Genetic analysis of heat shock proteins in maize

A genetic analysis of heat shock protein (HSP) synthesis was performed in seedling leaf tissue of two maize inbred lines, their F₁ hybrid and F₂ progeny. Protein synthesis following a high temperature treatment was visualized by [³⁵S]-methionine in vivo labelling and two-dimensional gel electrophoresis. The parental lines' HSP synthesis patterns revealed both qualitative and quantitative polymorphisms implicative of differences in HSP structural genes and regulatory factors. The F₁ hybrid HSP profile indicated that synthesis of all parental HSPs conformed to dominant inheritance patterns, including complete dominance, over-dominance and co-dominance. Alleles for six low-molecularweight HSPs in F₂ progeny assorted according to typical 31 Mendelian ratios for dominant gene expression. There is evidence for unlinked gene loci of four different HSP gene pairs, but data for three other HSP gene pairs were inconclusive, perhaps reflecting linkage for one pair and complex regulatory factor interactions for the other two pairs of genes. These results clearly indicate the existence of genetic variability in HSP synthesis and emphasize the potential of partitioning their roles in thermal tolerance using genetic and molecular analyses.     

Genetic characterization and regulation of the nadB locus of Salmonella typhimurium.

The nadB locus encodes the first enzyme of NAD synthesis. It has been reported that this gene and nadA are regulated by a positive regulatory protein encoded in the nadB region. In pursuing this regulatory mechanism, we constructed a fine-structure genetic map of the nadB gene. The region appears to include a single complementation group; no evidence for a positive regulatory element was found. Several mutations causing resistance to the analog 6-aminonicotinamide mapped within the structural gene and probably cause resistance to feedback inhibition. Regulatory mutations for nadB were isolated. These mutants mapped far from nadB near the pnuA gene, which encodes a function required for nicotinamide mononucleotide transport. The regulatory mutations appear to affect a distinct function encoded in the same operon as pnuA.     

Bacterioopsin-mediated regulation of bacterioruberin biosynthesis in Halobacterium salinarum

Integral membrane protein complexes consisting of proteins and small molecules that act as cofactors have important functions in all organisms. To form functional complexes, cofactor biosynthesis must be coordinated with the production of corresponding apoproteins. To examine this coordination, we study bacteriorhodopsin (BR), a light-induced proton pump in the halophilic archaeon Halobacterium salinarum. This complex consists of a retinal cofactor and bacterioopsin (BO), the BR apoprotein. To examine possible novel regulatory mechanisms linking BO and retinal biosynthesis, we deleted bop, the gene that encodes BO. bop deletion resulted in a dramatic increase of bacterioruberins, carotenoid molecules that share biosynthetic precursors with retinal. Additional studies revealed that bacterioruberins accumulate in the absence of BO regardless of the presence of retinal or BR, suggesting that BO inhibits bacterioruberin biosynthesis to increase the availability of carotenoid precursors for retinal biosynthesis. To further examine this potential regulatory mechanism, we characterized an enzyme, encoded by the lye gene, that catalyzes bacterioruberin biosynthesis. BO-mediated inhibition of bacterioruberin synthesis appears to be specific to the H. salinarum lye-encoded enzyme, as expression of a lye homolog from Haloferax volcanii, a related archaeon that synthesizes bacterioruberins but lacks opsins, resulted in bacterioruberin synthesis that was not reduced in the presence of BO. Our results provide evidence for a novel regulatory mechanism in which biosynthesis of a cofactor is promoted by apoprotein-mediated inhibition of an alternate biochemical pathway. Specifically, BO accumulation promotes retinal production by inhibiting bacterioruberin biosynthesis.     

Evaluating the role of natural selection in the evolution of gene regulation

Surveys of gene expression reveal extensive variability both within and between a wide range of species. Compelling cases have been made for adaptive changes in gene regulation, but the proportion of expression divergence attributable to natural selection remains unclear. Distinguishing adaptive changes driven by positive selection from neutral divergence resulting from mutation and genetic drift is critical for understanding the evolution of gene expression. Here, we review the various methods that have been used to test for signs of selection in genomic expression data. We also discuss properties of regulatory systems relevant to neutral models of gene expression. Despite some potential caveats, published studies provide considerable evidence for adaptive changes in gene expression. Future challenges for studies of regulatory evolution will be to quantify the frequency of adaptive changes, identify the genetic basis of expression divergence and associate changes in gene expression with specific organismal phenotypes.     

A "tagless" strategy for identification of stable protein complexes genome-wide by multidimensional orthogonal chromatographic separation and iTRAQ reagent tracking

Tandem affinity purification is the principal method for purifying and identifying stable protein complexes system-wide in whole cells. Although highly effective, this approach is laborious and impractical in organisms where genetic manipulation is not possible. Here, we propose a novel "tagless" strategy that combines multidimensional separation of endogenous complexes with mass spectrometric monitoring of their composition. In this procedure, putative protein complexes are identified based on the comigration of collections of polypeptides through multiple orthogonal separation steps. We present proof-of-principle evidence for the feasibility of key aspects of this strategy. A majority of Escherichia coli proteins are shown to remain in stable complexes during fractionation of a crude extract through three chromatographic steps. We also demonstrate that iTRAQ reagent-based tracking can quantify relative migration of polypeptides through chromatographic separation media. LC MALDI MS and MS/MS analysis of the iTRAQ-labeled peptides gave reliable relative quantification of 37 components of 13 known E. coli complexes: 95% of known complex components closely co-eluted and 57% were automatically grouped by a prototype computational clustering method. With further technological improvements in each step, we believe this strategy will dramatically improve the efficiency of the purification and identification of protein complexes in cells.     

Gradient Descent Optimization in Gene Regulatory Pathways

Background

Gene Regulatory Networks (GRNs) have become a major focus of interest in recent years. Elucidating the architecture and dynamics of large scale gene regulatory networks is an important goal in systems biology. The knowledge of the gene regulatory networks further gives insights about gene regulatory pathways. This information leads to many potential applications in medicine and molecular biology, examples of which are identification of metabolic pathways, complex genetic diseases, drug discovery and toxicology analysis. High-throughput technologies allow studying various aspects of gene regulatory networks on a genome-wide scale and we will discuss recent advances as well as limitations and future challenges for gene network modeling. Novel approaches are needed to both infer the causal genes and generate hypothesis on the underlying regulatory mechanisms.

Methodology

In the present article, we introduce a new method for identifying a set of optimal gene regulatory pathways by using structural equations as a tool for modeling gene regulatory networks. The method, first of all, generates data on reaction flows in a pathway. A set of constraints is formulated incorporating weighting coefficients. Finally the gene regulatory pathways are obtained through optimization of an objective function with respect to these weighting coefficients. The effectiveness of the present method is successfully tested on ten gene regulatory networks existing in the literature. A comparative study with the existing extreme pathway analysis also forms a part of this investigation. The results compare favorably with earlier experimental results. The validated pathways point to a combination of previously documented and novel findings.

Conclusions

We show that our method can correctly identify the causal genes and effectively output experimentally verified pathways. The present method has been successful in deriving the optimal regulatory pathways for all the regulatory networks considered. The biological significance and applicability of the optimal pathways has also been discussed. Finally the usefulness of the present method on genetic engineering is depicted with an example.     

Dosage balance in gene regulation: biological implications

Classical studies in genetics involving aneuploidy and ploidy comparisons and sex-determination mechanisms indicated a balance phenomenon such that changes of individual chromosomal dosage altered the phenotype more dramatically than changes in ploidy. Recent evidence suggests that a major contributor to this balance is the behavior of molecular complexes that function in various regulatory processes affecting gene expression. In this article, we discuss the potential contribution of regulatory balance to the control of quantitative traits, hybrid vigor, genome evolution and post-zygotic speciation mechanisms.     

Selection, adaptation, and bacterial operons

Bacteria are especially useful as systems to study the molecular basis of adaptive evolution. Selection for novel metabolic capabilities has allowed us to study the evolutionary potential of organisms and has shown that there are three major "strategies" for the evolution of new metabolic functions. (i) Regulatory mutations may allow a gene to be expressed under unusual conditions. If the product of that gene is already active toward a novel resource, then a regulatory mutation alone may confer a new metabolic capability. (ii) Structural gene mutations may alter the catalytic properties of enzymes so that they can act on novel substrates. These structural gene mutations may dramatically improve catalytic capabilities, and in some cases they can confer entirely new capabilities upon enzymes. In most cases both regulatory and structural gene mutations are required for the effective evolution of new metabolic functions. (iii) Operons that are normally silent, or cryptic, may be activated by either point mutations or by the action of mobile genetic elements. When activated, these operons can provide entirely new pathways for the metabolism of novel resources. Selection can also play a role in modulating the probability that a particular adaptive mutation will occur. In this paper I present evidence that a specific adaptive mutation, reversion of the metB1 mutation, occurs 60 to 80 times more frequently during prolonged selection on plates under conditions where the members of the population are not growing than it does in growing cells under nonselective conditions. This selective condition, methionine starvation, does not increase the frequency of other mutations unrelated to methionine biosynthesis.(ABSTRACT TRUNCATED AT 250 WORDS)     

Network- and attribute-based classifiers can prioritize genes and pathways for autism spectrum disorders and intellectual disability

Autism spectrum disorders (ASD) are a group of related neurodevelopmental disorders with significant combined prevalence (～1%) and high heritability. Dozens of individually rare genes and loci associated with high-risk for ASD have been identified, which overlap extensively with genes for intellectual disability (ID). However, studies indicate that there may be hundreds of genes that remain to be identified. The advent of inexpensive massively parallel nucleotide sequencing can reveal the genetic underpinnings of heritable complex diseases, including ASD and ID. However, whole exome sequencing (WES) and whole genome sequencing (WGS) provides an embarrassment of riches, where many candidate variants emerge. It has been argued that genetic variation for ASD and ID will cluster in genes involved in distinct pathways and protein complexes. For this reason, computational methods that prioritize candidate genes based on additional functional information such as protein-protein interactions or association with specific canonical or empirical pathways, or other attributes, can be useful. In this study we applied several supervised learning approaches to prioritize ASD or ID disease gene candidates based on curated lists of known ASD and ID disease genes. We implemented two network-based classifiers and one attribute-based classifier to show that we can rank and classify known, and predict new, genes for these neurodevelopmental disorders. We also show that ID and ASD share common pathways that perturb an overlapping synaptic regulatory subnetwork. We also show that features relating to neuronal phenotypes in mouse knockouts can help in classifying neurodevelopmental genes. Our methods can be applied broadly to other diseases helping in prioritizing newly identified genetic variation that emerge from disease gene discovery based on WES and WGS.     

Multi-way metamodelling facilitates insight into the complex input-output maps of nonlinear dynamic models

Background

The physical periphery of a biological cell is mainly described by signaling pathways which are triggered by transmembrane proteins and receptors that are sentinels to control the whole gene regulatory network of a cell. However, our current knowledge about the gene regulatory mechanisms that are governed by extracellular signals is severely limited.

Results

The purpose of this paper is three fold. First, we infer a gene regulatory network from a large-scale B-cell lymphoma expression data set using the C3NET algorithm. Second, we provide a functional and structural analysis of the largest connected component of this network, revealing that this network component corresponds to the peripheral region of a cell. Third, we analyze the hierarchical organization of network components of the whole inferred B-cell gene regulatory network by introducing a new approach which exploits the variability within the data as well as the inferential characteristics of C3NET. As a result, we find a functional bisection of the network corresponding to different cellular components.

Conclusions

Overall, our study allows to highlight the peripheral gene regulatory network of B-cells and shows that it is centered around hub transmembrane proteins located at the physical periphery of the cell. In addition, we identify a variety of novel pathological transmembrane proteins such as ion channel complexes and signaling receptors in B-cell lymphoma.     

Peptide pheromone-induced transfer of plasmid pCF10 in Enterococcus faecalis: probing the genetic and molecular basis for specificity of the pheromone response

The tetracycline resistance plasmid pCF10 represents a class of unique mobile genetic elements of the bacterial genus Enterococcus, whose conjugative transfer functions are inducible by peptide sex pheromones excreted by potential recipient cells. These plasmids play a significant role in the dissemination of virulence and antibiotic resistance genes among the enterococci, which have become major nosocomial pathogens. Pheromone response by plasmid-carrying donor cells involves specific import of the peptide signal molecule, and subsequent interaction of the signal with one or more intracellular regulatory gene products. The pheromones are chromosomally encoded hydrophobic octa- or hepta-peptides, and different families of homologous plasmids encode the ability to respond to each pheromone. Among the four pheromone-responsive plasmids that have been characterized in some detail, there is considerable conservation in the genes encoding pheromone sensing and regulatory functions, and the peptides themselves show considerable similarity. In spite of this, there is extremely high specificity of response to each peptide, with virtually no "cross-induction" of transfer of non-cognate pheromone plasmids by the pheromones. This communication reviews the evidence for this specificity and discusses current molecular and genetic approaches to defining the basis for specificity.     

Whole genome sequencing identifies <Emphasis Type="Italic">ANXA3</Emphasis> and <Emphasis Type="Italic">MTHFR</Emphasis> mutations in a large family with an unknown equinus deformity associated genetic disorder

The aim of this study was to characterize a previously uncharacterized genetic disorder associated with equinus deformity in a large Chinese family at the genetic level. Blood samples were obtained and whole genome sequencing was performed. Differential gene variants were identified and potential impacts on protein structure were predicted. Based on the control sample, several diseases associated variants were identified and selected for further validation. One of the potential variants identified was a ANXA3 gene [chr4, c.C820T(p.R274*)] variant. Further bioinformatic analysis showed that the observed mutation could lead to a three-dimensional conformational change. Moreover, a MTHFR variant that is different from variants associated with clubfoot was also identified. Bioinformatic analysis showed that this mutation could alter the protein binding region. These findings imply that this uncharacterized genetic disorder is not clubfoot, despite sharing some similar symptoms. Furthermore, specific CNV profiles were identified in association with the diseased samples, thus further speaking to the complexity of this multigenerational disorder. This study examined a previously uncharacterized genetic disorder appearing similar to clubfoot and yet having distinct features. Following whole genome sequencing and comparative analysis, several differential gene variants were identified to enable a further distinction from clubfoot. It is hoped that these findings will provide further insight into this disorder and other similar disorders.     

Inference of genetic regulatory networks with recurrent neural network models using particle swarm optimization

Genetic regulatory network inference is critically important for revealing fundamental cellular processes, investigating gene functions, and understanding their relations. The availability of time series gene expression data makes it possible to investigate the gene activities of whole genomes, rather than those of only a pair of genes or among several genes. However, current computational methods do not sufficiently consider the temporal behavior of this type of data and lack the capability to capture the complex nonlinear system dynamics. We propose a recurrent neural network (RNN) and particle swarm optimization (PSO) approach to infer genetic regulatory networks from time series gene expression data. Under this framework, gene interaction is explained through a connection weight matrix. Based on the fact that the measured time points are limited and the assumption that the genetic networks are usually sparsely connected, we present a PSO-based search algorithm to unveil potential genetic network constructions that fit well with the time series data and explore possible gene interactions. Furthermore, PSO is used to train the RNN and determine the network parameters. Our approach has been applied to both synthetic and real data sets. The results demonstrate that the RNN/PSO can provide meaningful insights in understanding the nonlinear dynamics of the gene expression time series and revealing potential regulatory interactions between genes.     

The adenovirus E1A-associated kinase consists of cyclin E-p33cdk2 and cyclin A-p33cdk2.

The adenovirus E1A oncoproteins form stable complexes with several cellular proteins. Association of E1A with these proteins has been shown to be important for the oncogenic potential of E1A. Several of these proteins have been identified and include the product of the retinoblastoma gene and a key cell cycle regulatory protein, cyclin A. E1A also associates with a potent histone H1 kinase. The two major components of this activity are the cyclin E-p33cdk2 and cyclin A-p33cdk2 complexes. Both the cyclin E-p33cdk2 and cyclin A-p33cdk2 complexes have been implicated in regulatory events controlling entry into or passage through DNA synthesis. Although the architecture of such interactions remains unclear, it is likely that by targeting such complexes, adenovirus is affecting some aspect of cell cycle control.