INVERTER: INtegrated Variable numbER Tandem rEpeat findeR

Analysis of the Taxonomy and Pathogenic Factors of Pectobacterium aroidearum L6 Using Whole-Genome Sequencing and Comparative Genomics

Soft rot pectobacteria are devastating plant pathogens with a global distribution and a broad host range. Pectobacterium aroidearum L6, previously isolated from leaves of Syngonium podophyllum, is a pectolytic bacterial pathogen that causes typical soft rot on S. podophyllum. There is a shortage for genome data of P. aroidearum, which seriously hinders research on classification and pathogenesis of Pectobacterium. We present here the complete genome sequence of P. aroidearum L6. The L6 strain carries a single 4,995,896-bp chromosome with 53.10% G + C content and harbors 4,306 predicted protein-coding genes. We estimated in silico DNA-DNA hybridization and average nucleotide identity values in combination with the whole-genome-based phylogeny from 19 Pectobacterium strains including P. aroidearum L6. The results showed that L6 and PC1 formed a population distinct from other populations of the Pectobacterium genus. Phylogenetic analysis based on 16S rRNA and genome sequences showed a close evolutionary relationship among Pectobacterium species. Overall, evolutionary analysis showed that L6 was in the same branch with PC1. In comparison with 18 Pectobacterium spp. reference pathogens, strain L6 had 2,712 gene families, among which 1,632 gene families were identified as orthologous to those strains, as well as 1 putative unique gene family. We discovered 478 genes, 10.4% of the total of predicted genes, that were potentially related to pathogenesis using the Virulence Factors of Pathogenic Bacteria database. A total of 25 genes were related to toxins, 35 encoded plant cell-wall degrading enzymes, and 122 were involved in secretion systems. This study provides a foundation for a better understanding of the genomic structure of P. aroidearum and particularly offers information for the discovery of potential pathogenic factors and the development of more effective strategies against this pathogen.

Decoding first complete chloroplast genome of toothbrush tree (Salvadora persica L.): insight into genome evolution, sequence divergence and phylogenetic relationship within Brassicales

BACKGROUND

Salvadora persica L. (Toothbrush tree - Miswak; family-Salvadoraceae) grows in the arid-land ecosystem and possesses economic and medicinal importance. The species, genus and the family have no genomic datasets available specifically on chloroplast (cp) genomics and taxonomic evolution. Herein, we have sequenced the complete chloroplast genome of S. persica for the first time and compared it with 11 related specie's cp genomes from the order Brassicales.

RESULTS

The S. persica cp genome was 153,379 bp in length containing a sizeable single-copy region (LSC) of 83,818 bp which separated from the small single-copy region (SSC) of 17,683 bp by two inverted repeats (IRs) each 25,939 bp. Among these genomes, the largest cp genome size (160,600 bp) was found in M. oleifera, while in S. persica it was the smallest (153,379 bp). The cp genome of S. persica encoded 131 genes, including 37 tRNA genes, eight rRNA genes and 86 protein-coding genes. Besides, S. persica contains 27 forward, 36 tandem and 19 palindromic repeats. The S. persica cp genome had 154 SSRs with the highest number in the LSC region. Complete cp genome comparisons showed an overall high degree of sequence resemblance between S. persica and related cp genomes. Some divergence was observed in the intergenic spaces of other species. Phylogenomic analyses of 60 shared genes indicated that S. persica formed a single clade with A. tetracantha with high bootstrap values. The family Salvadoraceae is closely related to Capparaceae and Petadiplandraceae rather than to Bataceae and Koberliniacaea.

CONCLUSION

The current genomic datasets provide pivotal genetic resources to determine the phylogenetic relationships, genome evolution and future genetic diversity-related studies of S. persica in complex angiosperm families.

Dot2dot: accurate whole-genome tandem repeats discovery

MOTIVATION

Large-scale sequencing projects have confirmed the hypothesis that eukaryotic DNA is rich in repetitions whose functional role needs to be elucidated. In particular, tandem repeats (TRs) (i.e. short, almost identical sequences that lie adjacent to each other) have been associated to many cellular processes and, indeed, are also involved in several genetic disorders. The need of comprehensive lists of TRs for association studies and the absence of a computational model able to capture their variability have revived research on discovery algorithms.

RESULTS

Building upon the idea that sequence similarities can be easily displayed using graphical methods, we formalized the structure that TRs induce in dot-plot matrices where a sequence is compared with itself. Leveraging on the observation that a compact representation of these matrices can be built and searched in linear time, we developed Dot2dot: an accurate algorithm fast enough to be suitable for whole-genome discovery of TRs. Experiments on five manually curated collections of TRs have shown that Dot2dot is more accurate than other established methods, and completes the analysis of the biggest known reference genome in about one day on a standard PC.

AVAILABILITY AND IMPLEMENTATION

Source code and datasets are freely available upon paper acceptance at the URL: https://github.com/Gege7177/Dot2dot.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

A bioinformatics approach to identify telomere sequences

Conventional approaches to identify a telomere motif in a new genome are laborious and time-intensive. An efficient new methodology based on next-generation sequencing (NGS), de novo sequence repeat finder (SERF) and fluorescence in situ hybridization (FISH) is presented. Unlike existing heuristic approaches, SERF utilizes an exhaustive analysis of raw NGS reads or assembled contigs for rapid de novo detection of conserved tandem repeats representing telomere motifs. SERF was validated using the NGS data from Ipheion uniflorum and Allium cepa with known telomere motifs. The analysis program was then used on NGS data to investigate the telomere motifs in several additional plant species and together with FISH proved to be an efficient approach to identify as yet unknown telomere motifs.

A new way to visualize DNA's base succession: the Caenorhabditis elegans chromosome landscapes

In the eukaryotic genomes, the genetic diseases are generally associated with the tandem repeats. These repeats seem to appear frequently. In this paper, we are describing a wavelet transform technique which provides a new way to represent the DNA succession bases as a DNA progression images. These images offer DNA landscapes, visualizing and following up periodicities through genomes. We investigated in a structural coding technique the Pnuc. Then, we illustrated, with time-frequency representation, the existence and the superposition of the periodicities in some biological features, their locations and the different ways in which they appear. The representations generated showed that one periodicity can sometimes be alone, but generally, it is incorporated to others. These periodicities associations create, in the Caenorhabditis elegans chromosome, a precise structural image of biological features, such as CeRep, Helitrons, repeats and satellites.

Review of tandem repeat search tools: a systematic approach to evaluating algorithmic performance

The prevalence of tandem repeats in eukaryotic genomes and their association with a number of genetic diseases has raised considerable interest in locating these repeats. Over the last 10-15 years, numerous tools have been developed for searching tandem repeats, but differences in the search algorithms adopted and difficulties with parameter settings have confounded many users resulting in widely varying results. In this review, we have systematically separated the algorithmic aspect of the search tools from the influence of the parameter settings. We hope that this will give a better understanding of how the tools differ in algorithmic performance, their inherent constraints and how one should approach in evaluating and selecting them.