Evaluation of the MGISEQ-2000 Sequencing Platform for Illumina Target Capture Sequencing Libraries

The performance of homopolymer detection using dichromatic and tetrachromatic fluorogenic next-generation sequencing platforms

OBJECTIVES

Homopolymer (HP) sequencing is error-prone in next-generation sequencing (NGS) assays, and may induce false insertion/deletions and substitutions. This study aimed to evaluate the performance of dichromatic and tetrachromatic fluorogenic NGS platforms when sequencing homopolymeric regions.

RESULTS

A HP-containing plasmid was constructed and diluted to serial frequencies (3%, 10%, 30%, 60%) to determine the performance of an MGISEQ-2000, MGISEQ-200, and NextSeq 2000 in HP sequencing. An evident negative correlation was observed between the detected frequencies of four nucleotide HPs and the HP length. Significantly decreased rates (P < 0.01) were found in all 8-mer HPs in all three NGS systems at all four expected frequencies, except in the NextSeq 2000 at 3%. With the application of a unique molecular identifier (UMI) pipeline, there were no differences between the detected frequencies of any HPs and the expected frequencies, except for poly-G 8-mers using the MGI 200 platform. UMIs improved the performance of all three NGS platforms in HP sequencing.

CONCLUSIONS

We first constructed an HP-containing plasmid based on an EGFR gene backbone to evaluate the performance of NGS platforms when sequencing homopolymeric regions. A highly comparable performance was observed between the MGISEQ-2000 and NextSeq 2000, and introducing UMIs is a promising approach to improve the performance of NGS platforms in sequencing homopolymeric regions.

Genomic characterization of vancomycin-resistant Enterococcus faecium clonal complex 17 isolated from urine in tertiary hospitals in Northeastern Thailand

Vancomycin-resistant Enterococci (VREs) have increasingly become a major nosocomial pathogen worldwide, earning high-priority category from the World Health Organization (WHO) due to their antibiotic resistance. Among VREs, vancomycin-resistant Enterococcus faecium (VREfm) is particularly concerning, frequently isolated and resistant to many antibiotics used in hospital-acquired infections. This study investigated VREfm isolates from rural tertiary hospitals in Northeastern Thailand based both antibiotic susceptibility testing and whole-genome sequencing. All isolates showed resistance to vancomycin, ampicillin, erythromycin, tetracycline, ciprofloxacin, norfloxacin, and rifampin. Nitrofurantoin and tigecycline resistance were also observed in nearly all isolates. Conversely, all isolates remained susceptible to chloramphenicol, daptomycin, and linezolid. Genomic characterization revealed that all VREfm isolates belonged to clonal complex 17 (CC17), primarily consisting of sequence type (ST) 80, followed by ST17, ST761, and ST117. Additionally, all isolates harbored numerous antimicrobial-resistant genes, including vanA, tet(L), tet(M), aac(6')-li, ant(6)-Ia, aph(3')-III, aac(6')-aph(2″), aph(2″)-la, ant(9)-la, erm(B), msr(C), erm(T), erm(A), fosB, dfrG, and cfr(B). Notably, all isolates contained virulence genes, for collagen adhesin (acm) and cell wall adhesin (efafm), while hylEfm (glycosyl hydrolase) was detected in VREfm ST80. This study provided important information for understanding the genomic features of VREfm isolated from urine.

Comparative transcriptomic analysis of Illumina and MGI next-generation sequencing platforms using RUNX3- and ZBTB46-instructed embryonic stem cells

Introduction: We have previously observed phenotypic and developmental changes upon the ectopic expression of the RUNX3 or the ZBTB46 transcription factors in mouse embryonic stem cell (ESC) derived progenitors. In this study, we evaluated the gene expression profiles of the RUNX3- and the ZBTB46-instructed murine ESCs with RNA-seq testing two next-generation sequencing technologies. Methods: We compared the DNA nanoball-based DNBSEQ G400 sequencer (MGI) with the bridge-PCR-based NextSeq 500 instrument (Illumina) for RNA sequencing. Moreover, we also compared two types of MGI sequencing reagents (Standard versus Hot-massive parallel sequencing (MPS)) with the DNBSEQ G400. Results: We observed that both sequencing platforms showed comparable levels of quality, sequencing uniformity, and gene expression profiles. For example, highly overlapping RUNX3- and ZBTB46-regulated gene lists were obtained from both sequencing datasets. Moreover, we observed that the Standard and the Hot-MPS-derived RUNX3- and ZBTB46-regulated gene lists were also considerably overlapped. This transcriptome analysis also helped us to identify differently expressed genes in the presence of the transgenic RUNX3 or ZBTB46. For example, we found that Gzmb, Gzmd, Gzme, Gdf6, and Ccr7 genes were robustly upregulated upon the forced expression of Runx3; on the other hand, Gpx2, Tdpoz4, and Arg2 were induced alongside the ectopic expression of Zbtb46. Discussion: Similar gene expression profile and greatly overlapping RUNX3- and ZBTB46-regulated gene sets were detected with both DNA sequencing platforms. Our analyses demonstrate that both sequencing technologies are suitable for transcriptome profiling and target gene selection. These findings suggest that DNBSEQ G400 represents a cost-effective alternative sequencing platform for gene expression monitoring. Moreover, this analysis provides a resource for exploration of the RUNX3- and ZBTB46-dependent gene regulatory networks.

Single-Cell Sequencing Technology and Its Application in the Study of Central Nervous System Diseases

The mammalian central nervous system consists of a large number of cells, which contain not only different types of neurons, but also a large number of glial cells, such as astrocytes, oligodendrocytes, and microglia. These cells are capable of performing highly refined electrophysiological activities and providing the brain with functions such as nutritional support, information transmission and pathogen defense. The diversity of cell types and individual differences between cells have brought inspiration to the study of the mechanism of central nervous system diseases. In order to explore the role of different cells, a new technology, single-cell sequencing technology has emerged to perform specific analysis of high-throughput cell populations, and has been continuously developed. Single-cell sequencing technology can accurately analyze single-cell expression in mixed-cell populations and collect cells from different spatial locations, time stages and types. By using single-cell sequencing technology to compare gene expression profiles of normal and diseased cells, it is possible to discover cell subsets associated with specific diseases and their associated genes. Therefore, scientists can understand the development process, related functions and disease state of the nervous system from an unprecedented depth. In conclusion, single-cell sequencing technology provides a powerful technology for the discovery of novel therapeutic targets for central nervous system diseases.

Genomic and transcriptomic characterization of pre-operative chemotherapy response in patients with osteosarcoma

Osteosarcoma is a heterogeneous disease with regard to its chemotherapy response and clinical outcomes. This study aims to investigate the genomic and transcriptomic characteristics related to pre-operative chemotherapy response. Samples from 25 osteosarcoma patients were collected to perform both whole exome and transcriptome sequencing. Osteosarcoma had significant amount of chromosomal copy number variants (CNVs). Chemotherapy responders showed the higher chromosomal CNV burden than non-responders (p = 0.0775), but the difference was not significant. The percentage of COSMIC signature 3, associated with homologous recombination repair deficiency, was higher in responders (56%) than in non-responders (45%). Transcriptomic analysis suggested that 11 genes were significantly up-regulated in responders and 18 genes were up-regulated in non-responders. Both GSEA and KEGG enrichment analysis indicted that four pathways related to cardiomyopathy were up-regulated in responders, while neuroactive ligand - receptor interaction was up-regulated in non-responders. Finally, a previously published chemoresistant model was validated using our dataset, with the area under the curve of 0.796 (95% CI, 0.583-1.000). Osteosarcoma had the heterogeneous mutational profile with frequent occurrence of CNVs. Transcriptomic analysis identified several signaling pathways associated with chemotherapy responsiveness to osteosarcoma. Transcriptomic signatures provides a potential research direction for predicting the chemotherapy response.

Pediatric intensive care unit treatment alters the diversity and composition of the gut microbiota and antimicrobial resistance gene expression in critically ill children

Introduction

Common critical illnesses are a growing economic burden on healthcare worldwide. However, therapies targeting the gut microbiota for critical illnesses have not been developed on a large scale. This study aimed to investigate the changes in the characteristics of the gut microbiota in critically ill children after short-term pediatric intensive care unit (PICU) treatments.

Methods

Anal swab samples were prospectively collected from March 2021 to March 2022 from children admitted to the PICU of Xinhua Hospital who received broad-spectrum antibiotics on days 1 (the D1 group) and 7 (the D7 group) of the PICU treatment. The structural and functional characteristics of the gut microbiota of critically ill children were explored using metagenomic next-generation sequencing (mNGS) technology, and a comparative analysis of samples from D1 and D7 was conducted.

Results

After 7 days of PICU admission, a significant decrease was noted in the richness of the gut microbiota in critically ill children, while the bacterial diversity and the community structure between groups remained stable to some extent. The relative abundance of Bacilli and Lactobacillales was significantly higher, and that of Campylobacter hominis was significantly lower in the D7 group than in the D1 group. The random forest model revealed that Prevotella coporis and Enterobacter cloacae were bacterial biomarkers between groups. LEfSe revealed that two Gene Ontology entries, GO:0071555 (cell wall organization) and GO:005508 (transmembrane transport), changed significantly after the short-term treatment in the PICU. In addition, 30 KEGG pathways were mainly related to the activity of enzymes and proteins during the processes of metabolism, DNA catabolism and repair, and substance transport. Finally, 31 antimicrobial resistance genes had significantly different levels between the D7 and D1 groups. The top 10 up-regulated genes were Erm(A), ErmX, LptD, eptB, SAT-4, tetO, adeJ, adeF, APH(3')-IIIa, and tetM.

Conclusion

The composition, gene function, and resistance genes of gut microbiota of critically ill children can change significantly after short PICU treatments. Our findings provide a substantial basis for a better understanding of the structure and function of gut microbiota and their role in critical illnesses.

Yueomyces silvicola sp. nov., a novel ascomycetous yeast species unable to utilize ammonium, glutamate, and glutamine as sole nitrogen sources

Five yeast strains isolated from tree bark and rotten wood collected in central and southwestern China, together with four Brazilian strains (three from soil and rotting wood collected in an Amazonian rainforest biome and one from Bromeliad collected in Alagoas state) and one Costa Rican strain isolated from a flower beetle, represent a new species closely related with Yueomyces sinensis in Saccharomycetaceae, as revealed by the 26S ribosomal RNA gene D1/D2 domain and the internal transcribed spacer region sequence analysis. The name Yueomyces silvicola sp. nov. is proposed for this new species with the holotype China General Microbiological Culture Collection Center 2.6469 (= Japan Collection of Microorganisms 34885). The new species exhibits a whole-genome average nucleotide identity value of 77.8% with Y. sinensis. The two Yueomyces species shared unique physiological characteristics of being unable to utilize ammonium and the majority of the amino acids, including glutamate and glutamine, as sole nitrogen sources. Among the 20 amino acids tested, only leucine and tyrosine can be utilized by the Yueomyces species. Genome sequence comparison showed that GAT1, which encodes a GATA family protein participating in transcriptional activation of nitrogen-catabolic genes in Saccharomyces cerevisiae, is absent in the Yueomyces species. However, the failure of the Yueomyces species to utilize ammonium, glutamate, and glutamine, which are generally preferred nitrogen sources for microorganisms, implies that more complicated alterations in the central nitrogen metabolism pathway might occur in the genus Yueomyces.

A cross-cohort computational framework to trace tumor tissue-of-origin based on RNA sequencing

Carcinoma of unknown primary (CUP) is a type of metastatic cancer with tissue-of-origin (TOO) unidentifiable by traditional methods. CUP patients typically have poor prognosis but therapy targeting the original cancer tissue can significantly improve patients' prognosis. Thus, it's critical to develop accurate computational methods to infer cancer TOO. While qPCR or microarray-based methods are effective in inferring TOO for most cancer types, the overall prediction accuracy is yet to be improved. In this study, we propose a cross-cohort computational framework to trace TOO of 32 cancer types based on RNA sequencing (RNA-seq). Specifically, we employed logistic regression models to select 80 genes for each cancer type to create a combined 1356-gene set, based on transcriptomic data from 9911 tissue samples covering the 32 cancer types with known TOO from the Cancer Genome Atlas (TCGA). The selected genes are enriched in both tissue-specific and tissue-general functions. The cross-validation accuracy of our framework reaches 97.50% across all cancer types. Furthermore, we tested the performance of our model on the TCGA metastatic dataset and International Cancer Genome Consortium (ICGC) dataset, achieving an accuracy of 91.09% and 82.67%, respectively, despite the differences in experiment procedures and pipelines. In conclusion, we developed an accurate yet robust computational framework for identifying TOO, which holds promise for clinical applications. Our code is available at http://github.com/wangbo00129/classifybysklearn .

Discrimination of monozygotic twins using mtDNA heteroplasmy through probe capture enrichment and massively parallel sequencing

Differentiating between monozygotic (MZ) twins remains difficult because they have the same genetic makeup. Applying the traditional STR genotyping approach cannot differentiate one from the other. Heteroplasmy refers to the presence of two or more different mtDNA copies within a single cell and this phenomenon is common in humans. The levels of heteroplasmy cannot change dramatically during transmission in the female germ line but increase or decrease during germ-line transmission and in somatic tissues during life. As massively parallel sequencing (MPS) technology has advanced, it has shown the extraordinary quantity of mtDNA heteroplasmy in humans. In this study, a probe hybridization technique was used to obtain mtDNA and then MPS was performed with an average sequencing depth of above 4000. The results showed us that all ten pairs of MZ twins were clearly differentiated with the minor heteroplasmy threshold at 1.0%, 0.5%, and 0.1%, respectively. Finally, we used a probe that targeted mtDNA to boost sequencing depth without interfering with nuclear DNA and this technique can be used in forensic genetics to differentiate the MZ twins.

Cross-platform comparisons for targeted bisulfite sequencing of MGISEQ-2000 and NovaSeq6000

BACKGROUND

An accurate and reproducible next-generation sequencing platform is essential to identify malignancy-related abnormal DNA methylation changes and translate them into clinical applications including cancer detection, prognosis, and surveillance. However, high-quality DNA methylation sequencing has been challenging because poor sequence diversity of the bisulfite-converted libraries severely impairs sequencing quality and yield. In this study, we tested MGISEQ-2000 Sequencer's capability of DNA methylation sequencing with a published non-invasive pancreatic cancer detection assay, using NovaSeq6000 as the benchmark.

RESULTS

We sequenced a series of synthetic cell-free DNA (cfDNA) samples with different tumor fractions and found MGISEQ-2000 yielded data with similar quality as NovaSeq6000. The methylation levels measured by MGISEQ-2000 demonstrated high consistency with NovaSeq6000. Moreover, MGISEQ-2000 showed a comparable analytic sensitivity with NovaSeq6000, suggesting its potential for clinical detection. As to evaluate the clinical performance of MGISEQ-2000, we sequenced 24 clinical samples and predicted the pathology of the samples with a clinical diagnosis model, PDACatch classifier. The clinical model performance of MGISEQ-2000's data was highly consistent with that of NovaSeq6000's data, with the area under the curve of 1. We also tested the model's robustness with MGISEQ-2000's data when reducing the sequencing depth. The results showed that MGISEQ-2000's data showed matching robustness of the PDACatch classifier with NovaSeq6000's data.

CONCLUSIONS

Taken together, MGISEQ-2000 demonstrated similar data quality, consistency of the methylation levels, comparable analytic sensitivity, and matching clinical performance, supporting its application in future non-invasive early cancer detection investigations by detecting distinct methylation patterns of cfDNAs.

Comparison of prokaryotes between Mount Everest and the Mariana Trench

BACKGROUND

Mount Everest and the Mariana Trench represent the highest and deepest places on Earth, respectively. They are geographically separated, with distinct extreme environmental parameters that provide unique habitats for prokaryotes. Comparison of prokaryotes between Mount Everest and the Mariana Trench will provide a unique perspective to understanding the composition and distribution of environmental microbiomes on Earth.

RESULTS

Here, we compared prokaryotic communities between Mount Everest and the Mariana Trench based on shotgun metagenomic analysis. Analyzing 25 metagenomes and 1176 metagenome-assembled genomes showed distinct taxonomic compositions between Mount Everest and the Mariana Trench, with little taxa overlap, and significant differences in genome size, GC content, and predicted optimal growth temperature. However, community metabolic capabilities exhibited striking commonality, with > 90% of metabolic modules overlapping among samples of Mount Everest and the Mariana Trench, with the only exception for CO₂ fixations (photoautotrophy in Mount Everest but chemoautotrophy in the Mariana Trench). Most metabolic pathways were common but performed by distinct taxa in the two extreme habitats, even including some specialized metabolic pathways, such as the versatile degradation of various refractory organic matters, heavy metal metabolism (e.g., As and Se), stress resistance, and antioxidation. The metabolic commonality indicated the overall consistent roles of prokaryotes in elemental cycling and common adaptation strategies to overcome the distinct stress conditions despite the intuitively huge differences in Mount Everest and the Mariana Trench.

CONCLUSION

Our results, the first comparison between prokaryotes in the highest and the deepest habitats on Earth, may highlight the principles of prokaryotic diversity: although taxa are habitat-specific, primary metabolic functions could be always conserved. Video abstract.

Human Retrotransposons and Effective Computational Detection Methods for Next-Generation Sequencing Data

Transposable elements (TEs) are classified into two classes according to their mobilization mechanism. Compared to DNA transposons that move by the "cut and paste" mechanism, retrotransposons mobilize via the "copy and paste" method. They have been an essential research topic because some of the active elements, such as Long interspersed element 1 (LINE-1), Alu, and SVA elements, have contributed to the genetic diversity of primates beyond humans. In addition, they can cause genetic disorders by altering gene expression and generating structural variations (SVs). The development and rapid technological advances in next-generation sequencing (NGS) have led to new perspectives on detecting retrotransposon-mediated SVs, especially insertions. Moreover, various computational methods have been developed based on NGS data to precisely detect the insertions and deletions in the human genome. Therefore, this review discusses details about the recently studied and utilized NGS technologies and the effective computational approaches for discovering retrotransposons through it. The final part covers a diverse range of computational methods for detecting retrotransposon insertions with human NGS data. This review will give researchers insights into understanding the TEs and how to investigate them and find connections with research interests.

Transcriptome Analysis to Identify Genes Related to Flowering Reversion in Tomato

Flowering reversion is a common phenomenon in plant development in which differentiated floral organs switch from reproductive growth to vegetative growth and ultimately form abnormal floral organs or vegetative organs. This greatly reduces tomato yield and quality. Research on this phenomenon has recently increased, but there is a lack of research at the molecular and gene expression levels. Here, transcriptomic analyses of the inflorescence meristem were performed in two kinds of materials at different developmental stages, and a total of 3223 differentially expressed genes (DEGs) were screened according to the different developmental stages and trajectories of the two materials. The analysis of database annotations showed that these DEGs were closely related to starch and sucrose metabolism, DNA replication and modification, plant hormone synthesis and signal transduction. It was further speculated that tomato flowering reversion may be related to various biological processes, such as cell signal transduction, energy metabolism and protein post-transcriptional regulation. Combined with the results of previous studies, our work showed that the gene expression levels of CLE9, FA, PUCHI, UF, CLV3, LOB30, SFT, S-WOX9 and SVP were significantly different in the two materials. Endogenous hormone analysis and exogenous hormone treatment revealed a variety of plant hormones involved in flowering reversion in tomato. Thus, tomato flowering reversion was studied comprehensively by transcriptome analysis for the first time, providing new insights for the study of flower development regulation in tomato and other plants.

CircRNA expression profiles in deltamethrin-susceptible and -resistant Culex pipiens pallens (Diptera: Culicidae)

The excessive and improper application of insecticides has caused the evolution of resistance in many mosquito populations, including Culex pipiens pallens (L.). Deltamethrin, a representative pyrethroid insecticide, is the most widely used synthetic insecticide in mosquito-borne control field. Comprehensively identifying genes and regulators associated with deltamethrin resistance and elucidating the manner in which they regulate this process is critical for effective control of mosquitoes. CircRNAs are the upstream regulatory factors of miRNAs and mRNAs, which play a role via the competitive endogenous RNA mechanism. In this study, we used high-throughput circRNA sequencing to identify circRNAs that were expressed differently in deltamethrin-susceptible strain (DS strain) and -resistant strain (DR strain) mosquitoes [NCBI Sequence Read Archive (SRA) database accession number: PRJNA714543]. We detected a total of 12,816 significantly differentially expressed circRNAs (DE-circRNAs). Among them, 6769 circRNAs were up-regulated and 6047 circRNAs were down-regulated in the DR strain compared to DS strain. Among the DE-circRNAs, we further screened that supercont3.352:252102|253283 was significantly over-expressed in the DR strain through qPCR multiple verification (P < 0.05).We used the divergent primer to amplify the rolling circle product and obtained the full-length sequence of supercont3.352:252102|253283 (GeneBank accession number: MW729338). Through software comparison and bioinformatics analysis, we predicted that supercont3.352:252102|253283 might participate in deltamethrin resistance by sponging cpp-miR-1671 and blocking its inhibition on CYP4G15.We further found that the expression of cpp-miR-1671 was significantly lower in DR strain (P < 0.01), while the expression of CYP4G15 was significantly higher in DR strain (P < 0.05).Taken together, the present study provided the most comprehensive circRNA expression profile of mosquitoes, and suggested that supercont3.352:252102|253283 might participate in deltamethrin resistance through the supercont3.352:252102|253283/cpp-miR-1671/CYP4G15 pathway.

Biomarker Characterization and Prediction of Virulence and Antibiotic Resistance from Helicobacter pylori Next Generation Sequencing Data

The Gram-negative bacterium Helicobacter pylori colonizes c.a. 50% of human stomachs worldwide and is the major risk factor for gastric adenocarcinoma. Its high genetic variability makes it difficult to identify biomarkers of early stages of infection that can reliably predict its outcome. Moreover, the increasing antibiotic resistance found in H. pylori defies therapy, constituting a major human health problem. Here, we review H. pylori virulence factors and genes involved in antibiotic resistance, as well as the technologies currently used for their detection. Furthermore, we show that next generation sequencing may lead to faster characterization of virulence factors and prediction of the antibiotic resistance profile, thus contributing to personalized treatment and management of H. pylori-associated infections. With this new approach, more and permanent data will be generated at a lower cost, opening the future to new applications for H. pylori biomarker identification and antibiotic resistance prediction.

Draft Genome Assembly and Annotation for Cutaneotrichosporon dermatis NICC30027, an Oleaginous Yeast Capable of Simultaneous Glucose and Xylose Assimilation

The identification of oleaginous yeast species capable of simultaneously utilizing xylose and glucose as substrates to generate value-added biological products is an area of key economic interest. We have previously demonstrated that the Cutaneotrichosporon dermatis NICC30027 yeast strain is capable of simultaneously assimilating both xylose and glucose, resulting in considerable lipid accumulation. However, as no high-quality genome sequencing data or associated annotations for this strain are available at present, it remains challenging to study the metabolic mechanisms underlying this phenotype. Herein, we report a 39,305,439 bp draft genome assembly for C. dermatis NICC30027 comprised of 37 scaffolds, with 60.15% GC content. Within this genome, we identified 524 tRNAs, 142 sRNAs, 53 miRNAs, 28 snRNAs, and eight rRNA clusters. Moreover, repeat sequences totaling 1,032,129 bp in length were identified (2.63% of the genome), as were 14,238 unigenes that were 1,789.35 bp in length on average (64.82% of the genome). The NCBI non-redundant protein sequences (NR) database was employed to successfully annotate 11,795 of these unigenes, while 3,621 and 11,902 were annotated with the Swiss-Prot and TrEMBL databases, respectively. Unigenes were additionally subjected to pathway enrichment analyses using the Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), Cluster of Orthologous Groups of proteins (COG), Clusters of orthologous groups for eukaryotic complete genomes (KOG), and Non-supervised Orthologous Groups (eggNOG) databases. Together, these results provide a foundation for future studies aimed at clarifying the mechanistic basis for the ability of C. dermatis NICC30027 to simultaneously utilize glucose and xylose to synthesize lipids.