Patterns of genetic differentiation and the footprints of historical migrations in the Iberian Peninsula

Bycroft, Clare; Fernández–Rozadilla, Ceres; Ruíz-Ponte, Clara; Quintela, Inés; Carracedo, Ángel; Donnelly, Peter; Myers, Simon

doi:10.1038/s41467-018-08272-w

Cited by 73 publications

(74 citation statements)

References 40 publications

(76 reference statements)

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“…We therefore explored the impact of fine-scale genetic structure described in this study and others 4–11 on GWAS statistics, using the ALS study from which the Dutch data derive as an exemplar trait. Generally, population-based PCs should not predict case/control status; if they do, this indicates that (sub)populations are stratified between cases and controls, introducing bias that artificially inflates GWAS statistics.…”

Section: Discussionmentioning

confidence: 99%

“…Recent studies have showcased the power of leveraging shared haplotypes to uncover and characterise previously unrecognised fine-grained genetic structure within populations, yielding novel insights into the demographic composition and history of Britain and Ireland 4–7 , Finland 8 , Japan 9 , Italy 10 and Spain 11 . Haplotype sharing has also revealed genetic affinities between populations, enabling inference of historical admixture events using modern populations as proxies for ancestral admixing sources 12 .…”

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confidence: 99%

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Dutch population structure across space, time and GWAS design

Byrne

Rheenen

Berg

et al. 2020

Preprint

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We studied fine-grained population genetic structure and demographic change across the Netherlands using 1 genome-wide single nucleotide polymorphism data (1,626 individuals) with associated geography (1,422 2 individuals). We applied ChromoPainter/fineSTRUCTURE, identifying 40 haplotypic clusters exhibiting 3 strong north/south variation and fine-scale differentiation within provinces. Clustering is tied to country-wide 4 ancestry gradients from neighbouring lands and to locally restricted gene flow across major Dutch rivers. 5 Despite superexponential population growth, north-south structure is temporally stable, with west-east 6 differentiation more transient, potentially influenced by migrations during the middle ages. Within Dutch 7 and international data, GWAS incorporating fine-grained haplotypic covariates are less confounded than 8 standard methods. 9 The Netherlands is a densely populated country on the northwestern edge of the European continent, bounded by 10 Germany, Belgium and the North Sea. The country is divided into twelve provinces and has a complex demographic 11 history, with occupation by several Germanic peoples since the collapse of the Roman Empire, including the 12 Frisians, the Low Saxons and the Franks. Over 17 million individuals now inhabit this relatively small region 13 (41,500km 2 ), making it one of the most densely populated countries in Europe. Despite its small geographical size, 14 previous genetic studies of the people of the Netherlands have demonstrated coarse population structure that 15 correlates with its geography, as well as apparent heterogeneity in effective population sizes across provinces 1,2 . 16 These observations suggest that the demographic past of the Dutch population has left residual signatures in its 17 present regional genetic structure; however this has not been fully explained in the context of neighbouring 18 populations and thus far the use of unlinked genetic markers have limited the resolution at which this structure can 19 be described. This resolution limit also confines the extent to which the confounding effects of population structure 20 can be controlled in genomic studies of health and disease such as genome-wide association studies (GWAS). As 21 these studies continue to seek ever-rarer genetic variation with ever-increasing cohort sizes, intricate understanding 22 and fine control of population structure is becoming increasingly relevant, but increasingly challenging 3 . 23 Recent studies have showcased the power of leveraging shared haplotypes to uncover and characterise previously 24 unrecognised fine-grained genetic structure within populations, yielding novel insights into the demographic 25 composition and history of Britain and Ireland 4-7 , Finland 8 , Japan 9 , Italy 10 and Spain 11 . Haplotype sharing has also 26 revealed genetic affinities between populations, enabling inference of historical admixture events using modern 27 populations as proxies for ancestral admixing sources 12 . Furthermore, geographic informat...

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Section: Discussionmentioning

confidence: 99%

mentioning

confidence: 99%

Dutch population structure across space, time and GWAS design

Byrne

Rheenen

Berg

et al. 2020

Preprint

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“…Our use of an extensive dataset and the use of population clusters based on genetic homogeneity allowed us to detect and describe events of admixture with more precision than previous studies investigation the influence of North African gene-flow into surrounding regions. Recent methods based on haplotype information, such as those presented here, will illuminate the finer structure and genetic history of Iberian populations, particularly as sampling increases both in terms of numbers and geographical regions encompassed [47]. In the case of the Canary Islands, ancient DNA studies might also help to better understand the origin of the first settlers of the islands and identify its influence in modern populations [48].…”

Section: Discussionmentioning

confidence: 96%

Dissecting human North African gene-flow into its western coastal surroundings

2019

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North African history and populations have exerted a pivotal influence on surrounding geographical regions, although scant genetic studies have addressed this issue. Our aim is to understand human historical migrations in the coastal surroundings of North Africa. We built a refined genome-wide dataset of North African populations to unearth the fine-scale genetic structure of the region, using haplotype information. The results suggest that the gene-flow from North Africa into the European Mediterranean coast (Tuscany and the Iberian Peninsula) arrived mainly from the Mediterranean coast of North Africa. In Tuscany, this North African admixture date estimate suggests the movement of peoples during the fall of the Roman Empire around the fourth century. In the Iberian Peninsula, the North African component probably reflects the impact of the Arab expansion since the seventh century and the subsequent expansion of the Christian Kingdoms. By contrast, the North African component in the Canary Islands has a source genetically related to present-day people from the Atlantic North African coast. We also find sub-Saharan gene-flow from the Senegambia region in the Canary Islands. Specifically, we detect a complex signal of admixture involving Atlantic, Senegambian and European sources intermixing around the fifteenth century, soon after the Castilian conquest. Our results highlight the differential genetic influence of North Africa into the surrounding coast and show that specific historical events have not only had a socio-cultural impact but additionally modified the gene pool of the populations.

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“…In addition, latitude effect could be only noticeable at an international scale, such as European, and not in a single country. It is also possible that a geographic pattern in Spain could have been weakened due to internal migratory flows over the course of history [40].…”

Section: Discussionmentioning

confidence: 99%

Temporal and Cartographic Analyses of the Distribution within Spain of Mortality Due to Granulomatosis with Polyangiitis (1984–2016)

Sánchez-Díaz

Escobar

Villaverde-Hueso

et al. 2019

IJERPH

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The aim is to conduct a descriptive, population-based study in order to assess temporal and spatial changes in mortality due to granulomatosis with polyangiitis (GPA) in Spain from 1984 to 2016. Mortality data were obtained from the Spanish Annual Death Registry. Deaths in which GPA was the underlying cause were selected using the 446.4 and M31.3 codes from the International Classification of Diseases, 9th and 10th revision. Annual average age at death and age-adjusted mortality rates were calculated. Geographic analysis was performed at municipality and district level. Variations in mortality according to the type of municipality (urban, agro-urban or rural), district and geographic location (degrees of latitude) were assessed using standardized mortality ratios (SMRs) and smoothed-SMRs. Over the whole period, 620 deaths due to GPA were identified. Age at death increased at an average annual rate of 0.78% over the period 1987–2016 (p < 0.05). Age-adjusted mortality rates increased by an annual average of 20.58% from 1984 to 1992, after which they fell by 1.91% a year (p < 0.05). The agro-urban category had the highest percentage (4.57%) of municipalities with a significantly higher GPA mortality rate than expected. Geographic analysis revealed four districts with a higher risk of death due to GPA, two in the North of Spain and two in the South. This population-based study revealed an increase in the age at death attributed to GPA. Age-adjusted mortality rates went up sharply until 1992, after which they started to decline until the end of the study period. Geographic differences in mortality risk were identified but further studies will be necessary to ascertain the reasons for the distribution of GPA disease.

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Patterns of genetic differentiation and the footprints of historical migrations in the Iberian Peninsula

Cited by 73 publications

References 40 publications

Dutch population structure across space, time and GWAS design

Dutch population structure across space, time and GWAS design

Dissecting human North African gene-flow into its western coastal surroundings

Temporal and Cartographic Analyses of the Distribution within Spain of Mortality Due to Granulomatosis with Polyangiitis (1984–2016)

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