Genetic markers for search of rhizobia based on symbiotic genes

The possible application of rhizobial symbiotic genes as markers for the search and primary identification of rhizobia from temperate-zone legumes was studied. It was shown that conservative sym genes nifH and nifD could be used as markers for rapid search of rhizobia among the analyzed isolates, while more variable genes nifK and nodC could be used for their primary identification. Efficiency of the proposed method was shown in analysis of bacterial isolates obtained from Onobrychis arenaria and Astragalus cicer root nodules.     

Homology search for genes

MOTIVATION: Life science researchers often require an exhaustive list of protein coding genes similar to a given query gene. To find such genes, homology search tools, such as BLAST or PatternHunter, return a set of high-scoring pairs (HSPs). These HSPs then need to be correlated with existing sequence annotations, or assembled manually into putative gene structures. This process is error-prone and labor-intensive, especially in genomes without reliable gene annotation. RESULTS: We have developed a homology search solution that automates this process, and instead of HSPs returns complete gene structures. We achieve better sensitivity and specificity by adapting a hidden Markov model for gene finding to reflect features of the query gene. Compared to traditional homology search, our novel approach identifies splice sites much more reliably and can even locate exons that were lost in the query gene. On a testing set of 400 mouse query genes, we report 79% exon sensitivity and 80% exon specificity in the human genome based on orthologous genes annotated in NCBI HomoloGene. In the same set, we also found 50 (12%) gene structures with better protein alignment scores than the ones identified in HomoloGene. AVAILABILITY: The Java implementation is available for download from http://www.bioinformatics.uwaterloo.ca/software.     

A search for susceptibility genes in multiple sclerosis

Multiple sclerosis is a chronic inflammatory, putatively autoimmune disease characterized by multifocal demyelination in the central nervous system. Two main strategies are used to identify genes influencing the susceptibility to multiple sclerosis: (i) elucidation of the role of a candidate gene chosen on the basis of the possible function of the encoded protein in etiology and/or pathogenesis of the disease, and (ii) complete genomic screen using a panel of anonymous genetic markers for identification of the chromosome regions involved in the disease development. The complete genomic search revealed multiple loci for multiple sclerosis on thirteen chromosomes, and analysis of the candidate genes added three more chromosomes to this list. The combined data prove the polygenic nature of this complex disease. Detection of individual genes responsible for susceptibility to multiple sclerosis is complicated by the genetic heterogeneity of analyzed populations and families, which is determined both by the ethnic heterogeneity and the peculiarity of clinical forms of the disease. However, it seems highly probable that HLA and non-HLA genes of the major histocompatibility complex, as well as some unidentified genes on chromosomes 5p and 17q, are involved in the disease development. In addition to HLA, some authors have also shown that a role in the disease development is played by the genes encoding other components of the trimolecular complex involved in antigen presentation: those of the T-cell receptor and the best studied autoantigen, the myelin basic protein. The most promising for further studies of the genetic susceptibility to multiple sclerosis are approaches that combine the candidate-gene strategy with the complete genomic search as well as distinguish the genetically differentiated forms of the disease.     

A high-density differential screening strategy for identification of fovea genes with altered expression in the retina during aging

A human fovea cDNA library was arrayed at high-density and reacted with age-specific (4 yr & 80 yr) retinal probes to identify genes with altered expression during aging. Using this approach, we screened 55,368 genes by Southern analysis and determined that 0.7% are differentially expressed in young and old tissues. Northern analysis of total RNA from retina of humans aged 2–94 yr show that expression of one of the clones identified (clone dd₁₁₂) decreases with aging.     

A computer program to search for tRNA genes.

This paper describes a computer program that can find tRNA genes within long DNA sequences. The program obviates the need to map the tRNA genes.     

An efficient model development strategy for bioprocesses based on neural networks in macroscopic balances

In the serial gray box modeling strategy, generally available knowledge, represented in the macroscopic balance, is combined naturally with neural networks, which are powerful and convenient tools to model the inaccurately known terms in the macroscopic balance. This article shows, for a typical biochemical conversion, that in the serial gray box modeling strategy the identification data only have to cover the input-output space of the inaccurately known term in the macroscopic balances and that the accurately known terms can be used to achieve reliable extrapolation. The strategy is demonstrated successfully on the modeling of the enzymatic (repeated) batch conversion of penicillin G, for which real-time results are presented. Compared with a more data-driven black box strategy, the serial gray box strategy leads to models with reliable extrapolation properties, so that with the same number of identification experiments the model can be applied to a much wider range of different conditions. Compared to a more knowledge-driven white box strategy, the serial gray box model structure is only based on readily available or easily obtainable knowledge, so that the development time of serial gray box models still may be short in a situation where there is no detailed knowledge of the system available. (c) 1997 John Wiley & Sons, Inc. Biotechnol Bioeng 53: 549-566, 1997.     

Targeting Alzheimer's disease genes with RNA interference: an efficient strategy for silencing mutant alleles

Tau and amyloid precursor protein (APP) are key proteins in the pathogenesis of sporadic and inherited Alzheimer’s disease. Thus, developing ways to inhibit production of these proteins is of great research and therapeutic interest. The selective silencing of mutant alleles, moreover, represents an attractive strategy for treating inherited dementias and other dominantly inherited disorders. Here, using tau and APP as model targets, we describe an efficient method for producing small interfering RNA (siRNA) against essentially any targeted region of a gene. We then use this approach to develop siRNAs that display optimal allele-specific silencing against a well-characterized tau mutation (V337M) and the most widely studied APP mutation (APPsw). The allele-specific RNA duplexes identified by this method then served as templates for constructing short hairpin RNA (shRNA) plasmids that successfully silenced mutant tau or APP alleles. These plasmids should prove useful in experimental and therapeutic studies of Alzheimer’s disease. Our results suggest guiding principles for the production of allele-specific siRNA, and the general method described here should facilitate the production of gene-specific siRNAs.     

The search for human osteoporosis genes

Osteoporosis is the most prevalent metabolic bone disease and a major clinical and public health problem. Heredity plays an important and well-established role in determining the lifetime risk of this disease. Major efforts are currently underway to identify the specific genes and their allelic variations that contribute to the heritable component to osteoporosis. A number of laboratories are using quantitative trait locus (QTL) methods of genome scanning in families and animal models to identify candidate genomic regions and, ultimately, the genes and genetic variations that lead to osteoporosis. Several chromosomal regions of the human genome have now been linked to osteoporosis-related phenotypes. Although the specific genes contributing to the majority of these linkage signals have not been identified, two positional candidate genes have now been identified: low density lipoprotein receptor-related protein 5 (LRP5) and bone morphogenetic protein 2 (BMP2). A number of QTL has also been identified by cross-breeding strains of mice with variable bone density and several of these QTL have been fine mapped, providing a rich new base for understanding osteoporosis. Genetic association analyses have also provided evidence for a modest relationship between allelic variants in several biological candidate genes and bone mass and the risk of fracture. These ongoing animal and human studies will provide a continuing source of new insight into the genetic regulation of bone and mineral metabolism and the molecular etiology of osteoporosis. The new insight that will emerge from this ongoing research should lead to new ways of diagnosing, preventing and treating the growing clinical and public health problem of osteoporosis.     

The search for nonconventional mitochondrial determinants of aging

Mitochondria are conventionally believed to modulate aging by affecting free-radical production and the energy supply. In this issue of Molecular Cell, Caballero et?al. (2011) reveal that altering protein complexes involved in mitochondrial translation control extends life span independent of redox homeostasis and oxidative phosphorylation.     

A practical and robust sequence search strategy for structural genomics target selection

MOTIVATION: Target selection strategies for structural genomic projects must be able to prioritize gene regions on the basis of significant sequence similarity with proteins that have already been structurally determined. With the rapid development of protein comparison software a robust prioritization scheme should be independent of the choice of algorithm and be able to incorporate different sequence similarity thresholds. RESULTS: A robust target selection strategy has been developed that can assign a priority level to all genes in any genome. Structural assignments to genome sequences are calculated at two thresholds and six levels (1-6) describe the prioritization of all whole genes and partial gene regions. This simple two-threshold approach can be implemented with any fold recognition or homology detection algorithms. The results for 10 genomes are presented using the SSEARCH and PSI-BLAST programs. AVAILABILITY: Programs are available on request from the authors.     

A PCR amplification strategy for unrestricted generation of chimeric genes

For analyzing protein function, protein dynamics, or protein–protein interactions, the use of chimeric proteins has become an indispensable tool. The generation of DNA constructs coding for such fused proteins can, however, be a tedious process. Currently used strategies often make use of available endonuclease sites, leading to limitations in the choice of the site of fusion between two genes and problems in maintaining protein secondary structure. We have developed a cloning strategy to get around these disadvantages that is based on a single round of PCR amplification followed by antibiotic-resistant gene complementation.     

Large-scale search for genes on which positive selection may operate

We conducted a systematic search for the candidate genes on which positive selection may operate, on the premise that for such genes the number of nonsynonymous substitution is expected to be larger than that of synonymous substitutions when the nucleotide sequences of genes under investigation are compared with each other. By obtaining 3,595 groups of homologous sequences from the DDBJ, EMBL, and GenBank DNA sequence databases, we found that 17 gene groups can be the candidates for the genes on which positive selection may operate. Thus, such genes are found to occupy only about 0.5% of the vast number of gene groups so far available. Interestingly enough 9 out of the 17 gene groups were the surface antigens of parasites or viruses.