Solanum habrochaites—a wild tomato species found in diverse Andean habitats in Ecuador and Peru. Using Restriction-site-Associated-DNA-Sequencing (RAD-seq) of 50 S. habrochaites accessions, we identified eight population clusters generated via isolation and hybridization dynamics of 4–6 ancestral populations. Detailed characterization of mating systems of these clusters revealed emergence of multiple self-compatible (SC) groups from progenitor self-incompatible populations in the northern part of the species range. Emergence of these SC groups was also associated with fixation of deleterious alleles inactivating acylsugar acetylation. The Amotape-Huancabamba Zone—a geographical landmark in the Andes with high endemism and isolated microhabitats—was identified as a major driver of differentiation in the northern species range, whereas large geographical distances contributed to population structure and evolution of a novel SC group in the central and southern parts of the range, where the species was also inferred to have originated. Findings presented here highlight the role of the diverse ecogeography of Peru and Ecuador in generating population differentiation, and enhance our understanding of the microevolutionary processes that create biological diversity.Evolutionary dynamics at the population level play a central role in creating the diversity of life on our planet. In this study, we sought to understand the origins of such population-level variation in mating systems and defensive acylsugar chemistry in  Solanum habrochaites, found in Peruvian and Ecuadorian Andes. Using Restriction site Associated DNA Sequencing (RAD-seq) (How new phenotypes emerge and evolve in populations has been a long-standing question in evolutionary biology . Over thRAD-seq)  in conjuSolanum habrochaites  group to the sucrose R2 position in acylsugars, and a “southern” supercluster that retained this activity   and pollen-expressed  factors that are not linked to the S-locus play a role in self pollen rejection (reviewed in ity (SI) . In thisS. habrochaites have been identified at the northern and southern species range margins , and suggests that SC has arisen at least twice at the northern margin  that span the entire species range—a distance of ∼2,000 km from Jipijapa, Ecuador (accession LA1625) in the north to Ocaña District, Peru in the south (accession LA1928). Four Solanum pennellii accessions were included as outgroups. As expected, there was large variation in the number of reads obtained per sample  using three different SNP data sets. These results suggested that the sampled S. habrochaites individuals arose from 4 to 6 ancestral populations  lie south of the AHZ. While K = 4 was the optimal cluster size based on the cross-entropy criterion  exhibit substantial incompatibilities . The SC-1 and SC-2 groups previously reported at the northern S. habrochaites species margin  between S. habrochaites and other tomato clade species—were analyzed, enabling us to produce a comprehensive inventory of reproductive traits for 34 accessions throughout the S. habrochaites range  accessions expressed S-RNases, as expected. In contrast, S-RNase proteins were not detectable in styles of the northern SC accessions (with the exception of PI251305) in agreement with previous findings . The sou with SC . In nine3 groups . In a noe allele  online ie allele  was deteHT-A gene demonstrated that these three Ecuadorian accessions all have the same nonsense mutation in the second exon of the gene  SC populations have been documented  that lacked interspecific barriers  with unknown S-RNase alleles, whose relationships to other SC groups were unclear.Based on our phenotyping results, we were able to distinguish four SC groups, SC-1, SC-2, SC-3, and SC-4. Surprisingly, in one region of central Ecuador near Alausí, we found different combinations of reproductive traits including After delineating the reproductive trait groups, we evaluated the association of these groups with the population clusters. Because there were several accessions of significant phenotypic interest that were not included in the RAD-seq population genetic study, we utilized Targeted Sanger Sequencing (TSS) of 22 broadly represented and high coverage polymorphic RAD-seq loci to incorporate these accessions into the population study.orange; LhgSRN-1 S-RNase allele at a low frequency  and these accessions were tentatively designated as group SC-6 . The emergence of the SC-4 group could have occurred from an MP type population  as a result of selection for reproductive assurance as the species migrated southward. Alternatively, LA0094 could be a hybrid between the purple SC and the SI sub-populations. Further experiments will be needed to address the origins of the MP individuals.In southern Peru, the SC-4 group with the e allele  clustersOverall, our detailed phenotyping of reproductive traits suggests that the six population clusters identified in the AHZ are a result of 1) population differentiation of SI clusters 3, 4 and 5, and 2) the independent establishment of multiple different SC groups. The unidirectional reproductive barriers seen between some populations further strengthened reproductive isolation, resulting in population differentiation between some SC and SI groups. Therefore, using the larger RAD-seq data set, we asked how the independent emergence of SC has influenced gene flow between different clusters in the context of the unique geographical features of Ecuador and Peru.S. habrochaites range allows us to ask two questions using genome-wide RAD-seq data: 1) what is the extent of gene flow between the different SC and SI/MP clusters?, and 2) which other evolutionary mechanisms contributed to S. habrochaites population structure besides emergence of SC? Three properties were assessed to address these questions—heterozygosity, population differentiation, and probability of isolation by distance (IBD). We also tested the effect of historical migration between clusters, but this was not found to be a major contributor to population structure (The characterization of mating systems across the tructure  online.Heterozygosity was measured separately using just variant or both variant and invariant sites. Both approaches showed that SC accessions had lower heterozygosity than SI accessions  online. fig. 4Fst) quantifies the degree to which total nucleotide diversity in a pair of populations can be attributed to between-population diversity, with values close to 0 indicating frequent inter-breeding and higher values indicating differentiation  (Fst and dxy differentiated the two superclusters at the HD (Fst and dxy in their pairwise comparisons versus other pairs of neighboring clusters (Fixation index (ntiation . Emergence (dxy) , which it the HD  online, t the HD  online. t the HD . In the t the HD B, again clusters B and C, clusters  online. P = 0.77) (P = 0.06) (P = 0.001)  D. When n = 0.06) E, but th= 0.001) F, providS. habrochaites population differentiation. To determine the phenotypic correlates of this population differentiation, we used previously studied metabolic, namely acylsugar, phenotypes as a model.Overall, these results reveal the role of three important players—the evolution of SC, population fragmentation caused by movement through the AHZ/HD, and IBD south of the HD—in S. habrochaites accessions , frameshift mutation in ASAT4 (chemotype D) and likely loss of the ASAT4 gene (chemotype C)  lies in cluster 7 in the Cajamarca region south of the AHZ. This finding further supports the model of origination of S. habrochaites in the Cajamarca region, and thereby implies that the functional ASAT4 allele was inactivated during the northward migration into the AHZ (Loss of acetylation in the north was previously found to occur via three different mechanisms—loss of otype C) . We founotype C)  online.  the AHZ .S. habrochaites in the context of population structure defined using genome-wide RAD-seq markers. Our results show eight different population clusters across the species range, which have been substantially influenced by geographic variation. The Ecuadorian accessions lie in areas that range from densely forested mountains with high precipitation to either dry or wet coastal regions. On the other hand, accessions south of the AHZ in Peru are often confined to isolated river valleys and experience more uniform environments with regard to altitude and temperature fluctuations. Diverse biotic and abiotic interactions and geographical features are associated with a range of metabolic and reproductive phenotypes in this species  as well as between SI cluster 3 and clusters 1, 2 (SC-2/3). Given that the known inter-population reproductive barriers are unidirectional, there is still potential for continued gene flow between ancestral SI and derivative SC groups. For example, in the case of the SC-2 and SC-4 groups, the loss of pollen SI factors create a unidirectional inter-population barrier that would only prohibit gene flow between SC males and SI females . Such unASAT4 was initially inactivated at the expression level in SI/MP clusters 3–6 during the northward migration   obtained from TGRC were sterilized with 10% trisodium phosphate, germinated on moist filter paper and transferred to peat pots where they were grown for 2 weeks under 16:8 light:dark conditions at 25 °C/16 °C, respectively. Up to four replicates of two-week old plants were then transferred to soil (2 Sure mix + 1/2 sand) where they were grown prior to their harvest for 2 more weeks under the same long day conditions with regular watering. The impact of using stock center accessions on RAD-seq and mating system analysis is described in At Michigan State University, 52 accessions of S-RNase allele analysis, plants were grown on a light shelf and a single young leaf was harvested from each plant for DNA preparation as previously described  and were planted into 4-in. pots containing ProMix-BX soil  with 16:8 light:dark conditions 26 °C/18 °C for 2 months. Plants were transplanted to outdoor agricultural fields at Colorado State University (May–September 2017) to obtain sufficient flowers for multiple crosses, and for collection of stylar tissue for immunoblotting analysis. For escribed . The impS. pennellii were selected for outgroup analysis . Integrity of DNA was verified as a single high molecular weight band on a 1% agarose gel. Biological replicates were obtained for two accessions  and technical replicates for 17 accessions . Four accessions of analysis  online—banalysis . Demultiprocess_radtags.pl script in the Stacks software v2.3d ((-b barcodes_6b.tab -q -c -t 90 -E phred33 -D -w 0.20 -s 10 --inline-null -e hindIII --adapter-1 ACACTCTTTCCCTACACGACGCTCTTCCGATCT --adapter-mm 2 --len-limit 90). Overall, 85.3% reads passed all quality filtering steps and were deemed high-quality (S. habrochaites LYC4 genome (populations module with default parameters. Filtering of SNPs was performed with vcftools v0.1.15 ((--max-missing 0.8 --min-meanDP 6 --max-meanDP 30 --maf 0.05 --mac 3). All individuals had <50% missing loci, so none were removed. Heterozygosity and mean read depth were calculated for each sample in vcftools, which resulted in sample LA0716 being removed from downstream analyses due to higher than expected levels of heterozygosity. Given that read depth can influence the accuracy of identifying heterozygotes ((-dosaf 1 -gl 1 -minQ 20 -minmapq 30). ANGSD results are shown in the main Overall, ∼198 million 100 bp single end reads were obtained after standard Illumina quality filtering. We first converted the FASTQ reads from Illumina 1.5 encoding to Sanger encoding using the seqret tool of the EMBOSS v6.5.0 package, trimmed the reads using FASTX toolkit v0.0.14 to a Phred score >20 and selected only 100 bp reads. Since the first base of all reads, which constituted part of the barcode, was “N,” it was trimmed away. The ∼187 million filtered reads were processed using the re v2.3d  with the-quality  online. 4 genome  using BW4 genome  with def4 genome . Variant v0.1.15  using thozygotes , heterozozygotes  online. ozygotes  by only r2 of 0.2 following a LD decay plot generated in PopLDdecay (F statistics (Fst). Summary statistics such F statistics (Fst) and dxy were calculated by using the filtered SNP VCF file, as well as directly from the RAD loci in Stacks using the populations command (populations --fstats). Accession-wise details are provided in To make some downstream analyses easier to complete, linkage disequilibrium filtering was performed using Plink v1.90b3.38 and a 10-kb sliding window and a pLDdecay . Two VCFS. habrochaites. (Set 2) Set 1 was further filtered using LD pruning as described above to produce a total of 93,129 SNPs, and analyzed using LEA. (Set 3). A different run of Stacks was performed using Stacks v1.44, which allowed more granularity in parameter selection. The non-default parameters included . The populations module in Stacks v1.44 was called with the following non-default parameters (-t 3 -r 0.5 -m 5 --min_maf 0.1 --lnl_lim -6 --merge_sites --write_random_snp). This set contained 25,752 SNPs. For ancestral populations inference, analyses of K = 2–15 were performed to determine the best K using the cross-entropy criterion  removed.Population structure was assessed with two different approaches—using inference of ancestral populations and using coalescent analyses. Ancestral population estimation was performed using three different data sets for increased robustness: (Set 1) We assessed 254,263 SNPs using the R package LEA v2.4.0 . STRUCTUriterion , using ariterion  was perfCoalescent analyses were performed with SNAPP as implemented in BEAST2 v2.4.5 . Due to Split network analysis was performed by implementing a Neighbor Net within splitsTree4 . The proLYC4 , and sequenced . For each of the 22 loci, sequences were aligned in MEGA7 . If no ambiguous calls were present in the trace files, the individual was assumed to be homozygous at that locus.The diploid state of each locus of each accession was determined by aligning the sequences for all accessions, trimming off poor-quality sequences, and examining the set of trace files for each locus manually for heterozygous base calls  for 10,000 burn-in and 10,000 MCMC cycles. Results were extracted using STRUCTURE HARVESTER vA.2 July 2014  in the v2.1.1.2  was usedv2.1.1.2  input mauly 2014  and repluly 2014 . All stauly 2014 .S-RNase alleles (NCBI BioProject PRJNA310635). Using a set of known S-RNase gene sequences as BlastN queries to the LA2119 assembly, a single putative S-RNase transcript sequence was recovered. Allele-specific primers were designed using this putative S-RNase sequence  of each accession were used for phenotyping. Mating system was determined for previously untested northern accessions  online aS. habrochaites SC accession LA0407 (SC-2 group) as male to test for the presence of pistil barriers that reject pollen of SC-2 plants and SI accession LA1777 as female to test for pollen resistance to S-RNase barriers as previously described  and imported into MS-DIAL (m/z values, MS/MS and previous results (Acylsugar sampling was performed from a single uniformly sized young leaflet of 2–3 plants per accession for 40 of the 50 accessions as previously described . Metabol MS-DIAL  for prep results . A 5-folMolecular Biology and Evolution online.msab092_Supplementary_DataClick here for additional data file.


Genetic distances, principal component analysis (PCA), STRUCTURE analysis, and the phylogenetic tree showed that genetic affinity among studied populations is consistent with linguistic, ethnic, and geographical classifications.The Xinjiang Uyghur Autonomous Region of China (XUARC) harbors almost 50 ethnic groups including the Uyghur (UGR: 45.84%), Han (HAN: 40.48%), Kazakh (KZK: 6.50%), Hui (HUI: 4.51%), Kyrgyz (KGZ: 0.86%), Mongol (MGL: 0.81%), Manchu (MCH: 0.11%), and Uzbek (UZK: 0.066%), which make it one of the most colorful regions with abundant cultural and genetic diversities. In our previous study, we established allelic frequency databases for 14 autosomal short tandem repeats (STRs) for four minority populations from XUARC  using the AmpFlSTR® Identifiler PCR Amplification Kit. In this study, we genotyped 2,121 samples using the GoldenEye™ 20A Kit  amplifying 19 autosomal STR loci for four major ethnic groups . These groups make up 97.33% of the total XUARC population. The total number of alleles for all the 19 STRs in these populations ranged from 232 (HAN) to 224 (KZK). We did not observe any departures from the Hardy–Weinberg equilibrium (HWE) in these populations after sequential Bonferroni correction. We did find minimal departure from linkage equilibrium (LE) for a small number of pairwise combinations of loci. The match probabilities for the different populations ranged from 1 in 1.66 × 10 The Altai is a mountain range in Central and East Asia and stretches around Kazakhstan and Russia in the west while Xinjiang in the northwest China and Mongolia in the East. In ancient times, Europeans were settled on the western side and Asians on the eastern side of these mountains . Later oThe Uyghurs are one of the officially recognized ethnic minorities in China, and most of them live in the southern basin (Tarim Basin). The official language is Mandarin; however, other languages are spoken in Xinjiang. The Uyghur language belongs to the Karluk branch of the Turkic language family. Since ancient times, Xinjiang has been a multiethnic region and has been mentioned in Chinese records from the 206 BC to 220 AD . The UygAccording to some historians, the Kazakh (KZK) population emerged around the 13th century. The ancestors of modern-day Kazakhs were the result of an admixture of this group with Mongol tribes from Eastern Chagatai Khanate. They speak the Kazakh language which also belongs to the Turkic language family. Till the 15th century, they were part of nomadic tribes. Kazakh is the third largest ethnic group of Xinjiang and represents 6.50% of the total Xinjiang population .Ancestors of Hui came to China from Central Asia and Islamic Persia as handicraftsmen, merchants, scholars, and soldiers. This human movement started in the seventh century and continued until the 13th century. After settling in China, they started intermingling with Han Chinese, Mongols, and Uyghurs. Ultimately, their phenotype, cultural characteristics, and language became thoroughly Chinese. Hui is the fourth largest ethnic group in Xinjiang and represents 4.51% of the total Xinjiang population .According to historical records, all Han Chinese can trace their origins to the Huaxia tribes which were agricultural tribes living along the Yellow River and formed during the Shang and Zhou dynasties (21st–8th centuries BC) . With thDNA regions with repeat units of 2–6 bps in length are called short tandem repeats (STRs), also identified as microsatellites. STR markers are present throughout the human genome and usually have stable polymorphisms, short sequence lengths, and a dense, uniform chromosomal distribution, which makes their detection and analysis smooth using PCR and sequencing . In foreThere are few studies available that focus on the characterization of autosomal STRs in the main ethnic groups of Xinjiang such as Uyghur  and KazaBlood samples were collected from 2,121 , 436 Kazakh , 593 Hui , and 559 Han  unrelated healthy individuals from the XUAR. All participants gave their informed consent either orally and with thumbprints (in case they could not write) or in writing after the study aims and procedures were carefully explained to them in their language. The study was approved by the ethical review board  of the China Medical University, Shenyang, Liaoning Province, People’s Republic of China. All blood samples were stored at -20°C before DNA extraction. DNA was isolated from blood using the ReliaPrep™ Blood gDNA Miniprep System  according to the manufacturer’s instructions. The quantities of extracted DNA samples were determined using a NanoDrop spectrophotometer , and the final concentration of DNA was diluted to 1–2 ng/μl.Multiplex PCR amplification of 19 autosomal STR loci  was performed using the Goldeneye™ 20A kit (Beijing PeopleSpot Inc.) for all extracted DNA samples. One to 2 ng of extracted DNA was amplified according to the manufacturer’s recommended protocol. Thermal cycling was conducted in a GeneAmp PCR System 9700 thermal cycler  using the following conditions:95°C for 5  min; 30 cycles of 94°C for 30  s, 60°C for 60  s, 70°C for 60  s; and a final extension of 60°C for 30 min.Amplified products were prepared using the Goldeneye™ ORG 500 internal size standard (Beijing PeopleSpot Inc.) and HiDi formamide. All samples were electrophoresed using a 3,500 genetic analyzer  according to the Goldeneye™ 20A standard protocol. POP-4™ polymer  was used for capillary electrophoresis (CE). The Goldeneye™ 20A kit allelic ladder was run for each CE injection. GeneMapper™ Software version 4.0 (Life Technologies) was used for calling all alleles, which was based on the allelic ladder which followed the ISFG recommendations in this regard 2O) as negative control. Negative (sH2O) and positive (AmpFlSTR® Control DNA 9947A) controls were employed for PCR amplification and capillary electrophoresis. All negative controls displayed an absence of amplified product while positive controls were consistent with known genotypes.All extraction and quantitation batches included sterile water (sHhttp://www.kovcomp.com). The phylogenetic tree was constructed using MEGA X, and ancestry component dissection was explored by using STRUCTURE v.2.3.4 software , and pair linkage disequilibrium tests were calculated with PowerMarker V3.25 [13]. The values for matching probability (MP), power of discrimination (PD), polymorphism information content (PIC), power of exclusion (PE) duos, typical paternity index (TPI), gene diversity (GD), and expected heterozygosity (He) were calculated by using the PowerStats software  [14]. Nei’s standard genetic distance between current and previously published reference populations  was compsoftware . The mod−24, 3.98 × 10−24, 6.05 × 10−24, and 1.66 × 10−24 in UGR, KZK, HUI, and HAN, respectively.The allelic frequencies for four Xinjiang ethnic groups are summarized in 17, 1/1.75 × 1018, 1/3.66 × 1018, 1/9.94 × 1018, 1/2.32 × 1018, 1/4.19 × 1018, 1/6.54 × 1018, and 1/1.37 × 1017, respectively. Penta E showed the greatest heterozygosities and PDs in all four newly studied populations. Penta E was also the most polymorphic locus in terms of alleles in the UGR (20), KZK (21), HUI (23), and HAN (21) while THO1 (6), TPOX (6), TH01 (7), and TH01 (7) were least polymorphic. Other forensic parameters such as GD, PIC, MP, PE, TPI, and Penta E loci exhibited a high level of informativeness while TPOX exhibited the least level of informativeness  and the current study , CPDs were 0.999 999 999 999 999 984 833, 0.999 999 999 999 999 990 057, 0.999 999 999 999 999 996 333, 0.999 999 999 999 999 998 244, 0.999 999 999 999 999 997 679, 0.999 999 999 999 999 995 805, 0.999 999 999 999 999 993 455, and 0.999 999 999 999 999 986 23, respectively. CPEs were 0.999 999 416, 0.999 999 483, 0.999 997 932, 0.999 998 973, 0.999 998 617, 0.999 998 811, 0.999 998 151, and 0.999 998 15, respectively. CMPs for the different populations were 1/1.51 × 10tiveness . The datp > 0.05), while only two loci for UGR (vWA and Penta E) and one STR locus for each HAN (D13S317) and KZK (D6S1043) were out of HWE. Subsequently, when we applied sequential Bonferroni correction , none of the loci in any of the four populations were found to be out of HWE (All of the loci were in the Hardy–Weinberg Equilibrium (HWE) in the HUI population  were lower than 0.05 and thus showing LD (The phenomena of linkage disequilibrium (LD) can be a result of the association between adjacent alleles co-inherited from single, ancestral chromosomes. Particularly for tightly linked genes, if a selection favors individuals with particular combinations of alleles, then it produces LD which can persist for some time. LD between two loci decays gradually in proportion to the recombination rate and time as measured in number of generations. When mutations are under positive selection, the LD surrounding the mutations is maintained because of the hitchhiking effect; thus, longer haplotypes at high frequencies can be maintained within the population. Many LD-based methods have been developed to detect positive selection. Hudson et al.  proposedowing LD . Subsequowing LD , only 17owing LD . PresentSTRUCTURE analysis  was done for four populations  and publicly available data for seven populations . The data were used to explore ancestry content and genetic landscapes of Xinjiang populations. The number of inferred clusters (K) varied from 2 to 10 with 10 repetitions of each K value and a total of 10,000 burnins and 10,000 Markov chain Monte Carlo (MCMC) simulations for each repetition. We observed that the best optimal number of ancestral populations was five (K = 5). Uyghur and Kazakh populations shared most of their genetic components with other Turkic-speaking populations such as Uzbek and Kyrgyz (yellow) while they shared a few genetic components with Tibetan (blue) and Han, Hui, Munch, and Korean populations (pink) . The pinPC2 (0.95%) and PC3 (0.87%) resulted in three clusters. In the first cluster, only the Tibetan population was grouped while in the second and third clusters all Altai-speaking populations and typical East Asian populations were present, respectively. PC1 and PC4 (0.84%) also gave us interesting results. Here, two clusters were formed. In the first cluster, the Tibetan population along with typical East Asian populations was grouped while in the second cluster all Altai-speaking populations were present. Results of PCA  were in . A heat map  based on Nei’s standard formula are listed in . A heatheat map  using thheat map , Uyghursheat map  found thheat map  used genheat map , the Kazheat map  found thheat map  found thheat map  found thheat map  investigheat map  reportedheat map  reportedGenetic distances among the HAN population and 104 worldwide populations were calculated using Nei’s standard formula and summarized in ® 20A panel appeared suitable for forensic investigations such as personal identification and paternity testing and had a high power of discrimination. The STR loci included in the kit showed no significant departures from HWE and minimal departure from LE for a very small number of pairwise combinations of loci. Genetic characterization showed that the Uyghur and Kazakh ethnic groups were closely related to other Turkic-speaking groups while the Han and Hui populations showed their associations with other Sinitic language-speaking populations. Interestingly, the Kazakh population showed an affinity with the Mongols which suggested an ancient divergence between Kazakh and Mongols when Mongols originally migrated to present-day Xinjiang (In the current study, we genotyped 20 autosomal STR loci in the Han, Uyghur, Kazakh, and Hui ethnic groups of Xinjiang and calculated the forensic parameters. The GoldeneyeXinjiang .


Mesocentrotus nudus is an important commercially aquatic species because of its high edible and medicinal values. However, wild stocks have dramatically decreased in recent decades. Understanding the population structure and genetic diversity can provide vital information for genetic conservation and improvement. In the present study, the genotyping-by-sequencing (GBS) approach was adopted to identify the genome-wide single-nucleotide polymorphisms (SNPs) from a collection of 80 individuals consisting of five geographical populations , covering the natural habitats of M. nudus in China seas. An average of 0.96-Gb clean reads per sample were sequenced, and a total of 51,738 biallelic SNPs were identified. Based on these SNPs, diversity index analysis showed that all populations have a similar pattern with positive Fis (0.136) and low Ne (724.3). Low genetic differentiation and high genetic connectivity among five geographical populations were detected by pairwise Fst, principal component analysis (PCA), admixture, and phylogenetic analysis. Besides, two YWL individuals originating from an isolated ancestor may imply that there is a genetically differentiated population in the adjacent sea. Overall, the results showed that GBS is an effective method to detect genome-wide SNPs for M. nudus and suggested that the protective measures and the investigation with larger spatial scale and sample size for M. nudus should be carried out in the future. Mesocentrotus nudus, a member of the family Strongylocentrotidae, inhabits the intertidal and subtidal rocky sea bottoms along the coast of northwestern Pacific  for derstood . Recentlderstood . So far,a lurida , Sillagojaponica , and Hals discus . HoweverM. nudus in China seas. The objectives were to detect and genotype single-nucleotide polymorphisms (SNPs) at a genome-wide level and to characterize the genetic diversity and population structure of M. nudus. The results will provide useful information for the utility of GBS on the genetic analysis of sea urchin species and contribute to the population conservation and genetic improvement of M. nudus.In the present study, GBS was used to genotype a total of 80 individuals consisting of five populations, covering the distribution range of M. nudus in China. Gonad tissue was sampled and fixed by ethanol on site. Genomic DNA of each sample was isolated from gonad tissue by using Plant Genomic DNA Kit  following the manual instruction. The purity and integrity of extracted DNA were determined by using a NanoDrop 1000 Spectrophotometer  and electrophoresis on 1% agarose gel. Qualified genomic DNA was stored at −20°C.In 2020, a total of 80 individuals were collected from five localities by SCUBA diving . The generated raw reads were filtered to remove the potential adaptor sequences by using STACKS software  minimum sequence depth was above 5; (2) the allelic number was equal to 2; (3) minor allele frequency (MAF) was greater than 0.05, and (4) missing rate was lower than 10%. The quality control of SNP data was performed using vcftools  were calculated at each SNP locus, and also across all loci, using hierfstat package in R software  was calculated using R package snpReady . The obssoftware . Besidessoftware . The effsoftware . Considest values were calculated with the function pairwise.neifst and significance was tested using 1,000 bootstrap replicates with the function boot.ppfst in the R package hierfstat  using R package SNPRelate  and plotierfstat .2 = 0.8) was used to reduce SNP redundancy, and 1,000 bootstrap analyses were fulfilled. The individual phylogenetic tree was visualized by using R package ggtree  of 94.30%. Statistics on clean reads further showed the quality value 20 (Q20) ≥ 96.33% and quality value 30 (Q30) ≥ 90.41%, and the guanine–cytosine (GC) contents ranged from 40.43 to 42.07%. The reference sequence constructed using STACKS pipeline contained 439,316 tags with an average length of 277 bp, the longest one being 1,036 bp and the shortest one being 71 bp. Initially, 992,728 putative SNPs were identified. After quality control based on successive filtering steps for sequence depth, allelic number, MAF, and missing rate, a total of 51,738 biallelic SNP markers located on 15,562 tags were retained.is), the lowest value was detected in the YWL and the highest in ZZD. Average individual MLH ranged from 0.241 to 0.246. Average sMLH values slightly varied across populations. The estimated effective population size (Ne) was 724.3 for all populations.Several diversity indices are shown in st values ranged from 0.0001 to 0.0039 with a mean value of 0.0019  (Lytechinus variegatus (36.1%) (M. nudus may have a more complex genome than S. purpuratus and L. variegatus.Reduced-representation sequencing could provide an opportunity for those species without prior genetic resources to understand their basic properties of the genome . In this (36.9%) , and Lyt (36.1%) . Conside (36.1%) , this reM. nudus and to determine the genetic diversity and population structure of this species in China seas. Several indices concerning heterozygosity were firstly analyzed across five geographical populations. In general, the DZD population displayed the highest genetic diversity. This result may benefit from the good ecological status in the surrounding waters of Danzi island especially after removal of the marine raft culture and minimizing the amount of waste water discharged into the coastal waters since 2010  genotype frequencies and indirectly reflect relative population heterozygosity. Generally, positive Fis values may be caused by mating among relatives, life history trait with free-spawned planktonic sperm, and selection acting on the genetic markers .The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found below: GenBank (Accession number: Mesocentrotus nudus during this study was approved by the Key Laboratory of Coastal Biology and Biological Resources Utilization, Yantai Institute of Coastal Zone Research, Chinese Academy of Sciences, prior to the initiation of the study and the Animal Management Regulations, revised on March 1, 2017, No. 676.Each of the procedures that were used to handle and treat the QW conducted the experiment and data processing. BL conceived and supervised the project. QW and YL collected the experimental animals. LY and LC contributed to preparing the genomic DNA for SNP genotyping. QW and BL wrote the manuscript. All authors have read and approved 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.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Africa is the continent with the greatest genetic diversity among humans and the level of diversity is further enhanced by incorporating non-majority groups, which are often understudied. Many of today’s minority populations historically practiced foraging lifestyles, which were the only subsistence strategies prior to the rise of agriculture and pastoralism, but only a few groups practicing these strategies remain today. Genomic investigations of Holocene human remains excavated across the African continent show that the genetic landscape was vastly different compared to today’s genetic landscape and that many groups that today are population isolate inhabited larger regions in the past. It is becoming clear that there are periods of isolation among groups and geographic areas, but also genetic contact over large distances throughout human history in Africa. Genomic information from minority populations and from prehistoric remains provide an invaluable source of information on the human past, in particular deep human population history, as Holocene large-scale population movements obscure past patterns of population structure. Here we revisit questions on the nature and time of the radiation of early humans in Africa, the extent of gene-flow among human populations as well as introgression from archaic and extinct lineages on the continent. Homo sapiens, evident by the highest genetic diversity and deepest splits being found among people from this continent. The fact that the earliest fossil finds of early humans have been found in Africa, including northern (dating to about 300 000 years old), southern  and eastern Africa , which rejects the idea of a single panmictic human population in eastern Africa that expands into southern and western Africa and out from Africa ,29,30. TThe high genetic diversity in Africa is a result of a deep population structure, likely shaped by periods of isolation, possibly driven by climatic oscillations ,41. VarieN due to a small census size  increase in the Holocene, contrasting to many other groups , and the set of individuals and populations used for the comparisons . Alterna. genealogical concordance, site-frequency based methods or approximate Bayesian computation analyses , potentially due to the fact that the former methods use the midpoint of cross-coalescences as the divergence time estimate. However, the rank order of divergence times does not differ much between the different approaches, which points to consistent population topology across the methods. The divergence between the ancestors of the Khoe–San and the ancestors of the rest of modern humans is estimated to between 340 000 and 200 000 ya . For instance, mtDNA and complete genomes repeatedly find the deepest divergence among humans being between Khoe–San and all other groups ,31,42,49Although not as well studied, the estimates for the divergence between northern and southern San have a large range as well, from ~170 000 to ~30 000 ya ,31,52. TThere has been a resurging interest in the question of archaic admixture in Africa. With the recovery of the first genome-wide data from Neanderthals and Denisovans ,67, admiet al.  modern humans  simply because the descendant groups (that live today) of this first divergence certainly are modern humans. The human Neandertal/Denisovan divergence of some 650 000 years into the past can then be viewed as an upper bound of the development of unique features of Homo sapiens. In other words, by using these constraints, we can ask the question how humans developed unique characteristics from the time of the common ancestor of Neandertals/Denisovans till the starting time of human stratification observed today. Such unique characteristics may be governed by genetic changes, including frequency changes, and potentially epigenetic changes. There are various models of the origin of our species in Africa. Some of these include versions of (i) a single origin that expands and replaces all other hominin populations, (ii) an African multiregional model, where several African groups  are deeply stratified, possibly by isolation and (iii) range expansion from one group/area, but with some regional continuity and/or archaic introgression (Homo sapiens in Africa (One of the questions that are still unresolved is how gression . The divn Africa ,30, but n Africa . HoweverDisentangling the potentially complex early history of humans is a challenging task as later events, including various forms of gene-flow and migration, can distort genetic signals. More complex models, more diverse data and better statistical tools will allow us to look beyond simple bifurcating models and facilitate disentangling the intricate demography of African populations and inform on the models of the origin of our species as outlined in the previous paragraph. With efforts to gather more data, we still see a bias in data sampling; southern Africa in particular is currently overrepresented, both for modern and ancient genomic data. More genomic data from understudied regions and potential improvements in analyzing ancient DNA will refine our geographic and temporal understanding of African prehistory and allow us to decipher the early events.


Arising from Marques et al. Nature Communications https://doi.org/10.1038/s41467-019-12182-w (2019)1 seek to address this question in lake and stream threespine stickleback fish from the Lake Constance (hereafter referred to as LC) basin in Central Europe. Based on population genetic methods, they conclude that incipient speciation between lake and stream stickleback was facilitated by the recent mixing of genetic variation from old lineages evolved in isolation . In this comment, I discuss conceptual and methodological problems and unrecognized conflicts with existing evidence that cast doubt on Marques et al.’s conclusion.Where genetic variation promoting speciation originates is a crucial question in evolutionary genomics. In a recent article, Marques et al.Marques et al. argue that threespine stickleback populations in the LC basin result from a contact between two deeply separated lineages from Northeastern and Western Europe, and that anthropogenic introduction played an important role in the colonization of the LC basin. I here revisit these views based on a comprehensive nuclear phylogeny for Central European stickleback.2 establishing that the circum-Mediterranean and Black Sea lineage reflects an ancient southern refugial ancestor, whereas the more northern populations derive from a large-scale postglacial surge in southwestward direction via an ancient Baltic Sea. However, the phylogeny does not support Marques et al.’s claim of the existence of an ancient, genetically distinct Western European stickleback lineage “evolved in isolation for several thousand generations”1: statistical support for the monophyly of the authors’ western lineage  stickleback via the Danube drainage. The LC basin nowadays drains into the Atlantic via the river Rhine, so its colonization via the Danube drainage may appear counter-intuitive. However, during the retreat of the Pleistocene ice cover, the present-day LC basin drained in an eastward direction via the Danube4. Even today, the Danube and the LC drainage remain connected through a sinkhole and a 12 km underground stream system5 inhabited by fish6. Evidence of a natural, postglacial colonization of the LC basin also emerges from the authors’ own demographic analysis: their deepest splitting time estimate between populations from the LC basin is 2800 generations (a generation is 1–2 years3) before present, a value in line with an earlier estimate for stream populations in the LC basin . While the authors recognize that these estimates conflict with a very recent anthropogenic origin, they consider shortcomings in their demographic modeling, but not the possibility that at least the stream ecotype may have colonized the LC basin naturally thousands of generations ago.The second insight from the phylogeny is that stickleback from the LC basin prove closely related to populations from the Danube drainage Fig. . The broOverall, Marques et al.’s assumption of a Western European stickleback lineage with a long history of evolution in isolation, and the view that recent introductions were important to the establishment of stickleback in the LC region, do not appear well supported by phylogenetic evidence. Although my analyses include new sequence data not available to the authors’ original investigation, analogous analyses considering only data contemporaneous with their work also raise the above concerns  assume selectively neutral evolution. However, natural selection imposed by novel local ecological conditions profoundly re-structures genetic variation all across the stickleback genome8. That such selection has the potential to bias demographic inference has been suggested in stickleback from the LC basin7. For fairness, it must be highlighted that Marques et al. attempt to reduce potential bias due to selection in their demographic analyses by excluding markers located in chromosome regions exhibiting a particularly low recombination rate. While this data manipulation may increase analytical robustness in older organismal systems in which genomic variation is shaped by background selection (a mutation-driven process), it may be less effective in a young, postglacial system like stickleback strongly influenced by the rapid directional selection of standing genetic variation. This skepticism is confirmed directly by a recent genomic analysis of lake-stream stickleback from the LC basin based on whole-genome marker resolution, revealing that signatures of divergent selection are neither less common nor less extensive physically in the chromosome peripheries exhibiting high recombination rates9 . Likewise, it is easy to imagine that selection can bias D statistics: Marques et al. argue that Northeastern European stickleback are phenotypically closer to ancestral marine stickleback than are Central European populations. However, stickleback within LC are selected for a pelagic lifestyle resembling that of marine fish7, hence greater allele sharing between the LC population and Northeastern European populations is an expected outcome of local adaptation potentially confounding the inference of admixture.Another problem in Marques et al. is that strong conclusions about evolutionary history are derived from population genetic analyses without carefully acknowledging potential violations of the underlying assumptions, and ambiguity in their interpretation. A major issue is that their main methodological tools . An inherent element of ecological vicariance, however, is population differentiation caused by strong divergent selection, for which there is clear experimental evidence in lake and stream fish from the LC basin11. Marques et al.’s demographic analysis, assuming the absence of selection, must therefore fail to offer an adequate comparison of relevant evolutionary scenarios. Another source of concern is that their demographic analysis assumes that all populations had constant sizes during evolution. Fluctuations in population sizes, however, can bias demographic model selection toward secondary contact scenarios12. These methodological caveats in mind, Marques et al.’s inference of an admixture history must be regarded as speculative and no more plausible than alternative scenarios.Also, Marques et al. claim to evaluate several possible demographic scenarios for the colonization and subsequent divergence of stickleback in the LC basin, and in particular to refute an “ecological vicariance” scenario  identify the specific haplotypes (DNA sequence stretches) holding alleles involved in divergent adaptation, and (ii) demonstrate that such haplotypes were initially missing in one or the other original population.A final issue is that even if we assume that admixture between distinct lineages has occurred in the LC basin, the evidence presented by Marques et al. is insufficient for demonstrating that this has promoted divergence. A challenge is that within the LC basin, the lake population has adapted relatively recently to the pelagic ecological niche and represents the most derived ecotype in that region, while stream-adapted populations are ancestral13. However, for a few genome regions under divergent lake-stream selection, genotype data at the level of phased haplotypes have been generated previously by targeted sequencing in stickleback from both the LC basin and the authors’ western lineage. These regions include the EDA locus underlying variation in body plating , and three large inversions . These data demonstrate that the genetic variants underlying lake-stream divergence within the LC basin are not only ubiquitous across Europe, but shared among populations on a worldwide scale. The strongest sequence-based evidence currently available thus indicates that lake and stream stickleback within the LC basin have diversified just as stickleback populations do everywhere: by sorting abundant standing genetic variation preexisting in their ancestors. Conclusively evaluating a potential contribution of admixture to adaptive diversification and speciation in this system would require a methodological stringency beyond the standard of Marques et al.’s work.However, none of the authors’ genetic population samples from outside the LC basin include more than seven individuals, thus precluding robust estimates of haplotype frequencies needed for inferring variational constraints broken by admixture. More fundamentally, the sparse marker resolution of Marques et al. is insufficient for haplotype-level inference in the first placeTo conclude, in view of the problems highlighted in this note, Marques et al.’s claim to “have demonstrated that secondary contact between divergent lineages and the re-assortment of introgressed alleles […] underlie recent ecological speciation” seems overconfident and lacking convincing empirical evidence.16. The data underlying this analysis are SbfI or PstI enzyme restriction site-associated DNA (RAD) sequences generated specifically for this study , or retrieved from published investigations20. In the latter case, the two individuals with the highest read depth were given priority when more than two individuals were available from a given locality. The full data set is described in detail in Supplementary Table The phylogenetic analysis involves stickleback samples from 39 localities in and around central Europe, most of which are represented by two individuals . This reduced analysis included 53 total individuals from 29 localities .Because some of these sequence data were not available to the investigation published in Marques et al.ShortRead21, all raw fastq files were initially filtered for reads starting with the exact SbfI restriction residual , and the reads were trimmed to 70 base pairs (bp). The fastq data thus obtained were aligned to the threespine stickleback reference genome assembly22 with Novoalign v3.00 , using the alignment parameters from ref. 23 (key settings: -t180 -g40 -x15). To obtain single-nucleotide polymorphisms (SNPs) for phylogenetic analysis, the alignments were then converted to BAM format and processed by using the R packages Rsamtools24 and stringr25. At each RAD locus in each individual, haploid genotyping was performed by retrieving the leading haplotype, defined as the single sequence exhibiting the highest read count among all unique sequences present at the RAD locus. RAD loci at which this leading haplotype did not occur in at least two copies, or exhibiting an excessive read depth beyond 4.5 times the expected read depth across all genome-wide RAD loci , were excluded from the analysis. This haploid genotyping approach was chosen because it avoids potential bias in the identification of heterozygous positions and is therefore highly reliable. RAD loci successfully genotyped in every single individual were then used for SNP detection . I accepted SNPs along a RAD locus only if they were at least 8 bp away from the previous polymorphic position, thus avoiding pseudo-SNPs arising from indels. For each individual, the nucleotides present at all SNPs were concatenated to a single string, and these strings combined across all individuals in a single fasta file. For the analysis using the complete data set , the fasta file contained genotype information from 7121 SNPs from 4429 genome-wide RAD loci shared among all individuals, while for the reduced analysis , 7616 SNPs from 4961 RAD loci were available.Using the R package As a robustness check, the above SNP detection and genotyping protocol was repeated for both the complete and reduced data set by using more stringent quality filters: for an individual, the leading haplotype at a RAD locus was accepted only if present in at least five (as opposed to two) copies, and the minimum spacing threshold for SNPs located on the same RAD locus was increased from 8 to 12 bp. This latter approach, yielding 797 SNPs from 563 RAD loci for the complete and 1161 SNPs from 824 loci for the reduced analysis, produced very similar phylogenetic tree topologies leading to the same conclusions (details not presented).ape26 and phangorn27. I first determined the most appropriate substitution model (GTR + G + I), estimated the maximum likelihood tree, and visualized this tree as phylogram. The phylogenies were complemented by visualization of genetic similarity among individuals using ordination. I here analyzed genetic distance matrices derived from the fasta files using principal coordinates analysis (PCoA). These supplementary analyses, performed for both the complete and reduced data sets, considered the European individuals only; the two CLU individuals from Canada were excluded. Individuals were plotted along the first two PCoA axes. All analyses were performed in R28.Phylogenetic analysis based on the above fasta files was carried out using the R packages Further information on research design is available in the Supplementary InformationDescription of Additional Supplementary FilesSupplementary Code 1Reporting Summary


Aspalathus linearis (Burm. F.) R. Dahlgren (Fabaceae) or rooibos, is a strict endemic species, limited to areas of the Cederberg (Western Cape) and the southern Bokkeveld plateau (Northern Cape) in the greater Cape Floristic Region (CFR) of South Africa. Wild rooibos, unlike the cultivated type, is variable in morphology, biochemistry, ecology and genetics, and these ecotypes are broadly distinguished into two main groups, namely, reseeders and resprouters, based on their fire-survival strategy. No previous assessment of genetic diversity or population structure using microsatellite markers has been conducted in A. linearis. This study aimed to test the hypothesis that wild rooibos ecotypes are distinct in genetic variability and that the ecotypes found in the Northern Cape are differentiated from those in the Cederberg that may be linked to a fire-survival strategy as well as distinct morphological and phytochemical differences. A phylogeographical and population genetic analyses of both chloroplast (trnLF intergenic region) and newly developed species-specific nuclear markers (microsatellites) was performed on six geographically representative wild rooibos populations. From the diversity indices, it was evident that the wild rooibos populations have low-to-moderate genetic diversity . The Jamaka population  had the lowest haplotype diversity (H = 0.286), and the lowest nucleotide diversity (π = 0.006) even though the data revealed large variations in haplotype diversity (h = 0.286–0.900) and nucleotide diversity (π = 0.006–0.025) between populations and amongst regions where wild rooibos populations are found. Our data suggests that populations of rooibos become less diverse from the Melkkraal population  down towards the Cederberg (Western Cape) populations, possibly indicative of clinal variation. The largest genetic differentiation was between Heuningvlei  and Jamaka (FST = 0.101) localities within the Cederberg mountainous region, and, Blomfontein (Northern Cape) and Jamaka (Cederberg) (FST = 0.101). There was also a significant isolation by distance . The presence of three main clusters is also clearly reflected in the discriminant analysis of principal components (DAPC) based on the microsatellite marker analyses. The correct and appropriate management of wild genetic resources of the species is urgently needed, considering that the wild Cederberg populations are genetically distinct from the wild Northern Cape plants and are delineated in accordance with ecological functional traits of reseeding or resprouting, respectively. The haplotype divergence of the ecotypes has also provided insights into the genetic history of these populations and highlighted the need for the establishment of appropriate conservation strategies for the protection of wild ecotypes. Aspalathus linearis (Burm. F.) R. Dahlgren (Fabaceae), is a commercially important South African legume, and a strict endemic of the Cape Floristic Region (CFR). It is more popularly known for its production of rooibos tea, an herbal beverage traditionally harvested in the wild, and now commercially produced for the global export market , Anthonotha macrophylla (P. Bauv), and commercial Cyclopia species  sequencing analysis and a panel of 11 nuclear microsatellite marker loci to investigate wild populations of Aspalathus linearis. This dual-marker approach was chosen as it would allow for a historical and a contemporary assessment of species diversity and genetic differentiation  agarose gel (6 µL EtBr) to confirm the presence of high-quality DNA.Total genomic DNA was extracted from collected leaf material preserved in silica gel, according to a CTAB protocol described by ™) using the trnLUAAF and trnFGAA primers: 5′-CGAAATCGGTAGACGCTACG-3′ and 5′-ATTTGAACTGGTGACACGAG-3′ , respectively, designed based on the work of 20 . The PCR reaction was performed with an initial 2-min denaturation step at 95°C. This was followed by 35 cycles, consisting of denaturation at 95°C for 1 min, annealing (adjusted from Extracted genomic DNA was subjected to polymerase chain reaction (PCR) amplification (BioRad T100—Applied BiosystemsThe PCR products were purified using a Sephadex A® G-50 column (Sigma Aldrich®), according to the manufacturer’s specifications, and, bidirectional sequencing reactions were performed using a BigDye™ Terminator v3.1 Cycle Sequencing Kit (Thermo Fisher Scientific), without any changes to the manufacturer’s instructions. Reactions were performed in volumes of 10 µL. Cycling conditions included an initial denaturation period of 1 min at 96°C, followed by 25 cycles of 10 s at 96°C, 5 s at 50°C, and 4 min at 60°C, as per the manufacturer’s instructions. Following this step, the sequencing reactions were sent for visualisation at the Central Analytical Facility (CAF) (DNA Sequencing Unit) at Stellenbosch University. The sequencing files were then manually trimmed on either end to a final length of 501 bp and edited using BioEdit v7.2.6.1 . The seqh), nucleotide diversity (π), and the average number of nucleotide substitutions (k). A hierarchical analysis of molecular variance (AMOVA) was performed using ARLEQUIN v3.5.2 (p < 0.05) to investigate potential population differentiation based on the chloroplast sequences. The AMOVA tested the hypothesis of panmixia, whereby there are no restrictions between populations  (FST). The AMOVA also tested for genetic differentiation between the Cederberg (Western Cape) and Northern Cape regions , among populations within the two regions (FSC) as well as the genetic differentiation within populations (FCT). A Median-Joining haplotype network (http://www.fluxus-engineering.com), to investigate the evolutionary relationships among haplotypes.Diversity indices were calculated in DNASP v5.0  for all N v3.5.2   (United Kingdom) for the development of 18 dinucleotide microsatellite markers (Short Sequence Repeats—SSRs) specific to  markers . The rem markers . The mar2O and sequenced at CAF (Stellenbosch University) using the 500 LIZ® size standard. Electropherograms were analysed using the software program GeneMapper v5.0 (Applied Biosystems) for the detection of peaks, bin calling and genotyping.Polymerase chain reaction amplifications were performed in order to test for successful amplification of the markers and to optimise the PCR conditions. Each reaction consisted of a total volume of 25 µL using 1 µL of 50 ng template gDNA and 1x Qiagen Multiplex PCR Master Mix . The PCR reaction was run at 95°C for 2 min as the initial denaturation step followed by 35 cycles of denaturation at 95°C for 30 s, annealing at the appropriate annealing temperature for each multiplex  for 30 sIS) for each sampling population and region  were also estimated in GENEPOP. Markers under selection were then tested for in ARLEQUIN v3.5.2 (p < 0.05).Microsatellite genotypes were evaluated for allele stuttering, allelic dropout and the presence of null alleles while the frequency of null alleles per locus per population was calculated using MICROCHECKER v2.2.3 . The sofN v3.5.2  (p < 0.0R), observed and expected heterozygosity (Ho and He), Shannon’s index (I), and fixation index (F) calculated in GENALEX v6.501  sampling populations treated separately  and 2) sampling populations grouped into broad geographic regions . This included the average number of alleles per locus (An), the effective number of alleles per locus (Ae), allelic richness, scaled to each population size of 15 individuals  in order to determine the degree of genetic differentiation. A hierarchical AMOVA was performed in ARLEQUIN v3.5.2 (p < 0.05). The AMOVA was used to interrogate panmixia and degree of genetic differentiation as previously described . Multivariate discriminant analysis of principal components (DAPC) was performed in R Studio (R v3.5.3) using the K-means clustering method in the adegenet package to determine the genetic structure. This was achieved by the estimation of the alpha score, determining the optimal number of principal components to retain. The clustering method was run at k = 20. The Bayesian Information Criterion , using a burn-in of 50,000 followed by 500,000 steps where data points were retained. The optimal K values were determined based on Delta K  within the wild rooibos populations was performed in GENALEX v6.501, using the Principal Coordinate Analysis (PCoA) was performed in GENALEX v6.501  to deterion BIC,  was usede v2.3.4 , assumin Delta K  and the Selector . AssignmSelector . An asseGeneland was used  to complete isolation (k = 6). Allele frequencies were assumed to be correlated between populations, and a spatial model was stipulated to explain spatial patterns due to gene flow between locations. This was performed for 1,00,000 MCMC runs across 10 independent iterations.Genotypic information and UTM coordinates were used as input files for the Geneland pipeline. The population cluster range specified was h = 0.286–0.900). Nucleotide diversity ranged from 0.0006 to 0.010 across all the populations but the Matarakopje plants displayed the highest nucleotide diversity  represented by 29 individuals across all populations whereas the remaining 3 haplotypes  are private haplotypes representing the Blomfontein, Jamaka and Matarakopje populations, respectively . H2 is rp < 0.05). For these reasons, this marker was excluded from further analysis. Locus ROI85 yielded little to no genotyping information, and was therefore also disregarded. Locus ROI73 presented with deviations from HWE across all populations and showed evidence of null alleles but was retained for further analysis as it did not display LD with any other markers and was also not found to be under selection. A total of 11 markers were therefore retained for further analyses. Overall, the mean number of observed alleles (An) was 6.788 while the mean number of effective alleles (Ae) was 4.217, ranging from 3.411 (Heuningvlei) to 4.966 (Matarakopje) . The observed heterozygosity varied from 0.528 to 0.704 while the expected heterozygosity was recorded at values of 0.618–0.723. The inbreeding coefficient (FIS) averaged at 0.038, indicating little to no inbreeding. Polymorphic Information Content (PIC) of the SSRs showed an average of 0.645  . Shannonof 0.645 . It shoutrnLUAAF—trnFGAA chloroplast region. Significant differentiation was observed among populations when testing for panmixia , as well as when assessing differentiation among the regions  and among populations within regions . However, there was no significant differentiation reported within populations . The AMOVA results support a divergence between regions (Cederberg and Suid Bokkeveld) as well as among populations within regions. There was no significant divergence within populations, which correlates to the presence of haplotype 1 in the majority of the total individuals that were sampled.The hierarchical AMOVA  highlighST estimates extended from 0.005 to 0.101 (p < 0.05). This indicates moderate genetic differentiation between the wild rooibos populations (ST = 0.101), and Blomfontein and Jamaka (FST = 0.101). The hierarchical AMOVA supported this genetic differentiation across all but one level  and among populations within regions . However, there was no significant differentiation reported within populations .Pairwise Fulations . The larne level . Signifik = 3  revealed no patterns of genetic structure , althougk = 3 . An assek = 3 .2 = 0.296, p = 0.044) between genetic distance and geographical distance . trnLUAAF—trnFGAA region, but no haplotype or nucleotide diversity was presented for comparison. There is, notably, large variation in haplotype diversity and nucleotide diversity between populations and between regions  as well as among the populations within the two regions . There was, however, no significant differentiation within populations  was investigated but little to no inbreeding was detected in the populations focused on in this study (IS = 0.038).To the best of our knowledge, no previous assessment of genetic diversity or population structure using microsatellite markers has been conducted in isozymes , as wellisozymes , focusinisozymes . Lower gisozymes  and thosisozymes . For thiGene flow is directly influenced through seed dispersal and pollinators  and spatST estimates , most likely as a result of physical isolation, despite some obvious similarities in terms of their morphological appearance and chemical profiles (The Heuningvlei and Jamaka populations showed the highest relatedness within populations  and werestimates . These tstimates . Furtherstimates . These tprofiles . This reAspalathus remain ill-defined but wasps and bees are thought to be the important animals for pollinating rooibos although no study has focused on this directly (Available scientific information regarding the reproductive ecology associated with rooibos is tenuous. As far as we are aware, the exact plant-pollinator networks for directly . For thidirectly . BecauseOur data suggests that genetic diversity of wild rooibos populations decline along a gradient, from Melkkraal in the north to Jamaka in the south . This maThere was a significant correlation between geographical distance and genetic distance . It is iST analyses revealed moderate genetic differentiation whereas DAPC analysis determined genetic structure across all sampled populations. These results show a high level of congruence between the genetic data sets, confirming the genetic patterns resolved using the chloroplast intergenic region (ST analysis. Additionally, the Bayesian structure analysis revealed the separation of populations into three clusters, the Northern Cape populations clustering together, and the two Western Cape populations clustered individually as distinct populations (k = 3; ST values (Pairwise Fc region . The DAPc region . In thisc region . These fs k = 3; . This cos k = 3; . The seps k = 3; . FurtherT values , and likA. linearis resources is thus strongly encouraged as distinct gene pools have been confirmed in this study. Many land-users have commented on the population decline over the last few decades and these knowledge-holders have emphasised that more recently it is becoming more difficult every year to find a suitable harvest of wild populations due to populations declining. Conservation initiatives may prove to be of value for both in situ and ex situ strategies. Additionally, it is important to prioritise conservation efforts at every step of the supply chain, particularly for such a uniquely endemic species such as rooibos. Conservation strategies could include thorough monitoring and record-keeping of wild harvesting that supports livelihoods as well as deposits of wild populations to a gene bank for the conservation of distinct populations.Haplotype divergence of the ecotypes from the Cederberg and Suid Bokkeveld provided insights into the genetic history of these populations and there was a clear separation between resprouters and reseeders corroborating the original hypothesis. Through using both nuclear markers and chloroplast sequencing, a comprehensive and complementary portrait of the genetic structure of wild rooibos was evident and there was an ancestral haplotype consisting of both reseeders and resprouters. This data may be indicative of clinal genetic variation that suggests decreased diversity from the Suid Bokkeveld populations down into the Cederberg region. Overall, low intra-specific population diversity was strongly evident in wild collected rooibos, particularly in the reseeder populations of Jamaka and Heuningvlei. Wild rooibos populations occur as sparse collections with few individuals and limited options for allowing frequent gene flow, making them more susceptible to biodiversity loss. The results presented herein thus highlight the importance of assessing genetic variability and the need for implementing strategies for conservation priorities for rooibos that is a highly restricted endemic growing in biogeographic regions that face both habitat degradation and future climate changes. In this particular context, the correct and appropriate management of wild genetic


Karsenia koreana, the sole Asian plethodontid salamander species, occurs only on the southern half of the Korean Peninsula and is thought to have found various climatic refugia. Despite its phylogenetic and biogeographic importance, no population-level genetic analysis has been performed on this species. Here we study the population genetic structure of K. koreana using mitochondrial and microsatellite loci to understand the recent historical dispersion process that shaped its current distribution. Overall, the genetic distance between populations correlated well with the spatial distance, and the genetic structure among populations showed signs of a unilateral northward expansion from a southernmost refugium population. Given the distinct genetic structure formed among the populations, the level of historical gene flow among populations appears to have been very low. As the estimated effective population size of K. koreana was also small, these results suggest that the small, restricted populations of K. koreana are extremely vulnerable to environmental changes that may require high levels of genetic diversity to cope with. Thus, special management strategies are needed to preserve these remnant populations.The Korean Peninsula, located at the southern tip of Northeast Asia, has never been covered by ice sheets and was a temperate refugium during the Pleistocene.  To avoid the advances of Pleistocene ice sheets, many terrestrial animals extirpated or migrated, with some in the northern hemisphere dispersing to the south and occupying sites that served as refugia3. Even after the retraction of the ice sheets, numerous species remained in place, further adapting and diversifying, resulting in some southern regions exhibiting high species diversity and endemism5. Phylogeographic approaches can be used to reconstruct the historical migration routes and diversification processes that species or other higher taxa underwent following glacial period7.Within a geographic area, the distribution of a species reflects its historical dispersion and isolation in the context of geological change and Quaternary climate fluctuation8. This area is characterized by a mountainous terrain resulting from complex geological activity, which offered temperate habitats or glacial refugia during the Quaternary glaciations9. Perhaps this is why the Korean Peninsula, despite its relatively small area, is a region with a reasonably high species diversity and endemism. This peninsula is home to ten species of salamander, of which eight are endemic11. Genetic studies of Hynobius and Onychodactylus salamander species on the Korean Peninsula detected a high level of intraspecific phylogeographic structure13, the existence of cryptic diversity12 and evolutionary relatedness to species inhabiting areas north of the peninsula. In total, these results suggest that the Korean Peninsula provided glacial refugia for salamander species that migrated southward.The Korean Peninsula has features that make it attractive for phylogeographic studies. It is located at the southern tip of Northeast Asia and has never been covered by ice sheets, although it was indirectly affected by the northern glaciation of the QuaternaryKarsenia koreana). Karsenia korena is the only plethodontid species in Asia, and until this species was first discovered in Korea in 200514, plethodontid salamanders were thought to be native only to Europe and the Americas. There have been various attempts to elucidate the biogeographic and phylogenetic histories of plethodontid salamanders, the most diverse family in the order Urodela19. However, the existence of one plethodontid species in Northeast Asia has introduced a complication in the reconstruction of the historical dispersion process of Plethodontidae20. Since K. koreana was first described, researchers have attempted to determine its phylogenetic placement as a means of inferring how this species became distributed in Asia21. The most convincing hypothesis suggests that a small ancestral group of K. koreana migrated from western North America to Eurasia through the Bering Land Bridge around 65 Ma22.One other monotypic genus of salamander is found on the Korean Peninsula—the Korean crevice salamander  have likely been extirpated. The populations on the Korean Peninsula may be considered remnants at the southern end of the biogeographic dispersion. The most effective way to identify the biogeographic pathways of K. koreana is to reconstruct the historical patterns of gene flow by measuring the genetic structure and diversity throughout its known distribution. To date, no population-level genetic analysis has been performed on this species.Although officially considered an endangered speciesa24 Fig. . VariousK. koreana on the Korean Peninsula to understand the historical dispersion process shaping the structure. Two types of genetic markers were used. First, mitochondrial COI (cytochrome c oxidase I) and Cyt b (cytochrome b) were used to estimate the historical migration and isolation processes of K. koreana populations. Second, microsatellites were used to determine the level of gene flow among populations and to estimate more recent demographic information compared to mitochondrial markers. Novel microsatellite markers were developed in this study. Considering that K. koreana is a rare species worldwide that needs careful management, the results of this study provide important baseline data that will inform future conservation strategies.This study was designed to uncover the population genetic structure of Karsenia koreana individuals were collected from April 2018 to August 2019 throughout all regions where this species is known to exist  and the guideline provided in the permits conforming to the Wildlife Protection and Management Act of the Korean Ministry of Environment.Genomic DNA was extracted using a DNeasy Blood and Tissue Kit  following the manufacturer's protocol. The quantity and quality of each DNA sample were assessed using an Epoch Microplate Spectrophotometer . Successfully extracted DNA samples were diluted to 10–20 ng/μL and stored at − 20 ℃ until use for the genetic analyses.31 in Geneious Prime 2019.1.3 (https://www.geneious.com) and Primer Premier 6.25 . Primers KkCOI_F6 and KkCOI_R7 were designed to amplify a complete COI gene  and 1 μL of template DNA using a TaKaRa PCR Thermal Cycler Dice Gradient (Takara Bio). The thermal cycle profile for the loci consisted of an initial denaturing at 94 ℃ for 5 min; 35 cycles of a denaturing at 94 ℃ for 45 s, an annealing at 60 ℃ for 1 min and an extension at 72 ℃ for 3 min (for Cyt b: 65 ℃ for 5 min); and a final extension at 72 ℃ for 10 min. This extension step at lower temperature for longer time of Cyt b was necessary, probably due to the putative secondary structure of flanking regions by poly A and T32, which was verified in our preliminary experiments. The PCR products were purified and sequenced by Macrogen Inc.  and Cosmo Genetech Inc.  on an AB 3730xl DNA analyzer .For the two mitochondrial loci, two novel primers sets were developed (Supplementary Information Table 33 (http://www.repeatmasker.org/) was used for the identification of repetitive DNA sequences. SSR Finder34 (ftp://ftp.gramene.org/pub/gramene/archives/software/scripts/) was used for annotating reads containing simple repeat sequence motifs. A total of 52 candidate markers  were selected for the testing of amplification and polymorphism with an 8-individual test panel . Fourteen microsatellite markers were chosen to genotype the remaining samples. Microsatellite PCR amplification was performed in 20 μL volume consisting of 1X Taq buffer with 2 mM MgCl2, 0.2 mM dNTP mixture, 0.5 μL of 10 μM forward and reverse primers each, 1 U i-StarTaq polymerase  and 1 μL of template DNA using a TaKaRa PCR Thermal Cycler Dice Gradient (Takara Bio). The PCR conditions consisted of an initial denaturing at 94 ℃ for 5 min; 20 cycles of denaturing at 94 ℃ for 20 s, touchdown annealing at 60–50 ℃ for 20 s and an extension at 72 ℃ for 20 s; additional 20 cycles of denaturing at for 20 s, annealing at 50 ℃ for 20 s and an extension at 72 ℃ for 20 s; and a final extension at 72 ℃ for 7 min. Amplified PCR products were genotyped on an ABI 3730xl by NICEM Inc. . Genotype quality check and peak calling were performed using GeneMapper 3.7 .The novel microsatellite markers were isolated by Macogen. Whole genomic DNA was subjected to pair-end sequencing using a MiSeq platform . The extracted reads were processed to remove adaptor sequences, and RepeatModeler35 under the default setting, implemented in MEGA X36. No gaps or ambiguous bases were found.The quality checking, trimming and editing of the mitochondrial sequence data were carried out using Geneious Prime. The sequences were aligned using ClustalWb using DnaSP 5.10.0137; number of haplotypes, haplotype diversity (Hd)38, nucleotide diversity (π)38 and sequence diversity 39. Haplotype sequences of the two loci obtained in this study were deposited in GenBank  were also calculated based on the haplotype data. The level of population divergence (ΦST40) and the average number of nucleotide differences per site between populations (DXY38) were estimated using Arlequin 3.5.2.241 and DnaSP 5.10.0137, respectively.We estimated the following parameters for each population based on the concatenated sequences of COI and Cyt 42 (http://www.fluxus-engineering.com). For phylogenetic tree reconstruction, we used Hydromantes brunus (GenBank accession No. AY728234.1) as an outgroup species, as it is the most probable sister taxon of K. koreana43. Prior to phylogenetic tree reconstruction, the selection of partitioning scheme and substitution models were performed based on a greedy algorithm44 with the Bayesian Information Criterion (BIC) using PartitionFinder 2.1.145. Phylogenetic trees were reconstructed based on maximum likelihood (ML) and Bayesian inference (BI) methods were implemented in RaxML46 on the CIPRES platform47 and MrBayes 3.2.648, respectively.The haplotype network was reconstructed using a median-joining approach in NETWORK 10.0.0.049. For the BI analysis, two independent Metropolis Coupled Markov Chain Monte Carlo (MCMC) runs of 107 generations were conducted using four chains per run with three heated and one cold (temperature set to 0.1). We sampled trees every 500 generations and discarded 25% of the trees as burn-in. We used TRACER 1.7.150 to assess convergence of parameter estimates and posterior probabilities. The remaining trees were summarized to obtain a 50% majority-rule consensus tree. The tree was visualized using FigTree 1.4.3 (http://tree.bio.ed.ac.uk/software/figtree/).For the ML analysis, we applied 'ML Thorough Boostrap' workflow with 1000 bootstrap replicates under the GTR + I substitution modelK. koreana were estimated using BEAST 2.6.151 based on the concatenated dataset of COI and Cyt b. Five outgroup taxa were used; Hydromantes brunus (AY728234.1), Aneides hardii (NC_006338.1), Desmognathus wrighti (NC_006337.1), Desmognathus fuscus (NC_006339.1) and Ensatina eschscholtzii (NC_006328.1). For molecular clock calibration, we adopted four molecular dating constraints  provided in Shen et al.19. The means and standard deviations of the normal distribution for these priors were chosen to reflect arithmetical medians of 95% credible intervals.Divergence times among populations of K. koreana lineages may be relatively close, we assigned a strict clock model52, coalescent constant population model and GTR + I + G substitution model under the default setting. Nested sampling algorithm54 posteriorly confirmed this combination of model parameters among multiple alternatives. The MCMC of BEAST consisted of three independent runs of 108 generations with sampling log and tree files every 1000 generations. After running, the convergence of chains was verified and burn-in periods were determined in TRACER to ensure the effective sample sizes (ESS) for all parameters were over 200. Three independent MCMC runs were combined in LogCombiner 2.6.1. Predetermined 10% burn-in trees were discarded and the final phylogenetic tree was annotated by maximum clade credibility type and median node heights in TreeAnnotator 2.6.0. The tree was drawn by FigTree 1.4.3.Given the population-level phylogenetic relationships among 55 was implemented in BEAST to estimate historical demographic change. An unpartitioned HKY + I substitution model56 was applied, and prior selection, clock model, parameter settings and MCMC setup were the same as those used for the divergence time estimation. To incorporate a time scale into the analysis, we assigned two additional priors; normal distributed clock rate  and lognormal distributed MRCA prior . The result was plotted with log-scale population size by time (Ma) using R package57 based on 'plotEBSP' function provided in BEAST. The likelihood of historical demographic expansion was tested based on Tajima's D58 and Fu's FS59, which was implemented in DnaSP 5.10.0137 with 10,000 replicates.Extended Bayesian skyline plot (EBSP)60 was used to detect null alleles, large allelic dropout and potential scoring errors. Hardy–Weinberg equilibrium and the likelihood of linkage disequilibrium among selected marker loci were examined using Fisher's exact test under 10,000 dememorization, 100 batches and 5000 iterations per batch, as implemented in Genepop 4.7.261. We calculated the following parameters using GenAlEx 6.50362: number of alleles (N), number of effective alleles (Na), observed heterozygosity (HO), expected heterozygosity (HE), and fixation index (FIS) for each locus and population and pairwise relatedness among samples to avoid duplicates. The signature of historical bottleneck was tested utilizing 1000 iterations of mode-shift at IAM, SMM and TPM  using BOTTLENECK 1.2.0263. Garza-Williamson index (M-ratio)64 was quantified using AGARst 3.365. When the M-ratio dropped significantly below 0.68 according to the traditional method, the population was considered to have experienced a severe historical population decline.Micro-Checker 2.2.3FST66 and -RST67 values were computed using FSTAT 2.9.468 and Arlequin 3.5.2.241 with 1000 permutations. Isolation by distance (IBD), the relationship between geographic distance and Slatkin's linearized FST (FST / (1 − FST))69, was analyzed and visualized using GenAlEx 6.50362. Covariance-standardized Principal Coordinate Analysis (PCoA) was performed to identify the distribution of genetic characteristics among populations at the individual level using GenAlEx 6.50362. Genetic barriers against gene flow among populations were mapped using BARRIER 2.270 according to Monmonier's maximum difference algorithm71 with 1000 bootstrapped Nei's chord distance (DA)72 and FST matrices generated by MSA 4.0573 and R package FinePop74, respectively. The level and pattern of population structure was visualized using Structure 2.3.475 that was implemented with 10 iterations of 105 MCMC generations  from K = 1 to K = 11 (the number of populations). The optimal K was determined on STRUCTURE HARVESTER web 0.6.9476 based on Evanno method77.Pairwise K. koreana populations, over 100 scenarios were predefined to include both northward and southward dispersal patterns of different geographically probable orders among genetic clusters. The scenarios were examined in DIYABC 2.1.078 in a tournament fashion. Genetically close populations were grouped into a single cluster to lower the computational load, resulting in seven populations/clusters. More than 105 simulations per scenario were performed and scenarios were compared based on posterior probabilities. If the comparison results of the direct and logistic approaches were inconsistent, the confidence of high-ranked scenarios were evaluated again to discriminate among them. For the last two selected scenarios, 106 simulations were implemented for each to estimate the parameters of effective population size and branching point.To infer the evolutionary history of . koreana populations, 37 of which were unique to an individual population. The Hd value of the species in total was identified (0.942), while its π value was relatively low (0.00995). The ratios of private haplotypes (NP / N and PH / H) were relatively low in populations [BE], [JS], [PC] and [SC] 19. In our results, the first split between population [GY] and the others was estimated to have occurred around 2.30 Ma (95% highest posterior density range: 1.74 ~ 2.92 Ma) , and loci K1011 and K1040 had null alleles in two or more populations. We included these three loci  in subsequent analyses as the analyses results did not differ with or without these loci . We did not detect any signature of linkage disequilibrium among the loci used (data now shown).Ten tetra-, two tri- and two di-nucleotide microsatellite markers were chosen, as they successfully amplified and contained adequate levels of polymorphism within and among populations. Although no large allelic dropout was detected, the presence of null alleles was suspected in all loci analyzed. Null alleles were found in only one or two populations across the loci and were not found associated with any specific population. This suggests that the potential for substructure or inbreeding within populations was low. The overall null allele frequencies in loci K1039 and K1040 were higher than that in the low-frequency zone (see Dakin and AviseHE = 0.841 − 0.921), whereas the di- and tri-nucleotide loci showed slightly lower levels of diversity (HE = 0.677 − 0.874) and were associated with high FIS values, indicating the likely presence of null alleles  was differentiated from the other populations. Furthermore, both the BEAST divergence and DIYABC analyses indicate that the most likely evolutionary scenario consists of northward divergence events originating from a southernmost population [GY].In general, K. koreana (π = 0.00011–0.00237) are relatively lower than those of other plethodontid species, e.g., European Hydromantes species (π = 0.003–0.037)84 and Gyrinophilus porphyriticus (π = 0.031)85; and East Asian salamander species, e.g., Pachyhynobius shangchengensis (π = 0.0345)86 and Hynobius quelpaertensis (π = 0.0174–0.0214)87. However, the frequency of heterozygotes in the microsatellite data (HO = 0.449–0.744) suggests that K. koreana is more genetically diverse than other plethodontid species, e.g., Plethodon cinereus (HO = 0.189–0.420)88; and other Northeast Asian salamanders, e.g., Japanese Onychodactylus species (HO = 0.28–0.61)89. Even at the population level, mitochondrial and microsatellite data show different patterns of genetic diversity, although differences in sample sizes should be taken into account. For example, populations located in the Taebaek Mountain range  showed the lowest levels of microsatellite diversity, while the mitochondrial diversity of these populations was slightly higher than those of populations [BE] and [HC], which had shallow levels of genetic differentiation.The range of values of mitochondrial diversity of Overall, the results of genetic structure at the population-level were congruent for mitochondrial DNA and microsatellite data. The spatial location of the populations correlated well with the genetic distance between populations using both genetic markers. Considering that this species does not actively move long distances and tends to stay in a limited habitat, it is unlikely that gene flow over long distances occurs. However, results from both mitochondrial and microsatellite loci, suggest strong gene flow has occurred between populations [PC], [JS] and [SC]. This is probably because populations occupying a complex, continuous mountain terrain have access to a shady, humid environment that allows for the relatively active movement of individuals.93.An incongruence between the population structures results based on the two genetic markers  should be noted. Microsatellite analysis via Structure and PCoA clustered together populations [DJ + GJ] and [HC], while [HC] was relatively well separated from the other populations based on mitochondrial analyses (the haplotype network and phylogenetic trees). In the mitochondrial results, [GJ] was relatively well separated from [DJ]; yet one haplotype of [GJ] grouped with the [DJ] haplotypes. However, these two genetic markers exhibit different modes of inheritance and act on different evolutionary time scales, thus it is not uncommon to observe such incongruences, and many theories and hypotheses provide plausible explanations for such findings94. Fluctuation by genetic drift is likely to occur in mitochondrial data, which provided smaller estimates of effective population size. Thus genetic drift may have caused the differences in the patterns of diversity and structure between the two markers. Historical demographic analyses based on both of the markers used in this study was unable to reject the null hypothesis (a constant population size) and additionally indicated small population sizes.Microsatellites and mitochondrial DNA provided different estimates in the effective population size, a finding that should be noted considering that this species is endangered95. Later, the retreating ice sheets allowed many animals to recolonize northward. However, if the environments in the southern refugium contain sufficient resources, populations may stay in the refugium and/or adapt to the surrounding areas, rather than recolonize their original habitats. Gómez and Lunt4 proposed that within a big refugium composed of complex mountain ranges, multiple small refugia could form. The idea of small refugia existing within a big refugium has been proposed in many studies98, including empirical studies on plethodontids100 and other East Asian animals105. This scenario also provides a reasonable interpretation of our data, i.e., genetically distinct K. koreana populations exist in small refugia that are distributed in or around the mountainous terrain of the Korean Peninsula, which in total may be considered one big refugium.During the glacial advances of the Pliocene and the glacial cycles of the Pleistocene, animal species in the Northern Hemisphere were restricted to a southern refugiumK. koreana crossed from western North America to East Asia approximately 65 Ma22. Since K. koreana is confined to the Korean Peninsula, we hypothesize that the current populations are the surviving relics of the species, and the present-day population genetic structure is the result of a relatively recent northward expansion from a southernmost population. With a few exceptions, the results of Structure, PCoA and haplotype network analyses indicate that the population structure of this species was formed in a unidirectional fashion that matches the terrain of the Korean Peninsula's mountain range. The BEAST divergence tree and the most probable DIYABC evolutionary scenario from mitochondrial and microsatellite data, respectively, are both consistent in their support for a historical northward dispersal and divergence from the southernmost population [GY]. Based on mitochondrial data, most K. koreana populations diverged approximately after 1 Ma; and the pattern of isolation by distance from genetically more differentiated southern populations [GY], [HC], [JE] and [JA] further support this idea. Taken overall, these data suggest that K. koreana populations that survived in the southern part of the peninsula throughout the Pleistocene glaciation migrated northward and most recently recolonized favorable habitats along the complex mountain ranges. To evaluate this hypothesis, future work should be done to locate additional populations in the northern part of the Korean Peninsula , and if there are, determine if they exhibit the same evolutionary pattern. Additionally, one outlier that needs further investigation is the divergence between [GY] and all the other populations, estimated to have occurred approximately 2.3 Ma  is important in conserving its current population genetic diversityKarsenia koreana as a species of "Least Concern,"23 mostly because it is widespread on the Korean Peninsula. However, our data suggest that historical gene flow between the populations was low, isolating populations and increasing the influence of genetic drift. Therefore, although this species is widespread, the average effective population size is very small. Conserving this species requires special conservation strategies that take into account the preservation of all seven MUs.Presently, the IUCN red list designates Supplementary Information