Evidence map›Paper›PMID 27356613›Full record

ArticleGenetics2016

A Genomic Resource for the Development, Improvement, and Exploitation of Sorghum for Bioenergy.

Zachary W Brenton, Elizabeth A Cooper, Mathew T Myers, Richard E Boyles, Nadia Shakoor, Kelsey J Zielinski, Bradley L Rauh, William C Bridges, Geoffrey P Morris, Stephen Kresovich

Abstract read
In one paragraph

Article in Genetics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 63 papers.

0numbers the graph read from it
0cells of the map it votes in
63citing 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

63 citing papers in PubMed.

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  12. Genomic resources, opportunities, and prospects for accelerated improvement of millets.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2024
    Review
  13. Article
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3 more citing papers are in PubMed but not listed here.

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.

Zachary W BrentonInstitute of Translational Genomics, Clemson University, South Carolina 29634 zwbrent@clemson.edu skresov@clemson.edu.
Elizabeth A CooperInstitute of Translational Genomics, Clemson University, South Carolina 29634 Department of Genetics and Biochemistry, Clemson University, South Carolina 29634.
Mathew T MyersInstitute of Translational Genomics, Clemson University, South Carolina 29634.
Richard E BoylesInstitute of Translational Genomics, Clemson University, South Carolina 29634 Department of Genetics and Biochemistry, Clemson University, South Carolina 29634.
Nadia ShakoorDonald Danforth Plant Science Center, St. Louis, Missouri 63132.
Kelsey J ZielinskiInstitute of Translational Genomics, Clemson University, South Carolina 29634.
Bradley L RauhInstitute of Translational Genomics, Clemson University, South Carolina 29634.
William C BridgesInstitute of Translational Genomics, Clemson University, South Carolina 29634 Department of Mathematical Sciences, Clemson University, South Carolina 29634.
Geoffrey P MorrisDepartment of Agronomy, Kansas State University, Manhattan, Kansas 66506.
Stephen KresovichInstitute of Translational Genomics, Clemson University, South Carolina 29634 Department of Genetics and Biochemistry, Clemson University, South Carolina 29634 zwbrent@clemson.edu skresov@clemson.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

With high productivity and stress tolerance, numerous grass genera of the Andropogoneae have emerged as candidates for bioenergy production. To optimize these candidates, research examining the genetic architecture of yield, carbon partitioning, and composition is required to advance breeding objectives. Significant progress has been made developing genetic and genomic resources for Andropogoneae, and advances in comparative and computational genomics have enabled research examining the genetic basis of photosynthesis, carbon partitioning, composition, and sink strength. To provide a pivotal resource aimed at developing a comparative understanding of key bioenergy traits in the Andropogoneae, we have established and characterized an association panel of 390 racially, geographically, and phenotypically diverse Sorghum bicolor accessions with 232,303 genetic markers. Sorghum bicolor was selected because of its genomic simplicity, phenotypic diversity, significant genomic tools, and its agricultural productivity and resilience. We have demonstrated the value of sorghum as a functional model for candidate gene discovery for bioenergy Andropogoneae by performing genome-wide association analysis for two contrasting phenotypes representing key components of structural and non-structural carbohydrates. We identified potential genes, including a cellulase enzyme and a vacuolar transporter, associated with increased non-structural carbohydrates that could lead to bioenergy sorghum improvement. Although our analysis identified genes with potentially clear functions, other candidates did not have assigned functions, suggesting novel molecular mechanisms for carbon partitioning traits. These results, combined with our characterization of phenotypic and genetic diversity and the public accessibility of each accession and genomic data, demonstrate the value of this resource and provide a foundation for future improvement of sorghum and related grasses for bioenergy production.

Indexed as

BiofuelsAgricultureAndropogonCarbohydratesChromosome MappingEdible GrainGenetic MarkersGenetic VariationGenome, PlantGenome-Wide Association StudyModels, GeneticPlant BreedingPoaceaeSorghumBiofuelsCarbohydratesGenetic MarkersBioenergy Association Panelbiomass compositioncarbon partitioningMPPMultiparent Advanced Generation Inter-Cross (MAGIC)multiparental populationsnonstructural sugars

Identifiers

PMID27356613
PMCPMC5012387

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.