8 research outputs found

    Preferential access to genetic information from endogenous hominin ancient DNA and accurate quantitative SNP-typing via SPEX

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    The analysis of targeted genetic loci from ancient, forensic and clinical samples is usually built upon polymerase chain reaction (PCR)-generated sequence data. However, many studies have shown that PCR amplification from poor-quality DNA templates can create sequence artefacts at significant levels. With hominin (human and other hominid) samples, the pervasive presence of highly PCR-amplifiable human DNA contaminants in the vast majority of samples can lead to the creation of recombinant hybrids and other non-authentic artefacts. The resulting PCR-generated sequences can then be difficult, if not impossible, to authenticate. In contrast, single primer extension (SPEX)-based approaches can genotype single nucleotide polymorphisms from ancient fragments of DNA as accurately as modern DNA. A single SPEX-type assay can amplify just one of the duplex DNA strands at target loci and generate a multi-fold depth-of-coverage, with non-authentic recombinant hybrids reduced to undetectable levels. Crucially, SPEX-type approaches can preferentially access genetic information from damaged and degraded endogenous ancient DNA templates over modern human DNA contaminants. The development of SPEX-type assays offers the potential for highly accurate, quantitative genotyping from ancient hominin samples

    Debiasing the NEOWISE Cryogenic Mission Comet Populations

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    We use NEOWISE data from the four-band and three-band cryogenic phases of the Wide-field Infrared Survey Explorer mission to constrain size distributions of the comet populations and debias measurements of the short- and long-period comet (LPC) populations. We find that the fit to the debiased LPC population yields a cumulative size−frequency distribution (SFD) power-law slope (ÎČ) of −1.0 ± 0.1, while the debiased Jupiter-family comet (JFC) SFD has a steeper slope with ÎČ = −2.3 ± 0.2. The JFCs in our debiased sample yielded a mean nucleus size of 1.3 km in diameter, while the LPCs' mean size is roughly twice as large, 2.1 km, yielding mean size ratios (〈D_(LPC)〉/〈D_(JFC)〉) that differ by a factor of 1.6. Over the course of the 8 months of the survey, our results indicate that the number of LPCs passing within 1.5 au are a factor of several higher than previous estimates, while JFCs are within the previous range of estimates of a few thousand down to sizes near 1.3 km in diameter. Finally, we also observe evidence for structure in the orbital distribution of LPCs, with an overdensity of comets clustered near 110° inclination and perihelion near 2.9 au that is not attributable to observational bias

    A Bayesian Evaluation of Human Mitochondrial Substitution Rates

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    Accurate estimates of mitochondrial substitution rates are central to molecular studies of human evolution, but meaningful comparisons of published studies are problematic because of the wide range of methodologies and data sets employed. These differences are nowhere more pronounced than among rates estimated from phylogenies, genealogies, and pedigrees. By using a data set comprising mitochondrial genomes from 177 humans, we estimate substitution rates for various data partitions by using Bayesian phylogenetic analysis with a relaxed molecular clock. We compare the effect of multiple internal calibrations with the customary human-chimpanzee split. The analyses reveal wide variation among estimated substitution rates and divergence times made with different partitions and calibrations, with evidence of substitutional saturation, natural selection, and significant rate heterogeneity among lineages and among sites. Collectively, the results support dates for migration out of Africa and the common mitochondrial ancestor of humans that are considerably more recent than most previous estimates. Our results also demonstrate that human mitochondrial genomes exhibit a number of molecular evolutionary complexities that necessitate the use of sophisticated analytical models for genetic analyses

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