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Review

Next Generation Sequencing Based Forward Genetic Approaches for Identification and Mapping of Causal Mutations in Crop Plants: A Comprehensive Review

by
Parmeshwar K. Sahu
1,†,
Richa Sao
1,†,
Suvendu Mondal
2,3,
Gautam Vishwakarma
2,3,
Sudhir Kumar Gupta
2,3,
Vinay Kumar
4,
Sudhir Singh
2,
Deepak Sharma
1,* and
Bikram K. Das
2,3,*
1
Department of Genetics and Plant Breeding, Indira Gandhi Krishi Vishwavidyalaya, Raipur 492012, Chhattisgarh, India
2
Nuclear Agriculture and Biotechnology Division, Bhabha Atomic Research Centre, Mumbai 400085, India
3
Homi Bhabha National Institute, Training School Complex, Anushaktinagar, Mumbai 400094, India
4
ICAR-National Institute of Biotic Stress Management, Baronda, Raipur 493225, Chhattisgarh, India
*
Authors to whom correspondence should be addressed.
†
These authors have contributed equally.
Plants 2020, 9(10), 1355; https://doi.org/10.3390/plants9101355
Submission received: 30 July 2020 / Revised: 14 September 2020 / Accepted: 21 September 2020 / Published: 14 October 2020
(This article belongs to the Special Issue Plant Mutation Breeding)
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Abstract

The recent advancements in forward genetics have expanded the applications of mutation techniques in advanced genetics and genomics, ahead of direct use in breeding programs. The advent of next-generation sequencing (NGS) has enabled easy identification and mapping of causal mutations within a short period and at relatively low cost. Identifying the genetic mutations and genes that underlie phenotypic changes is essential for understanding a wide variety of biological functions. To accelerate the mutation mapping for crop improvement, several high-throughput and novel NGS based forward genetic approaches have been developed and applied in various crops. These techniques are highly efficient in crop plants, as it is relatively easy to grow and screen thousands of individuals. These approaches have improved the resolution in quantitative trait loci (QTL) position/point mutations and assisted in determining the functional causative variations in genes. To be successful in the interpretation of NGS data, bioinformatics computational methods are critical elements in delivering accurate assembly, alignment, and variant detection. Numerous bioinformatics tools/pipelines have been developed for such analysis. This article intends to review the recent advances in NGS based forward genetic approaches to identify and map the causal mutations in the crop genomes. The article also highlights the available bioinformatics tools/pipelines for reducing the complexity of NGS data and delivering the concluding outcomes.
Keywords: NGS; induced mutagenesis; point mutations; forward genetics; bioinformatics; mapping; causal mutations NGS; induced mutagenesis; point mutations; forward genetics; bioinformatics; mapping; causal mutations

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MDPI and ACS Style

Sahu, P.K.; Sao, R.; Mondal, S.; Vishwakarma, G.; Gupta, S.K.; Kumar, V.; Singh, S.; Sharma, D.; Das, B.K. Next Generation Sequencing Based Forward Genetic Approaches for Identification and Mapping of Causal Mutations in Crop Plants: A Comprehensive Review. Plants 2020, 9, 1355. https://doi.org/10.3390/plants9101355

AMA Style

Sahu PK, Sao R, Mondal S, Vishwakarma G, Gupta SK, Kumar V, Singh S, Sharma D, Das BK. Next Generation Sequencing Based Forward Genetic Approaches for Identification and Mapping of Causal Mutations in Crop Plants: A Comprehensive Review. Plants. 2020; 9(10):1355. https://doi.org/10.3390/plants9101355

Chicago/Turabian Style

Sahu, Parmeshwar K., Richa Sao, Suvendu Mondal, Gautam Vishwakarma, Sudhir Kumar Gupta, Vinay Kumar, Sudhir Singh, Deepak Sharma, and Bikram K. Das. 2020. "Next Generation Sequencing Based Forward Genetic Approaches for Identification and Mapping of Causal Mutations in Crop Plants: A Comprehensive Review" Plants 9, no. 10: 1355. https://doi.org/10.3390/plants9101355

APA Style

Sahu, P. K., Sao, R., Mondal, S., Vishwakarma, G., Gupta, S. K., Kumar, V., Singh, S., Sharma, D., & Das, B. K. (2020). Next Generation Sequencing Based Forward Genetic Approaches for Identification and Mapping of Causal Mutations in Crop Plants: A Comprehensive Review. Plants, 9(10), 1355. https://doi.org/10.3390/plants9101355

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