Abstract
Improvement of agricultural species has exploited the genetic variation responsible for complex quantitative traits. Much of the functional variation is regulatory, in cis-regulatory elements and trans-acting factors that ultimately contribute to gene expression differences. However, the identification of gene regulatory network components that, when modulated, will increase plant productivity or resilience, is challenging, yet essential to provide increased predictive power for genome engineering approaches that are likely to benefit useful traits. Here, we discuss the opportunities and limitations of using data obtained from gene coexpression, transcription factor binding, and genome-wide association mapping analyses to predict regulatory interactions that impact crop improvement. It is apparent that a combination of information from these data types is necessary for the reliable identification and utilization of important regulatory interactions that underlie complex agronomic traits.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 1075-1082 |
| Number of pages | 8 |
| Journal | Trends in Plant Science |
| Volume | 24 |
| Issue number | 12 |
| DOIs | |
| State | Published - Dec 2019 |
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Keywords
- GWAS
- gene expression
- gene regulatory network
- transcription factor
- variation
Cite this
Challenges of Translating Gene Regulatory Information into Agronomic Improvements. / Springer, Nathan; de León, Natalia; Grotewold, Erich.
In: Trends in Plant Science, Vol. 24, No. 12, 12.2019, p. 1075-1082.Research output: Contribution to journal › Review article
}
TY - JOUR
T1 - Challenges of Translating Gene Regulatory Information into Agronomic Improvements
AU - Springer, Nathan
AU - de León, Natalia
AU - Grotewold, Erich
PY - 2019/12
Y1 - 2019/12
N2 - Improvement of agricultural species has exploited the genetic variation responsible for complex quantitative traits. Much of the functional variation is regulatory, in cis-regulatory elements and trans-acting factors that ultimately contribute to gene expression differences. However, the identification of gene regulatory network components that, when modulated, will increase plant productivity or resilience, is challenging, yet essential to provide increased predictive power for genome engineering approaches that are likely to benefit useful traits. Here, we discuss the opportunities and limitations of using data obtained from gene coexpression, transcription factor binding, and genome-wide association mapping analyses to predict regulatory interactions that impact crop improvement. It is apparent that a combination of information from these data types is necessary for the reliable identification and utilization of important regulatory interactions that underlie complex agronomic traits.
AB - Improvement of agricultural species has exploited the genetic variation responsible for complex quantitative traits. Much of the functional variation is regulatory, in cis-regulatory elements and trans-acting factors that ultimately contribute to gene expression differences. However, the identification of gene regulatory network components that, when modulated, will increase plant productivity or resilience, is challenging, yet essential to provide increased predictive power for genome engineering approaches that are likely to benefit useful traits. Here, we discuss the opportunities and limitations of using data obtained from gene coexpression, transcription factor binding, and genome-wide association mapping analyses to predict regulatory interactions that impact crop improvement. It is apparent that a combination of information from these data types is necessary for the reliable identification and utilization of important regulatory interactions that underlie complex agronomic traits.
KW - GWAS
KW - gene expression
KW - gene regulatory network
KW - transcription factor
KW - variation
UR - http://www.scopus.com/inward/record.url?scp=85069909591&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85069909591&partnerID=8YFLogxK
U2 - 10.1016/j.tplants.2019.07.004
DO - 10.1016/j.tplants.2019.07.004
M3 - Review article
C2 - 31377174
AN - SCOPUS:85069909591
VL - 24
SP - 1075
EP - 1082
JO - Trends in Plant Science
JF - Trends in Plant Science
SN - 1360-1385
IS - 12
ER -