Phytophthora root rot is one of the most prevalent diseases in the world,which can infect the seedlings and plants,with substantial negative impact on soybean yield and quality.MicroRNAs （miRNAs） are a class of post-transcriptional regulators of gene expression during growth and development of organisms.A soybean disease-resistance variety Suinong 10 was inoculated with Phytophthora sojae race No.1,and the specific miRNA resistant expression profile was acquired by microarray for the first time.Different expressional miRNAs have been found after comparing the results of the treated sample with the control sample.Furthermore,the target genes of different expressional miRNAs were predicted.Two miRNAs,cbr-mir-241 and ath-miR854a,regulated the disease-resistance process directly through their targets,some enzymes.Another two miRNAs,gma-miR169a and ath-miR169h,participated in disease-resistance regulation as transcription factors.Similarly,one miRNA,ptc-miR164f,has been reported to regulate the plant development.All of these studies would be served as the foundation for exploring the resistance mechanism.
WANG JingLIU Chun-yanZHANG Li-weiWANG Jia-linHU Guo-huaDING Jun-jieCHEN Qing-shan
Diseases caused by fungal pathogens account for approximately 50% of all soybean disease losses around the world. Conflicting results of fungal disease resistance QTLs from different populations often occurred. The objectives of this study were to： （i） evaluate evidence for reported fungal disease resistance QTLs associations in soybean and （ii） extract relatively reliable and useful information from the ＂real＂ QTLs and mine putative genes in soybean. An integrated map of fungal disease resistance QTLs in soybean was established with soymap 2 published in 2004 as a reference map. QTLs of fungal disease resistance developed from each of separate populations in recent 10 years were integrated into a combinative map for gene cloning and marker assisted selection in soybean. 107 QTLs from different maps were integrated and projected to the reference map with the software BioMercator 2.1. A method of meta-analysis was used to narrow down the confidence interval, and 23 ＂real＂ QTLs and their corresponding markers were obtained from 12 linkage groups （LG）, respectively. Two published R genes were found in these ＂real＂ QTLs intervals. Sequences in the ＂real＂ QTLs intervals were predicted by GENSCAN, and these predicted genes were annotated in Goblet. 228 resistance gene analogs （RGAs） in 12 different terms were mined. The results will lay the foundation for a bioinformatics platform combining abundant QTLs, and offer the basis for marker assisted selection and gene cloning in soybean.
WANG Jia-linLIU Chun-yanWANG JingQI Zhao-mingLI HuiHU Guo-huaCHEN Qing-shan
Mature soybean phenotyping is an important process in soybean breeding;however, the manual process is time-consuming and labor-intensive. Therefore, a novel approach that is rapid, accurate and highly precise is required to obtain the phenotypic data of soybean stems, pods and seeds. In this research, we propose a mature soybean phenotype measurement algorithm called Soybean Phenotype Measure-instance Segmentation(SPM-IS). SPM-IS is based on a feature pyramid network, Principal Component Analysis(PCA) and instance segmentation. We also propose a new method that uses PCA to locate and measure the length and width of a target object via image instance segmentation. After 60,000 iterations, the maximum mean Average Precision(m AP) of the mask and box was able to reach 95.7%. The correlation coefficients R^(2) of the manual measurement and SPM-IS measurement of the pod length, pod width, stem length, complete main stem length, seed length and seed width were 0.9755, 0.9872, 0.9692, 0.9803,0.9656, and 0.9716, respectively. The correlation coefficients R^(2) of the manual counting and SPM-IS counting of pods, stems and seeds were 0.9733, 0.9872, and 0.9851, respectively. The above results show that SPM-IS is a robust measurement and counting algorithm that can reduce labor intensity, improve efficiency and speed up the soybean breeding process.
