ArticleData in brief2023
Long-reads-based transcriptome dataset from leaves of lime,
Article in Data in brief, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
2 citing papers in PubMed, 3 citations in OpenAlex.
- Transcriptome dataset of gall-rust infected Sengon (Data in brief · 2024Article
- Long-reads-based transcriptome dataset from leaves of lime,Data in brief · 2023Article
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Authors and funding
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The lime plant is a horticultural plant that grows in tropical regions. One of the cultivation maintenances to increase the production of lime fruits is pruning. However, the pruning technique of lime requires high production costs. In addition, phytohormones such as ethylene and abscisic acid have regulation to help drop leaves and branches. The study aimed to identify genes in lime involved in the self-pruning process during ethephon and abscisic acid treatments. Total RNA was extracted and subjected to long-read sequencing using a PCR-cDNA sequencing kit, Oxford Nanopore Technologies. The transcripts were produced 5,914 using the RATTLE program and ranged from 201 - 8,156 bp, and N50 was 1,292 bp. The RNA-seq dataset is available as a raw sequence read that scientists can further process and analyze, and this data can be helpful for lime breeding programs that can shed branches and leaves.
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Registered trials
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