Repeated Selection of Alternatively Adapted Haplotypes Creates Sweeping Genomic Remodeling in Stickleback

Abstract

Heterogeneous genetic divergence can accumulate across the genome when populations adapt to different habitats while still exchanging alleles. How long does diversification take and how much of the genome is affected? When divergence occurs in parallel from standing genetic variation, how often are the same haplotypes involved? We explore these questions using restriction site-associated DNA sequencing genotyping data and show that broad-scale genomic repatterning, fueled by copious standing variation, can emerge in just dozens of generations in replicate natural populations of threespine stickleback fish (). After the catastrophic 1964 Alaskan earthquake, marine stickleback colonized newly created ponds on seismically uplifted islands. We find that freshwater fish in these young ponds differ from their marine ancestors across the same genomic segments previously shown to have diverged in much older lake populations. Outside of these core divergent regions the genome shows no population structure across the ocean-freshwater divide, consistent with strong local selection acting in alternative environments on stickleback populations still connected by significant gene flow. Reinforcing this inference, a majority of divergent haplotypes that are at high frequency in ponds are detectable in the sea, even across great geographic distances. Building upon previous population genomics work in this model species, our data suggest that a long history of divergent selection and gene flow among stickleback populations in oceanic and freshwater habitats has maintained polymorphisms of alternatively adapted DNA sequences that facilitate parallel evolution.

Stacks 2: Analytical methods for paired‐end sequencing improve RADseq‐based population genomics

“…The union of genome sampling protocols with massively parallel, short-read sequencing has produced an immensely successful research programme in population (Bassham, Catchen, Lescak, von Hippel, & Cresko, 2018), conservation (Dierickx, Shultz, Sato, Hiraoka, & Edwards, 2015) and landscape genomics (Bay et al, 2018), phylogenetics (Spriggs et al, 2019), and epigenetics (Trucchi et al, 2016), creating new experimental space for non-model organisms, and allowing, for example, ambitious sampling regimes in large geographical surveys (Dudaniec, Yong, Lancaster, Svensson, & Hansson, 2018), as well as wide-ranging taxon breadth in phylogenetic studies (Near et al, 2018). Regardless of the analytical approach, and in addition to any challenges of the experimental design, all RADseq strategies present two fundamental issues.…”

Repeatability of adaptive radiation depends on spatial scale: regional versus global replicates of stickleback in lake versus stream habitats

“…One explanation is that 463 these outliers are associated with the underlying genetic basis of adaptive phenotypes, which -as 464 described above -show greater parallelism at the regional than the global scale. Bassham et al, 2018). In support of this idea, we 472 found that Vancouver Island lake-stream pairs shared more outlier loci than did lake-stream pairs 473 at the global scale (21% of outliers were shared across a minimum of two pairs at the regional 474 scale but only 4% of outliers were shared across a minimum of two pairs at the global scale).…”

Simulation with RADinitio Improves RADseq Experimental Design and Sheds Light on Sources of Missing Data

“…We calculated the number of RAD loci obtained under different library configurations across different reference genomes. We selected species with previously published RAD datasets: the threespine stickleback Gasterosteus aculeatus (Bassham et al, 2018;Hohenlohe et al, 2010;Nelson & Cresko, 2018;Stuart et al, 2017) the yellow warbler Setophaga petechia (Bay et al, 2018), the postman butterfly Heliconius melpomene (Davey et al, 2017;Nadeau et al, 2014), and the bush monkeyflower Mimulus aurantiacus (Chase, Stankowski, & Streisfeld, 2017;Stankowski et al, 2019). We used available reference sequences for each of the species: stickleback -BROADS1 (Ensembl version 92), Heliconius -Hmel2.5 (Lepbase version 4), warbler -draft assembly (Bay et al, 2018), monkeyflower -chromosome-level assembly (Stankowski et al, 2019).…”

“…This family of protocols, referred hereafter as RADseq, while displaying individual benefits and disadvantages, have been designed for specific experimental contexts, and are a testament of the applicability of the general molecular approach. Independent of the specific molecular protocol used, RADseq has proven to be a versatile technique in a variety of genomics contexts, including the generation of linkage maps (Amores, Catchen, Ferrara, Fontenot, & Postlethwait, 2011;Amores, Wilson, Allard, Detrich, & Postlethwait, 2017;Small et al, 2016), de novo population genomics (Jeffery et al, 2017;Portnoy et al, 2015), landscape genomics (Bay et al, 2018;Dudaniec, Yong, Lancaster, Svensson, & Hansson, 2018), reference-based genome scans (Bassham, Catchen, Lescak, von Hippel, & Cresko, 2018), and phylogenomics/phylogeography (Cristofari et al, 2016;Razkin et al, 2016;Suchan et al, 2017).…”