"A system biology" approach to bioinformatics and functional genomics in complex human diseases: arthritis.

Human and other annotated genome sequences have facilitated generation of vast amounts of correlative data, from human/animal genetics, normal and disease-affected tissues from complex diseases such as arthritis using gene/protein chips and SNP analysis. These data sets include genes/proteins whose functions are partially known at the cellular level or may be completely unknown (e.g. ESTs). Thus, genomic research has transformed molecular biology from "data poor" to "data rich" science, allowing further division into subpopulations of subcellular fractions, which are often given an "-omic" suffix. These disciplines have to converge at a systemic level to examine the structure and dynamics of cellular and organismal function. The challenge of characterizing ESTs linked to complex diseases is like interpreting sharp images on a blurred background and therefore requires a multidimensional screen for functional genomics ("functionomics") in tissues, mice and zebra fish model, which intertwines various approaches and readouts to study development and homeostasis of a system. In summary, the post-genomic era of functionomics will facilitate to narrow the bridge between correlative data and causative data by quaint hypothesis-driven research using a system approach integrating "intercoms" of interacting and interdependent disciplines forming a unified whole as described in this review for Arthritis.

Intragenic variation of synonymous substitution rates is caused by nonrandom mutations at methylated CpG.

It has been observed that synonymous substitution rates vary among genes in various organisms, although the cause of the variation is unresolved. At the intragenic level, however, the variation of synonymous substitutions is somewhat controversial. By developing a rigorous statistical test and applying the test to 418 homologous gene pairs between mouse and rat, we found that more than 90% of gene pairs showed a statistical significance in intragenic variation of synonymous substitution rates. Moreover, by examining all conceivable possibilities for the cause of the variation, we successfully found that intragenic variation of synonymous substitutions in mammalian genes is caused mainly by a nonrandom mutation due to the methylation of CpG dinucleotides rather than by functional constraints.

Evolution of nicotinic acetylcholine receptor subunits.

A phylogenetic tree of a gene family of nicotinic acetylcholine receptor subunits was constructed using 84 nucleotide sequences of receptor subunits from 18 different species in order to elucidate the evolutionary origin of receptor subunits. The tree constructed showed that the common ancestor of all subunits may have appeared first in the nervous system. Moreover, we suggest that the alpha 1 subunits in the muscle system originated from the common ancestor of alpha 2, alpha 3, alpha 4, alpha 5, alpha 6, and beta 3 in the nervous system, whereas the beta 1, gamma, delta, and epsilon subunits in the muscle system shared a common ancestor with the beta 2 and beta 4 subunits in the nervous system. Using the ratio (f) of the number of nonsynonymous substitutions to that of synonymous substitutions, we predicted the functional importance of subunits. We found that the alpha 1 and alpha 7 subunits had the lowest f values in the muscle and nervous systems, respectively, indicating that very strong functional constraints work on these subunits. This is consistent with the fact that the alpha 1 subunit has sites binding to the ligand, and the alpha 7-containing receptor regulates the release of the transmitter. Moreover, the window analysis of the f values showed that strong functional constraints work on the so-called M2 region in all five types of muscle subunits. Thus, the window analysis of the f values is useful for evaluating the degree of functional constraints in not only the entire gene region, but also the within-gene subregion.

Evolutionary motif and its biological and structural significance.

We developed a method for multiple alignment of protein sequences. The main feature of this method is that it takes the evolutionary relationships of the proteins in question into account repeatedly for execution, until the relationships and alignment results are in agreement. We then applied this method to the data of the international DNA sequence databases, which are the most comprehensive and updated DNA databases in the world, in order to estimate the "evolutionary motif" by extensive use of a supercomputer. Though a few problems needed to be solved, we could estimate the length of the motifs in the range of 20 to 200 amino acids, with about 60 the most frequent length. We then discussed their biological and structural significance. We believe that we are now in a position to analyze DNA and protein not only in vivo and in vitro but also in silico.