Evidence map›Paper›PMID 34966928›Full record

ArticleGigaScience2021

Multi-dimensional leaf phenotypes reflect root system genotype in grafted grapevine over the growing season.

Zachary N Harris, Mani Awale, Niyati Bhakta, Daniel H Chitwood, Anne Fennell, Emma Frawley, Laura L Klein, Laszlo G Kovacs, Misha Kwasniewski, Jason P Londo and 4 more

Abstract read
In one paragraph

Article in GigaScience, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Genome assembly of the hybrid grapevineGigaByte (Hong Kong, China) · 2023
    Article
  5. Article
  6. Article
  7. 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

14 authors.

Zachary N HarrisDepartment of Biology, Saint Louis University, 3507 Laclede Avenue, St. Louis, MO 63103-2010, USA.ORCID 0000-0001-8299-3074
Mani AwaleDivision of Plant Sciences, University of Missouri, 135 Eckles Hall, Columbia, MO 65211, USA.ORCID 0000-0002-2256-7919
Niyati BhaktaDepartment of Biology, Saint Louis University, 3507 Laclede Avenue, St. Louis, MO 63103-2010, USA.
Daniel H ChitwoodDepartment of Horticulture, Michigan State University, East Lansing, MI 48824, USA.ORCID 0000-0003-4875-1447
Anne FennellDepartment of Agronomy, Horticulture & Plant Science, South Dakota State University, Brookings, SD 57006, USA.ORCID 0000-0002-4234-6419
Emma FrawleyDepartment of Biology, Saint Louis University, 3507 Laclede Avenue, St. Louis, MO 63103-2010, USA.ORCID 0000-0002-9721-1933
Laura L KleinDepartment of Biology, Saint Louis University, 3507 Laclede Avenue, St. Louis, MO 63103-2010, USA.ORCID 0000-0003-2603-878X
Laszlo G KovacsDepartment of Biology, Missouri State University, 901 S. National Avenue, Springfield, MO 65897, USA.ORCID 0000-0003-2220-797X
Misha KwasniewskiDivision of Plant Sciences, University of Missouri, 135 Eckles Hall, Columbia, MO 65211, USA.ORCID 0000-0003-3097-9638
Jason P LondoGrape Genetics Research Unit, United States Department of Agriculture - Agricultural Research Service, Geneva, NY, 14456, USA.ORCID 0000-0003-0535-4820
Qin MaDepartment of Biomedical Informatics, The Ohio State University, 1585 Neil Ave, Columbus, OH 43210, USA.ORCID 0000-0002-3264-8392
Zoë MigicovskyDepartment of Plant, Food, and Environmental Sciences, Faculty of Agriculture, Dalhousie University, Truro, NS B2N 5E3, Canada.ORCID 0000-0002-3931-1258
Joel F SwiftDepartment of Biology, Saint Louis University, 3507 Laclede Avenue, St. Louis, MO 63103-2010, USA.ORCID 0000-0002-7186-3298
Allison J MillerDepartment of Biology, Saint Louis University, 3507 Laclede Avenue, St. Louis, MO 63103-2010, USA.ORCID 0000-0002-2722-9361

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundModern biological approaches generate volumes of multi-dimensional data, offering unprecedented opportunities to address biological questions previously beyond reach owing to small or subtle effects. A fundamental question in plant biology is the extent to which below-ground activity in the root system influences above-ground phenotypes expressed in the shoot system. Grafting, an ancient horticultural practice that fuses the root system of one individual (the rootstock) with the shoot system of a second, genetically distinct individual (the scion), is a powerful experimental system to understand below-ground effects on above-ground phenotypes. Previous studies on grafted grapevines have detected rootstock influence on scion phenotypes including physiology and berry chemistry. However, the extent of the rootstock's influence on leaves, the photosynthetic engines of the vine, and how those effects change over the course of a growing season, are still largely unknown.

resultsHere, we investigate associations between rootstock genotype and shoot system phenotypes using 5 multi-dimensional leaf phenotyping modalities measured in a common grafted scion: ionomics, metabolomics, transcriptomics, morphometrics, and physiology. Rootstock influence is ubiquitous but subtle across modalities, with the strongest signature of rootstock observed in the leaf ionome. Moreover, we find that the extent of rootstock influence on scion phenotypes and patterns of phenomic covariation are highly dynamic across the season.

conclusionsThese findings substantially expand previously identified patterns to demonstrate that rootstock influence on scion phenotypes is complex and dynamic and underscore that broad understanding necessitates volumes of multi-dimensional data previously unmet.

Indexed as

Plant LeavesPlant RootsGenotypePhenotypeSeasons

Identifiers

PMID34966928
PMCPMC8716362

What OpenQuestion holds

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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.