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Comparison of Gene Expression Data Cluster Methods and Gene Network Construction for Phytophthora Sojae Genes

Author: YueChao
Tutor: ZhangYuanMing
School: Nanjing Agricultural College
Course: Crop Genetics and Breeding
Keywords: gene expression data cluster analysis Calinski-Harabasz index figure of merit correct classification rate gene network Phytophthora sojae
CLC: S435.651
Type: Master's thesis
Year: 2011
Downloads: 19
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Soybean root rot is caused by Phytophthora sojae, and it is one of the devastating diseases in soybean production, with total economic losses estimated at more than 10 billion dollars every year. To understand the genetic basis of the disease caused by Phytophthora sojae, microarray gene expression experiment is helpful. In the data analysis of the gene expression data, cluster analysis and gene network construction were regular approaches. The mined information is useful to soybean genetics and breeding.In this study there were three aspects. First, we needed to select an appropriate approach for cluster analysis of Phytophthora sojae gene expression profiles. Thus, Ma’s et al. (2006), Qu and Xu’s (2006) and Fu and Medico’s (2007) methods were used to analyze 52 simulated datasets and one real data in yeast, and three indicators, being Calinski-Harabasz index (CH), figure of merit (FOM) and correct classification rate (CCR), were used to select the best approach among the above-mentioned approaches. Then, the selected method was used to cluster Phytophthora sojae gene expression profiles and the expression pattern of genes in each cluster was identified. Finally, Edwards’et al (2010) method was used to construct the network of genes in each cluster using the R language package gRapHD. The main results are as follows.1) Fifty-two simulated data and one real data in yeast were analyzed by Ma’s et al. (2006), Qu and Xu’s (2006) and Fu and Medico’s (2007) methods. Results showed that the maximum for CH and CCR and the minimum for FOM were gotten by Ma’s et al (2006) method. This means that Ma’s et al (2006) method is the best among the above-mentioned approaches.2) The best method, Ma et al (2006), was used to cluster the genes in the Phytophthora sojae gene expression profiles. All the 8187 genes were clustered into twenty-one clusters and the number of genes in each cluster was 2593,501,566,381,9,676,105,40,98,1498, 63,126,168,49,795,29,28,28,34,385 and 15, respectively. In the expression trend analysis of the genes,997,792,1425,3993,4226,2824,0,49,9 and 0 genes are up-regulated in Mycelium, Sporangium, zoospore, Cyst, Germinated cyst, Infected 1.5 h, 3.0 h,6.0 h,12.0 h and 24.0 h, respectively; and 446,1084,4056,357,1234,1326,751,34, 74 and 89 genes are down-regulated in the corresponding stages.3) In the Phytophthora sojae genes for each cluster, gene networks were constructed by Edwards’et al (2010) method, along with R language pack gRapHD. A total of 21 gene networks were constructed and 60 key genes that needed to be further confirmed in the future were found and analyzed for their funitions.

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CLC: > Agricultural Sciences > Plant Protection > Pest and Disease Control > Crop pests and diseases and their prevention > Economic crop pests and diseases > Oil Crop pests and diseases > Soybean pests and diseases
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