Literature DB >> 30037991

Identifying a large number of high-yield genes in rice by pedigree analysis, whole-genome sequencing, and CRISPR-Cas9 gene knockout.

Ju Huang1, Jing Li1, Jun Zhou2, Long Wang1, Sihai Yang1, Laurence D Hurst3, Wen-Hsiung Li4,5, Dacheng Tian6.   

Abstract

Repeated artificial selection of a complex trait facilitates the identification of genes underlying the trait, especially if multiple selected descendant lines are available. Here we developed a pedigree-based approach to identify genes underlying the Green Revolution (GR) phenotype. From a pedigree analysis, we selected 30 cultivars including the "miracle rice" IR8, a GR landmark, its ancestors and descendants, and also other related cultivars for identifying high-yield genes. Through sequencing of these genomes, we identified 28 ancestral chromosomal blocks that were maintained in all the high-yield cultivars under study. In these blocks, we identified six genes of known function, including the GR gene sd1, and 123 loci with genes of unknown function. We randomly selected 57 genes from the 123 loci for knockout or knockdown studies and found that a high proportion of these genes are essential or have phenotypic effects related to rice production. Notably, knockout lines have significant changes in plant height (P < 0.003), a key GR trait, compared with wild-type lines. Some gene knockouts or knockdowns were especially interesting. For example, knockout of Os10g0555100, a putative glucosyltransferase gene, showed both reduced growth and altered panicle architecture. In addition, we found that in some retained chromosome blocks several GR-related genes were clustered, although they have unrelated sequences, suggesting clustering of genes with similar functions. In conclusion, we have identified many high-yield genes in rice. Our method provides a powerful means to identify genes associated with a specific trait.

Entities:  

Keywords:  Green Revolution; gene knockout; high-yield gene; pedigree analysis

Mesh:

Year:  2018        PMID: 30037991      PMCID: PMC6094097          DOI: 10.1073/pnas.1806110115

Source DB:  PubMed          Journal:  Proc Natl Acad Sci U S A        ISSN: 0027-8424            Impact factor:   11.205


  32 in total

1.  Inference of population structure using multilocus genotype data.

Authors:  J K Pritchard; M Stephens; P Donnelly
Journal:  Genetics       Date:  2000-06       Impact factor: 4.562

2.  Green revolution: a mutant gibberellin-synthesis gene in rice.

Authors:  A Sasaki; M Ashikari; M Ueguchi-Tanaka; H Itoh; A Nishimura; D Swapan; K Ishiyama; T Saito; M Kobayashi; G S Khush; H Kitano; M Matsuoka
Journal:  Nature       Date:  2002-04-18       Impact factor: 49.962

3.  Regulation of expansin gene expression affects growth and development in transgenic rice plants.

Authors:  Dongsu Choi; Yi Lee; Hyung-Taeg Cho; Hans Kende
Journal:  Plant Cell       Date:  2003-06       Impact factor: 11.277

4.  Gene discovery using mutagen-induced polymorphisms and deep sequencing: application to plant disease resistance.

Authors:  Ying Zhu; Hyung-gon Mang; Qi Sun; Jun Qian; Ashley Hipps; Jian Hua
Journal:  Genetics       Date:  2012-06-19       Impact factor: 4.562

5.  Targeted genome modification of crop plants using a CRISPR-Cas system.

Authors:  Qiwei Shan; Yanpeng Wang; Jun Li; Yi Zhang; Kunling Chen; Zhen Liang; Kang Zhang; Jinxing Liu; Jianzhong Jeff Xi; Jin-Long Qiu; Caixia Gao
Journal:  Nat Biotechnol       Date:  2013-08       Impact factor: 54.908

Review 6.  Zinc-finger transcription factors in plants.

Authors:  H Takatsuji
Journal:  Cell Mol Life Sci       Date:  1998-06       Impact factor: 9.261

7.  Quantitative trait loci (QTL) analysis for rice grain width and fine mapping of an identified QTL allele gw-5 in a recombination hotspot region on chromosome 5.

Authors:  Xiangyuan Wan; Jianfeng Weng; Huqu Zhai; Jiankang Wang; Cailin Lei; Xiaolu Liu; Tao Guo; Ling Jiang; Ning Su; Jianmin Wan
Journal:  Genetics       Date:  2008-08-09       Impact factor: 4.562

Review 8.  The genes of the Green Revolution.

Authors:  Peter Hedden
Journal:  Trends Genet       Date:  2003-01       Impact factor: 11.639

Review 9.  Candidate gene identification approach: progress and challenges.

Authors:  Mengjin Zhu; Shuhong Zhao
Journal:  Int J Biol Sci       Date:  2007-10-25       Impact factor: 6.580

Review 10.  The advantages and limitations of trait analysis with GWAS: a review.

Authors:  Arthur Korte; Ashley Farlow
Journal:  Plant Methods       Date:  2013-07-22       Impact factor: 4.993

View more
  12 in total

1.  The NAC Transcription Factors OsNAC20 and OsNAC26 Regulate Starch and Storage Protein Synthesis.

Authors:  Juan Wang; Zichun Chen; Qing Zhang; Shanshan Meng; Cunxu Wei
Journal:  Plant Physiol       Date:  2020-09-28       Impact factor: 8.340

2.  Dissection of the genetic variation and candidate genes of lint percentage by a genome-wide association study in upland cotton.

Authors:  Chengxiang Song; Wei Li; Xiaoyu Pei; Yangai Liu; Zhongying Ren; Kunlun He; Fei Zhang; Kuan Sun; Xiaojian Zhou; Xiongfeng Ma; Daigang Yang
Journal:  Theor Appl Genet       Date:  2019-04-13       Impact factor: 5.699

Review 3.  Modification of cereal plant architecture by genome editing to improve yields.

Authors:  Xin Huang; Julia Hilscher; Eva Stoger; Paul Christou; Changfu Zhu
Journal:  Plant Cell Rep       Date:  2021-02-09       Impact factor: 4.570

4.  Expansion and Evolutionary Patterns of Glycosyltransferase Family 8 in Gramineae Crop Genomes and Their Expression under Salt and Cold Stresses in Oryza sativa ssp. japonica.

Authors:  Weilong Kong; Ziyun Gong; Hua Zhong; Yue Zhang; Gangqing Zhao; Mayank Gautam; Xiaoxiao Deng; Chang Liu; Chenhao Zhang; Yangsheng Li
Journal:  Biomolecules       Date:  2019-05-15

Review 5.  Modern Trends in Plant Genome Editing: An Inclusive Review of the CRISPR/Cas9 Toolbox.

Authors:  Ali Razzaq; Fozia Saleem; Mehak Kanwal; Ghulam Mustafa; Sumaira Yousaf; Hafiz Muhammad Imran Arshad; Muhammad Khalid Hameed; Muhammad Sarwar Khan; Faiz Ahmad Joyia
Journal:  Int J Mol Sci       Date:  2019-08-19       Impact factor: 5.923

6.  Characterization of the Common Japonica-Originated Genomic Regions in the High-Yielding Varieties Developed from Inter-Subspecific Crosses in Temperate Rice (Oryza sativa L.).

Authors:  Jeonghwan Seo; So-Myeong Lee; Jae-Hyuk Han; Na-Hyun Shin; Yoon Kyung Lee; Backki Kim; Joong Hyoun Chin; Hee-Jong Koh
Journal:  Genes (Basel)       Date:  2020-05-18       Impact factor: 4.096

7.  Exploring Natural Allelic Variations of the β-Triketone Herbicide Resistance Gene HIS1 for Application in indica Rice and Particularly in Two-Line Hybrid Rice.

Authors:  Qiming Lv; Xiuli Zhang; Dingyang Yuan; Zhiyuan Huang; Rui Peng; Jiming Peng; Zuren Li; Li Tang; Ducai Liu; Xiaomao Zhou; Lifeng Wang; Lang Pan; Ye Shao; Bigang Mao; Yeyun Xin; Lihuang Zhu; Bingran Zhao; Lianyang Bai
Journal:  Rice (N Y)       Date:  2021-01-07       Impact factor: 4.783

8.  Using CRISPR-Cas9 to generate semi-dwarf rice lines in elite landraces.

Authors:  Xingming Hu; Yongtao Cui; Guojun Dong; Anhui Feng; Danying Wang; Chunyan Zhao; Yu Zhang; Jiang Hu; Dali Zeng; Longbiao Guo; Qian Qian
Journal:  Sci Rep       Date:  2019-12-13       Impact factor: 4.379

Review 9.  Targeted plant improvement through genome editing: from laboratory to field.

Authors:  Dragana Miladinovic; Dulce Antunes; Kubilay Yildirim; Allah Bakhsh; Sandra Cvejić; Ankica Kondić-Špika; Ana Marjanovic Jeromela; Hilde-Gunn Opsahl-Sorteberg; Antonios Zambounis; Zoe Hilioti
Journal:  Plant Cell Rep       Date:  2021-01-21       Impact factor: 4.570

10.  Genome Editing in Crop Plant Research-Alignment of Expectations and Current Developments.

Authors:  Meike Hüdig; Natalie Laibach; Anke-Christiane Hein
Journal:  Plants (Basel)       Date:  2022-01-14
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.