Evidence map›Paper›PMID 35780149›Full record

ArticleTAG. Theoretical and applied genetics. Theoretische und angewandte Genetik2022

The genetic basis for panicle trait variation in switchgrass (Panicum virgatum).

Li Zhang, Alice MacQueen, Xiaoyu Weng, Kathrine D Behrman, Jason Bonnette, John L Reilley, Francis M Rouquette, Philip A Fay, Yanqi Wu, Felix B Fritschi and 4 more

Abstract read
In one paragraph

Article in TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Advances and opportunities for computational interrogation of plant proteins.The Plant journal : for cell and molecular biology · 2026
    Review
  2. 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

14 authors.

Li Zhang *Department of Integrative Biology, University of Texas at Austin, Austin, TX, 78712, USA. zhanglicau@gmail.com.ORCID http://orcid.org/0000-0001-8625-8042
Alice MacQueen *Department of Integrative Biology, University of Texas at Austin, Austin, TX, 78712, USA.
Xiaoyu Weng *Department of Integrative Biology, University of Texas at Austin, Austin, TX, 78712, USA.
Kathrine D BehrmanDepartment of Integrative Biology, University of Texas at Austin, Austin, TX, 78712, USA.
Jason BonnetteDepartment of Integrative Biology, University of Texas at Austin, Austin, TX, 78712, USA.
John L ReilleyKika de la Garza Plant Materials Center, National Resources Conservation Service, US Department of Agriculture, Kingsville, TX, 78363, USA.
Francis M RouquetteTexas A&M AgriLife Research and Extension Center, Texas A&M University, Overton, TX, 75684, USA.
Philip A FayGrassland, Soil and Water Research Laboratory, Agricultural Research Service, US Department of Agriculture, Temple, TX, 76502, USA.
Yanqi WuDepartment of Plant and Soil Sciences, Oklahoma State University, Stillwater, OK, 74078, USA.
Felix B FritschiDivision of Plant Sciences, University of Missouri, Columbia, MO, 65211, USA.
Robert B MitchellWheat, Sorghum, and Forage Research Unit, Agricultural Research Service, US Department of Agriculture, University of Nebraska-Lincoln, Lincoln, NE, 68583, USA.
David B LowryDepartment of Plant Biology and DOE Great Lakes Bioenergy Research Center, Michigan State University, East Lansing, MI, 48824, USA.
Arvid R BoeDepartmentof Agronomy, Horticulture & Plant Science, South Dakota State University, Brookings, SD, 57007, USA.
Thomas E Juenger *Department of Integrative Biology, University of Texas at Austin, Austin, TX, 78712, USA. tjuenger@austin.utexas.edu.ORCID http://orcid.org/0000-0001-9550-9288

Funding

National Science Foundation IOS-1444533US department of energy DESC0014156
6 · The paper itself

Abstract

key messageWe investigate the genetic basis of panicle architecture in switchgrass in two mapping populations across a latitudinal gradient, and find many stable, repeatable genetic effects and limited genetic interactions with the environment. Grass species exhibit large diversity in panicle architecture influenced by genes, the environment, and their interaction. The genetic study of panicle architecture in perennial grasses is limited. In this study, we evaluate the genetic basis of panicle architecture including panicle length, primary branching number, and secondary branching number in an outcrossed switchgrass QTL population grown across ten field sites in the central USA through multi-environment mixed QTL analysis. We also evaluate genetic effects in a diversity panel of switchgrass grown at three of the ten field sites using genome-wide association (GWAS) and multivariate adaptive shrinkage. Furthermore, we search for candidate genes underlying panicle traits in both of these independent mapping populations. Overall, 18 QTL were detected in the QTL mapping population for the three panicle traits, and 146 unlinked genomic regions in the diversity panel affected one or more panicle trait. Twelve of the QTL exhibited consistent effects (i.e., no QTL by environment interactions or no QTL × E), and most (four of six) of the effects with QTL × E exhibited site-specific effects. Most (59.3%) significant partially linked diversity panel SNPs had significant effects in all panicle traits and all field sites and showed pervasive pleiotropy and limited environment interactions. Panicle QTL co-localized with significant SNPs found using GWAS, providing additional power to distinguish between true and false associations in the diversity panel.

Indexed as

OryzaPanicumChromosome MappingGenetic VariationGenome-Wide Association StudyPhenotypePolymorphism, Single NucleotideQuantitative Trait Loci

Identifiers

PMID35780149
PMCPMC9325832

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Registered trials

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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.