Evidence map›Paper›PMID 38243219›Full record

ArticleBMC genomics2024

Computational dissection of genetic variation modulating the response of multiple photosynthetic phenotypes to the light environment.

Huiying Gong, Ziyang Zhou, Chenhao Bu, Deqiang Zhang, Qing Fang, Xiao-Yu Zhang, Yuepeng Song

Open access · goldAbstract read
In one paragraph

Article in BMC genomics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.2field-weighted citation impact, top 47% 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

0 citing papers in PubMed, 1 citations in OpenAlex.

No citing paper in PubMed yet.

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

7 authors at 2 institutions in 2 countries.

Huiying Gong *College of Science, Beijing Forestry University, No. 35, Qinghua East Road, Beijing, 100083, P. R. China.
Ziyang Zhou *College of Science, Beijing Forestry University, No. 35, Qinghua East Road, Beijing, 100083, P. R. China.
Chenhao Bu *College of Biological Sciences and Technology, Beijing Forestry University, No. 35, Qinghua East Road, Beijing, 100083, P. R. China.
Deqiang ZhangCollege of Biological Sciences and Technology, Beijing Forestry University, No. 35, Qinghua East Road, Beijing, 100083, P. R. China.
Qing FangFaculty of Science, Yamagata University, Yamagata, 990, Japan.
Xiao-Yu ZhangCollege of Science, Beijing Forestry University, No. 35, Qinghua East Road, Beijing, 100083, P. R. China. xyzhang@bjfu.edu.cn.
Yuepeng SongCollege of Biological Sciences and Technology, Beijing Forestry University, No. 35, Qinghua East Road, Beijing, 100083, P. R. China. YuepengSong@bjfu.edu.cn.
Beijing Forestry University · CNYamagata University · JP

Funding

2023 Guiding Special Project of Beijing Forestry University School of Science 2023BJFULXYYD-16Horizontal Subject 2017HXKFLIXY001subproject of the National Science and Technology Major Project for IND (investigational new drug) 2019HXFWLIXY001the National Natural Science Foundation of China 61802009
6 · The paper itself

Abstract

backgroundThe expression of biological traits is modulated by genetics as well as the environment, and the level of influence exerted by the latter may vary across characteristics. Photosynthetic traits in plants are complex quantitative traits that are regulated by both endogenous genetic factors and external environmental factors such as light intensity and CO

resultsIn this paper, we proposed a research framework to investigate the genetic mechanism of high-dimensional complex photosynthetic traits in response to the light environment at the genome level. We established a set of high-dimensional equations incorporating environmental regulators to integrate functional mapping and dynamic screening of gene‒environment complex systems to elucidate the process and pattern of intrinsic genetic regulatory mechanisms of three types of photosynthetic phenotypes of Populus simonii that varied with light intensity. Furthermore, a network structure was established to elucidate the crosstalk among significant QTLs that regulate photosynthetic phenotypic systems. Additionally, the detection of key QTLs governing the response of multiple phenotypes to the light environment, coupled with the intrinsic differences in genotype expression, provides valuable insights into the regulatory mechanisms that drive the transition of photosynthetic activity and photoprotection in the face of varying light intensity gradients.

conclusionsThis paper offers a comprehensive approach to unraveling the genetic architecture of multidimensional variations in photosynthetic phenotypes, considering the combined impact of integrated environmental factors from multiple perspectives.

Indexed as

PhotosynthesisPopulusGenetic VariationLightPhenotypeElectron transport rateGenetic variationLight environmentNonphotochemical quenchingPhotochemical quenchingPhotosynthesis

Identifiers

PMID38243219
PMCPMC10799405
OpenAlexW4391053324

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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.