Engineering quantitative stomatal trait variation and local adaptation potential by cis‐regulatory editing

Cis-regulatory element editing can generate quantitative trait variation that mitigates extreme phenotypes and harmful pleiotropy associated with coding sequence mutations. Here, we applied a multiplexed CRISPR/Cas9 approach, informed by bioinformatic datasets, to generate genotypic variation in the promoter of OsSTOMAGEN, a positive regulator of rice stomatal density. Engineered genotypic variation corresponded to broad and continuous variation in stomatal density, ranging from 70% to 120% of wild-type stomatal density. This panel of stomatal variants was leveraged in physiological assays to establish discrete relationships between stomatal morphological variation and stomatal conductance, carbon assimilation and intrinsic water use efficiency in steady-state and fluctuating light conditions. Additionally, promoter alleles were subjected to vegetative drought regimes to assay the effects of the edited alleles on developmental response to drought. Notably, the capacity for drought-responsive stomatal density reprogramming in stomagen and two cis-regulatory edited alleles was reduced. Collectively our data demonstrate that cis-regulatory element editing can generate near-isogenic trait variation that can be leveraged for establishing relationships between anatomy and physiology, providing a basis for optimizing traits across diverse environments.

Authors

Institutions

Publication Details

Journal
Plant Biotechnology Journal
Published
2024-10-18
DOI
https://doi.org/10.1111/pbi.14464
Citations
7
Primary Topic
CRISPR and Genetic Engineering
Type
article
Field-Weighted Citation Impact
1.64

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Engineering quantitative stomatal trait variation and local adaptation potential by cis‐regulatory editing

Samantha E. Lieberman, Lillian Litvak, Nicholas G. Karavolias, Krishna Niyogi et al.
7 citations
Plant Biotechnology Journal
CRISPR and Genetic Engineering
1.64
article

Engineering quantitative stomatal trait variation and local adaptation potential by cis‐regulatory editing

Samantha E. Lieberman, Lillian Litvak, Nicholas G. Karavolias, Krishna Niyogi, Michelle Tjahjadi, Dhruv Patel‐Tupper, Myeong‐Je Cho, Brian J. Staskawicz, Ana Gallegos Cruz
article en
7 citations

Abstract

Cis-regulatory element editing can generate quantitative trait variation that mitigates extreme phenotypes and harmful pleiotropy associated with coding sequence mutations. Here, we applied a multiplexed CRISPR/Cas9 approach, informed by bioinformatic datasets, to generate genotypic variation in the promoter of OsSTOMAGEN, a positive regulator of rice stomatal density. Engineered genotypic variation corresponded to broad and continuous variation in stomatal density, ranging from 70% to 120% of wild-type stomatal density. This panel of stomatal variants was leveraged in physiological assays to establish discrete relationships between stomatal morphological variation and stomatal conductance, carbon assimilation and intrinsic water use efficiency in steady-state and fluctuating light conditions. Additionally, promoter alleles were subjected to vegetative drought regimes to assay the effects of the edited alleles on developmental response to drought. Notably, the capacity for drought-responsive stomatal density reprogramming in stomagen and two cis-regulatory edited alleles was reduced. Collectively our data demonstrate that cis-regulatory element editing can generate near-isogenic trait variation that can be leveraged for establishing relationships between anatomy and physiology, providing a basis for optimizing traits across diverse environments.

Plant Biotechnology JournalVol. 22(12)
Howard Hughes Medical Institute (US), Lawrence Berkeley National Laboratory (US), Innovative Genomics Institute (US), University of California, Berkeley (US)
National Science Foundation
Clean water and sanitation
Openalex Percentile: Top 16%
CRISPR and Genetic Engineering
1.64
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.