Causes and consequences of stochastic processes in development and disease

Recent developments in genomics indicate that epigenetic alterations may play an important causal role in predisposing normal cells to neoplastic transformation. Professor Teschendorff will begin by presenting data that support an epigenetic stem cell model of oncogenesis, according to which DNA methylation (DNAm) changes that accrue in normal cells as a function of age and other cancer risk factors, lead to differentiation defects and increased aberrant plasticity, promoting cancer development. In the context of two cancers (cervical and breast), he will demonstrate how specific DNAm changes in normal tissue can discriminate those tissues at future risk of neoplastic transformation from those that remain healthy. In the earliest stages these DNAm changes are inherently stochastic across individuals but exhibit selection and convergence upon neoplastic transformation. He will also describe how DNAm changes can be used to measure mitotic-age of tissues, and that DNAm-based mitotic clocks could be used for cancer risk prediction. In the last part of the talk, Professor Teschendorff will describe the group's efforts to quantify cancer risk at the resolution of single-cells via a bottom-up network model that quantifies dedifferentiation from single-cell RNA-Seq data in terms of diffusion entropy. Specifically, he will show how in the context of a multi-stage model of oesophageal cancer development, diffusion entropy identifies the precancerous cells that undergo selection during cancer progression. Mounting evidence points towards underlying epigenetic alterations being better cancer risk markers than genetic mutations or copy-number changes. He will end by discussing the implications of these findings for developing cancer risk prediction strategies.

Cilia are membrane-encased organelles present on the surface of most cells that rely upon intraflagellar transport (IFT) for their formation and function. Missense mutations in IFT genes cause skeletal, limb, eye and renal disease, and the group modelled several Ift80 mutations in mice. They find that some tissues are more susceptible to disease than others, and they describe incomplete penetrance in the absence of genetic background variation suggesting that stochastic processes determine disease susceptibility. One missense mutation within a splice acceptor affected multiple modes of gene function at the levels of RNA splicing, protein abundance and protein complex formation. This provides a means to investigate different sources of stochastic noise, and to use this biological variation to understand how mutational effects at different biological levels contribute to disease risk. A large proportion of mutations in human monogenic disease are also likely to be multimodal suggesting a generalised approach to investigate stochastic processes that could be applied to many diseases.

In this talk, Dr Pina will discuss the contributions of epigenetic heterogeneity and transcriptional noise in initiation and maintenance of Acute Myeloid Leukaemia. She will focus on KAT2A, a histone acetyltransferase (HAT) previously shown to regulate transcriptional noise levels in mammalian stem cell systems, and discuss the group's recent observations that Kat2a loss can both promote pre-leukaemia and impede leukaemia maintenance, with similar effects on variability on gene transcription and consequent cell diversification. She will discuss KAT2A roles through specific HAT complex integration, target programmes, and remodelling of gene regulatory networks, and integrate the findings with the transcriptional consequences of other epigenetic complexes previously implicated in regulation of transcriptional noise and progression of leukaemia. Drawing from stem cell and leukaemia models, she will discuss gene-specific responses to transcriptional noise modulation, and suggest potential contextual contributions to functional outcomes and putative value as markers of leukaemia progression and therapeutic response.

Chemical reactions serve as basic units for cellular information processing and control. However, reactions in cells are noisy, leading to substantial variability in the molecular constitution of genetically identical cells. How cells deal with such noise has been important question in quantitative biology. In this talk, Dr Zechner will discuss how the mesoscale organisation of molecules into condensates can be used by cells to suppress cellular noise. Using concepts from statistical physics and control theory, he will show that condensates mediate negative feedback, which maintains concentration levels at precise set points in the presence of noise. He will present experimental single-cell data from synthetic and endogenous systems supporting this prediction.

Stochastic mechanisms diversify cell fates during development. How cells randomly choose between two or more fates remains poorly understood. In the Drosophila eye, the random mosaic of two R7 photoreceptor subtypes is determined by expression of the transcription factor Spineless (Ss). The group investigated how cis-regulatory elements and trans factors regulate nascent transcriptional activity and chromatin compaction at the ss gene locus during R7 development. The ss locus is in a compact state in undifferentiated cells. An early enhancer drives transcription in all R7 precursors, and the locus opens. In differentiating cells, transcription ceases and the ss locus stochastically remains open or compacts. In Ss^ON R7s, ss is open and competent for activation by a late enhancer, whereas in Ss^OFF R7s, ss is compact, and repression prevents expression. These results suggest that a temporally dynamic antagonism, in which transcription drives large-scale decompaction and then compaction represses transcription, controls stochastic fate specification.

Gene expression in individual cells can be surprisingly noisy. In unicellular organisms this noise can be functional. For example, it can allow a fraction of the population to survive a sudden environmental stress. The role of gene expression noise in multicellular organisms is less clear. In this talk, Dr Locke will show how new techniques are revealing an unexpected level of variability in gene expression between and within genetically identical plants. He will discuss evidence that transcriptional noise can act as a mechanism for generating functional phenotypic diversity in plants.

Development from fertilised egg to functioning multi-cellular organism requires precision. Precision can only be achieved through plasticity. Plasticity is conferred in part by stochastic variation, which is inherently present in biological systems. Gene expression levels fluctuate at multiple stages: transcription, alternative splicing, translation, and turnover. Evolving multicellularity and cellular specialisation have exploited the small differences in gene expression to confer distinct functions on selected individual cells. This initial differentiation sets in motion regulatory interactions allowing the non-selected cells to acquire new functions along the spatiotemporal developmental trajectory. Many other components of the differentiation process are stochastic. The dynamic binding of transcriptional regulatory assemblies to DNA exhibit randomness. X-inactivation is normally random, non-random inactivation is generally a sign of mutational perturbation. Correct neural wiring arises through random connections, followed by maintenance only for functional links. This mechanism is well illustrated for the retina. In immune system development both antibody maturation in B cells and the emergence of a balanced population of T-cells begins through stochastic trial and error followed by functional selection. Multiple manifestations of disease arise when the switch from random fluctuation to established pattern selection fails. A wide spectrum of mostly deleterious DNA mutations through stochastic fluctuation in environmental factors: such as levels of radiation or presence of pollutants. The phenotypic outcome of mutations is dependent on variability across genomic functions and the environment. Variable environmental factors also determine which mutations prove advantageous. To ensure population survival, bet-hedging stochastic strategies are often deployed.