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Heritability and Genetic Constraints of Life-History Trait Evolution in Preindustrial Humans

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Heritability and Genetic Constraints of Life-History Trait Evolution in Preindustrial Humans Heritability and genetic constraints of life-history trait evolution in preindustrial humans Jenni E. Pettay*†, Loeske E. B. Kruuk‡, Jukka Jokela§, and Virpi Lummaa¶ *Section of Ecology, Department of Biology, University of Turku, FIN-20014, Turku, Finland; ‡Institute of Evolutionary Biology, School of Biological Sciences, University of Edinburgh, Edinburgh EH9 3JT, United Kingdom; §Department of Biology, University of Oulu, POB 3000, FIN-90014, Oulu, Finland; and ¶Department of Animal and Plant Sciences, University of Sheffield, Sheffield S10 2TN, United Kingdom Edited by Kristen Hawkes, University of Utah, Salt Lake City, UT, and approved January 4, 2005 (received for review September 10, 2004) An increasing number of studies have documented phenotypic vals were independent both of ages at first and last reproduction, selection on life-history traits in human populations, but less is whereas women who started to reproduce early also ceased known of the heritability and genetic constraints that mediate the reproduction young (10). Last, Strassmann and Gillespie (14) response to selection on life-history traits in humans. We collected showed evidence for a nonlinear relationship between female pedigree data for four generations of preindustrial (1745–1900) fecundity and reproductive success in Dogon farmers of Mali Finns who lived in premodern fertility and mortality conditions, because child mortality, rather than fecundity, was the primary and by using a restricted maximum-likelihood animal-model determinant of female fitness in this population. framework, we estimated the heritability of and genetic correla- From an evolutionary point of view, these correlations are tions between a suite of life-history traits and two alternative particularly interesting if they have a genetic basis, because measures of fitness. First, we demonstrate high heritability of key natural selection can lead to an evolutionary response only when life-history traits (fecundity, interbirth interval, age at last repro- it acts on a heritable character. However, estimating the heri- duction, and adult longevity) and measures of fitness (individual ␭ tability of human life-history traits is problematic, because the and lifetime reproductive success) for females but not for males. effects of common environments shared by close relatives and This sex difference may have arisen because most of the measured cultural transmission can inflate estimates of heritability. Twin traits are under physiological control of the female, such that a studies, in which identical twins are raised in different environ- male’s fitness in monogamous societies may depend mainly on the ments, are ideal for investigating such issues, but these kinds of reproductive quality of his spouse. We found strong positive data for humans are scarce. Consequently, little is known about genetic correlations between female age at first reproduction and whether the documented phenotypic selection on human life- longevity, and between interbirth intervals and longevity, sug- history traits could lead to changes over time because of the lack gesting reduced life spans in females who either started to breed of information on the heritability and genetic constraints of relatively early or who then bred frequently. Our results suggest reproductive traits in natural-state human populations (15). that key female life-history traits in this premodern human pop- An alternative approach to twin studies, which we adopt here, ulation had high heritability and may have responded to natural is to use a methodology that controls for common environment selection. However genetic constraints between longevity and effects as much as possible and considers the similarity between reproductive life-history traits may have constrained the evolution pairs of individuals of various degrees of relatedness, for which of life history and facilitated the maintenance of additive genetic shared environment may not be such a problem (16). In this variance in key life-history traits. study, we applied restricted maximum-likelihood (REML) esti- mation and an ‘‘animal model’’ to estimate heritabilities and genetic correlation ͉ Homo sapiens ͉ animal model ͉ natural selection ͉ genetic correlations between female and male life-history traits. tradeoff The advantage of this technique compared with more tradition- ally used parent–offspring and sibling regression analyses is that he cultural and biological factors that determine human it simultaneously incorporates information from a variety of Tlife-history evolution are of interest to scientists from several relationships of different degrees, such as offspring, parents, different fields of science. Evolutionary biologists and anthro- grandparents, full-siblings, and half-siblings, which makes it a pologists are interested in revealing the importance of different more powerful method than the traditional approaches (17, 18). life-history traits in affecting fitness and longevity and whether REML analyses also have less strict assumptions about selection these traits are under natural selection. Many studies have patterns or inbreeding and do not require balanced data sets, reported phenotypic correlations between different life-history which makes them considerably more amenable to data from traits, longevity, and measures of fitness in humans, but the natural populations (17, 18). nature of such associations is often contradictory. For example, In this article, our aims were to (i) estimate the heritability of although some studies have shown negative effects of high total human life-history traits, (ii) examine genetic correlations be- reproductive effort on postreproductive longevity (1–3), most tween the life-history traits and different fitness measures, and studies have found no association, or even positive correlations, (iii) compare the estimates obtained for male and female traits. between total reproductive effort and longevity (4–10). Like- We used pedigree data collected from genealogical records from wise, some studies have shown a negative relationship between preindustrial Finland. These records cover a historical era before age at first reproduction (AFR) and postreproductive mortality the availability of advanced medical care or modern birth- (1, 11), whereas others found no evidence for such an association control methods. We found that the key female life-history traits (6, 12, 13). In a historical northern Finnish population, the most were highly heritable, allowing rapid evolutionary response to important component of female fitness (i.e., the phenotypic trait with the highest selection differential) was the number of delivered offspring, but women also gained higher fitness (larger This paper was submitted directly (Track II) to the PNAS office. total number of offspring raised to adulthood over lifetime) if Abbreviations: AFR, age at first reproduction; LRS, lifetime reproductive success; MIBI, they began reproducing earlier, had shorter interbirth intervals, mean interbirth interval; ALR, age at last reproduction. and continued reproducing later (10). Phenotypic covariation †To whom correspondence should be addressed. E-mail: jenni.pettay@utu.fi. between female life-history traits indicated that interbirth inter- © 2005 by The National Academy of Sciences of the USA 2838–2843 ͉ PNAS ͉ February 22, 2005 ͉ vol. 102 ͉ no. 8 www.pnas.org͞cgi͞doi͞10.1073͞pnas.0406709102 Downloaded by guest on September 29, 2021 selection, but we also found considerable genetic constraints Lifetime reproductive success (LRS). LRS was measured as the total between reproductive traits and longevity. number of children produced in a lifetime that survived to adolescence (here, to 15 years of age). Methods Individual ␭ (calculated according to the method of McGraw and Caswell, Population Sample. We collected pedigrees of life-history data ref. 23). This measure considers at the same time both the timing following four generations of preindustrial Finns by using a large of reproduction and the number of children raised to adulthood genealogical database (Genealogia Sursilliana CD-2000 data- (15 years of age). LRS and ␭ may rank individuals differently base, I. B. Voipio, personal communication) (19). Our data set according to their fitness, because children produced at early includes 194 base individuals from the following four different ages contribute more to the fitness than children produced at parishes: Oulu, Kokkola, and Kaarlela in western Finland, and later ages. Rate-sensitive ␭ allows for more accurate estimation Kuusamo in eastern Finland. Base individuals (for whom parents of individual fitness in humans, even though overall reproductive were not known) were born in 1745–1765, and the data set success explains Ͼ90% of the variation in ␭ (24). The value of includes all of their descendants to the great-grandchildren level ␭ was calculated with MATLAB software (Mathworks, Natick, as well as spouses of all married individuals, giving a total of MA) by using a program written by J.J. (available by request). 5,018 individuals with latest birth date of 1903. Complete Fecundity. This trait was calculated as the number of children individual life histories (birth, death, and all reproductive events) produced in a lifetime. were recorded for three generations (a total of 1,894 individuals, AFR. This trait was calculated as the age in years when a woman of which 904 are female). Of the 904 females with complete life gave birth to her first child or a man fathered his first child.
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