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Through an extensive literature survey, we have upgraded the Leaf Senescence Database (LSD v5.0; https://ngdc.cncb.ac.cn/lsd/), a curated repository of comprehensive senescence-associated genes (SAGs) and their corresponding mutants. Since its inception in 2010, LSD undergoes frequent updates to encompass the latest advances in leaf senescence research and its current version comprises a high-quality collection of 31,740 SAGs and 1,209 mutants from 148 species, which were manually searched based on robust experimental evidence and further categorized according to their functions in leaf senescence. Furthermore, LSD was greatly enriched with comprehensive annotations for the SAGs through meticulous curation using both manual and computational methods. In addition, it was equipped with user-friendly web interfaces that facilitate text queries, BLAST searches, and convenient download of SAG sequences for localized analysis. Users can effortlessly navigate the database to access a plethora of information, including literature references, mutants, phenotypes, multi-omics data, miRNA interactions, homologs in other plants, and cross-links to various databases. Taken together, the upgraded version of LSD stands as the most comprehensive and informative plant senescence-related database to date, incorporating the largest collection of SAGs and thus bearing great utility for a wide range of studies related to plant senescence.

The leaf senescence database (LSD) is a comprehensive resource of senescence-associated genes (SAGs) and their corresponding mutants. Through manual curation and extensive annotation, we updated the LSD to a new version LSD 3.0, which contains 5853 genes and 617 mutants from 68 species. To provide sustainable and reliable services for the plant research community, LSD 3.0 (https://bigd.big.ac.cn/lsd/) has been moved to and maintained by the National Genomics Data Center at Beijing Institute of Genomics, Chinese Academy of Sciences. In the current release, we added some new features: (i) Transcriptome data of leaf senescence in poplar were integrated; (ii) Leaf senescence-associated transcriptome data information in Arabidopsis, rice and soybean were included; (iii) Senescence-differentially expressed small RNAs (Sen-smRNA) in Arabidopsis were identified; (iv) Interaction pairs between Sen-smRNAs and senescence-associated transcription factors (Sen-TF) were established; (v) Senescence phenotypes of 90 natural accessions (ecotypes) and 42 images of ecotypes in Arabidopsis were incorporated; (vi) Mutant seed information of SAGs in rice obtained from Kitbase was integrated; (vii) New options of search engines for ecotypes and transcriptome data were implemented. Together, the updated database bears great utility to continue to provide users with useful resources for studies of leaf senescence.

Leaf senescence is the last phase of plant development and a highly coordinated process regulated by a large number of senescence-associated genes (SAGs). By broad literature survey, we constructed a leaf senescence database (LSD) in 2011 and updated it to Version 2.0 in 2014 ( http://www.eplantsenescence.org/ and http://psd.cbi.pku.edu.cn/ ) which contains a total of 5357 genes and 324 mutants from 44 species. These SAGs were retrieved based on genetic, genomic, proteomic, physiological, or other experimental evidence and were classified into different categories according to their functions in leaf senescence or morphological phenotype of mutants. To provide comprehensive information for SAGs, we made extensive annotation by both manual and computational approaches. In addition, we predicted putative orthologues of the SAGs in other species. LSD has a user-friendly interface to allow users to make text queries or BLAST searches and to download SAGs sequences for local analysis. Functional analyses of putative SAGs reveal that WRKY75, AZF2, NAC16, and WRKY26 are positive regulators of leaf senescence, while MKP2 and CTR1 perform negative regulation to leaf senescence. This database has been served as a valuable resource for basic research on the function of SAGs and evolution of plant leaf senescence, as well as for the exploration of genetic traits in agronomically important plants.

This manuscript describes an update of the leaf senescence database (LSD) previously featured in the 2011 NAR Database Issue. LSD provides comprehensive information concerning senescence-associated genes (SAGs) and their corresponding mutants. We have made extensive annotations for these SAGs through both manual and computational approaches. Recently, we updated LSD to a new version LSD 2.0 (http://www.eplantsenescence.org/), which contains 5356 genes and 322 mutants from 44 species, an extension from the previous version containing 1145 genes and 154 mutants from 21 species. In the current version, we also included several new features: (i) Primer sequences retrieved based on experimental evidence or designed for high-throughput analysis were added; (ii) More than 100 images of Arabidopsis SAG mutants were added; (iii) Arabidopsis seed information obtained from The Arabidopsis Information Resource (TAIR) was integrated; (iv) Subcellular localization information of SAGs in Arabidopsis mined from literature or generated from the SUBA3 program was presented; (v) Quantitative Trait Loci information was added with links to the original database and (vi) New options such as primer and miRNA search for database query were implemented. The updated database will be a valuable and informative resource for basic research of leaf senescence and for the manipulation of traits of agronomically important plants.

By broad literature survey, we have developed a leaf senescence database (LSD, http://www.eplantsenescence.org/) that contains a total of 1145 senescence associated genes (SAGs) from 21 species. These SAGs were retrieved based on genetic, genomic, proteomic, physiological or other experimental evidence, and were classified into different categories according to their functions in leaf senescence or morphological phenotypes when mutated. We made extensive annotations for these SAGs by both manual and computational approaches, and users can either browse or search the database to obtain information including literatures, mutants, phenotypes, expression profiles, miRNA interactions, orthologs in other plants and cross links to other databases. We have also integrated a bioinformatics analysis platform WebLab into LSD, which allows users to perform extensive sequence analysis of their interested SAGs. The SAG sequences in LSD can also be downloaded readily for bulk analysis. We believe that the LSD contains the largest number of SAGs to date and represents the most comprehensive and informative plant senescence-related database, which would facilitate the systems biology research and comparative studies on plant aging.