Literature DB >> 14502996

Single-nucleotide mutations for plant functional genomics.

Steven Henikoff1, Luca Comai.   

Abstract

In the present genomics era, powerful reverse-genetic strategies are needed to elucidate gene and protein function in the context of a whole organism. However, most current techniques lack the generality and high-throughput potential of descriptive genomic approaches, such as those that rely on microarray hybridization. For example, in plant research, effective insertional mutagenesis and transgenic methods are limited to relatively few species or are inefficient. Fortunately, single-nucleotide changes can be induced in any plant by using traditional chemical mutagens, and progress has been made in efficiently detecting changes. Because base substitutions in proteins provide allelic series, and not just knockouts, this strategy can yield refined insights into protein function. Here, we review recent progress that has been made in genome-wide screening for point mutations and natural variation in plants. Its general applicability leads to the expectation that traditional mutagenesis followed by high-throughput detection will become increasingly important for plant functional genomics.

Mesh:

Year:  2003        PMID: 14502996     DOI: 10.1146/annurev.arplant.54.031902.135009

Source DB:  PubMed          Journal:  Annu Rev Plant Biol        ISSN: 1543-5008            Impact factor:   26.379


  54 in total

1.  Mismatch cleavage by single-strand specific nucleases.

Authors:  Bradley J Till; Chris Burtner; Luca Comai; Steven Henikoff
Journal:  Nucleic Acids Res       Date:  2004-05-11       Impact factor: 16.971

Review 2.  Molecular markers from the transcribed/expressed region of the genome in higher plants.

Authors:  P K Gupta; S Rustgi
Journal:  Funct Integr Genomics       Date:  2004-04-17       Impact factor: 3.410

3.  A single-base substitution suppresses flower color mutation caused by a novel miniature inverted-repeat transposable element in gentian.

Authors:  Masahiro Nishihara; Takashi Hikage; Eri Yamada; Takashi Nakatsuka
Journal:  Mol Genet Genomics       Date:  2011-10-15       Impact factor: 3.291

Review 4.  Computational approaches to study the effects of small genomic variations.

Authors:  Kamil Khafizov; Maxim V Ivanov; Olga V Glazova; Sergei P Kovalenko
Journal:  J Mol Model       Date:  2015-09-08       Impact factor: 1.810

5.  Allele-specific CAPS markers based on point mutations in resistance alleles at the pvr1 locus encoding eIF4E in Capsicum.

Authors:  Inhwa Yeam; Byoung-Cheorl Kang; Wouter Lindeman; James D Frantz; Nanne Faber; Molly M Jahn
Journal:  Theor Appl Genet       Date:  2005-11-09       Impact factor: 5.699

6.  Chemical- and irradiation-induced mutants of indica rice IR64 for forward and reverse genetics.

Authors:  Jian-Li Wu; Chanjian Wu; Cailin Lei; Marietta Baraoidan; Alicia Bordeos; Ma Reina Suzette Madamba; Marilou Ramos-Pamplona; Ramil Mauleon; Arlett Portugal; Victor Jun Ulat; Richard Bruskiewich; Guoliang Wang; Jan Leach; Gurdev Khush; Hei Leung
Journal:  Plant Mol Biol       Date:  2005-09       Impact factor: 4.076

7.  EMS mutagenesis and qPCR-HRM prescreening for point mutations in an embryogenic cell suspension of grapevine.

Authors:  Yosvanis Acanda; Óscar Martínez; María Jesús Prado; María Victoria González; Manuel Rey
Journal:  Plant Cell Rep       Date:  2013-12-21       Impact factor: 4.570

8.  Predicting the effects of coding non-synonymous variants on protein function using the SIFT algorithm.

Authors:  Prateek Kumar; Steven Henikoff; Pauline C Ng
Journal:  Nat Protoc       Date:  2009-06-25       Impact factor: 13.491

Review 9.  Mutagenesis and beyond! Tools for understanding legume biology.

Authors:  Million Tadege; Trevor L Wang; Jiangqi Wen; Pascal Ratet; Kirankumar S Mysore
Journal:  Plant Physiol       Date:  2009-09-09       Impact factor: 8.340

10.  Deletion-based reverse genetics in Medicago truncatula.

Authors:  Christian Rogers; Jiangqi Wen; Rujin Chen; Giles Oldroyd
Journal:  Plant Physiol       Date:  2009-09-16       Impact factor: 8.340

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.