Uncovering novel bacterial and archaeal diversity: genomic insights from metagenome-assembled genomes in Cuatro Cienegas, Coahuila.

A comprehensive study was conducted in the Cuatro Ciénegas Basin (CCB) in Coahuila, Mexico, which is known for its diversity of microorganisms and unique physicochemical properties. The study focused on the "Archaean Domes" (AD) site in the CCB, which is characterized by an abundance of hypersaline, non-lithifying microbial mats. In AD, we analyzed the small domes and circular structures using metagenome assembly genomes (MAGs) with the aim of expanding our understanding of the prokaryotic tree of life by uncovering previously unreported lineages, as well as analyzing the diversity of bacteria and archaea in the CCB. A total of 325 MAGs were identified, including 48 Archaea and 277 Bacteria. Remarkably, 22 archaea and 104 bacteria could not be classified even at the genus level, highlighting the remarkable novel diversity of the CCB. Besides, AD site exhibited significant diversity at the phylum level, with Proteobacteria being the most abundant, followed by Desulfobacteria, Spirochaetes, Bacteroidetes, Nanoarchaeota, Halobacteriota, Cyanobacteria, Planctomycetota, Verrucomicrobiota, Actinomycetes and Chloroflexi. In Archaea, the monophyletic groups of MAGs belonged to the Archaeoglobi, Aenigmarchaeota, Candidate Nanoarchaeota, and Halobacteriota. Among Bacteria, monophyletic groups were also identified, including Spirochaetes, Proteobacteria, Planctomycetes, Actinobacteria, Verrucomicrobia, Bacteroidetes, Candidate Bipolaricaulota, Desulfobacteria, and Cyanobacteria. These monophyletic groups were possibly influenced by geographic isolation, as well as the extreme and fluctuating environmental conditions in the pond AD, such as stoichiometric imbalance of C:N:P of 122:42:1, fluctuating pH (5-9.8) and high salinity (5.28% to saturation).

Comparative evaluation of bioinformatic tools for virus-host prediction and their application to a highly diverse community in the Cuatro Ciénegas Basin, Mexico.

Due to the enormous diversity of non-culturable viruses, new viruses must be characterized using culture-independent techniques. The associated host is an important phenotypic feature that can be inferred from metagenomic viral contigs thanks to the development of several bioinformatic tools. Here, we compare the performance of recently developed virus-host prediction tools on a dataset of 1,046 virus-host pairs and then apply the best-performing tools to a metagenomic dataset derived from a highly diverse transiently hypersaline site known as the Archaean Domes (AD) within the Cuatro Ciénegas Basin, Coahuila, Mexico. Among host-dependent methods, alignment-based approaches had a precision of 66.07% and a sensitivity of 24.76%, while alignment-free methods had an average precision of 75.7% and a sensitivity of 57.5%. RaFAH, a virus-dependent alignment-based tool, had the best overall performance (F1_score = 95.7%). However, when predicting the host of AD viruses, methods based on public reference databases (such as RaFAH) showed lower inter-method agreement than host-dependent methods run against custom databases constructed from prokaryotes inhabiting AD. Methods based on custom databases also showed the greatest agreement between the source environment and the predicted host taxonomy, habitat, lifestyle, or metabolism. This highlights the value of including custom data when predicting hosts on a highly diverse metagenomic dataset, and suggests that using a combination of methods and qualitative validations related to the source environment and predicted host biology can increase the number of correct predictions. Finally, these predictions suggest that AD viruses infect halophilic archaea as well as a variety of bacteria that may be halophilic, halotolerant, alkaliphilic, thermophilic, oligotrophic, sulfate-reducing, or marine, which is consistent with the specific environment and the known geological and biological evolution of the Cuatro Ciénegas Basin and its microorganisms.

A rapid approach for sex assignment by RAD-seq using a reference genome.

Sex identification is a common objective in molecular ecology. While many vertebrates display sexual dimorphism, determining the sex can be challenging in certain situations, such as species lacking clear sex-related phenotypic characteristics or in studies using non-invasive methods. In these cases, DNA analyses serve as valuable tools not only for sex determination but also for validating sex assignment based on phenotypic traits. In this study, we developed a bioinformatic framework for sex assignment using genomic data obtained through GBS, and having an available closely related genome assembled at the chromosome level. Our method consists of two ad hoc indexes that rely on the different properties of the mammalian heteromorphic sex chromosomes. For this purpose, we mapped RAD-seq loci to a reference genome and then obtained missingness and coverage depth values for the autosomes and X and Y chromosomes of each individual. Our methodology successfully determined the sex of 165 fur seals that had been phenotypically sexed in a previous study and 40 sea lions sampled in a non-invasive way. Additionally, we evaluated the accuracy of each index in sequences with varying average coverage depths, with Index Y proving greater reliability and robustness in assigning sex to individuals with low-depth coverage. We believe that the approach presented here can be extended to any animal taxa with known heteromorphic XY/ZW sex chromosome systems and that it can tolerate various qualities of GBS sequencing data.