genome sequencing and high-throughput array-based genotyping, scientists now have the opportunity to not only discover genomic mechanisms underlying CVD but use this knowledge for the life-course prevention and treatment of these conditions. The current review focuses on innovations in the field of genomics and their applications to monogenic and polygenic CVD prevention and treatment. With respect to monogenic CVD, we discuss how the emergence of whole-genome sequencing technology has accelerated the discovery of disease-causing variants, allowing comprehensive screening and early, aggressive CVD mitigation strategies in patients and their families. We further describe advances in gene editing technology, which might soon make possible cures for CVD conditions once thought untreatable. In relation to polygenic CVD, we focus on recent innovations that leverage findings of genome-wide association studies to identify druggable gene targets and develop predictive genomic models of disease, which are already facilitating breakthroughs in the life-course treatment and prevention of CVD. Gaps in current research and future directions of genomics studies are also discussed. In aggregate, we hope to underline the value of leveraging genomics and broader multiomics information for characterizing CVD conditions, work which promises to expand precision approaches for the life-course prevention and treatment of CVD.