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      Ancient DNA reveals differences in behaviour and sociality between brown bears and extinct cave bears

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          Abstract

          Ancient DNA studies have revolutionized the study of extinct species and populations, providing insights on phylogeny, phylogeography, admixture and demographic history. However, inferences on behaviour and sociality have been far less frequent. Here, we investigate the complete mitochondrial genomes of extinct Late Pleistocene cave bears and middle Holocene brown bears that each inhabited multiple geographically proximate caves in northern Spain. In cave bears, we find that, although most caves were occupied simultaneously, each cave almost exclusively contains a unique lineage of closely related haplotypes. This remarkable pattern suggests extreme fidelity to their birth site in cave bears, best described as homing behaviour, and that cave bears formed stable maternal social groups at least for hibernation. In contrast, brown bears do not show any strong association of mitochondrial lineage and cave, suggesting that these two closely related species differed in aspects of their behaviour and sociality. This difference is likely to have contributed to cave bear extinction, which occurred at a time in which competition for caves between bears and humans was likely intense and the ability to rapidly colonize new hibernation sites would have been crucial for the survival of a species so dependent on caves for hibernation as cave bears. Our study demonstrates the potential of ancient DNA to uncover patterns of behaviour and sociality in ancient species and populations, even those that went extinct many tens of thousands of years ago.

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          Is Open Access

          Double indexing overcomes inaccuracies in multiplex sequencing on the Illumina platform

          Due to the increasing throughput of current DNA sequencing instruments, sample multiplexing is necessary for making economical use of available sequencing capacities. A widely used multiplexing strategy for the Illumina Genome Analyzer utilizes sample-specific indexes, which are embedded in one of the library adapters. However, this and similar multiplex approaches come with a risk of sample misidentification. By introducing indexes into both library adapters (double indexing), we have developed a method that reveals the rate of sample misidentification within current multiplex sequencing experiments. With ~0.3% these rates are orders of magnitude higher than expected and may severely confound applications in cancer genomics and other fields requiring accurate detection of rare variants. We identified the occurrence of mixed clusters on the flow as the predominant source of error. The accuracy of sample identification is further impaired if indexed oligonucleotides are cross-contaminated or if indexed libraries are amplified in bulk. Double-indexing eliminates these problems and increases both the scope and accuracy of multiplex sequencing on the Illumina platform.
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            Correlating viral phenotypes with phylogeny: accounting for phylogenetic uncertainty.

            Many recent studies have sought to quantify the degree to which viral phenotypic characters (such as epidemiological risk group, geographic location, cell tropism, drug resistance state, etc.) are correlated with shared ancestry, as represented by a viral phylogenetic tree. Here, we present a new Bayesian Markov-Chain Monte Carlo approach to the investigation of such phylogeny-trait correlations. This method accounts for uncertainty arising from phylogenetic error and provides a statistical significance test of the null hypothesis that traits are associated randomly with phylogeny tips. We perform extensive simulations to explore and compare the behaviour of three statistics of phylogeny-trait correlation. Finally, we re-analyse two existing published data sets as case studies. Our framework aims to provide an improvement over existing methods for this problem.
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              Is Open Access

              Global Conservation Priorities for Marine Turtles

              Where conservation resources are limited and conservation targets are diverse, robust yet flexible priority-setting frameworks are vital. Priority-setting is especially important for geographically widespread species with distinct populations subject to multiple threats that operate on different spatial and temporal scales. Marine turtles are widely distributed and exhibit intra-specific variations in population sizes and trends, as well as reproduction and morphology. However, current global extinction risk assessment frameworks do not assess conservation status of spatially and biologically distinct marine turtle Regional Management Units (RMUs), and thus do not capture variations in population trends, impacts of threats, or necessary conservation actions across individual populations. To address this issue, we developed a new assessment framework that allowed us to evaluate, compare and organize marine turtle RMUs according to status and threats criteria. Because conservation priorities can vary widely (i.e. from avoiding imminent extinction to maintaining long-term monitoring efforts) we developed a “conservation priorities portfolio” system using categories of paired risk and threats scores for all RMUs (n = 58). We performed these assessments and rankings globally, by species, by ocean basin, and by recognized geopolitical bodies to identify patterns in risk, threats, and data gaps at different scales. This process resulted in characterization of risk and threats to all marine turtle RMUs, including identification of the world's 11 most endangered marine turtle RMUs based on highest risk and threats scores. This system also highlighted important gaps in available information that is crucial for accurate conservation assessments. Overall, this priority-setting framework can provide guidance for research and conservation priorities at multiple relevant scales, and should serve as a model for conservation status assessments and priority-setting for widespread, long-lived taxa.
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                Author and article information

                Journal
                Molecular Ecology
                Mol Ecol
                Wiley-Blackwell
                09621083
                October 2016
                October 06 2016
                : 25
                : 19
                : 4907-4918
                Article
                10.1111/mec.13800
                27506329
                919bcce8-3dfd-40bd-bdbe-115560eb4f38
                © 2016

                http://doi.wiley.com/10.1002/tdm_license_1.1

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