Tandem repeat interval pattern identifies animal taxa

2021 ◽  
Author(s):  
Balaram Bhattacharyya ◽  
Uddalak Mitra ◽  
Ramkishore Bhattacharyya
Keyword(s):  
Information Content ◽  
Tandem Repeat ◽  
Tandem Repeats ◽  
Ordered Set ◽  
Whole Genome Sequence ◽  
Supplementary Information ◽  
Whole Genome ◽  
Supplementary Data ◽  
Genome Sequences ◽  
Significant Achievement

Abstract Motivation We discover that maximality of information content among intervals of Tandem Repeats (TRs) in animal genome segregates over taxa such that taxa identification becomes swift and accurate. Successive TRs of a motif occur at intervals over the sequence, forming a trail of TRs of the motif across the genome. We present a method, Tandem Repeat Information Mining (TRIM), that mines 4k number of TR trails of all k length motifs from a whole genome sequence and extracts the information content within intervals of the trails. TRIM vector formed from the ordered set of interval entropies becomes instrumental for genome segregation. Results Reconstruction of correct phylogeny for animals from whole genome sequences proves precision of TRIM. Identification of animal taxa by TRIM vector upon feature selection is the most significant achievement. These suggest Tandem Repeat Interval Pattern (TRIP) is a taxa-specific constitutional characteristic in animal genome. Availabilityand implementation Source and executable code of TRIM along with usage manual are made available at https://github.com/BB-BiG/TRIM. Supplementary information Supplementary data are available at Bioinformatics online.

TIGER: inferring DNA replication timing from whole-genome sequence data

2021 ◽  
Author(s):  
Amnon Koren ◽  
Dashiell J Massey ◽  
Alexa N Bracci
Keyword(s):  
Dna Replication ◽  
Genome Sequence ◽  
Genomic Dna ◽  
Sequence Data ◽  
Replication Timing ◽  
Whole Genome Sequence ◽  
Supplementary Information ◽  
Whole Genome ◽  
Genome Sequence Data ◽  
Dna Replication Timing

Abstract Motivation Genomic DNA replicates according to a reproducible spatiotemporal program, with some loci replicating early in S phase while others replicate late. Despite being a central cellular process, DNA replication timing studies have been limited in scale due to technical challenges. Results We present TIGER (Timing Inferred from Genome Replication), a computational approach for extracting DNA replication timing information from whole genome sequence data obtained from proliferating cell samples. The presence of replicating cells in a biological specimen leads to non-uniform representation of genomic DNA that depends on the timing of replication of different genomic loci. Replication dynamics can hence be observed in genome sequence data by analyzing DNA copy number along chromosomes while accounting for other sources of sequence coverage variation. TIGER is applicable to any species with a contiguous genome assembly and rivals the quality of experimental measurements of DNA replication timing. It provides a straightforward approach for measuring replication timing and can readily be applied at scale. Availability and Implementation TIGER is available at https://github.com/TheKorenLab/TIGER. Supplementary information Supplementary data are available at Bioinformatics online

scholarly journals Whole-Genome Sequences of Influenza A(H1N1)pdm09 Virus Isolates from Kerala, India

2017 ◽  
Vol 5 (28) ◽  
Author(s):  
Sara Jones ◽  
Raji Prasad ◽  
Anjana S. Nair ◽  
Sanjai Dharmaseelan ◽  
Remya Usha ◽  
...  
Keyword(s):  
Amino Acid ◽  
Amino Acid Analysis ◽  
Influenza A ◽  
Whole Genome Sequence ◽  
Whole Genome ◽  
H1n1 Pandemic ◽  
Genome Sequences ◽  
Influenza A H1n1 ◽  
Virus Isolates ◽  
New Mutations

ABSTRACT We report here the whole-genome sequence of six clinical isolates of influenza A(H1N1)pdm09, isolated from Kerala, India. Amino acid analysis of all gene segments from the A(H1N1)pdm09 isolates obtained in 2014 and 2015 identified several new mutations compared to the 2009 A(H1N1) pandemic strain.

scholarly journals Whole genome characterization of strains belonging to the Ralstonia solanacearum species complex and in silico analysis of TaqMan assays for detection in this heterogenous species complex

2021 ◽  
Author(s):  
Viola Kurm ◽  
Ilse Houwers ◽  
Claudia E. Coipan ◽  
Peter Bonants ◽  
Cees Waalwijk ◽  
...  
Keyword(s):  
Ralstonia Solanacearum ◽  
In Silico ◽  
Species Complex ◽  
Sequence Data ◽  
In Silico Analysis ◽  
Whole Genome Sequence ◽  
Whole Genome ◽  
Genome Sequences ◽  
Pcr Assays

AbstractIdentification and classification of members of the Ralstonia solanacearum species complex (RSSC) is challenging due to the heterogeneity of this complex. Whole genome sequence data of 225 strains were used to classify strains based on average nucleotide identity (ANI) and multilocus sequence analysis (MLSA). Based on the ANI score (>95%), 191 out of 192(99.5%) RSSC strains could be grouped into the three species R. solanacearum, R. pseudosolanacearum, and R. syzygii, and into the four phylotypes within the RSSC (I,II, III, and IV). R. solanacearum phylotype II could be split in two groups (IIA and IIB), from which IIB clustered in three subgroups (IIBa, IIBb and IIBc). This division by ANI was in accordance with MLSA. The IIB subgroups found by ANI and MLSA also differed in the number of SNPs in the primer and probe sites of various assays. An in-silico analysis of eight TaqMan and 11 conventional PCR assays was performed using the whole genome sequences. Based on this analysis several cases of potential false positives or false negatives can be expected upon the use of these assays for their intended target organisms. Two TaqMan assays and two PCR assays targeting the 16S rDNA sequence should be able to detect all phylotypes of the RSSC. We conclude that the increasing availability of whole genome sequences is not only useful for classification of strains, but also shows potential for selection and evaluation of clade specific nucleic acid-based amplification methods within the RSSC.

scholarly journals Development of a Rapid, Efficient, Intelligent and Cost-Saving Tool to Diagnose Pasteurella Multocida by Using Whole Genome Sequence and Genotypes of Pasteurella Multocida From Different Hosts

2020 ◽  
Author(s):  
Zhong Peng ◽  
Junyang Liu ◽  
Wan Liang ◽  
Fei Wang ◽  
Li Wang ◽  
...  
Keyword(s):  
Cost Saving ◽  
Host Species ◽  
Pasteurella Multocida ◽  
Epidemiological Studies ◽  
Whole Genome Sequence ◽  
Clinical Settings ◽  
Whole Genome ◽  
Genome Sequences ◽  
Host Tropism ◽  
Tropism Prediction

Abstract Background: Different typing systems including capsular genotyping, lipopolysaccharide (LPS) genotyping, multilocus sequence typing (MLST), and virulence genotyping based on the detection of different virulence factor-encoding gene (VFG) profiles have been applied to characterize Pasteurella multocida strains from different host species. However, these methods require much time and effort in laboratories. Particularly, relying on one of these methods is difficult to address the biology of P. multocida from host species. Recently, we found that assigning P. multocida strains according to the combination of their capsular, LPS, and MLST genotypes (marked as capsular genotype: LPS genotype: MLST genotype) could help address the biological characteristics of P. multocida circulation in multiple hosts. However, it is still lack of a rapid, efficient, intelligent and cost-saving tool to diagnose P. multocida according to this system. Results: We have developed an intelligent genotyping and host tropism prediction tool PmGT for P. multocida strains according to their whole genome sequences by using machine learning and web 2.0 technologies. By using this tool, the capsular genotypes, LPS genotypes, and MLST genotypes as well as the main VFGs of P. multocida isolates in different host species were determined based on whole genome sequences. The results revealed a closer association between the genotypes and pasteurellosis rather than between genotypes and host species. Finally, we also used PmGT to predict the host species of P. multocida strains with the same capsular: lipopolysaccharide: MLST genotypes. Conclusions: With the advent of high-quality, inexpensive DNA sequencing, this platform represents a more efficient and cost-saving tool for P. multocida diagnosis in both epidemiological studies and clinical settings.

scholarly journals Misclassification of a whole genome sequence reference defined by the Human Microbiome Project: a detrimental carryover effect to microbiome studies

2019 ◽  
Author(s):  
DJ Darwin R. Bandoy ◽  
B Carol Huang ◽  
Bart C. Weimer
Keyword(s):  
Human Microbiome ◽  
Human Microbiome Project ◽  
Outbreak Detection ◽  
Whole Genome Sequence ◽  
Reference Database ◽  
Whole Genome ◽  
Reference Species ◽  
Genome Sequences ◽  
Genome Homology ◽  
Microbiome Data

AbstractTaxonomic classification is an essential step in the analysis of microbiome data that depends on a reference database of whole genome sequences. Taxonomic classifiers are built on established reference species, such as the Human Microbiome Project database, that is growing rapidly. While constructing a population wide pangenome of the bacterium Hungatella, we discovered that the Human Microbiome Project reference species Hungatella hathewayi (WAL 18680) was significantly different to other members of this genus. Specifically, the reference lacked the core genome as compared to the other members. Further analysis, using average nucleotide identity (ANI) and 16s rRNA comparisons, indicated that WAL18680 was misclassified as Hungatella. The error in classification is being amplified in the taxonomic classifiers and will have a compounding effect as microbiome analyses are done, resulting in inaccurate assignment of community members and will lead to fallacious conclusions and possibly treatment. As automated genome homology assessment expands for microbiome analysis, outbreak detection, and public health reliance on whole genomes increases this issue will likely occur at an increasing rate. These observations highlight the need for developing reference free methods for epidemiological investigation using whole genome sequences and the criticality of accurate reference databases.

scholarly journals ExpansionHunter: a sequence-graph-based tool to analyze variation in short tandem repeat regions

2019 ◽  
Vol 35 (22) ◽  
pp. 4754-4756 ◽  
Author(s):  
Egor Dolzhenko ◽  
Viraj Deshpande ◽  
Felix Schlesinger ◽  
Peter Krusche ◽  
Roman Petrovski ◽  
...  
Keyword(s):  
Tandem Repeat ◽  
Broad Class ◽  
Source Code ◽  
Computational Method ◽  
Supplementary Information ◽  
Dna Repeats ◽  
Supplementary Data ◽  
Sequence Graph ◽  
Version 2.0 ◽  
Short Tandem

Abstract Summary We describe a novel computational method for genotyping repeats using sequence graphs. This method addresses the long-standing need to accurately genotype medically important loci containing repeats adjacent to other variants or imperfect DNA repeats such as polyalanine repeats. Here we introduce a new version of our repeat genotyping software, ExpansionHunter, that uses this method to perform targeted genotyping of a broad class of such loci. Availability and implementation ExpansionHunter is implemented in C++ and is available under the Apache License Version 2.0. The source code, documentation, and Linux/macOS binaries are available at https://github.com/Illumina/ExpansionHunter/. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Whole-proteome tree of life suggests a deep burst of organism diversity

2020 ◽  
Vol 117 (7) ◽  
pp. 3678-3686 ◽  
Author(s):  
JaeJin Choi ◽  
Sung-Hou Kim
Keyword(s):  
Information Theory ◽  
Genome Sequence ◽  
Tree Of Life ◽  
Whole Genome Sequence ◽  
Whole Genome ◽  
Genome Sequences ◽  
Alignment Free ◽  
Whole Transcriptome ◽  
Evolutionary Progression ◽  
Feature Frequency

An organism tree of life (organism ToL) is a conceptual and metaphorical tree to capture a simplified narrative of the evolutionary course and kinship among the extant organisms. Such a tree cannot be experimentally validated but may be reconstructed based on characteristics associated with the organisms. Since the whole-genome sequence of an organism is, at present, the most comprehensive descriptor of the organism, a whole-genome sequence-based ToL can be an empirically derivable surrogate for the organism ToL. However, experimentally determining the whole-genome sequences of many diverse organisms was practically impossible until recently. We have constructed three types of ToLs for diversely sampled organisms using the sequences of whole genome, of whole transcriptome, and of whole proteome. Of the three, whole-proteome sequence-based ToL (whole-proteome ToL), constructed by applying information theory-based feature frequency profile method, an “alignment-free” method, gave the most topologically stable ToL. Here, we describe the main features of a whole-proteome ToL for 4,023 species with known complete or almost complete genome sequences on grouping and kinship among the groups at deep evolutionary levels. The ToL reveals 1) all extant organisms of this study can be grouped into 2 “Supergroups,” 6 “Major Groups,” or 35+ “Groups”; 2) the order of emergence of the “founders” of all of the groups may be assigned on an evolutionary progression scale; 3) all of the founders of the groups have emerged in a “deep burst” at the very beginning period near the root of the ToL—an explosive birth of life’s diversity.

scholarly journals A Method to Detect Differential Gene Expression in Cross-Species Hybridization Experiments at Gene and Probe Level

2010 ◽  
Vol 3 ◽  
pp. BII.S3846 ◽  
Author(s):  
Ying Chen ◽  
Rebekah Wu ◽  
James Felton ◽  
David M. Rocke ◽  
Anu Chakicherla
Keyword(s):  
Gene Expression ◽  
Gene Set Analysis ◽  
Model Organisms ◽  
Whole Genome ◽  
Supplementary Data ◽  
Genome Sequences ◽  
Data Set ◽  
Gene Set ◽  
Level Data ◽  
Species Hybridization

Motivation Whole genome microarrays are increasingly becoming the method of choice to study responses in model organisms to disease, stressors or other stimuli. However, whole genome sequences are available for only some model organisms, and there are still many species whose genome sequences are not yet available. Cross-species studies, where arrays developed for one species are used to study gene expression in a closely related species, have been used to address this gap, with some promising results. Current analytical methods have included filtration of some probes or genes that showed low hybridization activities. But consensus filtration schemes are still not available. Results A novel masking procedure is proposed based on currently available target species sequences to filter out probes and study a cross-species data set using this masking procedure and gene-set analysis. Gene-set analysis evaluates the association of some priori defined gene groups with a phenotype of interest. Two methods, Gene Set Enrichment Analysis (GSEA) and Test of Test Statistics (ToTS) were investigated. The results showed that masking procedure together with ToTS method worked well in our data set. The results from an alternative way to study cross-species hybridization experiments without masking are also presented. We hypothesize that the multi-probes structure of Affymetrix microarrays makes it possible to aggregate the effects of both well-hybridized and poorly-hybridized probes to study a group of genes. The principles of gene-set analysis were applied to the probe-level data instead of gene-level data. The results showed that ToTS can give valuable information and thus can be used as a powerful technique for analyzing cross-species hybridization experiments. Availability Software in the form of R code is available at http://anson.ucdavis.edu/~ychen/cross-species.html Supplementary Data Supplementary data are available at http://anson.ucdavis.edu/~ychen/cross-species.html

scholarly journals TandemTools: mapping long reads and assessing/improving assembly quality in extra-long tandem repeats

2020 ◽  
Vol 36 (Supplement_1) ◽  
pp. i75-i83 ◽  
Author(s):  
Alla Mikheenko ◽  
Andrey V Bzikadze ◽  
Alexey Gurevich ◽  
Karen H Miga ◽  
Pavel A Pevzner
Keyword(s):  
Quality Assessment ◽  
Chromosome Segregation ◽  
Tandem Repeats ◽  
Supplementary Information ◽  
Supplementary Data ◽  
Assembly Quality ◽  
Cellular Processes ◽  
Long Reads ◽  
Long Read ◽  
Eukaryotic Genomes

Abstract Motivation Extra-long tandem repeats (ETRs) are widespread in eukaryotic genomes and play an important role in fundamental cellular processes, such as chromosome segregation. Although emerging long-read technologies have enabled ETR assemblies, the accuracy of such assemblies is difficult to evaluate since there are no tools for their quality assessment. Moreover, since the mapping of error-prone reads to ETRs remains an open problem, it is not clear how to polish draft ETR assemblies. Results To address these problems, we developed the TandemTools software that includes the TandemMapper tool for mapping reads to ETRs and the TandemQUAST tool for polishing ETR assemblies and their quality assessment. We demonstrate that TandemTools not only reveals errors in ETR assemblies but also improves the recently generated assemblies of human centromeres. Availability and implementation https://github.com/ablab/TandemTools. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Coagulase-Negative Staphylococci Pathogenomics

2019 ◽  
Vol 20 (5) ◽  
pp. 1215 ◽  
Author(s):  
Xavier Argemi ◽  
Yves Hansmann ◽  
Kevin Prola ◽  
Gilles Prévost
Keyword(s):  
Staphylococcus Aureus ◽  
Virulence Factors ◽  
Molecular Basis ◽  
Sequence Data ◽  
Commensal Bacteria ◽  
Whole Genome Sequence ◽  
Whole Genome ◽  
Genome Sequences ◽  
Coagulase Negative Staphylococci ◽  
Major Pathogens

Coagulase-negative Staphylococci (CoNS) are skin commensal bacteria. Besides their role in maintaining homeostasis, CoNS have emerged as major pathogens in nosocomial settings. Several studies have investigated the molecular basis for this emergence and identified multiple putative virulence factors with regards to Staphylococcus aureus pathogenicity. In the last decade, numerous CoNS whole-genome sequences have been released, leading to the identification of numerous putative virulence factors. Koch’s postulates and the molecular rendition of these postulates, established by Stanley Falkow in 1988, do not explain the microbial pathogenicity of CoNS. However, whole-genome sequence data has shed new light on CoNS pathogenicity. In this review, we analyzed the contribution of genomics in defining CoNS virulence, focusing on the most frequent and pathogenic CoNS species: S. epidermidis, S. haemolyticus, S. saprophyticus, S. capitis, and S. lugdunensis.

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