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Functional genomics of soybean for improvement of productivity in adverse conditions

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Abstract

Global soybean production is frequently impacted by various stresses, including both abiotic and biotic stresses. To develop soybean plants with enhanced tolerance to different stressors, functional genomics of soybean and a comprehensive understanding of available biotechnological resources and approaches are essential. In this review, we will discuss recent advances in soybean functional genomics which provide unprecedented opportunities to understand global patterns of gene expression, gene regulatory networks, various physiological, biochemical, and metabolic pathways as well as their association with the development of specific phenotypes. Soybean functional genomics, therefore, will ultimately enable us to develop new soybean varieties with improved productivity under adverse conditions by genetic engineering.

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Abbreviations

EST:

Expressed sequence tag

FL-cDNA:

Full-length cDNA

GO:

Gene ontology

LG:

Linkage group

MAS:

Marker-assisted selection

MS:

Mass spectrometry

QTL:

Quantitative trait locus

RIL:

Recombinant inbred lines

SCN:

Soybean cyst nematode

SBR:

Soybean rust

TF:

Transcription factor

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Acknowledgments

Research in Tran’s lab is supported by Grants-in-Aid (Start-up) for Scientific Research (No. 21870046) from Ministry of Education, Culture, Sports, Science and Technology of Japan, and by Start-up Support grant (No. M36-57000) from Yokohama Institute Director Discretionary Funds.

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  1. RIKEN Plant Science Center, 1-7-22, Suehiro-cho, Tsurumi, Yokohama, 230-0045, Japan

    Lam-Son Phan Tran & Keiichi Mochida

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  1. Lam-Son Phan Tran
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  2. Keiichi Mochida
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Correspondence to Lam-Son Phan Tran.

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Tran, LS.P., Mochida, K. Functional genomics of soybean for improvement of productivity in adverse conditions. Funct Integr Genomics 10, 447–462 (2010). https://doi.org/10.1007/s10142-010-0178-z

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