Title

Identification of long non-coding RNA in rice lines resistant to Rice blast pathogen Maganaporthe oryzae

Authors

Priyanka Jain^{1, 3}, Vinay Sharma³, Himanshu Dubey¹, Pankaj Kumar Singh^{2, 3}, Ritu Kapoor², Mandeeep Kumari¹, Jyoti Singh¹, Deepak V. Pawar¹, Deepak Bisht¹, Amolkumar U. Solanke¹, T.K. Mondal¹, T. R. Sharma^{1, 2*}

Affiliation

¹ICAR-National Research Centre on Plant Biotechnology, Pusa Campus, New Delhi-110012, India;

²National Agri-Food Biotechnology Institute, Mohali, Punjab-140306, India;

³Department of Bioscience & Biotechnology, Banasthali University, Tonk, Rajasthan-304022, India

Email

trsharma@nabi.res.in;

Article Type

Hypothesis

Date

Received July 31, 2017; Accepted August 8, 2017; Published August 31, 2017

Rice blast disease caused by a fungus Magnaporthae oryzae is one of the most important biotic factors that severely damage the rice crop. Several molecular approaches are now being applied to tackle this issue in rice. It is of interest to study long non-coding RNA (lncRNA) in rice to control the disease. lncRNA, a non-coding transcript that does not encode protein, is known to play an important role in gene regulation of various biological processes. Here we describe a computational pipeline to identify lncRNA from a resistant rice line. The number of lncRNA found in resistant line was 1429, 1927 and 1981 in mock and M. oryzae (ZB13 and Zhong) inoculated samples, respectively. Functional classification of these lncRNA reveals a higher number of long intergenic non-coding RNA compared to antisense lncRNA in both mock and M. oryzae inoculated resistant rice lines. Many intergenic lncRNA candidates were identified from resistant rice line and their role to regulate the resistance mechanism in rice during M. oryzae invasion is implied.

Keywords

long non-coding RNA, rice lines resistant, blast pathogen, Maganaporthe oryzae

Citation

Jain et al. Bioinformation 13(8): 249-255 (2017)

Edited by

P Kangueane

ISSN

0973-2063

Publisher

Biomedical Informatics

License

This is an Open Access article which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. This is distributed under the terms of the Creative Commons Attribution License.