Research Article

Bhartiya Krishi Anusandhan Patrika, volume 36 issue 1 (march 2021) : 25-28

Next Generation Sequencing Data Analysis and its Applications in Agriculture

Shbana Begum, Rahul Banerjee

Affiliations

¹ICAR-Indian Agricultural Statistics Research Institute, Library Avenue, Pusa-110 012, New Delhi, India.

Submitted15-02-2021|
Accepted16-06-2021|
First Online 26-06-2021|
doi 10.18805/BKAP265

Cite article:- Begum Shbana, Banerjee Rahul (2021). Next Generation Sequencing Data Analysis and its Applications in Agriculture. Bhartiya Krishi Anusandhan Patrika. 36(1): 25-28. doi: 10.18805/BKAP265.

ABSTRACT

Next Generation sequencing (NGS) technologies are revolutionizing the acquisition of genomic data at relatively low cost. NGS technologies are rapidly changing approaches to complex genomic studies and generating a vast amount of data. New and more powerful bioinformatics proposals and tools are needed to handle such large biological collections of such huge amounts of data provided by NGS data analysis. In addition, specialized software tools and advanced computational resources are required for data integration. In this article, we are describing here the main computational approach for next generation sequencing data analysis and its role in agriculture for crop improvement.

KEYWORDS

REFERENCES

Andrews, K.R. and Luikart, G. (2014). Recent novel approaches for population genomics data analysis. Molecular Ecology. 23(7): 1661-1667.
Del Vecchio, F., Mastroiaco, V., Di Marco, A., Compagnoni, C., Capece, D., Zazzeroni, F. and Tessitore, A. (2017). Next-generation sequencing: recent applications to the analysis of colorectal cancer. Journal of Translational Medicine. 15(1): 246.
Esposito, A., Colantuono, C., Ruggieri, V. and Chiusano, M.L. (2016). Bioinformatics for agriculture in the Next-Generation sequencing era. Chemical and Biological Technologies in Agriculture. 3(1): 9.
Henry, R.J. (2012). Next-generation sequencing for understanding and accelerating crop domestication. Briefings in Functional Genomics. 11(1): 51-56.
Sirangelo, T.M. and Calabrò, G. (2020). Next Generation Sequencing Approach and Impact on Bioinformatics: Applications in Agri-Food Field. Journal of Bioinformatics and Systems Biology. 3: 32-44.
Tang, C.Y., Hung, C.L., Zheng, H., Lin, C.Y. and Jiang, H. (2015). Novel computational technologies for next-generation sequencing data analysis and their applications.
Wadapurkar, R.M. and Vyas, R. (2018). Computational analysis of next generation sequencing data and its applications in clinical oncology. Informatics in Medicine Unlocked. 11: 75-82.

Disclaimer :

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

Copyright :

This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Research Article

Next Generation Sequencing Data Analysis and its Applications in Agriculture

ABSTRACT

KEYWORDS

REFERENCES

Reviewed By

In this Article

APC

Publish With US

Become a Reviewer/Member

Open Access

Products and Services

Support and Policies

Editorial Board