TY - JOUR A1 - Hofreiter, Michael A1 - Hartmann, Stefanie T1 - Reconstructing protein-coding sequences from ancient DNA JF - Odorant binding and chemosensory proteins N2 - 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. KW - re-sequencing KW - mapping KW - genome assembly KW - targeted assembly KW - SRAssembler KW - ancient DNA KW - reference sequence KW - paleogenomics Y1 - 2020 SN - 978-0-12-821157-1 U6 - https://doi.org/10.1016/bs.mie.2020.05.008 SN - 0076-6879 VL - 642 SP - 21 EP - 33 PB - Academic Press, an imprint of Elsevier CY - Cambridge, MA. ER - TY - GEN A1 - Westbury, Michael V. A1 - Baleka, Sina Isabelle A1 - Barlow, Axel A1 - Hartmann, Stefanie A1 - Paijmans, Johanna L. A. A1 - Kramarz, Alejandro A1 - Forasiepi, Analía M. A1 - Bond, Mariano A1 - Gelfo, Javier N. A1 - Reguero, Marcelo A. A1 - López-Mendoza, Patricio A1 - Taglioretti, Matias A1 - Scaglia, Fernando A1 - Rinderknecht, Andrés A1 - Jones, Washington A1 - Mena, Francisco A1 - Billet, Guillaume A1 - de Muizon, Christian A1 - Aguilar, José Luis A1 - MacPhee, Ross D.E. A1 - Hofreiter, Michael T1 - A mitogenomic timetree for Darwin's enigmatic South American mammal Macrauchenia patachonica T2 - Postprints der Universität Potsdam Mathematisch-Naturwissenschaftliche Reihe N2 - The unusual mix of morphological traits displayed by extinct South American native ungulates (SANUs) confounded both Charles Darwin, who first discovered them, and Richard Owen, who tried to resolve their relationships. Here we report an almost complete mitochondrial genome for the litoptern Macrauchenia. Our dated phylogenetic tree places Macrauchenia as sister to Perissodactyla, but close to the radiation of major lineages within Laurasiatheria. This position is consistent with a divergence estimate of B66Ma (95% credibility interval, 56.64-77.83 Ma) obtained for the split between Macrauchenia and other Panperissodactyla. Combined with their morphological distinctiveness, this evidence supports the positioning of Litopterna (possibly in company with other SANU groups) as a separate order within Laurasiatheria. We also show that, when using strict criteria, extinct taxa marked by deep divergence times and a lack of close living relatives may still be amenable to palaeogenomic analysis through iterative mapping against more distant relatives. T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 793 KW - ancient DNA KW - evolutionary history KW - genome sequence KW - reveals KW - contamination KW - alignment KW - reads KW - bones Y1 - 2019 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-440801 SN - 1866-8372 IS - 793 ER - TY - GEN A1 - Barlow, Axel A1 - Hartmann, Stefanie A1 - Gonzalez, Javier A1 - Hofreiter, Michael A1 - Paijmans, Johanna L. A. T1 - Consensify BT - a method for generating pseudohaploid genome sequences from palaeogenomic datasets with reduced error rates T2 - Postprints der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe N2 - A standard practise in palaeogenome analysis is the conversion of mapped short read data into pseudohaploid sequences, frequently by selecting a single high-quality nucleotide at random from the stack of mapped reads. This controls for biases due to differential sequencing coverage, but it does not control for differential rates and types of sequencing error, which are frequently large and variable in datasets obtained from ancient samples. These errors have the potential to distort phylogenetic and population clustering analyses, and to mislead tests of admixture using D statistics. We introduce Consensify, a method for generating pseudohaploid sequences, which controls for biases resulting from differential sequencing coverage while greatly reducing error rates. The error correction is derived directly from the data itself, without the requirement for additional genomic resources or simplifying assumptions such as contemporaneous sampling. For phylogenetic and population clustering analysis, we find that Consensify is less affected by artefacts than methods based on single read sampling. For D statistics, Consensify is more resistant to false positives and appears to be less affected by biases resulting from different laboratory protocols than other frequently used methods. Although Consensify is developed with palaeogenomic data in mind, it is applicable for any low to medium coverage short read datasets. We predict that Consensify will be a useful tool for future studies of palaeogenomes. T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 1033 KW - palaeogenomics KW - ancient DNA KW - sequencing error KW - error reduction KW - D statistics KW - bioinformatics Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-472521 SN - 1866-8372 IS - 1033 ER - TY - JOUR A1 - Barlow, Axel A1 - Hartmann, Stefanie A1 - Gonzalez, Javier A1 - Hofreiter, Michael A1 - Paijmans, Johanna L. A. T1 - Consensify BT - a method for generating pseudohaploid genome sequences from palaeogenomic datasets with reduced error rates JF - Genes / Molecular Diversity Preservation International N2 - A standard practise in palaeogenome analysis is the conversion of mapped short read data into pseudohaploid sequences, frequently by selecting a single high-quality nucleotide at random from the stack of mapped reads. This controls for biases due to differential sequencing coverage, but it does not control for differential rates and types of sequencing error, which are frequently large and variable in datasets obtained from ancient samples. These errors have the potential to distort phylogenetic and population clustering analyses, and to mislead tests of admixture using D statistics. We introduce Consensify, a method for generating pseudohaploid sequences, which controls for biases resulting from differential sequencing coverage while greatly reducing error rates. The error correction is derived directly from the data itself, without the requirement for additional genomic resources or simplifying assumptions such as contemporaneous sampling. For phylogenetic and population clustering analysis, we find that Consensify is less affected by artefacts than methods based on single read sampling. For D statistics, Consensify is more resistant to false positives and appears to be less affected by biases resulting from different laboratory protocols than other frequently used methods. Although Consensify is developed with palaeogenomic data in mind, it is applicable for any low to medium coverage short read datasets. We predict that Consensify will be a useful tool for future studies of palaeogenomes. KW - palaeogenomics KW - ancient DNA KW - sequencing error KW - error reduction KW - D statistics KW - bioinformatics Y1 - 2020 U6 - https://doi.org/10.3390/genes11010050 SN - 2073-4425 VL - 11 IS - 1 PB - MDPI CY - Basel ER -