34 research outputs found

    Ancient reindeer mitogenomes reveal island-hopping colonisation of the Arctic archipelagos

    Get PDF
    Climate warming at the end of the last glacial period had profound effects on the distribution of cold-adapted species. As their range shifted towards northern latitudes, they were able to colonise previously glaciated areas, including remote Arctic islands. However, there is still uncertainty about the routes and timing of colonisation. At the end of the last ice age, reindeer/caribou (Rangifer tarandus) expanded to the Holarctic region and colonised the archipelagos of Svalbard and Franz Josef Land. Earlier studies have proposed two possible colonisation routes, either from the Eurasian mainland or from Canada via Greenland. Here, we used 174 ancient, historical and modern mitogenomes to reconstruct the phylogeny of reindeer across its whole range and to infer the colonisation route of the Arctic islands. Our data shows a close affinity among Svalbard, Franz Josef Land and Novaya Zemlya reindeer. We also found tentative evidence for positive selection in the mitochondrial gene ND4, which is possibly associated with increased heat production. Our results thus support a colonisation of the Eurasian Arctic archipelagos from the Eurasian mainland and provide some insights into the evolutionary history and adaptation of the species to its High Arctic habitat

    The population genomic legacy of the second plague pandemic

    Get PDF
    SummaryHuman populations have been shaped by catastrophes that may have left long-lasting signatures in their genomes. One notable example is the second plague pandemic that entered Europe in ca. 1,347 CE and repeatedly returned for over 300 years, with typical village and town mortality estimated at 10%–40%.1 It is assumed that this high mortality affected the gene pools of these populations. First, local population crashes reduced genetic diversity. Second, a change in frequency is expected for sequence variants that may have affected survival or susceptibility to the etiologic agent (Yersinia pestis).2 Third, mass mortality might alter the local gene pools through its impact on subsequent migration patterns. We explored these factors using the Norwegian city of Trondheim as a model, by sequencing 54 genomes spanning three time periods: (1) prior to the plague striking Trondheim in 1,349 CE, (2) the 17th–19th century, and (3) the present. We find that the pandemic period shaped the gene pool by reducing long distance immigration, in particular from the British Isles, and inducing a bottleneck that reduced genetic diversity. Although we also observe an excess of large FST values at multiple loci in the genome, these are shaped by reference biases introduced by mapping our relatively low genome coverage degraded DNA to the reference genome. This implies that attempts to detect selection using ancient DNA (aDNA) datasets that vary by read length and depth of sequencing coverage may be particularly challenging until methods have been developed to account for the impact of differential reference bias on test statistics.Results and discussion STAR★Method

    The population genomic legacy of the second plague pandemic

    Get PDF
    Human populations have been shaped by catastrophes that may have left long-lasting signatures in their genomes. One notable example is the second plague pandemic that entered Europe in ca. 1,347 CE and repeatedly returned for over 300 years, with typical village and town mortality estimated at 10%–40%.1 It is assumed that this high mortality affected the gene pools of these populations. First, local population crashes reduced genetic diversity. Second, a change in frequency is expected for sequence variants that may have affected survival or susceptibility to the etiologic agent (Yersinia pestis).2 Third, mass mortality might alter the local gene pools through its impact on subsequent migration patterns. We explored these factors using the Norwegian city of Trondheim as a model, by sequencing 54 genomes spanning three time periods: (1) prior to the plague striking Trondheim in 1,349 CE, (2) the 17th–19th century, and (3) the present. We find that the pandemic period shaped the gene pool by reducing long distance immigration, in particular from the British Isles, and inducing a bottleneck that reduced genetic diversity. Although we also observe an excess of large FST values at multiple loci in the genome, these are shaped by reference biases introduced by mapping our relatively low genome coverage degraded DNA to the reference genome. This implies that attempts to detect selection using ancient DNA (aDNA) datasets that vary by read length and depth of sequencing coverage may be particularly challenging until methods have been developed to account for the impact of differential reference bias on test statistics.publishedVersio

    The population genomic legacy of the second plague pandemic

    Get PDF
    Human populations have been shaped by catastrophes that may have left long-lasting signatures in their genomes. One notable example is the second plague pandemic that entered Europe in ca. 1,347 CE and repeatedly returned for over 300 years, with typical village and town mortality estimated at 10%-40%.1 It is assumed that this high mortality affected the gene pools of these populations. First, local population crashes reduced genetic diversity. Second, a change in frequency is expected for sequence variants that may have affected survival or susceptibility to the etiologic agent (Yersinia pestis).2 Third, mass mortality might alter the local gene pools through its impact on subsequent migration patterns. We explored these factors using the Norwegian city of Trondheim as a model, by sequencing 54 genomes spanning three time periods: (1) prior to the plague striking Trondheim in 1,349 CE, (2) the 17th-19th century, and (3) the present. We find that the pandemic period shaped the gene pool by reducing long distance immigration, in particular from the British Isles, and inducing a bottleneck that reduced genetic diversity. Although we also observe an excess of large FST values at multiple loci in the genome, these are shaped by reference biases introduced by mapping our relatively low genome coverage degraded DNA to the reference genome. This implies that attempts to detect selection using ancient DNA (aDNA) datasets that vary by read length and depth of sequencing coverage may be particularly challenging until methods have been developed to account for the impact of differential reference bias on test statistics

    Group 2i Isochrysidales produce characteristic alkenones reflecting sea ice distribution

    Get PDF
    AbstractAlkenones are biomarkers produced solely by algae in the order Isochrysidales that have been used to reconstruct sea surface temperature (SST) since the 1980s. However, alkenone-based SST reconstructions in the northern high latitude oceans show significant bias towards warmer temperatures in core-tops, diverge from other SST proxies in down core records, and are often accompanied by anomalously high relative abundance of the C37 tetra-unsaturated methyl alkenone (%C37:4). Elevated %C37:4 is widely interpreted as an indicator of low sea surface salinity from polar water masses, but its biological source has thus far remained elusive. Here we identify a lineage of Isochrysidales that is responsible for elevated C37:4 methyl alkenone in the northern high latitude oceans through next-generation sequencing and lab-culture experiments. This Isochrysidales lineage co-occurs widely with sea ice in marine environments and is distinct from other known marine alkenone-producers, namely Emiliania huxleyi and Gephyrocapsa oceanica. More importantly, the %C37:4 in seawater filtered particulate organic matter and surface sediments is significantly correlated with annual mean sea ice concentrations. In sediment cores from the Svalbard region, the %C37:4 concentration aligns with the Greenland temperature record and other qualitative regional sea ice records spanning the past 14 kyrs, reflecting sea ice concentrations quantitatively. Our findings imply that %C37:4 is a powerful proxy for reconstructing sea ice conditions in the high latitude oceans on thousand- and, potentially, on million-year timescales.</jats:p
    corecore