Gasterosteus aculeatus) as a model. We extend restriction site‐associated DNA sequencing (RAD‐seq) to produce phased haplotypes approaching 700 base pairs (bp) in length at each of over 50,000 loci across the stickleback genome. Parallel adaptation in two geographically isolated freshwater pond populations consistently involved fixation of haplotypes that are identical‐by‐descent. In these same genomic regions, sequence divergence between marine and freshwater stickleback, as measured by XYd, reaches tenfold higher than background levels and genomic variation is structured into distinct marine and freshwater haplogroups. By combining this dataset with a de novo genome assembly of a related species, the ninespine stickleback (Pungitius pungitius), we find that this habitat‐associated divergent variation averages six million years old, nearly twice the genome‐wide average. The genomic variation that is involved in recent and rapid local adaptation in stickleback has therefore been evolving throughout the 15‐million‐year history since the two species lineages split. This long history of genomic divergence has maintained large genomic regions of ancient ancestry that include multiple chromosomal inversions and extensive linked variation. These discoveries of ancient genetic variation spread broadly across the genome in stickleback demonstrate how selection on ecological timescales is a result of genome evolution over geological timescales, and vice versa.Adaptation in the wild often involves standing genetic variation (SGV), which allows rapid responses to selection on ecological timescales. However, we still know little about how the evolutionary histories and genomic distributions of SGV influence local adaptation in natural populations. Here, we address this knowledge gap using the threespine stickleback fish ( Adaptation to changing environments requires a source of genetic variation. When environments change quickly, species often rely on variation that is already present–‐so‐called standing genetic variation‐–because new adaptive mutations are too rare. The threespine stickleback, a small fish species living throughout the Northern Hemisphere, is well‐known for its ability to rapidly adapt to new environments. Populations living in coastal oceans are heavily armored with bony plates and spines that protect them from predators. These marine populations have repeatedly invaded and adapted to freshwater environments, losing much of their armor and changing in shape, size, color, and behavior.eda, that controls the shifts in armor plating. This discovery involved two surprises that continue to shape our understanding of the genetics of adaptation. First, freshwater stickleback from across the Northern Hemisphere share the same version, or allele, of this gene. Second, the “marine” and “freshwater” alleles arose millions of years ago, even though the freshwater populations studied arose much more recently. While it has been hypothesized that other genes in the stickleback genome may share these patterns, large‐scale surveys of genomic variation have been unable to test this prediction directly.Adaptation to freshwater environments can occur in mere decades and probably involves a significant amount of standing genetic variation. Indeed, one of the clearest examples we have of adaptation from standing genetic variation comes from a gene, eda gene. We find that nearly every region of the genome associated with marine‐freshwater genetic differences shares this pattern to some degree. Moreover, many of these regions are as old or older than eda, stretching back over 10 million years in the past and perhaps even predating the species we now call the threespine stickleback. We conclude that natural selection has maintained this variation over geological timescales and that the same alleles we observe in freshwater stickleback today are the descendants of those under selection in ancient, now‐extinct freshwater habitats. Our findings highlight the need to understand evolution on macroevolutionary timescales to understand and predict adaptation happening in the present day.Here, we use new sequencing technologies to survey DNA sequence variation across the stickleback genome for patterns like those at the The mode and tempo of adaptive evolution depend on the sources of genetic variation affecting fitness Wright . While nThe contribution of SGV to rapid divergence has important consequences for our understanding of evolutionary genetics. Existing genetic variants have evolutionary histories that are often unknown, but which may none‐the‐less have significant impacts on subsequent adaptation , allowing us to estimate divergence times for genealogies across the genome. Our results clearly demonstrate that the previous findings of deep evolutionary history based upon candidate loci are not unique but in fact the rule. A suite of adaptive variation structured into distinct marine and freshwater haplotypes that evolved over millions of years structures a deep pool of SGV fueling repeated and rapid evolution in stickleback.To address fundamental questions of genealogical relationships and molecular evolution in stickleback, we utilize the new RAD‐seq haplotyping approach to assay genome‐wide variation associated with adaptive divergence in two young freshwater ponds, which formed during the end‐Pleistocene glacial retreat , Boot Lake , and Bear Paw Lake   Fig. . Boot Lae, assuming Ne <106, Aldenhoven et al. We designed our sequencing to maximize detection of DNA sequence variation and divergence, with the ultimate goal being the estimation of absolute divergence times of marine and freshwater haplogroups. Previous work by us and others using short sequence reads provided clear evidence of changes in relative frequencies of alleles across stickleback populations  (Nei XYd) . Therefore, not only is this novel application of RAD‐seq ideally suited for our questions, our findings show that this approach may significantly decrease the necessary sample size, and thus resource expenditure, for many population genomic studies.Our sequencing design facilitated accurate inference of sequence variation even with smaller population samples than are typical among population genomic studies. While allele frequency‐based statistics like F (π) Nei  and divedXY) Nei  at a givdXY) Nei , the prePstI‐HF (New England Biolabs), followed by ligation to P1 Illumina adaptors with 6 bp inline barcodes. Ligated samples were multiplexed and sheared by sonication in a Bioruptor (Diagenode). To ensure that most of our paired‐end reads would overlap unambiguously and produce longer contiguous sequences, we selected a narrow fragment size range of 425–475 bp. The remainder of the protocol was per Baird et al. . Overlapping read pairs were then merged with fastq‐join  and required that contigs mapped uniquely to the reference. We then used the pstacks, cstacks, and sstacks components of the Stacks pipeline to identify RAD‐tags and call SNPs using the maximum likelihood algorithm implemented in pstacks, create a catalog of RAD tags across individuals, and match tags across individuals. All data were then passed through the Stacks error correction module rxstacks to prune unlikely haplotypes. We ran the Stacks component program populations on the final dataset to filter loci genotyped in fewer than four individuals in each population and to create output files for sequence analysis. We use the naming conventions of Baird et al.  and were used to generate sequence alignments for import into BEAST.We used the program PstI restriction sites. At 84,974 restriction sites, we recovered and successfully phased adjacent RAD tags  into single RAD loci. RAD tags with no variable sites were simply concatenated to the adjacent tag to form a single locus. We retained these 84,974 RAD loci for our analysis. For population genetic analyses, inclusion of singleton (i.e. unpaired) RAD tags did not qualitatively change our results. We chose to restrict genealogical analyses to loci of uniform length and to use the same set of loci in analyses of polymorphism and gene tree topologies.We recovered a total of 236,787 RAD tags after filtering, mapping to 151,813 MRCA of threespine stickleback RAD alleles, we used the ninespine stickleback (Pungitius pungitius) as an outgroup. RAD sequence analysis, however, relies on the presence of homologous restriction sites among sampled individuals and results in null alleles when mutations occur within a restriction site  using DISCOVAR de novo revision 52488 (https://software.broadinstitute.org/software/discovar/blog/). We used this single ninespine stickleback haplotype to estimate threespine‐ninespine sequence divergence and time calibrate coalescence times within the threespine stickleback. DISCOVAR de novo requires a single shotgun library of paired‐end 250‐bp sequence reads from short‐insert‐length DNA fragments. High molecular weight genomic DNA was extracted from an ethanol‐preserved fin clip by proteinase K digestion followed by DNA extraction with Ampure magnetic beads. Purified genomic DNA was mechanically sheared by sonication and size selected to a range of 200–800 bp by gel electrophoresis and extraction. We selected this fragment range to agree with the recommendations for de novo assembly using DISCOVAR de novo. This library was sequenced on a single lane of an Illumina HiSeq2500 at the University of Oregon's Genomics and Cell Characterization Core Facility (GC3F: https://gc3f.uoregon.edu/). We assembled the draft ninespine stickleback genome using DISCOVAR de novo. Raw sequence read pairs were first quality filtered and adaptor sequence contamination removed using the program process_shortreads, which is included in the Stacks analysis pipeline. We ran the genome assembly on the University of Oregon's Applied Computational Instrument for Scientific Synthesis (ACISS: http://aciss-computing.uoregon.edu).To estimate TWe included the single ninespine stickleback haplotype into our sequence analyses by aligning a single‐phased threespine stickleback RAD haplotype from each locus to the ninespine genome assembly. For those that aligned uniquely , we used a custom Python script to parse the alignment fields of the output BAM file  tree for each RAD locus and the is.monophyletic function included in the R package “ape” v3.0  runs of 1,000,000 states were specified, and trees logged every 100 states. We used a coalescent tree prior and the GTR+Γ substitution model with four rate categories and uniform priors for all substitution rates. We identified evidence of lineage sorting by using the program MRCA of all alleles in each gene tree was set at 15 Mya and each node age of interest was converted into years relative to the total height of the tree. Additionally, to use the ninespine stickleback as an outgroup, we required that threespine stickleback haplotypes at a RAD locus were monophyletic to the exclusion of the ninespine haplotype. Doing so reduced our analysis to 49,672 RAD loci for analyses included in Fig. MRCA for each RAD locus. Because of the somewhat limited information from any single RAD locus, and because the facts of the genealogical process mean that the true TMRCA at any locus likely differs from the 15 My estimate  and the size of the windows used.We determined Tπ, within and among populations along with XYd, the average pairwise distance between two sequences using only across‐population comparisons .We constructed haplotype networks of the RAD loci at  Paradis . The atpr et al. ]). The ehttps://github.com/thomnelson/ancient-divergence. Scripts for processing raw sequence data are available from the authors upon request.Scripts used to phase RAD‐tags, summarize gene trees, calculate population genetic statistics, and produce figures and statistics presented in article are available at Pungitius pungitius draft assembly is available at PRJNA429208. The final datasets needed to reproduce the figures and statistics presented in the article are available at https://github.com/thomnelson/ancient-divergence.Raw sequence data supporting these findings are available on NCBI at PRJNA429207. The Parallel adaptation to freshwater environments has been a major theme of stickleback evolutionary history  and identify patterns of identity‐by‐descent (IBD) among populations, which we defined as haplotypes from two populations forming a monophyletic group to the exclusion of the third population.Our sequencing strategy produced 57,992 RAD loci, each with 690 potential variable sites, present across the three threespine stickleback populations and aligned to the ninespine stickleback genome assembly. These data comprise over 40 Mb of sequence, or nearly 10% of the threespine stickleback genome (9.5% of 419 Mb assigned to chromosomes)  = 0.139, FST(RS‐BP) = 0.194, FST(BL‐BP) = 0.226; two‐sided Mann–Whitney test for all pairwise comparisons: P ≤ 1 × 10−10). Genome‐wide differentiation was highest between the freshwater populations, supporting the hypothesis of independent colonization and in agreement with previous morphological  among both freshwater populations Fig. . BackgroST peaks even though IBD was rare elsewhere  and comparable to previous estimates  when compared to π across all populations . Among divergent loci, however, we observed reductions in diversity in both habitats . This divergence ranged more than an order of magnitude (0.0013–0.0442), from substantially lower than the genome‐wide average to ten times greater than the average. These findings indicate that much of the genetic variation underlying adaptive divergence is vastly older than the diverging freshwater populations themselves. Not only was adaptive variation standing and structured by habitat, but it has been segregating and accumulating for millennia.Because the genealogical structure of divergence across the genome mirrors that at eda  with MRCA) of allelic variation, in years. We find that the divergence of marine and freshwater haplotypes has been ongoing for millions of years and extends back to the split with the ninespine stickleback lineage  are each estimated at over 10 MY old.Sequence divergence provides an important relative, but ultimately incomplete, evolutionary timescale. To more directly compare the timescales of ecological adaptation and genomic evolution, we translated patterns of sequence variation into the time to the most recent common ancestor . Outside of the nonrecombining portion of the sex chromosome (chr. 19), the oldest regions of the stickleback genome were those enriched for divergent loci. Patterns of ancient ancestry closely mirrored recent divergence in allele frequencies . This chromosome has been of particular interest because of its association with a number of phenotypes  nested within a large region of deep ancestry spanning 8.1 Mb. Moreover, at least two other peaks distal to eda, centered at 21.4 Mb and 26.6 Mb, were also several million years older than the genomic average at 6.8 MYA and 7.0 MYA, respectively.Adaptive divergence has impacted the history of the stickleback genome as a whole Fig. C. We ideies Fig. A and it MRCA remained outliers even after removing marine‐freshwater relative divergence outlier loci . We estimated that 7.5% of the genome had increased TMRCA even though only 1.9% of RAD loci  were classified as divergent based on marine‐freshwater reciprocal monophyly. When we removed these loci, along with loci with elevated marine‐freshwater differentiation (FST > 0.5), many of the regions in which they resided were still TMRCA outliers. It is possible that the remainder of this old variation is neutral with respect to fitness. However, we identified divergence outliers based on only a single axis of divergence: the marine‐freshwater axis. Throughout the entire species range, populations are locally experiencing multiple axes of divergence, including lake‐stream and benthic‐limnetic axes  but we also identified regions within these inversions in which haplotypes from marine or freshwater habitats, or both, were not monophyletic. inv1 and inv11 both contained two regions separated by loci in which neither habitat type was monophyletic; inv21, the largest of the three, contained ten such regions. Additionally, TMRCA and FST decreased sharply to background levels outside of the inversions, demonstrating the potential for gene flow and recombination to homogenize variation in these regions. We interpret this as evidence that these inversions help maintain linkage disequilibrium among multiple divergently adaptive variants in regions susceptible to homogenization  and absolute (dXY) sequence divergence are positively correlated genome‐wide in two instances of marine‐freshwater divergence.Figure S5. TMRCA outlier regions remain outliers after removing highly differentiated RAD loci.Figure S6. Marine‐freshwater divergence in threespine sticklebacks is associated with reduced signal of monophyly of threespine haplotypes.Table S1. Sequencing summary for threespine stickleback samples.Table S2. Genome assembly statistics for Pungitius pungitius.Click here for additional data file.


X-chromosome short tandem repeat markers (X-STRs), due to their special inheritance models, physical location on a single chromosome and the absence of recombination in male meiosis, play an important role in forensic and population genetics. While a series of genetic analyses focusing on the genetic diversity and forensic characteristics of X-STRs are well studied for ethnically/linguistically diverse and demographically large Chinese populations, genetic evidence from Gelao ethnicity is still sparse. Here, we genotyped the first batch of 19 X-STRs in 513 Chinese Gelao individuals , and reported genetic polymorphisms, forensic characteristics based on the single locus and seven linkage groups. DXS10135 with the highest PIC (0.9106) and LG1 (DXS10148-DXS10135-DXS8378) with the largest HD (0.9970) are polymorphic and informative. The CPDs in Gelao males and females are respectively larger than 0.999999999997095 and 0.99999999999999999999918, and the combined MECs are larger than 0.999999975715109. Subsequently, we investigated the population relationships among 14 Chinese populations based on 19 X-STRs and among 23 populations based on 11 overlapped X-STRs. Our results revealed genetic differentiations among Tibeto-Burman, Altaic and other Chinese homogenous populations, and demonstrated that Guizhou Gelao has the genetically closer relationships with Han Chinese and geographically close Guizhou Miao. STR is the repetitive nucleotide sequence, which comprises a repeating motif of 2–6 base pairs2. Previous studies have suggested that slippage events during the DNA replication make the contribution to higher mutation rate of averagely 10−3 to 10−4 mutations per generation than other types of genetic markers, such as binary markers of single nucleotide polymorphisms and insertion/deletions5. A large-scale surveys focused on lager number of autosomal STR variations have been performed and demonstrated that STRs are associated with regulating gene expression and complex molecular phenotype traits, as well as prevalence and susceptibility of Mendelian diseases and cancers7. Y-chromosomal STRs with the features of high mutation and male especial inheritance play an important role in the population genetics, genealogy researches, evolutionary and forensic studies9. In forensic science, more attentions have been paid to widely in the rates and patterns of de novo STR mutations, genetic polymorphisms and forensic characteristics of the CODIS (Combined DNA Index System) or expanded CODIS markers14, or specific Y chromosome STRs (Y Filer Plus and PowerPlex Y23)18 in geographically, linguistically, and ethnically diverse populations21.Short tandem repeat (STR), one kind of mutation-prone genetic marker and also often referred to as microsatellite and simple sequence repeat (SSR), is widely distributed in the human genome (approximately 1.6 million and spanning nearly 1% of the human genome)22. In the past decade, the commercially available kits of Mentype Argus X-8 kit23  and Investigator Argus X-1224  which can respectively co-amplify eight X-STRs and twelve X-STRs belonging to four linkage groups were utilized in human identification purposes and complex kinship identifications. Recently, to get higher discriminatory power, a new commercial AGCU X19 X-STRs amplification kit  has been developed25 and emerged to characterize the genetic polymorphisms and forensic characteristics, as well as reconstruct X-chromosomal genetic marker haplotype reference database in Chinese nationalities31. Unfortunately, genetic variations, haplotype diversity of X-chromosomal genetic markers in Chinese Gelao, as well as genetic relationships with geographically/ethnolinguistically related populations have not yet been addressed.X-chromosomal STRs with the advantage features of autosomal and uniparental biomarkers have been recognized to play an important complementary role in forensic deficiency cases and other complex kinship identifications35. Recently, China has been recognized as one of the hub of geneticists, molecular anthropologists, linguists, and archeologists35. Gelao ethnic group with the total population over 0.55 million, mainly scattered in the provinces of Guizhou, Guangxi, Sichuan, and Yunnan, as well as Ha Giang in northern Vietnam. And over 96% of Chinese Gelaos reside in Guizhou according to 2012 census. Previous cultural and archeological evidence has shown that present Gelao people are descendants of ancient Liao people residing in southwest China (https://en.wikipedia.org/wiki/Gelao_people). Ancient Liao, as a typical slow development population due to the limitations of the availability of resources, disgusting climatic conditions, possible diseases, and the spread of technological and cultural innovations, has experienced the long history of Hunter-Gather and Agriculture periods with hunter-gathering and nomadic lifestyle37.China is one ethnolinguistically diverse country consisting of 55 minority ethnic groups and one world largest group of Han nationality, whose speaking languages belong to at least five language families . Each of Chinese ethnicities is enriched with the special and complex population history, including origin, migration, as well as cultural and genetic admixture40 based on genetic variations of 19 X-STRs, and with 22 populations49 on the basis of 11 overlapped STR loci between the AGCU X19 amplification system25 and Investigator Argus X-12 amplification kit42. We sought out to address the following questions: (1) what about the genetic diversity of 19 X-STRs and seven linkage groups in Gelao ethnicity? (2) what are the locations of Chinese Gelao ethnicity in a nationwide genetic variation context? (3) what are the linguistic, geographic and social affiliations based on X-chromosomal genetic markers? (4) what are the features of Chinese population genetic substructures and the genetic distances between Gelao nationality and other reference populations?In the present study, we first genotyped the 19 X-STR loci in 513 Chinese Gelao individuals and then integrated our data with 13 previously published populations50. Statistically significant deviations from LD expectation are observed in 8 pairwise comparisons  in the female individuals  residing in Guizhou province, southwestern China. Linkage disequilibrium (LD) for all 171 pairs of loci among female individuals was conducted by permutation test using the expectation-maximization (EM) algorithm with the number of permutations of 10,000 and initial conditions for EM of 2, and exact test of pairwise LD in 248 male individuals was performed employing a Markov chain with the chain length of 10,000 and dememorization of 100051. As shown in Table We next performed the exact test using the Markov Chain with the forecasted chain length of 1,000,000 and dememorization steps of 100,000 to examine the Hardy-Weinberg equilibrium (HWE) of 19 X-STRs in the 265 female individuals on the basis of the distributions of the observed heterozygosity (Ho) and expected heterozygosity (He)f) and male (PDm), and four mean paternity exclusion change indexes introduced respectively by Krüger et al.52 (MEC Krüger), Kishida et al.53 (MEC Kishida), and Desmarais et al.54 (MEC Desmarais and MEC Desmarais Duo), of Gelao females, males and pooled population are presented in Supplementary Tables m and PDf are 0.99999999999985 and 0.99999999999999999999974. Four combined MEC values are respectively 0.999999975595042, 0.999999999998348, 0.999999999998334, and 0.999999995565582. We subsequently evaluated forensic efficiency in Gelao males. As shown in Fig. The forensic parameters, including genetic diversity (GD), polymorphism information content (PIC), power of exclusion (PE), power of discrimination in female 57, LG3 (DXS7132-DXS10079-DXS10074-DXS10075)49, LG4 (DXS6809-DXS6789)58, LG5 (DXS7424-DXS101)59, LG6 (DXS10103-HPRTB-DXS10101)56 and LG7 (DXS10134-DXS7423)49. The haplotype compositions and corresponding haplotype frequencies of seven linkage groups in 248 males are presented in Supplementary Table 19 X-STRs can be grouped into seven linkage groups (LG): LG1 (DXS10148-DXS10135-DXS8378)40 consisting of 3,410 unrelated individuals genotyped with 19 X-STRs using Nei’s genetic distance, principal component analysis (PCA), multidimensional scaling analysis (MDS) and Neighbor-Joining (N-J) tree. The reference populations comprised Southern Han (n = 308)30, Tibet Tibetan2 (n = 213)30, Xinjiang Uyghur2 (n = 211)30, Ningxia Hui (n = 200)30, Tibet Tibetan1 (n = 270)26, Xinjiang Uygur1 (n = 220)26, Guanzhong Han (n = 474)31, Xinjiang Kazakh (n = 300)39, Xinjiang Xibe (n = 179)40, Liangshan Yi (n = 331)27, Sichuan Han (n = 201)28, Sichuan Tibetan (n = 235)29, and Guizhou Miao (n = 268)60. The first three principal components extracted 58.687% of total genetic variations . As showed in Fig. We assessed the genetic relationships between the Guizhou Gelao and a panel of 13 nationwide populations49 from 12 diverse ethnicities and six language families, on the basis of 11 overlapped X-chromosomal genetic markers between the Investigator Argus X-12 QS Kit and AGCU X-19 amplification system. We first explored the genetic homogeneity and heterogeneity using PCA based on the allelic frequency distributions. We found that a total of 53.534% genetic variation was extracted from the total variance based on the first three components. As shown in Fig. To glean further details of Chinese genetic structure, we combined our investigated genetic variations of Gelao with more previously published populations, including 22 reference groups49 are estimated and presented in Supplementary Table Pairwise Nei’s genetic distances between the Guizhou Gelao and other 22 nationwide reference populations59 based on large scale pedigree and population genetic analyses revealed that the 19 X-STRs can be grouped into seven linkage groups (LG): LG1 comprises three loci located on X-chromosomal short arm56, LG2 is consisted of three genetic markers located on the centromere with low recombination rate57, LG349, LG458, LG559, LG656, LG749 are located on the long arm. DNA Commission of the International Society for Forensic Genetics (ISFG) recently recommended that haplotype frequency should be considered to calculate the likelihood when linkage inheritance exists in the included forensic X-STRs50. Thus, statistical parameters of forensic interest based on both single locus and linkage groups are analyzed.Forensic genetic workers are needed to illuminate the potential power (genetic polymorphisms and forensic parameters) in forensic application, in order to provide population-specific reference data for establishing a comprehensive database for a new PCR amplification system before its extensive use in forensic casework. Herein, Genotype data of 19 X-STRs included in AGCU X19 kit in 513 unrelated Chinese Gelao individuals is obtained. Before analyzing the forensic population frequency data, we evaluate the linkage disequilibrium. Linkage is the phenomenon that genetic markers are close together on a chromosome and can inherit as a unit during the meiosis phase of sexual reproduction. Linkage disequilibrium, also referred as allelic association, is non-random association of different alleles, which can be caused by linkage and specific population history, like population substructure, migration, non-random mating and genetic drift. In this study, linkage disequilibrium analyses were performed in both male and females. Most marker pairs which are of disequilibrium were observed within the linkage groups. Previous studies61, including GD, PIC, PE, PDf, PDm, and four mean paternity exclusion change indexes . PIC and GD are serviceable in both autosomal and X-chromosomal markers, and GD is also appropriate for Y-chromosomal markers61. MEC Krüger is conceived for addressing the deficiency cases without the alleged father which replaced by the paternal grandmother using X-chromosomal markers and normal trios using autosomal markers52. MEC Kishida and MEC Desmarais are specially designed and suitable for trios with a daughter54, and MEC Desmarais Duo is valid for cases of father/daughter duos or mother/son duos on the basis of X-chromosomal markers54. In this study, the combined powers of the aforesaid six parameters in Chinese Gelao pooled population on the basis of single locus allele frequencies are respectively 0.99999999999985, 0.99999999999999999999973, 0.999999975715109, 0.999999999998337, 0.999999999998324, and 0.999999995577508. For haplotype analyses, the combined powers of discrimination and mean paternity exclusion chances are also estimated. The combined PDm and PDf are 0.999999999997095 and 0.99999999999999999999918, respectively, which are slightly smaller than efficiency calculated by allele frequency distributions. The cumulative mean paternity exclusion chances in trios are 0.999999999394923 (Krüger), 0.999999999991709 (Kishida), 0.999999999996492 (Desmarais), and which in duos is 0.999999999682643 (Desmarais). The combined MEC Kishida, and MEC Desmarais based on genetic polymorphisms in the single locus are larger than that on the basis of genetic variation of haplotype distributions of seven linkage groups. However, the higher combined indexes of MEC Krüger and MEC Desmarais Duo are observed according to the genetic polymorphisms of haplotype. Our findings combined with our previous investigations29 indicate that the 19 X-STRs are informative and polymorphic in Chinese Gelao population and this amplification system can efficiently complement the analyses of autosomal13, mitochondrial and Y-chromosomal STRs16, single nucleotide polymorphisms (SNPs)62, insertion/deletions (InDels)63 in the forensic applications, especially in some special and complicated kinship cases .AGCU X-19 STR amplification system, co-amplification and fluorescent detection of the 19 X-STRs, was developed specifically to facilitate Chinese X-STR reference database establishment. To explore the power of this panel in forensic complex paternity testing and individual identification, we next comprehensively evaluate the forensic efficiency indexes and the genetic polymorphisms. A set of forensic parameters has been devised35. The detailed genetic structures of Chinese minority ethnicities with the exception of Uyghur and Tibetan64, particularly the Chinese Gelao, remains unresolved. We used two different datasets to investigate Chinese population structure. Significant genetic differences were identified between Turkic-speaking, Tibeto-Burman-speaking and other Chinese populations. Which are consisted with previous genetic studies64. Zhang et al. recently found the differentiated demographic histories of two Tibeto-Burman populations (Tibetan and Sherpa) and other east Asian populations, as well as revealed the high-altitude local adaptations (EPAS1and EGLN1)64. Feng et al. revealed four-way ancestries in modern Uyghurs (Turkic population): European and South Asian, East Asian and Siberian32. The specific genetic ancestry and population history, including high-altitude selection and admixture with surrounding populations, make a significantly different genetic architecture in Tibetans and Uyghurs.China, located on the East Asia and comprising 56 ethnically/linguistically diverse ethnicities officially recognized by the People’s Republic of China and several unrecognized populations , has been the genetic subject in the molecular anthropology, archaeology, population genetics and forensic genetics to shed light on the genetic diversity, origin, divergence, evolution, population migration and admixture of the eastern anatomically modern humans after migrating out of Africa around fifty millennium BC65 or TreeMix66. Which is also consisted with previous studies based on the Y-chromosomal, autosomal genetic markers68. Totally, our results based on the X-chromosomal markers demonstrated genetic differentiations among Turkic, Tibeto-Burman and other admixture groups . These patterns of genetic variation and structure are caused by the migration35, nature selection64, admixture32 and religious and cultural diffusion34.Except for Turkic and Tibeto-Burman populations, other Chinese populations are homogenous groups as revealed in this study. Our comprehensive population genetic comparisons demonstrated that Gelao keeps the genetic affinity with this homogenous group, especially for Han Chinese and Guizhou Miao . Since the remarkable cluster structure was displayed by different methods between Gelao and these diverse ethnic groups from different linguistic family, including mainly Sinitic-speaking , Hmong-Mien-speaking , and Tai-Kadai-speaking (Zhuang). Meanwhile, the closer genetic relationships between Gelao and others based on different methods and datasets are somewhat different: PCA revealed the Gelao shows close relationships mainly with Han, Miao and Xibe in Fig. 70. Additionally, Guizhou Miao is another minority group in Guizhou Province and geographically close to Guizhou Gelao60. The close genetic relationships of Guizhou Miao and Guizhou Gelao are displayed more explicitly and steadily than others (except for Han Chinese) based on all the tested methods, To better understand the origin and migration of Gelao ethnicity and dissect the fine-scale genetic structures and relationships with complex surrounding or related populations, additional genome and population analyses based on higher resolution genetic marker sets, such as high-density SNP chip and whole-genome sequencing data, are needed.As a typical example of the apparent genetic affinity between the Gelao and all compared Han populations derived from distinct administrative regions as shown by all three phylogenetic methods, it can also be explained as a mixed cluster pattern: an obvious ethnical cluster of different Han populations coupled with a probable geographical cluster of the Gelao ethnicity and local Han majority, since they have a long history of living and intermarriage with each other in the same northern part of Guizhou ProvinceTightly linked X-STR markers play an important role in forensic complex kinship cases or deficiency case identifications. In this study, we genotyped 19 X-STRs in 513 unrelated Chinese Gelao individuals to investigate the forensic characteristics, and combined with 13 previously studied nationwide populations based on the genetic variations of 19 X-STRs as well as 22 reference populations on the basis of 11 overlapping X-STRs to explore the Chinese population genetic relationships along ethnic, geographical and linguistic divisions. All 19 X-STRs are in accordance with the HWE. Forensic parameters are estimated according to both allele and haplotype frequency distributions. Locus of DXS10135 and linkage group of DXS10148-DXS10135-DXS8378 are the most informative and polymorphic genetic markers in Chinese Gelao population. The high combined power discrimination and mean paternity exclusion chance are achieved based on genetic variations of both 19 X-STRs and 7 linkage groups with minor differences, indicating that this panel could complement the applications of autosomal, Y-chromosomal and mitochondrial markers in forensic deficiency cases. This study also provides haplotype database for likelihood estimation of kinship identification in Guizhou Gelao. Additionally, our PCA, MDS and phylogenetic relationship reconstruction, which are based on two sets of genetic markers from a large of Chinese populations, are concordant in revealing the genetic distinctions among Tibeto-Burman-speaking populations, Altaic-speaking populations and other Chinese language family populations. Besides, Guizhou Gelao as a Tai-Kadai-speaking population, has the closer genetic relationship with Han Chinese and geographically close Guizhou Miao. Further genetic studies based on the whole-genome studies of modern or archaic samples in East Asia are needed due to the existing uncertainty of genetic relationships among Chinese populations.This study was performed with the approval of the Ethics Committee of the Zunyi Medical University and followed the guidelines published by Center of Forensic Expertise, Affiliated Hospital of Zunyi Medical University. Each voluntary participant has signed the written informed consent after being informed of the aim of the study. A total of 513 human blood samples  were collected from unrelated healthy Gelao individuals residing in the Zunyi City in Guizhou Province, southwest China. Samples from individuals whose parents and paternal grandparents belonged to the Gelao ethnolinguistic group and had non-consanguineous marriages within three generations.Genomic DNA was extracted and isolated using the salting-out method. Quantification analysis of DNA template was carried out using the Quantifiler Human DNA Quantification Kit (Thermo Fisher Scientific) on the basis of manufacturer’s instruction on the 7500 Real-Time PCR System (Thermo Fisher Scientific). All DNA sample was diluted to 1 ng/μl and preserved in the −20 °C until the following amplification.2O (7.5 μL). PCR cycling was employed as 95 °C for 2 min, followed by 10 cycles of 94 °C for 30 s, 60 °C for 1 min, 65 °C for 1 min, and then followed by 20 cycles of 94 °C for 30 s, 59 °C for 1 min, 72 °C for 1 min, and a final extension at 60 °C for 30 min and 4 °C preservation. PCR products were isolated and detected using the capillary electrophoresis (36 cm capillary array) with POP-4 polymer in the Applied 3500 Genetic Analyzer  which used 5 s at 3 kV for sample injection and 15 kV for 1500 s at 60 °C for electrophoresis. Allele allocation of gene fragment was conducted using the GeneMapper ID-X v.1.4 software (Thermo Fisher Scientific) in combination with the set of bins and panels, the allelic ladder, and AGCU Marker Size-500 following the manufacturer’s instruction.19 X-chromosomal STR loci  included in the AGCU X19 STR Kit  were co-amplified according to the manufacturer’s protocol on a GeneAmp PCR System 9700 Thermal Cycler  using the 25 μL reaction volume which contains reaction mix (10 μL), A-Taq DNA polymerase (0.5 μL), primers (5 μL), template DNA (2 μL), and sdHf) and male (PDm) and mean paternity exclusion chance (MEC) for trios cases introduced respectively by Krüger et al.52 (MEC Krüger), Kishida et al.53 (MEC Kishida), and Desmarais et al.54 (MEC Desmarais) and for duos cases introduced by Desmarais et al.54 (MEC Desmarais Duo) were evaluated using the online tool provided by the ChrX-STR.org 2.0 database (http://www.chrx-str.org/). Gene diversity (GD) and haplotype diversity (HD) were estimated using Nei’s formula51:N and Pi respectively denote the population size and ith allele frequency or haplotype frequency. The gender differentiation , Hardy-Weinberg equilibrium (HWE) in females, Linkage disequilibrium (LD) in males and females were calculated using the Arlequin software (version 3.5.2)71. Finally, we used the newly developed software StatsX (Statistics for X-STR) v2.072 to examine and validate our analysis results.We calculated the allele frequencies of 19 X-STRs in the Gelao males, females and pooled population using the modified PowerStat V1.2 spreadsheet . Haplotype distributions and corresponding haplotype frequencies of seven linkage groups were estimated by the direct counting. Forensic statistical parameters polymorphism information content (PIC), power of exclusion (PE), paternity index (PI), power of discrimination in female  version 3.22 software74. Multidimensional scaling analyses and phylogenetic relationships on the basis of the Neighbor-Joining algorithm were conducted respectively using IBM SPSS Statistics version 21 75 and Molecular Evolutionary Genetics Analysis Version 7.0 (Mega 7.0)76.To dissect the genetic heterogeneity and homogeneity between the studied Gelao population and other nationwide reference populations along ethnic, linguistic and administrative divisions, we first integrated our data with 13 previously investigated populations genotyped by 19 X-STRs and then combined our data with 22 reference populations on the basis of the overlapped 11 X-STRs . The first set of reference groups: Southern Han2O were intended for use as the controls in each batch of genotype.Most of our experiments in this study  were performed in the Department of Forensic Genetics, West China School of Basic Medical Sciences & Forensic Medicine, Sichuan University. This laboratory has passed the China National Accreditation Service for Conformity Assessment (CNAS) and the accreditation of ISO 17025. Besides, this department has taken part in international cooperation of Y-STR genotype quality control. Our experimental procedure was strictly following the guidelines and recommendations of this laboratory. The 9947A cell line and ddHSupplementary Figures S1-S6 and Tables S1-S11.


Plasmodium falciparum merozoite surface protein-1 (PfMSP-1) and -2 (PfMSP-2) are major blood-stage vaccine candidate antigens. Understanding the genetic diversity of the genes, pfmsp-1 and pfmsp-2, is important for recognizing the genetic structure of P. falciparum, and the development of an effective vaccine based on the antigens. In this study, the genetic diversities of pfmsp-1 and pfmsp-2 in the Myanmar P. falciparum were analysed.pfmsp-1 block 2 and pfmsp-2 block 3 regions were amplified by polymerase chain reaction from blood samples collected from Myanmar patients who were infected with P. falciparum in 2013–2015. The amplified gene fragments were cloned into a T&A vector, and sequenced. Sequence analysis of Myanmar pfmsp-1 block 2 and pfmsp-2 block 3 was performed to identify the genetic diversity of the regions. The temporal genetic changes of both pfmsp-1 and pfmsp-2 in the Myanmar P. falciparum population, as well as the polymorphic diversity in the publicly available global pfmsp-1 and pfmsp-2, were also comparatively analysed.The pfmsp-1 and pfmsp-2 were observed in the Myanmar P. falciparum isolates. Twenty-eight different alleles of pfmsp-1  and 59 distinct alleles of pfmsp-2  were identified in the Myanmar P. falciparum population in amino acid level. Comparative analyses of the genetic diversity of the Myanmar pfmsp-1 and pfmsp-2 alleles in the recent (2013–2015) and past (2004–2006) Myanmar P. falciparum populations indicated the dynamic genetic expansion of the pfmsp-1 and pfmsp-2 in recent years, suggesting that a high level of genetic differentiation and recombination of the two genes may be maintained. Population genetic structure analysis of the global pfmsp-1 and pfmsp-2 also suggested that a high level of genetic diversity of the two genes was found in the global P. falciparum population.High levels of genetic diversity of P. falciparum population still remains of sufficient size to allow the generation and maintenance of genetic diversity. The high level of genetic diversity of pfmsp-1 and pfmsp-2 in the global P. falciparum population emphasizes the necessity for continuous monitoring of the genetic diversity of the genes for better understanding of the genetic make-up and evolutionary aspect of the genes in the global P. falciparum population.Despite the recent remarkable decline of malaria cases, the Myanmar The online version of this article (10.1186/s12936-019-2879-7) contains supplementary material, which is available to authorized users. Although global malaria cases have remarkably decreased in recent years, malaria is still one of the most important public health concerns worldwide, with an estimated 219 million cases and 435,000 related deaths in 2016 [Plasmodium falciparum merozoite surface protein-1 (PfMSP-1) and -2 (PfMSP-2) are major blood-stage vaccine candidate antigens, which play important roles in erythrocyte invasion [P. falciparum sub-populations [pfmsp-1 is divided into 17 distinct blocks that are conserved, semi-conserved, and variable [pfmsp-2 alleles are in general grouped into two dimorphic families, FC27 and 3D7, which are based on block 2 and block 4, while repeat regions in block 3 also differ in the number and sequence of repeat units [Understanding the population genetic structure of malaria parasites is necessary to determine the epidemiology, diversity, distribution, and dynamics of the natural population of malaria parasites. invasion , 7, and invasion –12. Theyulations –17. PfMSulations . These fulations , 20. Thevariable , 21, 22,variable . PfMSP-2at units –26.P. falciparum population in other malaria endemic areas, the Myanmar P. falciparum population has also shown high levels of genetic diversity [pfmsp-1 and pfmsp-2 in P. falciparum Myanmar isolates that were collected in 2004–2006 [pfmsp-1 block 2 and pfmsp-2 block 3 in Myanmar P. falciparum isolates that were collected in 2013–2015. They were also compared with the sequences from previous years 2004–2006, to understand the temporal changes of genetic heterogeneity of the two genes in the Myanmar P. falciparum population. Comparative analysis of the global pfmsp-1 and pfmsp-2 was also performed, in order to gain in-depth understanding of the genetic make-up of the two genes in the global P. falciparum population.Similar to the iversity –29. Exte004–2006 . This stP. falciparum infected symptomatic patients who live in villages located in Naung Cho, Tha Beik Kyin, and Pyin Oo Lwin, Myanmar during community-based surveys from 2013 to 2015  targeting 18S ribosomal RNA (rRNA) gene [A total of 115 blood samples used in this study were obtained from NA) gene . Prior tpfmsp-1 and block 3 of pfmsp-2 were designed as described previously [Taq DNA polymerase  with proof-reading activity was used in all PCR amplification steps to minimize the nucleotide mis-incorporation. Each PCR product was resolved on a 1.5% agarose gel, and was visualized under ultraviolet (UV). The multiplicity of infection (MOI) was estimated by the average number of PCR fragments for the corresponding locus per infected individual [Escherichia coli DH5α competent cells, and colonies were screened for the presence of appropriate insert by colony PCR. The nucleotide sequences of the positive clones of pfmsp-1 and pfmsp-2 were analysed through automatic DNA sequencing with M13 forward and M13 reverse primers by the Sanger methods. Plasmids from at least two independent clones from each transformation mixture were sequenced in both directions, in order to verify the sequence accuracy. The nucleotide and deduced amino acid sequences of pfmsp-1 and pfmsp-2 were analysed using EditSeq and SeqMan in the DNASTAR package . The nucleotide sequences reported in this study have been deposited in the GenBank database under the accession numbers MH981972–MH982070 for pfmsp-1, and MH982071–MH982183 for pfmsp-2.Genomic DNA was purified from the blood filters by using a QIAamp DNA Blood Kit , following the manufacturer’s instructions. The primers specific for the block 2 of eviously , 31. Thedividual . The PCRpfmsp-1 and pfmsp-2 among global isolates was analysed. Accession numbers of sequences analysed in this study were presented in Additional file pfmsp-1, and block 3 of pfmsp-2. The genetic polymorphism of each population was analysed by the methods as describe above.The genetic diversity of pfmsp-1 and pfmsp-2 were analysed. The recombination parameter (R), which contained the effective population size and probability of recombination between adjacent nucleotides per generation, and the minimum number of recombination events (Rm) were measured, using DnaSP ver. 5.10.00 [2 index, using DnaSP ver. 5.10.00. The R2 values were plotted against the nucleotide diversity distances with the two-tailed Fisher’s exact test of significance [The recombination and linkage disequilibrium of Myanmar  5.10.00 . Linkageificance .pfmsp-1 block 2 were successfully amplified from 115 Myanmar P. falciparum isolates. They were classified into 3 different allele types: 28 sequences of K1 type, 52 sequences of MAD20 type, and 19 sequences of RO33 type. Amino acid sequence analysis of 99 Myanmar pfmsp-1 revealed 28 different alleles , all 3 types of pfmsp-1, K1, MAD20, and RO33, were identified in the recent years (2013–2015). The 7 alleles  were commonly identified in both the previous and recent years. Interestingly, the overall frequencies of 5 alleles  were decreased in recent years, compared to those in the previous years. Meanwhile, the frequencies of 2 alleles  were highly increased in the recent years than in the previous years. Whereas, 7 alleles , which were found in the previous years, were not identified in the recent years. On the other hand, 21 alleles  were observed only in the recent years, but not in the previous years  of 004–2006 . The genpfmsp-1 sequences from different geographic areas of Myanmar, India, Thailand, Vietnam, Philippines, Papua New Guinea, Solomon Islands, Vanuatu, Ghana, Kenya, Tanzania, Uganda, Peru, and Brazil were comparatively analysed, to understand the genetic structure of pfmsp-1 in the global P. falciparum population. Although the K1 and MAD20 types were the dominant ones in global pfmsp-1, the overall prevalence and distribution of pfmsp-1 allelic types differed by country or continent  and the South American pfmsp-1 . Comparative analysis of 1043 global pfmsp-1 sequences revealed that a total of 267 distinct alleles  were found in the global pfmsp-1. The block 2 region of all alleles belonging to K1 type consistently started with SAQ, and terminated with SGT or SGP  was found at the E3 region in all FC27 allelic types of Myanmar pfmsp-2. Several non-synonymous amino acid changes were also identified in E1, R2, and E3, but their frequencies were very low. The 3D7 allelic type sequences showed more complicated polymorphic characters than FC27 type sequences  copies of 96-bp repeat, while Thailand and Gambia pfmsp-2 had either 1 or 3 copies. The frequency of single copy of 96-bp repeat was the highest in all populations except Gambia, but the frequencies of other copy numbers differed by country. The numbers of R2 specific 36-bp repeat in all analysed global pfmsp-2 sequences ranged from 0 to 6 copies, in which 3 copies were predominant in Myanmar (2004–2006) (65.7%), India (52.3%), and Thailand (78.3%). Interestingly, the frequency of sequences with non 36-bp repeat was high in Myanmar (2013–2015) (36%) and Gambia (50%). Five and 6 copies of the 36-bp repeat were found in only Thailand and India, but the frequencies were very low in both countries. Comparative analysis of repeat units in R1 region of 3D7 type in global pfmsp-2 displayed a very complicated pattern of diversity  65.%, India pfmsp-1 and pfmsp-2 in P. falciparum collected in 2004–2006, respectively. The Rm values were greater in Myanmar P. falciparum collected in 2013–2015   were 4 and 7 for Myanmar ons Fig. . The redP. falciparum population plays a very important role in the natural acquisition of immunity against malaria infections [P. falciparum population is important to developing strategies to control the disease, including the design of effective vaccines against P. falciparum. Due to their polymorphic features, pfmsp-1 and pfmsp-2 have been employed as polymorphic markers in studies for malaria transmission dynamics in the natural P. falciparum population [Plasmodium falciparum cases in Myanmar have decreased in recent years [pfmsp-1 and pfmsp-2 were analysed in Myanmar P. falciparum isolates, to gain in-depth insight into the genetic nature of the Myanmar P. falciparum population.The genetic structure of fections , 34. Thepulation , 35–39. nt years , but thipfmsp-1 and pfmsp-2. Sequence analysis of 99 pfmsp-1 block 2 sequences revealed that a total of 28 distinct alleles  were identified in the Myanmar P. falciparum population that was analysed in this study. Similar to previous studies, different numbers and arrangements of unique tripeptide repeats were the main factors to contribute to the allelic diversity in the K1 and MAD20 types of Myanmar pfmsp-1 [pfmsp-2, 113 Myanmar sequences were classified into FC27 and 3D7 types, which showed highly different dimorphic structures in the variable central regions. The alleles of Myanmar pfmsp-2 belonging to the FC27 family were polymorphic, which was characterized by various numbers of FC27 family specific repeats in the R1 and R2 regions, in accord with previous reports [pfmsp-1 and pfmsp-2 increased in recent years (2013–2015) compared with the previous years (2004–2006), even though the incidence of malaria in the studied areas has reduced in recent years [pfmsp-1 were previously identified from 63 Myanmar P. falciparum isolates collected in 2004–2006 [pfmsp-1, K1, MAD20, and RO33, were identified in 99 sequences in recent years (2013–2015). Moreover, comparative analysis of alleles belonging to K1 and MAD20 types in the previous and recent years revealed that they have changed remarkably in recent years, with the appearance of new alleles, and disappearance of pre-existing alleles. The pfmsp-2 also showed a similar pattern of genetic diversity to pfmsp-1 in the Myanmar P. falciparum population. Twenty-two different alleles  in 148 sequences were identified in previous years, but 59 alleles  were identified in 113 sequences in recent years. As the numbers of P. falciparum isolates analysed both in previous and recent years were limited, it may not be easy to insist that the overall genetic diversity of Myanmar pfmsp-1 and pfmsp-2 has increased in recent years, compared to previous years. However, considering that the number of alleles for Myanmar pfmsp-1 and pfmsp-2 over the total number of sequences analysed has increased in recent years compared with those of previous years, it would be plausible to propose that the genetic diversity of the Myanmar pfmsp-1 and pfmsp-2 in the P. falciparum population in the studied areas has increased recently, and high levels of genetic complexity are still maintained in the population. High levels of the genetic diversity of pfmsp-1 and pfmsp-2 in the recent P. falciparum population in Southeast and Western Myanmar have also been reported [High levels of genetic polymorphisms were identified in the Myanmar  pfmsp-1 , 26. In  reports , 40. Thent years . A totalreported .pfmsp-1 and pfmsp-2 population structure in the studied areas has diversified so drastically in recent years, compared to the previous years, 2004–2006, despite the remarkable reduction of transmission in the last decade. In a declining population, rare alleles usually disappear, and the probability of multiplicity of infection (MOI) is reduced, so inbreeding is likely to increase. Overall decline of MOI was also identified in the Myanmar P. falciparum population analysed in this study. These declining patterns have been identified in both the P. falciparum and P. vivax populations, even in low transmission areas and pre-elimination settings [P. falciparum population. Another plausible explanation for the increased genetic diversity of Myanmar pfmsp-1 and pfmsp-2 in recent years can be speculated as the higher values of Rm for both genes, compared to those of previous years. The high values of recombination parameters identified in the recent pfmsp-1 and pfmsp-2 suggest that high levels of meiotic recombination events may occur in the genes, which render the genetic make-up of the genes more complex. The finding that high levels of MOI comparable to previous years (2.03 for pfmsp-1 and 2.35 for pfmsp-2) were still maintained in recent years (1.98 for pfmsp-1 and 2.41 for pfmsp-2) also supported this notion. Further combined analyses of other polymorphic markers, such as circumsporozoite protein and apical membrane antigen-1, with larger number of isolates, may be necessary for in-depth understanding of the genetic nature and genetic flow of the Myanmar P. falciparum population.It is not clear why the Myanmar settings –45. Thissettings . Asymptopfmsp-1 and pfmsp-2 in the global P. falciparum population also suggests that high levels of genetic diversity of the two genes are maintained in the global P. falciparum population. Interestingly, the overall distribution of allele types of pfmsp-1 differed by geographical origin. Although K1 and MAD20 types were largely predominant in the global pfmsp-1, the overall prevalence and distribution of pfmsp-1 allelic types differed by country or continent. In Southeast Asia countries, MAD20 was the most prevalent type, followed by K1 type. The MAD20 type was also dominant in Pacific countries, but RO33 allele type was also identified as of high proportion in these countries. Meanwhile, K1 type was the most prevalent allele type in the South American and African pfmsp-1. Further analysis of the global pfmsp-1 sequences showed more complicated patterns of genetic diversity of the global pfmsp-1. Most pfmsp-1 alleles among the total 267 global pfmsp-1 alleles were identified in a country-specific manner. The genetic diversity of K1 and MAD20 types was much greater than that of RO33 type. The pfmsp-2 also showed high level of genetic diversity in the global pfmsp-2 population. The R1 and R2 regions were highly polymorphic, with different numbers and arrangements of repeat units. The geographic patterns of genetic differentiation suggest that the functional consequences of the polymorphism should be considered for designing a vaccine based on pfmsp-1 or pfmsp-2. The results of this study contribute insight into the genetic nature of Myanmar pfmsp-1 and pfmsp-2, as well as aid understanding of the genetic diversity of the global pfmsp-1 and pfmsp-2, and may provide valuable information for the development of an effective vaccine based on pfmsp-1 and pfmsp-2.The comparative population structural analysis of pfmsp-1 and pfmsp-2 populations showed high levels of genetic diversity, and have remarkably diversified in recent years, despite the rapid decline of malaria cases in the country for the last decade. These suggest that the Myanmar P. falciparum population still remains of sufficient size to allow the generation and maintenance of genetic diversity. Therefore, continuous molecular epidemiological surveillance to supervise the genetic variation of the parasite in Myanmar would be necessary. Additional studies to examine the dynamics of the genetic diversity and gene flow of the P. falciparum population combined with factors including the malaria transmission intensity based on entomological inoculation rates, and the immune status of P. falciparum-infected individuals, may contribute to the guidance of malaria interventions. The extreme genetic diversity patterns of pfmsp-1 and pfmsp-2 found in the global P. falciparum population also warrant continuous monitoring of the genetic diversity of the two genes in the global population, to better understand the polymorphic nature and evolutionary aspect of the vaccine candidate antigens in the global P. falciparum population.The Myanmar Additional file 1: Table S1. Global pfmsp-1 and pfmsp-2 sequences analysed in this study.Additional file 2: Table S2. Distribution of K1 alleles among global pfmsp-1.Additional file 3: Table S3. Distribution of MAD20 alleles among global pfmsp-1.Additional file 4: Fig. S1. Polymorphisms and distributions of RO33 alleles among global pfmsp-1. (a) Sequence alignment of RO33 allelic types among global pfmsp-1. The eighteen RO33 alleles were identified in global pfmsp-1. The dots represent residues identical to the reference sequence of RO33 (AB276005). Amino acid changes were marked with reds. (b) Frequency of RO33 alleles among global pfmsp-1. PNG, Papua New Guinea.


F  = 2.84, p = .029, η2 = .118). However, significant age-related changes in imagery ability were not found in the three age groups. Change in imagery perspective preference with a trend towards an external imagery perspective was observed with ageing  = 3.16, p = .028, η2 = .096) but not between male and female. The results suggest that imagery ability may be preserved with ageing. As individuals age, their preference for using an imagery perspective shifts from a more internal to a more external perspective. This understanding is important when designing future imagery research and real-life application or clinical intervention.This study examined if imagery ability  and imagery perspective preference were affected by ageing and gender. Ninety-four participants, 31 young, 43 intermediate, and 20 older adults completed the Vividness of Movement Imagery Questionnaire-2 and a knee extension temporal congruence test to reflect on their imagery ability and an imagery perspective preference test. Male participants had a better imagery ability than the female participants ( In the past five decades, mental imagery has gathered a large body of research supporting its use in facilitating performance of motor and cognitive tasks . MotOn account of the growing body of research, there is now an increased understanding of what factors modulate imagery ability to enhance motor performance. These factors include the imagery perspective used  and the Previous studies have demonstrated that ageing causes a slight decline in imagery ability. For example, the vividness of imagery, measured in studies by Malouin, Richards, and Durand  and MuldSchott  found imDespite the increased knowledge, the age-related changes of imagery perspective preference and the role of imagery perspective preference in imagery ability are largely unknown. Although it has been proposed that preference for using an internal or external imagery perspective is identifiable through the ability to use these perspectives , Callow p = .040) and between the young and old groups (p = .049). No participant reported recent knee surgery or knee extension dysfunction which might have impacted on their ability to perform knee extensions for mental chronometry testing. All participants provided informed written consent, and the study protocol was approved by the local ethics committee.Ninety-four volunteers participated in the study: 31 young ; 43 intermediately aged , and 20 old . They were recruited by posting flyers in the Western Sydney University campuses. Using a snowball sampling method, participants referred their friends and family for the study. All participants were healthy through self-report, had no neurological conditions and musculoskeletal limitations, and showed normal cognitive function as screened by attention , comprehension , and short-term memory  items of the Cognistat . No statThe imagery ability was measured in terms of the individual's imagery of a real movement  and a self-reported vividness of imagery using a questionnaire (Vividness of Movement Imagery Questionnaire-2). The participants' preference over external or internal imagery is also measured.This assessment provides explicit information on the temporal coupling between real and simulated movements, and it is a widely used measure for assessing imagery . MeasureIn the current study, mental chronometry measurement of knee extensions (dominant side) was selected for its ease of testing amongst all age groups. To identify the dominant leg for measurement, the Foot Preference Questionnaire  was usedDuring testing, participants sat on a chair with a backrest. In the Time-Dependent Motor Imagery screening test, participants were instructed to imagine knee extensions (dominant side) over time periods of 15, 25, and 45 seconds, presented randomly to avoid time duration predictions. During testing, participants closed their eyes during imagery of knee extensions and signaled either verbally (such as counting) or physically (such as nodding head) each time their knee was extended mentally. The temporal congruence test involved participants imagining and then physically executing two series of five knee extensions. A minimum of 30-second rest intervals between each series and each imagined and executed condition was provided. As with the Time-Dependent Motor Imagery screening test, participants signaled when imagining a knee extension.The mean of the two series of imagined and executed conditions was computed. The temporal congruence between the imagined and executed knee extensions was represented by the calculated imagined/executed ratios, with a score of 1 representing perfect temporal equivalence between imagined and executed movements.Each participant's vividness of imagery was measured using the Vividness of Movement Imagery Questionnaire (VMIQ-2) . The VMITo determine preference for using either an internal or external imagery perspective, all participants rated their perspective preferences by visually imagining the 12 items in the VMIQ-2 . PrefereAfter obtaining informed consent, all participants who fulfilled the selection criteria were asked to provide their age, sex, occupational status, and highest education level. Measurement sessions were administered by trained clinicians either at participant homes, community centers, or university campus rooms. Participants were asked to complete the questionnaires without conferring with others, and each participant was tested individually for the knee extension mental chronometry test. To prevent ordering effects, the testing procedure was counterbalanced by administering either the VMIQ-2 or the mental chronometry test first. A randomized sequence of the assessments was used.Descriptive statistics were reported for all measures across the three age groups and gender. Imagery ability and imagery perspective preference, being in two different constructs, were analyzed separately. The normality of the measures of the three age groups was established using the Shapiro-Wilk tests.As there was a significant difference in comprehension scores of the Cognistat in the three age groups, the score was put as a covariate when comparing the results of the three age groups. Therefore, the multivariate analysis of covariance (MANCOVA) test was used to review if there was any difference in the imagery ability as measured by mental chronometry  and VMIQ-2  across the age groups and the analysis of covariance (ANCOVA) test was used to test if there was any difference in the imagery perspective preference as measured by the VMIQ-2 across the age groups. The multivariate analysis of variance (MANOVA) test and the analysis of variance (ANOVA) test were used to test if there was any difference in the imagery ability and the imagery perspective preference in the two gender groups.η2) indicating the effect size for those with significant differences was reported. The post hoc Tukey HSD test was then adopted to show the differences in imagery ability and imagery perspective preference in any two age groups.Partial eta squared  = 1.25, p = .27).Across all age groups, the temporal congruence ratio measured by the mental chronometry test indicating the imagery ability was 1.21 ± .37, indicating a longer imagined time than executed time. The older age group had the best temporal congruence while the young age group had the lowest temporal congruence . For theF  = 2.84, p = .029, η2 = .118). It was further revealed that significant differences were found in the temporal congruence , but not in imagery vividness for EVI, IVI, and KI.Male participants had a better imagery ability in both temporal congruence as measured by the mental chronometry and imagery vividness for EVI, IVI, and KI measured by the VMIQ-2 than the female participants . The resF  = 3.16, p = .028, η2 = .096). The post hoc Tukey HSD tests revealed that the difference in imagery perspective preference was significant between the young and older age groups (p = .010) and between the intermediate and older age groups (p = .048).The obtained mean in imagery perspective preference across all groups was 48.86 ± 30.79. The average score on each item was approximately four which lies between the “moderate internal visual preference” and “no preference” anchors on the scale. With the increasing age ranges, the mean scores became higher , indicatF  = .12, p = .733).Female participants seemed to indicate an increasing preference for EVI than male participants although the result of ANOVA did not reveal any significant difference  and between imagery perspective preference and vividness for IVI .No significant correlations were found between imagery perspective preference scores and temporal congruence and between imagery perspective preference scores and imagery vividness for KI. However, significant moderate correlations were found between imagery perspective preference and imagery vividness for EVI (The study did not find age-related changes in imagery ability although there was a trend showing that the older age group had a better temporal congruence while the young age group had a better imagery vividness. However, preference for an imagery perspective was found to change with ageing. A significant trend was observed in preference moving towards an external imagery perspective with ageing. When compared between male and female, the male participants had significantly better imagery ability, particularly in temporal congruence. No significant differences were found in imagery perspective preference between the two groups although the female participants showed a trend in preference moving towards an external imagery perspective. In regard to the relationship of imagery perspective preference and imagery ability, a significant moderate correlation was found between imagery perspective preference and imagery vividness in internal and external visual imagery. A preference towards external imagery perspective was significantly correlated with imagery vividness in external visual imagery. A similar trend of a significant correlation was found for those with a preference towards internal imagery perspective; they had a better score in the imagery vividness in internal visual imagery.The results of the present study for age-related imagery changes were somewhat conflicting to previous studies. For temporal congruence, the data revealed that as participants aged, their timing for imagining knee extensions became closer to their timing for executing knee extensions although the results were not significant. In contrast, previous researches show a greater difference between imagined and executed movements in the oldest age groups , 25, 26.No significant difference was found for imagery vividness amongst the three age groups. However, there was a trend that the older participants had a lower imagery vividness for internal visual imagery and kinesthetic imagery. This was both in accordance and in contrast with the findings of Mulder et al. , where nSurprisingly, despite the sustained internal visual imagery ability, the older age group showed a significant preference for using an external visual perspective in comparison to the internal visual perspective preferred by the young age group. This may be of interest to clinical practitioners implementing imagery in therapy, as older clients with motor impairments may more readily use an external imagery perspective. This perspective was found to be more effective for learning complex and form-based tasks, which is important for clients after stroke, as daily functional movements may be deemed as complex . Nilsen Also of interest for imagery scripts was that the younger participants' preference for an internal perspective was only moderate. A previous study has found certain imagery perspectives to be beneficial for certain tasks . TherefoThis study revealed a difference in imagery vividness but not imagery perspective preference between male and female participants. Male was found to have better imagery vividness in this study. This result is not consistent with the previous studies , 33 usinAssessing the imagery perspective preference is important. The objective was to investigate if imagery perspective preference was related to imagery ability. While no relationship was found with temporal congruence, a moderate relationship was found with vividness for external and internal visual imagery. The results showed a significant negative moderate correlation between imagery perspective preference and vividness for external visual imagery and a significant positive moderate correlation between imagery perspective preference and vividness for internal visual imagery. The moderate correlations support the findings and suggestion made by Callow and Roberts . AlthougFor temporal congruence as measured by the mental chronometry, a lack of relationship with imagery perspective preference may not be surprising, particularly, since the temporal congruence between imagined and executed movements using both an internal and external perspective was not examined. While mental chronometry using both perspectives has been previously studied , it willThe results were limited by only measuring vividness and temporal congruence as determinants of imagery ability. In order to capture a more comprehensive view of imagery ability, it would have been beneficial to use a measure of controllability which is also regarded as a component of imagery ability  and an aSome caution must also be taken concerning the generalizability of the present findings. The arbitrary age cutoff of the three age groups may not be the most appropriate and cannot represent truly people of the particular age group. There was an imbalance of male and female participants especially in the young group. As previously discussed, the sample from the older age group was mostly physically active and, therefore, may not be a true representative of the older people. Moreover, participants were recruited by convenience sampling. Therefore, the representation of the results to a wider population may be limited.In light of the findings in the present study, imagery ability seems to be preserved with ageing. Male seems to have a better imagery ability than female. For imagery perspective preference, a significant age-related change was observed, with results indicating that as individuals age, their preference for using a visual imagery perspective shifts from a more internal perspective to a more external perspective. This understanding is important when designing future imagery research and real-life application or clinical intervention, as the consideration of preferences may show more efficacious results. Also of interest is that the present study's findings suggest that across young, intermediate, and older ages, preference for using an internal or external imagery perspective is moderately related to better imagery vividness using that perspective.


The genetic diversity of the sheep breeds in the Arab countries might be considered to be a mirror of the ecology of the region. In this study, the genetic structure and diversity of sheep breeds from Saudi Arabia  and Awassi sheep from Jordan as an out-group were investigated using 19 microsatellites. All the breeds had high intra-population genetic diversity expressed as allelic number (7.33) and richness (2.9) and, expected heterozygosity (0.77). Structure analysis revealed three main gene pools underlying the ancestral genetic diversity of the study populations. The first pool had Harri, Najdi, and Rufidi breeds; the second had Naemi and Awassi breeds, and the third had the Arb breed which was significantly differentiated from the other breeds. Factorial correspondence analysis lent further support to the presence of the three gene pools. Although the outgroup Awassi sheep was more clearly differentiated, it still genetically close to Naemi sheep. The differentiation of the Arb breed could have been resulted from geographic and reproductive isolation. On the other hand, the genetic structure of the other two gene pools could be the result of the past and recent gene flow between individuals reared in the region known to be the center for animal husbandry and trading until the current time. The ecological diversity of the Arabian Peninsula has been reflected in the large number of sheep breeds found in the region (ACSAD (The Arab Center for the Studies of Arid Zones Dry lands)., It is a common assumption that gene flow is influenced by landscape and topographical features of the regions . Blood sampling was performed by taking 5 ml of blood out of Jugular vein into EDTA tubes. The tubes were stored immediately in Ice-boxes and shortly after they were stored at −20°C until DNA extraction step was performed.Genomic DNA was extracted from 1 mL blood aliquots using commercially available DNA extraction Kit . DNA concentrations and purity were determined and then all samples were standardized to 10 ng/μL for genotyping process. Nineteen microsatellite (MS) markers recommended by the FAO/ISAG Panel FAO, , were usA), allelic richness (AR), and expected heterozygosity (He) for each locus and breed were estimated using FSTAT software  and intra-population differentiation (Fis)   ranging between 2 and 6. The K-value, log probability of the data (L[K]) values for each cluster were estimated. The results were exported to STRUCTURE HARVESTER  values so as to determine the most likely number of clusters. Finally, GENETIX® software was used to perform factorial correspondence analysis  Nei,  using ARWE) Nei, . PopulatWE) Nei,  considerA and AR) and genetic diversity (He) , to 14 in both the Harri and the Najdi breeds  in the Arb and highest (3.0) in Awassi sheep  Table . The meaHewas 0.77, 0.75, 0.74, 0.80, 0.73, and 0.74 for the Harri, Najdi, Naemi, Awassi, Arb, and Rufidi breeds, respectively  indicating less heterozygosity than it is expected under HWE in four sheep breeds; 0.096, 0.091, 0.077, and 0.045  for Harri, Najdi, Naemi, and Arb, respectively  showed positive Fis-values in all the breeds. The results indicated a shortage of heterozygotes than it would be expected under HWE. The remaining loci showed that the Fis-value was either negative or positive in one breed or more  based on the distance method of different allele numbers were found significant between pairwise comparisons except between Naemi and Awassi. The pairwise Fst-values varied from lowest (0.006) between Neami and Awassi to highest (0.104) between the Arb and the Rufidi breeds   were solely assigned Naemi and Awassi together. The third genetic pool had Arb breed with very few individuals of limited admixture proportion (<20%) of the second gene pool. The shared proportion of the second gene pool was observed in the other two pools, indicating a common ancestry origin.The genetic population structure of each breed was determined based on admixture level for each sheep individual using correlated allele frequencies model implemented within the 3 Figure . The valThe results of correspondence analysis in this study highlighted better genetic admixture and differentiation between all individuals within and between the breeds Figure . The resA, RA and Hecould be the result of one or more past evolutionary events. The most likely reason to explain the high genetic variation, considering that the transhumant system still predominates in all regions of KSA, was gene flow. This reason could have involved past gene flow within the breeds reared in the same and adjacent regions. The best evidence for this occurrence is reflected in the individuals of Harri and Najdi breeds which existed in the same flocks reared from South to central regions with many crossbreds. The A and He-values were high at most of the loci studied in all the breeds. In particular, the Harri and Najdi had the highest A as well as He indicating that they are the most genetically variable breeds. Generally, if recipient populations have different allele frequencies and if selection is not operating, then it might be expected that migration alone would rapidly cause genetic variation  and also by the Institute Animal Care and Use Committee of the International Livestock Research Institute, Nairobi.RA-A and RA conceived and designed the experiment. RA and MA performed the experiment. RA-A and RA analyzed the data. RA-A performed the bioinformatics analysis. MA and AA contributed in data. RA-A, RA, and AA wrote the manuscript. All authors have agreed on the contents of 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.


Phragmites australis is a cosmopolitan reed growing in a wide range of habitats and its invasion history, especially in North America, has been relatively well studied, it provides an ideal system for studying the role and relationship of genetic and epigenetic variation in biological invasions. We used amplified fragment length polymorphism (AFLP) and methylation‐sensitive (MS) AFLP methods to evaluate genetic and epigenetic diversity and structure in groups of the common reed across its range in the world. Evidence from analysis of molecular variance (AMOVA) based on AFLP and MS‐AFLP data supported the previous conclusion that the invasive introduced populations of P. australis in North America were from European and Mediterranean regions. In the Gulf Coast region, the introduced group harbored a high level of genetic variation relative to originating group from its native location, and it showed epigenetic diversity equal to that of the native group, if not higher, while the introduced group held lower genetic diversity than the native. In the Great Lakes region, the native group displayed very low genetic and epigenetic variation, and the introduced one showed slightly lower genetic and epigenetic diversity than the original one. Unexpectedly, AMOVA and principal component analysis did not demonstrate any epigenetic convergence between native and introduced groups before genetic convergence. Our results suggested that intertwined changes in genetic and epigenetic variation were involved in the invasion success in North America. Although our study did not provide strong evidence proving the importance of epigenetic variation prior to genetic, it implied the similar role of stable epigenetic diversity to genetic diversity in the adaptation of P. australis to local environment.While many introduced invasive species can increase genetic diversity through multiple introductions and/or hybridization to colonize successfully in new environments, others with low genetic diversity have to persist by alternative mechanisms such as epigenetic variation. Given that  In a word, we would expect rapid epigenetic adaptation of introduced groups to new environments before slow genetic accommodation occurs.In this study, we first compared patterns of genetic and epigenetic variation in 22.1P. australis, representing eight phylogeographic groups, were sampled to investigate genetic and epigenetic variation  in the Great Lakes region was likely introduced from the native European counterpart (EU) based on haplotype evidence, and hybridization between the native and invasive groups in nature has not yet been documented in North America  and has become one predominant lineage in the Gulf Coast region  as an outgroup.All samples were collected in a common garden at Fanggan Research Station of Shandong University in Shandong Province, China 36°26′N, 117°27′E), where they had been growing for 2 years. This station has a typical warm temperate monsoon climate with a hot rainy summer and a cold dry winter under climate regulation effects of forest  method  with the function msap (no.bands = “u”). Then, we screened methylation‐susceptible loci (MSL), for which the observed proportion of methylated status across all samples exceeded the error rate‐based threshold (5% by default).To determine the DNA methylation status of every locus from the fragment presence/absence scores of both EcoRI–HpaII denotes a hemimethylated state in external cytosine, and the presence in only EcoRI‐MspI denotes a full‐ or hemimethylated state in internal cytosine, but no consensus exists on the interpretation of the last pattern where neither band is present. The last pattern caused by full methylation or genetic mutation in the target site should be considered as full methylated data, null data, or missing data. Here, all three strategies were used to compare global cytosine methylation percentage among ploidy levels in common reed. The global methylated cytosine was established using the sum of the internal methylated and the external hemimethylated cytosines.The “msap” package also provides a report on methylation levels for each group, but it is not forthright to estimate the global level of individual methylation. It is unambiguous that the presence in both bands denotes an unmethylated state, the presence in only ST values were used to evaluate genetic and epigenetic differentiation among all groups. In addition, principal component analysis (PCA) was conducted with the package “msap” to compare the variance between native and introduced populations in the Great Lakes region and between two introduced populations in the Gulf Coast region.The genetic and epigenetic diversity of every population was determined using the population genetic software GenAlEx 6.5 , missing (ANOVA: p = .645), or null data (ANOVA: p = .897)  Figure . The DNA) Figure .3.2P. australis displayed a higher value of all three diversity indices for epigenetic than genetic variation except for LAND where uHe for genetic variation (uHe = 0.40) was slightly higher than that for epigenetic variation (uHe = 0.39).We obtained 154 polymorphic AFLP loci and 151 MSL loci, and diversity indices showed high levels of both genetic and epigenetic variation Table . Among aIn the Great Lakes region, the introduced group (INT) exhibited levels of both genetic and epigenetic diversity higher than the native group (NAT) but lower than original groups (EU). Moreover, the native group had the lowest genetic and epigenetic diversity among all groups, and the introduced group followed.In the Gulf Coast region, the native group (LAND) had a much higher level of genetic diversity than the introduced group (DELTA) but a lower level of epigenetic diversity using the index uHe. The DELTA group had comparable genetic and epigenetic diversity with one possible original group (MED). Compared with another original group, the DELTA group had lower genetic diversity but higher epigenetic diversity.3.3ST = 0.182, p = .001) was more than epigenetic variance .AFLP and MS‐AFLP revealed similar variances among and within groups (see Table ST = 0.021) and epigenetic (ΦST = 0.029) differentiation from the original group EU. The native group NAT had more genetic variance with the introduced group INT (ΦST = 0.356) than the original group EU (ΦST = 0.268), and the NAT group still had more epigenetic variance with the INT group (ΦST = 0.191) than with EU (ΦST = 0.138). The PCA showed less difference in epigenetic variation between the INT and NAT group than in genetic variation, but this tendency was not significant [Figure In the Great Lakes region, the introduced group INT showed a very low level of genetic (Φ ΦST = 0.56 than tST = 0.081) and epigenetic (ΦST = 0.008) differentiation between the LAND group and the DELTA group than that between the LAND group and the MED group . The TA group had the lowest level of genetic differentiation with the LAND group among all groups of P. australis, but not the lowest level of epigenetic differentiation with the LAND group. The PCA displayed a weak decreasing trend of epigenetic differences between the LAND and DELTA group compared with genetic differences [Figure In the Gulf Coast region, there was low genetic and epigenetic variance (both nearly zero) between the introduced group DELTA and its possible original group MED, and there was a lower level of genetic  it is such a short time in the common garden compared to a hundred years of introduced history that most relatively stable epigenetic variation could remain; (2) the common environment has few chances to cause new epigenetic differences among all individuals. In other words, common garden can separate plastic and heritable components of epigenetic variation , spontaneous epimutations (B2), and environmentally induced epigenetic changes (B3) (Richards et al., Unlike many invasive clonal species spreading mostly by vegetative reproduction (Gao, Geng, Li, Chen, & Yang, P. australis M1 lineage were detected between the DELTA and MED groups (Guo et al., However, the adaptation of introduced groups cannot be explained entirely by adaptive evolution based on genetic or epigenetic variation in this study. Only a few diverged ecophysiological functional traits of the Mediterranean 5P. australis is often correlated with genetic variation, suggesting the closely correlated effect of genetic and epigenetic variation in species with high genetic diversity. When the introduced population cannot acquire adequate genetic diversity through hybridization with other introduced populations, the importance of epigenetic variation may rapidly emerge. Faster stable epigenetic convergence between introduced and native groups was not observed maybe due to the strong genetic effect. Further study in situ and in a common garden for several generations is necessary to associate the inheritable genetic and epigenetic loci with invasive traits, and it is better to use a reduced representation bisulfite sequencing approach based on high‐throughput sequencing technology (Robertson & Richards, In conclusion, epigenetic variation in introduced groups of None declared.LL, WG, and XG conceived the idea and designed the study. WG and XG transplanted reeds from the field and the cooperation garden to our common garden. SL, ND, and CP contributed to garden management and sample collection. LL and CP performed the molecular laboratory work. LL, ND, and XG analyzed and interpreted the data. LL drafted the manuscript, and all authors participated in manuscript modifications and gave final approval for publication.