Automated Author Profile

Peng, Jie

University of California, Davis

Current S-Index

2.6

Sum of Dataset Indices for all datasets

Average Dataset Index per Dataset

1.3

Average Dataset Index per dataset

Total Datasets

2

Total datasets for this author

Average FAIR Score

45.2%

Average FAIR Score per dataset

Total Citations

2

Total citations to the author's datasets

Total Mentions

0

Total mentions of the author's datasets

S-Index Interpretation

S-Index Over Time

Cumulative Citations Over Time

Cumulative Mentions Over Time

Datasets

Data from: Resolving distinct genetic regulators of tomato leaf shape within a heteroblastic and ontogenetic context (Version: 1)

Leaf shape is mutable, changing in ways modulated by both development and environment within genotypes. A complete model of leaf phenotype would incorporate the changes in leaf shape during juvenile-to-adult phase transitions and the ontogeny of each leaf. Here, we provide a morphometric description of >33,000 leaflets from a set of tomato (Solanum spp) introgression lines grown under controlled environment conditions. We first compare the shape of these leaves, arising during vegetative development, with >11,000 previously published leaflets from a field setting and >11,000 leaflets from wild tomato relatives. We then quantify the changes in shape, across ontogeny, for successive leaves in the heteroblastic series. Using principal component analysis, we then separate genetic effects modulating (1) the overall shape of all leaves versus (2) the shape of specific leaves in the series, finding the former more heritable than the latter and comparing quantitative trait loci regulating each. Our results demonstrate that phenotype is highly contextual and that unbiased assessments of phenotype, for quantitative genetic or other purposes, would ideally sample the many developmental and environmental factors that modulate it.

Authors

  • Chitwood, Daniel H. ;
  • Ranjan, Aashish ;
  • Kumar, Ravi ;
  • Ichihashi, Yasunori ;
  • Zumstein, Kristina ;
  • Headland, Lauren R. ;
  • Ostria-Gallardo, Enrique ;
  • Aguilar-Martínez, José A. ;
  • Bush, Susan ;
  • Carriedo, Leonela ;
  • Fulop, Daniel ;
  • Martinez, Ciera C. ;
  • Peng, Jie ;
  • Maloof, Julin N. ;
  • Sinha, Neelima R.
1 Citation0 Mentions13% FAIR0.6 Dataset Index
10.5061/dryad.4r267September 2015

Data from: A quantitative genetic basis for leaf morphology in a set of precisely defined tomato introgression lines (Version: 1)

Introgression lines (ILs), in which genetic material from wild tomato species is introgressed into a domesticated background, have been used extensively in tomato (Solanum lycopersicum) improvement. Here, we genotype an IL population derived from the wild desert tomato Solanum pennellii at ultrahigh density, providing the exact gene content harbored by each line. To take advantage of this information, we determine IL phenotypes for a suite of vegetative traits, ranging from leaf complexity, shape, and size to cellular traits, such as stomatal density and epidermal cell phenotypes. Elliptical Fourier descriptors on leaflet outlines provide a global analysis of highly heritable, intricate aspects of leaf morphology. We also demonstrate constraints between leaflet size and leaf complexity, pavement cell size, and stomatal density and show independent segregation of traits previously assumed to be genetically coregulated. Meta-analysis of previously measured traits in the ILs shows an unexpected relationship between leaf morphology and fruit sugar levels, which RNA-Seq data suggest may be attributable to genetically coregulated changes in fruit morphology or the impact of leaf shape on photosynthesis. Together, our results both improve upon the utility of an important genetic resource and attest to a complex, genetic basis for differences in leaf morphology between natural populations.

Authors

  • Chitwood, Daniel H. ;
  • Kumar, Ravi ;
  • Headland, Lauren R. ;
  • Ranjan, Aashish ;
  • Covington, Michael F. ;
  • Ichihashi, Yasunori ;
  • Fulop, Daniel ;
  • Jiménez-Gómez, José M. ;
  • Peng, Jie ;
  • Maloof, Julin N. ;
  • Sinha, Neelima R.
1 Citation0 Mentions77% FAIR2.0 Dataset Index
10.5061/dryad.rm5v5July 2013