Biology subjects

Mazloom, R.

Publications and source records attributed to Mazloom, R..

5 recordsLinked to original sources

bioRxiv2026

genomeRxiv: a genome-based identification web server that bridges the gap between taxonomy and strain typing

Precise identification depends on highly resolved classification. Therefore, whole genome-based strain typing schemes have been implemented for identification of the most important microbial human pathogens. However, there are no dedicated typing schemes for the majority of prokaryotic human, animal, and plant pathogens, or for non-pathogenic microbes, often limiting their identification to taxonomic classification tools that have the species as the smallest unit. To address this deficiency, we created the genomeRxiv web server which contains over 350,000 genomes and leverages the average nucleotide identity (ANI)-based Life Identification Number (LIN) approach, allowing users to identify prokaryotic genomes in real time from approximately genus-rank to near strain-level resolution. LINs are overlaid with circumscriptions of species and infraspecies classes, integrating taxonomy with strain typing. Metadata and distance trees are visualized to complement inferred phylogenetic relationships with epidemiological and ecological information. A command line tool is provided for users to upload k-mer sketches of unpublished genomes and associated metadata, facilitating epidemiological investigations without the need to share complete DNA sequences. In conclusion, genomeRxiv constitutes a much-needed resource for precise, rapid identification of the many prokaryotes not included in any pathogen-specific typing scheme.

bioinformatics↗

bioRxiv2026

Whole genome similarity provides a rapid, robust framework for classification of fungal taxa from the genus rank to intraspecies variants

Rapid and accurate microbial identification is critical for interpreting biological data in basic research and when making applied decisions on how to effectively treat patients and control human, animal, and plant diseases. Advancements in high-throughput sequencing have the potential to expedite fungal species identification and thus fungal biological research; however, analyses of ever-increasing numbers of genomes also present computational challenges. In this work, we evaluated how whole-genome similarity can serve as the basis for accurate classification and identification across the Kingdom Fungi and the Phylum Oomycota. Results from the computationally efficient k-mer-based tool sourmash are compared with those from more computationally demanding BLAST-based similarity method ANIb, as well as with conventional phylogenomic approaches, including maximum-likelihood concatenated ortholog trees and SNP-based methods. We observed that sourmash delivers orders-of-magnitude gains in speed and memory efficiency while maintaining strong concordance with phylogenomic methods. We found that a k-mer size of 21 is robust for genus and species determination, and that larger k-mers are well-suited for identification below the species rank. These results demonstrate that k-mer-based whole-genome similarity provides a scalable framework for fungal classification, enabling rapid analysis, lowering computational and bioinformatic barriers, and supporting the development of efficient identification pipelines.

bioinformatics↗

bioRxiv2024

Genotypic and Phenotypic Analyses Show Ralstonia solanacearum Cool Virulence is a Quantitative Trait Not Restricted to 'Race 3 biovar 2'

Most Ralstonia solanacearum species complex strains cause bacterial wilts in tropical or subtropical zones, but the group known as Race 3 biovar 2 (R3bv2) is cool virulent and causes potato brown rot at lower temperatures. R3bv2 has invaded potato-growing regions around the world but is not established in the United States. Phylogenetically, R3bv2 corresponds to a subset of the R. solanacearum phylotype IIB clade, but little is known about the distribution of the cool virulence phenotype within phylotype IIB. Therefore, genomes of 76 potentially cool virulent phylotype IIB strains and 30 public genomes were phylogenetically analyzed. A single clonal lineage within the sequevar 1 subclade of phylotype IIB that originated in South America has caused nearly all brown rot outbreaks worldwide. To correlate genotypes with relevant phenotypes, we quantified virulence of ten Ralstonia strains on tomato and potato at both 22{degrees}C and 28{degrees}C. Cool virulence on tomato did not predict cool virulence on potato. We found that cool virulence is a quantitative trait. Strains in the sequevar 1 pandemic clonal lineage caused the most disease, while other R3bv2 strains were only moderately cool virulent. However, some non-R3bv2 strains were highly cool virulent and aggressively colonized potato tubers. Thus, cool virulence is not consistently correlated with strains historically classified as R3bv2 group. To aid detection of sequevar 1 strains, this group was genomically delimited in the LINbase web server and a sequevar 1 diagnostic primer pair was developed and validated. We discuss implications of these results for the R3bv2 definition.

microbiology↗

bioRxiv2021

Meta Analysis of the Ralstonia solanacearum species complex (RSSC) based on comparative evolutionary genomics and reverse ecology

Ralstonia solanacearum species complex (RSSC) strains are bacteria that colonize plant xylem and cause vascular wilt diseases. However, individual strains vary in host range, optimal disease temperatures, and physiological traits. To increase our understanding of the evolution, diversity, and biology of the RSSC, we performed a meta-analysis of 100 representative RSSC genomes. These 100 RSSC genomes contain 4,940 genes on average, and a pangenome analysis found that there are 3,262 genes in the core genome ([~]60% of the mean RSSC genome) with 13,128 genes in the extensive flexible genome. Although a core genome phylogenetic tree and a genome similarity matrix aligned with the previously named species (R. solanacearum, R. pseudosolanacearum, R. syzygii) and phylotypes (I-IV), these analyses also highlighted an unrecognized sub-clade of phylotype II. Additionally, we identified differences between phylotypes with respect to gene content and recombination rate, and we delineated population clusters based on the extent of horizontal gene transfer. Multiple analyses indicate that phylotype II is the most diverse phylotype, and it may thus represent the ancestral group of the RSSC. Additionally, we also used our genome-based framework to test whether the RSSC sequence variant (sequevar) taxonomy is a robust method to define within-species relationships of strains. The sequevar taxonomy is based on alignments of a single conserved gene (egl). Although sequevars in phylotype II describe monophyletic groups, the sequevar system breaks down in the highly recombinogenic phylotype I, which highlights the need for an improved cost-effective method for genotyping strains in phylotype I. Finally, we enabled quick and precise genome-based identification of newly sequenced Ralstonia strains by assigning Life Identification Numbers (LINs) to the 100 strains and by circumscribing the RSSC and its sub-groups in the LINbase Web service. IMPACT STATEMENTThe Ralstonia solanacearum species complex (RSSC) includes dozens of economically important pathogens of many cultivated and wild plants. The extensive genetic and phenotypic diversity that exists within the RSSC has made it challenging to subdivide this group into meaningful subgroups with relevance to plant disease control and plant biosecurity. This study provides a solid genome-based framework for improved classification and identification of the RSSC by analyzing one hundred representative RSSC genome sequences with a suite of comparative evolutionary genomic tools. The results also lay the foundation for additional in-depth studies to gain further insights into evolution and biology of this heterogeneous complex of destructive plant pathogens. DATA SUMMARYThe authors confirm that all raw data and code and protocols have been provided within the manuscript. All publicly available sequencing data used for analysis have been supplemented with accession numbers to access the data. The assembled genome of strain 19-3PR_UW348 was submitted to NCBI under Bioproject PRJNA775652 Biosample SAMN22612291. This Whole Genome Shotgun project has been deposited at GenBank under the accession JAJMMU000000000. The version described in this paper is version JAJMMU010000000.

genomics↗

bioRxiv2020

Single-molecule sequencing of long DNA molecules allows high contiguity de novo genome assembly for the fungus fly, Sciara coprophila

The lower Dipteran fungus fly, Sciara coprophila, has many unique biological features. For example, Sciara undergoes paternal chromosome elimination and maternal X chromosome nondisjunction during spermatogenesis, paternal X elimination during embryogenesis, intrachromosomal DNA amplification of DNA puff loci during larval development, and germline-limited chromosome elimination from all somatic cells. Paternal chromosome elimination in Sciara was the first observation of imprinting, though the mechanism remains a mystery. Here, we present the first draft genome sequence for Sciara coprophila to take a large step forward in aiding these studies. We approached assembling the Sciara genome using multiple sequencing technologies: PacBio, Oxford Nanopore MinION, and Illumina. To find an optimal assembly using these datasets, we generated 44 Illumina assemblies using 7 short-read assemblers and 50 long-read assemblies of PacBio and MinION sequence data using 6 long-read assemblers. We ranked assemblies using a battery of reference-free metrics, and scaffolded a subset of the highest-ranking assemblies using BioNano Genomics optical maps. RNA-seq datasets from multiple life stages and both sexes facilitated genome annotation. Moreover, we anchored nearly half of the Sciara genome sequence into chromosomes. Finally, we used the signal level of both the PacBio and Oxford Nanopore data to explore the presence or absence of DNA modifications in the Sciara genome since DNA modifications may play a role in imprinting in Sciara, as they do in mammals. These data serve as the foundation for future research by the growing community studying the unique features of this emerging model system.

genomics↗