In silico Design and Validation of CRISPR/Cas9 gRNAs for Enhancing Drought Tolerance and Yield in Rice

Rice is a staple food crop globally, and its yield is significantly impacted by drought, posing a threat to food security. Several genes have been implicated in drought response and yield regulation, which can be targeted using CRISPR/Cas9 genome editing techniques to develop improved rice cultivars. This study aimed to design guide RNAs (gRNAs) for drought-responsive and yield-determining genes in rice, including flavanone 3-hydroxylase-1 (OsF3H-1), chalcone synthase 31 (OsCHS31), nodulin/SWEET12 (OsSWEET12), MYB47, and OsKALA3, utilizing bioinformatics tools. Genome sequences were retrieved from the Rice Genome Annotation Project (RGAP) and the Rice Annotation Project Database (RAP-DB). Optimal gRNAs were designed using the CRISPR-P v2 tool and evaluated based on parameters such as GC content, off-target score, on-target score, and genome location. The structural stability of the selected gRNAs was validated using the Mathews Lab RNA secondary structure prediction tool. Most gRNAs, except those targeting OsF3H-1, exhibited low self-folding probabilities and energy levels within acceptable ranges, indicating favorable structural stability. However, the OsF3H-1 gRNAs demonstrated higher susceptibility to self-folding, requiring further refinement. The designed gRNAs provide a strong foundation for future CRISPR/Cas9-based genome editing experiments. These findings pave the way for engineering rice to develop stress-resilient and high-yielding varieties, contributing to enhanced agricultural sustainability and global food security.

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Publication Details

Journal
Journal of Advances in Biology & Biotechnology
Published
2024-12-30
DOI
https://doi.org/10.9734/jabb/2024/v27i121852
Citations
1
Primary Topic
CRISPR and Genetic Engineering
Type
article
Field-Weighted Citation Impact
0.23
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article

In silico Design and Validation of CRISPR/Cas9 gRNAs for Enhancing Drought Tolerance and Yield in Rice

Ma J, Gurulingaiah Bhavya, Abida P.S, Acharya Arpita et al.
1 citations
Journal of Advances in Biology & Biotechnology
CRISPR and Genetic Engineering
0.23
article

In silico Design and Validation of CRISPR/Cas9 gRNAs for Enhancing Drought Tolerance and Yield in Rice

Ma J, Gurulingaiah Bhavya, Abida P.S, Acharya Arpita, S Shafana, Kripa Pappachan
article en
1 citations

Abstract

Rice is a staple food crop globally, and its yield is significantly impacted by drought, posing a threat to food security. Several genes have been implicated in drought response and yield regulation, which can be targeted using CRISPR/Cas9 genome editing techniques to develop improved rice cultivars. This study aimed to design guide RNAs (gRNAs) for drought-responsive and yield-determining genes in rice, including flavanone 3-hydroxylase-1 (OsF3H-1), chalcone synthase 31 (OsCHS31), nodulin/SWEET12 (OsSWEET12), MYB47, and OsKALA3, utilizing bioinformatics tools. Genome sequences were retrieved from the Rice Genome Annotation Project (RGAP) and the Rice Annotation Project Database (RAP-DB). Optimal gRNAs were designed using the CRISPR-P v2 tool and evaluated based on parameters such as GC content, off-target score, on-target score, and genome location. The structural stability of the selected gRNAs was validated using the Mathews Lab RNA secondary structure prediction tool. Most gRNAs, except those targeting OsF3H-1, exhibited low self-folding probabilities and energy levels within acceptable ranges, indicating favorable structural stability. However, the OsF3H-1 gRNAs demonstrated higher susceptibility to self-folding, requiring further refinement. The designed gRNAs provide a strong foundation for future CRISPR/Cas9-based genome editing experiments. These findings pave the way for engineering rice to develop stress-resilient and high-yielding varieties, contributing to enhanced agricultural sustainability and global food security.

Journal of Advances in Biology & BiotechnologyVol. 27(12)
Kerala Agricultural University (IN)
Zero hunger
Openalex Percentile: Top 40%
CRISPR and Genetic Engineering
0.23
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