Clustering and graph mining techniques for classification of complex structural variations in cancer genomes

For many years, a major question in cancer genomics has been the identification of those variations that can have a functional role in cancer, and distinguish from the majority of genomic changes that have no functional consequences. This is particularly challenging when considering complex chromosomal rearrangements, often composed of multiple DNA breaks, resulting in difficulties in classifying and interpreting them functionally. Despite recent efforts towards classifying structural variants (SVs), more robust statistical frames are needed to better classify these variants and isolate those that derive from specific molecular mechanisms. We present a new statistical approach to analyze SVs patterns from 2392 tumor samples from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium and identify significant recurrence, which can inform relevant mechanisms involved in the biology of tumors. The method is based on recursive KDE clustering of 152,926 SVs, randomization methods, graph mining techniques and statistical measures. The proposed methodology was able not only to identify complex patterns across different cancer types but also to prove them as not random occurrences. Furthermore, a new class of pattern that was not previously described has been identified.Among others, this study has been supported by projects: SAF2017-89450-R (TransTumVar) and PID2020-119797RB-100 (BenchSV) from Science and Innovation Spanish Minstry. It has also been supported by the Spanish Goverment (contract PID2019-107255GB), Generalitat de Catalunya (contract 2014-SGR-1051) and Universitat Politècnica de Catalunya (45-FPIUPC2018).Peer ReviewedPostprint (published version

Prebiotically plausible mechanisms increase compositional diversity of nucleic acid sequences

During the origin of life, the biological information of nucleic acid polymers must have increased to encode functional molecules (the RNA world). Ribozymes tend to be compositionally unbiased, as is the vast majority of possible sequence space. However, ribonucleotides vary greatly in synthetic yield, reactivity and degradation rate, and their non-enzymatic polymerization results in compositionally biased sequences. While natural selection could lead to complex sequences, molecules with some activity are required to begin this process. Was the emergence of compositionally diverse sequences a matter of chance, or could prebiotically plausible reactions counter chemical biases to increase the probability of finding a ribozyme? Our in silico simulations using a two-letter alphabet show that template-directed ligation and high concatenation rates counter compositional bias and shift the pool toward longer sequences, permitting greater exploration of sequence space and stable folding. We verified experimentally that unbiased DNA sequences are more efficient templates for ligation, thus increasing the compositional diversity of the pool. Our work suggests that prebiotically plausible chemical mechanisms of nucleic acid polymerization and ligation could predispose toward a diverse pool of longer, potentially structured molecules. Such mechanisms could have set the stage for the appearance of functional activity very early in the emergence of life

Optically Active Dye-Based Systems Templated by DNA Exhibiting Excitonic Delocalization

The concept of quantum computing was first developed in the early 1980’s. The attraction of quantum computers is their potential capacity to solve extremely complex problems, such as factorization, on a timescale far faster than that of classical computers. However, realization of quantum computation is currently in its infancy, and recent implementations possess serious drawbacks that reduce their appeal. Some challenges of current designs include the necessity to cool the systems using liquid helium to near absolute zero temperatures (15 mK) in order to maintain sufficiently long-lifetimes of the Qbits (i.e., unit of quantum information), difficulty with scaling up the processing systems, and prohibitively high manufacturing costs. Fundamentally, the key physical effect that enables high processing speeds in quantum computers is quantum superposition, which allows a single qbit to have two (or more) definite states (e.g., 0 and 1) simultaneously. Maintaining a superposition of states at room temperature, however, has proven difficult with silicon-based technology. Coherent exciton delocalization, which involves the superposition of excitonic states characterized by the delocalization of excitons (i.e., electron-hole pairs) across spatially proximate but separated molecules, has been observed in biological photosynthetic systems at ambient temperatures (295 K). Natural photosynthetic systems are composed of protein scaffolds that encompass and elegantly arrange an aggregate of optically active dye molecules (i.e., cluster of chromophores) with nanometer-scale precision in a manner that promotes coherence despite the inherently warm and “noisy” (i.e., rapidly fluctuating) environment inside a plant. As a result, light energy absorbed from the sun is quickly and efficiently transferred through the dye aggregate in a wavelike manner that both optimizes the transfer pathway and minimizes energy loss. Thus, exploiting excitonic delocalization, as inspired by biology, offers a potential path forward towards realizing quantum computing at room temperature. Here, we demonstrate coherent exciton delocalization in systems that utilize DNA, a biological material that affords atomically precise arrangement of dyes (e.g., Cy5) with nanometer proximity, as a scaffold. Leveraging the inherent programmability and functionality of DNA, which undergoes Watson-Crick base-pairing to enable simple structural control than the complex folding mechanisms involved with proteins, we have designed two dye-DNA complexes that are described in two journal manuscripts contained within this dissertation (Chapters 2 and 3). The first manuscript, which described the behavior and spectral properties of a relatively simple linear dye-DNA complex, achieved two milestones towards quantum information processing: (i) the identification of Cy5 dyes as promising candidates for the development of exciton-based devices and quantum gates due to the large Davydov splitting observed spectrally (i.e., a manifestation of dye-dye coupling and coherent exciton delocalization), and (ii) the data necessary to determine the physical parameters for a phenomenological theoretical model of exciton transport between Cy5 dyes within a DNA complex. The second manuscript, which encompassed a larger, more rigid, two-dimensional Holliday junction structure designed to form dye aggregates of a pre-determined size including dimers, trimers, and tetramers, validated the physical parameters used in the theoretical work for the first manuscript, showing that the same parameters can be used for other dye-DNA configurations. It also demonstrated that large Davydov splitting in dye aggregates can be achieved using a larger, more rigid two-dimensional Holliday junction structure. Taken together, the two manuscripts combined give confidence to the phenomenological theoretical model, which can be used as a predictive engineering tool for designing dye-DNA based excitonic devices and quantum gates, or as an analysis tool for determining dye configurations based on spectral data

Nucleic Acid Architectures for Therapeutics, Diagnostics, Devices and Materials

Nucleic acids (RNA and DNA) and their chemical analogs have been utilized as building materials due to their biocompatibility and programmability. RNA, which naturally possesses a wide range of different functions, is now being widely investigated for its role as a responsive biomaterial which dynamically reacts to changes in the surrounding environment. It is now evident that artificially designed self-assembling RNAs, that can form programmable nanoparticles and supra-assemblies, will play an increasingly important part in a diverse range of applications, such as macromolecular therapies, drug delivery systems, biosensing, tissue engineering, programmable scaffolds for material organization, logic gates, and soft actuators, to name but a few. The current exciting Special Issue comprises research highlights, short communications, research articles, and reviews that all bring together the leading scientists who are exploring a wide range of the fundamental properties of RNA and DNA nanoassemblies suitable for biomedical applications