Construction and screening of subtracted cDNA libraries from limited populations of plant cells: a comparative analysis of gene expression between maize egg cells and central cells.

ABSTRACT

The analysis of cell type-specific gene expression is an essential step in understanding certain biological processes during plant development, such as differentiation. Although methods for isolating specific cell types have been established, the application of cDNA subtraction to small populations of isolated cell types for direct identification of specific or differentially expressed transcripts has not yet been reported. As a first step in the identification of genes expressed differentially between maize egg cells and central cells, we have manually isolated these types of cell, and applied a suppression-subtractive hybridization (SSH) strategy. After microarray screening of 1030 cDNAs obtained from the subtracted libraries, we identified 340 differentially expressed clones. Of these, 142 were sequenced, which resulted in the identification of 62 individual cDNAs. The expression patterns of 20 cDNAs were validated by quantitative RT-PCR, through which we identified five transcripts with cell type-specific expression. The specific localization of some of these transcripts was also confirmed by in situ hybridization on embryo sac sections. Taken together, our data demonstrate the effectiveness of our approach in identifying differentially expressed and cell type-specific transcripts of relatively low abundance. This was also confirmed by the identification of previously reported egg cell- and central cell-specific genes in our screen. Importantly, from our analysis we identified a significant number of novel sequences not present in other embryo sac or, indeed, in other plant expressed sequence tag (EST) databases. Thus, in combination with standard EST sequencing and microarray hybridization strategies, our approach of differentially screening subtracted cDNAs will add substantially to the expression information in spatially highly resolved transcriptome analyses.