Evidence map›Paper›PMID 36345039›Full record

ArticleGenome biology2022

Comprehensive transcriptional variability analysis reveals gene networks regulating seed oil content of Brassica napus.

Zengdong Tan, Yan Peng, Yao Xiong, Feng Xiong, Yuting Zhang, Ning Guo, Zhuo Tu, Zhanxiang Zong, Xiaokun Wu, Jiang Ye and 13 more

Open access · goldAbstract read
In one paragraph

Article in Genome biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
9.4field-weighted citation impact, top 2% of its field
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

17 citing papers in PubMed, 48 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. A rare dominant alleleScience advances · 2025
    Article
  15. Article
  16. Article
  17. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

23 authors at 2 institutions in 2 countries.

Zengdong TanNational Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China.
Yan PengNational Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China.
Yao XiongNational Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China.
Feng XiongNational Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China.
Yuting ZhangNational Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China.
Ning GuoNational Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China.
Zhuo TuNational Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China.
Zhanxiang ZongNational Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China.
Xiaokun WuNational Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China.
Jiang YeNational Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China.
Chunjiao XiaNational Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China.
Tao ZhuNational Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China.
Yinmeng LiuNational Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China.
Hongxiang LouNational Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China.
Dongxu LiuNational Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China.
Shaoping LuNational Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China.
Xuan YaoNational Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China.
Kede LiuNational Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China.
Rod J SnowdonDepartment of Plant Breeding, Justus Liebig University, Giessen, Germany.
Agnieszka A GoliczDepartment of Plant Breeding, Justus Liebig University, Giessen, Germany.
Weibo XieNational Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China. weibo.xie@mail.hzau.edu.cn.
Liang GuoNational Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China. guoliang@mail.hzau.edu.cn.ORCID 0000-0001-7191-5062
Hu ZhaoNational Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China. zhaohu@mail.hzau.edu.cn.
Huazhong Agricultural University · CNJustus-Liebig-Universität Gießen · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundRegulation of gene expression plays an essential role in controlling the phenotypes of plants. Brassica napus (B. napus) is an important source for the vegetable oil in the world, and the seed oil content is an important trait of B. napus.

resultsWe perform a comprehensive analysis of the transcriptional variability in the seeds of B. napus at two developmental stages, 20 and 40 days after flowering (DAF). We detect 53,759 and 53,550 independent expression quantitative trait loci (eQTLs) for 79,605 and 76,713 expressed genes at 20 and 40 DAF, respectively. Among them, the local eQTLs are mapped to the adjacent genes more frequently. The adjacent gene pairs are regulated by local eQTLs with the same open chromatin state and show a stronger mode of expression piggybacking. Inter-subgenomic analysis indicates that there is a feedback regulation for the homoeologous gene pairs to maintain partial expression dosage. We also identify 141 eQTL hotspots and find that hotspot87-88 co-localizes with a QTL for the seed oil content. To further resolve the regulatory network of this eQTL hotspot, we construct the XGBoost model using 856 RNA-seq datasets and the Basenji model using 59 ATAC-seq datasets. Using these two models, we predict the mechanisms affecting the seed oil content regulated by hotspot87-88 and experimentally validate that the transcription factors, NAC13 and SCL31, positively regulate the seed oil content.

conclusionsWe comprehensively characterize the gene regulatory features in the seeds of B. napus and reveal the gene networks regulating the seed oil content of B. napus.

Indexed as

Brassica napusGene Regulatory NetworksPlant OilsQuantitative Trait LociSeedsPlant OilsBrassica napuseQTLMachine learningRegulatory networkSeed oil contentSubgenome

Identifiers

PMID36345039
PMCPMC9639296
OpenAlexW4308771837

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.