The population genomic legacy of the second plague pandemic

Abstract

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 17^th-19^th 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 F_ST 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.

Keywords: Trondheim; Yersinia pestis; pandemic genomics; plague; population genomics; population replacement; second plague pandemic; selection.

Figure 1

Estimated population size in Trondheim Illustrative reconstruction of Trondheim’s population size from 1,000 CE (based on Sandnes and Salvesen, Christophersen, and Sandnes and Supphellen⁹). Three major demographic phases were experienced: (1) an initial growth period up until around the 14th century, (2) a plague pandemic induced bottleneck followed by a low, fluctuating population size for ca. 300 years up to the mid-17th century, and (3) relatively rapid growth from ca. 1,650 CE. The midpoint of the estimate of the ages of samples from which genomic data were generated is shown on the x axis—for full age distributions see Table S1. See also Figure S1 and Data S1A.

Figure 2

Ancestry estimates of ancient and modern Trondheim individuals (A) Principal-component analysis projection of the ancient and modern Trondheim individuals on the principal components estimated in reference populations from Scandinavia and the British Isles. (B) Ancestry proportions estimated for ancient and modern Trondheim samples, visualized using a supervised ADMIXTURE analysis with modern Norse and Gaelic populations used as the two reference populations. The high proportion of Gaelic ancestry in SK339 can likely be attributed to its low sequencing coverage. (C) The mean Gaelic ancestry of the three temporal groups from Trondheim, based on the ADMIXTURE results with 95% CI shown as error bars. See also Figures S2 and S3.

Figure 3

Population-pairwise F_ST estimates The Bhatia-Hudson estimate of F_ST (uncorrected for reference genome bias) for each of the two-way population comparisons, computed across the entire genome in 500-kb overlapping windows, using a step size of 20 kb. See also Figure S4.

Figure 4

Reference bias among the historical samples The proportion of sites that are shared identical-by-state (IBS) to reference genome plotted as a function of sample characteristics. (A) The IBS values are plotted against the average autosomal sequencing depth of the samples. (B) The IBS values are plotted as a function of the length of mapped reads, for ancient and modern Trondheim individuals.