Genomics and Bioinformatics Team | 2024 Progress Report

View the Genomics Team progress report including all tables and figures in pages 12 – 19 of the pdf version of this report.

Genomics and Bioinformatics Team members:
Zhangjun Fei (Boyce Thompson Institute)
Shan Wu (Boyce Thompson Institute)
Amnon Levi (USDA, ARS)
Yiqun Weng (USDA, ARS)
Michael Mazourek (Cornell University)
Jim McCreight (USDA, ARS)
Rebecca Grumet (Michigan State University)

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Super-pangenome for watermelon and its wild relatives

“The super-pangenome provides a valuable genetic toolkit for breeders and researchers to improve cultivated watermelon,” said Fei. “By understanding the genetic makeup and evolutionary patterns of watermelons, we can develop varieties with enhanced yield, increased disease resistance, and improved adaptability.”
The “super-pangenome” for watermelon and its wild relatives, the researchers hope, will uncover beneficial genes lost during domestication. Traits of interest affect seeds; rind thickness; fruit size, shape, texture, and sweetness; and improving disease resistance, which might lessen reliance on agrochemicals.

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CucCAP researchers assemble genomic tools to study the development of giant pumpkin fruit

Cucurbit fruits come in different shapes and sizes, controlled by genes underlying cell size and number. In a recent study, a team at West Virginia State University (WVSU) identified genetic factors underlying the giant fruit size of the mammoth group of Cucurbita maxima. The study elucidated genome diversity and identified single nucleotide polymorphism (SNP) markers associated with genes controlling fruit size. In addition to the genomic toolkit useful for breeding programs aiming at pumpkin fruit traits, this study provides insight into population differentiation and evolutionary origins of rare variants contributing to the giant fruit size of certain pumpkin varieties.

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Cucurbit Genomics Database version 2

Version 2 of the Cucurbit Genomics database (CuGenDBv2) was released in April 2022. Database users will notice improved speed and performance.The updated database includes 33 reference genomes from 26 cucurbit species/subspecies belonging to 10 different genera; novel functions for mining and analysis of large-scale variant data; and a comprehensive cucurbit expression atlas.

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