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Peterson, D. G.

Publications and source records attributed to Peterson, D. G..

2 recordsLinked to original sources

The Gossypium longicalyx genome as a resource for cotton breeding and evolution

Cotton is an important crop that has made significant gains in production over the last century. Emerging pests such as the reniform nematode have threatened cotton production. The rare African diploid species Gossypium longicalyx is a wild species that has been used as an important source of reniform nematode immunity. While mapping and breeding efforts have made some strides in transferring this immunity to the cultivated polyploid species, the complexities of interploidal transfer combined with substantial linkage drag have inhibited progress in this area. Moreover, this species shares its most recent common ancestor with the cultivated A-genome diploid cottons, thereby providing insight into the evolution of long, spinnable fiber. Here we report a newly generated de novo genome assembly of G. longicalyx. This high-quality genome leveraged a combination of PacBio long-read technology, Hi-C chromatin conformation capture, and BioNano optical mapping to achieve a chromosome level assembly. The utility of the G. longicalyx genome for understanding reniform immunity and fiber evolution is discussed.

genomics

PAST: Pathway Association Studies Tool

BackgroundIn recent years, a bioinformatics method for interpreting GWAS data using metabolic pathway analysis has been developed and successfully used to find significant pathways and mechanisms explaining phenotypic traits of interest in plants. However, the many scripts implementing this method were not straightforward to use, had to be customized for each project, required user supervision, and took more than 24 hours to process data. PAST (Pathway Association Study Tool), a new implementation of this method, has been developed to address these concerns.\n\nResultsPAST is implemented as a package for the R language. Two user-interfaces are provided; PAST can be run by loading the package in R and calling its methods, or by using an R Shiny guided user interface. In testing, PAST completed analyses in approximately one hour by processing data in parallel. PAST has many user-specified options for maximum customization. PAST produces the same results as the previously developed method.\n\nConclusionsIn order to promote a powerful new method of pathway analysis that interprets GWAS data to find biological mechanisms associated with traits of interest, we developed a more accessible and user friendly tool. This tool is more efficient and requires less knowledge of programming languages to use than previous methods. Moreover, it produces similar results in significantly less time. These attributes make PAST accessible to researchers interested in associating metabolic pathways with GWAS datasets to better understand the genetic architecture and mechanisms affecting phenotype.

bioinformatics