[Comparison of statistical methods for detecting differential expression in microarray data].

DNA microarray is a new tool in biotechnology, which allows simultaneously monitoring thousands of gene expression in cells. The goal of differential gene expression analysis is to detect genes with significant change of gene expression levels arising from experimental conditions. Although various statistical methods have been suggested to confirm differential gene expression, only a few studies compared performance of the statistical methods. This paper presented comparison of statistical methods for finding differentially expressed genes (DEGs) from the microarray data. Using simulated and real datasets (Populus cDNA microarray data), we compared eight methods of identifying differential gene expression. The simulated datasets included four differential distributions (normal distribution, uniform distribution, c2 distribution, and exponential distribution). The results of simulated datasets analysis showed that the eight methods were more preferable with the microarray data of uniform distribution than normal distribution. They were not preferable with the c2 distribution and exponential distribution. Of these eight methods, SAM (Significance Analysis of Microarrays) and Wilcoxon rank sum test performed well in most cases. The results of real cDNA microarray data of Populus showed that there was much similarity of SAM, Samroc, and regression modeling approach. Wilcoxon rank sum test was different from them. Samroc and regression modeling approach were similar in the eight methods. For both simulated and real datasets, SAM, Samroc, and regression modeling approach performed better than other methods.

A preliminary analysis of synonymous codon usage in poplar species.

Poplar is among the most important deciduous tree species in plantations over the world and has been used as an important model system for molecular genetics of trees. The analysis of codon usage may improve the understanding of the mechanism of codon distribution and variation in poplar and the understanding of factors shaping the codon usage patterns. Here, an EN(c) (effective number of codons)-plot method and multivariate statistical method called correspondence analysis (COA) were used to examine the codon usage of 314 genes of poplar. The results show that the main trend was highly negative correlated with the gene expression level assessed by the ''Codon Adaptation Index'' value. Moreover, there were two significant correlations between axis 1 coordinates and GC3(s) content and gene length, we infer that gene nucleotide composition and gene length also play an important role in shaping the codon usage bias in poplar. The result of relative synonymous codon usage (RSCU) analysis shows a high bias of codon usage toward the codon with A or T ending. In addition, we compared the codon preferences among poplar, Arabidopsis thaliana, Oryza sative, Homo sapiens and Escherichia coli, and poplar was found to be most similar to A.thaliana and least similar to E.coli. In this paper, 10 codons defined firstly as optimal codons through an analysis of the high-expression codon in poplar may provide some useful information for genetic engineering of poplar.

[Constructing genetic linkage maps in Chinese Fir using F1 progeny].

A new strategy was proposed for constructing linkage maps for 1:1 segregation molecular markers in Chinese fir. Linkage phase and recombination ratio for any two loci can be inferred and estimated. For the best order in a linkage group, the Hidden Markov Chain Model was used for multilocus linkage analysis. The mapping method proposed here was more effective than the 'pseudo-testcross' method commonly used in forest trees. In this paper,with the AFLP marker data obtained from the F1 progeny of 'Jurong 0' (female) x 'Rouye' (male), the genetic linkage maps of the Chinese fir clones, 'Jurong' and 'Rouye', were reconstructed based on the new mapping method. In the genetic linkage map of "Jurong 0", 101 markers were distributed in 11 linkage groups with an average distance of 22.6 cM and a total length of 2 282.6 cM. There were as many as 17 markers and as few as 5 markers in single linkage groups of the map. In the genetic linkage map of 'Rouye', 94 markers were distributed in the 11 linkage groups with an average distance of 27.3 cM and a total length of 2 565.8 cM. There were as many as 16 markers and as few as 4 markers in single linkage groups of the map. Compared with the 'pseudo- testcross' method, the two maps increased 26 markers and 28 markers, respectively, and totally 54 markers were added. The two maps contained 195 AFLP markers and each spanned more than 2 000 cM, almost covering the whole genome of Chinese fir. Therefore, the resolutions of linkage maps of Chinese fir 'Jurong 0' and 'Rouye' were improved with the new mapping method, and the maps provide the framework for further genetic analysis.