Methylation-sensitive amplified polymorphism analysis of Verticillium wilt-stressed cotton (Gossypium).

In this study, a methylation-sensitive amplification polymorphism analysis system was used to analyze DNA methylation level in three cotton accessions. Two disease-sensitive near-isogenic lines, PD94042 and IL41, and one disease-resistant Gossypium mustelinum accession were exposed to Verticillium wilt, to investigate molecular disease resistance mechanisms in cotton. We observed multiple different DNA methylation types across the three accessions following Verticillium wilt exposure. These included hypomethylation, hypermethylation, and other patterns. In general, the global DNA methylation level was significantly increased in the disease-resistant accession G. mustelinum following disease exposure. In contrast, there was no significant difference in the disease-sensitive accession PD94042, and a significant decrease was observed in IL41. Our results suggest that disease-resistant cotton might employ a mechanism to increase methylation level in response to disease stress. The differing methylation patterns, together with the increase in global DNA methylation level, might play important roles in tolerance to Verticillium wilt in cotton. Through cloning and analysis of differently methylated DNA sequences, we were also able to identify several genes that may contribute to disease resistance in cotton. Our results revealed the effect of DNA methylation on cotton disease resistance, and also identified genes that played important roles, which may shed light on the future cotton disease-resistant molecular breeding.

Gene regulatory network identification from the yeast cell cycle based on a neuro-fuzzy system.

Many studies exist for reconstructing gene regulatory networks (GRNs). In this paper, we propose a method based on an advanced neuro-fuzzy system, for gene regulatory network reconstruction from microarray time-series data. This approach uses a neural network with a weighted fuzzy function to model the relationships between genes. Fuzzy rules, which determine the regulators of genes, are very simplified through this method. Additionally, a regulator selection procedure is proposed, which extracts the exact dynamic relationship between genes, using the information obtained from the weighted fuzzy function. Time-series related features are extracted from the original data to employ the characteristics of temporal data that are useful for accurate GRN reconstruction. The microarray dataset of the yeast cell cycle was used for our study. We measured the mean squared prediction error for the efficiency of the proposed approach and evaluated the accuracy in terms of precision, sensitivity, and F-score. The proposed method outperformed the other existing approaches.

Development of EST-SSR markers related to disease resistance and their application in genetic diversity and evolution analysis in Gossypium.

Cotton (Gossypium spp) is one of the most economically important crops that provide the world's most widely used natural fiber. Diseases such as Fusarium wilt and particularly Verticillium wilt seriously affect cotton production, and thus breeding for disease resistance is one of the most important goals of cotton breeding programs. Currently, potential exists to improve disease resistance in cultivated cotton. Increasing the understanding of the distribution, structure, and organization of genes or quantitative trait loci for disease resistance will help the breeders improve crop yield even in the event of disease. To facilitate the mapping of disease-resistance quantitative trait loci to achieve disease-resistant molecular breeding in cotton, it is necessary to develop polymorphic molecular markers. The objective of this study was to develop simple sequence repeat markers based on cotton expressed sequence tags for disease resistance. The efficacy of these simple sequence repeat markers, their polymorphisms, and cross-species transferability were evaluated. Their value was further investigated based on genetic diversity and evolution analysis. In this study, the unique sequences used to develop markers were compared with the G. arboretum and G. raimondii genome sequences to investigate their position, homology, and collinearity between G. arboretum and G. raimondii.

Development of EST-SSR markers related to salt tolerance and their application in genetic diversity and evolution analysis in Gossypium.

Salt stress is becoming one of the major problems in global agriculture with the onset of global warming, an increasing scarcity of fresh water, and improper land irrigation and fertilization practices, which leads to reduction of crop output and even causes crop death. To speed up the exploitation of saline land, it is a good choice to grow plants with a high level of salt tolerance and economic benefits. As the leading fiber crop grown commercially worldwide, cotton is placed in the moderately salt-tolerant group of plant species, and there is promising potential to improve salt tolerance in cultivated cotton. To facilitate the mapping of salt-tolerant quantitative trait loci in cotton so as to serve the aims of salt-tolerant molecular breeding in cotton, it is necessary to develop salt-tolerant molecular markers. The objective of this research was to develop simple sequence repeat (SSR) markers based on cotton salt-tolerant expressed sequence tags. To test the efficacy of these SSR markers, their polymorphism and cross-species transferability were evaluated, and their value was further investigated on the basis of genetic diversity and evolution analysis.