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Missaoui, A.

Publications and source records attributed to Missaoui, A..

2 recordsLinked to original sources

Genomic Characterization of Novel Endophyte Strains from Tall Fescue Shows Genome Fragmentation Post-Hybridization

Interspecific hybridization in fungi has gained attention for its role in fungal evolution and potential commercial applications. Successful hybridization can enhance fitness and facilitate adaptation to new ecological niches. However, the genomic consequences of hybridization in fungi remain poorly understood. Epichloe is a genus of fungi that includes both non-hybrid and hybrid species, with the hybrids forming through parasexual hybridization and reproducing asexually. Some Epichloe hybrids are of commercial significance, as they colonize Lolium arundinaceum (Schreb.) Darbysh., a crucial forage and turf grass species. In this study, we sought to generate high-quality genome assemblies for two previously uncharacterized Epichloe hybrid strains, both of which are similar to Epichloe sp. FaTG-3. We aimed to characterize their genomes and examine the effects of parasexual interspecific hybridization on fungal genome structure. Our results reveal that the genomes of both strains are rich in AT-rich blocks and repetitive elements. Upon comparison with putative progenitor genomes, we observed significant fragmentation and rearrangement. Despite the genomic instability, more than 85% of gene homologs from each progenitor species were retained. This study demonstrates that while parasexual hybridization dramatically alters genome structure, it does not significantly affect gene content.

genomics↗

RWRtoolkit: multi-omic network analysis using random walks on multiplex networks in any species

Leveraging the use of multiplex multi-omic networks, key insights into genetic and epigenetic mechanisms supporting biofuel production have been uncovered. Here, we introduce RWRtoolkit, a multiplex generation, exploration, and statistical package built for R and command line users. RWRtoolkit enables the efficient exploration of large and highly complex biological networks generated from custom experimental data and/or from publicly available datasets, and is species agnostic. A range of functions can be used to find topological distances between biological entities, determine relationships within sets of interest, search for topological context around sets of interest, and statistically evaluate the strength of relationships within and between sets. The command-line interface is designed for parallelisation on high performance cluster systems, which enables high throughput analysis such as permutation testing. Several tools in the package have also been made available for use in reproducible workflows via the KBase web application.

bioinformatics↗