Coregonus artedi, in inland lakes have experienced numerous extirpations along the southern edge of their range in recent decades, which are thought to result from environmental degradation and loss of cold, well‐oxygenated habitat as lakes warm. Yet, cisco extirpations do not show a clear latitudinal pattern, suggesting that local environmental factors and potentially local adaptation may influence resilience. Here, we used genomic tools to investigate the nature of this pattern of resilience. We used restriction site‐associated DNA capture (Rapture) sequencing to survey genomic diversity and differentiation in southern inland lake cisco populations and compared the frequency of deleterious mutations that potentially influence fitness across lakes. We also examined haplotype diversity in a region of the major histocompatibility complex involved in stress and immune system response. We correlated these metrics to spatial and environmental factors including latitude, lake size, and measures of oxythermal habitat and found significant relationships between genetic metrics and broad and local factors. High levels of genetic differentiation among populations were punctuated by a phylogeographic break and residual patterns of isolation‐by‐distance. Although the prevalence of deleterious mutations and inbreeding coefficients was significantly correlated with latitude, neutral and non‐neutral genetic diversity were most strongly correlated with lake surface area. Notably, differences among lakes in the availability of estimated oxythermal habitat left no clear population genomic signature. Our results shed light on the complex dynamics influencing these isolated populations and provide valuable information for their conservation.Small, isolated populations present a challenge for conservation. The dueling effects of selection and drift in a limited pool of genetic diversity make the responses of small populations to environmental perturbations erratic and difficult to predict. This is particularly true at the edge of a species range, where populations often persist at the limits of their environmental tolerances. Populations of cisco,  Sources of selective pressure are numerous, and studies using genotype–environment association analyses that detect locally adapted populations can provide valuable insight on the environmental forces that influence population viability  as a model organism to understand how spatial and environmental factors influence genetic integrity of small, isolated populations under a changing climate. Cisco are an important forage fish found in deep, cold lakes across northern North America  sequencing Ali et al.  to surve22.1® Blood & Tissue Kit reagents.Cisco used in our study were collected from 29 lakes across the southern part of the species’ range using vertical gill nets or from die‐offs during 2012–2019 , northern Wisconsin (N = 37), central Wisconsin (N = 26), southern Wisconsin (N = 10), Indiana (N = 13), and Michigan (N = 19). RAD library preparation was conducted using the SbfI enzyme according to the methods of Ali et al. , ustacks , cstacks , and populations . In addition, since all salmonids including cisco have experienced a recent genome duplication, putatively paralogous loci were identified with the program HDPlot  data from 129 individuals  with minor modifications. Libraries were hybridized with the bait mixture for 16 hr at 65°C and amplified with 10 PCR cycles, universal primers, and an annealing temperature of 56°C. Baited Rapture libraries were purified with 1X AMPureXP beads and sequenced on five Illumina HiSeq 4000 lanes at either the Michigan State Genomics Core Facility or Novogene.process_radtags (parameter flags: ‐e SbfI ‐c ‐q ‐r ‐t 140 ‐‐filter_illumina ‐‐bestrad). Filtered reads for each individual were aligned to create matching stacks with ustacks (flags: ‐‐disable‐gapped ‐m 3 ‐M 5 ‐H ‐‐max_locus_stacks 4 ‐‐model_type bounded ‐‐bound_high 0.05). A master catalog of consensus loci was built in cstacks from a catalog of 51 C. artedi used in the development of a cisco linkage map . Locus stacks for individuals were matched to the catalog using sstacks (flag: ‐‐disable_gapped), data were oriented by locus in tsv2bam, and reads were aligned to loci and SNPs were called with gstacks. SNPs genotyped in >30% of individuals (flag: ‐r 0.3) were exported with populations to a variant call format (vcf) file.Raw sequences were processed with Stacks v2.41  was estimated in each population with the bias‐corrected linkage disequilibrium method . Analysis of genetic differentiation across our populations indicated that we likely sampled inland lakes across a putative phylogeographic break. We constructed a population tree from allele frequency data using the software POPTREE2 to identify which populations belonged to which divergent clade. Genetic distance between inland lake populations was measured with AD )  was plotted. We also examined the relationship of genetic distance and spatial heterogeneity in effective population size by testing the correlation between pairwise genetic differentiation (FST /(1 − FST)) and the di metric of Prunier et al.  genome  to assess whether each mutation was putatively deleterious (PROVEAN score ≤ −2.5) and outputs were parsed with a custom script (parse_provean_output.py). We interpreted the allele that generated the negative PROVEAN score to be the deleterious allele and the alternative allele (≥2.5) to be neutral, following similar approaches in the literature , and (2) proportion of deleterious mutations (Propdel mut), which was calculated as the number of loci with an allele frequency >0 for a deleterious mutation in that population divided by the total number of deleterious mutations in the dataset.We identified putative deleterious mutations in our Rapture data using the program PROVEAN . Forward and reverse reads were merged using the software tool FLASH  using a minimum base quality score  of 30. The demultiplexing process removed barcodes from sequences so those were extracted from sequence headers and inserted at the beginning of reads (barcodes‐min.py) before importing into the software jMHC  by randomly sampling N = 5 individuals (minimum sample size in our study) from each population 1000 times and calculating the mean number of haplotypes found in those samples. We also estimated the proportion of individuals in each population that contain more than one allele (Proppoly) and the proportion of individuals in a population with more than two MHC alleles . We conducted a codon‐based Z‐test of selection in MEGA 7 using the Nei‐Gojobori method . This model simplifies lakes using a vertical Lagrangian layer approach, where horizontal variability is ignored, and each layer's thickness dynamically changes in response to water density .We used the open source, vertical one‐dimensional hydrodynamic General Lake Model , US Geological Service, Michigan DNR, Minnesota DNR, Wisconsin DNR, University of Wisconsin‐Madison, and Purdue University and compiled as supplemental material on Dryad. We performed a manual calibration for each lake based on the full set of temperature and dissolved oxygen profiles available. Model parameters were first calibrated for water temperature and second for dissolved oxygen. Lake‐specific data were only available for water temperature and dissolved oxygen, so default values were used for other model parameters, as is standard practice. Models were run at an hourly timestep starting April 4, 1979, and continuing through December 31, 2015, with output profiles once daily at noon. Model configuration files, input, and output profiles are accessible on Dryad.Historic climate drivers for each lake were estimated using data from ; 30‐day maximum TDO3 (TDO330day); COSD  values were calculated following Jacobsen et al.  with the R packages Hmisc , removal of loci that were not genotyped in every lake (n = 59), and filtering to a single SNP per Rapture locus, 7546 SNPs genotyped in 770 individuals  DNA in the extracts used for Rapture library preparation, which has been shown to highly impact the percentage of retained tags , and FST was comparatively low between all three proximal populations in this region . This pattern was uncommon across the rest of the sampled populations. For example, many of the populations in northern Wisconsin were tightly clustered and highly differentiated, such as Pallette (PLT) and White Sand (WSL) lake, which are <2 km apart and had an FST of 0.239 and Plum (PLM) and Big Muskellunge (MSK) lake, which are <8 km apart and had an FST of 0.201. The highest FST was measured between Atkins Lake (ATK) in northern Wisconsin and EVE in Indiana (FST: 0.661); however, overall ATK was more differentiated from other populations than any other lake . Since ATK also contained a significantly larger number of samples (n = 54) than other sites, we randomly subsampled 30 individuals from ATK and regenerated pairwise FST values to test whether sample size could be driving the higher levels of differentiation. After reducing the sample size to 30, ATK still maintained the highest average pairwise differentiation with other sites indicating this pattern is not driven by sample size effects  and EVE in Indiana (FST: 0.575).Differentiation among populations was high  and geographic distance , but likely biased by hierarchical structure between the two lineages. Mantel tests restricted to populations within lineages showed significant IBD) in the GL lineage , but nonsignificant IBD in the MS lineage . When ATK was removed, the test for IBD in the MS lineage was significant , indicating that populations in close proximity to ATK had reduced the strength of the IBD relationship. Partial Mantel tests with ATK removed suggested lineage and geographic distance had a significant correlation to FST/1 − FST, but that lineage‐corrected geographic distance was a larger factor  than distance corrected‐lineage membership . Similarly, an AMOVA indicated that lineages accounted for 13.6% of the variance in the data (p < 0.001), whereas populations accounted for 25.6% of the variance ] and average pairwise differentiation to log (surface area) to the MS lineage with ATK excluded  and di of log (surface area) ; however, the average pairwise differentiation for a lake was slightly negatively correlated with log (surface area) .Mantel and partial Mantel tests indicated significant correlation between e Figure . A ManteHo,He) varied substantially  with the lowest Ho measured in Eve Lake in Indiana (EVE) and the highest in Trude Lake in northern Wisconsin (TRU). Estimates of inbreeding were similarly broad (GIS: 0.028–0.582) with the same two lakes accounting for the extremes . Estimates of effective population size (Ne) were highly variable across populations . The two populations that had an Ne > 1000—White Sand (WSL) and Rainbow (RBW) lake—were both in Wisconsin, and the three lakes that had an Ne < 100—Sugar Lake in Minnesota (SGR), Black Oak Lake in northern Wisconsin (BLK), and Crooked Lake in Indiana (CRD)—were distributed across the sample range. An additional two populations generated ‘infinite’ estimates, EVE in Indiana and Howard Lake (HOW) in Michigan. An ‘infinite’ Ne is more likely a sign that the sample sizes in these populations were too small to generate a finite estimate with the LDNE method rather than a reflection of extremely large population sizes , and 173 of these mutations (54.9%) were predicted to be putatively deleterious (PROVEAN score ≤ −2.5). The proportion of all identified deleterious mutations found in each population  averaged 0.95 and varied from 0.80 to 1 , providing strong evidence that MHC haplotypes in this system have historically undergone balancing selection. Most individuals in the dataset contained at least two MHC haplotypes . Initial correlations indicated that different variants of the same model parameters were highly correlated, for example, the six TDO3 variables had pairwise correlation coefficients ranging from 0.91–1.00 (average r = 0.95). Of the six remaining variables after iterative removal with a threshold of VIF <5 ‐ latitude, surface area, depth, COSD(max), minimum oxythermal habitat volume(average), and TDO3max(max)—two pairs were correlated above the threshold of |r| >0.70 . Of these, we arbitrarily excluded minimum oxythermal habitat volume and COSD from the final list of predictors, but we treat interpretations of the remaining variables as potentially supporting for discarded variables.Sampled populations varied substantially in habitat metrics Table . For exay Figure . For exay Figure  and 2. Pp < 0.001, 46% of variation in genetic metrics explained by predictor variables, R2adj=0.375) demonstrated that AFdel mut and GIS responded differently to predictors and were not strongly associated with other genetic variables, as compared to Ho, Propdel mut, and Proppoly (Rapture), which had similar loadings on RDA1&2 , whereas lake surface area and maximum depth were associated with differences in genetic variables with high loadings on RDA2. Populations did not cluster tightly by geography indicating that variation in genetic and environmental variables is at least somewhat spatially decoupled. Analysis of variance on the RDA results indicated that latitude and surface area significantly influenced genetic variables . To assess whether previously removed environmental variables that were correlated with depth or TDO3max (r > 0.80) might explain a significant portion of genomic variance, we replaced these variables and reran the ANOVA. When depth was replaced with minimum oxythermal habitat volume (average), an even lower proportion of variance was explained (p = 0.549). Similarly, when TDO3max was replaced with COSD, the amount of genomic variance explained remained nonsignificant (p = 0.591).Results from the RDA  as the response variables and four spatial or environmental metrics  as the predictor variables indicated that the predictor with the highest relative importance on average was latitude followed by surface area, and maximum depth , and Nhap (MHC), and latitude explaining the most variance in GIS, AFdel mut, Propdel mut, and Proppoly (MHC). The average amount of variation explained in each regression was 0.38, with the lowest value (0.18) found for Proppoly (MHC) and the highest (0.68) for AFdel mut. Univariate regression with the significant predictor variables in the RDA (latitude and surface area) revealed significant positive relationships between latitude and Ho, AFdel mut, and Propdel mut, and significant positive relationships between surface area  and Ho, Propdel mut, and Nhaps  were significantly correlated for one metric, but not the other. Notably, AFdel mut was not significantly correlated with surface area but was highly correlated with latitude .Multiple linear regressions conducted with seven genetic metrics . Although the prevalence of deleterious mutations and inbreeding coefficients were significantly correlated with latitude, largely neutral (Rapture) and non‐neutral (MHC) genetic diversity were most strongly correlated with lake surface area. Our results provide valuable information for guiding restoration efforts as well as spatial and environmental factors that may govern the persistence of ciscoes and other cold‐water specialist species as the climate continues to warm.4.1C. artedi. Turgeon and Bernatchez  and brook trout   edge of the species range is not straightforward. Several studies have observed increased mutational load on the edges of a species range   benefitted survival and recruitment, and a similar approach may maximize successful reintroductions of inland lake cisco given the apparent influence of population size and drift over selection and adaptation in inland lake populations. In Wisconsin, where historic MS and GL lineages converge, careful consideration should be given before implementing a reintroduction or augmentation plan that involves mixing divergent genetic lineages as the presence of fixed differences in highly divergent populations is a risk factor for outbreeding depression  and lake trout, which are more likely to be targeted by recreational fishers (Frey, th century in Indiana and Michigan exist (Frey, Augmentation through supplementation is rare in inland cisco populations compared to other northern lacustrine salmonids such as lake whitefish (rs Frey, . A handfst Frey, , and incst Frey, . To the st Frey,  found nost Frey,  rather tst Frey, , 2016. Tst Frey,  or minimst Frey, . Ferchaust Frey,  found inst Frey, , which ast Frey, . Given tOsmerus mordax (Hrabik et al., The correlation we observed between genetic diversity and lake surface area suggests one key to resilience in southern inland lake cisco populations may be maintaining populations that are large and diverse enough to survive the stochastic demographic, environmental, or genetic factors that drive the extinction of small populations (Frankham, The authors declare no conflict of interest.Table S1Click here for additional data file.Table S2Click here for additional data file.Table S3Click here for additional data file.Figure S1Click here for additional data file.Figure S2Click here for additional data file.Data S1Click here for additional data file.Data S2Click here for additional data file.Table S4Click here for additional data file.Figure S3Click here for additional data file.


Anthus berthelotii), a passerine endemic to three North Atlantic archipelagos. First, we use demographic trees and 3f statistics to show that genome-wide divergence across the species range is largely shaped by colonization and bottlenecks, with evidence of very weak gene flow between populations. Then, using a genome scan approach, we identify signatures of divergent selection within archipelagos at single nucleotide polymorphisms (SNPs) in genes potentially associated with craniofacial development and DNA repair. We did not detect within-archipelago selection at the same SNPs as were detected previously at broader spatial scales between archipelagos, but did identify signatures of selection at loci associated with similar biological functions. These findings suggest that similar ecological factors may repeatedly drive selection between recently separated populations, as well as at broad spatial scales across varied landscapes.Oceanic island archipelagos provide excellent models to understand evolutionary processes. Colonization events and gene flow can interact with selection to shape genetic variation at different spatial scales. Landscape-scale variation in biotic and abiotic factors may drive fine-scale selection within islands, while long-term evolutionary processes may drive divergence between distantly related populations. Here, we examine patterns of population history and selection between recently diverged populations of the Berthelot's pipit ( The abiIsland archipelagos provide replicated, ecologically variable and simplified landscapes, that can greatly facilitate the study of adaptation in the wild ,10). Var. Var10]). It has long been recognized that consideration of spatial scales is important when identifying patterns and drivers of adaptation among populations, but few studies have quantified adaptation across a range of scales. In particular, it is important not to neglect intermediate scales  when studying adaptation, as these may provide powerful systems with which to detect ecologically relevant adaptations.Selection operates at a range of geographical scales within and across island archipelagos . StudyinAnthus berthelotii) is a Macaronesian endemic passerine distributed across three North Atlantic archipelagos (Avipoxvirus and Plasmodium) varies greatly among islands within archipelagos. Both the Canary Islands and Madeiran archipelago have populations with both high and low pathogen loads, and population-level patterns of pathogen prevalence are consistent over time [Berthelot's pipit  markers from across the Berthelot's pipit range to address the following questions: (i) what new insights do analyses of genomic variation provide for population history, including colonization, bottlenecks and gene flow across the species range? (ii) can we detect signatures of selection across recently diverged populations within archipelagos? (iii) what are the loci, and traits, under selection within archipelagos? and (iv) are the same loci under selection within and across archipelagos? To address these questions, we first use population genetic analyses to examine colonization history and gene flow across the species range. We also quantify population structure and genetic diversity within the Canarian and Madeiran archipelagos independently, providing a finer-scale assessment of genetic structure compared to previous studies in this system. We then use genome scan approaches to identify loci under divergent selection within archipelagos, and where appropriate, link patterns of genetic variation to variation in phenotypic traits. Finally, we compare our results to previous research on this species, to help understand how population history, selection and drift interact to shape patterns of diversity at different scales across island populations.. 2. 2.1et al. [et al. [et al. [Tenebrio molitor larvae. A blood sample (ca 25 µl) was taken from each bird by brachial venipuncture and stored in 800 µl absolute ethanol at room temperature. DNA was extracted using the salt extraction protocol described by Richardson et al. [Berthelot's pipits were sampled on 12 islands across their geographical range , as repoet al.  and Spur [et al. . As in A [et al. , we consn et al. , and birn et al. . Seven mn et al. .Taeniopygia guttata; v. 3.2.4; [The initial ddRAD library was generated using the protocol by DaCosta & Sorenson  which as. 3.2.4; ). The dar = 0.92, 0.98 and 0.96 for the Canary Islands, Madeiran archipelago and Selvagens, respectively), so we only report the Plink calculated values. Using these , one individual from any pair identified as having a relatedness value greater than 0.2 was randomly removed to avoid first- and second-order relatives being included in the population genetic and selection analyses.The Berthelot's marker sets were first grouped by archipelago and then trimmed using Plink 1.9  to remov. 2.2TreeMix at these different population scales with the aim of further understanding the evolutionary processes behind the patterns of population structuring we see. First, we used an ‘All Pipits’ dataset which, in addition to the Berthelot's pipits includes 16 tawny pipits (Anthus campestris), the Berthelot's pipit sister species [r2 threshold, for a sliding window 50 kb with 10 marker step) and sex-linked loci .Population genetic analyses were carried out using two datasets to determine patterns of colonization and gene flow among populations across the species range . Strong  species , sampledTreeMix v. 1.13 [TreeMix analysis were calculated within populations using Plink, after marker pruning . We modelled several scenarios allowing zero to eight migration events , discounting migration events when the relative increase in model likelihood was less than 1%. For each analyses, 10 000 bootstrap replicates were generated, resampling blocks of 20, 50 and 80 SNPs to evaluate the robustness of the tree topology; this corresponds to a window size of approximately 10–30 Mb as used by Pickrell & Pritchard [TreeMix. Residual plots were assessed to display model fit and identify poorly fitted population pairs. FST was calculated between pairs of populations in Plink [TreeMix tree topology. To test for admixture among Berthelot's pipit populations, we computed the three-population statistic  for allatistic;  implemendmixture .Ne) and founder events in humans [Canis lupus [Canis lupus familiaris [Ne, and LD at distant SNPs reflects Ne in more recent time. To further understand patterns of genetic diversity and population size in the Berthelot's pipit, we estimated LD for each island population using Plink. The r2 values were compared to physical distance between loci for all pairs of SNPs situated on the same chromosome. We fitted a locally weighted linear regression (loess) curve to the r2 data using the R function ‘loess’ using the default span parameter (0.75), with 95% confidence intervals calculated. Population structure was examined within the Canary Islands and Madeiran archipelago independently using a PCA, implemented using Plink, based on the trimmed and filtered marker sets.We next investigated fine-scale population genetic structure between recently separated populations within archipelagos. From the initial Berthelot's RAD library, we generated separate Canary Islands and Madeiran archipelago marker sets prior to trimming to maximize the number of loci at each level of clustering within-archipelago datasets . As we only sampled one population in the Selvagens, no within-archipelago analysis was conducted for this archipelago. These data were also trimmed to remove SNPs with MAF < 0.03  was filtered according to MAF (SNPs with MAF < 0.03 excluded) within archipelagos, LD analysis was MAF-filtered (SNPs with MAF < 0.03 excluded) within populations), and closely related individuals were removed (as above). LD summarizes both mutational and recombination history, whereby larger, more outbred populations show rapid decay of LD between genetic markers compared to small inbred populations . Patternn humans ,51, selen humans  and wildis lupus , and vilmiliaris . The rel. 2.3igenGWAS [www.github.com/gc5k/GEAR/wiki), to identify loci consistent with selection within archipelagos. EigenGWAS performs a PCA to generate gradients of population structure, then assesses each genetic marker individually for an association with these axes. EigenGWAS provides genomic inflation factor corrected p-values (λGC)—with the significance threshold determined by Bonferroni-correction—to control for genome-wide population stratification and drift. Loci above this significance threshold are putatively under selection across the gradient of population structure . All SNPs in the Madeiran subset were also in the Canary Island dataset as a result of reduced genetic diversity in the Madeiran archipelago, and hence, direct comparisons of SNP variation are made. To identify genes located near outlier SNPs, we viewed regions of interest using the zebra finch genome (v. Taeniopygia_guttata-3.2.4) in NCBI Genome Data Viewer v. 4.8. (www.ncbi.nlm.nih.gov/genome/gdv/browser).For genome scan analyses, using the archipelago level marker sets, close relatives and SNPs with an MAF < 0.03 were removed (as above), but we did not filter based on LD, which enabled us to identify and visualize genomic regions under selection . We used EigenGWAS , implemeAfter having identified candidate SNPs which may be associated with skeletal development (see Results/Discussion), we determined the genotype–phenotype associations for these loci across all Berthelot's pipit populations. We used linear mixed models (LMMs) implemented in R using the lme4 package v. 1.1.15, to test the hypothesis that SNP variation within the candidate gene is associated with phenotypic variation in morphological traits. To check whether skeletal development is associated with genotypic variation at these candidate SNPs, we fitted LMMs with wing, tarsus and head length, bill length, width and height and weight as dependant variables. Population was modelled as a random effect nested within archipelago, and genotype , sex and age as fixed effects in the model. Separate models were fitted for each of the SNPs within the morphology associated gene. All estimates are reported with associated 95% confidence intervals.. 3TreeMix Berthelot's tree, we trimmed all 13 Berthelot's pipit populations together from the initial RAD library, and after MAF and LD filtering retained 2850 loci across the Canary Islands, Madeiran archipelago and Selvagens.The initial RAD library provided 9960 genome-wide polymorphic SNPs across the entire geographical population range of Berthelot's pipit. After MAF filtering separately in each archipelago, we retained 4470 SNPs in the Canary Islands subset and 2938 in the Madeiran archipelago subset. For the r < 0.05), there were some pairs with high relatedness sampled in the smallest isolated populations of the Canary Islands (El Hierro and La Graciosa) and the islands of Madeira and Deserta Grande in the Madeiran archipelago . No pairs of individuals had relatedness of r > 0.2 in the Selvagens. To avoid including closely related individuals in the population genetic and selection analyses, one individual was removed from each dyad with a relatedness score r > 0.2, resulting in three individuals from La Graciosa, one from Lanzarote, two from El Hierro, three from Madeira and seven from Deserta Grande being removed.Relatedness varied within and among populations: while most pairs of individuals showed low relatedness , with shortest branch lengths to the central Canary Islands . Populations in the Madeiran archipelago had poor residual fit with the tawny pipit , suggesting that these populations may be more closely related than is presented by the best-fit tree. However, adding migration events did not improve the residual fit of these models. Despite this, the tawny pipit rooted tree, obtained without adding migration events, explained the majority of allele frequency variation (variance = 99.55%) between populations.We used a). Tree topology within the Canary Islands roughly reflects geographical distance between islands, with branches east and west of Tenerife, and Mount Teide as a separate branch point from lowland Tenerife (a). Generally, weak drift is observed across the Canary Islands, with the longest within-archipelago branch lengths in El Hierro and La Graciosa. These same patterns are reflected in pairwise FST values, with moderate divergence between El Hierro and La Graciosa (FST = 0.04) the most geographically distant pair of populations, and increasingly weaker divergence between more closely located populations in the Canary Islands, especially in the central islands in the archipelago (FST range = 0.01–0.03). In the Madeiran archipelago, longer branch lengths were observed, with the highest divergence between Deserta Grande and the other Madeiran islands . Tree topology was broadly robust to window size, but there were minor differences within the Canary Islands including the source populations for the Madeiran archipelago ; here, we present specific model results calculated using windows of 50 SNPs. The majority of allele frequency variation (variance = 99.86%) is described solely by the tree topology, with good residual support for most populations . Sequentially adding migration events did not substantially improve model support  or the degree of variance explained by trees . Weakly negative 3f statistics (>− 5.3 × 10−4) and Z-scores > −1.3 were found for Tenerife (including El Teide), Gran Canaria, Fuerteventura and Lanzarote in the Canary Islands and the island of Madeira when in a three-way population comparison . F3 results suggest few admixture events subsequent to branch divergence may have occurred between Madeira and Porto Santo and Fuerteventura/Lanzarote and La Graciosa. This is consistent with geographical distance between islands, suggesting no admixture between geographically distant populations.Maximum-likelihood trees limited to the 13 Berthelot's pipit populations placed the Madeiran and Selvagens archipelagos on long, independent branches, grouping with the central/eastern and western Canary Islands, respectively a. Tree tTenerife a. Generab and electronic supplementary material, figure S7. LD was highest in the smallest and most isolated populations across the Berthelot's pipit range. Thus, across all populations, the Selvagens had the highest LD with a long-range decay pattern; LD was lower across the three Madeiran islands, and was lowest in the Canary Islands, especially in large central islands (figure 2b).Patterns of LD within populations are shown in figure 2a). The second component separates El Hierro, Lanzarote and La Graciosa from the other islands. PCA of the Madeiran archipelago separated Deserta Grande from Madeira and Porto Santo along the first axis, and separated Porto Santo from Madeira on the second axis, with a weak gradient from Madeira to Deserta Grande to Porto Santo (b).To investigate potential-fine-scale population structure within archipelagos, we conducted a PCA of individuals using the archipelago datasets. Within the Canary Islands, we found that the first principal component (PC) roughly reflects an east–west gradient of population structure, with El Hierro and La Graciosa separating most distinctly from the other islands a. The seto Santo b.Figure. 3.2igenGWAS analyses to identify loci under divergent selection across the gradients of population structure seen in the Canary Islands and Madeiran archipelago, separately (λGC) were substantial for both PCs  for the Canary Islands, we detected one outlier SNP for PC1 . No outlier SNPs were detected for PC2 . For the Madeiran archipelago, after correcting for the λGC of 3.4 for PC1 and 1.4 for PC2, three outlier SNPs exceeded our Bonferroni-corrected significance threshold of p < 1.70 × 10−5 (n SNPs = 2938). Two of these were on the same RAD locus, within 20 bases of each other . CorrecFST values were not correlated between archipelagos , but significant SNPs from the EigenGWAS analyses had the highest FST values (igenGWAS as being under selection across the Canary Islands (219s24), had a high MAF in the western islands of El Hierro and La Palma, and a low MAF across the central and eastern islands within that archipelago . All SNPs under selection across the Madeiran archipelago had near 50% prevalence of the ‘minor allele’ in the Deserta Grande population while being absent from the two other islands, with a low frequency of the minor allele observed across the Canary Islands and Selvagens.Locus T values . The SNPigenGWAS SNPs to the zebra finch genome and determine their likely genomic location  mapped to intronic regions of a candidate gene for morphology, ADAM12, on chromosome 6 . We found a similar effect of genotype on head length at both SNPs putatively under selection within the ADAM12 gene  as well as strong differences between the sexes (p< 3.3 x10−6). Homozygous individuals for the minor allele were only detected in the Deserta Grande population for both of the SNPs, while heterozygous individuals were present at low frequency for eight of the 13 pipit populations . Genotype was not significantly associated with beak morphology variables , weight, wing length or tarsus length, although there were differences between sexes for tarsus length (p < 0.003), wing length (p < 0.002) and bill length (p < 0.010) as we expect for a sexually dimorphic species.. 4We examined genetic divergence and selection between recently founded island populations in an attempt to understand population history and uncover traits of adaptive importance across selective environments in the wild. Using RAD sequenced markers generated for 13 populations of Berthelot's pipit, we first analysed genome-wide variation to uncover patterns of colonization, admixture and population demography. Our analyses support the establishment of Berthelot's pipit across the three archipelagos via independent colonization events, with evidence of weak subsequent gene flow between populations. Patterns of genetic diversity are consistent with signatures of founder events and geographical isolation. We applied a genome scan approach to identify signatures of selection, and inferred traits of ecological importance between recently separated populations within archipelagos. We detected SNPs putatively under selection within the Canarian and Madeiran archipelagos, but found no overlap between candidate SNPs identified from previous analyses at a broader spatial scale, i.e. between archipelagos . We founTreeMix, and examine population-level patterns of genetic diversity using LD decay. TreeMix shows strong divergence between the tawny and Berthelot's pipit , consistent with phylogeny-based estimates [a). There are weak signatures of within-archipelago divergence and structure (FST 0.01–0.06), with the longest population branch lengths (a) and individual PCA clustering (b) and support previously reported patterns based on microsatellite and RAD data . Sim. SimTreeata  and forms part of a family of proteins involved in development, homeostasis and disease [ADAM12 gene was no longer significant when two individuals (out of 19) with particularly large beaks were removed from Deserta Grande, and larger sample sizes are needed to determine the robustness of this result. Nonetheless, this research adds to the growing body of evidence that genes associated with craniofacial development may be excellent candidates for the study of natural selection in wild birds [The most significant SNPs (1585s94 and 1585s112) in the Eld birds ,62,63.igenGWAS approach, we previously observed a larger number of divergent selection signatures between archipelagos, identifying dozens of SNPs putatively under selection . Our fibonicus; ) and barrustica; ) and bet trutta; ) and Atlo salar; ). Adaptio salar; ,68,69). . 5Combining the study of population history, drift and selection between island populations at different spatial scales provides an opportunity to understand how evolution shapes variation in nature. We assessed contemporary patterns of variation across the range of Berthelot's pipit, revealing that genetic diversity is largely shaped by colonization events, with very weak evidence of gene flow between islands. We uncover outlier loci putatively under divergent selection between recently separated populations within archipelagos. Patterns of diversity at these loci, and the ecological adaptation they may be involved in, may be masked by other evolutionary processes when assessing genetic variation at broader scales. Our findings suggest natural selection may act repeatedly on traits, particularly bill morphology, at different spatial scales, and that signals of selection appear to be weaker between recently separated populations. Moving forward, studying demography and selection at a range of spatial scales is likely to prove a powerful approach for determining the strength and nature of adaptation in the wild.Click here for additional data file.


A total of 176 and 155 different alleles were observed across all 23 Y-STRs for Guangdong Hakka  and Guangdong She (0.0047–0.8605), respectively. The gene diversity ranged from 0.4877 to 0.9671 (Guangdong Hakka) and 0.3277–0.9526 (Guangdong She), while the haplotype diversities were 0.9994 and 0.9939 for Guangdong Hakka and Guangdong She, with discrimination capacity values of 0.8885 and 0.5674, respectively. With reference to geographical and linguistic scales, the phylogenetic analyses showed us that Guangdong Hakka has a close relationship with Southern Han, and the genetic pool of Guangdong Hakka was influenced by surrounding Han populations. The predominant haplogroups of the Guangdong She group were O2-M122 and O2a2a1a2-M7, while Guangdong She clustered with other Tibeto-Burman language-speaking populations (Guizhou Tujia and Hunan Tujia), which shows us that the Guangdong She group is one of the branches of Tibeto-Burman populations and the Huonie dialect of She languages may be a branch of Tibeto-Burman language families.Guangdong province is situated in the south of China with a population size of 113.46 million. Hakka is officially recognized as a branch of Han Chinese, and She is the official minority group in mainland China. There are approximately 25 million Hakka people who mainly live in the East and North regions of China, while there are only 0.7 million She people. The genetic characterization and forensic parameters of these two groups are poorly defined (She) or still need to be explored (Hakka). In this study, we have genotyped 475 unrelated Guangdong males (260 Hakka and 215 She) with Promega PowerPlex Hakka is one of the far-reaching ethnic groups that have a worldwide distribution and is officially recognized as a branch of Han Chinese in China. Hakka is a unique group that is not named after the region . There aShe is one of the largest ethnic minorities in Jiangxi, Fujian, and Zhejiang provinces. Their presence is also reported in the provinces of Anhui and Guangdong. She people are shifting cultivation group in South China and had migrated from their primitive habitations in Fenghuang Mountain in Guangdong Chaozhou to Fujian, Zhejiang, Jiangxi, Anhui, and other provinces for more than a thousand years . The tot® Y23 System  in Guangdong Hakka and Guangdong She groups, (2) the population structures of the two groups, and (3) the language classification of Guangdong She —we used the Promega 5-dye multiplex system to genotype 23 Y-STRs in 260 Guangdong Hakka and 215 Guangdong She males and evaluated the system effectiveness of forensic applications in two groups. Furthermore, we conducted population genetics employing diversified analyses among globally dispersed human populations and regional closely related populations to make the issues clearer.Y-chromosomal variant analysis for determining the patterns of present and past flow of genes between populations is very helpful . Y-chromTM, GE Healthcare, Chicago, IL, United States), with their written informed consent. This study and the procedures were approved by the Institutional Review Boards of Hainan Medical University and the Medical Ethics Committee of Hainan Medical University (no. HYLL-2020-012). All the experimental procedures were performed following the standards of the Declaration of Helsinki.In this study, a total of 475 unrelated male individuals (260 Hakka and 215 She) were recruited from Guangdong province of China . Blood s® Y23 System , which is a five-dye multiplex kit that analyzes the 17 Yfiler Y-STRs  together with six discriminating Y-STRs  on a Veriti® 96 Well Thermal Cycler System  following the manufacturer’s instructions. The amplified products were separated by capillary electrophoresis on a 3500XL Genetic Analyzer , and data were analyzed using GeneMapper® ID-X Software v1.6 .One punched bloodstain paper (the size was 1.2 mm × 1.2 mm) was used as a PCR template directly for each sample without DNA extraction procedures. Y-STRs were co-amplified using Promega PowerPlexHaplotype and allele frequencies were calculated using Arlequin v3.5 . Gene din is the number of alleles at each Y-STR locus, and Pi is the frequency of the i-th allele. Haplotype diversity (HD) was estimated similarly as GD, while n and Pi were the total number of haplotypes and the frequency of the i-th haplotype, respectively. Discrimination capacity (DC) was determined as the ratio between the number of different haplotypes and the sample size. Match probability (MP) was defined as MP = Pi was the frequency of the i-th haplotype.where, RST (RST) and corresponding p values between different populations were estimated by analysis of molecular variance (AMOVA) by the online tool available at YHRD1. The principal component analysis (PCA) and multidimensional scaling plot (MDS) were conducted based on allele frequencies using the R programming language. Additionally, phylogenetic relationships among different populations were drawn in Molecular Evolutionary Genetics Analysis 7.0 software (RST matrices) and visualized by the Interactive Tree of Life v5  and YA004708 . The Y-STR profiles, with variants  for all samples, were re-amplified and re-genotyped by AmpFLSTR® Yfiler® PCR Amplification Kit  and Geno-ID Y41 Human Typing  for confirmation.The haplotype data of 475 unrelated male individuals from Guangdong Hakka and Guangdong She populations in the present study have been submitted to the YHRD database and received the accession number The allele frequencies, allele numbers, and GD values of 23 Y-STR loci in the Guangdong Hakka and She groups are presented in In Guangdong Hakka, 176 distinct alleles were observed at all loci, and the corresponding allelic frequencies ranged from 0.0038 to 0.7423 (DYS438). The number of different alleles varied from three (DYS437) to 40 (DYS385a/b). The GD values of six Y-STRs were greater than 0.9, and the highest (0.9671) and lowest (0.4877) estimates of GD corresponded to loci DYS385a/b and DYS438, respectively. We identified three off-ladders at DYS576 (19.1) and DYS458 (16.1) and the microvariant 19.1 at DYS576 which happened twice. All loci having intermediate values found in the Guangdong Hakka were re-amplified and re-genotyped for confirmation and were commonly observed in YHRD.In the Guangdong She group, a total of 155 different alleles were obtained, and the number of diverse alleles ranged from four (at seven Y-STRs) to 36 (at DYS385a/b). The allele frequencies varied from 0.0047 to 0.8605 (DYS438). On one hand, the set of 23 Y-STR loci had a high level of genetic polymorphisms in the She group, DYS458 (0.9526), DYS385a/b (0.9180), DYS481 (0.9146), and DYS448 (0.9060), while the DYS438 (0.3277) and DYS391 (0.4875) showed extreme values of the GD distribution . In this study, no null allele, off-ladder, and copy number variant were found in the Guangdong She group.The haplotypes and haplotype frequencies of 23 Y-STRs in the two groups are shown in ® Y23 System was not seemingly appropriate for the Guangdong She group. With the Guangdong She group being relatively isolated, there was limited gene flow, which led to the decrease in the discrimination capacity of the Y-STR system. In this regard, there is a dire need to get more knowledge about the mutability of currently known Y-STRs and to incorporate the rapidly mutating Y-STRs into forensic systems to enhance the capacity of discrimination, especially for isolated groups.As shown in Dimensionality reduction analyses including PCA, MDS, linear discriminant analysis, Laplacian Eigenmaps, and locally linear embedding can accelerate the speed of algorithm execution, improve the performance of the analysis model, and reduce the complexity of data at the same time. To illustrate the genetic landscapes of globally dispersed human populations, especially for Guangdong Hakka and She groups, the dimensionality reduction analyses (PCA and MDS) were conducted based on the frequencies of 23 Y-STRs.The PCA provides a method of visualizing the essential patterns of genetic relationships and allows us to identify and plot the major patterns within a multivariate dataset to indicate that the populations with closer geographical distances have more intimate relationships. We collected the 23 Y-STR frequency profiles of 48,162 individuals from 159 worldwide populations having nine language families within five continents  to conduTo further clarify the genetic relationships on a relatively small scale, we performed PCA within Chinese populations . PopulatMDS plots were conducted based on allele frequencies by Euclidean distance and Manhattan distance, respectively. As shown in Whether from the perspective of geographical or linguistic scale, the results of MDS analysis by Euclidean distance  had no aFurthermore, to illustrate partial genetic relationships, we collected Guangdong Hakka, Guangdong She, and 83 other Chinese populations to perform MDS analyses with Euclidean distance and Manhattan distance . The MDSRST and the corresponding p values between Guangdong Hakka and 13 other Chinese Han populations from Southern and Northern Han regions (RST = 0.0028) and Jiangxi Han (RST = 0.0029). Subsequently, the results of the phylogenetic analysis among Guangdong Hakka and Chinese Han populations are displayed in a phylogenetic tree based on the neighbor-joining method , while significant genetic differences were observed between Guangdong She and all other Chinese minority populations (p < 0.05). The phylogenetic relationships between Guangdong She and 42 Chinese minorities were visualized in the neighbor-joining tree. As shown in From the dimensionality reduction analyses discussed above, the genetic relationships between Guangdong She and other Chinese populations were not clarified. In addition, we employed the Y-STR haplotype profiles of 42 Chinese minorities and Guangdong She to assess the population pairwise genetic distances by AMOVA . The pai2. In addition, a PCA graph was performed among 77 populations . From the perspectives of geographical and linguistic scales, the phylogenetic analyses indicated that Guangdong Hakka had a close relationship with Southern Han, and there were extensive gene flows between Guangdong Hakka and the surrounding Han populations. For Guangdong She, we identified 155 distinct alleles with a range of allele frequencies from 0.0047 to 0.8605. The GD values for 23 Y-STRs ranged from 0.3277 to 0.9526, and the overall DC and HD were 0.5674 and 0.9939, respectively. The predominant haplogroups of the Guangdong She group were O2-M122 and O2a2a1a2-M7. Moreover, Guangdong She clustered with Tibeto-Burman language-speaking populations (Guizhou Tujia and Hunan Tujia), which demonstrates that the Guangdong She group seems to be one branch of Tibeto-Burman populations and the Huonie dialect of She languages may be a branch of Tibeto-Burman language families.In the present study, a total of 475 unrelated Guangdong males (260 Hakka and 215 She) were genotyped by using 23 Y-STRs  by Promega PowerPlexThe datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/The studies involving human participants were reviewed and approved by Medical Ethics Committee of Hainan Medical University. The patients/participants provided their written informed consent to participate in this study.HF contributed to conceptualization, formal analysis, visualization, and writing—original draft preparation. CL and DP took charge of resources and contributed to project administration. HF, LW, and KR were in charge of software. LD, YL, QX, and YZ conducted the investigation. LD, YZ, FW, and ZD performed the validation. CL contributed to data curation. QX, SN, and MJ contributed to writing—review and editing. PQ and S-QW supervised the study. CL, HF, FW, and ZD took charge of funding acquisition. All authors reviewed the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The handling editor AA declared a past collaboration with the author SN.


Nannoperca australis) and Yarra (N. obscura) pygmy perches, to assess the degree of concordance in their responses to Plio-Pleistocene climatic changes. We described contemporary genetic diversity, phylogenetic histories, demographic histories, and historical species distributions across both species, and statistically evaluated the degree of concordance in co-occurring populations.Understanding how species biology may facilitate resilience to climate change remains a critical factor in detecting and protecting species at risk of extinction. Many studies have focused on the role of particular ecological traits in driving species responses, but less so on demographic history and levels of standing genetic variation. Additionally, spatial variation in the interaction of demographic and adaptive factors may further complicate prediction of species responses to environmental change. We used environmental and genomic datasets to reconstruct the phylogeographic histories of two ecologically similar and largely co-distributed freshwater fishes, the southern (N. obscura. Although several co-occurring populations within a shared climatic refugium demonstrated concordant demographic histories, idiosyncratic population size changes were found at the range edges of the more spatially restricted species. Discordant responses between species were associated with low standing genetic variation in peripheral populations. This might have hindered adaptive potential, as documented in recent demographic declines and population extinctions for the two species.Marked differences in contemporary genetic diversity, historical distribution changes and historical migration were observed across the species, with a distinct lack of genetic diversity and historical range expansion suggested for Our results highlight both the role of spatial scale in the degree of concordance in species responses to climate change, and the importance of standing genetic variation in facilitating range shifts. Even when ecological traits are similar between species, long-term genetic diversity and historical population demography may lead to discordant responses to ongoing and future climate change.The online version contains supplementary material available at 10.1186/s12862-022-01990-2. Understanding how or whether species may be able to adapt to current and future climatic changes is critical for conservation management of threatened taxa . HoweverFrom a genetic perspective, adaptation to novel climatic conditions more often relies upon SGV than de novo mutations –11. The Understanding factors underlying species responses to historical climatic fluctuations provides an empirical framework for determining how species may respond to current and future environmental changes . ExtendiBiogeographic regions that experienced major environmental change in the past are particularly useful for studying species responses to climate change. In this regard, the southeast Australian temperate zone provides a model region to test how species have responded to major environmental changes such as aridification and eustatic changes. Mainland Australia has experienced significant environmental changes since the late Miocene, which heralded the onset of major aridification . Other tNannoperca australis) and Yarra (N. obscura) pygmy perches provide an ideal comparative study system. Both species possess highly similar morphology, reproductive biology, salinity tolerance and habitat preferences, and also display similar patterns of metapopulation structure [N. australis [N. obscura [N. australis that show that patterns of adaptation in traits related to reproductive fitness [Freshwater-dependent species are important indicators of historical environmental changes given their reliance on suitable habitat and often limited capacity for dispersal . Within tructure –39. Bothtructure , 39. Bottructure ) and shoustralis , and two obscura . Given t fitness , 43, in  fitness  and in v fitness  are stroN. australis as Near Threatened and N. obscura as Endangered) within the IUCN Red List [N. obscura is considered at higher risk due to their narrow range and extremely low genetic diversity [N. obscura within the Murray-Darling Basin in the last 5 years [N. obscura is not thought to be due to any particularly severe past bottleneck [N. obscura in some regions where N. australis is found is the result of historical local extinctions or a failure to initially colonise the habitat.Despite their ecological similarities, the two species demonstrate marked differences in conservation status, genetic diversity and total distribution range. While both species are of conservation concern  and broad-scale (species-level) responses to assess the role of intraspecific patterns in driving lineage responses.N. australis is also found across eastern Victorian drainages, northern Tasmania and the highlands of the southern Murray-Darling Basin [N. obscura and nine populations of N. australis occurring across all major drainages of the region  from Lake Alexandrina were also included for demographic analyses. For phylogenetic analyses, five samples of a sister species (Nannoperca vittata) were included as outgroup [While both species are distributed across southwest Victoria and the lower Murray-Darling Basin , N. austng Basin . The finion Fig. . An addioutgroup . SpecimeSbf1 and Mse1 and selecting fragments 300–800 base pairs in length. Our samples contain a combination of previously obtained sequences, from prior population genomic work on N. australis [N. australis (n = 33 samples) and four N. obscura (n = 21 samples) populations were previously paired-end sequenced on an Illumina HiSeq 2000 at Genome Quebec . The remaining 44 samples were single-end sequenced on an Illumina HiSeq 2500 at the South Australia Health and Medical Research Institute (SAHMRI).DNA was extracted from muscle tissue or fin clips using a modified salting-out method  or a Qiaustralis , phylogeustralis , and preustralis ; AdditioN. obscura; 31 in N. australis; Additional file n < 3) using PyRAD  to estimate mean values per locus per population. Due to the larger sample sizes available for Lake Alexandrina populations, genetic diversity parameters were also calculated using n = 15 rarefaction and loci aligned separately within each population. For these populations, we also calculated effective population size (Ne) using NeEstimator [Population-level genetic diversity summaries  were estimated using the R package ierfstat . Given ustimator  and a mistimator . DiffereMaximum likelihood (ML) phylogenies of each species were estimated using RAxML 8.2.11  with theTo better account for incomplete lineage sorting, we also estimated phylogenetic trees using the SNP-based multispecies coalescent approach SVDQuartets . All unln for each species  and evaluated the fit of each tree based on the standard error of the covariance matrix. We further assessed model fit by calculating the percentage of variance explained (https://github.com/wlz0726/Population_Genomics_Scripts/tree/master/03.treemix). The best supported number of migrations was determined by the asymptote of the likelihood, where additional migrations did not substantially increase model likelihood.As historical migration may impact the topology of a phylogenetic tree, we also used TreeMix  to infer–8 mutations per site per generation, and a generation time of one year for both species [Demographic histories for all populations were estimated using stairway plots and one-dimensional SFS calculated for each independent population alignment. Stairway plots were estimated assuming a mutation rate of 10 species , 63. AltWe used FastSimCoal2  to simuln = 8 haploid samples) using easySFS (github: isaacovercast/easySFS.git). A model of exponential growth followed by exponential decline was applied to all populations using broad uniform priors .Additionally, we ran co-demographic hierarchical approximate Bayesian computation simulations using the aggregate site frequency spectrum (aSFS) and Multi-DICE  to asses package . We furthttp://www.ala.org.au/). We filtered the occurrence data to reduce the impact of spatial autocorrelation, resulting in final datasets of 1,021 and 163 observations for N. australis and N. obscura, respectively  were estimated using an ensemble modelling approach within biomod2 . We estin = 500) per species randomly from background cells > 50 km away from occurrences to reduce the likelihood of generating false absences within habitable areas [n = 27 models total), and an ensemble model generated per time period using the weighted mean of all models. These algorithms are among the most widely used for presence-only SDM analyses and encapsulate diverse statistical approaches, with the weighted mean the most commonly used ensemble generation approach [We selected eight non-correlated environmental variables for estimating species distributions  in N. australis .Phylogenetic analysis of both datasets returned a highly supported phylogenetic tree for each species. Species trees estimated using SVDQuartets were concordant with the maximum likelihood trees, with strong support all for major nodes  than N. obscura (one event)  Fig. : Fig. S9N. australis appeared generally more stable over time. Both Lake Alexandrina populations (NobCHI and NauALE) showed significant historical increases in Ne > 200 Kya, and long-term stable population sizes following this expansion.Stairway plots demonstrated broadly similar demographic histories across the two species, with most populations relatively stable or declining slightly over the last 1 Mya Fig. A. PopulaN. obscura population (NobGCL) contrasted this pattern, with a model of low but constant population size more supported than other demographic histories (Model 3). Strong post-glacial declines were present in Lake Alexandrina populations of both species, with weaker declines in the more eastern population pairs.Most populations chosen for comparative analysis demonstrated fluctuating demographic histories Fig. B, with aA confusion matrix suggested that the co-demographic model was more likely to infer fully synchronous ξ = 1) or fully asynchronous (ξ = 0.167) co-contractions over intermediate proportions of taxa  and impede range expansions. Thus, we cannot completely rule out some role of ecology and its interactions with genetic diversity in driving discordant responses. The lower genetic diversity in N. obscura could not be directly attributed to notable and widespread genetic bottlenecks, suggesting instead that the species suffered from a consistent pattern of being genetically depauperate. Combined, these factors suggest that long-term SGV may be a key factor driving the temporally and spatially widespread discordance in response to Pleistocene climate changes.Spatial variation in demographic history, and by extension concordance across taxa, may result from several different mechanisms , 76. Pare swamps . This suN. australis to capitalise on the colder temperatures and stronger rivers of glacial periods and subsequently expand. Similarly, historical connectivity across now-isolated river drainages [N. australis may have also facilitated range expansion if locally adaptive alleles were transferred into edge populations [N. obscura may have prevented them from expanding under these conditions, leading to the species-wide discordance. The spatial variation in the degree of concordance, with discordance occurring at the edge of the N. obscura pre-glacial refugium, supports this conclusion.Adaptive responses, particularly in scenarios of range expansion, are often driven by soft sweeps of SGV . While mrainages  likely frainages , 80. Thiulations . ContrasN. obscura may have contributed to their local extirpation and to the failure of reintroductions of captive-born offspring at range margins, as documented for the lower Murray-Darling Basin [N. australis that simultaneously took place in that site using the same captive-breeding design [Discordant species-wide responses to past climatic change may play an important role in contemporary genetic diversity and, by extension, current conservation efforts. For example, low genetic diversity resulting from historical bottlenecks can drive contemporary inbreeding depression . Additiong Basin . This cog design , 46.Understanding how, and which, species may be able to adapt under contemporary climate change remains a critical aspect of evolutionary biology . TypicalDifferences in long-term standing genetic variation drove discordance in the response of closely related and ecologically similar freshwater fishes to historical climate change, by potentially facilitating range expansion of one species but not the other. However, in the centre of a putatively shared habitat refugium, demographic histories were concordant, suggesting that spatial variation in the degree of concordance is linked to the interaction of standing genetic variation and distribution edge effects. Together, this demonstrates the importance of the maintenance of standing genetic variation for adaptive potential in response to climatic changes and the role of non-ecological traits in driving patterns of concordance or discordance.Additional file 1: Methods. Additional details of sequencing, demographic modelling and species distribution modelling methods. Table S1. Locality data for samples used in this study. Table S2. Breakdown of sequencing approach for all samples. Table S3. Prior ranges for individual population demographic models estimated within FastSimCoal2. Table S4. Pearson’s pairwise correlation for all 19 bioclimatic variables. Table S5. Model likelihoods for demographic syndrome models estimated using FastSimCoal2. Table S6. Posterior distributions of parameters from co-demographic models in Multi-DICE. Figure S1. Diagrammatic representations of demographic syndromes tested per population selected for codemographic analysis, using FastSimCoal2. Figure S2. Diagrammatic representations of codemographic models within Multi-DICE. Figure S3. Maps of occurrence data used for species distribution modelling. Figure S4. Histogram of missing data per sample in the species-wide alignments. Figure S5. Unrooted species trees inferred using SVDQuartets. Figure S6. Full maximum likelihood phylogenetic tree for N. australis. Figure S7. Full maximum likelihood phylogenetic tree for N. obscura.Figure S8. Gene and site concordance factors between gene trees estimated with individual RAD loci and the concatenated phylogenies. Figure S9. Likelihoods and percentage of variance explained in TreeMix models. Figure S10. Residual matrices under the best supported TreeMix models. Figure S11. Standard error of the covariance matrices under the best supported TreeMix models. Figure S12. Confusion matrix of ξ hyperparameter within the co-demographic Multi-DICE model. Figure S13. Ensemble species distribution models over time.


Despite their central economic and cultural role, the origin of cattle populations living in Indian Ocean islands still remains poorly documented. Here, we unravel the demographic and adaptive histories of the extant Zebus from the Mayotte and Madagascar islands using high-density SNP genotyping data. We found that these populations are very closely related and both display a predominant indicine ancestry. They diverged in the 16th century at the arrival of European people who transformed the trade network in the area. Their common ancestral cattle population originates from an admixture between an admixed African zebu population and an Indian zebu that occurred around the 12th century at the time of the earliest contacts between human African populations of the Swahili corridor and Austronesian people from Southeast Asia in Comoros and Madagascar. A steep increase in the estimated population sizes from the beginning of the 16th to the 17th century coincides with the expansion of the cattle trade. By carrying out genome scans for recent selection in the two cattle populations from Mayotte and Madagascar, we identified sets of candidate genes involved in biological functions  broadly representative of the physiological adaptation to tropical conditions. Overall, the origin of the cattle populations from Western Indian Ocean islands mirrors the complex history of human migrations and trade in this area. In this study, the authors inferred the demographic history of cattle from Mayotte and Madagascar islands using high-density SNP genotyping data. They found that it closely mirrors the complex pattern of human exchanges in the last centuries in the Western Indian Ocean. They further characterized the adaptive history of the two breeds providing insights into the main adaptive constraints experienced by these two populations since their arrival in the area. The Indian Ocean has played a prominent role in the human-mediated migration of cattle populations between East-Africa, Middle-East, and South-West Asia. However, the origin and genetic diversity of cattle populations living in Indian Ocean islands remain poorly investigated and relatively unclear. Their understanding may provide insights into the recent history of human populations in this area that has long displayed important levels of interaction, trade, migration, and domestic species translocation over time , 2019b.Within the large Indian Ocean area, the Comoro Islands  and Madagascar occupy a key position in the maritime trade routes that has linked the East-African coast, Middle East, and Asia over the past two millennia. Interestingly, cattle may have been introduced early in this area and have subsequently represented an important domestic species. In both Mayotte and Madagascar where human have permanently settled from the 6th century CE, the most ancient archaeological and skeletal evidence of cattle presence traces back to the 9th –10th centuries CE but the quantities of identified cattle bones only increased from 14th to 15th centuries CE . The firwww.fao.org). Both MAY and ZMA populations are considered to be well adapted to their respective islands conditions. In particular, they are generally regarded as more resistant to heat stress and tick-borne diseases than imported European breeds, such as African zebu and N’Dama breeds  by the French government for conservation purpose , includiIf the MAY zebu population has not been genetically characterized yet, previous genetic characterization of ZMA populations based on the analysis of a few tens of microsatellite markers or medium-density SNP genotyping data suggested a hybrid composition between African taurine (AFT) and indicine (ZEB) ancestries, the latter being predominant (n = 44) and the Lagune  West-African taurine breeds and to the Fulani West-African Zebu . These newly generated data were combined to publicly available BovineHD genotyping data for 363 individuals belonging to eight other breeds representative of EUT , another AFT (N’Dama), Indian Zebus (Gir and Nelore), and East African Zebus  together with 113 individuals belonging to the Somba  together with 24 Zebus of Madagascar (ZMA) and 113 West-African cattle DNA samples , sampled in the 1990s and previously genetically characterized on the Illumina BovineSNP50 beadchip , we selected a group of 32 presumably nonrelated individuals  representative of the phenotypic diversity of the local population. They each originated from 32 different farms located in 17 townships spread over the Grande and Petite terres of the Mayotte Island  could then be obtained for 721,583 SNPs (92.8%). Among the 53,750 remaining SNPs, the number of alignment hits ranged from 2 to 1,790 and followed a L-shaped distribution with a median and mean values of 3 and 20.2, respectively. As a matter expedience, we thus chose to discard from further analysis the 15,533 SNPs with more than 9 alignment hits (i.e. the third quartile of the aforementioned distribution) and to assign to the 40,846 other SNPs (with 2–9 hits) the position given by the alignment with the highest score. We indeed noticed that for these latter SNPs, multiple alignments mostly consisted of a single high scoring hit (score > 100 for 99% of them), the other alternative hits being generated by partial alignment of only a few tens bases of the SNP sequence.To obtain the position of the 777,962 SNPs included in the BovineHD genotyping assay onto the latest ARS-UCD1.2 (aka bosTau9) bovine genome assembly (ng pblat  run withwww.illumina.com) representative of the bovine worldwide genetic diversity . Finally, the overall and pairwise-population STF were computed with version 2.0 of the R package poolfstat  based on individual SNP genotyping data was performed with smartpca . Unsuperf-statistics based demographic inference  and within-population heterozygosities. As for STF, standard-errors of the estimated statistics (and their corresponding Z-scores for f3 and f4) were estimated using block-jackknife defining blocks of 5,000 consecutive SNPs . In addition, to mitigate SNP ascertainment bias by favoring SNPs of most remote ancestry (i.e. discard SNPs of exclusive European ancestry), we only kept for f-statistics based demographic inference the 497,949 polymorphic SNPs that were polymorphic (MAF>0.05) in both ZEB (GIR and NEL combined) and in AFT  populations. Following f3 statistics. A negative Z-score  consisting of two AFT breeds (NDA and LAG), two ZEB breeds (GIR and NEL), and one EUT breed (HOL) with the rooted.njtree.builder function. We further relied on the graph.builder function (ran with default options) to jointly include EAZ, MAY, and ZMA that showed clear evidence for admixture on the graph considering all the six possible orders of inclusion. The fit of the best fitting graph  was further validated with the compare.fitted.fstats function that allows to compare to which extent the estimated f-statistics depart from their predicted values based on the fitted admixture graph parameters via a Z-score (We estimated the timing of admixture events (in generations) with the program mALDER . Such a eN) were inferred for the MAY and ZMA breeds with the program GONE that implements an approach recently developed by eN trajectories by first identifying 55 nonoverlapping blocks of 10,000 consecutive SNPs (block size ranging from 32.8 to 40.2 Mb) out of the 680,338 genotyped ones. We then analyzed 55 different data sets of 670,338 SNPs that were each formed by removing from the original data sets one block of 10,000 SNPs. The resulting 55 inferred eN trajectories were then summarized by computing a mean trajectory and a 95% confidence envelope defined by the 2.5 and 97.5 percentiles from the 55 estimated eN at each time point.Historical effective population sizes  allowing to capture the contribution to the overall individual inbreeding levels from each age-based classes of ancestors .The characterization of individual levels of inbreeding at a global and local scale in MAY and ZMA breeds was performed with the model-based approach implemented in the RZooRoH package . Each HB-Ku40 -Kl10 -Ki10. Genetic distances between consecutive SNPs were obtained from physical distances assuming a cM to Mb ratio equal to 1 (see above). Based on haplotype information, we further computed the iHS (Rsb (iHS) or across populations (Rsb). Note that for the computation of iHS within MAY and ZMA populations, we chose to not polarize the SNP alleles (i.e. scan_hh function was run with option polarized=FALSE) as discussed in section 7.6 of the online rehh package vignette (https://cran.r-project.org/web/packages/rehh/vignettes/rehh.html). The different SNP iHS and Rsb statistics were further transformed into iHS and Rsb scores are normally distributed under neutrality, iHSp and Rsbp might thus be a 2-sided The genome-wide scan for footprints of positive selection within and between MAY and ZMA breeds was performed using extended haplotype homozygosity (EHH)-based tests. To that end we first jointly phased the genotyping data for MAY, ZMA, EAZ, GIR, and NEL individuals with version 1.4 of the fastPHASE software  for eachiHS . A SNP was then considered as representative of one of these RefSeq genes if localized within its boundary positions extended by 15 kb upstream and downstream to account for persistence of LD . Among the 13,535 genes symbols taken into account in the analysis, 12,324 were mapped in the Ingenuity Pathway Knowledge Base (IPKB) and were considered as the reference data set. Among the candidate genes identified for MAY (N = 27) and ZMA (N = 47) breeds, 24 and 45 were respectively mapped to IPKB. The top significant functions and diseases  were obtained by comparing functions associated with the candidate genes under selection against functions associated with all genes in the reference set, using the right-tailed Fisher exact test. In the network analysis, a score S was computed for each network that contained at most 140 molecules (including candidate genes under selection) based on a right-tailed Fisher exact test for the over-representation of candidate genes under selection  and ZMA (n = 23) populations together with 473 individuals belonging to 11 cattle breeds representative of the bovine genetic diversity  is relevant to study their genetic history at the population level  associated Z-score equal to –3.92] and the NDA/NEL pair for MAY [f3 associated Z-score equal to –6.38]. Among the 11 other populations, EAZ, ZFU, and SOM also showed clear evidence for admixture with 14, 14, and 6 f3-based tests with a significantly negative Z-score (at the 99% significance threshold), respectively. For each of these three target populations, the lowest Z-score was always associated with the LAG/NEL pair of source proxies .Out of the 66 possible To infer the history of MAY and ZMA ancestry, we constructed an admixture graph relating these two populations with two out of the three AFT breeds , the two ZEB breeds (GIR and NEL), one (HOL) out of four EUT breeds and the EAZ African hybrid. We did not seek to include ZFU as it was more remotely related to East-African populations with a recent origin not directly informative for the MAY and ZMA history (y-intercept) estimate of the fitted weighted LD curve was obtained with NDA and NEL as source proxies which suggests that these populations are the closest (among the sampled ones) to the actual source population .We estimated the timing of the two aforementioned admixture event eN was about twice lower in MAY compared to ZMA. More precisely, the harmonic mean of the (mean) historical eN from generation 80 (76 for ZMA) onward was found equal to 2,160 and 1,045 for ZMA and MAY, respectively. Surprisingly, a close inspection of the inferred admixed graph in eN since the estimated (leave) branch lengths was about twice higher for ZMA compared to MAY. This thus rather suggested increased drift in ZMA since these estimates  might be interpreted under a pure-drift model of divergence as inversely proportional to eN . Population-specific STF estimates for MAY and ZMA essentially confirmed this trend  with MAY receiving twice as many migrants as ZMA from a common gene pool (vs. =2×10−3) .eN . Hence, most of the estimated inbreeding level originated from the foundation of the two populations. Consistently, only a few individuals displayed a high proportion of HBD segments associated with the most recent common ancestors, two generations ago. More precisely, two MAY individuals showed more than 49% of their genome in HBD classes and two ZMA individuals showed more than 40% of their genome classified has HBD.In order to characterize individual levels of recent inbreeding at both a global (genome-wide) and local (locus-specific) scale, we estimated the individual inbreeding coefficients in MAY and ZMA populations by applying the method implemented in RZooRoH software . OverallNe , most HBrehh 3.1.2 , the computation of the iHS statistic for each SNP over the whole MAY and ZMA genomes detected two (i.e. GRIK2 and RBM47) and 12  genes under selection located on two (i.e. BTA6 and 9) and six  chromosomes, respectively , 3, 16, 12, 18, 11 and 11 candidate genes were identified with the Rsb involving MAY or ZMA populations were different . However, seven candidates genes  were identified under selection in both breeds by some of these tests. Specifically, GRIK2, located on BTA9 was found under selection by five tests , two geographically closely related island cattle populations from the Western Indian Ocean, showed that they share a similar recent and rather complex demographic history. In particular, we detected in these two populations a weak African taurine ancestry and a predominant indicine ancestry. The indicine ancestry in MAY and ZMA was even higher than in the East-African zebu breed, the African continental breed with the highest estimated indicine ancestry proportion in our dataset. This pattern had already been reported for ZMA in some previous studies  based oneN. More specifically, in both populations, the contribution to individual inbreeding levels of HBD classes of most recent origin  and human-driven constraints imposed to the common ancestral population of MAY and ZMA breeds (i.e. predating their divergence). Among these genes, TRIM10 and TRIM15 are involved in innate immune response and were already detected under selection in Muturu cattle in Africa (From the 12th century (i.e. ca. 150 generations ago) onward, cattle living in Comoros and Madagascar islands have likely experienced various environmental and artificial selection pressures. To identify their footprints in the MAY and ZMA breeds, we relied on EHH-based tests considering different contrasts that our detailed inference of the demographic history helped interpreting. First, it should be noticed that only a few candidate genes were found in common in the two populations when comparing the various population-specific signals. These include (1) two genes (TRIM10 and TRIM15) with significant n = 18 vs n = 3) were found with this test, as expected from the twice highest eN of ZMA over the period which may result in improved detection power. Among the three genes that display significant signals in the MAY breed , GSTCD is involved in lung function and was identified as CNVR-harbored gene associated with adaptation to hypoxia in yak population  are related to cancer and skin properties and may have played a role in adaptation to Mayotte and Madagascar climates by increasing tolerance to thermal stress, humidity, and UV exposition. Respiratory function in which some candidate genes are involved (e.g. GSTCD in MAY) may also be related to tropical environment adaptation, breeds from warm climates presenting lower respiration rates under heat stress to maintain their body temperature. Several genes carrying footprints of selection are involved in nervous system and cattle behavior (e.g. GRIK2 in MAY and ZMA) which indicates also a physiological adaptation to the livestock system and the proximity with breeders in both islands. Development of different organs or physiological structures, gastrointestinal and hepatic system function, metabolism, and hormone production are also among the main functions targeted by selection in the two breeds . If these signatures of selection could be related to artificial selection on conformation and production traits, they could also be linked to the adaptation to tropical climate (e.g. through thermoregulation) and to available food and water resources. At last, several candidate genes involved in inflammatory and immune response  play a role in adaptation of Mayotte and Madagascar breeds suggesting that tropical pathogens responsible for e.g. as East Coast Fever, Rift Valley Fever, or blackleg documented outbreaks, may have had a deep impact on the adaptive genetic diversity of MAY and ZMA breeds  and in the portal Data INRAE .SNP genotyping data are available in the WIDDE database (G3 online.jkac029_Supplemental_FiguresClick here for additional data file.jkac029_Supplemental_TablesClick here for additional data file.


Gadus morhua) was previously identified as the highest outlier based on FST in a RADseq study of Pacific cod  across the West Coast of North America. However, because of the limited length of the RAD sequence and restricted geographic area of sampling, no conclusion on the functional significance of the observed variation was possible. In other marine species, ZP3 is involved in reproductive isolation, local adaptation, and has neofunctionalized as an antifreeze gene, and so it may provide important insights in functional population structure of Pacific cod. Here, we sequenced a 544‐bp region of ZP3 in 230 Pacific cod collected from throughout their geographic range. We observed striking patterns of spatial structuring of ZP3 haplotypes, with a sharp break near Kodiak, Alaska, USA where populations within ~200 km of each other are nearly fixed for different haplotypes, contrasting a pattern of isolation by distance at other genetic markers in this region (FST = 0.003). Phylogenetic analysis of ZP3 haplotypes revealed that the more southern haplotypes appear to be ancestral, with the northern haplotype evolving more recently, potentially in response to a novel selective pressure as Pacific cod recolonized northern latitudes after glaciation. The sharp break in haplotype frequencies suggests strong selective pressures are operating on small spatial scales and illustrates that selection can create high divergence even in marine species with ample opportunities for gene flow.Genetic differentiation has been observed in marine species even when no obvious barriers to gene flow exist, and understanding such differentiation is essential for effective fisheries management. Highly differentiated outlier loci can provide information on how genetic variation might not only contribute to local adaptation but may also be affected by historical demographic events. A locus which aligned to a predicted zona pellucida sperm‐binding protein 3 gene (ZP3) in Atlantic cod ( We document a sharp break in haplotype frequencies for a putative sperm‐binding protein zona pellucida subunit 3 in Pacific cod. Results suggest strong selective pressures are operating on small spatial scales and illustrate that selection can create high divergence even in marine species with ample opportunities for gene flow. While the ocean offers few apparent boundaries to long distance dispersal at any life stage, population divergence has been observed in many species  provide an interesting case study to investigate the effects of selective differentiation. Pacific cod are found demersally throughout the Western Pacific as far south as the Korean Peninsula, northward to the Bering and Chukchi Sea, throughout the Aleutian Islands and southward along the eastern Pacific as far as northern California. Populations at the southern edges of both the eastern and western Pacific show deep genetic divergence from northern populations  throughout the North Pacific that display a general isolation‐by‐distance pattern indicating somewhat limited dispersal . ZP3 egg coat proteins are part of a multigene family that is central to reproductive isolation and prevention of polyspermy in mammals  study Table  was a geIn this study, we used DNA sequencing to assess geographic variation and examine signals of selection in the putative ZP3‐coding gene among samples representative of the range of Pacific cod. We also integrated ZP3 data with a previously published RADseq dataset  and 72°C for 30 s, and then by 30 cycles of 98°C for 10 s, 58°C for 30 s, and 72°C for 30 s, and concluded at 72°C for 5 min.Following this initial screening, a single set of primers was designed to focus on variable regions observed in Exons 2, 3, and 4 in the ZP3‐coding region  and nucleotide diversity (π) were calculated using the R package pegas. We calculated expected heterozygosity (He) per population using the estimator θH, which corrects for potential overestimation when few loci are present, in Arlequin v. 3.5  was calculated as the proportion of heterozygous individuals , out of the total number sequenced. FIS was calculated by haplotype as FIS = 1–Ho/He  and 107 Markov Chain replicates. We enumerated the number of transitions and transversions over all haplotypes.ata Nei, . GST ca Winter, . DendrogHe Nei, . Fisher’2.3N) and synonymous (dS) substitutions were enumerated based on open reading frames from the predicted Gadus morhua zona pellucida sperm protein 3‐like sequence (GenBank Accession number XM_030365288). Several tests were performed to test for selective neutrality. The Ewens–Watterson homozygosity test for selective neutrality and an exact test for selective neutrality based on Ewens’ sampling theory were performed in Arlequin v. 3.5 with 16,000 simulated samples. The exact test based on Ewens’ sampling theory  were calculated from the data and the expected F was generated from a simulated random neutral sample with the same number of haplotypes. For the exact test and the Ewens–Watterson homozygosity test, small probability values, p = Pr (FEXP ≤ FOBS) indicate balancing selection , while large values indicate directional or divergent selection ; note that these p values are not statistical test probabilities but the placement of an observed value in a distribution of values expected under neutrality. Tajima’s D test was calculated as an additional measure of statistical neutrality in pegas, and p‐values were calculated based on the assumption that D follows a beta distribution scaled from 0 to 1. A negative value of Tajima’s D indicates population size expansion, such as after a bottleneck or a selective sweep and/or purifying selection, while a positive value indicates balancing selection or decrease in population size. Tajima’s D was not calculated over multiple collections, as an admixed sample can result in the appearance of an excess of low‐frequency mutations  for detecting changes in population size . First, the RADseq dataset was aligned with gadMor3.0 using bowtie2 v. 2.2.6 software  . New primers (ZP_GM) were designed to sequence variation observed in Exons 2, 3, and 4 because primer ZP_L2 did not amplify in all collections Table . Data foSequences were trimmed to a final length of 544 bp, which included 40 amino acid residues from Exon 2, 35 amino acid residues from Exon 3, and 4 amino acid residues from Exon 4. There were nine variable sites; three were located in exons and six in introns , with probabilities of .272, .256, and .469. This was a unique case with two heterozygous sites and probabilities were constrained to sum to 1. While 3.2There were 14 unique DNA haplotypes present among all sample collections Table . The mosTranslation of the coding regions into amino acid sequences resulted in eight segregating polypeptide sequences Table , with thTests for Hardy–Weinberg equilibrium indicated that genotype frequencies in most of the Eastern Pacific collections deviated significantly from HWE . In contrast, Kiska was the only collection in the Bering Sea that deviated from HWE, and in this collection, 11% of the haplotypes represented a unique variant Table . HWE was3.3GST was not found to be dependent on sample size (R2 = 0.07). Global GST was 0.551, with 95% confidence intervals 0.514–0.588. The dendrogram based on GST at ZP3  at position 523, which was not variable in Pacific cod. Within Pacific cod sequences, there were five transitions and four transversions Table .dF81, indicating the greatest similarity to gadMor3.0, followed by Haplotypes 12 and 5, and then Haplotypes 9 and 11 (Table The model with the lowest BIC score was a four‐parameter model with a proportion of invariable sites (I) and a moderate number of parameters, 31  and the exact test based on Ewens’ sampling theory (Slatkin’s p) (>0.9), indicative of directional selection, were observed within the Kodiak collections, and within the combined Bering Sea . The global FST associated with that SNP was 0.71. Linkage disequilibrium decayed quickly along LG09, and only seven SNPs that were <0.025 Mb apart had R2 values > 0.20 ; Data curation (lead); Formal analysis (lead); Funding acquisition (lead); Investigation (lead); Methodology (lead); Project administration (lead); Writing‐original draft (lead). Daniel P Drinan: Conceptualization ; Methodology . Eleni Leto Petrou: Investigation ; Methodology ; Visualization ; Writing‐review & editing . Rory Spurr: Data curation ; Investigation ; Methodology . Carolyn Tarpey: Data curation ; Formal analysis ; Writing‐review & editing . Theodore Hartinger: Conceptualization ; Data curation ; Formal analysis . Wesley A. Larson: Formal analysis ; Writing‐review & editing . Lorenz Hauser: Conceptualization ; Project administration ; Writing‐review & editing .