TY - JOUR A1 - Yuan, Junxia A1 - Sheng, Guilian A1 - Preick, Michaela A1 - Sun, Boyang A1 - Hou, Xindong A1 - Chen, Shungang A1 - Taron, Ulrike Helene A1 - Barlow, Axel A1 - Wang, Linying A1 - Hu, Jiaming A1 - Deng, Tao A1 - Lai, Xulong A1 - Hofreiter, Michael T1 - Mitochondrial genomes of Late Pleistocene caballine horses from China belong to a separate clade JF - Quaternary science reviews : the international multidisciplinary research and review journal N2 - There were several species of Equus in northern China during the Late Pleistocene, including Equus przewalskii and Equus dalianensis. A number of morphological studies have been carried out on E. przewalskii and E. dalianensis, but their evolutionary history is still unresolved. In this study, we retrieved near-complete mitochondrial genomes from E. dalianensis and E. przewalskii specimens excavated from Late Pleistocene strata in northeastern China. Phylogenetic analyses revealed that caballoid horses were divided into two subclades: the New World and the Old World caballine horse subclades. The Old World caballine horses comprise of two deep phylogenetic lineages, with modern and ancient Equus caballus and modern E. przewalskii forming lineage I, and the individuals in this study together with one Yakut specimen forming lineage II. Our results indicate that Chinese Late Pleistocene caballoid horses showed a closer relationship to other Eurasian caballine horses than that to Pleistocene horses from North America. In addition, phylogenetic analyses suggested a close relationship between E. dalianensis and the Chinese fossil E. przewalskii, in agreement with previous researches based on morphological analyses. Interestingly, E. dalianensis and the fossil E. przewalskii were intermixed rather than split into distinct lineages, suggesting either that gene flow existed between these two species or that morphology-based species assignment of palaeontological specimens is not always correct. Moreover, Bayesian analysis showed that the divergence time between the New World and the Old World caballoid horses was at 1.02 Ma (95% CI: 0.86-1.24 Ma), and the two Old World lineages (I & II) split at 0.88 Ma (95% CI: 0.69-1.13 Ma), which indicates that caballoid horses seem to have evolved into different populations in the Old World soon after they migrated from North America via the Bering Land Bridge. Finally, the TMRCA of E. dalianensis was estimated at 0.20 Ma (95% CI: 0.15-0.28 Ma), and it showed a relative low genetic diversity compared with other Equus species. KW - Equus dalianensis KW - Equus przewalskii KW - Pleistocene caballine horses KW - ancient DNA KW - phylogenetic relationship KW - divergence time Y1 - 2020 U6 - https://doi.org/10.1016/j.quascirev.2020.106691 SN - 0277-3791 VL - 250 PB - Elsevier CY - Amsterdam [u.a.] 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 - 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 - 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 -