Analysis of lamprey meis genes reveals that conserved inputs from Hox, Meis and Pbx proteins control their expression in the hindbrain and neural tube.

Meis genes are known to play important roles in the hindbrain and neural crest cells of jawed vertebrates. To explore the roles of Meis genes in head development during evolution of vertebrates, we have identified four meis genes in the sea lamprey genome and characterized their patterns of expression and regulation, with a focus on the hindbrain and pharynx. Each of the lamprey meis genes displays temporally and spatially dynamic patterns of expression, some of which are coupled to rhombomeric domains in the developing hindbrain and select pharyngeal arches. Studies of Meis loci in mouse and zebrafish have identified enhancers that are bound by Hox and TALE (Meis and Pbx) proteins, implicating these factors in the direct regulation of Meis expression. We examined the lamprey meis loci and identified a series of cis-elements conserved between lamprey and jawed vertebrate meis genes. In transgenic reporter assays we demonstrated that these elements act as neural enhancers in lamprey embryos, directing reporter expression in appropriate domains when compared to expression of their associated endogenous meis gene. Sequence alignments reveal that these conserved elements are in similar relative positions of the meis loci and contain a series of consensus binding motifs for Hox and TALE proteins. This suggests that ancient Hox and TALE-responsive enhancers regulated expression of ancestral vertebrate meis genes in segmental domains in the hindbrain and have been retained in the meis loci during vertebrate evolution. The presence of conserved Meis, Pbx and Hox binding sites in these lamprey enhancers links Hox and TALE factors to regulation of lamprey meis genes in the developing hindbrain, indicating a deep ancestry for these regulatory interactions prior to the divergence of jawed and jawless vertebrates.

HOXA1 and TALE proteins display cross-regulatory interactions and form a combinatorial binding code on HOXA1 targets.

Hoxa1 has diverse functional roles in differentiation and development. We identify and characterize properties of regions bound by HOXA1 on a genome-wide basis in differentiating mouse ES cells. HOXA1-bound regions are enriched for clusters of consensus binding motifs for HOX, PBX, and MEIS, and many display co-occupancy of PBX and MEIS. PBX and MEIS are members of the TALE family and genome-wide analysis of multiple TALE members (PBX, MEIS, TGIF, PREP1, and PREP2) shows that nearly all HOXA1 targets display occupancy of one or more TALE members. The combinatorial binding patterns of TALE proteins define distinct classes of HOXA1 targets, which may create functional diversity. Transgenic reporter assays in zebrafish confirm enhancer activities for many HOXA1-bound regions and the importance of HOX-PBX and TGIF motifs for their regulation. Proteomic analyses show that HOXA1 physically interacts on chromatin with PBX, MEIS, and PREP family members, but not with TGIF, suggesting that TGIF may have an independent input into HOXA1-bound regions. Therefore, TALE proteins appear to represent a wide repertoire of HOX cofactors, which may coregulate enhancers through distinct mechanisms. We also discover extensive auto- and cross-regulatory interactions among the Hoxa1 and TALE genes, indicating that the specificity of HOXA1 during development may be regulated though a complex cross-regulatory network of HOXA1 and TALE proteins. This study provides new insight into a regulatory network involving combinatorial interactions between HOXA1 and TALE proteins.

Coupling the roles of Hox genes to regulatory networks patterning cranial neural crest.

The neural crest is a transient population of cells that forms within the developing central nervous system and migrates away to generate a wide range of derivatives throughout the body during vertebrate embryogenesis. These cells are of evolutionary and clinical interest, constituting a key defining trait in the evolution of vertebrates and alterations in their development are implicated in a high proportion of birth defects and craniofacial abnormalities. In the hindbrain and the adjacent cranial neural crest cells (cNCCs), nested domains of Hox gene expression provide a combinatorial'Hox-code' for specifying regional properties in the developing head. Hox genes have been shown to play important roles at multiple stages in cNCC development, including specification, migration, and differentiation. However, relatively little is known about the underlying gene-regulatory mechanisms involved, both upstream and downstream of Hox genes. Furthermore, it is still an open question as to how the genes of the neural crest GRN are linked to Hox-dependent pathways. In this review, we describe Hox gene expression, function and regulation in cNCCs with a view to integrating these genes within the emerging gene regulatory network for cNCC development. We highlight early roles for Hox1 genes in cNCC specification, proposing that this may be achieved, in part, by regulation of the balance between pluripotency and differentiation in precursor cells within the neuro-epithelium. We then describe what is known about the regulation of Hox gene expression in cNCCs and discuss this from the perspective of early vertebrate evolution.

Integrated stability and activity control of the Drosophila Rbf1 retinoblastoma protein.

The retinoblastoma (RB) family transcriptional corepressors regulate diverse cellular events including cell cycle, senescence, and differentiation. The activity and stability of these proteins are mediated by post-translational modifications; however, we lack a general understanding of how distinct modifications coordinately impact both of these properties. Previously, we showed that protein turnover and activity are tightly linked through an evolutionarily conserved C-terminal instability element (IE) in the Drosophila RB-related protein Rbf1; surprisingly, mutant proteins with enhanced stability were less, not more active. To better understand how activity and turnover are controlled in this model RB protein, we assessed the impact of Cyclin-Cdk kinase regulation on Rbf1. An evolutionarily conserved N-terminal threonine residue is required for Cyclin-Cdk response and showed a dominant impact on turnover and activity; however, specific residues in the C-terminal IE differentially impacted Rbf1 activity and turnover, indicating an additional level of regulation. Strikingly, specific IE mutations that impaired turnover but not activity induced dramatic developmental phenotypes in the Drosophila eye. Mutation of the highly conserved Lys-774 residue induced hypermorphic phenotypes that mimicked the loss of phosphorylation control; mutation of the corresponding codon of the human RBL2 gene has been reported in lung tumors. Our data support a model in which closely intermingled residues within the conserved IE govern protein turnover, presumably through interactions with E3 ligases, and protein activity via contacts with E2F transcription partners. Such functional relationships are likely to similarly impact mammalian RB family proteins, with important implications for development and disease.

Evaluation of Hi-C sequencing for the detection of gene fusions in hematologic and solid pediatric cancer samples.

HiC sequencing is a DNA-based next-generation sequencing method that preserves the 3D conformation of the genome and has shown promise in detecting genomic rearrangements in translational research studies. To evaluate HiC as a potential clinical diagnostic platform, analytical concordance with routine laboratory testing was assessed using primary pediatric leukemia and sarcoma specimens previously positive for clinically significant genomic rearrangements. Archived specimen types tested included viable and nonviable frozen leukemic cells, as well as formalin-fixed paraffin-embedded (FFPE) tumor tissues. Initially, pediatric acute myeloid leukemia (AML) and alveolar rhabdomyosarcoma (A-RMS) specimens with known genomic rearrangements were subjected to HiC analysis to assess analytical concordance. Subsequently, a discovery cohort consisting of AML and acute lymphoblastic leukemia (ALL) cases with no known genomic rearrangements based on prior clinical diagnostic testing were evaluated to determine whether HiC could detect rearrangements. Using a standard sequencing depth of 50 million raw read-pairs per sample, or approximately 5X raw genomic coverage, 100% concordance was observed between HiC and previous clinical cytogenetic and molecular testing. In the discovery cohort, a clinically relevant gene fusion was detected in 45% of leukemia cases (5/11). This study demonstrates the value of HiC sequencing to medical diagnostic testing as it identified several clinically significant rearrangements, including those that might have been missed by current clinical testing workflows. Key points: HiC sequencing is a DNA-based next-generation sequencing method that preserves the 3D conformation of the genome, facilitating detection of genomic rearrangements.HiC was 100% concordant with clinical diagnostic testing workflows for detecting clinically significant genomic rearrangements in pediatric leukemia and rhabdomyosarcoma specimens.HiC detected clinically significant genomic rearrangements not previously detected by prior clinical cytogenetic and molecular testing.HiC performed well with archived non-viable and viable frozen leukemic cell samples, as well as archived formalin-fixed paraffin-embedded tumor tissue specimens.

Severus: accurate detection and characterization of somatic structural variation in tumor genomes using long reads.

Most current studies rely on short-read sequencing to detect somatic structural variation (SV) in cancer genomes. Long-read sequencing offers the advantage of better mappability and long-range phasing, which results in substantial improvements in germline SV detection. However, current long-read SV detection methods do not generalize well to the analysis of somatic SVs in tumor genomes with complex rearrangements, heterogeneity, and aneuploidy. Here, we present Severus: a method for the accurate detection of different types of somatic SVs using a phased breakpoint graph approach. To benchmark various short- and long-read SV detection methods, we sequenced five tumor/normal cell line pairs with Illumina, Nanopore, and PacBio sequencing platforms; on this benchmark Severus showed the highest F1 scores (harmonic mean of the precision and recall) as compared to long-read and short-read methods. We then applied Severus to three clinical cases of pediatric cancer, demonstrating concordance with known genetic findings as well as revealing clinically relevant cryptic rearrangements missed by standard genomic panels.

Predicting neuroblastoma using developmental signals and a logic-based model.

Genomic information from human patient samples of pediatric neuroblastoma cancers and known outcomes have led to specific gene lists put forward as high risk for disease progression. However, the reliance on gene expression correlations rather than mechanistic insight has shown limited potential and suggests a critical need for molecular network models that better predict neuroblastoma progression. In this study, we construct and simulate a molecular network of developmental genes and downstream signals in a 6-gene input logic model that predicts a favorable/unfavorable outcome based on the outcome of the four cell states including cell differentiation, proliferation, apoptosis, and angiogenesis. We simulate the mis-expression of the tyrosine receptor kinases, trkA and trkB, two prognostic indicators of neuroblastoma, and find differences in the number and probability distribution of steady state outcomes. We validate the mechanistic model assumptions using RNAseq of the SHSY5Y human neuroblastoma cell line to define the input states and confirm the predicted outcome with antibody staining. Lastly, we apply input gene signatures from 77 published human patient samples and show that our model makes more accurate disease outcome predictions for early stage disease than any current neuroblastoma gene list. These findings highlight the predictive strength of a logic-based model based on developmental genes and offer a better understanding of the molecular network interactions during neuroblastoma disease progression.

Quantitative perturbation-based analysis of gene expression predicts enhancer activity in early Drosophila embryo.

Enhancers constitute one of the major components of regulatory machinery of metazoans. Although several genome-wide studies have focused on finding and locating enhancers in the genomes, the fundamental principles governing their internal architecture and cis-regulatory grammar remain elusive. Here, we describe an extensive, quantitative perturbation analysis targeting the dorsal-ventral patterning gene regulatory network (GRN) controlled by Drosophila NF-κB homolog Dorsal. To understand transcription factor interactions on enhancers, we employed an ensemble of mathematical models, testing effects of cooperativity, repression, and factor potency. Models trained on the dataset correctly predict activity of evolutionarily divergent regulatory regions, providing insights into spatial relationships between repressor and activator binding sites. Importantly, the collective predictions of sets of models were effective at novel enhancer identification and characterization. Our study demonstrates how experimental dataset and modeling can be effectively combined to provide quantitative insights into cis-regulatory information on a genome-wide scale.