Zhi Li

Zhi Li

orcid

Research Focus & Metrics

Academic Career Length

10Years (2017-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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17 March 2020 in The Plant Cell
Verified
Journal Article
Open access
PDF file
PZPeng Zhou
Peng Zhou
ZLZhi Li
Zhi Li
EMErika Magnusson
Erika Magnusson
FCFabio Gomez Cano
Fabio Gomez Cano
PCPeter Crisp
Peter Crisp
NSNathan M. Springer
Nathan M. Springer
The regulation of gene expression is central to many biological processes. Gene regulatory networks (GRNs) link transcription factors (TFs) to their target genes and represent maps of potential transcriptional regulation. Here, we analyzed a large number of publically available maize (Zea mays) transcriptome data sets including >6000 RNA sequencing samples to generate 45 coexpression-based GRNs that represent potential regulatory relationships between TFs and other genes in different populations of samples (cross-tissue, cross-genotype, and tissue-and-genotype samples). While these networks are all enriched for biologically relevant interactions, different networks capture distinct TF-target associations and biological processes. By examining the power of our coexpression-based GRNs to accurately predict covarying TF-target relationships in natural variation data sets, we found that presence/absence changes rather than quantitative changes in TF gene expression are more likely associated with changes in target gene expression. Integrating information from our TF-target predictions and previous expression quantitative trait loci (eQTL) mapping results provided support for 68 TFs underlying 74 previously identified trans-eQTL hotspots spanning a variety of metabolic pathways. This study highlights the utility of developing multiple GRNs within a species to detect putative regulators of important plant pathways and provides potential targets for breeding or biotechnological applications.

30 September 2020 in The Plant Cell
Verified
Journal Article
Open access
PDF file
ZLZhi Li
Zhi Li
AZAn Dan Zhu
An Dan Zhu
QSQingxin Song
Qingxin Song
HCHelen Y. Chen
Helen Y. Chen
FHFrank G. Harmon
Frank G. Harmon
Z. Jeffrey ChenZ. Jeffrey Chen
Z. Jeffrey Chen
Heterosis or hybrid vigor is widespread in plants and animals. Although the molecular basis for heterosis has been extensively studied, metabolic and proteomic contributions to heterosis remain elusive. Here we report an integrative analysis of time-series metabolome and proteome data in maize (Zea mays) hybrids and their inbred parents. Many maize metabolites and proteins are diurnally regulated, and many of these show nonadditive abundance in the hybrids, including key enzymes and metabolites involved in carbon assimilation. Compared with robust trait heterosis, metabolic heterosis is relatively mild. Interestingly, most amino acids display negative mid-parent heterosis (MPH), i.e., having lower values than the average of the parents, while sugars, alcohols, and nucleoside metabolites show positive MPH. From the network perspective, metabolites in the photosynthetic pathway show positive MPH, whereas metabolites in the photorespiratory pathway show negative MPH, which corresponds to nonadditive protein abundance and enzyme activities of key enzymes in the respective pathways in the hybrids. Moreover, diurnally expressed proteins that are upregulated in the hybrids are enriched in photosynthesis-related gene-ontology terms. Hybrids may more effectively remove toxic metabolites generated during photorespiration, and thus maintain higher photosynthetic efficiency. These metabolic and proteomic resources provide unique insight into heterosis and its utilization for high yielding maize and other crop plants.

29 November 2020 in The Plant Journal
Verified
Journal Article
Closed access
ZLZhi Li
Zhi Li
PZPeng Zhou
Peng Zhou
RCRafael Della Coletta
Rafael Della Coletta
TZTifu Zhang
Tifu Zhang
ABAlex B. Brohammer
Alex B. Brohammer
CHCandice N. Hirsch
Candice N. Hirsch

18 November 2022
Verified
Book Chapter
Closed access
ZLZhi Li
Zhi Li
JSJiabin Sun
Jiabin Sun
CHCandice N. Hirsch
Candice N. Hirsch

15 January 2026 in Nature Plants
Verified
Journal Article
Closed access
PDF file
TZTian Zhang
Tian Zhang
LYLu Yu
Lu Yu
YWYueyuan Wang
Yueyuan Wang
PLPan Li
Pan Li
XFXiaoyan Feng
Xiaoyan Feng
CSChun-Peng Song
Chun-Peng Song

26 April 2017 in bioRxiv
Verified
Preprint
Open access
PDF file
ZLZhi Li
Zhi Li
LCLisa Coffey
Lisa Coffey
JGJacob Garfin
Jacob Garfin
NMNathan Miller
Nathan Miller
MWMichael R. White
Michael R. White
CHCandice N. Hirsch
Candice N. Hirsch
The environment can influence heterosis, the phenomena in which the offspring of two inbred parents exhibits phenotypic performance beyond the inbred parents for specific traits. In this study we measured 25 traits in a set of 47 maize hybrids and their inbred parents grown in 16 different environments, and each had varying levels of average productivity. By quantifying 25 vegetative and reproductive traits across the life cycle we were able to analyze interactions between the environment and multiple distinct instances of heterosis. The magnitude and rank among hybrids of better-parent heterosis (BPH) varied for the different traits and environments. Across the traits, a higher within plot variance was observed for inbred lines compared to hybrids. However, for most traits, variance across environments was not significantly different for inbred lines compared to hybrids. Further, for many traits the correlations of BPH to hybrid performance and BPH to better parent performance were of comparable magnitude. These results indicate that inbreds and hybrids are showing similar trends in environmental response and are both contribute to genotype-by-environment interactions for heterosis. This study highlights that degree of heterosis is not an inherent trait of a specific hybrid, but varies depending on the trait measured and the environment where that trait is measured. Studies that attempt to correlate molecular processes with heterosis are hindered by the fact that heterosis is not a consistent attribute of a specific hybrid.