Meiotic recombination shapes precision of pedigree- and marker-based estimates of inbreeding

Abstract

The proportion of an individual's genome that is identical by descent (GWIBD) can be estimated from pedigrees (inbreeding coefficient 'Pedigree F') or molecular markers ('Marker F'), but both estimators come with error. Assuming unrelated pedigree founders, Pedigree F is the expected proportion of GWIBD given a specific inbreeding constellation. Meiotic recombination introduces variation around that expectation (Mendelian noise) and related pedigree founders systematically bias Pedigree F downward. Marker F is an estimate of the actual proportion of GWIBD but it suffers from the sampling error of markers plus the error that occurs when a marker is homozygous without reflecting common ancestry (identical by state). We here show via simulation of a zebra finch and a human linkage map that three aspects of meiotic recombination (independent assortment of chromosomes, number of crossovers and their distribution along chromosomes) contribute to variation in GWIBD and thus the precision of Pedigree and Marker F. In zebra finches, where the genome contains large blocks that are rarely broken up by recombination, the Mendelian noise was large (nearly twofold larger s.d. values compared with humans) and Pedigree F thus less precise than in humans, where crossovers are distributed more uniformly along chromosomes. Effects of meiotic recombination on Marker F were reversed, such that the same number of molecular markers yielded more precise estimates of GWIBD in zebra finches than in humans. As a consequence, in species inheriting large blocks that rarely recombine, even small numbers of microsatellite markers will often be more informative about inbreeding and fitness than large pedigrees.

Recent advances in conservation and population genomics data analysis

“…Genomic approaches capture variation in realized inbreeding that is missed by pedigree analysis due to the stochastic effects of linkage and unknown common ancestors of parents (Franklin, 1977; Thompson, 2013). Thus, while deep and accurate pedigrees can often precisely measure individual inbreeding in species with many chromosomes and/or high recombination rates (Kardos et al., 2018; Knief, Kempenaers, & Forstmeier, 2017; Nietlisbach et al., 2017), genomic approaches are expected to more reliably measure inbreeding and inbreeding depression (Kardos, Luikart, & Allendorf, 2015a; Kardos et al., 2018; Keller, Visscher, & Goddard, 2011; Wang, 2016). Given that many studies have used only shallow pedigrees or few DNA markers, it is possible that power to detect inbreeding depression has been low; therefore, inbreeding depression could be more common, widespread, and severe than previously thought.…”

Pedigree-based inbreeding coefficient explains more variation in fitness than heterozygosity at 160 microsatellites in a wild bird population

“…identical-by-state (IBS) rather than IBD, and hence not predict the probability of IBD at adjacent chromosomal regions (i.e. IBD-IBS discrepancy) [25,29].…”

“…Thereby they capture variation in IBD introduced by stochasticity inherent to Mendelian segregation and recombination [21][22][23][24]. For example, the standard deviation in realized IBD among offspring of full sibling matings (pedigree F ¼ 0.25) is 0.044 in humans (Homo sapiens) [23] and 0.084 in zebra finches (Taeniopygia guttata) [25]. Third, markers can capture variation in inbreeding that is not captured because of shallow, incomplete or erroneous pedigree data (e.g.…”

“…In practice however, a finite number of chromosomes and reduced recombination among markers located on the same chromosome introduces Mendelian noise, which causes realized IBD at the marker loci to differ from its pedigreebased expectation, weakening the association between F and fitness ( [25]; figure 1). Mendelian noise can be accounted for by dividing the right side of equation (1.1) by the squared correlation coefficient between F and realized IBD (r 2 realized IBD,F ), which following [25] Note that in these equations, F is defined as the pedigreebased expectation of IBD [18] and that it is assumed that loci are physically unlinked [30].…”

“…Mendelian noise can be accounted for by dividing the right side of equation (1.1) by the squared correlation coefficient between F and realized IBD (r 2 realized IBD,F ), which following [25] Note that in these equations, F is defined as the pedigreebased expectation of IBD [18] and that it is assumed that loci are physically unlinked [30]. Equations (1.4) and (1.5) remain valid (with F as pedigree-based inbreeding) when loci are linked because the reduction in r F,H and b F,H due to increased Mendelian noise is accounted for by dividing by the variance in H, which is higher for linked loci.…”