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Obtaining information about functional details of proteins of extinct species is of critical importance for a better understanding of the real-life appearance, behavior and ecology of these lost entries in the book of life. In this chapter, we discuss the possibilities to retrieve the necessary DNA sequence information from paleogenomic data obtained from fossil specimens, which can then be used to express and subsequently analyze the protein of interest. We discuss the problems specific to ancient DNA, including mis-coding lesions, short read length and incomplete paleogenome assemblies. Finally, we discuss an alternative, but currently rarely used approach, direct PCR amplification, which is especially useful for comparatively short proteins.
Background
Contiguous genome assemblies are a highly valued biological resource because of the higher number of completely annotated genes and genomic elements that are usable compared to fragmented draft genomes. Nonetheless, contiguity is difficult to obtain if only low coverage data and/or only distantly related reference genome assemblies are available.
Findings
In order to improve genome contiguity, we have developed Cross-Species Scaffolding—a new pipeline that imports long-range distance information directly into the de novo assembly process by constructing mate-pair libraries in silico.
Conclusions
We show how genome assembly metrics and gene prediction dramatically improve with our pipeline by assembling two primate genomes solely based on ∼30x coverage of shotgun sequencing data.
Background
Contiguous genome assemblies are a highly valued biological resource because of the higher number of completely annotated genes and genomic elements that are usable compared to fragmented draft genomes. Nonetheless, contiguity is difficult to obtain if only low coverage data and/or only distantly related reference genome assemblies are available.
Findings
In order to improve genome contiguity, we have developed Cross-Species Scaffolding—a new pipeline that imports long-range distance information directly into the de novo assembly process by constructing mate-pair libraries in silico.
Conclusions
We show how genome assembly metrics and gene prediction dramatically improve with our pipeline by assembling two primate genomes solely based on ∼30x coverage of shotgun sequencing data.