Development through the eyes of functional genomics

A genome-wide MeSH-based literature mining system predicts implicit gene-to-gene relationships and networks

Background

The large amount of literature in the post-genomics era enables the study of gene interactions and networks using all available articles published for a specific organism. MeSH is a controlled vocabulary of medical and scientific terms that is used by biomedical scientists to manually index articles in the PubMed literature database. We hypothesized that genome-wide gene-MeSH term associations from the PubMed literature database could be used to predict implicit gene-to-gene relationships and networks. While the gene-MeSH associations have been used to detect gene-gene interactions in some studies, different methods have not been well compared, and such a strategy has not been evaluated for a genome-wide literature analysis. Genome-wide literature mining of gene-to-gene interactions allows ranking of the best gene interactions and investigation of comprehensive biological networks at a genome level.

Results

The genome-wide GenoMesh literature mining algorithm was developed by sequentially generating a gene-article matrix, a normalized gene-MeSH term matrix, and a gene-gene matrix. The gene-gene matrix relies on the calculation of pairwise gene dissimilarities based on gene-MeSH relationships. An optimized dissimilarity score was identified from six well-studied functions based on a receiver operating characteristic (ROC) analysis. Based on the studies with well-studied Escherichia coli and less-studied Brucella spp., GenoMesh was found to accurately identify gene functions using weighted MeSH terms, predict gene-gene interactions not reported in the literature, and cluster all the genes studied from an organism using the MeSH-based gene-gene matrix. A web-based GenoMesh literature mining program is also available at: http://genomesh.hegroup.org. GenoMesh also predicts gene interactions and networks among genes associated with specific MeSH terms or user-selected gene lists.

Conclusions

The GenoMesh algorithm and web program provide the first genome-wide, MeSH-based literature mining system that effectively predicts implicit gene-gene interaction relationships and networks in a genome-wide scope.

Broad network-based predictability of Saccharomyces cerevisiae gene loss-of-function phenotypes

Loss-of-function phenotypes of yeast genes can be predicted from the loss-of-function phenotypes of their neighbours in functional gene networks. This could potentially be applied to the prediction of human disease genes.

We demonstrate that loss-of-function yeast phenotypes are predictable by guilt-by-association in functional gene networks. Testing 1,102 loss-of-function phenotypes from genome-wide assays of yeast reveals predictability of diverse phenotypes, spanning cellular morphology, growth, metabolism, and quantitative cell shape features. We apply the method to extend a genome-wide screen by predicting, then verifying, genes whose disruption elongates yeast cells, and to predict human disease genes. To facilitate network-guided screens, a web server is available .

Signature pathways identified from gene expression profiles in the human uterine cervix before and after spontaneous term parturition

OBJECTIVE

This study aimed to discover "signature pathways" that characterize biologic processes, based on genes differentially expressed in the uterine cervix before and after spontaneous labor.

STUDY DESIGN

The cervical transcriptome was characterized previously from biopsy specimens taken before and after term labor. Pathway analysis was used to study the differentially expressed genes, based on 2 gene-to-pathway annotation databases (Kyoto Encyclopedia of Genes and Genomes [Kanehisa Laboratories, Kyoto University, Kyoto, Japan] and Metacore software [GeneGo, Inc, St. Joseph, MI]). Overrepresented and highly impacted pathways and connectivity nodes were identified.

RESULTS

Fifty-two pathways in the Metacore database were enriched significantly in differentially expressed genes. Three of the top 5 pathways were known to be involved in cervical remodeling. Two novel pathways were plasmin signaling and plasminogen activator urokinase signaling. The same analysis with the Kyoto Encyclopedia of Genes and Genomes database identified 4 significant pathways that the impact analysis confirmed. Multiple nodes that provide connectivity within the plasmin and plasminogen activator urokinase signaling pathways were identified.

CONCLUSION

Three strategies for pathway analysis were consistent in their identification of novel, unexpected, and expected pathways, which suggests that this approach is both valid and effective for the elucidation of biologic mechanisms that are involved in cervical dilation and remodeling.

Quantitative expression profiling of identified neurons reveals cell-specific constraints on highly variable levels of gene expression

The postdevelopmental basis of cellular identity and the unique cellular output of a particular neuron type are of particular interest in the nervous system because a detailed understanding of circuits responsible for complex processes in the brain is impeded by the often ambiguous classification of neurons in these circuits. Neurons have been classified by morphological, electrophysiological, and neurochemical techniques. More recently, molecular approaches, particularly microarray, have been applied to the question of neuronal identity. With the realization that proteins expressed exclusively in only one type of neuron are rare, expression profiles obtained from neuronal subtypes are analyzed to search for diagnostic patterns of gene expression. However, this expression profiling hinges on one critical and implicit assumption: that neurons of the same type in different animals achieve their conserved functional output via conserved levels and quantitative relationships of gene expression. Here we exploit the unambiguously identifiable neurons in the crab stomatogastric ganglion to investigate the precise quantitative expression profiling of neurons at the level of single-cell ion channel expression. By measuring absolute mRNA levels of six different channels in the same individually identified neurons, we demonstrate that not only do individual cell types possess highly variable levels of channel expression but that this variability is constrained by unique patterns of correlated channel expression.

Zac1 regulates an imprinted gene network critically involved in the control of embryonic growth

Genomic imprinting is an epigenetic mechanism of regulation that restrains the expression of a small subset of mammalian genes to one parental allele. The reason for the targeting of these approximately 80 genes by imprinting remains uncertain. We show that inactivation of the maternally repressed Zac1 transcription factor results in intrauterine growth restriction, altered bone formation, and neonatal lethality. A meta-analysis of microarray data reveals that Zac1 is a member of a network of coregulated genes comprising other imprinted genes involved in the control of embryonic growth. Zac1 alters the expression of several of these imprinted genes, including Igf2, H19, Cdkn1c, and Dlk1, and it directly regulates the Igf2/H19 locus through binding to a shared enhancer. Accordingly, these data identify a network of imprinted genes, including Zac1, which controls embryonic growth and which may be the basis for the implementation of a common mechanism of gene regulation during mammalian evolution.

Developmental constraints vs. variational properties: How pattern formation can help to understand evolution and development

This article suggests that apparent disagreements between the concept of developmental constraints and neo-Darwinian views on morphological evolution can disappear by using a different conceptualization of the interplay between development and selection. A theoretical framework based on current evolutionary and developmental biology and the concepts of variational properties, developmental patterns and developmental mechanisms is presented. In contrast with existing paradigms, the approach in this article is specifically developed to compare developmental mechanisms by the morphological variation they produce and the way in which their functioning can change due to genetic variation. A developmental mechanism is a gene network, which is able to produce patterns in space though the regulation of some cell behaviour (like signalling, mitosis, apoptosis, adhesion, etc.). The variational properties of a developmental mechanism are all the pattern transformations produced under different initial and environmental conditions or IS-mutations. IS-mutations are DNA changes that affect how two genes in a network interact, while T-mutations are mutations that affect the topology of the network itself. This article explains how this new framework allows predictions not only about how pattern formation affects variation, and thus phenotypic evolution, but also about how development evolves by replacement between pattern formation mechanisms. This article presents testable inferences about the evolution of the structure of development and the phenotype under different selective pressures. That is what kind of pattern formation mechanisms, in which relative temporal order, and which kind of phenotypic changes, are expected to be found in development.

Studying phenotypic evolution using multivariate quantitative genetics

Quantitative genetics provides a powerful framework for studying phenotypic evolution and the evolution of adaptive genetic variation. Central to the approach is G, the matrix of additive genetic variances and covariances. G summarizes the genetic basis of the traits and can be used to predict the phenotypic response to multivariate selection or to drift. Recent analytical and computational advances have improved both the power and the accessibility of the necessary multivariate statistics. It is now possible to study the relationships between G and other evolutionary parameters, such as those describing the mutational input, the shape and orientation of the adaptive landscape, and the phenotypic divergence among populations. At the same time, we are moving towards a greater understanding of how the genetic variation summarized by G evolves. Computer simulations of the evolution of G, innovations in matrix comparison methods, and rapid development of powerful molecular genetic tools have all opened the way for dissecting the interaction between allelic variation and evolutionary process. Here I discuss some current uses of G, problems with the application of these approaches, and identify avenues for future research.

Whole-genome analysis of the SHORT-ROOT developmental pathway in Arabidopsis

Stem cell function during organogenesis is a key issue in developmental biology. The transcription factor SHORT-ROOT (SHR) is a critical component in a developmental pathway regulating both the specification of the root stem cell niche and the differentiation potential of a subset of stem cells in the Arabidopsis root. To obtain a comprehensive view of the SHR pathway, we used a statistical method called meta-analysis to combine the results of several microarray experiments measuring the changes in global expression profiles after modulating SHR activity. Meta-analysis was first used to identify the direct targets of SHR by combining results from an inducible form of SHR driven by its endogenous promoter, ectopic expression, followed by cell sorting and comparisons of mutant to wild-type roots. Eight putative direct targets of SHR were identified, all with expression patterns encompassing subsets of the native SHR expression domain. Further evidence for direct regulation by SHR came from binding of SHR in vivo to the promoter regions of four of the eight putative targets. A new role for SHR in the vascular cylinder was predicted from the expression pattern of several direct targets and confirmed with independent markers. The meta-analysis approach was then used to perform a global survey of the SHR indirect targets. Our analysis suggests that the SHR pathway regulates root development not only through a large transcription regulatory network but also through hormonal pathways and signaling pathways using receptor-like kinases. Taken together, our results not only identify the first nodes in the SHR pathway and a new function for SHR in the development of the vascular tissue but also reveal the global architecture of this developmental pathway.

Meta-analysis to combine the results of several microarray experiments reveals a new function for the transcription factor SHORT-ROOT in the development of vascular tissue.

Laser microdissection of plant tissue: what you see is what you get

Laser microdissection (LM) utilizes a cutting or harvesting laser to isolate specific cells from histological sections; the process is guided by microscopy. This provides a means of removing selected cells from complex tissues, based only on their identification by microscopic appearance, location, or staining properties (e.g., immunohistochemistry, reporter gene expression, etc.). Cells isolated by LM can be a source of cell-specific DNA, RNA, protein or metabolites for subsequent evaluation of DNA modifications, transcript/protein/metabolite profiling, or other cell-specific properties that would be averaged with those of neighboring cell types during analysis of undissected complex tissues. Plants are particularly amenable to the application of LM; the highly regular tissue organization and stable cell walls of plants facilitate the visual identification of most cell types even in unstained tissue sections. Plant cells isolated by LM have been the starting point for a variety of genomic and metabolite studies of specific cell types.

Asymmetric cell divisions in flowering plants - one mother, "two-many" daughters

Plant development shows a fascinating range of asymmetric cell divisions. Over the years, however, cellular differentiation has been interpreted mostly in terms of a mother cell dividing mitotically to produce two daughter cells of different fates. This popular view has masked the significance of an entirely different cell fate specification pathway, where the mother cell first becomes a coenocyte and then cellularizes to simultaneously produce more than two specialized daughter cells. The "one mother - two different daughters" pathways rely on spindle-assisted mechanisms, such as translocation of the nucleus/spindle to a specific cellular site and orientation of the spindle, which are coordinated with cell-specific allocation of cell fate determinants and cytokinesis. By contrast, during "coenocyte-cellularization" pathways, the spindle-assisted mechanisms are irrelevant since cell fate specification emerges only after the nuclear divisions are complete, and the number of specialized daughter cells produced depends on the developmental context. The key events, such as the formation of a coenocyte and migration of the nuclei to specific cellular locations, are coordinated with cellularization by unique types of cell wall formation. Both one mother - two different daughters and the coenocyte-cellularization pathways are used by higher plants in precise spatial and time windows during development. In both the pathways, epigenetic regulation of gene expression is crucial not only for cell fate specification but also for its maintenance through cell lineage. In this review, the focus is on the coenocyte-cellularization pathways in the context of our current understanding of the asymmetric cell divisions. Instances where cell differentiation does not involve an asymmetric division are also discussed to provide a comprehensive account of cell differentiation.