Comparative Genomics Meets Genome Assembly: from Ancestral Reconstruction to Genome Scaffolding
Open Access DepositedExponentially growing number of complete DNA sequences of various organisms enriched and revolutionized biological and biomedical research tremendously. Despite recent progress in computational biology there is still a large number of important unanswered questions particularly in the area of comparative analysis, phylogenetics, and genome assembly. In the described research we present our work on various problems in the aforementioned areas and demonstrate how methodology traditionally utilized in comparative genomics can be adapted to problems in the area of genome assembly. In comparative evolutionary genomics, the rearrangement distance between two genomes (equal the minimal number of large-scale genome rearrangements required to transform them into a single genome) is often used for measuring their evolutionary remoteness. Generalization of this measure to three genomes is known as the median score. We first study relationship and interplay of pairwise distances between three genomes and their median score under the model of Double-Cut-and-Join (DCJ) genome rearrangements. We describe the space of genome triplets for which the lower bound of the median score is attainable, demonstrate that median score for a triplet can remain intact regardless of how pairwise distances are changed by a single genome rearrangement. We also show that the upper bound of the median score can not be represented as a sum of its bound and some constant. We then move to an even more general problem of ancestral genome reconstruction for multiple given genomes. We present MGRA2: an expansion of the algorithmic toolbox initially introduced in the MGRA ancestral reconstruction framework. We add the support for the input genomes with unequal gene content (i.e. adding gene gain/loss evolutionary events into the model) as well as several heuristics to better deal with the problem of breakpoint reuse, which is known to be one of the key obstacles in the area of evolutionary analysis of multiple genomes. We remark that for the two previously described problems input genomes are expected to be complete and error free. However, it, is often not the case in the real world, where assembly methods still struggle to produced complete genomics sequences from the data obtained in the in vivo sequencing experiments. In an attempt to bridge this gap we present a novel algorithm for scaffold assembling: the problem of completing genomic sequence from a set of unordered and unoriented fragments. We also demonstrate the benefits of combining the methodology for multi-genomes rearrangement analysis and the presented genome scaffolding algorithm. We then investigate the problem of comparing and merging multiple scaffold assemblies of the same organism. This problem is of great importance, as there is a large number of both in vivo and in silico methods aimed at addressing the scaffold assembly problem, and processing results obtained from a variety of these methods manually in a comprehensive manner can be very time-consuming. We present CAMSA: a tool for comparative analysis of multiple scaffold assemblies. It also provides several strategies for merging multiple assemblies together. We note that to our knowledge CAMSA is the only tool that treats both oriented and unoriented scaffold assemblies in a unifying way, thus providing a robust framework for a streamlined comprehensive analysis of both in silico and in vivo scaffolding results
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Aganezov_gwu_0075A_13493.pdf | 2025-04-11 | Open Access |
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