Du, W., Xia, L., Li, R., Zhao, X., Jin, D., Wang, X., Pei, Y., Zhou, R., Chen, J., & Yu, X. (2024). Updated Gene Prediction of Cucumber Genome through Manual Annotation. Preprints. https://doi.org/10.20944/preprints202404.1323.v1
Chicago/Turabian Style
Du, W., Jinfeng Chen and Xiaqing Yu. 2024 "Updated Gene Prediction of Cucumber Genome through Manual Annotation" Preprints. https://doi.org/10.20944/preprints202404.1323.v1
Abstract
Thorough and precise gene structure annotations are essential for maximizing the benefits of genomic data and unveiling valuable genetic insights. The cucumber genome was first released in 2009 and updated in 2019. To increase the accuracy of predicted gene models, 64 published RNA-seq data and 9 new strand-specific RNA-seq data from multiple tissues were used for manual comparison with the gene models. The updated annotation file (version 2.0) contains increased 24,145 predicted genes from previous version (24317 genes) with a higher BUSCO value of 96.9%. 6231 and 1490 transcripts were adjusted and newly added, respectively, accounting for 31.99% of the overall gene tally. These newly added and adjust genes were renamed (CsaV3.1_XGXXXXX), while genes remaining unaltered preserve their original des ignations. A random selection of 21 modified/added genes were validated using RT-PCR analyses. Additionally, tissue-specific patterns of gene expression were examined using newly obtained transcriptome data with the revised gene prediction model. This improved annotation of cucumber genome will provide essential and accurate resources for studies in cucumber.
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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