The presence of intermittently dispersed insertion sequences and transposases in the Mycobacterium tuberculosis (Mtb) genome makes intra-genome recombination events inevitable. Understanding their effect on the gene repertoires (GR), which may contribute to the development of drug-resistant Mtb, is critical. In this study, publicly available WGS data of clinical Mtb isolates (endemic region n = 2,601; non-endemic region n = 1,130) were de novo assembled, filtered, scaffolded into assemblies, and functionally annotated. Out of 2,601 Mtb WGS data sets from endemic regions, 2,184 (drug resistant/sensitive: 1,386/798) qualified as high quality. We identified 3,784 core genes, 123 softcore genes, 224 shell genes, and 762 cloud genes in the pangenome of Mtb clinical isolates from endemic regions. Sets of 33 and 39 genes showed positive and negative associations (P < 0.01) with drug resistance status, respectively. Gene ontology clustering showed compromised immunity to phages and impaired DNA repair in drug-resistant Mtb clinical isolates compared to the sensitive ones. Multidrug efflux pump repressor genes (Rv3830c and Rv3855c) and CRISPR genes (Rv2816c-19c) were absent in the drug-resistant Mtb. A separate WGS data analysis of drug-resistant Mtb clinical isolates from the Netherlands (n = 1130) also showed the absence of CRISPR genes (Rv2816c-17c). This study highlights the role of CRISPR genes in drug resistance development in Mtb clinical isolates and helps in understanding its evolutionary trajectory and as useful targets for diagnostics development.IMPORTANCEThe results from the present Pan-GWAS study comparing gene sets in drug-resistant and drug-sensitive Mtb clinical isolates revealed intricate presence-absence patterns of genes encoding DNA-binding proteins having gene regulatory as well as DNA modification and DNA repair roles. Apart from the genes with known functions, some uncharacterized and hypothetical genes that seem to have a potential role in drug resistance development in Mtb were identified. We have been able to extrapolate many findings of the present study with the existing literature on the molecular aspects of drug-resistant Mtb, further strengthening the relevance of the results presented in this study.

Arbuscular mycorrhizal (AM) fungi are ubiquitous endosymbionts of terrestrial plants. It helps plants to extract more nutrients from the soil and enhances the plant tolerance to various ecological stress factors. The AM fungal genome sequence helps to identify the gene repertoires that are crucial for adaptation to different habitat and mechanisms for interaction with host plant. The present work comprises the first draft of the genome sequence of Rhizophagus proliferus, which is an important AM species present in biofertilizer consortia for agricultural purpose. The estimated genome size of R. proliferus is ~ 110 Mbps and its genomic assembly is 94.35% complete. Genome mining was carried out to identify putative gene families important for biological functions. A total of 22,526 protein-coding genes were estimated in the genome, with an abundance of kinases and reduced number of glycoside hydrolases as compared to other fungal classes. A striking finding in the R. proliferus genome was higher number of carbohydrate esterases (CE), which may suggest towards presence of higher saprotrophic activity in this species as compared to the previously reported AM fungi, which may indicate towards its role as a link between plants and soil mineral nutrients. The genome sequence and annotation of R. proliferus presented here would serve as an important reference for functional genomics studies required for developing biofertilizer formulations in future. In addition, the findings from this work may also prove important in deciphering molecular mechanisms in AM fungi that govern the host-specific interaction and associated agriculture benefits.

Knowledge of population-level processes is essential to understanding the efficacy of selection operating within a species. However, attempts at estimating effective population sizes (Ne) are particularly challenging in bacteria due to their extremely large census populations sizes, varying rates of recombination and arbitrary species boundaries.
In this study, we estimated Ne for 153 species (152 bacteria and one archaeon) defined under a common framework and found that ecological lifestyle and growth rate were major predictors of Ne; and that contrary to theoretical expectations, Ne was unaffected by recombination rate. Additionally, we found that Ne shapes the evolution and diversity of total gene repertoires of prokaryotic species.
Together, these results point to a new model of genome architecture evolution in prokaryotes, in which pan-genome sizes, not individual genome sizes, are governed by drift-barrier evolution.

The comparison of gene and genome structures across species has the potential to reveal major trends of genome evolution. However, such a comparative approach is currently hampered by a lack of standardization (e.g., Elliott TA, Gregory TR, Philos Trans Royal Soc B: Biol Sci 370:20140331, 2015). For example, testing the hypothesis that the total amount of coding sequences is a reliable measure of potential proteome diversity (Wang M, Kurland CG, Caetano-Anollés G, PNAS 108:11954, 2011) requires the application of standardized definitions of coding sequence and genes to create both comparable and comprehensive data sets and corresponding summary statistics. However, such standard definitions either do not exist or are not consistently applied. These circumstances call for a standard at the descriptive level using a minimum of parameters as well as an undeviating use of standardized terms, and for software that infers the required data under these strict definitions. The acquisition of a comprehensive, descriptive, and standardized set of parameters and summary statistics for genome publications and further analyses can thus greatly benefit from the availability of an easy to use standard tool.
We developed a new open-source command-line tool, COGNATE (Comparative Gene Annotation Characterizer), which uses a given genome assembly and its annotation of protein-coding genes for a detailed description of the respective gene and genome structure parameters. Additionally, we revised the standard definitions of gene and genome structures and provide the definitions used by COGNATE as a working draft suggestion for further reference. Complete parameter lists and summary statistics are inferred using this set of definitions to allow down-stream analyses and to provide an overview of the genome and gene repertoire characteristics. COGNATE is written in Perl and freely available at the ZFMK homepage ( https://www.zfmk.de/en/COGNATE ) and on github ( https://github.com/ZFMK/COGNATE ).
The tool COGNATE allows comparing genome assemblies and structural elements on multiples levels (e.g., scaffold or contig sequence, gene). It clearly enhances comparability between analyses. Thus, COGNATE can provide the important standardization of both genome and gene structure parameter disclosure as well as data acquisition for future comparative analyses. With the establishment of comprehensive descriptive standards and the extensive availability of genomes, an encompassing database will become possible.