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Shakya, P.

Publications and source records attributed to Shakya, P..

3 recordsLinked to original sources

A Chromosome-scale Reference Genome of Meloidogyne hapla reveals localized recombination hotspots enriched with Effector Proteins

Root-knot nematodes (Meloidogyne spp.) are among the most destructive agricultural pests that cause significant yield losses across a wide range of crops. Meloidogyne hapla, a diploid species, is a valuable model for studying root-knot nematodes due to its parasitic diversity, small genome, and a reproductive strategy that facilitates genetic analysis. Here, we present a high-quality chromosome-scale assembly of M. hapla, generated using multiple sequencing platforms-PacBio HiFi, ONT, Illumina and HiC. The 59 Mb assembly comprises 16 chromosome-length scaffolds, notably lacking canonical telomeric repeats. Instead, we identified a tandem 16-mer repeat mainly present at scaffold ends, suggesting an alternative system for chromosome-end maintenance. Genetic linkage analysis of F2 populations derived from crosses between M. hapla strains validated the assembly but also revealed anomalies indicating chromosome structure differences between parental isolates such as fissions, fusions, and rearrangements. This analysis also revealed sharply delineated zones of high recombination on most chromosome arms. We also identified 1,258 genes encoding putative secreted proteins (PSP), which should be enriched in genes involved in host interaction and pathogenicity. Most of the PSP genes had orthologs in other plant parasitic nematode species, and the majority were pioneers, lacking known functional domains. Notably, we found that PSPs are significantly enriched in high-recombination zones, possibly facilitating their rapid evolution. Overall, our study provides new insights into the genome structure of diploid root-knot nematodes and highlights the interplay between genome architecture, recombination, and parasitism. These findings raise new questions about how genetic and genomic adaptations drive the success of rootknot nematodes as plant parasites.

plant biology↗

Dynamic μ-PBWT: Dynamic Run-length Compressed PBWT for Biobank Scale Data

Durbins positional Burrows-Wheeler transform (PBWT) supports efficient haplotype matching and queries given a panel of haplotypes. It has been widely used for statistical phasing, imputation and identity-by-descent (IBD) detection. However, the original PBWT panel doesnt support dynamic updates when haplotypes need to be added or deleted from the panel. Dynamic-PBWT (d-PBWT) solved this problem but it is not memory efficient. While the memory constraint problem of the PBWT has been tackled by Syllable-PBWT and {micro}-PBWT, these are static data structures that do not allow updates. Additionally, Syllable-PBWT only supports long-match query and {micro}-PBWT only supports set-maximal match query, limiting their functionality in the compressed form. In this paper, we present Dynamic {micro}-PBWT (which can also be seen as compressed d-PBWT) that is memory efficient and supports dynamic updates. We run-length compress PBWT to achieve better compression rate and store the runs in the self-balancing trees to enable dynamic updates. We show that the number of updates per insertion or deletion in the tree at each site is constant regardless of the number of haplotypes in the panel and the updates can be made without decompressing the index. In addition, we use orders of magnitude less memory than d-PBWT. We also provide a long match query algorithm that can easily be extended back to the original {micro}-PBWT. Overall, the flexibility and space-efficiency of Dynamic {micro}-PBWT makes it a potential index data structure for biobank scale genetic data analyses. The source code for Dynamic {micro}-PBWT is available at https://github.com/ucfcbb/Dynamic-mu-PBWT.

bioinformatics↗

mcPBWT: Space-efficient Multi-column PBWT Scanning Algorithm for Composite Haplotype Matching

Positional Burrows-Wheeler Transform (PBWT) is a data structure that supports efficient algorithms for finding matching segments in a panel of haplotypes. It is of interest to study the composite patterns of multiple matching segments or blocks arranged contiguously along a same haplotype as they can indicate recombination crossover events, gene-conversion tracts, or, some-times, errors of phasing algorithms. However, current PBWT algorithms do not support search of such composite patterns efficiently. Here, we present our algorithm, mcPBWT (multi-column PBWT), that uses multiple synchronized runs of PBWT at different variant sites providing a "look-ahead" information of matches at those variant sites. Such "look-ahead" information allows us to analyze multiple contiguous matching pairs in a single pass. We present two specific cases of mcPBWT, namely double-PBWT and triple-PBWT which utilize two and three columns of PBWT respectively. double-PBWT finds two matching pairs combinations representative of crossover event or phasing error while triple-PBWT finds three matching pairs combinations representative of gene-conversion tract.

bioinformatics↗