Computational prediction of human metabolic pathways from the complete human genome

Background  

We present a computational pathway analysis of the human genome that assigns enzymes encoded therein to predicted metabolic pathways. Pathway assignments place genes in their larger biological context, and are a necessary first step toward quantitative modeling of metabolism.     

Findings emerging from complete microbial genome sequences

Sixteen microorganisms, including one eukaryote, four archaeons, and 11 eubacteria, have been completely sequenced and published. More than 50 genomes are scheduled to be completed by the year 2000. This explosive growth of information is forcing change in many scientific disciplines (e.g. bioinformatics and molecular genetics), spawning new fields, and even changing the way scientific information is used and shared. Novel, global genome sequence comparisons seem slow to appear but the infrastructure for these projects is being built, and we expect exciting developments in the near future.     

Complete mitochondrial genome sequences of three Crocodylus species and their comparison within the Order Crocodylia

Host-pathogen interactions are complex processes, and revealing these interactions is challenging. Beauveria bassiana is a destructive pathogen to the economically beneficial silkworm, Bombyx mori, but is also a good pathogenic material for investigating insect responses to fungal infection. For better understanding of the molecular regulation of immune response and the interactive mechanism between the silkworm and B. bassiana, suppression subtractive hybridization was employed to identify differentially expressed genes in the pathogen-stimulated silkworm larvae. Complementary DNA libraries were constructed, in which 240 clones were sequenced. A total of 77 genes were found to be involved in the infection process, among which 55 were known genes and 22 were novel. Expression profiling of 6 genes by quantitative PCR showed that they were induced by fungal challenge. This study establishes the first step to understanding the molecular mechanisms by which silkworm responds to fungal infection.     

Reconstruction of ancient genome and gene order from complete microbial genome sequences

Microbial genome sequences provide us with the fossil records for inferring their origination and evolution. Assuming that current microbial genomes are the evolutionary results of ancient genomes or fragments and the neighboring genes in ancient genomes are more likely neighbors in current genomes, in this paper we proposed a paleontological algorithm and assembled the orthologous gene groups from 66 complete and current microbial genome sequences into a pseudo-ancient genome, which consists of continuous fragments of various sizes. We performed bootstrap resampling and correlation analyses and the results showed that the assembled ancient genome and fragments are statistically significant and the genes of the same fragment are inherently related and likely derived from common ancestors. This method provides a new computational tool for studying microbial genome structure and evolution.     

Computational identification of novel microRNAs and targets in Brassica napus

MicroRNAs (miRNAs) are a newly discovered class of non-protein-coding small RNAs with roughly 22 nucleotide-long. Increasing evidence has shown that miRNAs play multiple roles in biological processes, including development, cell proliferation and apoptosis and stress responses. In this research, several approaches were combined to make computational prediction of potential miRNAs and their targets in Brassica napus. We used previously known miRNAs from Arabidopsis, rice and other plant species against both expressed sequence tags (EST) and genomic survey sequence (GSS) databases to search for potential miRNAs in B. napus. A total of 21 potential miRNAs were detected following a range of strict filtering criteria. Using these potential miRNA sequences, we could further blast the mRNA database and found 67 potential targets in this species. According to the mRNA target information provided by NCBI (http://www.ncbi.nlm.nih.gov/), most of the target mRNAs appeared to be involved in plant growth, development and stress responses. To validate the prediction of miRNAs in B. napus, we performed a RT-PCR based assay of mature miRNA expression. Five miRNAs were identified in response to auxin, cadmium stress and phosphate starvation. So far, little is known about experimental or computational identification of miRNA in B. napus species. To improve efficiency for blast search, we developed an implementation (miRNAassist) that can identify homologs of miRNAs and their targets, with high sensitivity and specificity. The program is allowed to be run on Windows Operation System platform. miRNAassist is freely available if required.