ArticlePloS one2018
RNA-seq transcriptome analysis of the immature seeds of two Brassica napus lines with extremely different thousand-seed weight to identify the candidate genes related to seed weight.
Article in PloS one, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 15 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
15 citing papers in PubMed, 1 synthesis or guideline pooled it, 23 citations in OpenAlex.
- Meta-analysis of seed weight QTLome using a consensus and highly dense genetic map in Brassica napus L.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2023Pooled it
- Combined BSA-seq and RNA-seq approaches reveal candidate genes associated with seed weight inFrontiers in plant science · 2025Article
- Genotyping-by-Sequencing Analysis Reveals Associations between Agronomic and Oil Traits in Gamma Ray-Derived Mutant Rapeseed (Plants (Basel, Switzerland) · 2024Article
- Integrating Genome-Wide Association Study, Transcriptome and Metabolome Reveal Novel QTL and Candidate Genes That Control Protein Content in Soybean.Plants (Basel, Switzerland) · 2024Article
- Integrated analysis of BSA-seq and RNA-seq identified the candidate genes for seed weight inFrontiers in plant science · 2024Article
- Exploration into Natural Variation Genes Associated with Determinate and Capitulum-like Inflorescence inInternational journal of molecular sciences · 2023Article
- Comparative Analysis of Seed Transcriptome and Coexpression Analysis Reveal Candidate Genes for Enhancing Seed Size/Weight inFrontiers in genetics · 2022Article
- Transcriptomic analysis of rapeseed (Frontiers in plant science · 2022Article
- Transcriptome Analysis of Seed Weight Plasticity inInternational journal of molecular sciences · 2021Article
- Transcriptome Analysis Reveals Key Pathways and Candidate Genes Controlling Seed Development and Size in Ricebean (Frontiers in genetics · 2021Article
- Comparative transcriptome and metabolite profiling of four tissues from Alisma orientale (Sam.) Juzep reveals its inflorescence developmental and medicinal characteristics.Scientific reports · 2019Article
- Article
- Article
- Article
- Small RNA and degradome profiling involved in seed development and oil synthesis of Brassica napus.PloS one · 2018Article
Corrections and comments
- Erratum issued
Authors and funding
9 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Brassica napus is an important oilseed crop worldwide. Although seed weight is the main determinant of seed yield, few studies have focused on the molecular mechanisms that regulate seed weight in B. napus. In this study, the immature seeds of G-42 and 7-9, two B. napus doubled haploid (DH) lines with extremely different thousand-seed weight (TSW), were selected for a transcriptome analysis to determine the regulatory mechanisms underlying seed weight at the whole gene expression level and to identify candidate genes related to seed weight. A total of 2,251 new genes and 2,205 differentially expressed genes (DEGs) were obtained via RNA-seq (RNA sequencing). Among these genes, 1,747 (77.61%) new genes and 2020 (91.61%) DEGs were successfully annotated. Of these DEGs, 1,118 were up-regulated and 1,087 were down-regulated in the large-seed line. The Kyoto Encyclopedia of Genes and Genomes (KEGG) database analysis indicated that 15 DEGs were involved in ubiquitin-mediated proteolysis and proteasome pathways, which might participate in regulating seed weight. The Gene Ontology (GO) database indicated that 222 DEGs were associated with the biological process or molecular function categories related to seed weight, such as cell division, cell size and cell cycle regulation, seed development, nutrient reservoir activity, and proteasome-mediated ubiquitin-dependent protein catabolic processes. Moreover, 50 DEGs encoding key enzymes or proteins were identified that likely participate in regulating seed weight. A DEG (GSBRNA2T00037121001) identified by the transcriptome analysis was also previously identified in a quantitative trait locus (QTL) region for seed weight via SLAF-seq (Specific Locus Amplified Fragment sequencing). Finally, the expression of 10 DEGs with putative roles in seed weight and the expression of the DEG GSBRNA2T00037121001 were confirmed by a quantitative real-time reverse transcription PCR (qRT-PCR) analysis, and the results were consistent with the RNA sequencing data. This work has provided new insights on the molecular mechanisms underlying seed weight-related biosynthesis and has laid a solid foundation for further improvements to the seed yield of oil crops.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.