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Divya Sain

Researcher at University of California, Riverside

Publications -  6
Citations -  1751

Divya Sain is an academic researcher from University of California, Riverside. The author has contributed to research in topics: Comparative genomics & Genome. The author has an hindex of 5, co-authored 6 publications receiving 1504 citations.

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Comparative genomics reveals mobile pathogenicity chromosomes in Fusarium

Li-Jun Ma, +65 more
- 18 Mar 2010 - 
TL;DR: Comparison of genomes of three phenotypically diverse Fusarium species revealed lineage-specific genomic regions in F. oxysporum that include four entire chromosomes and account for more than one-quarter of the genome, putting the evolution of fungal pathogenicity into a new perspective.
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Shared Signatures of Parasitism and Phylogenomics Unite Cryptomycota and Microsporidia

TL;DR: The first Cryptomycotan genome is sequence and it is proposed that Cryptomycota and microsporidia share a common endoparasitic ancestor, with the clade unified by a chitinous cell wall used to develop turgor pressure in the infection process.
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Deciphering the uniqueness of Mucoromycotina cell walls by combining biochemical and phylogenomic approaches.

TL;DR: The uniqueness of the cell wall structure of the Mucoromycotina Rhizopus oryzae and Phycomyces blakesleeanus compared with the better characterized cell wall of the ascomycete Neurospora crassa is revealed and the presence of abundant fucose-based polysaccharides similar to algal fucoidans is uncovered.
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Comparative genomic analysis of the 'pseudofungus' Hyphochytrium catenoides.

TL;DR: Comparative genomics identified differences in the repertoire of genes associated with filamentous growth between the Fungi and the Pseudofungi, including differences in vesicle trafficking systems, cell-wall synthesis pathways and motor protein repertoire, demonstrating that unique cellular systems underpinned the convergent evolution of filamentous osmotrophic growth in these two eukaryotic groups.
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Detection of structural variation using target captured next-generation sequencing data for genetic diagnostic testing.

TL;DR: The SVs presented here can be used as a valuable resource for clinical research and diagnostics and illustrate NGS as a powerful tool for SV detection.