Human genetic structure in Northwest France provides new insights into West European historical demography

Abstract

The demographical history of France remains largely understudied despite its central role toward understanding modern population structure across Western Europe. Here, by exploring publicly available Europe-wide genotype datasets together with the genomes of 3234 present-day and six newly sequenced medieval individuals from Northern France, we found extensive fine-scale population structure across Brittany and the downstream Loire basin and increased population differentiation between the northern and southern sides of the river Loire, associated with higher proportions of steppe vs. Neolithic-related ancestry. We also found increased allele sharing between individuals from Western Brittany and those associated with the Bell Beaker complex. Our results emphasise the need for investigating local populations to better understand the distribution of rare (putatively deleterious) variants across space and the importance of common genetic legacy in understanding the sharing of disease-related alleles between Brittany and people from western Britain and Ireland.

Fig. 1. Population structure, linguistics, and patronym distribution in Northwestern France.

a fineSTRUCTURE clustering of 3234 samples from Brittany and the downstream Loire basin at k = 3. WBR stands for Western Brittany, EBP for Eastern Brittany and Pays-de-la-Loire and SLO for South Loire. b Distribution of the Breton language over time. Loth line 1, attested by the border between Celtic place names in –ac (on the west side) and Romance place names in –é (on the east side), represents the westernmost boundary between Armorican Gaulish and Gallo-Romance spoken varieties (25). Loth line 2 represents the Celto-Romance linguistic border in the 16th century CE. Grey lines encircle political territorial divisions called départements. Only départements belonging to the regions of Brittany and Pays-de-la-Loire are coloured. In the inset, the départements are abbreviated as FIN (Finistère), COT (Côtes-d’Armor), MOR (Morbihan), ILL (Ille-et-Vilaine), MAY (Mayenne), SAR (Sarthe), MAI (Maine-et-Loire), LOI (Loire-Atlantique), VEN (Vendée). c Neighbour Joining tree from pairwise Arccos distances (68) computed on the distribution of surnames between pairs of arrondissements from Northwestern France. The support of the tree nodes was obtained by bootstrapping 1000 times the distance matrices. d 18 genetic clusters identified using total variation distances (TVD) from the fineSTRUCTURE results (see Material and Methods for details). The TVD-based tree was cut at k = 39 and to ease visualisation we merged clusters with <5 individuals into the closest cluster (>= 31 individuals) resulting in a tree with 18 clusters. All the clusters have at least 31 individuals. The TVD-based tree is sample size independent and is more informative on cluster genetic affinities. The tree was built using the clustree and ggtree packages of R-statistical software and the map with the following R libraries: sp as in (a, b). In (a) and (c), individuals are coloured according to their cluster assignment. Individuals’ coordinates correspond to the most common grandparents’ birthplace.

Fig. 2. Allele sharing within and between populations.

Proportions of individuals assigned to different clusters for each département in Northwestern France (see Fig. 1b), using hierarchical clustering on levels of rare allele sharing between pairs of individuals. Allele-sharing matrices were computed for alleles present in two chromosomes (MAC 2) and three to 10 chromosome copies (MAC 3–10) across 620 individuals from Northwestern France and from one million randomly selected sites. Maps were generated with the R statistical package together with the following libraries: ComplexHeatmap, rgdal, sp, broom, ggplot2 and scatterpie.

Fig. 3. PCA and supervised admixture analysis of present-day western Europeans.

a The two first principal components of genetic variation in the “modern merged dataset”, which includes 843 French WGSs for which the four grand-parent origin was concordant, and genome-wide data from 20 central and western European populations^,(population acronyms below, see Methods for further details). To avoid bias due to sample size differences among regions, all locations are represented by a maximum of 100 individuals resulting in a total of 2070 samples and 201,999 independent SNPs (MAF > 4%). For simpler visualisation samples from Norway, Sweden, and Denmark were labelled as “Scandinavia”, samples from Belgium and Germany were labelled as “Central Europe”. FranceGenRef samples are represented by dots and labelled with boxes while non-French samples are represented by 2*sd of the two PCs. UK samples other than those from the POBI dataset, whose origin of the grandparents is known, are not shown. Similarly, French samples from public datasets are also not shown. To better visualise the distribution of our samples the plot is a zoom of the full PCA (Fig. S20). b Ancestry proportions retrieved from a Supervised Admixture analysis considering Ireland, Spain, and Germany as proxy source populations on the basis of their polarised positions relative to the distribution of the 843 French samples on (a). In the boxplot the central mark and edges indicate the 50th (median), 25th and 75th percentiles. Whiskers encompass the largest or smallest point comprised within 1.5× of the interquartile range from both edges.

Fig. 4. Genetic affinities between Brittany and Ireland/West British Isles from f-statistics.

a Heatmap reporting outgroup f3-statistics in the form f3(Mbuti; French population/cluster, X), where French population/cluster is represented on the y-axis and X on the x-axis. b f₄-statistics of the form f₄(Mbuti, French cluster; Dyfed, X), where X are the populations on the right side of the plot. Due to disparities in samples sizes, both the outgroup f₃- and f₄-statistics were computed on a n = 25 samples/population, excepting for the Mbuti (n = 10), Basque (n = 20), Normandy (n = 19) and the Orcadians (n = 13). In bold are represented f4-statistics values with a corresponding |Z | > 3 and ranges correspond the standard deviation (sd) from weighted block jackknife. Cluster acronyms: western Brittany (WBR), eastern Brittany and Pays-de-la-Loire (EBP), south Loire (SLO). Region/country acronyms: Brittany (BRI); Pays-de-la-Loire (PAY); Normandie (NOR); Hauts-de-France (HAU); Grand Est (GRA); Centre-Val de Loire (CEN); Nouvelle-Aquitaine (NOU), Basque Country (Basq), Belgium (Belg), Cornwall (Corn), Denmark (Denm), Dyfed (Dyfe), Finland (Finl), Germany (Germ), Gwynedd (Gwyn), Ireland (Irel), Italy (Ital), Kent (Kent), Norfolk (Norf), Northern Ireland (NIrel), Norway (Norw), Orkney Islands (Orca), Poland (Pola), Sardinia (Sard), Spain (Spai), Sweden (Swed), United Kingdom (UK). Plots were generated with the R statistical package and the heatmap with the library lattice.

Fig. 5. Genetic continuity, admixture and relationship between modern and ancient French populations.

a Timeline of the ancient individuals used to test one- and two-way models of admixture for the ancestry of present-day French using qpAdm. The numbers in brackets represent the sample sizes. b Mixture proportions from the three major populations contributing to the European ancestry using three-way admixture model, where each population on the left (y-axis) is modelled as a mixture of Mesolithic Western Hunter-Gatherer- (WHG), Neolithic early farmers- (EF) and Early Bronze Age Steppe- (SP) derived ancestry. c Shared drift between Bell-Beaker-associated individuals and present-day Europeans by means of the outgroup f₃-statistics of the form f₃(Mbuti; Bell Beaker Pop, X), where X is the population on the x-axis. These analyses were performed on the “ancient merged dataset” (, see Material and Methods for details). Plots were generated with the R statistical package and the heatmap as explained in Fig. 5a.