{"title":"A telomere-to-telomere gapless genome reveals SlPRR1 control of circadian rhythm and photoperiodic flowering in tomato.","authors":"Hui Liu, Jia-Qi Zhang, Jian-Ping Tao, Chen Chen, Li-Yao Su, Jin-Song Xiong, Ai-Sheng Xiong","doi":"10.1093/gigascience/giaf058","DOIUrl":null,"url":null,"abstract":"<p><p>Cultivated tomato (Solanum lycopersicum) is a major vegetable crop of high economic value that serves as an important model for studying flowering time in day-neutral plants. A complete, continuous, and gapless genome of cultivated tomato is essential for genetic research and breeding programs. Here, we report the construction of a telomere-to-telomere (T2T) gap-free genome of S. lycopersicum cv. VF36 using a combination of sequencing technologies. The 815.27-Mb T2T \"VF36\" genome contained 600.23 Mb of transposable elements. Through comparative genomics and phylogenetic analysis, we identified structural variations between the \"VF36\" and \"Heinz 1706\" genomes and found no evidence of a recent species-specific whole-genome duplication in the \"VF36\" tomato. Furthermore, a core circadian oscillator, SlPRR1, was identified, which peaked at night in a circadian rhythm. CRISPR/Cas9-mediated knockdown of SlPRR1 in tomatoes demonstrated that slprr1 mutant lines exhibited significantly earlier flowering under long-day condition than wild type. We present a hypothetical model of how SlPRR1 regulates flowering time and chlorophyll biosynthesis in response to photoperiod. This T2T genomic resource will accelerate the genetic improvement of large-fruited tomatoes, and the SlPRR1-related hypothetical model will enhance our understanding of the photoperiodic response in cultivated tomatoes, revealing a regulatory mechanism for manipulating flowering time.</p>","PeriodicalId":12581,"journal":{"name":"GigaScience","volume":"14 ","pages":""},"PeriodicalIF":11.8000,"publicationDate":"2025-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12218202/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"GigaScience","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1093/gigascience/giaf058","RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
引用次数: 0
Abstract
Cultivated tomato (Solanum lycopersicum) is a major vegetable crop of high economic value that serves as an important model for studying flowering time in day-neutral plants. A complete, continuous, and gapless genome of cultivated tomato is essential for genetic research and breeding programs. Here, we report the construction of a telomere-to-telomere (T2T) gap-free genome of S. lycopersicum cv. VF36 using a combination of sequencing technologies. The 815.27-Mb T2T "VF36" genome contained 600.23 Mb of transposable elements. Through comparative genomics and phylogenetic analysis, we identified structural variations between the "VF36" and "Heinz 1706" genomes and found no evidence of a recent species-specific whole-genome duplication in the "VF36" tomato. Furthermore, a core circadian oscillator, SlPRR1, was identified, which peaked at night in a circadian rhythm. CRISPR/Cas9-mediated knockdown of SlPRR1 in tomatoes demonstrated that slprr1 mutant lines exhibited significantly earlier flowering under long-day condition than wild type. We present a hypothetical model of how SlPRR1 regulates flowering time and chlorophyll biosynthesis in response to photoperiod. This T2T genomic resource will accelerate the genetic improvement of large-fruited tomatoes, and the SlPRR1-related hypothetical model will enhance our understanding of the photoperiodic response in cultivated tomatoes, revealing a regulatory mechanism for manipulating flowering time.
期刊介绍:
GigaScience seeks to transform data dissemination and utilization in the life and biomedical sciences. As an online open-access open-data journal, it specializes in publishing "big-data" studies encompassing various fields. Its scope includes not only "omic" type data and the fields of high-throughput biology currently serviced by large public repositories, but also the growing range of more difficult-to-access data, such as imaging, neuroscience, ecology, cohort data, systems biology and other new types of large-scale shareable data.