Using reference-assisted chromosome assemblies to study chromosome structures and evolution in vertebrates

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Genomes contain genes that encode proteins that build organisms. In the course of evolution genomes change and these changes affect genes by changing the time when proteins are formed or even leading to formation of new genes or death of old genes. These events together form one of the sources of variations used by the natural selection to form new species or for species adaptation to the environment. Complete sequencing of a genome refers to the identification of the sequence of nucleotides along chromosomes. To understand what mechanisms drive changes in chromosome structures in different species and how this affects formation of new species or an adaptation of existing species to changing environment we will reconstruct complete chromosome structures of newly sequenced species using an novel algorithm called "reference-assisted chromosome assembly" or RACA. This algorithm compares sequenced parts of one organism' genome to existing complete chromosome assembly of another and reconstructs chromosomes of their putative common ancestor. Then it uses parts of the newly sequenced genome and searches for the differences between the ancestral organization of chromosomes and the organization proposed by parts of chromosomes that are generated for the organism. At the final step it organizes parts or ancestral chromosomes according to the order proposed by sequence scaffolds. In the research proposed in this proposal we will develop several algorithms to verify these reconstructions by looking at the specific features of chromosomes like "telomeres" - chromosome ends and "centromeres" - important for cell division. These structures contain specific sequence features that could be reconstructed from the sequence data produced during sequencing projects. By detecting positions of these features in the reconstructed chromosomes we will be able to check how close the structure of reconstructed chromosomes is to real chromosomes in the species of interest. If there are issues, we will adapt the RACA algorithm to improve the assembly. In the next step we will use RACA-generated chromosomes to investigate mechanisms driving chromosomal changes at the DNA level. We will check if the distribution of chromosome parts that are not rearranged in all genomes included in our analysis can be explained by the random breakage of chromosomes in evolution, or if there is a selection against chromosomal rearrangements in some parts of a vertebrate genome. If we analyze a large set of species we might be able to find "built blocks" of mammalian, amniote, or vertebrate genomes that cannot be rearranged without a lethal effect for the organism. Evolutionary breakpoint regions are regions of chromosomes where chromosomes were broken and then rejoined in a different combinations or orientation in evolution. We will use multiple RACA genomes to investigate what features of the genomes are driving these events. An important question to answer is "which genes would more likely be affected by these evolutionary events?" Previously we demonstrated that the evolutionary breakpoint regions are enriched for the genes that are associated with the lineage-specific features. In this project we will perform bioinformatics analysis of these intervals in an attempt to classify lineage-specific changes that happened in ancestral genomes of some lineages leading to the formation of their specific traits chosen by natural selection, e.g., formation of the rumen in ruminant species. Our hypothesis is that the changes in ancestral genomes of the livestock species will be connected to those features of the species that made them attractive source of proteins for humans. Therefore, detection of these ancestral changes is an important step for improving genetics of these species as it will identify best gene and other targets for future artificial selection and breed improvement.