Evidence map›Paper›PMID 28121983›Full record

ArticlePloS one2017

Dissecting Genetic Network of Fruit Branch Traits in Upland Cotton by Association Mapping Using SSR Markers.

Yongjun Mei, Jiwen Yu, Angli Xue, Shuli Fan, Meizhen Song, Chaoyou Pang, Wenfeng Pei, Shuxun Yu, Jun Zhu

Abstract read
In one paragraph

Article in PloS one, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
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

4 citing papers in PubMed.

  1. Article
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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

9 authors.

Yongjun MeiCollege of Plant Science, Tarim University, Alar, Xinjiang, China.
Jiwen YuState Key Laboratory of Cotton Biology, Key Laboratory of Cotton Genetic Improvement, Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, Henan, China.
Angli XueKey Laboratory of Crop Germplasm Resource of Zhejiang Province, Zhejiang University, Hangzhou, China.
Shuli FanState Key Laboratory of Cotton Biology, Key Laboratory of Cotton Genetic Improvement, Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, Henan, China.
Meizhen SongState Key Laboratory of Cotton Biology, Key Laboratory of Cotton Genetic Improvement, Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, Henan, China.
Chaoyou PangState Key Laboratory of Cotton Biology, Key Laboratory of Cotton Genetic Improvement, Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, Henan, China.
Wenfeng PeiState Key Laboratory of Cotton Biology, Key Laboratory of Cotton Genetic Improvement, Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, Henan, China.
Shuxun YuState Key Laboratory of Cotton Biology, Key Laboratory of Cotton Genetic Improvement, Ministry of Agriculture, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang, Henan, China.
Jun ZhuKey Laboratory of Crop Germplasm Resource of Zhejiang Province, Zhejiang University, Hangzhou, China.ORCID 0000-0002-8509-8304

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Genetic architecture of branch traits has large influences on the morphological structure, photosynthetic capacity, planting density, and yield of Upland cotton (Gossypium hirsutum L.). This research aims to reveal the genetic effects of six branch traits, including bottom fruit branch node number (BFBNN), bottom fruit branch length (BFBL), middle fruit branch node number (MFBNN), middle fruit branch length (MFBL), upper fruit branch node number (UFBNN), and upper fruit branch length (UFBL). Association mapping was conducted for these traits of 39 lines and their 178 F1 hybrids in three environments. There were 20 highly significant Quantitative Trait SSRs (QTSs) detected by mixed linear model approach analyzing a full genetic model with genetic effects of additive, dominance, epistasis and their environment interaction. The phenotypic variation explained by genetic effects ranged from 32.64 ~ 91.61%, suggesting these branch traits largely influenced by genetic factors.

Indexed as

Chromosomes, PlantGene Regulatory NetworksGenetic MarkersGenome, PlantQuantitative Trait LociCrosses, GeneticFruitGenetic LinkageGossypiumPhenotypeGenetic Markers

Identifiers

PMID28121983
PMCPMC5266336

What OpenQuestion holds

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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.