Birds as a Model for Comparative Genomic Studies

Comparative genomics provides a tool to investigate large biological datasets, i.e. genomic datasets. In my thesis I focused on inferring patterns of selection in coding and non-coding regions of avian genomes. Until recently, large comparative studies on selection were mainly restricted to model species with sequenced genomes. This limitation has been overcome with advances in sequencing technologies and it is now possible to gather large genomic data sets for non-model species. Next-generation sequencing data was used to study patterns of nucleotide substitutions and from this we inferred how selection has acted in the genomes of 10 non-model bird species. In general, we found evidence for a negative correlation between neutral substitution rate and chromosome size in birds. In a follow up study, we investigated two closely related bird species, to study expression levels in different tissues and pattern of selection. We found that between 2% and 18% of all genes were differentially expressed between the two species. We showed that non-coding regions adjacent to genes are under evolutionary constraint in birds, which suggests that noncoding DNA plays an important functional role in the genome. Regions downstream to genes (3’) showed particularly high level of constraint. The level of constraint in these regions was not correlated to the length of untranslated regions, which suggests that other causes play also a role in sequence conservation. We compared the rate of nonsynonymous substitutions to the rate of synonymous substitutions in order to infer levels of selection in protein-coding sequences. Synonymous substitutions are often assumed to evolve neutrally. We studied synonymous substitutions by estimating constraint on 4-fold degenerate sites of avian genes and found significant evolutionary constraint on this category of sites (between 24% and 43%). These results call for a reappraisal of synonymous substitution rates being used as neutral standards in molecular evolutionary analysis (e.g. the dN/dS ratio to infer positive selection). Finally, the problem of sequencing errors in next-generation sequencing data was investigated. We developed a program that removes erroneous bases from the reads. We showed that low coverage sequencing projects and large genome sequencing projects will especially gain from trimming erroneous reads