PLoS ONE (Jan 2022)

The effective family size of immigrant founders predicts their long-term demographic outcome: From Québec settlers to their 20th-century descendants.

  • Damian Labuda,
  • Tommy Harding,
  • Emmanuel Milot,
  • Hélène Vézina

DOI
https://doi.org/10.1371/journal.pone.0266079
Journal volume & issue
Vol. 17, no. 5
p. e0266079

Abstract

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Population history reconstruction, using extant genetic diversity data, routinely relies on simple demographic models to project the past through ascending genealogical-tree branches. Because genealogy and genetics are intimately related, we traced descending genealogies of the Québec founders to pursue their fate and to assess their contribution to the present-day population. Focusing on the female and male founder lines, we observed important sex-biased immigration in the early colony years and documented a remarkable impact of these early immigrants on the genetic make-up of 20th-century Québec. We estimated the immigrants' survival ratio as a proportion of lineages found in the 1931-60 Québec to their number introduced within the immigration period. We assessed the effective family size, EFS, of all immigrant parents and their Québec-born descendants. The survival ratio of the earliest immigrants was the highest and declined over centuries in association with the immigrants' EFS. Parents with high EFS left plentiful married descendants, putting EFS as the most important variable determining the parental demographic success throughout time for generations ahead. EFS of immigrant founders appears to predict their long-term demographic and, consequently, their genetic outcome. Genealogically inferred immigrants' "autosomal" genetic contribution to 1931-60 Québec from consecutive immigration periods follow the same yearly pattern as the corresponding maternal and paternal lines. Québec genealogical data offer much broader information on the ancestral diversity distribution than genetic scrutiny of a limited population sample. Genealogically inferred population history could assist studies of evolutionary factors shaping population structure and provide tools to target specific health interventions.