AbstractOctopusminor is an economically important resource commonly found in Chinese coastal waters. The nuclear gene (RD and ODH) approach of investigation has not reported in this species. Rhodopsin (RD) and octopine dehydrogenase (ODH) genes were used to elaborate the genetic structure collected from eight localities ranging from the northern to the southern coast of China. In total, 118 individuals for the RD gene and 108 for the ODH were sequenced. Overall (RD and ODH) genes resulted in high  haplotype and low nucleotide  diversity. Molecular variance displayed higher values among the populations and lower values within the population where the fixation index FST denoted 0.880 and 0.584 in RD and ODH genes respectively. The Dongshan population clustered separately in a phylogenetic tree as in the haplotype networking assessment. The current data suggests that the Dongshan population needs separate management. Cephalopoda embraces animals which are exclusively marine inhabitants. They have immense commercial and ecological significance, including a profound contribution as a source of protein for humans. The cephalopod has lobed and folded brain like that of vertebrates and are ingenious, migrant and largest of all molluscs  were performed using formula mN= (1-FST)/2FST. Haplotype and nucleotide diversity were estimated using DnaSP Rhodopsin Gene  ranged from 0.090 to 0.833, nucleotide diversity (π) remained in the lower range (0.00027–0.001), where the average number of differences (k) ranged from 0.166 to 1.388 Octopine dehydrogenase  than nucleotide diversity (π) (0.001–0.004). The average number of differences (k) ranged from 0.444 to 2.733 (Table ST) was determined as 0.584 , the higher haplotype diversity was noted in Xiamen population and lowest haplotype diversity showed in Dongshan population. The ODH gene haplotype diversity was higher in Shanghai population (1.000) and was lowest in Wenzhou population (0.222). Comparative studies of RD and ODH gene showed higher values  in Xiamen population. Yang et al. (2015) included five populations and reported that Qingdao has high diversity and more diverse than others but present research described high diversity of all northern populations  reported lower AMOVA values (10.88%) between populations and higher values (89.12%) within population, which is discordant. Higher FST values indicate a lower level of gene flow (Nm) and higher genetic differentiation among populations  because the geographic coastal distance between Dongshan and Xiamen is only 157 KM while the gene flow between them is meagre as shown by RD and ODH , whereas the coastal distance between Dalian and Xiamen is approximately 3700 Km but the gene flow is higher . O.vulgaris including high mortality, philopatric behaviour of larvae and potential cryptic berries. Nevertheless, the above-mentioned factors are difficult to be disentangled, furthermore, oceanic fronts , upwelling and current systems can also influence the larval dispersal (O.minor gave high haplotype diversity in this region, including the present study.The Tajima’s D analysis of the  studies . The ODHigations  where thigations . Neverthigations  where Weispersal . It has ispersal . Howeverispersal . Most ofO.minor along the Chinese coast and it also shed light on the need for separate management of the Dongshan population: once an evolutionary lineage is lost, there is no possibility to be recover it (O.minor reported along Chinese coastal waters.Our present investigation has significant implications for conservation and favourable management of cover it . We also


Ornithonyssus sylviarum, is an obligatory hematophagous ectoparasite of birds and one of the most important pests in the poultry industry on several continents. Although NFM poses a serious problem, it remains a neglected pest of poultry in China and other Asian countries. Therefore, a molecular analysis was conducted to provide baseline information on the occurrence, genetic diversity and emergence of NFM in poultry farms from China.The northern fowl mite (NFM), cox1 gene and phylogenetic analysis. We have also used the DNA sequences of the cox1 gene to study the genetic diversity, population structure and demographic history. The neutrality tests were used to analyze signatures of historical demographic events.This study focused on morphological description and identification of adults based on electron microscopy, molecular sequencing of the mitochondrial Ornithonyssus sylviarum based on external morphological characterization using electron microscopy. Molecular analysis using a 756-bp long partial fragment of the cox1 gene revealed 99–100% sequence identity with NFM and phylogenetic inferences showed a bootstrap value of 99% indicating a well-supported monophyletic relationship. Molecular diversity indices showed high levels of haplotype diversity dominated by private haplotypes, but low nucleotide divergence between haplotypes. The Tajima’s D test and Fu’s Fs test showed negative value, indicating deviations from neutrality and both suggested recent population expansion of mite populations supported by a star-like topology of the isolates in the network analysis. Our genetic data are consistent with a single introduction of NFM infestations and the spread of NFM infestation in Hainan poultry farms and a private haplotype dominance, which suggest that infestations are recycled within the farms and transmission routes are limited between farms.The mites collected were identified as the northern fowl mite To our knowledge, this is the first time a molecular report of NFM in chicken from China including other Asian countries using DNA barcoding. The findings have potential implications with respect to understanding the transmission patterns, emergence and populations trends of parasitic infestations of poultry farms that will help for setting the parameters for integrated pest management (IPM) tactics against mite infestations. Ornithonyssus sylviarum,  (Mesostigmata: Macronyssidae), was first discovered in Pisa, Italy, in 1877 [Ornithonyssus bursa and the poultry red mite (PRM) Dermanyssus gallinae, are largely considered as avian-specific ectoparasites, when natural host is absent, hungry mites will occasionally feed on a range of mammals, i.e. dogs [D. gallinae (Mesostigmata: Dermanyssidae) was first identified by De Geer in 1778 and the tropical fowl mite, O. bursa  (Mesostigmata: Macronyssidae) was first recognized as a potentially serious poultry pest by Wood [D. gallinae feeds mainly at night and for short periods of time. The rest of the time, mites reside in multi-stage colonies in cracks, crevices and hide away from the birds for the remainder of the time [The northern fowl mite (NFM),  in 1877 . It is o in 1877 . Althoug.e. dogs , cats [5.e. dogs , and hum.e. dogs . The pou by Wood . Tropica by Wood , 13. Sup by Wood . Unlike the time . In contthe time , 17. Thethe time , 18. NFMthe time . Althougthe time . PRM hasthe time . The trothe time . In Chinthe time  found ththe time . This suthe time .c oxidase subunit 1 (cox1) has been used as successful genetic marker in barcoding of mites. Many studies have demonstrated that cox1 can provide a powerful tool for phylogenetics at the deepest levels within the Acari [cox1 has been known as the ‘barcoding gene’ and it has proven successful for its use for species identification and discovery across a variety of animal organisms [cox1 data generated for a variety of organisms in public databases. More importantly, the analysis of intraspecific mtDNA variation can also reveal information about the interconnectivity of populations and past demographic events such as population expansions [Although exact species identification is an important first step in any biological study, species that are closely related can be difficult to distinguish by the use of morphological characters alone because of similar gross morphology, unclear or inconsistent diagnostic morphological characters and high levels of morphological plasticity –25. Morehe Acari –31, and he Acari . cox1 harganisms . The usepansions .cox1 gene and assess the population structure of NFM from different localities. A further aim of this study was to use molecular genetic approaches to gain insight into the patterns of emergence and spread of O. sylviarum infestation in Hainan poultry farms, providing proof of concept for a novel approach to the study of parasite epidemiology, and eventually supports the formulation of an effective control strategy.China produces more than 40% of all the eggs in the world, making it the worldʼs largest egg producer . These l2, sputter-coated with gold using an Anhui Beq SBC-12 coating apparatus, and examined using a field emission scanning electron microscope .The sampling was carried out between May and November 2018, across seven different locations within Hainan Island ; BC (n = 12); WB (n = 14). Total genomic DNA was extracted from individual mites using a QIAamp® DNA Mini Kit  and protocols therein with some modifications. DNA extraction was carried out following previously described protocols [cox1 forward primer OS6F (5′-GTG CAG GGA CTG GAT GAA CT-3′) was designed in the present study using NFM cox1 sequences available on GenBank . Sequences were downloaded and aligned by ClustalW algorithm using the EMBL site [′-TAC AGC TCC TAT AGA TAA AAC-3′) was previously reported [Escherichia coli strain DH5-Alpha competent cells, according to the manufacturer’s instructions. Plasmids from positive colonies were isolated using SanPrep Column Plasmid Mini-Preps Kit  according to the manufacturer’s instructions and subjected to Sanger sequencing on an ABI PRISM 3730 XL DNA Analyzer, using a BigDye® Terminator v3.1 Cycle Sequencing Kit . Both strands were sequenced for all PCR products to ensure good quality of the sequences used in the subsequent analysis. This sequence protocol generated a 756-bp fragment from Ornithonyssus sylviarum to be used in the analysis (without primer region).The number of samples for DNA extraction in each farm was set to a minimum 12 mites from each population; QA . However, traditional phylogenetic methods have poor statistical power because intraspecific data sets have small genetic distances between individuals [The obtained chromatograms were imported into Contig express module in Vector NTI  and any flanking sequence containing PCR primers were manually removed before sequence alignment and phylogenetic analysis. Forward and reverse chromatograms were assembled in pairs for each sample. First, all sequences generated were aligned by a ClustalW algorithm  using thividuals . Therefoividuals . This haividuals . Sequenccox1 sequence (DNA barcoding marker) were performed using MEGA version 7.0 [Fst) was tested by 1000 permutations of the data matrix. The neutrality indices of Tajimaʼs D and Fuʼs Fs in each population were also calculated using Arlequin 3.5.1 version, with P-values generated using 1000 simulations under a model of selective neutrality [D uses the frequency of segregating nucleotide sites, while Fu’s Fs uses the distribution of alleles or haplotypes [To confirm our study in the context of divergence within the species, analyses on divergence of sion 7.0  based onsion 7.0 . Haplotysion 7.0 . Arlequision 7.0 . The sigutrality . Tajima’plotypes , 57. BotP < 0.05 for all statistical analyses. Molecular diversity indices data were expressed as the mean ± standard deviation (SD).All data were entered in Microsoft Excel 2016. The significance level was set to A total of seven farms were sampled representing a total of 281,000 birds, of which two farms were for parent birds , five farms were for commercial layer and broiler birds . Three farms were infested with NFM representing a total of 120,000 birds, of which one farm was for parent layer birds and the other two were commercial layer farms . The main feature differentiating NFM from PRM is the shape of the anal plate and the presence of elongate chelicerae in females with movable digit present in NFM but absent in PRM  showed 100% similarity to the Swedish strain (GenBank: KF218580) whereas the others showed more than 99% identity. The coverage score was however not high, as no available NFM sequences in the database covered the complete regions described in our dataset. There was< 86% sequence identity to Ornithonyssus bacoti (GenBank: FM179677.2) and< 80% identity to D. gallinae (GenBank: LC029547.1). A combined length of 756 bp of the cox1 gene for a total of 38 isolates from three different farms were used to determine intraspecies sequence variability. The overall nucleotide compositions were 42.1% T, 28.7% A, 16.6 % C and 12.5% G. This high A-T content  is consistent with the general feature of the cox1 mitochondrial DNA region in arthropods, and is similar to cox1 data from other studies on insects and other mite species [DNA concentration on the mite extracts ranged from 13.2 to 38.6 ng/μl. PCR amplification was successful for 99% of the samples. A nucleotide BLAST (megablast/blastn) of the generated sequences in NCBI GenBank database confirmed the identity of the species as all top hits were of  species , 47. TheAn alignment using the shorter GenBank NFM entries included in the phylogenetic calculations, and flanking sites were not included in the analysis. Neighbor-Joining and Maximum Likelihood trees had virtually equivalent topologies. The results of NJ analysis with bootstrap values are shown in Figs. cox1 haplotypes in each Hainan population are shown in Table Fst values for genetic differentiation varied from 0.02625 to 0.01299. The pairwise Fst values among QA, BC and WB populations were relatively low and with non-significant P-values, except for the comparison between QA and WB, indicating very little genetic differentiation. The pairwise Fst with P-values between the locations are shown in Table Fst values.A total of 32 haplotypes were identified in the 38 samples. Among these identified haplotypes, 29 haplotypes were detected as singletons (unique to a single population) and three haplotypes H9, H13 and H14) were most widely shared. Haplotype 9 was the most common in each population . The relative frequencies of the 3 and H14D test and Fu’s Fs test are presented in Table P-values. Tajima’s D values were significantly negative for all populations, indicating an excess of rare nucleotide site variants compared to the expectation under a neutral model of evolution. The results of Fu’s Fs test, which is based on the distribution of haplotypes, also showed highly significant negative values for all populations, indicating an excess of rare haplotypes over what would be expected under neutrality. Following this test, the hypothesis of neutral evolution was rejected for all populations.The results of Tajima’s O. sylviarum spends its entire life attached to its host, whereas poultry red mites are nocturnal active ectoparasites which typically (though not exclusively) during short visits suck the birds’ blood during periods of darkness and hide themselves in all kinds of gaps and cracks during the daytime [The northern fowl mite,  daytime , 19. Thi daytime . To the  daytime . A range daytime , 59.cox1 gene. This molecular marker is known to be highly polymorphic within species, hence its widespread use in analyses of intraspecific variation [It is not surprising that the data in this study reported a high degree of variability within the ariation . Accordiariation , intraspariation . The paiariation  to estimZachvatkinia isolata [D and Fu’s Fs test) were negative with highly significant P-values, particularly for the Fu’s Fs test for all populations. The overall negative values resulting from both tests indicate that there is an excess of rare mutations in the populations, which imply a recent population expansion. An analysis including additional neutral nuclear DNA markers could give a more complete perspective on the neutral population structure of these mite populations. Population expansion from a small effective population can be influenced by the following factors. First, the entire life-cycle is short, and large populations can develop rapidly on the birds just after 5 to 12 days [A major finding of this study was the high haplotype diversity and the low nucleotide diversity, indicating only small differences between haplotypes. This was also evident from the Median-Joining network, which showed mostly single nucleotide differences between haplotypes Fig. . In addi isolata , and is  isolata . In this 12 days . ConsequFst pairwise values between two populations (BC and WB) were very low (0.00194) with a high P-value, three shared haplotypes and four shared branches in the network, indicating no divergence between populations  were relatively high (0.02625) with a significant P-value and no shared branches in the analysis, but still shared a common haplotype with the other populations. The distance between the two farms is nearly 120 km . For these two populations, the genetic distance value indicated that the geographical distance is one of the factors causing differences in genetic distance values, the farther the distance between populations, the higher the genetic distance value. It is not surprising that the overall Fst values are relatively low since they probably came from the same source and a bottleneck population  and are still expanding. Furthermore, a star-like gene tree of this part of the network indicates very little geographical structure. Finally, although we identified high genetic diversity, there was little evidence for differentiation between populations, indicating a single panmictic population.In terms of population structure, the ns Table , Fig. 7.Ornithonyssus spp. mites [cox1 gene sequencs for NFM from Asian countries, as all information is originated from European countries, USA or Canada. To our knowledge, the present study reports, for the first time, mitochondrial cox1 sequence data for O. sylviarum from China which could provide essential information on the genetic structure of NFM populations circulating in Hainan Island. A further aim of the present study was to use novel molecular genetic approaches to gain insight into the emergence and spread of NFM infestation in Hainan. At the farm level, infestation may emerge singly or on multiple occasions through animal movement [D. gallinae; mostly single haplotypes were found on most farms, suggesting that infestations are recycled within the farms and the transmission routes are few between farms [Calicophoron daubneyi infection in United Kingdom cattle herds, as multiple common haplotypes were identified in 26 populations [The molecular toolbox is largely unexplored regarding p. mites . At presmovement . The ideen farms . In contulations . It is aulations .O. sylviarum in China. These findings demonstrate a single introduction of a mite population at the farm level followed by extreme population expansion. Our dataset is limited, so further research is needed in order to understand possible transmission routes of this parasite, and to access the significance of its genetic variation and diversity in understanding the epidemiology and biology of this parasite.This study highlights the importance of an integrative approach in taxonomic studies, combining morphology and molecular features. To our knowledge, this study describes for the first time key comparative morphological features for differentiating three mite species sharing the same host species and environment. Our genetic data also provide the first insight into the emergence and the spread of


Gadus morhua) populations in the Gulf of Maine (GoM) are at a fraction of their historical abundance, creating economic hardships for fishermen and putting at risk the genetic diversity of the remaining populations. An understanding of the biocomplexity among GoM populations will allow for adaptive genetic diversity to be conserved to maximize the evolutionary potential and resilience of the fishery in a rapidly changing environment. We used restriction-site-associated DNA sequencing (RADseq) to characterize the population structure and adaptive genetic diversity of five spawning aggregations from the western GoM and Georges Bank. We also analyzed cod caught in the eastern GoM, an under-sampled area where spawning aggregations have been extirpated. Using 3,128 single nucleotide polymorphisms (SNPs), we confirmed the existence of three genetically separable spawning groups: (1) winter spawning cod from the western GoM, (2) spring spawning cod, also from the western GoM, and (3) Georges Bank cod. Non-spawning cod from the eastern GoM could not be decisively linked to either of the three spawning groups and may represent a unique component of the resource, a mixed sample, or cod from other unsampled source populations. The genetic differentiation among the three major spawning groups was primarily driven by loci putatively under selection, particularly loci in regions known to contain genomic inversions on linkage groups (LG) 7 and 12. These LGs have been found to be linked to thermal regime in cod across the Atlantic, and so it is possible that variation in timing of spawning in western GoM cod has resulted in temperature-driven adaptive divergence. This complex population structure and adaptive genetic differentiation could be crucial to ensuring the long-term productivity and resilience of the cod fishery, and so it should be considered in future management plans.Atlantic cod ( Identifying stock boundaries of marine populations remains a challenge despite rapid advances in genetic stock identification methods due to the considerable complexity in the population structure of many marine species . Most maGene flow is often used to infer demographic connectivity, so that groups connected by high gene flow are often considered as one continuous stock. However, populations can be demographically independent despite high gene flow . FurtherGadus morhua) is complex [Population structure of Atlantic cod  are at a fraction of their historical abundance ,43. Curret al., [et al., [In their investigation of genetic stock structure in the GoM using microsatellites, Kovach et al.,  found ge[et al.,  also fou[et al., –51 and h[et al., –55, temp[et al., ,56, betw[et al., ,55,57,58[et al., ,53. Ther[et al., ,24.To date, no genetic studies have focused on cod in the eastern GoM (from US waters off midcoast and eastern Maine). Ames’  analysisIn this study, we used genome-wide genetic data to analyze both the neutral and putatively adaptive population structure of cod in the GoM. We sampled seasonally divergent spawning aggregations in the western GoM to characterize gene flow and adaptive divergence between populations that spawn in the same locations but in different seasons. We also investigated connectivity among these western GoM spawning aggregations, a Georges Bank spawning aggregation, and cod caught by the sentinel fishery in the eastern GoM that were not in spawning condition. If there were distinct subpopulations in the eastern GoM, as hypothesized ,20, and et al., [For the western GoM, fin clip samples from spawning adult cod were collected on known spawning grounds in Ipswich and Massachusetts Bays at two distinct spawning seasons–late spring (May/June) and winter , following the manufacturer’s protocols. RAD libraries were prepared and sequenced by Floragenex Inc. , following standard protocols of . LibrariRaw read quality was assessed with FastQC  and readSNP calling was performed using the ipyrad v0.7.21 pipeline  mapping p < 0.01 significance level. PGDSpider [After SNP calling, SNPs were further filtered using vcftools v0.1.15  so that GDSpider  was usedST outlier method implemented in BayeScan [ST among spawning aggregations within the GoM [ST outliers, to create our putatively neutral SNP dataset, hereafter “neutral dataset”. Further analyses were conducted with and without these outlier loci and are referred to as the full dataset and neutral dataset, respectively.To identify a putatively neutral SNP dataset for determining gene flow among groups, we first thinned the data using vcftools such that SNPs were at least 10 kb apart to avoid tightly linked SNPs. We then used the FBayeScan  to identBayeScan , and in  the GoM . TherefoST values between groups were calculated for the neutral and full SNP datasets with the Hudson estimator as it has been shown to be insensitive to variation in sample sizes and was found to be unbiased when tested on SNP datasets [et al., [Pairwise Fdatasets ,75. To c[et al., , correctadegenet v2.1.1 packages in R [scaleGen function, and missing values were replaced by the mean allele frequency. PCA was performed with the dudi.pca function.Population structure was visualized with both datasets using a principal components analysis (PCA), performed using the ges in R –79. Befofind.clusters algorithm suggested the most likely number of clusters within the data was equal to one (K = 1) for both datasets, suggesting population differentiation was subtle, and so we used the a priori clustering of individuals by group instead. The number of principal components (PCs) to retain was estimated by cross-validation using the xvalDAPC function with 1000 replicates [Discriminant Analysis of Principal Components  was also performed to assess genetic differentiation. The plicates .To verify that variation in sequencing depth and missing data did not produce erroneous signals of population structure, we created a more stringent SNP dataset, subsetting the final SNP dataset for SNPs with less than 5% missing data across all sampling locations and repeated the DAPC analysis, as above. With this stringent SNP dataset, we also recoded missing data as 1 and genotypes as 0 and performed a PCA using the prcomp function in R, scaling and centering the data, to check that patterns of missing data were not driving population structure.Structure v2.3.4 [K = 1, allowing lambda to vary, to estimate the value of lambda that was then set in all subsequent runs. Structure was run both with and without sampling locations as priors to differentiate between subtle and strong population differentiation, and values of K from one to six were tested. Each analysis was run for 150,000 generations, discarding the first 50,000 as burn-in, and repeated ten times from a random seed for each value of K. Structure Harvester web v0.6.94 [K according to the Evanno method [e v2.3.4  was also v0.6.94  was usedo method , and preo method . CLUMPP o method . To checqqman for locus-specific FST values from the full dataset for all pairwise comparisons between groups. Locus-specific FST was calculated using the Weir and Cockerham [To investigate patterns of genetic differentiation throughout the genome, we created Manhattan plots using the R package ockerham  estimatoPopulation structure section), which had received much lower coverage and were sequenced in lane 2.After discarding individuals with low read counts, we called SNPs in a total of 128 individuals across our six sampling locations . The avehttps://doi.org/10.6084/m9.figshare.7683938.v1) and another 106 SNPs located in regions in high linkage disequilibrium on LG 2, 7, and 12. This resulted in a neutral dataset of 2,689 SNPs.We initially identified 73,495 SNPs across all RADtags using Ipyrad. After SNP filtering, we retained 3,128 SNPs which had a mean sequencing depth of 77.5X when averaging across all individuals  was varied from two to four, the spring spawners appeared differentiated from other groups . Our full dataset included 62 SNPs from the inversion on LG7 and 61 from the inversion on LG12, making it possible to see the influence that these inversions were having on the inferred population structure  and primarily driven by loci that are putatively under selection, the majority of which were located in the genomic regions on LG 7 and 12 containing chromosomal inversions known to be divergent among other cod populations in both the Northeast and Northwest Atlantic [From our genome-wide analysis of population structure, we found evidence for differentiation among three major spawning groups: cod that spawn in the spring in Ipswich and Massachusetts Bays, cod that spawn in the winter in the same bays, and cod spawning on the northeast peak of Georges Bank. The spring spawning cod in the western GoM appeared to be the most genetically differentiated from the other spawning populations. Levels of genetic differentiation were low overall , and the latter segregating primarily between the spring spawning groups and the others. Our small sample of genomic SNPs was insufficient to perform a genome-wide scan for selection because a much higher density of SNPs and an estimate of genome-wide linkage disequilibrium would be necessary [In addition to differences in the frequency of inversions on LG 7 and 12 among the groups studied, we found several outlier SNPs with elevated Fecessary . Therefoecessary . Our datecessary –97 resulAnopheles mosquitoes [Heliconious butterflies [et al., [There is a growing body of evidence from a variety of taxa that chromosomal inversions can capture multiple adaptive alleles governing complex traits and therefore act as ‘supergenes’ . In Atlterflies ,55,57,58terflies , variatiterflies , and witterflies . The invterflies ,55,56 anterflies . Barney [et al.,  identifipers. comm.). Lastly, temperature differences may also be associated with adult movement patterns if populations differ in their offshore migration patterns and their affinity for deeper, cooler waters outside of the spawning season. Spring spawning cod in Massachusetts Bay move to offshore feeding grounds in the summer and fall, and then overwinter in deep (>150 m) offshore basins [Consistent with findings from other Atlantic cod populations, temperature and/or offshore and vertical (depth) movement patterns may also be selective pressures that maintain the polymorphisms that we observed. Spring spawning cod in the western GoM differed from the winter GoM and the Georges Bank spawners in the frequencies of the inversions on both LG 7 and 12 (and LG 2 according to REF 24), suggesting they experienced divergent selective pressures from those groups. Winter spawning cod in the western GoM appeared to be under similar selective pressures as cod spawning on Georges Bank, based on more similar frequencies of the inversions . Divergent temperature-associated selection pressures could act at different life stages . For example, eggs that are spawned in the spring in the western GoM will experience warmer waters (based on surface temperature) than those spawned in the winter at the same location and on Georges Bank . However, depth differences during juvenile settlement may also be a factor; spring-spawned juveniles settle at greater depths (up to 80 m) and a narrower range of temperatures (<10°C) compared with winter-spawned juveniles, which settle in shallower inshore waters (< 30 m) at a greater range of temperatures , during which cod could have moved into this area from different locations (including possibly a mix of Canadian and U.S. waters). Further studies using genetic data from historical samples  pre-dating the collapse of the eastern GoM stocks are needed to definitively test the hypothesis about demographic separation of this population in the past. These studies could indicate whether there has been long-term connectivity between eastern GoM and other areas, which would be informative for investigating potential mechanisms for rebuilding of cod in the eastern GoM.et al., [et al., [The patterns of fine-scale population structure that we found have been confirmed by several studies ,24,28 anet al.,  suggesteet al.,  and are [et al.,  and showStrongylocentrotus purpuratus [Carcharhinus amblyrhynchos [Hypoplectrus spp., [Homarus americanus, [Placopecten magellanicus, [Pandalus borealis, [Despite high dispersal potential in marine species at either larval or adult stages, local adaptation is common  and locricanus, , sea scalanicus, , northerorealis, ). Conserorealis, . Adaptivorealis, , becauseorealis, . TherefoPreserving population diversity or biocomplexity is also critical for fishery stability and resilience by providing diverse responses to the environment ,15,16. PS1 AppendixContains supplementary table A and supplementary figures A—H.(PDF)Click here for additional data file.


Lindera glauca (Lauraceae) is a tree of economic and ecological significance that reproduces sexually and asexually via apomictic seeds. It is widely distributed in the low-altitude montane forests of East Asia. Despite the potential implications of a mixed reproductive system in terms of genetic diversity, few studies have focused on this aspect. In this study, the genetic structure of wild populations of L. glauca was investigated via genetic analyses. Overall, 13 nuclear microsatellites (nSSRs) and five chloroplast microsatellites (cpSSRs) were used to genotype 300 individual plants, taken from 20 wild populations  and two cultivated populations ranging across nearly the entire natural distribution of mainland China. The populations exhibited low levels of genetic diversity , and no significant effect of isolation by distance between populations existed, regardless of marker type . Haplotype networks showed complex relationships among populations, and the H12 haplotype was predominant in most populations. Analyses of molecular variance obtained with nuclear markers  and chloroplast markers  were similar. The migration ratio of pollen flow versus seed flow in this study was negative (r = −1.149). Results suggest that weak barriers of dispersal between populations and/or the similarity of founders shared between neighbors and distant populations are indicative of the gene flow between populations more likely involving seeds. Wild L. glauca in mainland China was inferred to have highly skewed sex ratios with predominant females. In addition, some populations experienced a recent bottleneck effect, especially in Gujianshan, Chongqing, and southwest China (population GJS). It is suggested that few wild male individuals should be conserved in order to maintain overall genetic diversity in the wild populations of this species. These findings provide important information for the sustainable utilization and preservation of the overall genetic diversity of L. glauca. Taraxacum), apomictic clones can be widely distributed and are temporarily ecologically successful  Blume (Lauraceae), a deciduous shrub or small tree with both apomixis    and a sey seeds) , is disty seeds) . As one y seeds) . Some roy seeds)  and somey seeds) . Additioruit oil . There hL. glauca is native to the mainland China, and diploids (2n = 24)   (2n = 24)  with sex2n = 24) . In a strocarpa) . Howeverulations . Interpoulations . Some naulations . In prevulations , L. glau method) , implyinL. glauca may well be more complex than previously thought. It is essential to study the gene flow and estimate the relative rates of pollen and seed migration among natural populations. Furthermore, population bottleneck effect is thought to be responsible for the very low levels of genetic variation found in a number of species that now have large population sizes  detect genetic variation within and differentiation among natural populations, (3) assess the relative importance of pollen and seeds as agents of gene flow, and (4) determine whether natural populations experienced a decline in size (bottleneck effect). Molecular genetic analyses were performed and individuals in 20 wild populations (and two cultivated populations) of L. glauca were genotyped using 13 nuclear and five chloroplast microsatellite markers developed in the previous work  investigate the genetic diversity of ous work .L. glauca in mainland China  method . MicrosaRaw data matrices containing information of alleles and haplotypes for 13 nSSR and 5 cpSSR loci were checked for scoring errors. All SSR analyses were conducted with 300 samples. Data editing and formatting were performed using GenAlEx v. 6.502 .NA), observed heterozygosity (Ho), expected heterozygosity (He), percentage of polymorphic loci (PPB), Wright’s inbreeding coefficient (FIS), and Nei’s (HWE) tests and to test for the presence of private (null) alleles. The differentiation index FST was computed for pairs of populations using Arlequin v. 3.5.1.3 (AR) was calculated using the software FSTAT v. 1.2 (Nb), genetic diversity (Dv), haplotype richness (Hrs), the number of private alleles (Prv), and the polymorphism information content (PIC) per locus were estimated using HAPLOTYPE v. 1.05 , K was set from 1 to 20, and the analysis was run with 20 iterations for each K with a burn-in of 1,000,000 generations followed by 50,000 generations for the Markov chain Monte Carlo (MCMC) simulation. The admixture level for each individual (Q) was also inferred. The program STRUCTURE HARVESTER v. 0.6.94  was analyzed using the Bayesian clustering approach implemented in STRUCTURE v. 2.3.4 , assumin. 0.6.94  was usedCS v.1.1 .L. glauca inter-population in mainland China was tested. In view of the potential importance of pollen in the spread of apomixis (r) was calculated. In order to examine IBD, the Mantel test was performed using GenAlEx, correlating the pairwise genetic distances [FST∕(1 − FST)] with the pairwise geographic distances (in kilometers). To calculate r, we used the followed formula: r = mp∕ms = [(1∕FST(n) − 1)(1 + FIS) − 2(1∕FST(cp) − 1)]∕(1∕FST(cp) − 1)  are population differentiation estimates derived from AMOVA, FST(n) is the nuclear FST and FST (cp) is the chloroplast FST.Considering that isolation by distance (IBD) can be a key factor keeping populations apart by limiting gene flow , the IBDapomixis , the polcp) − 1) , where mPopulation bottlenecks were evaluated using BOTTLENECK v. 1.2.02  with theL. glauca. For each locus, the number of alleles for 13 nSSR loci ranged from 3 (P-298) to 8 (XBLG-060), with a mean of 5.7 alleles , He (0.145), and PPB (42.31%) in two cultivated populations were much lower. Significant deviations from the HWE indicating a heterozygote deficiency were detected in 9 of 22 populations. For some populations , negative FIS values within the populations were observed, indicating more heterozygotes than expected. However, none of the 13 nSSR loci with the heterozygote excesses appear when calculating it on all samples  to 44 (population ZJJ), with a mean of 32.9, and allelic richness ranged from 1.231 to 2.011, with a mean of 1.740 . Populatn of 85% . The val samples , and theDv ranged from 0.115 to 0.249 per locus, and PIC varied from 0.155 to 0.218. Analyzing combinations of all alleles, there were 22 unique haplotypes  to 0.964 (population FJS), and the mean genetic distance between individuals (Genetic diversity parameters for cpSSR loci are summarized in ion JGS) .K = 2), with only slight admixture at the individual level in each population, except for population ATM  for the nSSR dataset and 0.312 (P ≤ 0.0001) for the cpSSR dataset.The 2 clusters revealed by STRUCTURE analysis were set as groups for AMOVA based on both the nSSR and cpSSR dataset . Using tFST value) based on 13 nSSRs ranged from 0.023 (between WJS and GJS) to 0.427 (between LDZ and FHS) . Adopting a P-value of 0.01, no significant correlation between pairwise genetic distance [FST/(1 − FST)] and geographic distance (in kilometers) was found using the Mantel test  or the cpSSR dataset , suggesting that L. glauca in mainland China does not exhibit significant IBD. The FST values for the nSSR and cpSSR were similar  , excluditel test  for the  similar , and theHe > Heq)   under thulations . More spulations .L. glauca populations exhibited low levels based on both nSSR  and cpSSR  loci. Our estimates of genetic diversity in L. glauca were almost half those of long-lived perennials , out-crossing species , and plants with wide distributions     , which w = 0.56) . There aulations . Similar − 0.37) . DiffereFsc = 0.293 and FST = 0.362 for nSSRs; 0.299 and 0.312 for cpSSRs) was observed, indicating general consistency between chloroplasts and nuclear DNA. More specifically, predominant apomixis in wild L. glauca could explain how FST observed for nuclear markers is a little higher than that for chloroplast markers, and vice versa. In addition, apomictic reproduction of L. glauca could also affect the results. Therefore the use of clone-corrected data (removing the data of clones from the same parent) is necessary if clones are detected, because L. glauca trees could form clones via vegetative reproduction with stolons.On the other hand, a marked similarity in the molecular variance revealed by the 2 types of markers  indicated inbreeding, and negative FIS of wild populations  suggested outbreeding. However, considering that clonality probably generates significant negative FIS in some wild plant populations with asexual reproduction when considering all individuals , coupled with the result grouped by NJ tree and the cluster pattern of the NJ tree (blue cluster) . There is mixed reproductive system existed in this species, thus explaining the FIS pattern.Nine populations had more heterozygotes than expected. STRUCTURE analysis showed that the 9 populations were grouped into one group and the rest into another, suggesting negative ividuals , the obscluster) , suggestDaktulosphaira vitifoliae ] values) and geographic distances (in kilometers) was not detected in L. glauca populations, regardless of marker type, suggesting that weak barriers to dispersal between populations and/or the common founders between neighbors, distant populations, and apomictic populations did not completely limit gene flow. Results indicate that sexual dispersion and apomixis co-occurred in the same natural population. However, further research is needed to investigate the extent to which apomixis limits gene flow, and the exact rate of sexual production and apomixis that occurred among and within populations.Populations can cluster according to habitat type or geographic distance. However, for species with predominantly asexual populations, like tifoliae , Crataegouglasii , and Tarficinale , no signr) in this study was negative (−1.149), suggesting that gene flow between populations is more likely to involve seeds. Usually, the value of r is positive in almost all angiosperm species , the migration ratio of pollen flow versus seed flow . The second inference means having an early maternal ancestor through apomictic reproduction for many individuals. However, all the living species are at the tips of the tree of life, and apomixis is a derived condition  that have a population genetic structure of diploid sexual and polyploid apomicts  that reproduces through parthenogenesis  present in many individuals from different populations more likely.Ne = 4(NmNf)/(Nm + Nf), where Nm represents the number of males, and Nf represents the number of females , correcting for clone and apomictic reproduction, across the full range of L. glauca, including Japan, South Korea, and Taiwan.According to the relationship  females , the acc decades , some sp decades , it is iL. glauca than that of some other species in Lauraceae. The conclusion is that wild L. glauca populations have female-skewed sex ratios, which was consistent with our field survey and sampling for 5 consecutive years. The destruction of habitats in order to plant other commercial or medicinal crops and felling by local farmers may explain the low frequency of male L. glauca in mainland China, although the species is common and widely distributed in other regions. The authors propose finding male individuals and promoting sexual reproduction in order to maintain this species’ overall genetic diversity.Genetic diversity is recognized as an important population attribute for both conservation and evolutionary purposes . The purL. glauca across nearly its the entire natural distribution in mainland China. A complex correlation between populations was revealed by haplotype networks. Genetic structure within and among populations was similar at the nuclear and chloroplast levels. Furthermore, some populations experienced a recent bottleneck, and gene flow between populations is more likely to involve seed. This implies that wild L. glauca in mainland China has highly skewed sex ratios with predominant females.This study has shown low levels of genetic diversity in 10.7717/peerj.8304/supp-1Table S1Click here for additional data file.10.7717/peerj.8304/supp-2Table S2Click here for additional data file.10.7717/peerj.8304/supp-3Table S3Click here for additional data file.10.7717/peerj.8304/supp-4Table S4Click here for additional data file.


Astatotilapia burtoni is a member of the “modern haplochromines,” the most species‐rich lineage within the family of cichlid fishes. Although the species has been in use as research model in various fields of research since almost seven decades, including developmental biology, neurobiology, genetics and genomics, and behavioral biology, little is known about its spatial distribution and phylogeography. Here, we examine the population structure and phylogeographic history of A. burtoni throughout its entire distribution range in the Lake Tanganyika basin. In addition, we include several A. burtoni laboratory strains to trace back their origin from wild populations. To this end, we reconstruct phylogenetic relationships based on sequences of the mitochondrial DNA (mtDNA) control region (d‐loop) as well as thousands of genomewide single nucleotide polymorphisms (SNPs) derived from restriction‐associated DNA sequencing. Our analyses reveal high population structure and deep divergence among several lineages, however, with discordant nuclear and mtDNA phylogenetic inferences. Whereas the SNP‐based phylogenetic hypothesis uncovers an unexpectedly deep split in A. burtoni, separating the populations in the southern part of the Lake Tanganyika basin from those in the northern part, analyses of the mtDNA control region suggest deep divergence between populations from the southwestern shoreline and populations from the northern and southeastern shorelines of Lake Tanganyika. This phylogeographic pattern and mitochondrial haplotype sharing between populations from the very North and the very South of Lake Tanganyika can only partly be explained by introgression linked to lake‐level fluctuations leading to past contact zones between otherwise isolated populations and large‐scale migration events. We then explore the population structure via nearest neighbor haplotype co‐ancestry analyses. Finally, by including samples from different laboratory strains in phylogenetic and population genetic analyses, we trace back their origins from wild populations.In this study, we examine the population structure and phylogeographic history of 22.1A. burtoni used in research laboratories, one bred at the University of Texas at Austin, USA, provided by H. Hofman/S. Renn and established by R. Fernald from wild collections from the Ruzizi area in Burundi  according to the manufacturer's protocol.Sampling was carried out between February 2010 and November 2015 in the Zambian, Tanzanian, and Burundian parts of Lake Tanganyika and inflowing rivers, as well as in Lake Cohoha (Burundi) and Lake Chila (Zambia) Figures . All spe2.2xl genetic analyzer using the BigDye Terminator v3.1 Cycle Sequencing Kit (Applied Biosystems). Sequences obtained in this study  were supplemented with available data from previous work . fabox  was conducted using published primers . The libraries were size selected on a gel before P2 adapter ligation was performed. The final enrichment PCR was split into six separate reactions per library to avoid amplification bias. The readily prepared libraries were single‐end sequenced in 100–200 cycles on an Illumina HiSeq 2000 platform at the Genomics Facility Basel jointly operated by ETH Zurich Department of Biosystems Science and Engineering (D‐BSSE) and the University of Basel. Illumina reads are available from the Sequence Read Archive (SRA) at NCBI under the accession numbers SRX2967972–SRX2968211 (SRA Study Number: SRP110734) and SRX3733973–SRX3734072 (SRA Study Number: SRP 133290).For RAD sequencing, we selected one to five individuals per sampling location and obtained a total of 150 individuals from 29 locations and including both laboratory strains. Libraries were prepared according to the protocol described in Roesti, Hendry, Salzburger, and Berner . In shor2.4A. burtoni reference genome . The alignment score was set to 200 with a default gap‐opening penalty and a gap extend penalty of 15 accepted  , the scientific computing core facility at University of Basel, with support from the Swiss Institute of Bioinformatics.Restriction site‐associated DNA tag processing was performed in R version 3.2.2, R Development Core Team  using th2.5A. burtoni samples from wild populations only . In the second SNP dataset, we included one specimen each of Haplochromis paludinosus  using the Schliep, . The app Posada, , and a b2.6fineRAdstructure . After quality filtering and co‐ancestry matrix construction, almost all populations were still represented with at least one individual, except for KIG and KKA )) and a southern clade (ranging from Ninde (NIN (8)) to the Ndole Bay (NDB (31)); and including A. burtoni from Lake Chila (LCZ (33)))  revealed a deep split between a northern clade ) to the Igalula River (IGR (7)) on the eastern shore and Kalemie (KKA (32)) on the western shore of Lake Tanganyika; and including The phylogenetic reconstruction including laboratory strains and three outgroup taxa  resulted in a highly similar topology as described above Figure . The inc3.3fineRAdstructure  occupies the most ancestral branches, suggesting that A. burtoni have colonized the northern part of Lake Tanganyika starting from the Lukuga River. The Lukuga River is the only intermittent outflow of Lake Tanganyika connecting the lake to the Congo drainage via the Lualaba River at periods of high lake‐level stands  and from the lake site near the estuary of the Lufubu River (LFL) diverged between 161–213 ka  Oney Figure ; (2) a sEretmodus cyanosticus, Tropheus moorii and Variabilichromis moorii—such mtDNA/ncDNA discordance patterns due to introgression/hybridization have been linked to lake‐level fluctuations leading to past contact zones between otherwise isolated populations and large‐scale migration events  turned out to cluster with the specimens from Lunzua River  and the populations around Mpulungu , as already discussed in Theis et al. . According to a FAO report from 1991 , Sarotherodon niloticus (now Oreochromis niloticus), S. macrochir (now O. macrochir), and Astatoreochromis alluaudi. In this report, A. burtoni is not mentioned; however, an accidental introduction of the species, for example, in the course of stocking Lake Cohoha with O. niloticus, seems to be way more likely than natural dispersal.The SNP‐based phylogeny further indicates two likely cases of human‐mediated translocation of s et al. , is mosts et al. . SimilarA. burtoni  under study. In two recent studies dealing with the genomics of sex determination in A. burtoni, Böhne et al. . Mitochondrial D‐loop sequences obtained in this study are available at GenBank under the accession numbers MG987216–MG987279.Raw RAD sequencing reads generated for this study are available from the Sequence Read Archive (SRA) at NCBI under the accession numbers  Click here for additional data file. Click here for additional data file. Click here for additional data file.


The rapid accumulation of ancient human genomes from various areas and time periods potentially enables the expansion of studies of biodiversity, biogeography, forensics, population history, and epidemiology into past populations. However, most ancient DNA (aDNA) data were generated through microarrays designed for modern-day populations, which are known to misrepresent the population structure. Past studies addressed these problems by using ancestry informative markers (AIMs). It is, however, unclear whether AIMs derived from contemporary human genomes can capture ancient population structures, and whether AIM-finding methods are applicable to aDNA. Further the high missingness rates in ancient—and oftentimes haploid—DNA can also distort the population structure. Here, we define ancient AIMs (aAIMs) and develop a framework to evaluate established and novel AIM-finding methods in identifying the most informative markers. We show that aAIMs identified by a novel principal component analysis (PCA)-based method outperform all of the competing methods in classifying ancient individuals into populations and identifying admixed individuals. In some cases, predictions made using the aAIMs were more accurate than those made with a complete marker set. We discuss the features of the ancient Eurasian population structure and strategies to identify aAIMs. This work informs the design of single nucleotide polymorphism (SNP) microarrays and the interpretation of aDNA results, which enables a population-wide testing of primordialist theories. Over the past decade, genomic techniques have been reshaping our fundamental understanding of human prehistory and origins . AncientWhole genome sequencing and single nucleotide polymorphism (SNP) microarrays are the two leading approaches to aDNA sequencing. Although the former is preferable as it provides more data, by late 2017, only a quarter of the 1100 sequenced ancient genomes were whole genomes. The vast majority of these genomes 762) were captured by SNP microarrays  and Illu2 were caSingle nucleotide polymorphism genotyping microarrays were originally developed to detect phenotype–genotype associations in association mapping, admixture mapping, identity by descent mapping, and similar studies. It was not until later that SNP microarrays were employed in population genetic studies aimed at inferring population structure through principal component analyses (PCAs), ADMIXTURE-like programs, and other tools aimed at predicting group membership. It soon became clear that the allele frequency spectrum obtained through microarrays is more skewed for some populations than for other ones due to the choice of SNP panels . The HumAny inference of identity in archeological studies is fraught with difficulties. Carbon dating requires extracting organic material from fossil bones and authenticating it as composed of degraded proteins; this process is highly susceptible to contamination, which yields erroneous estimates . The ideThe difficulties related to establishing an acceptable population model are partially due to our incomplete knowledge of human population biodiversity in the past and present. Often, modern-day populations are assumed to be the parental populations of the modern-day population of interest, which results in population stratification. This problem arises due to differences in the allele frequencies of unknown case/control subpopulations due to separate demographic histories . A misunderstanding of the population structure necessitates mismatched cases and controls, which introduces genetic heterogeneity into the analysis that can lead to spurious associations and obscure the true association . TherebyPast studies have resolved, to a large extent, the problems faced in DNA analyses with ancestry informative markers (AIMs). Ancestry informative markers are SNPs that exhibit large variation in minor allele frequencies (MAF) among populations. Over the past two decades, geneticists have scoured genomes for these patterns, and to date produced numerous AIM sets to determine an individual’s ancestry, detect stratification in biomedical studies, infer geographic structure, find risk loci in a candidate region, and localize biogeographical origins  AIMs are still frequently used in forensics, carrier screening, and biogeography in both microarrays e.g., ,21) and  and 21])STF) . At each iteration i, k-means was used to identify the k subclusters; then, the F-test was applied on each pair of subclusters to test whether they were significantly different (p < 0.05). If two clusters were significantly different from all of the pairs at iteration i, the process repeats for i + 1 until at least one pair violates the condition, in which case the optimal number of k subclusters or reference populations within that population is the number of subclusters that did not violate the condition.Genomically defining reference populations: For each population with supervised ADMIXTURE, we calculated the admixture proportions of the individuals in relation to the putative ancient ancestral populations. Population assignment was then made based on the minimal Euclidean distance between the admixture components of each genome and those of the reference populations. The assignment accuracy was measured against the population classification  and Mesolithic Swedish genomes having the lowest . The SNP-based missingness ranged from 30% to 98%, with an mean of 54%.Missingness varied greatly within the samples, as well as within the markers. The sample-based missingness ranged from 0.05% (KK1) to 99.2% (I1951), with a mean of 54%. Similarly, missingness also varied among the populations, with Levantine Epipaleolithic and Neolithic genomes having the highest missingness  of the ancient genomes substantiated previous observations of a Europe–Middle East contrast along the vertical principal component (PC1) and parallel clines (PC2) in both Europe and the Middle East . Genomesunsupervised ADMIXTURE analysis with a range of splits (K)   and the Russia Mid Late Bronze (magenta), which were predominantly found among European genomes, could be identified. Except for their predominance in Neolithic Turkish genomes, these two components also exist in most Neolithic Central Europeans. Some 20–30% of Central European genomes have discernible fractions of Europe Late Neolithic–Early Bronze (navy-blue) and Russia Mid–Late Bronze (deep-pink) components, respectively. Two components (cyan and dark purple) appeared sporadically in a few populations, which was likely due to noise.Our lits (K)  found thor (CVE) , as expe  to 2160 (Admixture1 and Admixture2). Interestingly, Infocalc and STF, which are often used together, share only ~10% of their aAIM candidates. The PD method shares 13.7% of its aAIMs with STF and ~10% with Infocalc.We developed a framework to identify and evaluate the efficacy of aAIM candidates in capturing ancient population structure and allowing admixture mapping . AncientSTF captured the aAIMs with a high frequency of low–mid MAFs. By contrast, PD and the admixture-based methods exhibited higher frequencies of high MAF SNPs, with Admixture2 having the highest proportion of high MAF aAIMs (75% of the aAIMS have MAF >0.4). Remarkably, the MAF distributions exhibited a similarity with modern populations  compared to those obtained from the other aAIMs , STF , Admixture1 , Admixture2 , Rand10k , and Rand15k ). Infocalc’s aAIMs produced the second-shortest distances from the CSS ; however, these differences in the distances compared to those obtained with the two random datasets were not statistically significant  and Rand15k , respectively), suggesting that Infocalc was unable to capture the population structure. STF-derived AIMs  performed significantly worse than the Rand15k aAIMs , and similar to the Rand10k aAIMs . Finally, the two admixture-based datasets performed the worst out of all the methods  and significantly worse than the two random datasets .Secondly, we quantitatively assessed which dataset produced the closest admixture signature to that of the CSS . For thaSTF) to 61% (PD), with the PD outperforming all of the other methods (10k = 42 ± 5% and Rand15k = 50 ± 5%), with Infocalc (50 ± 6%) outperforming the remaining methods. Of note is the poor performance of STF aAIMs, which indicates its unsuitability for aDNA data. As expected, high missingness was associated with incorrect predictions  and the known population classification . The mea methods . In othedictions . For exaThe last criterion used to evaluate the accuracy of the aAIMs was to test whether they can identify hybrid individuals. Due to the high accuracy of the PD aAIMs in classifying individuals into populations, when compared to the alternative datasets, we decided to focus on aAIMs identified by the PD. µ = 0.05, σ = 0.04) than the genetic admixture distances between the CSS and the random SNP set  and those between the PD and the random SNP set . Thus, we demonstrated that PD aAIMs can be used for studying admixed individuals and can be potentially used in future admixture mapping involving aDNA.The genetic admixture distances between the hybrid individuals that were generated using the CSS and PD aAIMs were significantly smaller , capture the population structure, and allow the identification of admixed individuals is one of the challenges of population genetics. We showed that the aAIMs identified through the PD method outperformed all other methods, in agreement with previous studies that tested PCA-based methods . In fortThe use of PCA to infer population structure is controversial ,54,55,56STF that are commonly used to identify AIMs [STF already shown to be particularly small within continental populations [Surprisingly, Infocalc and ify AIMs  and are ify AIMs , have ofulations , but theOur study has several limitations. We studied an uneven number of Eurasian populations from various times and locations, causing a skew toward markers that predict central European populations from the Late Neolithic and Bronze Age. A modest attempt to reduce this bias was made by including modern-day African and Asian populations; however, more comprehensive analyses should be made when more global genomes are available from consecutives eras. Second, the aAIMs were calculated independently by each method with individual populations considered independent, although the PCA and ADMIXTURE plots indicate that central European populations may not be independent. Finally, due to the high missingness of the data, it is likely that our study missed informative markers that could improve the classification accuracy in newly sequenced populations. Therefore, our framework and methods must be applied again when more comprehensive aDNA datasets are available.The use of ancient genomes in research is in its infancy, and is expected to intensify and expand to new fields as more data become available. One of the main advantages of aDNA is that it widens the number of ancestry types and makes them multi-faceted, requiring fine-tuned molecular utilities to depict ancestry over time. AIMs are some of the most effective tools that have spear-headed population genetics over the past two decades and are ancillary to the challenge of understanding population structure. Here, we defined aAIMs, proposed a framework to evaluate AIM-finding methods, demonstrated the accuracy of a novel aAIM-finding method, and reported the most successful set of aAIMs. Future analyses may benefit from using our framework, methods, and aAIMs in order to refine ancient population structure models and examine primordialist theories.


Anser albifrons) is a migratory waterfowl species with a largely circumpolar distribution consisting of up to six subspecies roughly corresponding to phenotypic variation. We examined the rangewide population genetic structure of greater white‐fronted geese using mtDNA control region sequence data and microsatellite loci from 23 locales across North America and Eurasia. We found significant differentiation in mtDNA between sampling locales with flyway delineation explaining a significant portion of the observed genetic variation (~12%). This is concordant with band recovery data which shows little interflyway or intercontinental movements. However, microsatellite loci revealed little genetic structure suggesting a panmictic population across most of the Arctic. As with many high‐latitude species, Beringia appears to have played a role in the diversification of this species. A common Beringian origin of North America and Asian populations and a recent divergence could at least partly explain the general lack of structure at nuclear markers. Further, our results do not provide strong support for the various taxonomic proposals for this species except for supporting the distinctness of two isolated breeding populations within Cook Inlet, Alaska (A. a. elgasi) and Greenland (A. a. flavirostris), consistent with their subspecies status.Dispersal and migratory behavior are influential factors in determining how genetic diversity is distributed across the landscape. In migratory species, genetic structure can be promoted via several mechanisms including fidelity to distinct migratory routes. Particularly within North America, waterfowl management units have been delineated according to distinct longitudinal migratory flyways supported by banding data and other direct evidence. The greater white‐fronted goose ( The two western Alaskan breeding locales have been recently proposed but not currently accepted as comprising a separate subspecies due to their small body size .Within North America, the Pacific Flyway population of greater white‐fronted geese is comprised of three distinct breeding regions representing two subspecies Figure : Cook InA. a. albifrons; Owen, A. a. frontalis), based on similarity in body size. Mooji , based on wintering distribution, migratory routes, and slightly larger body size than western Palearctic areas. Geese nesting in Greenland and wintering primarily in Ireland and United Kingdom are designated as a separate subspecies (A. a. flavirostris) due to their large size, dark coloration and nonoverlapping breeding and wintering distribution with other potential subspecies.Within Eurasia, the Khatanga River has been proposed as the geographic break between western and eastern Palearctic populations  and H542  and nucleotide (π) diversity, for mtDNA control region using ARLEQUIN ver. 3.5.1.2  and significantly different than random distribution of individuals were the most probable geographic divisions (p < 0.05).We used two approaches to explore the genetic partitioning of genetic variation among and within breeding groups. We first used an analysis of molecular variance (AMOVA) in ARLEQUIN to test for significance of geographic partitioning of a priori hypothesized genetic units using mtDNA and microsatellite loci with statistical significance tested by 16,000 permutations. Populations were grouped to test  iterations. Initially the analyses were repeated five times for each K and based on these preliminary results, 10 additional replicated were performed for K = 1–10 for a total of fifteen independent runs. We used the ∆K method of Evanno, Regnaut, and Goudet , to determine the most likely number of groups at the uppermost level of population structure.Secondly, we used a Bayesian‐clustering program, STRUCTURE 2.2.3  for each contemporary population and the ancestral populations, 2Nm , and t . We ran 20 Markov chains under a geometric heating scheme (option ‐hfg), with chain temperatures of 0.90 and 0.75. We ran preliminary analyses using large, flat priors for each parameter. From the results of these runs, we defined narrower upper bounds for each parameter that encompassed the full posterior distributions from each initial run. The final values used for population size, migration rate and splitting time were as follows: −q 300, −m 10, −t 5. The analysis was repeated four times to check for convergence, and all ESS values were >100 in all runs. To convert the estimated parameters into demographic units we used a mutation rate of 4.8 × 10−8  substitutions per site per year that has been previously used for other waterfowl studies  using the equation G = α + (s/(1 − s)), where α is the age of maturity and s is the expected adult survival rate  Bird Banding Laboratory (BBL) in Laurel, Maryland for greater white‐fronted geese which included data from birds banded or recovered in North America through 2015. To assess intercontinental dispersal and flyway switching within Eurasia, we contacted the BBL directly , the Russian Ringing Centre , and accessed Euring data . Banding records came from geese captured on breeding and wintering areas, but there were very few recoveries (or observations) on northern breeding areas. More information on band recovery data is available in Supporting Information Appendix 33.1r2 = 0.44 p = 0.025) and east to west within the eastern Palearctic Flyway (r2 = 0.97 p = 0.003).One hundred and sixty‐two unique mtDNA haplotypes were found from 550 individuals representing 23 different breeding localities Figure . This haSD 4.14) alleles per locus (Table SD 6.7%). All populations and loci were in Hardy–Weinberg and linkage equilibrium. No significant correlation with allelic richness and longitude was detected within Old or New World regions or within each flyway.Based on 665 individuals genotyped, the number of alleles per autosomal microsatellite locus ranged from 3 (BCA 6) to 16 (OXY 13), with an average of 8.38 . However, not all sampling sites were significantly differentiated from each other  so nonsignificant pairwise FST values associated with Magadan may reflect Type II error.We found significant overall differentiation for mtDNA . Alternatively, if Lena River and Yana River was placed within the eastern or western Palearctic, 9.3% and 10.8% of the genetic variation was explained with these groupings  was the same as best flyway grouping with the only difference was Greenland was included within North American midcontinent population. In general, the inclusion of Greenland within the western Palearctic for hypothesized geographic groupings generally lowered the amount of genetic variance explained compared to when Greenland was placed within North America  revealed that the best partition of genetic variance was when all populations were grouped primarily by major flyway  and eastern Palearctic (with break at Lena River) grouped together and the western Palearctic as a second group; although it was marginally significant  of the genetic variation was explained. In general, while flyway, geographic or subspecies groupings typically accounted for approximately 8%–14% of the genetic variation, AMOVAs showed that genetic variation was to a large extent partitioned within populations/localities (>50%).When testing the different subspecies classifications (excluding Greenland and tule goose), the best grouping was proposed by Delacour  with NorFST estimates were restricted to comparisons with Greenland and Cook Inlet populations (Table K = 3 deemed by both Evanno's method (ΔK = 5.0) and assessing Ln P(K)  using the LOCIPRIOR (r < 1). When no location information prior was used, the most likely number of genetic clusters was one. The three genetic clusters corresponded with FST estimates whereby Greenland and Cook Inlet individuals were grouped in separate clusters with the remaining populations from Asia and North America representing a single cluster or showing admixture  and Yana River Delta in Russia (Tajima's D).In general, the population size parameter (ϴ) was larger than the ancestral effective population size Figure . The popNm = three migrants per generation) and in the reverse direction (2Nm = 14 migrants per generation). Although the peak values showed a strong asymmetrical direction of gene flow from Old World into New World, confidence intervals broadly overlapped  peaked at 1.518, which when converted to years (assuming a generation time of 6 years) suggests that Old and New World lineages diverged around 86,000 years before the present , prior to the peak of the last glacial maximum.Prominent traces of gene flow were detected from New World populations into Old World populations  being the most distinctive. The high mtDNA structure, and general lack of nuclear DNA structure is a common finding in waterfowl; however, this is one of the first studies in waterfowl to our knowledge to show that proposed flyway delineation corresponds to a significant partitioning in mtDNA genetic variance  compared to other regions  and New World (North America). The pattern (lower structure in microsatellite loci relative to mtDNA) could be due to a greater level of philopatry in females, with gene flow largely mediated by males as suggested for the near panmictic population structure across the Arctic at nuclear markers for some dabbling duck species  scale but also on a more local (microgeographic) scale  and Greenland (A. a. flavirostris) populations as valid subspecies has been little challenged, given their large body size and darker coloration, with slight overlap with other populations . Mitochondrial control region sequences are available on GenBank .Microsatellite genotype data and sample information are available in Wilson ( Click here for additional data file. Click here for additional data file. Click here for additional data file. Click here for additional data file.


Using multilocus analyses that for the first time include populations from the Colombian Andes, we also examined the hypothesis that Ruddy Duck populations from northern South America are of hybrid origin. We found that neutral and functional genes appear to have moved into the Colombian Andes from both North America and southern South America, and that high‐altitude Colombian populations do not exhibit evidence of adaptation to hypoxia in hemoglobin genes. Therefore, the biogeographic history of Ruddy Ducks is likely more complex than previously inferred. Our new data raise questions about the hypothesis that adaptation via natural selection to high‐altitude conditions through amino acid replacements in the hemoglobin protein allowed Ruddy Ducks to disperse south along the high Andes into southern South America. The existence of shared genetic variation with populations from both North America and southern South America as well as private alleles suggests that the Colombian population of Ruddy Ducks may be of old hybrid origin. This study illustrates the breadth of inferences one can make by combining data from nuclear and functionally important loci in phylogeography, and underscores the importance of complete range‐wide sampling to study species history in complex landscapes.Phylogeographic studies often infer historical demographic processes underlying species distributions based on patterns of neutral genetic variation, but spatial variation in functionally important genes can provide additional insights about biogeographic history allowing for inferences about the potential role of adaptation in geographic range evolution. Integrating data from neutral markers and genes involved in oxygen (O However2)‐transport physiology.A long‐standing question in biogeography is that of the evolutionary origin of high‐elevation organisms. In the New World, in particular, researchers have long been interested in understanding the origins of biotas occurring in the high Andes of South America, with a leading hypothesis being that tropical high‐elevation species are derived from low‐elevation ancestors occupying areas with similarly cool climates in the temperate zone Chapman, . Example2 transport protein hemoglobin. Many organisms native to high altitude exhibit hemoglobin with a high affinity for oxygen  obtained based on hemoglobin alleles are much lower than those inferred from neutral markers; in light of biochemical properties of amino acid substitutions differing across elevations, such differences in hemoglobin gene flow are consistent with a role for selection structuring genetic and phenotypic variation  relative to those from lowland areas, and Fst across elevations for a functionally important site in the βA‐globin gene is greater than Fst values for most coding SNPs across the genome , a diving duck found throughout the New World from southern Canada to Tierra del Fuego  occurs in North America and Middle America, the Colombian subspecies  is restricted to middle and high elevations in the Colombian Andes, and the Andean‐Patagonian subspecies  ranges throughout the Northern Andes and Southern Andes from southern Colombia to Tierra del Fuego. Consistent with the general hypothesis that highland tropical lineages are derived from temperate‐zone lineages and with a biogeographic hypothesis for Ruddy Ducks proposed by Fjeldså , beta fibrinogen intron 7 , and ornithine decarboxylase intron 5 ; (3) the complete coding sequence of the αA‐globin subunit; and (d) exon 1, intron 1, exon 2, and part of intron 2 of the βA‐globin subunit (581 bp), encompassing the three previously described amino acid polymorphisms at positions 13, 14, and 69 documented by McCracken, Barger, Bulgarella, Johnson, Sonsthagen, et al. (http://www.geneious.com) or Sequencher v.4.6  and aligned by eye using Se‐Al v.2.0a11 ; for GRIN1 two individuals had allele pairs with p = .70 and two other individuals with p = .85. For PCK1, four individuals had allele pairs with p = .61.To resolve the gametic phase of nuclear genes, we used PHASE v.2.1 , 31 of O. j. andina , and 42 of O. j. ferruginea (lowlands and highlands from Ecuador to Argentina). For simplicity, we refer hereafter to our three populations based on the regional distribution of the three Ruddy Duck subspecies: North America corresponds to areas occupied by O. j. jamaicensis, Colombia to areas occupied by O. j. andina, and Southern Andes to areas occupied by O. j. ferruginea. To infer relationships among haplotypes at each locus, we constructed unrooted parsimony allelic networks in TCS v1.21 .We combined our new sequence data with previously published sequences for a total of 69 individuals of st values for each locus based on the Tamura & Nei (1993) nucleotide substitution model in Arlequin v.3.5.1.3 . We used the admixture model (α = 1) with correlated allele frequencies and tested models for varying numbers of populations (K = 2–4). Each analysis was run for one million generations  and replicated 10 times. To choose the best value of K, we used the Evanno, Regnaut, and Goudet  between populations, we used a population genetic approach based on isolation‐with‐migration coalescent models implemented in the program IMa2  estimated by IMa2. To ensure that all the parameters converged, autocorrelation and effective sample sizes (ESS) were monitored, and runs were continued until the ESS for each parameter was at least 100.To estimate gene flow , and more allelic diversity was found in Colombia than in the southern Andes for three of five loci . However, mtDNA haplotype diversity was greater in the Southern Andes than in Colombia  corresponding to the three geographic populations of Ruddy Ducks. Most individuals had high probabilities of being assigned (p > .93) to their respective population based on their multilocus genotypes, except for two individuals from the Colombian cluster that were genetically admixed with North America , indicating that all STRUCTURE runs were congruent.The STRUCTURE analysis showed strong support for the existence of three genetic clusters (m/u = 0.35), but the posterior distribution overlapped zero, and the posterior gene flow from North America to Colombia was flat, indicating that it could not be estimated reliably , whereas gene flow on the opposite direction was probably zero  but the posterior also overlapped zero, and gene flow into Colombia from North America could not be estimated , but these markers revealed no evidence of gene flow in the opposite direction from Colombia to the Southern Andes  and in the opposite direction (m/u = 1.72) were positive  to be secondarily developed, because all species except jamaicenis and the Eurasian leucocephala have black heads. However, because the Colombian population is genetically admixed (see below), with lineages from both North America and the Southern Andes, a plausible interpretation of historical gene flow might be that this population has received immigrants from both the Southern Andes and North America and such gene flow may have obscured our ability to recover the true biogeographic pattern of colonization of different parts of the Americas by Ruddy Ducks. Indeed, because the Colombian population is genetically admixed, we were unable to reliably estimate splitting parameters measuring the fraction of individuals in the ancestral population contributing to one population  from Colombia and the first to consider a large number of Colombian individuals sampled for mtDNA, show there is likely more complexity to the historical scenario of north‐to‐south colonization with adaptation to elevation postulated by earlier analyses , which suggests that the phenotypic variability existing among Colombian individuals is not the result of recent influx of individuals from other populations. Taken together, our data may support the hypothesis that during periods of glaciation  variation with dense sampling in populations from northern South America is critical to gain a comprehensive understanding of the biogeographic history of species with broad distribution ranges in the Americas (Avendaño, Arbeláez‐Cortés, & Cadena, Finally, we note that the Colombian Ruddy Duck is endemic to isolated high‐Andean wetlands in and it is currently considered endangered (Renjifo, Amaya‐Villarreal, Burbano‐Girón, & Velásquez‐Tibata, None declared.MLJ, CDC, and KMC concieved the ideas and designed the methodology. MLJ and KMC conducted fieldwork and collected data. MLJ analyzed the data. MLJ and CDC led the writing of the manuscript. All authors contributed critically to the drafts and gave final approval for publication. Click here for additional data file. Click here for additional data file. Click here for additional data file.


The set of 55 ancestry informative SNPs (AISNPs) originally developed by the Kidd Lab has been studied on a large number of populations and continues to be applied to new population samples. The existing reference database of population samples allows the relationships of new population samples to be inferred on a global level. Analyses show that these autosomal markers constitute one of the better panels of AISNPs. Continuing to build this reference database enhances its value. Because more than half of the 25 ethnic groups recently studied with these AISNPs are from Southwest Asia and the Mediterranean region, we present here various analyses focused on populations from these regions along with selected reference populations from nearby regions where genotype data are available. Many of these ethnic groups have not been previously studied for forensic markers. Data on populations from other world regions have also been added to the database but are not included in these focused analyses. The new population samples added to ALFRED and FROG-kb increase the total to 164 population samples that have been studied for all 55 AISNPs. In previous publications , 2 we rehttp://www.1000genomes.org) [From the start of the Neolithic until now, Southwest Asia has been intimately involved in human history and the genetic consequences of the human migrations from and through the region are of considerable interest. Yet populations in this geographical region and nearby areas such as North Africa and Central Asia have not been well represented in the two largest of the human diversity studies, the CEPH-HGDP panel  and the mes.org) . IncludiN), the laboratories generating the data, and the typing methods employed, along with the sample unique identifier (UID) in ALFRED are all included in Table N), and the unique sample identifier in the ALFRED database for looking up the description of each sample. The three character population abbreviations employed in various figures in this report are also found in Table The 25 new populations studied for the 55 AISNPs are listed in Table in silico haplogroup assignments were made. The patrilineal relationships of these groups are discussed there in light of these Y-haplogroup findings and comparisons are also made to what is known from the literature about other ethnic groups in the broader geographic region. The introductory section in Dogan et al. [Samples were collected primarily within the geographic bounds of an ethnic group’s home region but some were collected elsewhere  to calculate the PCs for the populations using their SNP frequencies. Table Principal component analyses (PCA) of the population allele frequencies compared the similarities and differences among the populations. We used XLSTAT 2018  iterations. Table not among the new groups in Table The STRUCTURE software  providesBecause we expect the Northern Iraqi populations to be closely related we also used the likelihood calculations in FROG-kb to examine how similar the likelihoods of populations would be for two Kurds as examples. As noted, FROG-kb now has all of the new population allele frequencies entered as reference population data. Two Kurds were selected to be examples for the 55 AISNP panel. We are aware that testing them against the entire sample from which they were chosen introduces a slight bias favoring finding them most similar to the Kurdish population. However, given the sample size involved  the bias is very small and can be ignored when using these as examples.The calculation of likelihoods of ancestry for selected example individuals employed the function in FROG-kb for the Kidd lab 55 AISNP panel. The input is the genotype profile for each individual. For each population the calculation is the product of the frequencies of the genotypes of the input individual across all 55 loci. In the output the populations are ranked from highest to lowest likelihood.The random match probability (RMP) for each population sample was computed assuming Hardy–Weinberg ratios. While RMP values will differ for each unique genotype, values have been calculated as the expected value based on the allele frequencies in each population. No correction was made for within-sample population structure since the focus is on distinct, well defined population samples representing global population structure.Population tree diagrams are a common way to represent population relationships. The Neighbor Joining (NJ) method  is a comThe SNP data collected for the 55 AISNPs by the various research groups employing several different methods are consistent in that the same alleles are being detected and the frequencies appear similar to other populations sampled in the same geographical region. For 20 of the 25 new populations  solution with both internal and terminal negative segments. The LS search program was used with several different input tree structures in addition to the NJ tree and a total of 387 different tree structures were evaluated by least squares. Eight slightly different tree structures among the highest ranked had no internal negative segments but all had 52 negative segments for the branches connecting populations to the backbone structure of the tree. A very small negative value for a segment connecting a population to the tree could be explained as sampling error. Unfortunately, not all the values were so small as to be explained away so simply.The graphical presentations based on analyses of the 55 AISNP panel show very strong geographical clustering of the 76 reference populations analyzed from Southwest Asia–Europe and the immediately adjacent areas. The PCA image Fig.  of the fOne way to think about the way that STRUCTURE defines clusters of individuals in an analysis is that it attempts to find Mendelian populations. From that perspective it becomes clear that the numbers of individuals in each input population is relevant as is the nature of the other populations. For example, a small population with a unique set of different allele frequencies can be absorbed into a large cluster if it is not too different relative to other possible clusterings. The deviation from Hardy–Weinberg ratios will not be that great. On the other hand, if the allele frequencies are different from all other groups, this small population can show membership in several clusters or cause the emergence of a distinct new cluster if the frequency differences are strong enough.The large number of negative segments in all trees examined by both the inexact neighbor joining method and the exact least squares method argues strongly against the model of an additive genetic distance for these populations. Although one could find general groupings of populations with similarities to the clusters in the PCA analyses, we conclude that the underlying model of random genetic drift and a tree structure for relationships among the majority of these populations is invalid. The negative segments preclude a drawing. One possible explanation for the negative segments is that the populations are more similar than the model would predict and considerable gene flow would cause that to occur.−9, while others such as the Ethiopian Jews have among the lowest values of 10−13.The random match probabilities (RMP) for the new populations in Fig. A total of 164 population samples  now have allele frequencies on all of the 55 Kidd lab AISNPs. Sixteen of the newest reference populations have been studied via commercial kits from ThermoFisher Scientific or from Verogen that employ massively parallel sequencing. Researchers employing these resources will find the enhanced set of reference populations useful in a wide range of forensic, anthropological, and medical genetic studies. Both of the kits include the 55 Kidd AISNPs. The combined 55 Kidd and 128 Seldin  AISNP se−14, a meaningful value that would be especially valuable in combination with forensic STR markers. For these two examples the RMP values are smaller than the average for Kurds of between 10−10 and 10−11 (Fig. The functionality in FROG-kb has been used to compute the relative likelihoods that two Kurdish individuals originate from each of the 164 reference populations now available in FROG-kb for the 55 AISNP panel Fig. . These eSuppl Tables S1,S2,S3Suppl Table S4--dataset informationSuppl Table S5--dataset information