Evidence map›Paper›PMID 33217213›Full record

ArticleThe plant genome2020

Accelerating forest tree breeding by integrating genomic selection and greenhouse phenotyping.

Filipe C Alves, Kelly M Balmant, Marcio F R Resende, Matias Kirst, Gustavo de Los Campos

Abstract read
In one paragraph

Article in The plant genome, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

15 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
  4. Article
  5. Article
  6. Article
  7. Review
  8. Review
  9. Article
  10. Article
  11. Article
  12. Article
  13. Review
  14. Article
  15. Article
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

5 authors.

Filipe C AlvesDepartment of Epidemiology and Biostatistics, Michigan State University, East Lansing, MI, 48824, USA.ORCID 0000-0002-2127-4276
Kelly M BalmantSchool of Forest Resources and Conservation, University of Florida, Gainsville, FL, 32611, USA.ORCID 0000-0001-5189-5121
Marcio F R ResendePlant Molecular and Cellular Biology Graduate Program, University of Florida, Gainsville, FL, 32611, USA.ORCID 0000-0002-2367-0766
Matias KirstSchool of Forest Resources and Conservation, University of Florida, Gainsville, FL, 32611, USA.ORCID 0000-0002-8186-3945
Gustavo de Los CamposDepartment of Epidemiology and Biostatistics, Michigan State University, East Lansing, MI, 48824, USA.ORCID 0000-0001-5692-7129

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Breeding forest species can be a costly and slow process because of the extensive areas needed for field trials and the long periods (e.g., five years) that are required to measure economically and environmentally relevant phenotypes (e.g., adult plant biomass or plant height). Genomic selection (GS) and indirect selection using early phenotypes (e.g., phenotypes collected in greenhouse conditions) are two ways by which tree breeding can be accelerated. These approaches can both reduce the costs of field-testing and the time required to make selection decisions. Moreover, these approaches can be highly synergistic. Therefore, in this study, we used a data set comprising DNA genotypes and longitudinal measurements of growth collected from a population of Populus deltoides W. Bartram ex Marshall (eastern cottonwood) in the greenhouse and the field, to evaluate the potential impact of integrating large-scale greenhouse phenotyping with conventional GS. We found that the integration of greenhouse phenotyping and GS can deliver very early selection decisions that are moderately accurate. Therefore, we conclude that the adoption of these approaches, in conjunction with reproductive techniques that shorten the generation interval, can lead to an unprecedented acceleration of selection gains in P. deltoides and, potentially, other commercially planted tree species.

Indexed as

Selection, GeneticTreesBreedingForestsGenomics

Identifiers

PMID33217213
PMCPMC12807299

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.