VCF file of multiple single-cyst-derived Ro1 and Ro2 lines of New York fields on Globodera rostochiensis genome
Cite this dataset
Wang, Xiaohong et al. (2020). VCF file of multiple single-cyst-derived Ro1 and Ro2 lines of New York fields on Globodera rostochiensis genome [Dataset]. Dryad. https://doi.org/10.5061/dryad.rxwdbrv6b
The potato cyst nematode, Globodera rostochiensis, is a regulated pest posing a serious threat to potato production worldwide. Although the endemic pathotype (Ro1) of G. rostochiensis has been confined to New York State for several decades as a result of quarantine regulations and management with resistant potato cultivars, a virulent pathotype, Ro2, has emerged, for which control measures are scarce. The ability to detect Ro2 early in fields is necessary to sustain the success of G. rostochiensis quarantine in the US. Here, we report the comparative analysis of whole-genome sequences of multiple single-cyst-derived Ro1 and Ro2 lines, propagated from original field populations. The identified discriminant variants are good targets for developing molecular diagnostic tools for differentiating G. rostochiensis pathotypes in NY.
DNA extractions of twenty cysts per population of New York Globodera rostochiensis Ro1/Ro2 lines. TruSeq DNA library construction and Illumina NextSeq500 sequencing were performed at Cornell Institute of Biotechnology. Sequencing reads were trimmed with Trimmomatic v0.36 (Bolger et al. 2014) to a minimum length of 50 bp and a minimum Phred quality score of 20. Unpaired reads were discarded and the remaining sequences were aligned to the G. rostochiensis reference genome nGr.v1.1 (Eves-van den Akker et al. 2016) using BWA-MEM v0.7.12 (Li et al. 2009). Variants were identified using FreeBayes v1.2.0 (Garrison and Marth 2012) with minimum mapping quality set at 30, minimum base quality at 20, minimum alternate count at 2, minimum alternate fraction at 0.05. Additional filters were applied to keep only the variant calls with a minimum coverage of 5 in each of the 55 lines and no missing data.
United States Department of Agriculture, Award: 2014-07639