Literature DB >> 26301381

Genetic resources offer efficient tools for rice functional genomics research.

Shuen-Fang Lo1,2, Ming-Jen Fan3, Yue-Ie Hsing4, Liang-Jwu Chen2,5, Shu Chen6, Ien-Chie Wen6, Yi-Lun Liu1,2, Ku-Ting Chen1, Mirng-Jier Jiang1,2, Ming-Kuang Lin1,2, Meng-Yen Rao1, Lin-Chih Yu1, Tuan-Hua David Ho2,4,7, Su-May Yu1,2,7.   

Abstract

Rice is an important crop and major model plant for monocot functional genomics studies. With the establishment of various genetic resources for rice genomics, the next challenge is to systematically assign functions to predicted genes in the rice genome. Compared with the robustness of genome sequencing and bioinformatics techniques, progress in understanding the function of rice genes has lagged, hampering the utilization of rice genes for cereal crop improvement. The use of transfer DNA (T-DNA) insertional mutagenesis offers the advantage of uniform distribution throughout the rice genome, but preferentially in gene-rich regions, resulting in direct gene knockout or activation of genes within 20-30 kb up- and downstream of the T-DNA insertion site and high gene tagging efficiency. Here, we summarize the recent progress in functional genomics using the T-DNA-tagged rice mutant population. We also discuss important features of T-DNA activation- and knockout-tagging and promoter-trapping of the rice genome in relation to mutant and candidate gene characterizations and how to more efficiently utilize rice mutant populations and datasets for high-throughput functional genomics and phenomics studies by forward and reverse genetics approaches. These studies may facilitate the translation of rice functional genomics research to improvements of rice and other cereal crops.
© 2015 John Wiley & Sons Ltd.

Entities:  

Keywords:  T-DNA; functional genomics; gene activation; gene knockout; promoter trapping; rice

Mesh:

Year:  2015        PMID: 26301381     DOI: 10.1111/pce.12632

Source DB:  PubMed          Journal:  Plant Cell Environ        ISSN: 0140-7791            Impact factor:   7.228


  11 in total

1.  The 2'-O-methyladenosine nucleoside modification gene OsTRM13 positively regulates salt stress tolerance in rice.

Authors:  Youmei Wang; Dongqin Li; Junbao Gao; Xukai Li; Rui Zhang; Xiaohuan Jin; Zhen Hu; Bo Zheng; Staffan Persson; Peng Chen
Journal:  J Exp Bot       Date:  2017-03-01       Impact factor: 6.992

2.  Editorial: Genomics and Functional Genomics of Stress-mediated Signaling in Plants: Volume II.

Authors:  Manisha Sharma; Girdhar K Pandey
Journal:  Curr Genomics       Date:  2018-01       Impact factor: 2.236

3.  EAT-Rice: A predictive model for flanking gene expression of T-DNA insertion activation-tagged rice mutants by machine learning approaches.

Authors:  Chi-Chou Liao; Liang-Jwu Chen; Shuen-Fang Lo; Chi-Wei Chen; Yen-Wei Chu
Journal:  PLoS Comput Biol       Date:  2019-05-08       Impact factor: 4.475

4.  Osa-miR7695 enhances transcriptional priming in defense responses against the rice blast fungus.

Authors:  Ferran Sánchez-Sanuy; Cristina Peris-Peris; Shiho Tomiyama; Kazunori Okada; Yue-Ie Hsing; Blanca San Segundo; Sonia Campo
Journal:  BMC Plant Biol       Date:  2019-12-18       Impact factor: 4.215

5.  A T-DNA mutant screen that combines high-throughput phenotyping with the efficient identification of mutated genes by targeted genome sequencing.

Authors:  Ulrike Frank; Susanne Kublik; Dörte Mayer; Marion Engel; Michael Schloter; Jörg Durner; Frank Gaupels
Journal:  BMC Plant Biol       Date:  2019-12-04       Impact factor: 4.215

6.  Lack of Genotype and Phenotype Correlation in a Rice T-DNA Tagged Line Is Likely Caused by Introgression in the Seed Source.

Authors:  Fu-Jin Wei; Yuan-Ching Tsai; Yu-Ming Hsu; Yu-An Chen; Ching-Ting Huang; Hshin-Ping Wu; Lin-Tzu Huang; Ming-Hsin Lai; Lin-Yun Kuang; Shuen-Fang Lo; Su-May Yu; Yann-Rong Lin; Yue-Ie Caroline Hsing
Journal:  PLoS One       Date:  2016-05-17       Impact factor: 3.240

7.  Large-scale phenomics analysis of a T-DNA tagged mutant population.

Authors:  Hshin-Ping Wu; Fu-Jin Wei; Cheng-Chieh Wu; Shuen-Fang Lo; Liang-Jwu Chen; Ming-Jen Fan; Shu Chen; Ien-Chie Wen; Su-May Yu; Tuan-Hua David Ho; Ming-Hsin Lai; Yue-Ie C Hsing
Journal:  Gigascience       Date:  2017-08-01       Impact factor: 6.524

8.  Candidate regulators of Early Leaf Development in Maize Perturb Hormone Signalling and Secondary Cell Wall Formation When Constitutively Expressed in Rice.

Authors:  Peng Wang; Shanta Karki; Akshaya K Biswal; Hsiang-Chun Lin; Mary Jacqueline Dionora; Govinda Rizal; Xiaojia Yin; Mara L Schuler; Tom Hughes; Jim P Fouracre; Basel Abu Jamous; Olga Sedelnikova; Shuen-Fang Lo; Anindya Bandyopadhyay; Su-May Yu; Steven Kelly; W Paul Quick; Jane A Langdale
Journal:  Sci Rep       Date:  2017-07-03       Impact factor: 4.379

Review 9.  Functional genomic approaches to improve crop plant heat stress tolerance.

Authors:  Baljeet Singh; Neha Salaria; Kajal Thakur; Sarvjeet Kukreja; Shristy Gautam; Umesh Goutam
Journal:  F1000Res       Date:  2019-10-04

Review 10.  Mutagenesis in Rice: The Basis for Breeding a New Super Plant.

Authors:  Vívian Ebeling Viana; Camila Pegoraro; Carlos Busanello; Antonio Costa de Oliveira
Journal:  Front Plant Sci       Date:  2019-11-08       Impact factor: 5.753

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