Literature DB >> 31980835

High-throughput phenotypic screening of random genomic fragments in transgenic rice identified novel drought tolerance genes.

Toshiyuki Komori1, Yuejin Sun2, Masakazu Kashihara3, Natsuko Uekawa3, Norio Kato3, Satoru Usami3, Noriko Ishikawa3, Yukoh Hiei3, Kei Kobayashi3, Rise Kum3, Esteban Bortiri2, Kimberly White2, Paul Oeller2, Naoki Takemori3, Nicholas J Bate2,4, Toshihiko Komari3.   

Abstract

KEY MESSAGE: Novel drought tolerance genes were identified by screening thousands of random genomic fragments from grass species in transgenic rice. Identification of agronomically important genes is a critical step for crop breeding through biotechnology. Multiple approaches have been employed to identify new gene targets, including comprehensive screening platforms for gene discovery such as the over-expression of libraries of cDNA clones. In this study, random genomic fragments from plants were introduced into rice and screened for drought tolerance in a high-throughput manner with the aim of finding novel genetic elements not exclusively limited to coding sequences. To illustrate the power of this approach, genomic libraries were constructed from four grass species, and screening a total of 50,825 transgenic rice lines for drought tolerance resulted in the identification of 12 reproducibly efficacious fragments. Of the twelve, two were from the mitochondrial genome of signal grass and ten were from the nuclear genome of buffalo grass. Subsequent sequencing and analyses revealed that the ten fragments from buffalo grass carried a similar genetic element with no significant homology to any previously characterized gene. The deduced protein sequence was rich in acidic amino acid residues in the C-terminal half, and two of the glutamic acid residues in the C-terminal half were shown to play an important role in drought tolerance. The results demonstrate that an open-ended screening approach using random genomic fragments could discover trait genes distinct from gene discovery based on known pathways or biased toward coding sequence over-expression.

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Year:  2020        PMID: 31980835     DOI: 10.1007/s00122-020-03548-6

Source DB:  PubMed          Journal:  Theor Appl Genet        ISSN: 0040-5752            Impact factor:   5.699


  32 in total

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