The evolution of mobile DNAs: when will transposons create phylogenies that look as if there is a master gene?

Some families of mammalian interspersed repetitive DNA, such as the Alu SINE sequence, appear to have evolved by the serial replacement of one active sequence with another, consistent with there being a single source of transposition: the "master gene." Alternative models, in which multiple source sequences are simultaneously active, have been called "transposon models." Transposon models differ in the proportion of elements that are active and in whether inactivation occurs at the moment of transposition or later. Here we examine the predictions of various types of transposon model regarding the patterns of sequence variation expected at an equilibrium between transposition, inactivation, and deletion. Under the master gene model, all bifurcations in the true tree of elements occur in a single lineage. We show that this property will also hold approximately for transposon models in which most elements are inactive and where at least some of the inactivation events occur after transposition. Such tree shapes are therefore not conclusive evidence for a single source of transposition.

A test of the master gene hypothesis for interspersed repetitive DNA sequences

Many families of interspersed repetitive DNA elements, including human Alu and LINE (Long Interspersed Element) elements, have been proposed to have accumulated through repeated copying from a single source locus: the "master gene." The extent to which a master gene model is applicable has implications for the origin, evolution, and function of such sequences. One repetitive element family for which a convincing case for a master gene has been made is the rodent ID (identifier) elements. Here we devise a new test of the master gene model and use it to show that mouse ID element sequences are not compatible with a strict master gene model. We suggest that a single master gene is rarely, if ever, likely to be responsible for the accumulation of any repeat family.

The role of satellite image-processing for national-scale estimates of gene flow from genetically modified crops: rapeseed in the UK as a model.

1. There is concern over the possibility of unwanted environmental change following transgene movement from genetically modified (GM) rapeseed Brassica napus to its wild and weedy relatives. 2. The aim of this research was to develop a remote sensing-assisted methodology to help quantify gene flow from crops to their wild relatives over wide areas. Emphasis was placed on locating sites of sympatry, where the frequency of gene flow is likely to be highest, and on measuring the size of rapeseed fields to allow spatially explicit modelling of wind-mediated pollen-dispersal patterns. 3. Remote sensing was used as a tool to locate rapeseed fields, and a variety of image-processing techniques was adopted to facilitate the compilation of a spatially explicit profile of sympatry between the crop and Brassica rapa. 4. Classified satellite images containing rapeseed fields were first used to infer the spatial relationship between donor rapeseed fields and recipient riverside B. rapa populations. Such images also have utility for improving the efficiency of ground surveys by identifying probable sites of sympatry. The same data were then also used for the calculation of mean field size. 5. This paper forms a companion paper to Wilkinson et al. (2003), in which these elements were combined to produce a spatially explicit profile of hybrid formation over the UK. The current paper demonstrates the value of remote sensing and image processing for large-scale studies of gene flow, and describes a generic method that could be applied to a variety of crops in many countries. 6. Synthesis and applications. The decision to approve or prevent the release of a GM cultivar is made at a national rather than regional level. It is highly desirable that data relating to the decision-making process are collected at the same scale, rather than relying on extrapolation from smaller experiments designed at the plot, field or even regional scale. It would be extremely difficult and labour intensive to attempt to carry out such large-scale investigations without the use of remote-sensing technology. This study used rapeseed in the UK as a model to demonstrate the value of remote sensing in assembling empirical information at a national level.

The role of satellite image-processing for national-scale estimates of gene flow from genetically modified crops: rapeseed in the UK as a model

1.There is concern over the possibility of unwanted environmental change following transgene movement from genetically modified (GM) rapeseed Brassica napus to its wild and weedy relatives. 2. The aim of this research was to develop a remote sensing-assisted methodology to help quantify gene flow from crops to their wild relatives over wide areas. Emphasis was placed on locating sites of sympatry, where the frequency of gene flow is likely to be highest, and on measuring the size of rapeseed fields to allow spatially explicit modelling of wind-mediated pollen-dispersal patterns. 3. Remote sensing was used as a tool to locate rapeseed fields, and a variety of image-processing techniques was adopted to facilitate the compilation of a spatially explicit profile of sympatry between the crop and Brassica rapa. 4. Classified satellite images containing rapeseed fields were first used to infer the spatial relationship between donor rapeseed fields and recipient riverside B. rapa populations. Such images also have utility for improving the efficiency of ground surveys by identifying probable sites of sympatry. The same data were then also used for the calculation of mean field size. 5. This paper forms a companion paper to Wilkinson et al. (2003), in which these elements were combined to produce a spatially explicit profile of hybrid formation over the UK. The current paper demonstrates the value of remote sensing and image processing for large-scale studies of gene flow, and describes a generic method that could be applied to a variety of crops in many countries. 6.Synthesis and applications. The decision to approve or prevent the release of a GM cultivar is made at a national rather than regional level. It is highly desirable that data relating to the decision-making process are collected at the same scale, rather than relying on extrapolation from smaller experiments designed at the plot, field or even regional scale. It would be extremely difficult and labour intensive to attempt to carry out such large-scale investigations without the use of remote-sensing technology. This study used rapeseed in the UK as a model to demonstrate the value of remote sensing in assembling empirical information at a national level.

A phylogenetic mixture model for detecting pattern-heterogeneity in gene sequence or character-state data

We describe a general likelihood-based 'mixture model' for inferring phylogenetic trees from gene-sequence or other character-state data. The model accommodates cases in which different sites in the alignment evolve in qualitatively distinct ways, but does not require prior knowledge of these patterns or partitioning of the data. We call this qualitative variability in the pattern of evolution across sites "pattern-heterogeneity" to distinguish it from both a homogenous process of evolution and from one characterized principally by differences in rates of evolution. We present studies to show that the model correctly retrieves the signals of pattern-heterogeneity from simulated gene-sequence data, and we apply the method to protein-coding genes and to a ribosomal 12S data set. The mixture model outperforms conventional partitioning in both these data sets. We implement the mixture model such that it can simultaneously detect rate- and pattern-heterogeneity. The model simplifies to a homogeneous model or a rate- variability model as special cases, and therefore always performs at least as well as these two approaches, and often considerably improves upon them. We make the model available within a Bayesian Markov-chain Monte Carlo framework for phylogenetic inference, as an easy-to-use computer program.

Pathogenic LRRK2 mutations do not alter gene expression in cell model systems or human brain tissue

Point mutations in LRRK2 cause autosomal dominant Parkinson's disease. Despite extensive efforts to determine the mechanism of cell death in patients with LRRK2 mutations, the aetiology of LRRK2 PD is not well understood. To examine possible alterations in gene expression linked to the presence of LRRK2 mutations, we carried out a case versus control analysis of global gene expression in three systems: fibroblasts isolated from LRRK2 mutation carriers and healthy, non-mutation carrying controls; brain tissue from G2019S mutation carriers and controls; and HEK293 inducible LRRK2 wild type and mutant cell lines. No significant alteration in gene expression was found in these systems following correction for multiple testing. These data suggest that any alterations in basal gene expression in fibroblasts or cell lines containing mutations in LRRK2 are likely to be quantitatively small. This work suggests that LRRK2 is unlikely to play a direct role in modulation of gene expression, although it remains possible that this protein can influence mRNA expression under pathogenic cicumstances.

Rescue of gene expression by modified REST decoy oligonucleotides in a cellular model of Huntington's disease

Transcriptional dysfunction is a prominent hallmark of Huntington's disease (HD). Several transcription factors have been implicated in the aetiology of HD progression and one of the most prominent is repressor element 1 (RE1) silencing transcription factor (REST). REST is a global repressor of neuronal gene expression and in the presence of mutant Huntingtin increased nuclear REST levels lead to elevated RE1 occupancy and a concomitant increase in target gene repression, including brain-derived neurotrophic factor. It is of great interest to devise strategies to reverse transcriptional dysregulation caused by increased nuclear REST and determine the consequences in HD. Thus far, such strategies have involved RNAi or mutant REST constructs. Decoys are double-stranded oligodeoxynucleotides corresponding to the DNA-binding element of a transcription factor and act to sequester it, thereby abrogating its transcriptional activity. Here, we report the use of a novel decoy strategy to rescue REST target gene expression in a cellular model of HD. We show that delivery of the decoy in cells expressing mutant Huntingtin leads to its specific interaction with REST, a reduction in REST occupancy of RE1s and rescue of target gene expression, including Bdnf. These data point to an alternative strategy for rebalancing the transcriptional dysregulation in HD.

Landscape gene flow, coexistence and threshold effect: The case of genetically modified herbicide tolerant oilseed rape (Brassica napus)

Globally there have been a number of concerns about the development of genetically modified crops many of which relate to the implications of gene flow at various levels. In Europe these concerns have led the European Union (EU) to promote the concept of 'coexistence' to allow the freedom to plant conventional and genetically modified (GM) varieties but to minimise the presence of transgenic material within conventional crops. Should a premium for non-GM varieties emerge on the market, the presence of transgenes would generate a 'negative externality' to conventional growers. The establishment of maximum tolerance level for the adventitious presence of GM material in conventional crops produces a threshold effect in the external costs. The existing literature suggests that apart from the biological characteristics of the plant under consideration (e.g. self-pollination rates, entomophilous species, anemophilous species, etc.), gene flow at the landscape level is affected by the relative size of the source and sink populations and the spatial arrangement of the fields in the landscape. In this paper, we take genetically modified herbicide tolerant oilseed rape (GM HT OSR) as a model crop. Starting from an individual pollen dispersal function, we develop a spatially explicit numerical model in order to assess the effect of the size of the source/sink populations and the degree of spatial aggregation on the extent of gene flow into conventional OSR varieties under two alternative settings. We find that when the transgene presence in conventional produce is detected at the field level, the external cost will increase with the size of the source area and with the level of spatial disaggregation. on the other hand when the transgene presence is averaged among all conventional fields in the landscape (e.g. because of grain mixing before detection), the external cost will only depend on the relative size of the source area. The model could readily be incorporated into an economic evaluation of policies to regulate adoption of GM HT OSR. (c) 2007 Elsevier B.V. All rights reserved.

A model of seed dormancy in wild oats (Avena fatua) for investigating genotype x environment interactions

Dormancy is an adaptive trait in seed populations that helps ensure that seed germination is distributed over time and occurs in environmental conditions suitable for seedling growth. Several genes.. associated with seed dormancy in various plant species, have been integrated into a hypothetical dormancy model for Avena fatua L. (wild oats). Generally, the synthesis of, and sensitivity to, abscisic acid (ABA) during imbibition determines whether genes similar to those during maturation are expressed leading to a maintenance of dormancy during extended imbibition. Alternatively, there may be a shift towards expression of genes associated with gibberellins leading to germination. Environmental factors during maturation, after-ripening and imbibition are likely to interact with the genotype to affect gene expression and hence whether or not a seed germinates. In spite of the difficulties of working on a hexaploid species, A. fatua was selected for study because of its worldwide importance as a weed. Dormant and non-dormant genotypes of this species were also available. Gene expression studies are being carried out on three A.fatua genotypes produced tinder different environmental conditions to investigate the role of specific genes in dormancy and genotype X environment interactions in relation to dormancy.

Juvenile-mature wood transition in pine: correlation between wood properties and candidate gene expression profiles

There is a strong desire to exploit transcriptomics data from model species for the genetic improvement of non-model crops. Here, we use gene expression profiles from the commercial model Pinus taeda to identify candidate genes implicated in juvenile-mature wood transition in the non-model relative, P. sylvestris. Re-analysis of 'public domain' SAGE data from xylem tissues of P. taeda revealed 283 mature-abundant and 396 juvenile-abundant tags (P < 0.01), of which 70 and 137, respectively matched to genes with known function. Based on sequence similarity, we then isolated 16 putative homologues of genes that in P. taeda exhibited widest divergence in expression between juvenile and mature samples. Candidate expression levels in P. sylvestris were almost invariably differential between juvenile and mature woody tissue samples among two cohorts of five trees collected from the same seed source and selected for genetic uniformity by genetic distance analysis. However, the direction of differential expression was not always consistent with that described in the original P. taeda SAGE data. Correlation was observed between gene expression and juvenile-mature wood anatomical characteristics by OPLS analysis. Four candidates (alpha-tubulin, porin MIP1, lipid transfer protein and aquaporin like protein) apparently had greatest influence on the wood traits measured. Speculative function of these genes in relation to juvenile-mature wood transition is briefly explored. Thus, we demonstrate the feasibility of exploiting SAGE data from a model species to identify consistently differentially expressed candidates in a related non-model species.

Use of global gene expression patterns in mechanistic studies of oestrogen action in MCF7 human breast cancer cells

Over the years, the MCF7 human breast cancer cell line has provided a model system for the study of cellular and molecular mechanisms in oestrogen regulation of cell proliferation and in progression to oestrogen and antioestrogen independent growth. Global gene expression profiling has shown that oestrogen action in MCF7 cells involves the coordinated regulation of hundreds of genes across a wide range of functional groupings and that more genes are down regulated than upregulated. Adaptation to long-term oestrogen deprivation, which results in loss of oestrogen-responsive growth, involves alterations to gene patterns not only at early time points (0-4 weeks) but continuing through to later times (20-55 weeks), and even involves alterations to patterns of oestrogen-regulated gene expression. Only 48% of the genes which were regulated >= 2-fold by oestradiol in oestrogen-responsive cells retained this responsiveness after long-term oestrogen deprivation but other genes developed de novo oestrogen regulation. Long-term exposure to fulvestrant, which resulted in loss of growth inhibition by the antioestrogen, resulted in some very large fold changes in gene expression up to 10,000-fold. Comparison of gene profiles produced by environmental chemicals with oestrogenic properties showed that each ligand gave its own unique expression profile which suggests that environmental oestrogens entering the human breast may give rise to a more complex web of interference in cell function than simply mimicking oestrogen action at inappropriate times. (C) 2009 Elsevier Ltd. All rights reserved.

Using phylogeny to investigate the origins of the Cape flora: the importance of taxonomic, gene and genome sampling strategies

Phylogenetic methods hold great promise for the reconstruction of the transition from precursor to modern flora and the identification of underlying factors which drive the process. The phylogenetic methods presently used to address the question of the origin of the Cape flora of South Africa are considered here. The sampling requirements of each of these methods, which include dating of diversifications using calibrated molecular trees, sister pair comparisons, lineage through time plots and biogeographical optimizations are reviewed. Sampling of genes, genomes and species are considered. Although increased higher-level studies and increased sampling are required for robust interpretation, it is clear that much progress is already made. It is argued that despite the remarkable richness of the flora, the Cape flora is a valuable model system to demonstrate the utility of phylogenetic methods in determining the history of a modern flora.

Restricted expression of NADPH oxidase/peroxidase gene (Duox) in zone VII of the ascidian endostyle

The ascidian Ciona intestinalis, a marine invertebrate chordate, is an emerging model system for developmental and evolutionary studies. The endostyle, one of the characteristic organs of ascidians, is a pharyngeal structure with iodine-concentrating and peroxidase activities and is therefore considered to be homologous to the follicular thyroid of higher vertebrates. We have previously reported that a limited part of the endostyle (zone VII) is marked by the expression of orthologs of the thyroid peroxidase (TPO) and thyroid transcription factor-2 (TTF-2/FoxE) genes. In this study, we have identified the Ciona homolog of NADPH oxidase/peroxidase (Duox), which provides hydrogen peroxide (H2O2) for iodine metabolism by TPO in the vertebrate thyroid. Expression patterns assessed by in situ hybridization have revealed that Ciona Duox (Ci-Duox) is predominantly expressed in the dorsal part of zone VII of the endostyle. Furthermore, two-color fluorescent in situ hybridization with Ci-Duox and Ciona TPO (CiTPO) has revealed that the ventral boundary of the Ci-Duox domain of expression is more dorsal than that of CiTPO. We have also characterized several genes, such as Ci-Fgf8/17/18, 5HT7, and Ci-NK4, which are predominantly expressed in the ventral part of zone VII, in a region complementary to the Ci-Duox expression domain. These observations suggest that, at the molecular level, zone VII has a complex organization that might have some impact on the specification of cell types and functions in this thyroid-equivalent element of the ascidian endostyle.

Predicting functional gene links from phylogenetic-statistical analyses of whole genomes

An important element of the developing field of proteomics is to understand protein-protein interactions and other functional links amongst genes. Across-species correlation methods for detecting functional links work on the premise that functionally linked proteins will tend to show a common pattern of presence and absence across a range of genomes. We describe a maximum likelihood statistical model for predicting functional gene linkages. The method detects independent instances of the correlated gain or loss of pairs of proteins on phylogenetic trees, reducing the high rates of false positives observed in conventional across-species methods that do not explicitly incorporate a phylogeny. We show, in a dataset of 10,551 protein pairs, that the phylogenetic method improves by up to 35% on across-species analyses at identifying known functionally linked proteins. The method shows that protein pairs with at least two to three correlated events of gain or loss are almost certainly functionally linked. Contingent evolution, in which one gene's presence or absence depends upon the presence of another, can also be detected phylogenetically, and may identify genes whose functional significance depends upon its interaction with other genes. Incorporating phylogenetic information improves the prediction of functional linkages. The improvement derives from having a lower rate of false positives and from detecting trends that across-species analyses miss. Phylogenetic methods can easily be incorporated into the screening of large-scale bioinformatics datasets to identify sets of protein links and to characterise gene networks.