38 results found
Burga A, Lehner B, 2013, Predicting phenotypic variation from genotypes, phenotypes and a combination of the two., Curr Opin Biotechnol, Vol: 24, Pages: 803-809
A central challenge for medicine is to predict disease risk and treatment outcomes for individuals. But what kind of information should be used to make useful predictions in biology? One important cause of phenotypic variation is of course genetics. However genetic predictions have both practical and fundamental limitations: most genetic influences on a trait are usually unknown, and phenotypic variation is not just due to genetics. A pragmatic alternative is to use intermediate phenotypes such as gene expression and other molecular measurements to make predictions about later trait variation such as disease risk. Intermediate phenotypes are useful because they capture both genetic and non-genetic influences on a system, and can reflect both the current state of a system and its history. Here we discuss examples of both genetic and non-genetic approaches to predicting phenotypic variation. Moreover, we argue that it will be by combining these two sources of information-genetics and intermediate molecular phenotypes-that it will be possible to make accurate predictions about variation in many phenotypic traits, even if we will not always mechanistically understand why this is the case. In particular, we encourage the human genetics community to focus more on combining genetics with intermediate phenotypes when attempting to predict clinically relevant traits such as disease risk.
Lehner B, 2013, Genotype to phenotype: lessons from model organisms for human genetics., Nat Rev Genet, Vol: 14, Pages: 168-178
To what extent can variation in phenotypic traits such as disease risk be accurately predicted in individuals? In this Review, I highlight recent studies in model organisms that are relevant both to the challenge of accurately predicting phenotypic variation from individual genome sequences ('whole-genome reverse genetics') and for understanding why, in many cases, this may be impossible. These studies argue that only by combining genetic knowledge with in vivo measurements of biological states will it be possible to make accurate genetic predictions for individual humans.
Park S, Lehner B, 2013, Epigenetic epistatic interactions constrain the evolution of gene expression., Mol Syst Biol, Vol: 9
Reduced activity of two genes in combination often has a more detrimental effect than expected. Such epistatic interactions not only occur when genes are mutated but also due to variation in gene expression, including among isogenic individuals in a controlled environment. We hypothesized that these 'epigenetic' epistatic interactions could place important constraints on the evolution of gene expression. Consistent with this, we show here that yeast genes with many epistatic interaction partners typically show low expression variation among isogenic individuals and low variation across different conditions. In addition, their expression tends to remain stable in response to the accumulation of mutations and only diverges slowly between strains and species. Yeast promoter architectures, the retention of gene duplicates, and the divergence of expression between humans and chimps are also consistent with selective pressure to reduce the likelihood of harmful epigenetic epistatic interactions. Based on these and previous analyses, we propose that the tight regulation of epistatic interaction network hubs makes an important contribution to the maintenance of a robust, 'canalized' phenotype. Moreover, that epigenetic epistatic interactions may contribute substantially to fitness defects when single genes are deleted.
Warnecke T, Supek F, Lehner B, 2012, Nucleoid-Associated Proteins Affect Mutation Dynamics in E. coli in a Growth Phase-Specific Manner, PLOS COMPUTATIONAL BIOLOGY, Vol: 8, ISSN: 1553-734X
Vavouri T, Lehner B, 2012, Human genes with CpG island promoters have a distinct transcription-associated chromatin organization., Genome Biol, Vol: 13
BACKGROUND: More than 50% of human genes initiate transcription from CpG dinucleotide-rich regions referred to as CpG islands. These genes show differences in their patterns of transcription initiation, and have been reported to have higher levels of some activation-associated chromatin modifications. RESULTS: Here we report that genes with CpG island promoters have a characteristic transcription-associated chromatin organization. This signature includes high levels of the transcription elongation-associated histone modifications H4K20me1, H2BK5me1 and H3K79me1/2/3 in the 5' end of the gene, depletion of the activation marks H2AK5ac, H3K14ac and H3K23ac immediately downstream of the transcription start site (TSS), and characteristic epigenetic asymmetries around the TSS. The chromosome organization factor CTCF may be bound upstream of RNA polymerase in most active CpG island promoters, and an unstable nucleosome at the TSS may be specifically marked by H4K20me3, the first example of such a modification. H3K36 monomethylation is only detected as enriched in the bodies of active genes that have CpG island promoters. Finally, as expression levels increase, peak modification levels of the histone methylations H3K9me1, H3K4me1, H3K4me2 and H3K27me1 shift further away from the TSS into the gene body. CONCLUSIONS: These results suggest that active genes with CpG island promoters have a distinct step-like series of modified nucleosomes after the TSS. The identity, positioning, shape and relative ordering of transcription-associated histone modifications differ between genes with and without CpG island promoters. This supports a model where chromatin organization reflects not only transcription activity but also the type of promoter in which transcription initiates.
Burga A, Lehner B, 2012, Beyond genotype to phenotype: why the phenotype of an individual cannot always be predicted from their genome sequence and the environment that they experience., FEBS J, Vol: 279, Pages: 3765-3775
One promise of personalized medicine is that it will be possible to make useful predictions about the phenotypes of individuals from their complete genome sequences (e.g. concerning their susceptibility to disease). However, to what extent is knowledge about an individual's genotype, together with information about the environment that they have experienced, sufficient to predict phenotypic variation? In the present review, we argue that, although the 'typical' phenotypic outcome of an individual's genome can be predicted, it is much more difficult to predict the actual outcome for a particular individual. We highlight three reasons for this. First, the outcome of mutations can be influenced by random (stochastic) processes. Second, genetic variation present in one generation can influence phenotypic traits in the next generation, even if individuals do not inherit this variation. Third, the environment experienced by one generation can influence phenotypic variation in the next generation. These contributions to phenotypic variation have long been appreciated by quantitative geneticists, although they have only recently been studied at the molecular level. Taken together, they mean that, in many cases, the genotypes of individuals and the environment that they experience may not be sufficient to determine their phenotypes. A more comprehensive genotype-to-phenotype model will be required to make accurate predictions about the biology of individuals.
Schuster-Böckler B, Lehner B, 2012, Chromatin organization is a major influence on regional mutation rates in human cancer cells., Nature, Vol: 488, Pages: 504-507
Cancer genome sequencing provides the first direct information on how mutation rates vary across the human genome in somatic cells. Testing diverse genetic and epigenetic features, here we show that mutation rates in cancer genomes are strikingly related to chromatin organization. Indeed, at the megabase scale, a single feature—levels of the heterochromatin-associated histone modification H3K9me3—can account for more than 40% of mutation-rate variation, and a combination of features can account for more than 55%. The strong association between mutation rates and chromatin organization is upheld in samples from different tissues and for different mutation types. This suggests that the arrangement of the genome into heterochromatin- and euchromatin-like domains is a dominant influence on regional mutation-rate variation in human somatic cells.
Casanueva MO, Burga A, Lehner B, 2012, Fitness trade-offs and environmentally induced mutation buffering in isogenic C. elegans., Science, Vol: 335, Pages: 82-85
Mutations often have consequences that vary across individuals. Here, we show that the stimulation of a stress response can reduce mutation penetrance in Caenorhabditis elegans. Moreover, this induced mutation buffering varies across isogenic individuals because of interindividual differences in stress signaling. This variation has important consequences in wild-type animals, producing some individuals with higher stress resistance but lower reproductive fitness and other individuals with lower stress resistance and higher reproductive fitness. This may be beneficial in an unpredictable environment, acting as a "bet-hedging" strategy to diversify risk. These results illustrate how transient environmental stimuli can induce protection against mutations, how environmental responses can underlie variable mutation buffering, and how a fitness trade-off may make variation in stress signaling advantageous.
Burga A, Casanueva MO, Lehner B, 2011, Predicting mutation outcome from early stochastic variation in genetic interaction partners., Nature, Vol: 480, Pages: 250-253
Many mutations, including those that cause disease, only have a detrimental effect in a subset of individuals. The reasons for this are usually unknown, but may include additional genetic variation and environmental risk factors. However, phenotypic discordance remains even in the absence of genetic variation, for example between monozygotic twins, and incomplete penetrance of mutations is frequent in isogenic model organisms in homogeneous environments. Here we propose a model for incomplete penetrance based on genetic interaction networks. Using Caenorhabditis elegans as a model system, we identify two compensation mechanisms that vary among individuals and influence mutation outcome. First, feedback induction of an ancestral gene duplicate differs across individuals, with high expression masking the effects of a mutation. This supports the hypothesis that redundancy is maintained in genomes to buffer stochastic developmental failure. Second, during normal embryonic development we find that there is substantial variation in the induction of molecular chaperones such as Hsp90 (DAF-21). Chaperones act as promiscuous buffers of genetic variation, and embryos with stronger induction of Hsp90 are less likely to be affected by an inherited mutation. Simultaneously quantifying the variation in these two independent responses allows the phenotypic outcome of a mutation to be more accurately predicted in individuals. Our model and methodology provide a framework for dissecting the causes of incomplete penetrance. Further, the results establish that inter-individual variation in both specific and more general buffering systems combine to determine the outcome inherited mutations in each individual.
Jelier R, Semple JI, Garcia-Verdugo R, et al., 2011, Predicting phenotypic variation in yeast from individual genome sequences., Nat Genet, Vol: 43, Pages: 1270-1274
A central challenge in genetics is to predict phenotypic variation from individual genome sequences. Here we construct and evaluate phenotypic predictions for 19 strains of Saccharomyces cerevisiae. We use conservation-based methods to predict the impact of protein-coding variation within genes on protein function. We then rank strains using a prediction score that measures the total sum of function-altering changes in different sets of genes reported to influence over 100 phenotypes in genome-wide loss-of-function screens. We evaluate our predictions by comparing them with the observed growth rate and efficiency of 15 strains tested across 20 conditions in quantitative experiments. The median predictive performance, as measured by ROC AUC, was 0.76, and predictions were more accurate when the genes reported to influence a trait were highly connected in a functional gene network.
Lehner B, 2011, Molecular mechanisms of epistasis within and between genes., Trends Genet, Vol: 27, Pages: 323-331, ISSN: 0168-9525
'Disease-causing' mutations do not cause disease in all individuals. One possible important reason for this is that the outcome of a mutation can depend upon other genetic variants in a genome. These epistatic interactions between mutations occur both within and between molecules, and studies in model organisms show that they are extremely prevalent. However, epistatic interactions are still poorly understood at the molecular level, and consequently difficult to predict de novo. Here I provide an overview of our current understanding of the molecular mechanisms that can cause epistasis, and areas where more research is needed. A more complete understanding of epistasis will be vital for making accurate predictions about the phenotypes of individuals.
Francesconi M, Jelier R, Lehner B, 2011, Integrated genome-scale prediction of detrimental mutations in transcription networks., PLoS Genet, Vol: 7
A central challenge in genetics is to understand when and why mutations alter the phenotype of an organism. The consequences of gene inhibition have been systematically studied and can be predicted reasonably well across a genome. However, many sequence variants important for disease and evolution may alter gene regulation rather than gene function. The consequences of altering a regulatory interaction (or "edge") rather than a gene (or "node") in a network have not been as extensively studied. Here we use an integrative analysis and evolutionary conservation to identify features that predict when the loss of a regulatory interaction is detrimental in the extensively mapped transcription network of budding yeast. Properties such as the strength of an interaction, location and context in a promoter, regulator and target gene importance, and the potential for compensation (redundancy) associate to some extent with interaction importance. Combined, however, these features predict quite well whether the loss of a regulatory interaction is detrimental across many promoters and for many different transcription factors. Thus, despite the potential for regulatory diversity, common principles can be used to understand and predict when changes in regulation are most harmful to an organism.
Vavouri T, Lehner B, 2011, Chromatin organization in sperm may be the major functional consequence of base composition variation in the human genome., PLoS Genet, Vol: 7
Chromatin in sperm is different from that in other cells, with most of the genome packaged by protamines not nucleosomes. Nucleosomes are, however, retained at some genomic sites, where they have the potential to transmit paternal epigenetic information. It is not understood how this retention is specified. Here we show that base composition is the major determinant of nucleosome retention in human sperm, predicting retention very well in both genic and non-genic regions of the genome. The retention of nucleosomes at GC-rich sequences with high intrinsic nucleosome affinity accounts for the previously reported retention at transcription start sites and at genes that regulate development. It also means that nucleosomes are retained at the start sites of most housekeeping genes. We also report a striking link between the retention of nucleosomes in sperm and the establishment of DNA methylation-free regions in the early embryo. Taken together, this suggests that paternal nucleosome transmission may facilitate robust gene regulation in the early embryo. We propose that chromatin organization in the male germline, rather than in somatic cells, is the major functional consequence of fine-scale base composition variation in the human genome. The selective pressure driving base composition evolution in mammals could, therefore, be the need to transmit paternal epigenetic information to the zygote.
Lehner B, Kaneko K, 2011, Fluctuation and response in biology., Cell Mol Life Sci, Vol: 68, Pages: 1005-1010
In 1905, Albert Einstein proposed that the forces that cause the random Brownian motion of a particle also underlie the resistance to macroscopic motion when a force is applied. This insight, of a coupling between fluctuation (stochastic behavior) and responsiveness (non-stochastic behavior), founded an important branch of physics. Here we argue that his insight may also be relevant for understanding evolved biological systems, and we present a 'fluctuation-response relationship' for biology. The relationship is consistent with the idea that biological systems are similarly canalized to stochastic, environmental, and genetic perturbations. It is also supported by in silico evolution experiments, and by the observation that 'noisy' gene expression is often both more responsive and more 'evolvable'. More generally, we argue that in biology there is (and always has been) an important role for macroscopic theory that considers the general behavior of systems without concern for their intimate molecular details.
Lehner B, 2010, Conflict between noise and plasticity in yeast., PLoS Genet, Vol: 6
Gene expression responds to changes in conditions but also stochastically among individuals. In budding yeast, both expression responsiveness across conditions ("plasticity") and cell-to-cell variation ("noise") have been quantified for thousands of genes and found to correlate across genes. It has been argued therefore that noise and plasticity may be strongly coupled and mechanistically linked. This is consistent with some theoretical ideas, but a strong coupling between noise and plasticity also has the potential to introduce cost-benefit conflicts during evolution. For example, if high plasticity is beneficial (genes need to respond to the environment), but noise is detrimental (fluctuations are harmful), then strong coupling should be disfavored. Here, evidence is presented that cost-benefit conflicts do occur and that they constrain the evolution of gene expression and promoter usage. In contrast to recent assertions, coupling between noise and plasticity is not a general property, but one associated with particular mechanisms of transcription initiation. Further, promoter architectures associated with coupling are avoided when noise is most likely to be detrimental, and noise and plasticity are largely independent traits for core cellular components. In contrast, when genes are duplicated noise-plasticity coupling increases, consistent with reduced detrimental affects of expression variation. Noise-plasticity coupling is, therefore, an evolvable trait that may constrain the emergence of highly responsive gene expression and be selected against during evolution. Further, the global quantitative data in yeast suggest that one mechanism that relieves the constraints imposed by noise-plasticity coupling is gene duplication, providing an example of how duplication can facilitate escape from adaptive conflicts.
Semple JI, Garcia-Verdugo R, Lehner B, 2010, Rapid selection of transgenic C. elegans using antibiotic resistance., Nat Methods, Vol: 7, Pages: 725-727
Caenorhabditis elegans is an important model organism in biology, but until now no antibiotic selection markers have been successfully demonstrated for this species. We have developed a selection system using puromycin that allows the rapid and easy isolation of large populations of transgenic worms. This approach is sufficiently powerful to select single-copy transgenes, does not require any particular genetic background and also works in C. briggsae.
Lehner B, 2010, Genes confer similar robustness to environmental, stochastic, and genetic perturbations in yeast., PLoS One, Vol: 5
Gene inactivation often has little or no apparent consequence for the phenotype of an organism. This property-enetic (or mutational) robustness-is pervasive, and has important implications for disease and evolution, but is not well understood. Dating back to at least Waddington, it has been suggested that mutational robustness may be related to the requirement to withstand environmental or stochastic perturbations. Here I show that global quantitative data from yeast are largely consistent with this idea. Considering the effects of mutations in all nonessential genes shows that genes that confer robustness to environmental or stochastic change also buffer the effects of genetic change, and with similar efficacy. This means that selection during evolution for environmental or stochastic robustness (also referred to as canalization) may frequently have the side effect of increasing genetic robustness. A dynamic environment may therefore promote the evolution of phenotypic complexity. It also means that "hub" genes in genetic interaction (synthetic lethal) networks are generally genes that confer environmental resilience and phenotypic stability.
Vavouri T, Semple JI, Garcia-Verdugo R, et al., 2009, Intrinsic protein disorder and interaction promiscuity are widely associated with dosage sensitivity., Cell, Vol: 138, Pages: 198-208
Why are genes harmful when they are overexpressed? By testing possible causes of overexpression phenotypes in yeast, we identify intrinsic protein disorder as an important determinant of dosage sensitivity. Disordered regions are prone to make promiscuous molecular interactions when their concentration is increased, and we demonstrate that this is the likely cause of pathology when genes are overexpressed. We validate our findings in two animals, Drosophila melanogaster and Caenorhabditis elegans. In mice and humans the same properties are strongly associated with dosage-sensitive oncogenes, such that mass-action-driven molecular interactions may be a frequent cause of cancer. Dosage-sensitive genes are tightly regulated at the transcriptional, RNA, and protein levels, which may serve to prevent harmful increases in protein concentration under physiological conditions. Mass-action-driven interaction promiscuity is a single theoretical framework that can be used to understand, predict, and possibly treat the effects of increased gene expression in evolution and disease.
Vavouri T, Lehner B, 2009, Conserved noncoding elements and the evolution of animal body plans., Bioessays, Vol: 31, Pages: 727-735
The genomes of vertebrates, flies, and nematodes contain highly conserved noncoding elements (CNEs). CNEs cluster around genes that regulate development, and where tested, they can act as transcriptional enhancers. Within an animal group CNEs are the most conserved sequences but between groups they are normally diverged beyond recognition. Alternative CNEs are, however, associated with an overlapping set of genes that control development in all animals. Here, we discuss the evidence that CNEs are part of the core gene regulatory networks (GRNs) that specify alternative animal body plans. The major animal groups arose >550 million years ago. We propose that the cis-regulatory inputs identified by CNEs arose during the "re-wiring" of regulatory interactions that occurred during early animal evolution. Consequently, different animal groups, with different core GRNs, contain alternative sets of CNEs. Due to the subsequent stability of animal body plans, these core regulatory sequences have been evolving in parallel under strong purifying selection in different animal groups.
Bossi A, Lehner B, 2009, Tissue specificity and the human protein interaction network., Mol Syst Biol, Vol: 5
A protein interaction network describes a set of physical associations that can occur between proteins. However, within any particular cell or tissue only a subset of proteins is expressed and so only a subset of interactions can occur. Integrating interaction and expression data, we analyze here this interplay between protein expression and physical interactions in humans. Proteins only expressed in restricted cell types, like recently evolved proteins, make few physical interactions. Most tissue-specific proteins do, however, bind to universally expressed proteins, and so can function by recruiting or modifying core cellular processes. Conversely, most 'housekeeping' proteins that are expressed in all cells also make highly tissue-specific protein interactions. These results suggest a model for the evolution of tissue-specific biology, and show that most, and possibly all, 'housekeeping' proteins actually have important tissue-specific molecular interactions.
Vavouri T, Semple JI, Lehner B, 2008, Widespread conservation of genetic redundancy during a billion years of eukaryotic evolution., Trends Genet, Vol: 24, Pages: 485-488, ISSN: 0168-9525
Genetic redundancy means that two genes can perform the same function. Using a comprehensive phylogenetic analysis, we show here in both Saccharomyces cerevisiae and Caenorhabditis elegans that genetic redundancy is not just a transient consequence of gene duplication, but is often an evolutionary stable state. In multiple examples, genes have retained redundant functions since the divergence of the animal, plant and fungi kingdoms over a billion years ago. The stable conservation of genetic redundancy contrasts with the more rapid evolution of genetic interactions between unrelated genes and can be explained by theoretical models including a 'piggyback' mechanism in which overlapping redundant functions are co-selected with nonredundant ones.
Lehner B, Lee I, 2008, Network-guided genetic screening: building, testing and using gene networks to predict gene function., Brief Funct Genomic Proteomic, Vol: 7, Pages: 217-227
A challenge facing nearly all biologists is to identify the complete set of genes that are important for a process or disease. This applies to scientists investigating fundamental pathways in model organisms, but also to clinicians trying to understand human disease. There are many different types of experimental data that can be used to predict the genes that are important for a process, but these data are normally dispersed across numerous publications and databases, and are of varying and unknown quality. Integrated functional gene networks aim to gather functional information from all of these data into a single intuitive graph model that can be used to predict gene functions. In this approach, the ability of each data set to predict functional associations between genes is first measured using a standard benchmark, and then the scored predictions by each data set are combined. The resulting integrated probabilistic gene network can be used by all researchers to predict gene function, with much greater coverage and accuracy than any individual data set. In this review, we discuss how such integrated gene networks are constructed, how their predictive power for gene function can be tested, and how experimental biologists can use these networks to guide their research. We pay particular attention to such networks constructed for Caenorhabditis elegans, because in this complex multicellular model system functional predictions for genes can be rapidly tested in vivo using RNAi. The approach is, however, widely applicable to any system, and might soon be a common method used to dissect the genetics of human complex diseases.
Tischler J, Lehner B, Fraser AG, 2008, Evolutionary plasticity of genetic interaction networks., Nat Genet, Vol: 40, Pages: 390-391
Non-additive genetic interactions contribute to many genetic disorders, but they are extremely difficult to predict. Here we show that genetic interactions identified in yeast, unlike gene functions or protein interactions, are not highly conserved in animals. Genetic interactions are therefore unlikely to represent simple redundancy between genes or pathways, and genetic interactions from yeast do not directly predict genetic interactions in higher eukaryotes, including humans.
Semple JI, Vavouri T, Lehner B, 2008, A simple principle concerning the robustness of protein complex activity to changes in gene expression., BMC Syst Biol, Vol: 2
BACKGROUND: The functions of a eukaryotic cell are largely performed by multi-subunit protein complexes that act as molecular machines or information processing modules in cellular networks. An important problem in systems biology is to understand how, in general, these molecular machines respond to perturbations. RESULTS: In yeast, genes that inhibit growth when their expression is reduced are strongly enriched amongst the subunits of multi-subunit protein complexes. This applies to both the core and peripheral subunits of protein complexes, and the subunits of each complex normally have the same loss-of-function phenotypes. In contrast, genes that inhibit growth when their expression is increased are not enriched amongst the core or peripheral subunits of protein complexes, and the behaviour of one subunit of a complex is not predictive for the other subunits with respect to over-expression phenotypes. CONCLUSION: We propose the principle that the overall activity of a protein complex is in general robust to an increase, but not to a decrease in the expression of its subunits. This means that whereas phenotypes resulting from a decrease in gene expression can be predicted because they cluster on networks of protein complexes, over-expression phenotypes cannot be predicted in this way. We discuss the implications of these findings for understanding how cells are regulated, how they evolve, and how genetic perturbations connect to disease in humans.
Lehner B, 2008, Selection to minimise noise in living systems and its implications for the evolution of gene expression., Mol Syst Biol, Vol: 4
Gene expression, like many biological processes, is subject to noise. This noise has been measured on a global scale, but its general importance to the fitness of an organism is unclear. Here, I show that noise in gene expression in yeast has evolved to prevent harmful stochastic variation in the levels of genes that reduce fitness when their expression levels change. Therefore, there has probably been widespread selection to minimise noise in gene expression. Selection to minimise noise, because it results in gene expression that is stable to stochastic variation in cellular components, may also constrain the ability of gene expression to respond to non-stochastic variation. I present evidence that this has indeed been the case in yeast. I therefore conclude that gene expression noise is an important biological trait, and one that probably limits the evolvability of complex living systems.
Lehner B, 2007, Modelling genotype-phenotype relationships and human disease with genetic interaction networks., J Exp Biol, Vol: 210, Pages: 1559-1566, ISSN: 0022-0949
Probably all heritable traits, including disease susceptibility, are affected by interactions between mutations in multiple genes. We understand little, however, about how genes interact to produce phenotypes, and there is little power to detect interactions between genes in human population studies. An alternative approach towards understanding how mutations combine to produce phenotypes is to construct systematic genetic interaction networks in model organisms. Here I describe the methods that are being used to map genetic interactions in yeast and C. elegans, and the insights that these networks provide for human disease. I also discuss the mechanistic interpretation of genetic interaction networks, how genetic interactions can be used to understand gene function, and methods that have been developed to predict genetic interactions on a genome-wide scale.
Vavouri T, Walter K, Gilks WR, et al., 2007, Parallel evolution of conserved non-coding elements that target a common set of developmental regulatory genes from worms to humans., Genome Biol, Vol: 8
BACKGROUND: The human genome contains thousands of non-coding sequences that are often more conserved between vertebrate species than protein-coding exons. These highly conserved non-coding elements (CNEs) are associated with genes that coordinate development, and have been proposed to act as transcriptional enhancers. Despite their extreme sequence conservation in vertebrates, sequences homologous to CNEs have not been identified in invertebrates. RESULTS: Here we report that nematode genomes contain an alternative set of CNEs that share sequence characteristics, but not identity, with their vertebrate counterparts. CNEs thus represent a very unusual class of sequences that are extremely conserved within specific animal lineages yet are highly divergent between lineages. Nematode CNEs are also associated with developmental regulatory genes, and include well-characterized enhancers and transcription factor binding sites, supporting the proposed function of CNEs as cis-regulatory elements. Most remarkably, 40 of 156 human CNE-associated genes with invertebrate orthologs are also associated with CNEs in both worms and flies. CONCLUSION: A core set of genes that regulate development is associated with CNEs across three animal groups (worms, flies and vertebrates). We propose that these CNEs reflect the parallel evolution of alternative enhancers for a common set of developmental regulatory genes in different animal groups. This 're-wiring' of gene regulatory networks containing key developmental coordinators was probably a driving force during the evolution of animal body plans. CNEs may, therefore, represent the genomic traces of these 'hard-wired' core gene regulatory networks that specify the development of each alternative animal body plan.
Lehner B, Crombie C, Tischler J, et al., 2006, Systematic mapping of genetic interactions in Caenorhabditis elegans identifies common modifiers of diverse signaling pathways., Nat Genet, Vol: 38, Pages: 896-903, ISSN: 1061-4036
Most heritable traits, including disease susceptibility, are affected by interactions between multiple genes. However, we understand little about how genes interact because very few possible genetic interactions have been explored experimentally. We have used RNA interference in Caenorhabditis elegans to systematically test approximately 65,000 pairs of genes for their ability to interact genetically. We identify approximately 350 genetic interactions between genes functioning in signaling pathways that are mutated in human diseases, including components of the EGF/Ras, Notch and Wnt pathways. Most notably, we identify a class of highly connected 'hub' genes: inactivation of these genes can enhance the phenotypic consequences of mutation of many different genes. These hub genes all encode chromatin regulators, and their activity as genetic hubs seems to be conserved across animals. We propose that these genes function as general buffers of genetic variation and that these hub genes may act as modifier genes in multiple, mechanistically unrelated genetic diseases in humans.
Lehner B, Tischler J, Fraser AG, 2006, RNAi screens in Caenorhabditis elegans in a 96-well liquid format and their application to the systematic identification of genetic interactions., Nat Protoc, Vol: 1, Pages: 1617-1620
We describe a protocol for performing RNA interference (RNAi) screens in Caenorhabditis elegans in liquid culture in 96-well plates. The procedure allows a single researcher to set-up and score RNAi experiments at approximately 2,000 genes per day. By comparing RNAi phenotypes between wild-type worms and worms carrying a defined genetic mutation, we have used this protocol to identify synthetic lethal interactions between genes systematically. We also describe how the protocol can be adapted to target two genes simultaneously by combinatorial RNAi.
Tischler J, Lehner B, Chen N, et al., 2006, Combinatorial RNA interference in Caenorhabditis elegans reveals that redundancy between gene duplicates can be maintained for more than 80 million years of evolution., Genome Biol, Vol: 7
BACKGROUND: Systematic analyses of loss-of-function phenotypes have been carried out for most genes in Saccharomyces cerevisiae, Caenorhabditis elegans, and Drosophila melanogaster. Although such studies vastly expand our knowledge of single gene function, they do not address redundancy in genetic networks. Developing tools for the systematic mapping of genetic interactions is thus a key step in exploring the relationship between genotype and phenotype. RESULTS: We established conditions for RNA interference (RNAi) in C. elegans to target multiple genes simultaneously in a high-throughput setting. Using this approach, we can detect the great majority of previously known synthetic genetic interactions. We used this assay to examine the redundancy of duplicated genes in the genome of C. elegans that correspond to single orthologs in S. cerevisiae or D. melanogaster and identified 16 pairs of duplicated genes that have redundant functions. Remarkably, 14 of these redundant gene pairs were duplicated before the divergence of C. elegans and C. briggsae 80-110 million years ago, suggesting that there has been selective pressure to maintain the overlap in function between some gene duplicates. CONCLUSION: We established a high throughput method for examining genetic interactions using combinatorial RNAi in C. elegans. Using this technique, we demonstrated that many duplicated genes can retain redundant functions for more than 80 million years of evolution. This provides strong support for evolutionary models that predict that genetic redundancy between duplicated genes can be actively maintained by natural selection and is not just a transient side effect of recent gene duplication events.
This data is extracted from the Web of Science and reproduced under a licence from Thomson Reuters. You may not copy or re-distribute this data in whole or in part without the written consent of the Science business of Thomson Reuters.