Lisa Simirenko

Bio: Lisa Simirenko is an academic researcher from Lawrence Berkeley National Laboratory. The author has contributed to research in topics: Blastoderm & Gene. The author has an hindex of 5, co-authored 7 publications receiving 1071 citations. Previous affiliations of Lisa Simirenko include Joint Genome Institute.

Transcription factors bind thousands of active and inactive regions in the Drosophila blastoderm.

Abstract: Identifying the genomic regions bound by sequence-specific regulatory factors is central both to deciphering the complex DNA cis-regulatory code that controls transcription in metazoans and to determining the range of genes that shape animal morphogenesis. We used whole-genome tiling arrays to map sequences bound in Drosophila melanogaster embryos by the six maternal and gap transcription factors that initiate anterior–posterior patterning. We find that these sequence-specific DNA binding proteins bind with quantitatively different specificities to highly overlapping sets of several thousand genomic regions in blastoderm embryos. Specific high- and moderate-affinity in vitro recognition sequences for each factor are enriched in bound regions. This enrichment, however, is not sufficient to explain the pattern of binding in vivo and varies in a context-dependent manner, demonstrating that higher-order rules must govern targeting of transcription factors. The more highly bound regions include all of the over 40 well-characterized enhancers known to respond to these factors as well as several hundred putative new cis-regulatory modules clustered near developmental regulators and other genes with patterned expression at this stage of embryogenesis. The new targets include most of the microRNAs (miRNAs) transcribed in the blastoderm, as well as all major zygotically transcribed dorsal–ventral patterning genes, whose expression we show to be quantitatively modulated by anterior–posterior factors. In addition to these highly bound regions, there are several thousand regions that are reproducibly bound at lower levels. However, these poorly bound regions are, collectively, far more distant from genes transcribed in the blastoderm than highly bound regions; are preferentially found in protein-coding sequences; and are less conserved than highly bound regions. Together these observations suggest that many of these poorly bound regions are not involved in early-embryonic transcriptional regulation, and a significant proportion may be nonfunctional. Surprisingly, for five of the six factors, their recognition sites are not unambiguously more constrained evolutionarily than the immediate flanking DNA, even in more highly bound and presumably functional regions, indicating that comparative DNA sequence analysis is limited in its ability to identify functional transcription factor targets.

Developmental roles of 21 Drosophila transcription factors are determined by quantitative differences in binding to an overlapping set of thousands of genomic regions

Abstract: We previously established that six sequence-specific transcription factors that initiate anterior/posterior patterning in Drosophila bind to overlapping sets of thousands of genomic regions in blastoderm embryos. While regions bound at high levels include known and probable functional targets, more poorly bound regions are preferentially associated with housekeeping genes and/or genes not transcribed in the blastoderm, and are frequently found in protein coding sequences or in less conserved non-coding DNA, suggesting that many are likely non-functional. Here we show that an additional 15 transcription factors that regulate other aspects of embryo patterning show a similar quantitative continuum of function and binding to thousands of genomic regions in vivo. Collectively, the 21 regulators show a surprisingly high overlap in the regions they bind given that they belong to 11 DNA binding domain families, specify distinct developmental fates, and can act via different cis-regulatory modules. We demonstrate, however, that quantitative differences in relative levels of binding to shared targets correlate with the known biological and transcriptional regulatory specificities of these factors. It is likely that the overlap in binding of biochemically and functionally unrelated transcription factors arises from the high concentrations of these proteins in nuclei, which, coupled with their broad DNA binding specificities, directs them to regions of open chromatin. We suggest that most animal transcription factors will be found to show a similar broad overlapping pattern of binding in vivo, with specificity achieved by modulating the amount, rather than the identity, of bound factor.

Three-dimensional morphology and gene expression in the Drosophila blastoderm at cellular resolution I: data acquisition pipeline

Abstract: To model and thoroughly understand animal transcription networks, it is essential to derive accurate spatial and temporal descriptions of developing gene expression patterns with cellular resolution. Here we describe a suite of methods that provide the first quantitative three-dimensional description of gene expression and morphology at cellular resolution in whole embryos. A database containing information derived from 1,282 embryos is released that describes the mRNA expression of 22 genes at multiple time points in the Drosophila blastoderm. We demonstrate that our methods are sufficiently accurate to detect previously undescribed features of morphology and gene expression. The cellular blastoderm is shown to have an intricate morphology of nuclear density patterns and apical/basal displacements that correlate with later well-known morphological features. Pair rule gene expression stripes, generally considered to specify patterning only along the anterior/posterior body axis, are shown to have complex changes in stripe location, stripe curvature, and expression level along the dorsal/ventral axis. Pair rule genes are also found to not always maintain the same register to each other. The application of these quantitative methods to other developmental systems will likely reveal many other previously unknown features and provide a more rigorous understanding of developmental regulatory networks.

PointCloudXplore: visual analysis of 3d gene expression data using physical views and parallel coordinates

Abstract: To allow a more rigorous understanding of animal gene regulatory networks, the Berkeley Drosophila Transcription Network Project (BDTNP) has developed a suite of methods that support quantitative, computational analysis of three-dimensional (3D) gene expression patterns with cellular resolution in early Drosophila embryos. Here we report the first components of a visualization tool, PointCloudXplore, that allows the relationships between different gene's expression to be analyzed using the BDTNP's datasets. PointCloudXplore uses the established visualization techniques of multiple views, brushing, and linking to support the analysis of high-dimensional datasets that describe many genes' expression. Each of the views in PointCloud- Xplore shows a different gene expression data property. Brushing is used to select and emphasize data associated with defined subsets of embryo cells within a view. Linking is used to show in additional views the expression data for a group of cells that have first been highlighted as a brush in a single view, allowing further data subset properties to be determined. In PointCloudXplore, physical views of the data are linked to parallel coordinates. Physical views show the spatial relationships between different genes' expression patterns within the embryo. Parallel coordinates, on the other hand, show only some features of each gene's expression, but allow simultaneous analysis of data for many more genes than would be possible in a physical view. We have developed several extensions to standard parallel coordinates to facilitate brushing the visualization of 3D gene expression data.

{PointCloudXplore}: a visualization tool for 3D gene expressiondata

Abstract: PointCloudXplore: A Visualization Tool for 3D Gene Expression Data Oliver R¨ bel ∗,1,2 , Gunther H. Weber 2,3 , Soile V.E. Ker¨ nen 3 , Charless C. Fowlkes 4 , u a Cris L. Luengo Hendriks 3 , Lisa Simirenko 3 , Nameeta Y. Shah 2 , Michael B. Eisen 3 , Mark D. Biggin 3 , Hans Hagen 1 , Damir Sudar 3 , Jitendra Malik 4 , David W. Knowles 3 , and Bernd Hamann 1,2 International Research Training Group “Visualization of Large and Unstructured Data Sets,” University of Kaiserslautern, Germany Institute for Data Analysis and Visualization, University of California, Davis, CA, USA Life Sciences and Genomics Divisions, Lawrence Berkeley National Laboratory, Berkeley, CA, USA Computer Science Division, University of California, Berkeley, CA, USA Abstract: The Berkeley Drosophila Transcription Network Project (BDTNP) has de- veloped a suite of methods that support quantitative, computational analysis of three- dimensional (3D) gene expression patterns with cellular resolution in early Drosophila embryos, aiming at a more in-depth understanding of gene regulatory networks. We describe a new tool, called PointCloudXplore (PCX), that supports effective 3D gene expression data exploration. PCX is a visualization tool that uses the established visualization techniques of multiple views, brushing, and linking to support the analysis of high-dimensional datasets that describe many genes’ expression. Each of the views in PointCloudXplore shows a different gene expression data property. Brushing is used to select and em- phasize data associated with defined subsets of embryo cells within a view. Linking is used to show in additional views the expression data for a group of cells that have first been highlighted as a brush in a single view, allowing further data subset properties to be determined. In PCX, physical views of the data are linked to abstract data displays such as parallel coordinates. Physical views show the spatial relationships between different genes’ expression patterns within an embryo. Abstract gene expression data displays on the other hand allow for an analysis of relationships between different genes directly in the gene expression space. We discuss on parallel coordinates as one example abstract data view currently available in PCX. We have developed several ex- tensions to standard parallel coordinates to facilitate brushing and the visualization of 3D gene expression data. ∗ oliverruebel@web.de

Transcription factors: from enhancer binding to developmental control.

Abstract: Developmental progression is driven by specific spatiotemporal domains of gene expression, which give rise to stereotypically patterned embryos even in the presence of environmental and genetic variation. Views of how transcription factors regulate gene expression are changing owing to recent genome-wide studies of transcription factor binding and RNA expression. Such studies reveal patterns that, at first glance, seem to contrast with the robustness of the developmental processes they encode. Here, we review our current knowledge of transcription factor function from genomic and genetic studies and discuss how different strategies, including extensive cooperative regulation (both direct and indirect), progressive priming of regulatory elements, and the integration of activities from multiple enhancers, confer specificity and robustness to transcriptional regulation during development.

Pioneer transcription factors: establishing competence for gene expression

Abstract: Transcription factors are adaptor molecules that detect regulatory sequences in the DNA and target the assembly of protein complexes that control gene expression. Yet much of the DNA in the eukaryotic cell is in nucleosomes and thereby occluded by histones, and can be further occluded by higher-order chromatin structures and repressor complexes. Indeed, genome-wide location analyses have revealed that, for all transcription factors tested, the vast majority of potential DNA-binding sites are unoccupied, demonstrating the inaccessibility of most of the nuclear DNA. This raises the question of how target sites at silent genes become bound de novo by transcription factors, thereby initiating regulatory events in chromatin. Binding cooperativity can be sufficient for many kinds of factors to simultaneously engage a target site in chromatin and activate gene expression. However, in cases in which the binding of a series of factors is sequential in time and thus not initially cooperative, special "pioneer transcription factors" can be the first to engage target sites in chromatin. Such initial binding can passively enhance transcription by reducing the number of additional factors that are needed to bind the DNA, culminating in activation. In addition, pioneer factor binding can actively open up the local chromatin and directly make it competent for other factors to bind. Passive and active roles for the pioneer factor FoxA occur in embryonic development, steroid hormone induction, and human cancers. Herein we review the field and describe how pioneer factors may enable cellular reprogramming.

Transcriptional enhancers: from properties to genome-wide predictions.

Abstract: Cellular development, morphology and function are governed by precise patterns of gene expression. These are established by the coordinated action of genomic regulatory elements known as enhancers or cis-regulatory modules. More than 30 years after the initial discovery of enhancers, many of their properties have been elucidated; however, despite major efforts, we only have an incomplete picture of enhancers in animal genomes. In this Review, we discuss how properties of enhancer sequences and chromatin are used to predict enhancers in genome-wide studies. We also cover recently developed high-throughput methods that allow the direct testing and identification of enhancers on the basis of their activity. Finally, we discuss recent technological advances and current challenges in the field of regulatory genomics.