Unveiling potential virulence determinants in Vibrio isolates from Anadara tuberculosa through whole genome analyses

The genus Vibrio includes pathogenic bacteria able to cause disease in humans and aquatic organisms, leading to disease outbreaks and significant economic losses in the fishery industry. Despite much work on Vibrio in several marine organisms, no specific studies have been conducted on Anadara tuberculosa. This is a commercially important bivalve species, known as "piangua hembra," along Colombia's Pacific coast. Therefore, this study aimed to identify and characterize the genomes of Vibrio isolates obtained from A. tuberculosa. Bacterial isolates were obtained from 14 A. tuberculosa specimens collected from two locations along the Colombian Pacific coast, of which 17 strains were identified as Vibrio: V. parahaemolyticus (n = 12), V. alginolyticus (n = 3), V. fluvialis (n = 1), and V. natriegens (n = 1). Whole genome sequence of these isolates was done using Oxford Nanopore Technologies (ONT). The analysis revealed the presence of genes conferring resistance to β-lactams, tetracyclines, chloramphenicol, and macrolides, indicating potential resistance to these antimicrobial agents. Genes associated with virulence were also found, suggesting the potential pathogenicity of these Vibrio isolates, as well as genes for Type III Secretion Systems (T3SS) and Type VI Secretion Systems (T6SS), which play crucial roles in delivering virulence factors and in interbacterial competition. This study represents the first genomic analysis of bacteria within A. tuberculosa, shedding light on Vibrio genetic factors and contributing to a comprehensive understanding of the pathogenic potential of these Vibrio isolates.IMPORTANCEThis study presents the first comprehensive report on the whole genome analysis of Vibrio isolates obtained from Anadara tuberculosa, a bivalve species of great significance for social and economic matters on the Pacific coast of Colombia. Research findings have significant implications for the field, as they provide crucial information on the genetic factors and possible pathogenicity of Vibrio isolates associated with A. tuberculosa. The identification of antimicrobial resistance genes and virulence factors within these isolates emphasizes the potential risks they pose to both human and animal health. Furthermore, the presence of genes associated with Type III and Type VI Secretion Systems suggests their critical role in virulence and interbacterial competition. Understanding the genetic factors that contribute to Vibrio bacterial virulence and survival strategies within their ecological niche is of utmost importance for the effective prevention and management of diseases in aquaculture practices.

Selection signatures and population dynamics of transposable elements in lima bean

The domestication process in lima bean (Phaseolus lunatus L.) involves two independent events, within the Mesoamerican and Andean gene pools. This makes lima bean an excellent model to understand convergent evolution. The mechanisms of adaptation followed by Mesoamerican and Andean landraces are largely unknown. Genes related to these adaptations can be selected by identification of selective sweeps within gene pools. Previous genetic analyses in lima bean have relied on Single Nucleotide Polymorphism (SNP) loci, and have ignored transposable elements (TEs). Here we show the analysis of whole-genome sequencing data from 61 lima bean accessions to characterize a genomic variation database including TEs and SNPs, to associate selective sweeps with variable TEs and to predict candidate domestication genes. A small percentage of genes under selection are shared among gene pools, suggesting that domestication followed different genetic avenues in both gene pools. About 75% of TEs are located close to genes, which shows their potential to affect gene functions. The genetic structure inferred from variable TEs is consistent with that obtained from SNP markers, suggesting that TE dynamics can be related to the demographic history of wild and domesticated lima bean and its adaptive processes, in particular selection processes during domestication.

New algorithms for accurate and efficient de novo genome assembly from long DNA sequencing reads

Building de novo genome assemblies for complex genomes is possible thanks to long-read DNA sequencing technologies. However, maximizing the quality of assemblies based on long reads is a challenging task that requires the development of specialized data analysis techniques. We present new algorithms for assembling long DNA sequencing reads from haploid and diploid organisms. The assembly algorithm builds an undirected graph with two vertices for each read based on minimizers selected by a hash function derived from the k-mer distribution. Statistics collected during the graph construction are used as features to build layout paths by selecting edges, ranked by a likelihood function. For diploid samples, we integrated a reimplementation of the ReFHap algorithm to perform molecular phasing. We ran the implemented algorithms on PacBio HiFi and Nanopore sequencing data taken from haploid and diploid samples of different species. Our algorithms showed competitive accuracy and computational efficiency, compared with other currently used software. We expect that this new development will be useful for researchers building genome assemblies for different species.

Robust and efficient software for reference-free genomic diversity analysis of genotyping-by-sequencing data on diploid and polyploid species

Genotyping-by-sequencing (GBS) is a widely used and cost-effective technique for obtaining large numbers of genetic markers from populations by sequencing regions adjacent to restriction cut sites. Although a standard reference-based pipeline can be followed to analyse GBS reads, a reference genome is still not available for a large number of species. Hence, reference-free approaches are required to generate the genetic variability information that can be obtained from a GBS experiment. Unfortunately, available tools to perform de novo analysis of GBS reads face issues of usability, accuracy and performance. Furthermore, few available tools are suitable for analysing data sets from polyploid species. In this manuscript, we describe a novel algorithm to perform reference-free variant detection and genotyping from GBS reads. Nonexact searches on a dynamic hash table of consensus sequences allow for efficient read clustering and sorting. This algorithm was integrated in the Next Generation Sequencing Experience Platform (NGSEP) to integrate the state-of-the-art variant detector already implemented in this tool. We performed benchmark experiments with three different empirical data sets of plants and animals with different population structures and ploidies, and sequenced with different GBS protocols at different read depths. These experiments show that NGSEP has comparable and in some cases better accuracy and always better computational efficiency compared to existing solutions. We expect that this new development will be useful for many research groups conducting population genetic studies in a wide variety of species.