Pyrosequencing™

Nucleotide sequencing is an established method for gaining information relating to partial gene, whole gene, or whole genome sequence. Here we describe some of the background leading to the advent of modern nucleotide sequencing and how it has led to the development of Pyrosequencing™, a relatively new method for real-time nucleotide sequencing. In particular, we describe how this method can be used for typing bacterial pathogens.     

Confounding factors in HGT detection: statistical error, coalescent effects, and multiple solutions.

Prokaryotic organisms share genetic material across species boundaries by means of a process known as horizontal gene transfer (HGT). This process has great significance for understanding prokaryotic genome diversification and unraveling their complexities. Phylogeny-based detection of HGT is one of the most commonly used methods for this task, and is based on the fundamental fact that HGT may cause gene trees to disagree with one another, as well as with the species phylogeny. Using these methods, we can compare gene and species trees, and infer a set of HGT events to reconcile the differences among these trees. In this paper, we address three factors that confound the detection of the true HGT events, including the donors and recipients of horizontally transferred genes. First, we study experimentally the effects of error in the estimated gene trees (statistical error) on the accuracy of inferred HGT events. Our results indicate that statistical error leads to overestimation of the number of HGT events, and that HGT detection methods should be designed with unresolved gene trees in mind. Second, we demonstrate, both theoretically and empirically, that based on topological comparison alone, the number of HGT scenarios that reconcile a pair of species/gene trees may be exponential. This number may be reduced when branch lengths in both trees are estimated correctly. This set of results implies that in the absence of additional biological information, and/or a biological model of how HGT occurs, multiple HGT scenarios must be sought, and efficient strategies for how to enumerate such solutions must be developed. Third, we address the issue of lineage sorting, how it confounds HGT detection, and how to incorporate it with HGT into a single stochastic framework that distinguishes between the two events by extending population genetics theories. This result is very important, particularly when analyzing closely related organisms, where coalescent effects may not be ignored when reconciling gene trees. In addition to these three confounding factors, we consider the problem of enumerating all valid coalescent scenarios that constitute plausible species/gene tree reconciliations, and develop a polynomial-time dynamic programming algorithm for solving it. This result bears great significance on reducing the search space for heuristics that seek reconciliation scenarios. Finally, we show, empirically, that the locality of incongruence between a pair of trees has an impact on the numbers of HGT and coalescent reconciliation scenarios.     

The multiple facets of homology and their use in comparative genomics to study the evolution of genes, genomes, and species

The incredible development of comparative genomics during the last decade has required a correct use of the concept of homology that was previously utilized only by evolutionary biologists. Unhappily, this concept has been often misunderstood and thus misused when exploited outside its evolutionary context. This review brings back to the correct definition of homology and explains how this definition has been progressively refined in order to adapt it to the various new kinds of analysis of gene properties and of their products that appear with the progress of comparative genomics. Then, we illustrate the power and the proficiency of such a concept when using the available genomics data in order to study the evolution of individual genes, of entire genomes and of species, respectively. After explaining how we detect homologues by an exhaustive comparison of a hundred of complete proteomes, we describe three main lines of research we have developed in the recent years. The first one exploits synteny and gene context data to better understand the mechanisms of genome evolution in prokaryotes. The second one is based on phylogenomics approaches to reconstruct the tree of life. The last one is devoted to reminding that protein homology is often limited to structural segments (SOH=segment of homology or module). Detecting and numbering modules allows tracing back protein history by identifying the events of gene duplication and gene fusion. We insist that one of the main present difficulties in such studies is a lack of a reliable method to identify genuine orthologues. Finally, we show how these homology studies are helpful to annotate genes and genomes and to study the complexity of the relationships between sequence and function of a gene.     

Functional analyses of genetic pathways controlling petal specification in poppy

MADS-box genes are crucial regulators of floral development, yet how their functions have evolved to control different aspects of floral patterning is unclear. To understand the extent to which MADS-box gene functions are conserved or have diversified in different angiosperm lineages, we have exploited the capability for functional analyses in a new model system, Papaver somniferum (opium poppy). P. somniferum is a member of the order Ranunculales, and so represents a clade that is evolutionarily distant from those containing traditional model systems such as Arabidopsis, Petunia, maize or rice. We have identified and characterized the roles of several candidate MADS-box genes in petal specification in poppy. In Arabidopsis, the APETALA3 (AP3) MADS-box gene is required for both petal and stamen identity specification. By contrast, we show that the AP3 lineage has undergone gene duplication and subfunctionalization in poppy, with one gene copy required for petal development and the other responsible for stamen development. These differences in gene function are due to differences both in expression patterns and co-factor interactions. Furthermore, the genetic hierarchy controlling petal development in poppy has diverged as compared with that of Arabidopsis. As these are the first functional analyses of AP3 genes in this evolutionarily divergent clade, our results provide new information on the similarities and differences in petal developmental programs across angiosperms. Based on these observations, we discuss a model for how the petal developmental program has evolved.     

Perturbations to uncover gene networks

After the major achievements of the DNA sequencing projects, an equally important challenge now is to uncover the functional relationships among genes (i.e. gene networks). It has become increasingly clear that computational algorithms are crucial for extracting meaningful information from the massive amount of data generated by high-throughput genome-wide technologies. Here, we summarise how systems identification algorithms, originating from physics and control theory, have been adapted for use in biology. We also explain how experimental perturbations combined with genome-wide measurements are being used to uncover gene networks. Perturbation techniques could pave the way for identifying gene networks in more complex settings such as multifactorial diseases and for improving the efficacy of drug evaluation.     

Gene network analysis of Arabidopsis thaliana flower development through dynamic gene perturbations

Understanding how flowers develop from undifferentiated stem cells has occupied developmental biologists for decades. Key to unraveling this process is a detailed knowledge of the global regulatory hierarchies that control developmental transitions, cell differentiation and organ growth. These hierarchies may be deduced from gene perturbation experiments, which determine the effects on gene expression after specific disruption of a regulatory gene. Here, we tested experimental strategies for gene perturbation experiments during Arabidopsis thaliana flower development. We used artificial miRNAs (amiRNAs) to disrupt the functions of key floral regulators, and expressed them under the control of various inducible promoter systems that are widely used in the plant research community. To be able to perform genome‐wide experiments with stage‐specific resolution using the various inducible promoter systems for gene perturbation experiments, we also generated a series of floral induction systems that allow collection of hundreds of synchronized floral buds from a single plant. Based on our results, we propose strategies for performing dynamic gene perturbation experiments in flowers, and outline how they may be combined with versions of the floral induction system to dissect the gene regulatory network underlying flower development.     

RNAi knock-down mice: an emerging technology for post-genomic functional genetics

RNA interference (RNAi) has been extensively used for sequence-specific silencing of gene function in mammalian cells. The latest major breakthrough in the application of RNAi technology came from experiments demonstrating RNAi-mediated gene repression in mice and rats. After more than two decades of functional mouse research aimed at developing and continuously improving transgenic and knock-out technology, the advent of RNAi knock-down mice represents a valuable new alternative for studying gene function in vivo. In this review we provide some basic insight as to how RNAi can induce gene silencing to then focus on recent findings concerning the applicability of RNAi for regulating gene function in the mouse. Reviewed topics will include delivery methods for RNAi-mediating molecules, a comparison between traditional knock-out and innovative transgenic RNAi technology and the generation of graded RNAi knock-down phenotypes. Apart from the exciting possibilities RNAi provides for studying gene function in mice, we discuss several caveats and limitations to be considered. Finally, we present prospective strategies as to how RNAi technology might be applied for generating conditional and tissue-restricted knock-down mice.     

Genetic dissection of gene regulation in multiple mouse tissues

The analysis of the influence of genetic variation on regulation of gene expression at a near-genome-wide level has become the focus of much recent interest. It is widely appreciated that many genes are expressed in a tissue-specific manner and that others are more ubiquitously expressed but relatively little is known about how genetic variation might influence these tissue patterns of gene expression. In this review we discuss what is known about the tissue specificity of the influence of genetic variation and review the challenges that we face in combining hugely parallel, microarray-based gene analysis with equally expensive genetic analysis. We conclude that the available data suggest that genetic variation is essentially tissue specific in its effects upon gene expression and this has important implications for experimental analysis.     

Understanding the molecular machinery of genetics through 3D structures

Detailed knowledge of the three-dimensional structures of biological molecules has had an enormous impact on all areas of biological science, including genetics, as structure can reveal the fine details of how molecules perform their biological functions. Here we consider how changes in protein sequence affect the corresponding 3D structure, and describe how structural information about proteins, DNA and chromatin has shed light on gene regulatory mechanisms and the storage and transmission of epigenetic information. Finally, we describe how structure determination is benefiting from the high-throughput technologies of the worldwide structural genomics projects.     

Robust method for detecting differential gene expression in twin studies

MOTIVATION: A steadily increasing number of experiments with microarrays stimulate the further development of the statistical methods of the analysis of gene expression data. One of the central problems in this area is detecting differential gene expression under two or more conditions. Unfortunately, up to now it has not been studied how the correlations between related individuals, such as twins influence the estimates of differential gene expression. RESULTS: In this paper, we discuss this problem and propose a new method that is robust with respect to correlations of gene expression data for twins.     

Orthology relations, symbolic ultrametrics, and cographs

Orthology detection is an important problem in comparative and evolutionary genomics and, consequently, a variety of orthology detection methods have been devised in recent years. Although many of these methods are dependent on generating gene and/or species trees, it has been shown that orthology can be estimated at acceptable levels of accuracy without having to infer gene trees and/or reconciling gene trees with species trees. Thus, it is of interest to understand how much information about the gene tree, the species tree, and their reconciliation is already contained in the orthology relation on the underlying set of genes. Here we shall show that a result by Böcker and Dress concerning symbolic ultrametrics, and subsequent algorithmic results by Semple and Steel for processing these structures can throw a considerable amount of light on this problem. More specifically, building upon these authors’ results, we present some new characterizations for symbolic ultrametrics and new algorithms for recovering the associated trees, with an emphasis on how these algorithms could be potentially extended to deal with arbitrary orthology relations. In so doing we shall also show that, somewhat surprisingly, symbolic ultrametrics are very closely related to cographs, graphs that do not contain an induced path on any subset of four vertices. We conclude with a discussion on how our results might be applied in practice to orthology detection.     

Repatterning in amphibian limb regeneration: A model for study of genetic and epigenetic control of organ regeneration

Limb regeneration is an excellent model for understanding organ reconstruction along PD, AP and DV axes. Re-expression of genes involved in axial pattern formation is essential for complete limb regeneration. The cellular positional information in the limb blastema has been thought to be a key factor for appropriate gene re-expression. Recently, it has been suggested that epigenetic mechanisms have an essential role in development and regeneration processes. In this review, we discuss how epigenetic mechanisms may be involved in the maintenance of positional information and the regulation of gene re-expression during limb regeneration.     

Tissue-Specific Effects of Genetic and Epigenetic Variation on Gene Regulation and Splicing

Understanding how genetic variation affects distinct cellular phenotypes, such as gene expression levels, alternative splicing and DNA methylation levels, is essential for better understanding of complex diseases and traits. Furthermore, how inter-individual variation of DNA methylation is associated to gene expression is just starting to be studied. In this study, we use the GenCord cohort of 204 newborn Europeans’ lymphoblastoid cell lines, T-cells and fibroblasts derived from umbilical cords. The samples were previously genotyped for 2.5 million SNPs, mRNA-sequenced, and assayed for methylation levels in 482,421 CpG sites. We observe that methylation sites associated to expression levels are enriched in enhancers, gene bodies and CpG island shores. We show that while the correlation between DNA methylation and gene expression can be positive or negative, it is very consistent across cell-types. However, this epigenetic association to gene expression appears more tissue-specific than the genetic effects on gene expression or DNA methylation (observed in both sharing estimations based on P-values and effect size correlations between cell-types). This predominance of genetic effects can also be reflected by the observation that allele specific expression differences between individuals dominate over tissue-specific effects. Additionally, we discover genetic effects on alternative splicing and interestingly, a large amount of DNA methylation correlating to alternative splicing, both in a tissue-specific manner. The locations of the SNPs and methylation sites involved in these associations highlight the participation of promoter proximal and distant regulatory regions on alternative splicing. Overall, our results provide high-resolution analyses showing how genome sequence variation has a broad effect on cellular phenotypes across cell-types, whereas epigenetic factors provide a secondary layer of variation that is more tissue-specific. Furthermore, the details of how this tissue-specificity may vary across inter-relations of molecular traits, and where these are occurring, can yield further insights into gene regulation and cellular biology as a whole.     

Implications of diffusion and time-varying morphogen gradients for the dynamic positioning and precision of bistable gene expression boundaries

The earliest models for how morphogen gradients guide embryonic patterning failed to account for experimental observations of temporal refinement in gene expression domains. Following theoretical and experimental work in this area, dynamic positional information has emerged as a conceptual framework to discuss how cells process spatiotemporal inputs into downstream patterns. Here, we show that diffusion determines the mathematical means by which bistable gene expression boundaries shift over time, and therefore how cells interpret positional information conferred from morphogen concentration. First, we introduce a metric for assessing reproducibility in boundary placement or precision in systems where gene products do not diffuse, but where morphogen concentrations are permitted to change in time. We show that the dynamics of the gradient affect the sensitivity of the final pattern to variation in initial conditions, with slower gradients reducing the sensitivity. Second, we allow gene products to diffuse and consider gene expression boundaries as propagating wavefronts with velocity modulated by local morphogen concentration. We harness this perspective to approximate a PDE model as an ODE that captures the position of the boundary in time, and demonstrate the approach with a preexisting model for Hunchback patterning in fruit fly embryos. We then propose a design that employs antiparallel morphogen gradients to achieve accurate boundary placement that is robust to scaling. Throughout our work we draw attention to tradeoffs among initial conditions, boundary positioning, and the relative timescales of network and gradient evolution. We conclude by suggesting that mathematical theory should serve to clarify not just our quantitative, but also our intuitive understanding of patterning processes.