Gclust: A Parallel Clustering Tool for Microbial Genomic Data

Li, Ruilin; He, Xiaoyu; Dai, Chuangchuang; Zhu, Hongwei; Lang, Xianyu; Chen, Wei; Li, Xiaodong; Zhao, Dan; Han, Xinyin; Tie, Niu; Zhao, Yi; Cao, Rongqiang; He, Rong; Lu, Zhiyong; Chi, Xuebin; Li, Weizhong; Niu, Beifang

doi:10.1016/j.gpb.2018.10.008

Cited by 11 publications

(6 citation statements)

References 24 publications

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“…These Illumina reads were generated from libraries prepared using the Nextera prep kit (Illumina) and sequenced on an Illumina NextSeq 500 with 150 cycle paired-end sequencing. Duplicate contigs were removed using gclust v1.0 [ 111 ] and these representative contigs were used as a reference for aligning IS-Seq reads as described above.…”

Section: Methodsmentioning

confidence: 99%

Targeted IS-element sequencing uncovers transposition dynamics during selective pressure in enterococci

et al. 2023

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Insertion sequences (IS) are simple transposons implicated in the genome evolution of diverse pathogenic bacterial species. Enterococci have emerged as important human intestinal pathogens with newly adapted virulence potential and antibiotic resistance. These genetic features arose in tandem with large-scale genome evolution mediated by mobile elements. Pathoadaptation in enterococci is thought to be mediated in part by the IS element IS256 through gene inactivation and recombination events. However, the regulation of IS256 and the mechanisms controlling its activation are not well understood. Here, we adapt an IS256-specfic deep sequencing method to describe how chronic lytic phage infection drives widespread diversification of IS256 in E. faecalis and how antibiotic exposure is associated with IS256 diversification in both E. faecalis and E. faecium during a clinical human infection. We show through comparative genomics that IS256 is primarily found in hospital-adapted enterococcal isolates. Analyses of IS256 transposase gene levels reveal that IS256 mobility is regulated at the transcriptional level by multiple mechanisms in E. faecalis, indicating tight control of IS256 activation in the absence of selective pressure. Our findings reveal that stressors such as phages and antibiotic exposure drives rapid genome-scale transposition in the enterococci. IS256 diversification can therefore explain how selective pressures mediate evolution of the enterococcal genome, ultimately leading to the emergence of dominant nosocomial lineages that threaten human health.

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Section: Methodsmentioning

confidence: 99%

Targeted IS-element sequencing uncovers transposition dynamics during selective pressure in enterococci

et al. 2023

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“…These blocks were mapped to NipRG (including mitochondrion and plastid) again using minimap2 v2.17 ( Li 2018 ), and the sequences mapped with ≥90% identity and 80% coverage were removed. The remaining sequences were clustered into nonredundant sequences with identity cutoff of 90% using Gclust v1.0.0 ( Li et al 2019 ) and EUPAN v0.44 ( Hu et al 2017 ) blastCluster. After that, the remaining sequences were mapped to NT database (June 18, 2020) using BLAST+ v2.10.1 ( Camacho et al 2009 ) BLASTN.…”

Section: Methodsmentioning

confidence: 99%

Long-read sequencing of 111 rice genomes reveals significantly larger pan-genomes

et al. 2022

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The concept of a pan-genome, which is the collection of all genomes from a population, has shown great potential in genomics study, especially for crop sciences. The rice pan-genome constructed from the second-generation sequencing (SGS) data is about 270 Mb larger than Nipponbare, the rice reference genome (NipRG), but it still suffers from incompleteness and loss of genomic contexts. The third-generation sequencing (TGS) with long reads can help to construct better pan-genomes. In this paper, we reported a high-quality rice pan-genome construction method by introducing a series of new steps to deal with the long-read data including unmapped sequence block filtering, redundancy removing, and sequence block elongating. Compared to NipRG, the long-read sequencing-based pan-genome constructed from 105 rice accessions, which contains 604 Mb novel sequences, is much more comprehensive than the one constructed from ~3000 rice genomes sequenced with short reads. The repetitive sequences are the main components of novel sequences, which partially explained the differences between the pan-genomes based on TGS and SGS. Adding 6 wild rice accessions, there are about 879 Mb novel sequences and 19,000 novel genes in the rice pan-genome in total. In addition, we have created high-quality reference genomes for all representative rice populations, including 5 gapless reference genomes. This study has brought significant progress for our understanding about the rice pan-genome, and this pan-genome construction method for long-read data can be applied to accelerate a broad range of genomics studies.

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“…Gclust, a parallel technique was developed [18] to group entire or partial gene data. In this model, a new multithreading mechanism and a rapid gene evaluation technique were adopted by the Sparse Suffix Arrays (SSAs) to speed up the grouping.…”

Section: Literature Surveymentioning

confidence: 99%

An Adaptive Local Gravitation-based Optimized Weighted Consensus Clustering for Gene Expression Data Classification

2022

IJIES

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The appropriate categorization of tumors from a vast quantity of Gene Expression Data (GED) is one of the most difficult processes in clinical diagnosis. To combat this challenge, a Weighted Consensus of Lion Optimized K-means Ensemble with Peak Density Clustering (WECLO K-means-PDC) algorithm has been developed that calculates the Symmetric Neighborhood (SN) correlation among Data Points (DPs) using the lion optimization. An SN Graph (SNG) was created to select the number of Cluster Centroids (ClustCenter) at every iteration of clustering. But, it was not suitable if the dataset was sparse, as well as the constant density threshold may influence the distinguishing DPs within the cluster boundaries. In this paper, an Adaptive Local resultant Force neighborhood PDC for WECR K-means (WECLO K-means-ALFPDC) algorithm is proposed, which considers additional measures to determine the symmetric neighborhood correlation among the DPs when the dataset is sparse. The major goal is to consider the distinct variances between the sizes and orientations of the DPs nearer to the ClustCenters and edges. To find such variations, two novel local measures called Centrality (CR) and Coordination (CO) are introduced instead of SNG to select the ClustCenters and obtain more precise clustering for classifying cancer from genomic data. Finally, the test results show that the WECLO K-means-ALFPDC algorithm attains 88.7%, 89.1%, 88.42%, 88.38% and 89.04% accuracy on leukemia, lymphoma, prostate cancer, SRBCT and breast cancer databases, respectively compared to the WECLO K-means-PDC algorithm.

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Gclust: A Parallel Clustering Tool for Microbial Genomic Data

Cited by 11 publications

References 24 publications

Targeted IS-element sequencing uncovers transposition dynamics during selective pressure in enterococci

Targeted IS-element sequencing uncovers transposition dynamics during selective pressure in enterococci

Long-read sequencing of 111 rice genomes reveals significantly larger pan-genomes

An Adaptive Local Gravitation-based Optimized Weighted Consensus Clustering for Gene Expression Data Classification

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