Regulation of gene expression during embryogenesis and development is a crucial clue for a normal anatomy and physiology. In fact, very little is known regarding factors that influence and regulate developmental gene expression. Similarly, there is little information available concerning the effects of a coordinate expression of a group of functionally related genes. The analysis of temporal patterns of gene expression in embryos is essential for the understanding of the molecular mechanisms that control development. This scientific field has been innovated by the combined use of experimental high-throughput methods, such as DNA microarrays, and bioinformatic methods that take advantage of the completion of the human genome sequence, along with the genomes of related species. Microarray analysis, in fact, provides a large amount of data -at molecular level- that once acquired, must be functionally integrated in order to find common patterns within a defined group of biological samples. Following the enormous number of data obtained from these experiments, a new type of comparative embryology is now emerging, and it is based on the comparison of gene expression patterns. The sequencing of several new genomes, the increasing computational power and new bioinformatic algorithms cooperate to overcome some of the intrinsic difficulties in the study of gene regulation, thus permitting, for example, to identify regulation sites located far away from the genes. Recent bioinformatic methods applied to gene regulation are reviewed that either follow the "single species, many genes" approach or the "single gene, many species" one.In this chapter we would review the new application of DNA microarray and bioinformatics to define a new combinatorial approach for analysis of gene expression during development.
|Title of host publication||Developmental Gene Expression Regulation|
|Publisher||Nova Science Publishers, Inc.|
|Number of pages||26|
|Publication status||Published - 2009|
ASJC Scopus subject areas
- Biochemistry, Genetics and Molecular Biology(all)