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Legume genomics: understanding biology through DNA and RNA sequencing
Jamie A O'Rourke1, Yung-Tsi Bolon2, Bruna Bucciarelli1
1United States Department of Agriculture, Agricultural Research Service, University of Minnesota, St. Paul, MN 55108, USA Department of Agronomy and Plant Genetics, University of Minnesota, 1991 Upper Buford Circle, St. Paul, MN 55108, USA.
Background:
The legume family (Leguminosae) consists of approx. 17 000 species. A few of these species, including, but not limited to, Phaseolus vulgaris, Cicer arietinum and Cajanus cajan, are important dietary components, providing protein for approx. 300 million people worldwide. Additional species, including soybean (Glycine max) and alfalfa (Medicago sativa), are important crops utilized mainly in animal feed. In addition, legumes are important contributors to biological nitrogen, forming symbiotic relationships with rhizobia to fix atmospheric N2 and providing up to 30 % of available nitrogen for the next season of crops. The application of high-throughput genomic technologies including genome sequencing projects, genome re-sequencing (DNA-seq) and transcriptome sequencing (RNA-seq) by the legume research community has provided major insights into genome evolution, genomic architecture and domestication.
Scope And Conclusions:
This review presents an overview of the current state of legume genomics and explores the role that next-generation sequencing technologies play in advancing legume genomics. The adoption of next-generation sequencing and implementation of associated bioinformatic tools has allowed researchers to turn each species of interest into their own model organism. To illustrate the power of next-generation sequencing, an in-depth overview of the transcriptomes of both soybean and white lupin (Lupinus albus) is provided. The soybean transcriptome focuses on analysing seed development in two near-isogenic lines, examining the role of transporters, oil biosynthesis and nitrogen utilization. The white lupin transcriptome analysis examines how phosphate deficiency alters gene expression patterns, inducing the formation of cluster roots. Such studies illustrate the power of next-generation sequencing and bioinformatic analyses in elucidating the gene networks underlying biological processes.
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