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Changes in gene expression represent an important source of phenotypic innovation. Yet, how such changes emerge and impact the evolution of traits remains elusive. Here, we explore the molecular mechanisms associated with the development of masculinizing ovotestes in female moles. By performing integrative analyses of epigenetic and transcriptional data in mole and mouse, we identified the co-option of SALL1 expression in mole ovotestes formation. Chromosome conformation capture analyses highlight a striking conservation of the 3D organization at the SALL1 locus, but an evolutionary divergence of enhancer activity. Interspecies reporter assays support the capability of mole-specific enhancers to activate transcription in urogenital tissues. Through overexpression experiments in transgenic mice, we further demonstrate the capability of SALL1 to induce kidney-related gene programs, which are a signature of mole ovotestes. Our results highlight the co-option of gene expression, through changes in enhancer activity, as a plausible mechanism for the evolution of traits.

Linking genomic variation to phenotypical traits remains a major challenge in evolutionary genetics. In this study, we use phylogenomic strategies to investigate a distinctive trait among mammals: the development of masculinizing ovotestes in female moles. By combining a chromosome-scale genome assembly of the Iberian mole, Talpa occidentalis, with transcriptomic, epigenetic, and chromatin interaction datasets, we identify rearrangements altering the regulatory landscape of genes with distinct gonadal expression patterns. These include a tandem triplication involving CYP17A1, a gene controlling androgen synthesis, and an intrachromosomal inversion involving the pro-testicular growth factor gene FGF9, which is heterochronically expressed in mole ovotestes. Transgenic mice with a knock-in mole CYP17A1 enhancer or overexpressing FGF9 showed phenotypes recapitulating mole sexual features. Our results highlight how integrative genomic approaches can reveal the phenotypic impact of noncoding sequence changes.

Genome-wide analysis methods, such as array comparative genomic hybridization (CGH) and whole-genome sequencing (WGS), have greatly advanced the identification of structural variants (SVs) in the human genome. However, even with standard high-throughput sequencing techniques, complex rearrangements with multiple breakpoints are often difficult to resolve, and predicting their effects on gene expression and phenotype remains a challenge. Here, we address these problems by using high-throughput chromosome conformation capture (Hi-C) generated from cultured cells of nine individuals with developmental disorders (DDs). Three individuals had previously been identified as harboring duplications at the SOX9 locus and six had been identified with translocations. Hi-C resolved the positions of the duplications and was instructive in interpreting their distinct pathogenic effects, including the formation of new topologically associating domains (neo-TADs). Hi-C was very sensitive in detecting translocations, and it revealed previously unrecognized complex rearrangements at the breakpoints. In several cases, we observed the formation of fused-TADs promoting ectopic enhancer-promoter interactions that were likely to be involved in the disease pathology. In summary, we show that Hi-C is a sensible method for the detection of complex SVs in a clinical setting. The results help interpret the possible pathogenic effects of the SVs in individuals with DDs.

The regulatory specificity of enhancers and their interaction with gene promoters is thought to be controlled by their sequence and the binding of transcription factors. By studying Pitx1, a regulator of hindlimb development, we show that dynamic changes in chromatin conformation can restrict the activity of enhancers. Inconsistent with its hindlimb-restricted expression, Pitx1 is controlled by an enhancer (Pen) that shows activity in forelimbs and hindlimbs. By Capture Hi-C and three-dimensional modeling of the locus, we demonstrate that forelimbs and hindlimbs have fundamentally different chromatin configurations, whereby Pen and Pitx1 interact in hindlimbs and are physically separated in forelimbs. Structural variants can convert the inactive into the active conformation, thereby inducing Pitx1 misexpression in forelimbs, causing partial arm-to-leg transformation in mice and humans. Thus, tissue-specific three-dimensional chromatin conformation can contribute to enhancer activity and specificity in vivo and its disturbance can result in gene misexpression and disease.

Pulmonary large-cell neuroendocrine carcinomas (LCNECs) have similarities with other lung cancers, but their precise relationship has remained unclear. Here we perform a comprehensive genomic (n = 60) and transcriptomic (n = 69) analysis of 75 LCNECs and identify two molecular subgroups: "type I LCNECs" with bi-allelic TP53 and STK11/KEAP1 alterations (37%), and "type II LCNECs" enriched for bi-allelic inactivation of TP53 and RB1 (42%). Despite sharing genomic alterations with adenocarcinomas and squamous cell carcinomas, no transcriptional relationship was found; instead LCNECs form distinct transcriptional subgroups with closest similarity to SCLC. While type I LCNECs and SCLCs exhibit a neuroendocrine profile with ASCL1high/DLL3high/NOTCHlow, type II LCNECs bear TP53 and RB1 alterations and differ from most SCLC tumors with reduced neuroendocrine markers, a pattern of ASCL1low/DLL3low/NOTCHhigh, and an upregulation of immune-related pathways. In conclusion, LCNECs comprise two molecularly defined subgroups, and distinguishing them from SCLC may allow stratified targeted treatment of high-grade neuroendocrine lung tumors.

Copy number variations (CNVs) often include noncoding sequences and putative enhancers, but how these rearrangements induce disease is poorly understood. Here we investigate CNVs involving the regulatory landscape of IHH (encoding Indian hedgehog), which cause multiple, highly localized phenotypes including craniosynostosis and synpolydactyly. We show through transgenic reporter and genome-editing studies in mice that Ihh is regulated by a constellation of at least nine enhancers with individual tissue specificities in the digit anlagen, growth plates, skull sutures and fingertips. Consecutive deletions, resulting in growth defects of the skull and long bones, showed that these enhancers function in an additive manner. Duplications, in contrast, caused not only dose-dependent upregulation but also misexpression of Ihh, leading to abnormal phalanges, fusion of sutures and syndactyly. Thus, precise spatiotemporal control of developmental gene expression is achieved by complex multipartite enhancer ensembles. Alterations in the composition of such clusters can result in gene misexpression and disease.

The genomic loci bound by the glucocorticoid receptor (GR), a hormone-activated transcription factor, show little overlap between cell types. To study the role of chromatin and sequence in specifying where GR binds, we used Bayesian modeling within the universe of accessible chromatin. Taken together, our results uncovered that although GR preferentially binds accessible chromatin, its binding is biased against accessible chromatin located at promoter regions. This bias can only be explained partially by the presence of fewer GR recognition sequences, arguing for the existence of additional mechanisms that interfere with GR binding at promoters. Therefore, we tested the role of H3K9ac, the chromatin feature with the strongest negative association with GR binding, but found that this correlation does not reflect a causative link. Finally, we find a higher percentage of promoter-proximal GR binding for genes regulated by GR across cell types than for cell type-specific target genes. Given that GR almost exclusively binds accessible chromatin, we propose that cell type-specific regulation by GR preferentially occurs via distal enhancers, whose chromatin accessibility is typically cell type-specific, whereas ubiquitous target gene regulation is more likely to result from binding to promoter regions, which are often accessible regardless of cell type examined.

We have sequenced the genomes of 110 small cell lung cancers (SCLC), one of the deadliest human cancers. In nearly all the tumours analysed we found bi-allelic inactivation of TP53 and RB1, sometimes by complex genomic rearrangements. Two tumours with wild-type RB1 had evidence of chromothripsis leading to overexpression of cyclin D1 (encoded by the CCND1 gene), revealing an alternative mechanism of Rb1 deregulation. Thus, loss of the tumour suppressors TP53 and RB1 is obligatory in SCLC. We discovered somatic genomic rearrangements of TP73 that create an oncogenic version of this gene, TP73Δex2/3. In rare cases, SCLC tumours exhibited kinase gene mutations, providing a possible therapeutic opportunity for individual patients. Finally, we observed inactivating mutations in NOTCH family genes in 25% of human SCLC. Accordingly, activation of Notch signalling in a pre-clinical SCLC mouse model strikingly reduced the number of tumours and extended the survival of the mutant mice. Furthermore, neuroendocrine gene expression was abrogated by Notch activity in SCLC cells. This first comprehensive study of somatic genome alterations in SCLC uncovers several key biological processes and identifies candidate therapeutic targets in this highly lethal form of cancer.

In addition to guiding proteins to defined genomic loci, DNA can act as an allosteric ligand that influences protein structure and activity. Here we compared genome-wide binding, transcriptional regulation, and, using NMR, the conformation of two glucocorticoid receptor (GR) isoforms that differ by a single amino acid insertion in the lever arm, a domain that adopts DNA sequence-specific conformations. We show that these isoforms differentially regulate gene expression levels through two mechanisms: differential DNA binding and altered communication between GR domains. Our studies suggest a versatile role for DNA in both modulating GR activity and also in directing the use of GR isoforms. We propose that the lever arm is a "fulcrum" for bidirectional allosteric signaling, conferring conformational changes in the DNA reading head that influence DNA sequence selectivity, as well as conferring changes in the dimerization domain that connect functionally with remote regulatory surfaces, thereby influencing which genes are regulated and the magnitude of their regulation.

Background: Gene regulation and metabolic reactions are two primary activities of life. Although many works have been dedicated to study each system, the coupling between them is less well understood. To bridge this gap, we propose a joint model of gene regulation and metabolic reactions. Results: We integrate regulatory and metabolic networks by adding links specifying the feedback control from the substrates of metabolic reactions to enzyme gene expressions. We adopt two alternative approaches to build those links: inferring the links between metabolites and transcription factors to fit the data or explicitly encoding the general hypotheses of feedback control as links between metabolites and enzyme expressions. A perturbation data is explained by paths in the joint network if the predicted response along the paths is consistent with the observed response. The consistency requirement for explaining the perturbation data imposes constraints on the attributes in the network such as the functions of links and the activities of paths. We build a probabilistic graphical model over the attributes to specify these constraints, and apply an inference algorithm to identify the attribute values which optimally explain the data. The inferred models allow us to 1) identify the feedback links between metabolites and regulators and their functions, 2) identify the active paths responsible for relaying perturbation effects, 3) computationally test the general hypotheses pertaining to the feedback control of enzyme expressions, 4) evaluate the advantage of an integrated model over separate systems. Conclusion: The modeling results provide insight about the mechanisms of the coupling between the two systems and possible "design rules" pertaining to enzyme gene regulation. The model can be used to investigate the less well-probed systems and generate consistent hypotheses and predictions for further validation.

In molecular biology, just as in many other fields of science, data often come in the form of matrices or contingency tables with many observations (rows) for a set of variables (columns). While projection methods like principal component analysis or correspondence analysis (CA) can be applied for obtaining an overview of such data, in cases where the matrix is very large the associated loss of information upon projection into two or three dimensions may be dramatic. However, when the set of variables can be grouped into clusters, this opens up a new angle on the data. We focus on the question of which observations are associated to a cluster and distinguish it from other clusters. CA employs a geometry geared towards answering this question. We exploit this feature in order to introduce Association Plots for visualizing cluster-specific observations in complex data. Regardless of the data matrix dimensionality Association Plots are two-dimensional and depict the observations associated to a cluster of variables. We demonstrate our method on two small data sets and then use it to study a challenging genomic data set comprising >10,000 samples. We show that Association Plots can clearly highlight those observations which characterise a cluster of variables. [ABSTRACT FROM AUTHOR]