Evidence map›Paper›PMID 38231256›Full record

ReviewTAG. Theoretical and applied genetics. Theoretische und angewandte Genetik2024

Genomic and co-expression network analyses reveal candidate genes for oil accumulation based on an introgression population in Upland cotton (Gossypium hirsutum).

Jianjiang Ma, Bing Jia, Yingying Bian, Wenfeng Pei, Jikun Song, Man Wu, Wenkui Wang, Kashif, Shahzad, Li Wang and 5 more

Abstract readReview
PubMed Publisher
In one paragraph

Review in TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
5.4field-weighted citation impact, top 5% 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

7 citing papers in PubMed, 9 citations in OpenAlex.

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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

15 authors at 3 institutions in 2 countries.

Jianjiang Ma *State Key Laboratory of Cotton Biology, Key Laboratory of Cotton Genetic Improvement, Institute of Cotton Research of the Chinese Academy of Agricultural Sciences, Ministry of Agriculture, Anyang, China.
Bing Jia *State Key Laboratory of Cotton Biology, Key Laboratory of Cotton Genetic Improvement, Institute of Cotton Research of the Chinese Academy of Agricultural Sciences, Ministry of Agriculture, Anyang, China.
Yingying Bian *State Key Laboratory of Cotton Biology, Key Laboratory of Cotton Genetic Improvement, Institute of Cotton Research of the Chinese Academy of Agricultural Sciences, Ministry of Agriculture, Anyang, China.
Wenfeng PeiState Key Laboratory of Cotton Biology, Key Laboratory of Cotton Genetic Improvement, Institute of Cotton Research of the Chinese Academy of Agricultural Sciences, Ministry of Agriculture, Anyang, China.
Jikun SongState Key Laboratory of Cotton Biology, Key Laboratory of Cotton Genetic Improvement, Institute of Cotton Research of the Chinese Academy of Agricultural Sciences, Ministry of Agriculture, Anyang, China.
Man WuState Key Laboratory of Cotton Biology, Key Laboratory of Cotton Genetic Improvement, Institute of Cotton Research of the Chinese Academy of Agricultural Sciences, Ministry of Agriculture, Anyang, China.
Wenkui WangState Key Laboratory of Cotton Biology, Key Laboratory of Cotton Genetic Improvement, Institute of Cotton Research of the Chinese Academy of Agricultural Sciences, Ministry of Agriculture, Anyang, China.
Kashif
ShahzadState Key Laboratory of Cotton Biology, Key Laboratory of Cotton Genetic Improvement, Institute of Cotton Research of the Chinese Academy of Agricultural Sciences, Ministry of Agriculture, Anyang, China.
Li WangState Key Laboratory of Cotton Biology, Key Laboratory of Cotton Genetic Improvement, Institute of Cotton Research of the Chinese Academy of Agricultural Sciences, Ministry of Agriculture, Anyang, China.
Bingbing ZhangState Key Laboratory of Cotton Biology, Key Laboratory of Cotton Genetic Improvement, Institute of Cotton Research of the Chinese Academy of Agricultural Sciences, Ministry of Agriculture, Anyang, China.
Pan FengState Key Laboratory of Cotton Biology, Key Laboratory of Cotton Genetic Improvement, Institute of Cotton Research of the Chinese Academy of Agricultural Sciences, Ministry of Agriculture, Anyang, China.
Liupeng YangState Key Laboratory of Cotton Biology, Key Laboratory of Cotton Genetic Improvement, Institute of Cotton Research of the Chinese Academy of Agricultural Sciences, Ministry of Agriculture, Anyang, China.
Jinfa ZhangDepartment of Plant and Environmental Sciences, New Mexico State University, Las Cruces, USA. jinzhang@nmsu.edu.
Jiwen YuState Key Laboratory of Cotton Biology, Key Laboratory of Cotton Genetic Improvement, Institute of Cotton Research of the Chinese Academy of Agricultural Sciences, Ministry of Agriculture, Anyang, China. yujw666@hotmail.com.ORCID http://orcid.org/0000-0002-0254-8024
Cotton Research Institute · CNZhengzhou University · CNNew Mexico State University · US

Funding

the National Natural Science Foundation of China 32101716
6 · The paper itself

Abstract

key messageIntegrated QTL mapping and WGCNA condense the potential gene regulatory network involved in oil accumulation. A glycosyl hydrolases gene (GhHSD1) for oil biosynthesis was confirmed in Arabidopsis, which will provide useful knowledge to understand the functional mechanism of oil biosynthesis in cotton. Cotton is an economical source of edible oil for the food industry. The genetic mechanism that regulates oil biosynthesis in cottonseeds is essential for the genetic enhancement of oil content (OC). To explore the functional genomics of OC, this study utilized an interspecific backcross inbred line population to dissect the quantitative trait locus (QTL) interlinked with OC. In total, nine OC QTLs were identified, four of which were novel, and each QTL explained 3.62-34.73% of the phenotypic variation of OC. The comprehensive transcript profiling of developing cottonseeds revealed 3,646 core genes differentially expressed in both inbred parents. Functional enrichment analysis determined 43 genes were annotated with oil biosynthesis processes. Implementation of weighted gene co-expression network analysis showed that 803 differential genes had a significant correlation with the OC phenotype. Further integrated analysis identified seven important genes located in OC QTLs. Of which, the GhHSD1 gene located in stable QTL qOC-Dt3-1 exhibited the highest functional linkages with the other network genes. Phylogenetic analysis showed significant evolutionary differences in the HSD1 sequences between oilseed- and starch- crops. Furthermore, the overexpression of GhHSD1 in Arabidopsis yielded almost 6.78% higher seed oil. This study not only uncovers important genetic loci for oil accumulation in cottonseed, but also provides a set of new candidate genes that potentially influence the oil biosynthesis pathway in cottonseed.

Indexed as

ArabidopsisGossypiumCottonseed OilGenomicsPhylogenyCottonseed Oil

Identifiers

PMID38231256
OpenAlexW4390941075

What OpenQuestion holds

Textmetadata
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.