Genomic Approaches to Understanding Hox Gene Function

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Genomic Approaches to Understanding Hox Gene Function Siew Woh Choo*,† and Steven Russell* *Department of Genetics and Cambridge Systems Biology Centre, University of Cambridge, Cambridge, United Kingdom † Research and Training Unit, Dean’s Office, Faculty of Dentistry, University of Malaya, Kuala Lumpur, Malaysia

I. Introduction: Historical Perspective II. The Molecular Genetics of Hox Complexes: Conservation and Colinearity III. Hox Target Genes and Functions IV. Early Experiments to Identify Hox Target Genes V. Genomic Approaches to Identifying Hox Target Genes VI. Microarray Expression Profiling VII. ChIP Approaches VIII. Computational Approaches IX. Prospects References

ABSTRACT For many years, biologists have sought to understand how the homeodomaincontaining transcriptional regulators encoded by Hox genes are able to control the development of animal morphology. Almost a century of genetics and several decades of molecular biology have defined the conserved organization of homeotic gene clusters in animals and the basic molecular properties of Hox transcription factors. In contrast to these successes, we remain relatively ignorant of how Hox proteins find their target genes in the genome or what sets of genes a Hox Advances in Genetics, Vol. 76 Copyright 2011, Elsevier Inc. All rights reserved.

0065-2660/11 $35.00 DOI: 10.1016/B978-0-12-386481-9.00003-1

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protein regulates to direct morphogenesis. The recent deployment of genomic methods, such as whole transcriptome mRNA expression profiling and genomewide analysis of protein–DNA interactions, begins to shed light on these issues. Results from such studies, principally in the fruit fly, indicate that Hox proteins control the expression of hundreds, if not thousands, of genes throughout the gene regulatory network and that, in many cases, the effects on the expression of individual genes may be quite subtle. Hox proteins regulate both high-level effectors, including other transcription factors and signaling molecules, as well as the cytodifferentiation genes or Realizators at the bottom of regulatory hierarchies. Insights emerging from mapping Hox binding sites in the genome begin to suggest that Hox binding may be strongly influenced by chromatin accessibility rather than binding site affinity. If this is the case, it indicates we need to refocus our efforts at understanding Hox function toward the dynamics of gene regulatory networks and chromatin epigenetics. ß 2011, Elsevier Inc.

I. INTRODUCTION: HISTORICAL PERSPECTIVE For centuries, the myriad forms that characterize multicellular organisms have fascinated scientists, particularly when, at the dawn of the scientific revolution in the sixteenth century, comparative anatomists began to realize that morphological similarities revealed hitherto unsuspected relationships between creatures. The next two centuries of natural science saw several important breakthroughs: the development of the microscope produced revelations about the complexity of biological form at all levels; Linnaeus’s use of form developed the first systematic classification of the living world; Darwin’s use of comparative anatomy provided support for the idea of descent with modification; and finally, Mendel worked out the mechanism underpinning inheritance. During the latter part of the nineteenth century, developments in experimental biology and the rediscovery of Mendel’s work by Vries and Correns set the scene for over a century of subsequent and ongoing research into the specification and elaboration of biological form. The Cambridge geneticist William Bateson coined the term homeosis to describe situations where natural variation resulted in the replacement of one body part by another (Bateson, 1894). It soon became clear, especially with a conceptual framework for describing inheritance in place, that the type of homeotic transformations described by Bateson offered a route for exploring the control of form. Enter the fly: it should come as no surprise to Drosophila researchers to learn that the first bona fide homeotic mutation, bithorax (bx), was discovered by Calvin Bridges (on 22 September 1915; Bridges and Morgan, 1923). The subsequent analysis of homeotic mutations in several species, but particularly in the fruit fly, serves as a poster child for the success of classical forward genetics, and latterly molecular biology, in seeking to

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understand the molecular basis of patterning (Lewis, 1994; McGinnis, 1994). Nevertheless, despite almost 100 years of research, we still have much to learn, and it is hoped that the current crop of genomic techniques will be brought into play to further our understanding of the molecular mechanisms underpinning the regulation of form. Homeobox (Hox) genes encode key regulators of cellular identity in all bilaterian animals, including nematodes, arthropods, and vertebrates. Hox genes were initially identified in Drosophila melanogaster, and while the classical geneticists from the Columbia fly lab set in play the analysis of Drosophila homeotic mutations, it is safe to say it was the seminal and Nobel Prize winning work of Edward B. Lewis on the genetics of homeotic genes that really defined the genetic analysis of homeotic function (Lewis, 1978). Hox proteins control the morphological distinction of segments along the anterior–posterior (AP) body axis by regulating specific sets of target genes. During metazoan embryonic development, Hox proteins specify segmental identities, for example, which part of the body develops particular appendages such as arms, legs, or wings. Along with these decisions on external morphological features, Hox proteins also control the proper development of the internal organs and nervous system as well as, in vertebrates, the skeleton. To perform these diverse functions, Hox proteins are believed to function as master regulators, controlling sets of downstream genes (reviewed in Akam, 1998; Graba et al., 1997; Grier et al., 2005; Hueber and Lohmann, 2008; Lappin et al., 2006; Lohmann, 2006; McGinnis and Krumlauf, 1992; Pradel and White, 1998). Thus, one of the key issues for understanding how Hox proteins control the development of the metazoan body plan is the identification of comprehensive sets of Hox target genes. One of the most iconic of homeotic transformations in Drosophila, where the modified hind wing (balance organs known as halteres that are characteristic of dipterans) is transformed into forewings, is displayed by mutations associated with the Ultrabithorax (Ubx) gene (Bridges and Morgan, 1923; Lewis, 1978). The most striking example involves a combination of three Ubx regulatory mutations (anterobithorax (abx), bithorax (bx), and postbithorax (pbx)) which can lead to a virtually complete transformation of the third thoracic segment into a copy of the second thoracic segment, generating the famous four-winged fly (Fig. 3.1). The work of Lewis on the genetics of this class of homeotic mutations defined the first Hox cluster, the bithorax complex (BX-C), which specifies the correct development of the posterior thorax and the abdominal segments of the fly. Subsequent work by Thomas Kaufman and colleagues showed similar properties for the homeotic genes encoded by the Antennapedia complex (ANT-C) in specifying the development of structures in the head and anterior portion of the thorax (Abbott and Kaufman, 1986; Kaufman et al., 1980). Together, these studies set the scene for the genetic and molecular analysis of homeotic gene function.

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bx

Wild type

abx bx pbx

Figure 3.1. Homeotic transformations. On the left, Edith Wallace’s drawing of the original bithorax mutation isolated by Bridges (Bridges and Morgan, 1923), note the partial transformation of haltere to wing (from a drawing in the Caltech archive: http://archives.caltech. edu/news/wallace.html). Middle and left, the famous four-winged fly. A loss of Ubx function in the third thoracic segment (from flies carrying the abx, bx, and pbx alleles) transforms the halter and notum structures to second thoracic segment identities. Redrawn from Nobel foundation images.

It would be fair to say that modern genomics, the systematic analysis of genome sequence, began with the molecular cloning of the BX-C in the laboratory of David Hogness during the early 1980s (Bender et al., 1983), quickly followed by the cloning of the ANT-C in the Kaufman and Gehring labs (Garber et al., 1983; Scott et al., 1983). Subsequent work in the mid-1980s by the laboratories of Walter Gehring and Matt Scott discovered that the homeotic genes of the ANT-C and BX-C encode a set of related proteins that function as transcriptional regulators: they share a highly conserved 180-bp DNA sequence, the homeobox, encoding a 60-amino acid DNA binding domain, the homeodomain (Gehring and Hiromi, 1986; McGinnis et al., 1984; Scott and Weiner, 1984). The homeodomain motif comprises three a-helices with the third helix designated the recognition helix since it contains several key residues that confer DNA binding specificity (Mann, 1995). Based on sequence relationships within the increasingly large family, homeobox containing proteins are divided into classes (Antp, Prd, POU, ZF, and LIM; Duboule, 1994; Merabet et al., 2009). Here, we are concerned with the genes of the Antp class, which encode those Hox proteins with homeotic functions. Over the years, many in vitro studies have been performed to examine the binding specificity of Hox transcription factors. Surprisingly, these studies have shown that all Hox proteins bind to the same or a very similar six base sequence containing a TAAT core (Beachy et al., 1988; Catron et al., 1993; Ekker et al., 1991; Mann, 1995; Pellerin et al., 1994; Walter et al., 1994). These observations raised a key issue in Hox biology: in vivo Hox proteins have clearly distinct functions, each specifying the development of different segmental identities along the AP axis of the animal. In order to achieve this functional specificity, we imagine that individual Hox proteins largely control distinct sets of target genes or differentially control a similar set of targets (Hueber et al., 2007; Joshi et al., 2010; Stobe et al., 2009). How Hox

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proteins select target genes to achieve the high degree of in vivo specificity necessary, despite their apparent similar DNA binding specificity is still not fully understood. Unfortunately, classical genetics and molecular biology have yielded relatively few Hox targets to date: this undoubtedly restricts our understanding of Hox function and how Hox proteins achieve in vivo specificity. Here, we review the work identifying Hox target genes prior to genomic era since these studies have been instrumental in forming our ideas of Hox function (for reviews see Akam, 1998; Graba et al., 1997; Pradel and White, 1998). We go on to describe more recent studies that search for Hox target genes on a genome-wide scale using a variety of genomic approaches and discuss how the findings from these studies improve our understanding of Hox function (reviewed in Hueber and Lohmann, 2008; Pavlopoulos and Akam, 2007). Much of the initial Hox work was carried out with Drosophila, which has served as excellent and highly tractable model for exploring the molecular basis of patterning. Latterly, work building on our understanding of Hox function in the fly has begun to address the more complex issue of Hox function in vertebrates (for reviews, see Mallo et al., 2010; Tumpel et al., 2009; Wellik, 2009; Zakany and Duboule, 2007). Here, we mainly focus on the work in Drosophila aimed at defining Hox functions, introducing studies with other organisms where appropriate. We finish with very recent work applying genome-scale approaches to identifying direct target genes in Drosophila and speculation on how these and future studies will provide a better understanding of how morphology is specified.

II. THE MOLECULAR GENETICS OF HOX COMPLEXES: CONSERVATION AND COLINEARITY In the Drosophila genome, there are eight Hox genes located within the two genetically defined complexes on chromosome 3R (ANT-C and BX-C) (Duncan, 1987; Gehring and Hiromi, 1986; Kaufman et al., 1980; Lewis, 1978). The ANT-C comprises five Hox genes: labial (lab), proboscipedia (pb), Deformed (Dfd), Sex combs reduced (Scr), and Antennapedia (Antp), along with a few non-Hox regulators such as zerknult (zen), bicoid (bcd), and fushi tarazu (ftz). The BX-C, which is separated from the ANT-C by some 10 Mb, contains three Hox genes: Ultrabithorax (Ubx), abdominal-A (abd-A), and Abdominal-B (Abd-B). The genes of the ANT-C control the development of anterior structures of the fly, including the head and half of the thoracic region, whereas the genes in BX-C control the development of the posterior structures including the abdomen and some thoracic regions. While it has been proposed that the two fly Hox complexes represent an ancient single Hox cluster that has been split during the fly lineage and that the ancestral state is a single colinear Hox complex, more recent studies suggest that the fly Hox clusters may be unusual

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(see Garcia-Fernandez, 2005; Gehring et al., 2009; Maeda and Karch, 2009; Negre and Ruiz, 2007 for a discussion). The characterization of Hox genes and homeotic complexes in a range of phyla is an ongoing effort that aims to understand the evolution of these primary regulators of animal morphology. During embryogenesis, a Drosophila embryo is divided into 14 segments, a series of repeating morphological units that coincide with morphological features on the larval cuticle: there are three head, three thoracic and eight abdominal segments. Along with the segments, embryos are metamerized into 14 repeating units called parasegments. Although there is the same number of segments and parasegments, their boundaries do not coincide: each parasegment consists of the posterior half of a segment and the anterior region of the adjacent segment. In essence, one can consider segments as the morphological manifestation of a metameric body plan whereas the parasegments are the primary genetic units of segmentation (Deutsch, 2004). Hox genes are expressed in overlapping parasegments along the AP axis of the embryo. For example, Ubx is expressed in parasegments 5–13, abd-A in parasegments 7–14, and Abd-B in parasegments 10–14. The regulatory relationships between genes in Hox clusters is a complex issue that is still far from clear in Drosophila and is even less well understood in vertebrates. This complex area is outwith the scope of this particular review and interested readers are referred to some recent reviews (Maeda and Karch, 2006, 2009; Singh and Mishra, 2008). Remarkably, the expression of Hox genes along the AP axis of the developing Drosophila embryo shows a striking colinear relationship with the position of the Hox genes within the gene clusters (see Fig. 3.2A for an overview). Thus, the lab gene, located at the proximal end of the ANT-C closest to the centromere, is expressed in the most anterior segments of the embryo (the intercalary segment in the head), and the Abd-B gene, located at the distal end of the BX-C closest to the telomere, is expressed in the most posterior segments of the abdomen (Abzhanov and Kaufman, 1999; Maeda and Karch, 2006). The functional significance of this organization remains unclear, although it is widely believed to be linked to the requirement for precise spatial and temporal expression of each Hox gene. The finding that Hox colinearity is not unique to Drosophila suggests that the underlying molecular requirement for precise gene order in Hox clusters is likely to be intimately associated with the evolution of the metazoan body plan (Fig. 3.2B; Duboule, 1998; Mann, 1997). As we alluded to earlier, Hox genes are not unique to flies, they are also present in the genomes of all animals characterized to date, and there are orthologues within fungal and plant genomes (Lappin et al., 2006). Although this family of transcription factors is widespread in the eukaryotes, it is in the animals that we see an ancient organization of Antp class Hox genes into clusters (Garcia-Fernandez, 2005). For example, the nematode Caenorhabditis elegans has a Hox cluster containing five genes (orthologues of lab, pb, Dfd, and Antp along with a fifth, Hox3; Aboobaker and Blaxter, 2003). In the Pufferfish, Tetraodon

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A

lab

pb

Dfd Scr Antp

abd-A

Ubx

ANT-C

Abd-B

BX-C

B

Mus chr 6 Hum chr 7 Mus chr 11 Hum chr 17

a1

a2

a3

a4

a5

a6

a7

b1

b2

b3

b4

b5

b6

b7

c4

c5

c6

Mus chr 15 Hum chr 12 Mus chr 2 Hum chr 2

d1

d3

d4

a9

a10

a11

a13

b8

b9

b13

c8

c9

c10

d8

d9

d10 d11 d12 d13

c11 c12

c13

Figure 3.2. Hox colinearity and conservation. (A) Drosophila embryo and adult colored to indicate the expression domains of the Hox genes within the ANT-C and BX-C. (B) A schematic of the four mammalian Hox clusters indicating the content of each cluster with genes colored according to their orthology with fly Hox genes. The stylized schematic of a mouse embryo above the gene clusters indicates Hox colinearity in a vertebrate embryo. Hox complexes are not drawn to scale. The mammalian Hox gene nomenclature follows the scheme of Scott (1992).

nigroviridis, there are four Hox clusters while in some fish, such as the zebrafish Danio rerio, the number of Hox clusters is increased to seven as a result of a whole genome duplication during the evolution of some fish lineages (Hoegg et al., 2007; Schilling and Knight, 2001). While basal Chordates, such as Amphioxus, have only a single cluster containing 10 Hox genes (Garcia-Fernandez and Holland, 1994), mammalian and avian genomes generally contain four Hox clusters (Garcia-Fernandez, 2005). The presence of clusters of Antp class Hox genes with similar organizations across different kingdoms is a strong indication that these genes play critical and ancient roles in development. Although the genes within the two Drosophila Hox clusters show a high degree of similarity to genes in Hox clusters from other organisms, there is considerable variability in terms of the number of Hox genes in each cluster.

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While Drosophila has a total of eight Hox genes, the number of identified Hox genes in vertebrates is far larger. For example, 39 Antp class homeotic genes have been identified in the human and mouse genomes, subdivided into different groups based on their sequence similarities to the fly Hox genes. In vertebrates, the four clusters of Hox genes (Hoxa, Hoxb, Hoxc, and Hoxd) are usually unlinked and located on different chromosomes (Fig. 3.2B). The number of Hox genes varies among the clusters, with some Hox genes deleted or duplicated in particular clusters over the course of evolution. For example, in the human genome, the lab orthologues (Hoxa1, Hoxb1, and Hoxd1) are present in three clusters but absent from the Hoxc cluster, while the Hoxa cluster contains four Abd-B orthologues (Hoxa9, Hoxa10, Hoxa11, and Hoxa13). Thus, although the basic ground plan of a Hox cluster is conserved across phyla, individual species can have multiple clusters, each with a unique constellation of Hox genes within each cluster. Despite the variability, generally speaking, the key features of Hox organization are conserved: the colinearity of gene order and AP expression characteristic of the fly clusters are seen across the Metazoa (Garcia-Fernandez, 2005; McGinnis and Krumlauf, 1992).

III. HOX TARGET GENES AND FUNCTIONS The highly conserved genomic organization and expression of Hox clusters suggest that Hox gene functions provide key aspects of the molecular machinery regulating the patterning of the metazoan body plan. Critical to understanding how Hox proteins regulate developmental processes is the identification of the sets of target genes controlled by individual Hox proteins. Identifying Hox targets is important for two reasons: first, as described above, we need to understand how a set of transcription factors with apparently similar DNA target site specificities can regulate different sets of targets genes. Second, we need to understand conceptually how a single transcription factor can control a complex series of cellular functions to generate the diversity of body plan morphologies that characterize the Metazoa. Thinking about how homeotic genes could control the development of particular structures, Antonio Garcia-Bellido proposed the concept of Activators, Selectors, and Realizators (Garcia-Bellido, 1975). In this model, conceived before the molecular cloning of Hox genes, a set of Selector genes encode factors that control specific cytodifferentiation or Realizator genes. The expression of Selector genes in different segments along the AP axis of the developing organism is regulated by a set of Activators that determine positional information. While we now know that the Hox Selector genes encode transcriptional regulators and we have a relatively good understanding, at least in Drosophila, of the molecular hierarchy that specifies positional information along the body axis and directs expression of Hox genes to each segment (Lawrence, 1992), our understanding of how Hox proteins function is

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limited by the fact that very few bona fide target Realizator genes have been identified to date. Prior to the application of genomic approaches, there were approximately 20 candidate Hox target genes identified in Drosophila using a variety of strategies (Table 3.1). Encouragingly, even this small set of targets does provide some clues about Hox functions, though perhaps not directly fitting the GarciaBellido model, since the majority of identified targets encode transcription factors or components of cell signaling pathways (Graba et al., 1997; Pradel and White, 1998) and not the cytodifferentiation genes envisaged as Realizators. Among the transcription factor genes are nervy, unplugged (unp), oddpaired (opa), spalt major (salm), and teashirt (tsh): cell signaling molecules include scabrous (sca), decapentaplegic (dpp), wingless (wg), and other members of the Wnt gene family. This repertoire suggests that at least some aspects of Hox function are to act at the top levels of regulatory hierarchies, controlling the expression of effectors that subsequently modulate many downstream targets and biological processes. However, it should be borne in mind that, in general, this set of studies is somewhat biased since individual research groups tended to focus their efforts on the analysis of regulatory molecules that subsequently become identified as Hox targets. It is less common for research groups to work on the more “mundane” housekeeping functions that would represent the Realizators: sets of genes encoding proteins that specify cellular level characteristics central to morphogenetic processes, such as cell size and shape, cell proliferation, cell–cell communication, cell adhesion, cell differentiation, and cell death (Garcia-Bellido, 1975; Lohmann, 2006; Pradel and White, 1998). Despite this research bias, some Realizators have been identified (Akam, 1998; Weatherbee et al., 1998), including the apoptosis-activating protein reaper (rpr) (Lohmann et al., 2002); centrosomin (cnn), a protein important for controlling the assembly or stabilization of microtubules that is required for proper cell division and proliferation (Li and Kaufman, 1996); connectin (con), a cell adhesion protein that has been shown to play a role in the formation of neuromuscular connections (Gould and White, 1992), and b3-tubulin, which has been shown to be involved in changes in cellular morphology (Hinz et al., 1992). Thus, a picture emerged where Hox proteins act directly at many levels of a regulatory hierarchy, a conclusion supported by the work of Carroll and colleagues (Weatherbee et al., 1998) examining genes involved in determining the morphological difference between the homologous structures of wing and haltere. They found that Ubx represses several target genes at multiple levels of the regulatory hierarchy specifying wing development, including the gene encoding the Wg signaling molecule and a subset of Wg-activated targets that are downstream in the pathway, including vestigial (vg), achaete-scute, spalt-related, and serum response factor (SRF). A more recent analysis by Castelli-Gair and colleagues begins to shed light on the complexity of Hox function, by giving us the first glimpse of how the gene regulatory network linking the Hox gene Abd-B to a set of Realizator genes controls a

Table 3.1. A List of Known Direct Hox Target Genes Target gene scabrous (sca) La-related protein spalt major (salm) Distal-less (Dll) wingless (wg) teashirt (tsh) connectin (con) b-3-tubulin Deformed (Dfd) Wnt-4 forkhead Knot serpent (srp) reaper (rpr) CG13222 1.28 Dpp Antp CG11339 labial (lab) centrosomin (cnn) pterous (ap) Transcript 48 (T48)

Hox regulators

Target class

Evidence for direct Hox regulation

Reference

Ubx Scr, Ubx Ubx Ubx, Abd-A Abd-A Antp, Ubx Ubx, Abd-A Ubx Dfd Ubx Scr Ubx Ubx Dfd Ubx Dfd Ubx, Abd-A Antp, Ubx, Abd-A Lab Lab Antp Antp Ubx

Signaling molecule Realizator Transcription factor Transcription factor Signaling molecule Transcription factor Realizator Realizator Transcription factor Signaling molecule Transcription factor Transcription factor Transcription factor Realizator Realizator Unknown Signaling molecule Transcription factor Realizator Transcription factor Realizator Transcription factor Unknown

ChIP using Ubx ChIP using Ubx Enhancer with mutated Hox sites tested in larvae Enhancer with mutated Hox sites tested in embryos Enhancer with mutated Hox sites tested in embryos Enhancer with mutated Hox sites tested in embryos ChIP using Ubx Enhancer with mutated Hox sites tested in embryos Enhancer with mutated Hox sites tested in embryos ChIP using Ubx Enhancer with mutated Hox sites tested in embryos Enhancer with mutated Hox sites tested in embryos One-hybrid assay using Ubx Enhancer with mutated Hox sites tested in embryos Enhancer with mutated Hox sites tested in larvae Enhancer with mutated Hox sites tested in embryos Bicoid site swap (K50) using Ubx and Abd-A Enhancer with mutated Hox sites tested in embryos Enhancer with mutated Hox sites tested in embryos Enhancer with mutated Hox sites tested in embryos ChIP using Ubx Bicoid site swap (K50) using Antp ChIP using Ubx

Graba et al. (1992) Chauvet et al. (2000) Galant et al. (2002) Vachon et al. (1992) Grienenberger et al. (2003) McCormick et al. (1995) Gould and White (1992) Hinz et al. (1992) Zeng et al. (1994) Graba et al. (1995) Ryoo and Mann (1999) Hersh and Carroll (2005) Mastick et al. (1995) Lohmann et al. (2002) Hersh et al. (2007) Pederson et al. (2000) Capovilla et al. (1994) Appel and Sakonju (1993) Ebner et al. (2005) Grieder et al. (1997) Heuer et al. (1995) Capovilla et al. (2001) Strutt and White (1994)

Their functions, Hox regulation, target classes, and references are also given.

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specific aspect of morphogenesis, in this case, the formation of the posterior spiracle (Lovegrove et al., 2006). Abd-B is specifically expressed in the posterior spiracle and is required for its formation. Abd-B activates the expression of genes encoding four intermediate regulators: the transcription factors spalt major (salm), cut (ct), empty spiracles (ems), and the JAK/STAT signaling pathway ligand outstretched (os): these transcription factors and signaling molecules subsequently activate different sets of Realizator genes. Among the Realizators regulated in this way are the cell polarity protein Crumbs (Crb), cytoskeleton proteins, such as the RhoGAP88C, Gef64C, and Rho GTPases, and cell–cell adhesion proteins including E-Cadherin (E-Cad), Cad86c, and Cad74a. Importantly, it is still unclear whether these Realizators are also directly controlled by Abd-B in a feedforward loop regulatory motif. In this respect, it is interesting to note that ectopic expression of a set of four primary targets genes (upd, ems, ct, and grn) in the absence of Abd-B leads to the induction of, albeit abnormal, spiracle-like structures. This suggests that, at least for some aspects of spiracle development, direct Hox input into Realizators may not be required, though we emphasize that spiracles are far from normal. Further insights into how cytodifferentiation functions of Hox Realizators control morphogenetic processes come from an analysis of the well-studied Hox target gene reaper (rpr). The rpr gene encodes a central regulator of programmed cell death or apoptosis, and it has many roles during fly development. In the developing head, rpr has been shown to play an important role in maintaining the boundary between the maxillary and mandibular segments of the embryo (Lohmann et al., 2002). Dfd is active in the whole maxillary segment and is required for the activation of rpr expression. In Dfd mutants, the boundary between maxillary and mandibular segments is lost but this can be restored by supplying rpr in the maxillary segment, suggesting that apoptosis induced by rpr is required and sufficient to maintain the boundary between the segments. Taken together, these studies suggest that Hox proteins can act as master regulators and micromanagers to manipulate target genes at multiple levels of the regulatory hierarchy controlling a developmental process (Akam, 1998). They also highlight how important it is that we expand our catalogue of Hox targets and relate these with a view of the fly gene regulatory network.

IV. EARLY EXPERIMENTS TO IDENTIFY HOX TARGET GENES Prior to the genomic era, Hox target genes were initially identified from enhancer trap expression patterns. In this approach, a transposon (most frequently a P element) carrying a reporter gene hooked up to a minimal promoter is randomly integrated into the fly genome. If the transposon inserts near an endogenous enhancer element, the reporter gene may be expressed in the pattern dictated by this regulatory element. Over the years, a large number of enhancer trap lines have been generated, and among these, some were candidates for identifying

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potential Hox target genes on the basis of their segmentally modulated expression patterns (O’Kane and Gehring, 1987). Target genes found by this in vivo strategy include decapentaplegic (dpp), encoding a fly TFG-b signaling molecule, and Distal-less (Dll), a transcription factor involved in appendage development. Although the enhancer trapping approach is powerful, it has some limitations: first, it does not tell us whether targets are direct or indirect. Second, there are biases in the insertion site preference, with P elements most commonly integrating close to promoters that may miss many enhancers (Bier et al., 1989). Apart from enhancer trapping, other large-scale methods have been used to screen for Hox targets. A one-hybrid approach in the yeast Saccharomyces cerevisiae assayed fragments of the Drosophila genome for Ubx-regulatable activity (Mastick et al., 1995). Six fly genomic fragments conferring Ubx-responsive reporter activation identified genes expressed in a Hox-dependent fashion in the Drosophila embryo. Prior to the development of microarray technology, differential cDNA screening and subtractive hybridization were widely used comprehensive methods to compare biological samples for identifying differentially expressed genes. A subtractive hybridization screen comparing wild-type embryos with those ubiquitously expressing Ubx identified several Ubx targets (Feinstein et al., 1995). However, as with all gene expression-based assays, this approach cannot readily distinguish between direct Hox targets and secondary events caused by cellular responses to gain of Hox function. Finally, one of the first applications of in vivo Chromatin immunoprecipitation (ChIP), in which DNA–protein complexes were immunopurified from native embryo chromatin and the enriched DNA subsequently cloned, isolated direct Hox targets in the fly genome (Gould and White, 1992). This landmark study successfully identified several Ubx target genes including Transcript 48 (T48), connectin (con), and scabrous (sca) (Gould and White, 1992; Graba et al., 1992; Strutt and White, 1994). Of the four “pregenomic” methods, the ChIP approach is potentially the most powerful since it identifies in vivo Hox bound target regions in the endogenous genomic environment. Taken together, the use of increasingly sophisticated molecular biology techniques slowly increased the repertoire of Hox targets in the fly genome but still left a considerable gap in our understanding.

V. GENOMIC APPROACHES TO IDENTIFYING HOX TARGET GENES The emergence of high-throughput technologies such as DNA microarrays, and more recently second-generation sequencing, offered the prospect of identifying Hox target genes at a whole genome scale. Since the turn of the century, a variety of genome-wide studies, principally in fly and mouse, have been published and are summarized in Table 3.2. While such technologies provide potentially

Table 3.2. Identification of Hox Target Genes Using a Variety of Large Scale Genomic Approaches Hox genes

Organism

Microarray expression profiling Ubx Drosophila Ubx Drosophila Ubx Drosophila Dfd, Ubx, Abd-A, AbdDrosophila B, Scr, and Antp Lab Drosophila Hoxa1 Mouse Hoxa13 Mouse Hoxa11 Mouse Hoxd10 Mouse Hoxa1 Mouse Hoxc8 Mouse Hoxd cluster gene Mouse Hoxa13 Mouse Hoxa11 and Hoxd11 Mouse Hoxb1a Hoxc13 Hoxb1b Hoxa10 ChIP Ubx Ubx Hoxd13 Hoxa13 and Hoxd13 Computational Lab Combined Dfd

Zebrafish Mice Zebrafish Human Drosophila Drosophila Human Mouse

Tissue

Developmental stage

Reference

Haltere and wing disc Haltere and wing disc Haltere and wing disc Whole embryo

Third instar larva Third instar larva Third instar larva, prepupa, and pupa Embryonic stages 11 and 12

Mohit et al. (2006) Hersh et al. (2007) Pavlopoulos and Akam (2011) Hueber et al. (2007)

Whole embryo Teratocarcinoma stem cell line Cervix and uterus tissue Kidney tissue Spinal cord tissue Embryonic blastocysts (cell culture) Embryonic fibroblasts (cell culture) Mouse tissue of limbs and genitalia Embryonic fibroblasts (cell culture) Whole embryonic kidneys and urogenital tissue Whole embryo Skin Embryo Cell culture—umbilical cord cells

Embryonic stages 10–17

Leemans et al. (2001) Shen et al. (2000) Zhao and Potter (2001) Valerius et al. (2002) Hedlund et al. (2004) Martinez-Ceballos et al. (2005) Lei et al. (2005) Cobb and Duboule (2005) Williams et al. (2005) Schwab et al. (2006)

Haltere Haltere Bone chondroplast cell line

Drosophila Drosophila

4.5 week old Embryonic stage 18.5 Embryonic stage 12.5

Embryonic stage 12.5 Embryonic stages 11.5, 12.5, 13.5, 16.5 þ adult 19–20 h postfertilization

Third instar larva Third instar larva

Rohrschneider et al. (2007) Potter et al. (2011) van den Akker et al. (2010) Ferrell et al. (2005) Choo et al. (2011) Slattery et al. (2011) Salsi et al. (2008) McCabe and Innis (2005) Ebner et al. (2005)

Whole embryo

Table was modified from Hueber and Lohmann (2008).

Hueber et al. (2007)

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comprehensive genome coverage, limitations in the underlying biology can limit their success. Hox mutations, or global overexpression of Hox genes, have pleiotropic phenotypes, and individual Hox proteins are likely to regulate different sets of targets, or have quantitatively different effects on a target gene, in different tissues. Thus, analyses relying on whole animals, or even isolated tissues, can only provide a composite view of Hox targets. Similarly, analysis of Hox targets in tissue culture systems is likely to be limited since such cells are generally terminally differentiated and lack the normal patterning cues received by cells in vivo. As we shall see, even with the application of genome-wide approaches, we are still some way from a comprehensive understanding of the target repertoire of even a single Hox protein in an individual cell type.

VI. MICROARRAY EXPRESSION PROFILING After the release of the Drosophila genome sequence and the emergence of microarray technology, several research groups reported results from microarray expression profiling studies aimed at the identification of Hox downstream genes on a genome-wide scale (Ferrell et al., 2005; Hedlund et al., 2004; Hersh et al., 2007; Hueber et al., 2007; Leemans et al., 2001; Lei et al., 2005; MartinezCeballos et al., 2005; Mohit et al., 2006; Pavlopoulos and Akam, 2011; Rohrschneider et al., 2007; Schwab et al., 2006; Shen et al., 2000; Valerius et al., 2002; Williams et al., 2005; Zhao and Potter, 2001). In general, the approach is to identify genes that show differential expression in response to alterations in Hox gene expression. In Drosophila, screens for Hox-responsive target genes have been performed with whole embryos and with specific larval imaginal discs. In one of the first fly microarray studies, Leemans et al. (2001) used a custom Affymetrix array containing probes against some 1500 Drosophila genes to screen for transcripts differentially expressed when Labial was ubiquitously overexpressed in the embryo via a heat-inducible promoter. Around 6% of the genes on the array responded to Labial expression with half upregulated and half downregulated. Of particular interest, the experiment identified genes encoding proteins with a range of functional annotations, from signaling pathway components and transcript factors through to structural components of the cell, cell cycle and apoptotic proteins, and other Realizator class genes. Of course, the experimental design does not allow the differentiation of direct and indirect targets; nevertheless, the experiment does reinforce the idea that Hox proteins are active at many levels of the regulatory network.

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A more comprehensive study by Hueber and colleagues searched for genes that are responsive to six different Drosophila Hox proteins (Dfd, Ubx, Abd-A, Abd-B, Scr, and Antp) by comparing the transcriptomes of embryos misexpressing individual Hox genes with control embryos misexpressing a LacZ gene. The study examined two stages of embryonic development, 11 and 12, reflecting a developmental period when Hox proteins are active in regulating cellular differentiation in all germ layers of the embryo (Hueber et al., 2007). The analysis identified approximately 1500 potential Hox target genes, with verification of a randomly selected subset indicating that many of these genes are likely to be under Hox control. Interestingly, many of the target genes were affected by multiple Hox genes, suggesting that Hox-regulated targets are likely to be deployed in multiple segments and contribute to a variety of morphological outcomes. They also found that many of the Hox targets encode Realizator functions, annotated as being involved in basic morphogenetic functions such as cell proliferation, cell–cell communication, adhesion, cell migration, and apoptosis, strengthening the view that Hox execute functions through batteries of Realizators during development. It should be noted that there are some limitations with both of these studies. First, the experiments utilize Hox misexpression throughout the embryo and thus are not likely to accurately reflect gene regulation in native Hox expression domains. Second, ectopically expressing Hox genes throughout the embryo is likely to lead to complications since there are extensive cross-regulatory interactions between Hox genes (Capovilla and Botas, 1998; Miller et al., 2001) as well as dose-dependent Hox responses (Pavlopoulos and Akam, 2007; Tour et al., 2005). However, for the first time, these studies provide not only a comprehensive insight into the functions of Hox targets in the development of the Drosophila embryo but also a preliminary gene lists for further analysis. Aside from the embryo, several groups sought to identify Ubx-responsive target genes in the haltere imaginal disc (Hersh et al., 2007; Mohit et al., 2006; Pavlopoulos and Akam, 2011). In these studies, a variety of strategies have been utilized, including comparisons between wild-type wing and haltere discs or comparisons between wild-type wing discs and wing discs misexpressing Ubx. The wing and haltere are homologous structures (Fig. 3.3), and it has long been known that Ubx is necessary and sufficient to specify haltere versus wing fate (Casares et al., 1996; Roch and Akam, 2000). Since Ubx is solely responsible for the specification of the haltere, any genes that show differential expression between the two dorsal discs could, in principal, be regulated by Ubx. The first study compared wild-type wing and haltere discs, as well as wildtype and mutant wing discs (UbxCbx-Hm, a allele that misexpresses Ubx in the posterior compartment of the wing disc, and vg-GAL4/UAS-Ubx, a situation where Ubx is also misexpressed in the wing pouch) (Mohit et al., 2006), identifying around 500 genes as potential Ubx targets. The second study also

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Wing

A Pouch

Haltere

Capitellum

Hinge Hinge Notum Notum

Ubx Hth

B

Figure 3.3. The wing and haltere. (A) Schematic of the third larval instar wing and haltere imaginal discs with an indication of the adult structures deriving from each region. The discs are shaded to denote the extent of Homothorax expression (excluded from the pouch and capitellum regions), and the stippling indicates Ubx expression in the haltere but not in the wing disc. (B) The adult wing and haltere are radically different structures in terms of size and morphology.

compared wild-type haltere and wing discs, as well as wild-type and UbxCbx1 wing discs (Hersh et al., 2007), and identified approximately 200 potential targets. While these studies were undoubtedly useful and certainly generated a new set of validated Hox targets, it is important to realize that there are again some limitations. First, there is relatively little overlap between the gene lists generated by the two studies, suggesting that they are far from comprehensive. Second, there is the possibility that some expression changes are allele specific and reflect the peculiarities of the different genetic backgrounds employed. Third, gene expression profiling experiments, even using restricted tissues, will not detect genes that change their expression pattern but not their overall steady-state levels. Fourth, it is likely that genes with relatively small expression changes will be missed by the arbitrary thresholds applied in microarray analysis. Fifth, except for a few validated targets, it is not possible to differentiate between direct and indirect targets.

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Accepting these limitations, the studies do provide new insights into Hox function: the Mohit et al. study concluded that an important aspect of Ubx activity in directing haltere development is the downregulation of A/P and D/V signaling pathways. In contrast, Hersh and colleagues chose to highlight the fact that activation of haltere-specific functions by Ubx is important for haltere development and that repression of “wing genes” is unlikely to be sufficient to account for Ubx control of haltere morphogenesis. We emphasize that these conclusions are not mutually exclusive, and it is likely that Hox regulation contributes to both of these processes in defining a haltere. A more recent, and by far the most comprehensive gene expression-based study of Ubx function to date, searched for Ubx target genes in the haltere at three different stages of imaginal disc development: late larval, prepupal, and pupal (Pavlopoulos and Akam, 2011). In this study, the authors ectopically expressed Ubx only in the wing pouch and compared these discs with control wing discs expressing eGFP. To precisely control the ectopic expression of Ubx in the wing pouch, the GAL4/UAS system in combination with a temperature-sensitive GAL80 repressor was used. With this system, Ubx is not ectopically expressed at 19  C due to the repression of GAL4-mediated induction by GAL80: at the permissive temperature of 29  C, GAL80 is inactive and Ubx is expressed. At each developmental stage, a primary analysis identified genes with altered expression comparing Ubx-expressing and eGFP-expressing discs at the permissive temperature but that did not significantly change in comparisons between samples raised at the restrictive temperature. Across all of the time points, a total of 872 Ubxresponsive genes were identified: an important insight from this study is that the sets of Hox-responsive target genes identified at each stage of development are largely nonoverlapping, indicating that Hox functions are likely to be highly integrated with other signals, for example, hormonal responses, during development. The Ubx-responsive target genes encode proteins annotated as being involved in a wide range of biological processes, including development, regulation of growth, transcription factor activity, apoptosis, and cell differentiation (Pavlopoulos and Akam, 2011). This accords well with the findings from the embryo Hox misexpression study and emphasizes the broad nature of Hox targets. A second revealing insight from the analysis is an indication that Ubx regulates many target genes in a subtle way with the majority of differentially expressed genes showing a mean change of around 1.5-fold, confirmed for a subset of genes by qRT-PCR assays. Since most genomic studies employ some statistical threshold to select differentially expressed genes (in this case a 5% false discovery rate (FDR)), it is likely that many genes with even smaller Ubxdependent expression changes were not selected by the criteria used in the study. Taken together, these three broadly comparable imaginal disc gene expression studies identified a set of potential Ubx target genes that may contribute to the gene network specifying haltere development. While the lack of

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substantive overlap in terms of the genes uncovered by each study might suggest limitations to microarray-based technology, it is more likely a reflection of the different experimental designs employed. We can take from these studies that in the haltere there are hundreds of genes, ranging from high-level regulators to cytodifferentiation genes, likely to be under Hox control. Importantly, very few of the identified genes show dramatic expression differences between wing and haltere; rather, most exhibit relatively small changes, suggesting that Hox proteins act as subtle expression modulators at the level of the individual gene. While the fly is experimentally tractable and, compared to vertebrates, has a comparatively simple Hox repertoire, there is considerable interest in discovering Hox targets in mammals. As with Drosophila, several expression profiling studies have been used in vertebrates, usually aimed at identifying targets of a single Hox protein (Cobb and Duboule, 2005; Valerius et al., 2002; Williams et al., 2005). Some of the vertebrate work highlights the problems of using cell lines for analysis. For example, overexpression of Hoxc8 in mouse fibroblast cells identified 34 genes with at least twofold change compared to control cell lines (Lei et al., 2005). While most of these encode proteins involved in cell differentiation, metabolism, apoptosis, and proliferation, compared to the fly studies, the target list is small. It is possible that the fibroblasts lack necessary Hoxc8 cofactors or it may be that since fibroblasts are terminally differentiated, much of the gene network is no longer Hox responsive. Experiments in vertebrates that are more directly aimed at in vivo Hox biology reveal a similar picture as those emerging from the fly studies. In the tractable zebrafish system, morpholino-mediated knockdown of Hoxb1a identified around 450 genes with Hox-dependent expression in an analysis of rhombomere 4, a structure that requires Hoxb1a for its identity (Rohrschneider et al., 2007). The targets include the usual suspects, high-level transcriptional regulators, as well as cytodifferentiation genes. A second study highlights how important context is when looking at Hox function: here, Hoxb1b, a paralog of Hoxb1a, was overexpressed in the early zebrafish embryo and gene expression profiles generated using the same microarray platform as the rhombomere 4 study. Approximately 200 genes changed expression in comparison to wild-type controls; however, there is no overlap between the early embryo and rhombomere data (van den Akker et al., 2010). This may be indicative of highly tissue-specific Hox function, genuine differences between Hoxb1a and Hoxb1b or simply reflect the difference between downregulation and upregulation. In addition, the early embryo study also examined the consequences of overexpressing Xenopus Hoxd1. Surprisingly, the frog gene elicited a greater number of gene expression changes ( 350), although there was a gratifying correspondence between the targets affected by the fish and frog Hox proteins. The most revealing in vivo experiments with mouse and human have focused on specific tissues. An interesting analysis of hair follicle development identified around 180 target genes using the skin from Hoxc13 mutant mice

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(Potter et al., 2011). Many of these target genes encode cytoskeletal components as well as keratin and keratin-associated proteins, suggesting that Hox proteins are likely to be involved throughout the differentiation of a particular tissue, even up to the last stages of differentiation. This view of Hox function is strengthened by an analysis of the role of HOXA10 in human uterine adaptation or decidualization. Human endometrial cells undergo hormone-induced changes to prepare the uterine wall for implantation: in a cell culture system, stimulated endometrial cells were transfected with siRNA against HOXA10 and compared to wild-type cells. Approaching 500 gene expression changes are identified, primarily affecting genes encoding Realizators associated with cell cycle, cell death, growth, proliferation, and cellular movement. Thus, as with the mouse epithelium, a fate change in a relatively differentiated cell, going from a stromal cell to a cellular matrix, appears to be under the control of a Hox protein. Taken together, these studies demonstrate that gene expression profiling screening can successfully uncover potential Hox target genes at a whole genome scale. The finding that many potential targets show only modest Hox-dependent changes in gene expression suggests that a more sensitive RNAseq-based approach will uncover even more targets and is likely to reveal that Hox effects on gene networks are pervasive. Another important finding is that Hox proteins appear to regulate different sets of target genes, even within the same tissue, at different stages of development. Thus, as a cell begins its differentiation program, one can imagine Hox-controlling networks regulating growth, proliferation, and death, whereas once the cell is reaching the terminal stages of development, sets of Realizators encoding structural aspects of the cell are the more likely targets. This view suggests that Hox activity in a cell is likely to be dynamic and forces us to think about analyzing Hox function in purified cell populations in the future. The major drawback of the expression profiling approach is that changes in expression do not necessarily equate with direct Hox regulation. Even though some of the identified expression changes are likely to be indirect, such indirect effects are nevertheless useful since they reflect the outcome of Hox activity on a gene network and identify potential targets of Hox-controlled secondary regulators. It does, however, remain highly desirable that we identify the full gamut of direct Hox targets.

VII. CHIP APPROACHES With the introduction of high-throughput technologies such as ChIP-CHIP, ChIPPET, and ChIP-Seq, it is possible to identify the direct targets of a transcription factor at a genome-wide scale (Euskirchen et al., 2007; Johnson et al., 2007; Kwong et al., 2008; Li et al., 2008; Robertson et al., 2007; Wei et al., 2006). In this approach, DNA fragments bound by a transcription factor are enriched, generally by

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cross-linking chromatin immunopurification, and their genomic locations identified by hybridization to genomic tiling microarrays or by high-throughput sequencing technologies. Initially developed in yeast and soon adapted to metazoans, ChIP approaches have begun to be applied to the identification of Hox target genes (Choo et al., 2011; Salsi et al., 2008; Slattery et al., 2011). In mouse, the direct targets of Hoxd13 in a bone chondroplast cell line have been mapped by ChIP-CHIP analysis with human CpG island (promoter) arrays. Approximately 250 genes were identified as having significant Hoxd13 binding; as would be expected from our previous discussion, these encode both high-level regulators and cytodifferentiation genes. A few of the targets were shown to be associated with limb development and directly Hox responsive; however, there was no systematic attempt to correlate Hox binding with gene expression (Salsi et al., 2008). In Drosophila, there have been two basic ChIP approaches for directly identifying Hox targets. On the one hand, experiments by Choo et al. (2011) and from the large-scale modENCODE project (Negre et al., 2011) report Ubx binding profiles from embryo chromatin. While these studies can reveal Ubx binding potential, they are limited since they sample cells from throughout the embryo and at different developmental stages. Consequently, it is expected that only a subset of in vivo targets will be identified, generally those bound in multiple cell types over a relatively large window of development. Those target genes under Hox control in a few cells or for a small window of development are likely to be missed due to sensitivity issues. To address these concerns, two groups mapped Hox binding in specific imaginal discs since these are far more homogeneous tissues than the complex mixture of cell types present in the embryo (Choo et al., 2011; Slattery et al., 2011). Both groups independently generated Ubx binding profiles from isolated haltere discs as well as complementary Homothorax (Hth) binding profiles. Hth is a Meis-class homeodomain protein believed to act as a Hox cofactor in some circumstances and has been shown to be required for aspects of Ubx function in the haltere disc (Galant et al., 2002). In addition, Slattery et al. mapped Ubx and Hth in the third thoracic leg disc while Choo et al. mapped Hth binding in the wing disc. Each study used a slightly different approach for the ChIP assays: Slattery et al. used specific antibodies against each of the proteins while Choo et al. took advantage of YFP-tagged protein trap insertions in the Ubx and Hth genes generated by the Cambridge protein trap project (FlyProt; Rees et al., 2011; Ryder et al., 2009). Overall, the binding profiles of Ubx and Hth in haltere discs generated by both groups are reassuringly similar (Fig. 3.4A), although microarray probe-level correlations are relatively weak. It is interesting look at the conclusions about Hox activity drawn by both groups since this highlights how genomic data are still very much a matter of interpretation: importantly, raw data are available from data repositories and can be reanalyzed or interpreted by those interested in drawing their own conclusions about Ubx or Hth binding.

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A Ubx Haltere Choo et al.

Ubx Haltere Slattery et al.

Hth Haltere Choo et al.

Hth Haltere Slattery et al.

Hth Wing Choo et al. simj

10,650,000

tna 10,700,000

10,750,000

10,800,000

10,850,000

B

1101

1041

907

1078 177

46 185

Larva (20%)

106

69

349

281

Prepupa (23%)

Pupa (20%)

702

All (20%)

Larva (46) 24 7

6 9

77

Prepupa (106)

13

41

Pupa (69)

Figure 3.4. ChIP-CHIP studies. (A) A comparison of ChIP binding profiles from two independent studies (Choo et al., 2011; Slattery et al., 2011). A representative region of approximately 250 kb from chromosome 3L with Ubx and Hth in the haltere disc and Hth in the wing disc. The plots represent the normalized ratio of enriched to control chromatin. While not identical, the Ubx and Hth profiles from each study are very similar; note also the

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The Choo et al. study chose to focus on a gene-based interpretation; they identified 1147 genes directly bound by Ubx at a relatively stringent 1% FDR. In the haltere, Ubx binds 20% of the 1488 Ubx-responsive genes compiled from the traditional and microarray-based expression profiling studies described above. This represents a minimal set of 294 Ubx-bound-and -responsive genes. It is likely, due to thresholding of the ChIP and gene expression data and the fact that the largest gene expression study was restricted to the pouch region (Pavlopoulos and Akam, 2011), that many of the remaining 850 Ubx-bound genes are also Ubx regulated. Indeed, comparing the functional annotations of the 249-bound-and-responsive genes or the entire set of 1147 Ubx-bound genes reveals a very similar set of functional annotations, identifying genes implicated in transcription, signaling, and basic cytodifferentiation (Table 3.3). Mapping the Ubx-bound genes onto a recently developed Drosophila gene network (Costello et al., 2009) indicates that Ubx target genes are broadly distributed across all levels of the network (Fig. 3.5). Together, these observations provide strong support for the view that Ubx is involved in modulating a wide range of biological processes in directing haltere development. Direct comparisons between the gene expression data generated from different stages of haltere development (Pavlopoulos and Akam, 2011) highlight a potentially interesting facet of Hox function. As described above, the sets of Ubx-responsive genes identified in the imaginal disc gene expression studies are largely nonoverlapping between larval, prepupal, and pupal stages. However, the binding study (performed at the larval stage) detects Ubx binding at genes that only show Ubx responsiveness at later stages of development, suggesting that, at least in some circumstances, Ubx binding prefigures gene expression changes (Fig. 3.4B). In this scenario, we imagine Ubx bound at an enhancer waiting for additional regulatory inputs, for example, binding of co-regulators or the removal of repressors. The Slattery et al. study identified approximately 3400 Ubx-bound genes in the haltere at a slightly less stringent 5% FDR (in comparison Choo et al. found 2350 genes at 5% FDR). As before, the range of functional annotations is in accordance with expectations, identifying both high-level regulators and downstream Realizators. In this case, the authors emphasize a prominent

similarity of the Hth wing disc binding profile to both the Ubx and Hth haltere profiles. (B) Comparisons between the set of Ubx-bound genes from haltere chromatin (Choo et al., 2011) with Ubx-regulated genes identified with a microarray screen (Pavlopoulos and Akam, 2011). The top row represents the overlaps between the 1147 Ubx-bound gene set and Ubx-regulated genes identified at different developmental stages (larval, prepupal, pupal) and the combined gene expression set (far right). Underneath, the overlaps between the Ubx-bound-and-regulated genes identified at the three different stages, demonstrating that they are largely nonoverlapping.

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Table 3.3. Gene Ontology and Other Function Enrichments Associated with Ubx-Bound-andValidated Genes or the Complete Set of Ubx-Bound Genes at 1% FDR Choo et al. (2011) 294 Ubx-bound-and-validated genes Genes

p value

All Ubx-bound genes

Genes

p value

Biological process Developmental processes Neurogenesis Ectoderm development mRNA transcription mRNA transcription regulation Cell communication Signal transduction Cell adhesion Cell adhesion-mediated signaling Nucleoside and nucleotide metabolism Cell motility

69 29 29 49 41 25 52 18 13 62 13

9.80  10 22 4.70  10 11 1.20  10 10 1.10  10 9 2.60  10 9 8.70  10 9 4.00  10 8 7.10  10 7 8.40  10 7 3.30  10 5 7.60  10 4

176 67 70 144 116 56 154 40 23 198 35

1.20  10 30 9.80  10 15 2.30  10 15 2.70  10 18 7.50  10 17 2.10  10 10 1.90  10 13 5.20  10 8 3.90  10 6 5.30  10 9 1.80  10 7

Pathways Cadherin signaling Wnt signaling Presenilin pathway

8 13 8

8.10  10 4 5.70  10 4 3.50  10 3

20 34 19

1.40  10 7 2.70  10 7 2.00  10 5

overrepresentation of transcriptional regulators in the Ubx target list, indicative of Ubx control at the highest level of the regulatory network. Of particular interest in this study is the identification of substantial number of tissue-specific Ubx binding peaks. In the leg imaginal disc, 779 Ubx-bound genes are identified, and 11% of these are not found in the list of 3400 haltere-bound genes; similarly, most of the haltere targets are not found in the leg. The disparity in the number of identified targets between haltere and leg may reflect the fact that haltere and wing are radically different tissues while the difference between different legs is far less pronounced, and thus, we may not expect many segment-specific (i.e., Ubx-dependent) expression changes. Both groups also mapped the binding of the Hox cofactor Hth in haltere discs; again both groups chose to focus on different aspects of the data. Choo et al. highlight a striking similarity in Ubx and Hth binding profiles in the haltere, with most (97%) Ubx-bound genes also associated with Hth binding (Fig. 3.4A). They also report an equally strong correspondence between Hth binding profiles from haltere and wing discs (80% of Hth-bound genes in the haltere also bind Hth in the wing). Since Ubx is not active in the wing disc and, in the case of the haltere, Hth is absent from the central region

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A

B

Figure 3.5. Ubx-bound genes in the gene network. (A) A Cytoscape representation showing that Ubx-bound genes identified in a ChIP-CHIP study (blue; Choo et al., 2011) are distributed throughout the 20K Drosophila gene network (Costello et al., 2009). Of the 111 clusters identified in the network, 39% contain Ubx-bound genes. (B) The set of Ubx-bound genes with selected network subclusters colored to highlight Ubx involvement in many processes. Genes bound by Ubx and showing expression changes are indicated as diamonds and the remaining genes as circles (Choo et al., 2011).

that gives rise to the capitellum, these authors suggest that the binding of both Ubx and Hth is a reflection of chromatin accessibility. In this view, Hox binding is relatively promiscuous in the genome, attracted to any regions

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with open chromatin, and it is then subsequent interactions with coactivators or repressors that define Hox responsiveness. This strong influence of chromatin accessibility has also been proposed by the Berkeley Drosophila Transcriptional Network Project in their analysis of the binding of over 20 transcription factors during early embryonic development (Kaplan et al., 2011; Li et al., 2008; MacArthur et al., 2009). This raises the issue of how specific regions of the genome are opened to facilitate Hox binding, and it is clear that the open chromatin hypothesis needs further evaluation. Interestingly, a very recent report from the Berkeley group shows a strong association between the genome-wide binding patterns of many different transcription factors and chromatin accessibility as measured by nuclease sensitivity, providing support for the open chromatin model (Li et al., 2011). Slattery et al. highlight the differences between Ubx and Hth binding profiles, identifying a substantial number of tissue- and factor-specific binding peaks across the genome. They support the significance of these observations by identifying tissue- and factor-specific sequence motifs enriched in particular classes of binding peak, that is, Ubx haltere specific, Hth leg specific, etc. In this view, Hox specificity derives from interactions between Hox proteins and different cofactors: the sequence analysis identifies several enriched motifs that suggest candidate cofactors. Reconciling these views, it is likely that Hox binding is specified by a combination of open chromatin and cofactor interactions. Thus, even though each study highlights different facets of the binding profiles, they provide rich data sets that are a foundation for a continued analysis of Hox function. One interesting observation relating to both Ubx and Hth binding profiles highlighted by both groups is that some genes are associated with multiple distinct binding peaks whereas others have a single binding peak. While the reason for this difference is currently unclear, Slattery et al. suggest that genes with multiple Ubx peaks are more likely to encode developmental regulators while single peak genes encode metabolism or cell cycle-related genes. Taken together, these studies highlight how the ChIP approach can provide new insights into the identity of in vivo Hox targets at a genome-wide scale. However, without additional data, it can be difficult to differentiate between functional and nonfunctional binding. This is particularly relevant since it is becoming increasingly apparent from the modENCODE genomewide studies in flies and worms that a substantial fraction of transcription factor binding detected in ChIP assays may be nonfunctional (Gerstein et al., 2010; Negre et al., 2011; Niu et al., 2010; Roy et al., 2010). To help overcome this limitation, binding and gene expression data from the same tissue or cell type need to be compared. Even with such data, it should be borne in mind that transcriptional effects may be subtle or, as seen with Ubx in the haltere, Hox binding can substantially prefigure expression changes.

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VIII. COMPUTATIONAL APPROACHES An alternative way of identifying potential Hox target genes is to use computational methods to search the genome, or subsets of the genome, for sequence matches to transcription factor binding sites (see Berman et al., 2002; Kel et al., 2006; Rajewsky et al., 2002 for examples of this approach in Drosophila). Clearly, to begin such an analysis, one must first obtain a consensus binding sequence for the factor in question. In general, this information is compiled from binding sequences identified in DNA footprinting, SELEX, or EMSAs. While undoubtedly successful with some transcription factors, the approach may be limited in the case of Hox proteins due to their apparently low degree of binding specificity (Beachy et al., 1988; Catron et al., 1993; Mann, 1995; Noyes et al., 2008; Pellerin et al., 1994). Despite this limitation, some studies have been performed. In some circumstances, Hox proteins have been shown to form a trimeric complex with the Tale/Meis-class homeodomain proteins Extradenticle and Homothorax to cooperatively bind at target sites. It proposed that the cooperation between Hox and these (or other) cofactors might enhance binding specificity and allow more specific in vivo target selection (Ferretti et al., 2000; Gebelein et al., 2002, 2004; Jacobs et al., 1999; Merabet et al., 2007; Stultz et al., 2006). Based on this idea, Ebner and colleagues searched the Drosophila genome for matches to a consensus sequence derived for the Lab/Exd heterodimer (TGATGGAT(T/G)G) and selected those sites within 40 bp of a match to a consensus Hth binding sequence (CTGTCA) (Ebner et al., 2005). These relatively stringent criteria identified 30 genomic sites, with an analysis of the expression of genes neighboring the binding sites revealing two genes with lab-like patterns (lab itself and CG11339). We have seen that Hox genes may have subtle effects on widely expressed genes, so the remaining 28 genomic sites may not be false positives. Even so, the relatively low number of genes identified in this analysis suggests that searching the genome for binding sites may not be productive for Hox targets. We can imagine a number of reasons why so few targets were identified in this study: first, the criteria used may be too stringent, for example, the distance between the Hth and Lab/Exd sites may be more than 40 bp in vivo. Second, the Lab/Exd/Hth binding site might be more divergent in vivo than the sites used in the search. Third, the Lab/Exd/Hth complex may not be the most common mechanism employed by Lab to select target genes. Indeed, it is likely that Hox proteins collaborate with multiple cofactors in regulating target gene expression (Hueber and Lohmann, 2008; Walsh and Carroll, 2007). Thus, at present, it would appear that, in the case of Hox proteins, strictly computational approaches are not yet suitable for indentifying Hox targets at a genome-wide scale. Clearly, a major limitation is the relatively poor information content of a Hox monomer binding site, coupled with our limited understanding of the repertoire of cofactors used by Hox proteins.

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The ChIP data generated from the recent imaginal disc and embryo studies offer a source of genomic locations bound by Hox proteins that can be analyzed to better understand sequence motifs associated with Hox binding. The analyses by Choo et al. and Slattery et al. provide a good start for Ubx and Hth. Future computational studies, informed by the in vivo binding regions identified in ChIP, should help better define the enhancer anatomy associated with Hox binding and elucidate the relative orientation and spacing of Hox and cofactor binding sites. Such approaches have been successful in Drosophila for other transcription factors (Erives and Levine, 2004; Markstein et al., 2004). Finally, most of the motif finding and pattern searching algorithms in common use are far from perfect (Su et al., 2010; Tompa et al., 2005), and we expect that improvements in computational approaches, coupled with better underlying data on Hox binding sites, will facilitate more accurate genome-wide searching.

IX. PROSPECTS As we have seen, it is likely that the continued deployment of genomic technologies is likely to be critical in furthering our understanding of Hox function. In particular, genome-wide expression profiling and mapping of protein–DNA interactions will improve the catalogue of direct Hox target genes. We believe that substantial progress here requires particular attention to two key areas: tissue specificity and temporal dynamics. The lessons from the studies in Drosophila, using ChIP-based technology to map Hox binding sites in imaginal disc tissues, indicate that improved signal-to-noise ratios identify many more binding sites that using complex tissue sources such as whole embryos. Yet even here it is likely that we miss a considerable amount of subtlety since the imaginal discs contain cells responding to different signaling gradients and microenvironments. Thus, we need to develop more refined methods for purifying particular populations of cells from their in vivo locations. The use of fluorescence-activated cell sorting in combination with reporter-based marking of specific lineages is likely to become increasingly important in this respect (see Estrada et al., 2006 for an example of this approach in the Drosophila embryonic mesoderm). Alternatively, nucleic acid tagging approaches directed to specific cell populations may be employed (Miller et al., 2009), at least for the isolation of cell-type-specific transcripts. Even in model organisms with compact genomes, it is likely that sequencing-based assays will replace the use of microarray technologies for mapping; however, we still need to improve analytical methods (Aleksic and Russell, 2009; Ho et al., 2011). In particular, we need to move away from data thresholding approaches and focus more on the binding profiles, for example, by developing more probabilistic-based approaches to capturing binding profiles (e.g., Zhang et al., 2011). We also need to improve our understanding of

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chromatin architecture and how particular chromatin states are linked to transcription factor binding (Li et al., 2011; MacQuarrie et al., 2011). We need to do this not only in the linear dimension of the genome sequence but also in the three dimensions of the genome in the nucleus. Here, the use of chromatinconformation-capture type assays (3C, 5C, HiC, etc.; see Hakim et al., 2010; Osborne et al., 2011 for recent reviews of these technologies) will become increasingly important in understanding how enhancers and basal promoters interact and how the genome is organized into regulatory domains. It is likely that genome organization will play a critical role in how Hox proteins find targets in the genome and how they exert specific regulator inputs. Ultimately, we need to be able to map gene expression, Hox binding, and chromatin state in single cells. The prospects for expression profiling single purified cells are good (Nojima and Tougan, 2011; Tang et al., 2011) with methods already becoming established. However, single-cell ChIP has not been reported, and it may be that the development of lab-on-a-chip type microfluidics will be needed here (Le Gac and van den Berg, 2010; Schmid et al., 2010). The single-cell studies will be interesting not only for the precise identification of target genes but also in helping characterize the contribution of stochasticity to the determination of cell fate, an area of increasing interest in metazoan development (see Oates, 2011 for a summary of recent interests in stochasticity). The ability to monitor single cells, or at least relatively homogeneous populations of cells, will also be critical for following temporal aspects of Hoxregulated responses. This is important in light of the findings from both fly and mammalian systems that demonstrate Hox regulation throughout the developmental path a cell or tissue takes. Thus, we need to see how Hox proteins change binding, but more importantly how gene expression changes, as a cell traverses a differentiation program. Relating gene expression changes and Hox binding with chromatin state will also be important. Of course, it goes without saying that Hox proteins do not act in isolation, and we will require a similar detailed understanding of what cofactors are required at each Hox-regulated enhancer and how these change over developmental time. Looking to the immediate future, a promising avenue of investigation is emerging with the increasing availability of genome sequence from a variety of animals coupled with the ability to apply genomic analysis via high-throughput sequencing. It is now feasible to consider, for example, mapping Hox binding at a genome-wide scale in less tractable model organisms such as the red flour beetle, Tribolium castaneum, which has some Hox genetics already established (Stuart et al., 1991). In Tribolium, Ubx specifies development of the membraneous hind wing rather than the hard wing covers (elytra) that the forewings develop: RNAi against Ubx results in a homeotic transformation of hind wing to forewing (Schro¨der et al., 2008; Tomoyasu et al., 2005). Thus, in the beetle, Ubx specifies development of a wing in contrast to Drosophila where it represses wing fate.

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Similarly, in the butterfly, Precis coenia, Ubx is believed to specify aspects of hind wing-specific patterning (Weatherbee et al., 1999). The use of classical genetics or RNAi-mediated gene knockdown in other insect systems offers the possibility of applying genomic techniques to identify Hox-dependent gene expression changes via RNA-seq. While this will be easier in organisms with a genome sequence, the pace of genome sequence acquisition is likely to accelerate and relatively soon any experimentally tractable animal will be amenable to genomic studies. Such evolutionary studies should enable comparisons between speciesspecific Hox targets to better understand how modulating gene networks generate different morphologies. It is very likely that comparative evolutionary analysis of Hox activity will be critical in fully understanding Hox function. Finally, and perhaps most critically, we need to view Hox regulation in the context of the gene regulatory network active in the cell (Carroll, 2008). It is possible that Hox factors direct the elaboration of different morphologies by causing small changes in the expression of thousands of genes across the network, and the cumulative effect of this is to dramatically alter the output of the network in terms of cell behavior and thus final morphology. In this speculative view, we imagine that making small alterations to the underpinning gene network dramatically alters the terrain of the regulatory landscape proposed by Waddington (Slack, 2002; Waddington, 1957). The contribution of both network structure and stochastic aspects of gene expression are becoming increasingly important considerations in our understanding of cellular decision making (Balazsi et al., 2011), and it is most likely, at these levels, that Hox proteins act to direct cell fates. As Garcia-Bellido presciently described in his paper elaborating the Selector–Realizator model: “The appearance of new selector genes does not demand new Realizator genes, but only a quantitatively different utilization of those already existing, so that, in this sense, the amount of genetic information required for evolutionary complication is kept to a minimum” (Garcia-Bellido, 1975). One can interpret this as suggesting, just as the genomic studies indicate, that Hox proteins exert their influence by changing the expression levels of many genes. Capturing the way Hox proteins influence the structure of the regulatory network will clearly improve our understanding of Hox function and, perhaps more importantly, provide fundamental insights into how plasticity in regulatory networks generate very different biological outputs. Taken together, it is clear that we have much to learn not only about how Hox proteins function in a cell lineage or in an animal but also how they integrate with other levels of regulation (i.e., Mattick et al., 2009) and, perhaps more importantly, how they have modified the output of gene regulatory networks during the course of evolution to give us “Endless Forms Most Beautiful” (Carroll, 2005). We have enjoyed more than a century of research into homeosis; we suspect we can easily look forward to another century before we come close to fully understanding Hox function.

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