Divergence of mutational signatures in association with breast cancer subtype.

Abnormal molecular processes occurring throughout the genome leave distinct somatic mutational patterns termed mutational signatures. Exploring the associations between mutational signatures and clinicopathological features can unravel potential mechanisms driving tumorigenic processes. We analyzed whole genome sequencing (WGS) data of tumor and peripheral blood samples from 37 primary breast cancer (BC) patients receiving neoadjuvant chemotherapy. Comprehensive clinico-pathologic features were correlated with genomic profiles and mutational signatures. Somatic mutational landscapes were highly concordant with known BC data sets. Remarkably, we observed a divergence of dominant mutational signatures in association with BC subtype. Signature 5 was overrepresented in hormone receptor positive (HR+) patients, whereas triple-negative tumors mostly lacked Signature 5, but expectedly overrepresented Signature 3. We validated these findings in a large WGS data set of BC, demonstrating dominance of Signature 5 in HR+ patients, mostly in luminal A subtype. We further investigated the association between Signature 5 and gene expression signatures, and identified potential networks, likely related to estrogen regulation. Our results suggest that the yet elusive Signature 5 represents an alternative mechanism for mutation accumulation in HR+ BC, independent of the homologous recombination repair machinery related to Signature 3. This study provides theoretical basis for further elucidating the processes promoting hormonal breast carcinogenesis.

Codon usage of highly expressed genes affects proteome-wide translation efficiency.

Although the genetic code is redundant, synonymous codons for the same amino acid are not used with equal frequencies in genomes, a phenomenon termed "codon usage bias." Previous studies have demonstrated that synonymous changes in a coding sequence can exert significant cis effects on the gene's expression level. However, whether the codon composition of a gene can also affect the translation efficiency of other genes has not been thoroughly explored. To study how codon usage bias influences the cellular economy of translation, we massively converted abundant codons to their rare synonymous counterpart in several highly expressed genes in Escherichia coli This perturbation reduces both the cellular fitness and the translation efficiency of genes that have high initiation rates and are naturally enriched with the manipulated codon, in agreement with theoretical predictions. Interestingly, we could alleviate the observed phenotypes by increasing the supply of the tRNA for the highly demanded codon, thus demonstrating that the codon usage of highly expressed genes was selected in evolution to maintain the efficiency of global protein translation.

Nucleosome organization affects the sensitivity of gene expression to promoter mutations.

Gene expression diverges rapidly between related species, playing a key role in the evolution of new phenotypes. The extent of divergence differs greatly between genes and is correlated to promoter nucleosome organization. We hypothesized that this may be partially explained by differential sensitivity of expression to mutations in the promoter region. We measured the sensitivity of 22 yeast promoters with varying nucleosome patterns to random mutations in sequence. Mutation sensitivity differed by up to 10-fold between promoters. This difference could not be explained by the abundance of transcription factor binding sites. Rather, mutation sensitivity positively correlated with the relative occupancy of nucleosomes at the proximal promoter region. Furthermore, mutation sensitivity was reduced upon introduction of a binding site for Reb1, a factor that blocks nucleosome formation, suggesting that nucleosome organization directly regulates mutation sensitivity. Our study suggests an important role for chromatin structure in the evolution of gene expression.

Expression noise and acetylation profiles distinguish HDAC functions.

Gene expression shows a significant variation (noise) between genetically identical cells. Noise depends on the gene expression process regulated by the chromatin environment. We screened for chromatin factors that modulate noise in S. cerevisiae and analyzed the results using a theoretical model that infers regulatory mechanisms from the noise versus mean relationship. Distinct activities of the Rpd3(L) and Set3 histone deacetylase complexes were predicted. Both HDACs repressed expression. Yet, Rpd3(L)C decreased the frequency of transcriptional bursts, while Set3C decreased the burst size, as did H2B monoubiquitination (ubH2B). We mapped the acetylation of H3 lysine 9 (H3K9ac) upon deletion of multiple subunits of Set3C and Rpd3(L)C and of ubH2B effectors. ubH2B and Set3C appear to function in the same pathway to reduce the probability that an elongating PolII produces a functional transcript (PolII processivity), while Rpd3(L)C likely represses gene expression at a step preceding elongation.

UTAP: User-friendly Transcriptome Analysis Pipeline.

BACKGROUND: RNA-Seq technology is routinely used to characterize the transcriptome, and to detect gene expression differences among cell types, genotypes and conditions. Advances in short-read sequencing instruments such as Illumina Next-Seq have yielded easy-to-operate machines, with high throughput, at a lower price per base. However, processing this data requires bioinformatics expertise to tailor and execute specific solutions for each type of library preparation. RESULTS: In order to enable fast and user-friendly data analysis, we developed an intuitive and scalable transcriptome pipeline that executes the full process, starting from cDNA sequences derived by RNA-Seq [Nat Rev Genet 10:57-63, 2009] and bulk MARS-Seq [Science 343:776-779, 2014] and ending with sets of differentially expressed genes. Output files are placed in structured folders, and results summaries are provided in rich and comprehensive reports, containing dozens of plots, tables and links. CONCLUSION: Our User-friendly Transcriptome Analysis Pipeline (UTAP) is an open source, web-based intuitive platform available to the biomedical research community, enabling researchers to efficiently and accurately analyse transcriptome sequence data.

Noise-mean relationship in mutated promoters.

Gene expression depends on the frequency of transcription events (burst frequency) and on the number of mRNA molecules made per event (burst size). Both processes are encoded in promoter sequence, yet their dependence on mutations is poorly understood. Theory suggests that burst size and frequency can be distinguished by monitoring the stochastic variation (noise) in gene expression: Increasing burst size will increase mean expression without changing noise, while increasing burst frequency will increase mean expression and decrease noise. To reveal principles by which promoter sequence regulates burst size and frequency, we randomly mutated 22 yeast promoters chosen to span a range of expression and noise levels, generating libraries of hundreds of sequence variants. In each library, mean expression (m) and noise (coefficient of variation, η) varied together, defining a scaling curve: η(2) = b/m + η(ext)(2). This relation is expected if sequence mutations modulate burst frequency primarily. The estimated burst size (b) differed between promoters, being higher in promoter containing a TATA box and lacking a nucleosome-free region. The rare variants that significantly decreased b were explained by mutations in TATA, or by an insertion of an out-of-frame translation start site. The decrease in burst size due to mutations in TATA was promoter-dependent, but independent of other mutations. These TATA box mutations also modulated the responsiveness of gene expression to changing conditions. Our results suggest that burst size is a promoter-specific property that is relatively robust to sequence mutations but is strongly dependent on the interaction between the TATA box and promoter nucleosomes.

Promoter nucleosome organization shapes the evolution of gene expression.

Understanding why genes evolve at different rates is fundamental to evolutionary thinking. In species of the budding yeast, the rate at which genes diverge in expression correlates with the organization of their promoter nucleosomes: genes lacking a nucleosome-free region (denoted OPN for "Occupied Proximal Nucleosomes") vary widely between the species, while the expression of those containing NFR (denoted DPN for "Depleted Proximal Nucleosomes") remains largely conserved. To examine if early evolutionary dynamics contributes to this difference in divergence, we artificially selected for high expression of GFP-fused proteins. Surprisingly, selection was equally successful for OPN and DPN genes, with -80% of genes in each group stably increasing in expression by a similar amount. Notably, the two groups adapted by distinct mechanisms: DPN-selected strains duplicated large genomic regions, while OPN-selected strains favored trans mutations not involving duplications. When selection was removed, DPN (but not OPN) genes reverted rapidly to wild-type expression levels, consistent with their lower diversity between species. Our results suggest that promoter organization constrains the early evolutionary dynamics and in this way biases the path of long-term evolution.

Experimental Evolution of Bacillus subtilis Reveals the Evolutionary Dynamics of Horizontal Gene Transfer and Suggests Adaptive and Neutral Effects.

Tracing evolutionary processes that lead to fixation of genomic variation in wild bacterial populations is a prime challenge in molecular evolution. In particular, the relative contribution of horizontal gene transfer (HGT) vs.de novo mutations during adaptation to a new environment is poorly understood. To gain a better understanding of the dynamics of HGT and its effect on adaptation, we subjected several populations of competent Bacillus subtilis to a serial dilution evolution on a high-salt-containing medium, either with or without foreign DNA from diverse pre-adapted or naturally salt tolerant species. Following 504 generations of evolution, all populations improved growth yield on the medium. Sequencing of evolved populations revealed extensive acquisition of foreign DNA from close Bacillus donors but not from more remote donors. HGT occurred in bursts, whereby a single bacterial cell appears to have acquired dozens of fragments at once. In the largest burst, close to 2% of the genome has been replaced by HGT. Acquired segments tend to be clustered in integration hotspots. Other than HGT, genomes also acquired spontaneous mutations. Many of these mutations occurred within, and seem to alter, the sequence of flagellar proteins. Finally, we show that, while some HGT fragments could be neutral, others are adaptive and accelerate evolution.

Noise propagation and signaling sensitivity in biological networks: a role for positive feedback.

Interactions between genes and proteins are crucial for efficient processing of internal or external signals, but this connectivity also amplifies stochastic fluctuations by propagating noise between components. Linear (unbranched) cascades were shown to exhibit an interplay between the sensitivity to changes in input signals and the ability to buffer noise. We searched for biological circuits that can maintain signaling sensitivity while minimizing noise propagation, focusing on cases where the noise is characterized by rapid fluctuations. Negative feedback can buffer this type of noise, but this buffering comes at the expense of an even greater reduction in signaling sensitivity. By systematically analyzing three-component circuits, we identify positive feedback as a central motif allowing for the buffering of propagated noise while maintaining sensitivity to long-term changes in input signals. We show analytically that noise reduction in the presence of positive feedback results from improved averaging of rapid fluctuations over time, and discuss in detail a particular implementation in the control of nutrient homeostasis in yeast. As the design of biological networks optimizes for multiple constraints, positive feedback can be used to improve sensitivity without a compromise in the ability to buffer propagated noise.

High Expression of CD200 and CD200R1 Distinguishes Stem and Progenitor Cell Populations within Mammary Repopulating Units.

Aiming to unravel the top of the mammary epithelial cell hierarchy, a subset of the CD49fhighCD24med mammary repopulating units (MRUs) was identified by flow cytometry, expressing high levels of CD200 and its receptor CD200R1. These MRUCD200/CD200R1 repopulated a larger area of de-epithelized mammary fat pads than the rest of the MRUs, termed MRUnot CD200/CD200R1. MRUCD200/CD200R1 maintained a much lower number of divergently defined, highly expressed genes and pathways that support better cell growth, development, differentiation, and progenitor activity than their MRUnot CD200/CD200R1 counterparts. A defined profile of hierarchically associated genes supporting a single-lineage hypothesis was confirmed by in vitro mammosphere analysis that assembled 114 genes with decreased expression from MRUCD200/CD200R1 via MRUnot CD200/CD200R1 toward CD200+CD200R1- and CD200R1+CD200- cells. About 40% of these genes were shared by a previously published database of upregulated genes in mammary/breast stem cells and may represent the core genes involved in mammary stemness.

Morphogen gradient formation in a complex environment: an anomalous diffusion model.

Current models of morphogen-induced patterning assume that morphogens undergo normal, or Fickian, diffusion, although the validity of this assumption has never been examined. Here we argue that the interaction of morphogens with the complex extracellular surrounding may lead to anomalous diffusion. We present a phenomenological model that captures this interaction, and derive the properties of the morphogen profile under conditions of anomalous (non-Fickian) diffusion. In this context we consider the continuous time random walk formalism and extend its application to account for degradation of morphogen particles. We show that within the anomalous diffusion model, morphogen profiles are fundamentally distinct from the corresponding Fickian profiles. Differences were found in several key aspects, including the role of degradation in determining the profile, the rate by which it spreads in time and its long-term behavior. We analyze the effect of an abrupt change in the extracellular environment on the concentration profiles. Furthermore, we discuss the robustness of the morphogen distribution to fluctuations in morphogen production rate, and describe a feedback mechanism that can buffer such fluctuations. Our study also provides rigorous criteria to distinguish experimentally between Fickian and anomalous modes of morphogen transport.