Coalescent theory of migration network motifs

Abstract

Natural populations display a variety of spatial arrangements, each potentially with a distinctive impact on genetic diversity and genetic differentiation among subpopulations. Although the spatial arrangement of populations can lead to intricate migration networks, theoretical developments have focused mainly on a small subset of such networks, emphasizing the island-migration and stepping-stone models. In this study, we investigate all small network motifs: the set of all possible migration networks among populations subdivided into at most four subpopulations. For each motif, we use coalescent theory to derive expectations for three quantities that describe genetic variation: nucleotide diversity, F ST , and half-time to equilibrium diversity. We describe the impact of network properties on these quantities, finding that motifs with a large mean node degree have the largest nucleotide diversity and the longest time to equilibrium, whereas motifs with small density have the largest F ST . In addition, we show that the motifs whose pattern of variation is most strongly influenced by loss of a connection or a subpopulation are those that can be split easily into several disconnected components. We illustrate our results using two example datasets-sky island birds of genus Brachypteryx and Indian tigers-identifying disturbance scenarios that produce the greatest reduction in genetic diversity; for tigers, we also compare the benefits of two assisted gene flow scenarios. Our results have consequences for understanding the effect of geography on genetic diversity and for designing strategies to alter population migration networks to maximize genetic variation in the context of conservation of endangered species.KEYWORDS coalescent theory; genetic differentiation; network; population structure Correctly predicting the effect of connectivity patterns on the 8 expected amount of nucleotide diversity and genetic differentia-9 tion is important in a range of settings. In population genetics,

Genomic evidence for inbreeding depression and purging of deleterious genetic variation in Indian tigers

“…Interestingly, both inbreeding and mutation load for the southern large connected population (from Western ghats in India) are higher than the central large connected population (from Central India, Figures 1 and 2). This could reflect the central location of this population (see Alcala et al 2019, Natesh et al 2017, Kolipakam et al 2019). Additionally, the central large connected population may have had higher historical connectivity (with other population clusters), a two dimensional network of local populations (versus a linear array in southern large connected populations) and other ecological factors that allow higher population densities to be achieved in all habitats of central large connected population compared top southern large connected populations.…”

“…Each genetic cluster consists of several protected areas, with varying connectivity with other such protected areas and clusters (Jhala et al 2020, Kolipakam et al 2019, Alcala et al 2019). For the purpose of this paper, we defined populations, and whether they are ‘isolated’ or ‘connected’ based on population genetic and gene flow analyses using markers across the genome (Armstrong et al 2021, Natesh et al 2017 and Alcala et al 2019). Here, the ‘large’ populations currently have hundreds of tigers (minimum 300 tigers), while ‘small’ populations currently have below 100 tigers (Jhala et al 2020).…”

“…The southern large-connected population is disconnected from other tiger population genetic clusters in India (e.g. from Central India and Northwest), while central large-connected population (Central Indian landscape) was connected by gene flow to other tiger genetic clusters until recently (see Natesh et al 2017 and Alcala et al 2019). SFS-based demographic history models in Armstrong et al (2021) suggest that most Indian tigers diverged from each other recently.…”

“…We found that the large connected populations showed inbreeding due to recent ancestors (on average up to 5 generations ago) of less than F ROH>5Mb = 0.1. The large southern population has more inbred individuals than the large central population, potentially due its geographical placement, historic size (Figure 1d) and connectivity (Jhala et al 2020, Natesh et al 2017, Alcala et al 2019). Overall, although the theoretical expectation is that populations with N e < 1,000 are unlikely to persist (Lynch et al 1995, Frankham et al 2014, Grossen et al 2020, Jamieson & Allendorf 2012), this result indicates that a population with a census size of ~600 tigers may be sufficiently large to buffer short term inbreeding effects with some geneflow, although the long term viability of these populations remains to be tested.…”

“…All Bengal tiger populations have been through historic bottlenecks, but inbreeding and genetic variation vary among populations. Also, some populations are relatively large and connected while others are small and isolated from both genetic (Alcala et al 2019) and demographic perspectives (Jhala et al 2020, Qureshi et al 2014), making them an ideal system to investigate inbreeding, mutation load and possible genetic rescue strategies.…”