Submitted to: Sequencing
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: August 11, 2012
Publication Date: December 1, 2011
Citation: Tremblay, A., Hosseini, P., Alkharouf, N.W., Li, S., Matthews, B.F. 2011. Gene expression study of phakopsoara pachyrzhiz-glycine max in interaction in susceptible plant using next generation sequencing. Sequencing. doi:10.1155/2011/827250. Interpretive Summary: Soybean is among the top five crops in the U.S. in terms of economic value and numerous pathogens attack this crop. The soybean rust fungus originates from Asia and is an important soybean pathogen which has been in the U.S. since 2004. It can be responsible for 37 to 67% losses in soybean yield. We need to understand the developmental process of this fungus on soybean as well as which soybean genes are affected during the infection process so we can build a new resistance mechanism in soybean through biotechnology. We focused our research on a late stage of infection, 10 days after infection. We used a new technology that allowed us to identify novel soybean and rust genes. With this new technology, we identified numerous genes belonging to soybean that were expressed at a lower level in a rust infected plant as compared to that of a healthy soybean plant. We also identified genes expressed at a higher level in the infected plants. These results demonstrate that the pathogen at the latest stage of infection strongly affects plant metabolism. This information provides candidate genes useful to develop a broader resistance to this pathogen which will be useful in the future for scientists to develop soybean cultivars resistant to rust infection.
Technical Abstract: Soybean is one of the top five agricultural products in the United States. Protection of soybean from pathogens is very important for soybean production. Soybean rust is caused by the obligate fungus Phakopsora pachyrhizi Sydow, an exotic pathogen. This pathogen causes yield important losses. From this perspective we want to analyze the expression pattern of soybean host genes during the infection process to understand molecular events during the infection process. Thus, we constructed and analyzed cDNA libraries by deep sequencing to identify candidate genes that may be useful to provide resistance to P. pachyrhizi. Libraries were constructed from RNA isolated from soybean palisade and mesophyll cells. Samples included non-infected cells as a control and cells 10 days after infection with P. pachyrhizi. The libraries were sequenced using a Solexa/Illumina platform. DNA sequences were aligned to the soybean genome and homology searches were conducted to determine the identity of the genes. We obtained 15 million sequences aligning to the soybean genome. Resulting genes were overlaid on Kyoto Encyclopedia of Genes and Genomes biochemical pathways. Forty-three percent of the genes were down-regulated including genes involved in amino acid and carbohydrate metabolisms as well as transport facilitation while 31% were up-regulated including genes involved in lipid metabolism, glycan biosynthesis and cellular communication and signal transduction. For 26% of the genes expression stayed stable. We also found 9 million sequences without any homology to the soybean genome. These are expected to be P. pachyrhizi sequences and soybean sequences belonging to gaps of the currently known soybean genome sequence. In the future, host genes will be studied to determine if they can be used to control soybean rust in soybean.