Evidence map›Paper›PMID 35087554›Full record

ArticleFrontiers in plant science2021

Identification of Candidate Forage Yield Genes in Sorghum (

Lihua Wang, Yanlong Liu, Li Gao, Xiaocui Yang, Xu Zhang, Shaoping Xie, Meng Chen, Yi-Hong Wang, Jieqin Li, Yixin Shen

Open access · goldAbstract read
In one paragraph

Article in Frontiers in plant science, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
3.4field-weighted citation impact, top 7% 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

13 citing papers in PubMed, 19 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

10 authors at 4 institutions in 2 countries.

Lihua WangCollege of Agro-Grassland Science, Nanjing Agricultural University, Nanjing, China.
Yanlong LiuCollege of Agriculture, Anhui Science and Technology University, Fengyang, China.
Li GaoCollege of Agriculture, Anhui Science and Technology University, Fengyang, China.
Xiaocui YangCollege of Agriculture, Anhui Science and Technology University, Fengyang, China.
Xu ZhangCollege of Agriculture, Anhui Science and Technology University, Fengyang, China.
Shaoping XieCollege of Agriculture, Anhui Science and Technology University, Fengyang, China.
Meng ChenCollege of Agriculture, Anhui Science and Technology University, Fengyang, China.
Yi-Hong WangDepartment of Biology, University of Louisiana at Lafayette, Lafayette, LA, United States.
Jieqin LiCollege of Agriculture, Anhui Science and Technology University, Fengyang, China.
Yixin ShenCollege of Agro-Grassland Science, Nanjing Agricultural University, Nanjing, China.
Anhui Science and Technology University · CNAnhui University of Science and Technology · CNNanjing Agricultural University · CNUniversity of Louisiana at Lafayette · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Genetic dissection of forage yield traits is critical to the development of sorghum as a forage crop. In the present study, association mapping was performed with 85,585 SNP markers on four forage yield traits, namely plant height (PH), tiller number (TN), stem diameter (SD), and fresh weight per plant (FW) among 245 sorghum accessions evaluated in four environments. A total of 338 SNPs or quantitative trait nucleotides (QTNs) were associated with the four traits, and 21 of these QTNs were detected in at least two environments, including four QTNs for PH, ten for TN, six for SD, and one for FW. To identify candidate genes, dynamic transcriptome expression profiling was performed at four stages of sorghum development. One hundred and six differentially expressed genes (DEGs) that were enriched in hormone signal transduction pathways were found in all stages. Weighted gene correlation network analysis for PH and SD indicated that eight modules were significantly correlated with PH and that three modules were significantly correlated with SD. The blue module had the highest positive correlation with PH and SD, and the turquoise module had the highest negative correlation with PH and SD. Eight candidate genes were identified through the integration of genome-wide association studies (GWAS) and RNA sequencing. Sobic.004G143900, an indole-3-glycerol phosphate synthase gene that is involved in indoleacetic acid biosynthesis, was down-regulated as sorghum plants grew in height and was identified in the blue module, and Sobic.003G375100, an SD candidate gene, encoded a DNA repair RAD52-like protein 1 that plays a critical role in DNA repair-linked cell cycle progression. These findings demonstrate that the integrative analysis of omics data is a promising approach to identify candidate genes for complex traits.

Indexed as

candidate geneforage yield traitgenome-wide association studyRNA-seqsorghum

Identifiers

PMID35087554
PMCPMC8787639
OpenAlexW4205092491

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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.