Pangasius krempfi is a critically important anadromous catfish in the Mekong River, and its migration pathways and genetic structure have attracted much interest. To investigate, we quantified the genetic diversity of this species using the control region (D‐loop) and Cytochrome b (Cytb) of the mitochondrial genome. Fish were sampled (n = 91) along the Mekong tributaries from upstream to estuaries and coastal areas in the Mekong Delta and compared to three samples from Pakse (Laos). The D‐loop haplotype (0.941 ± 0.014) and nucleotide diversity (0.0083 ± 0.0005) were high in all populations, but that of Cytb was low . No genetic difference was detected between populations, indicating strong gene flow and confirming a long migration distance for this species. Pangasius krempfi was not genetically structured according to geographical populations but was delineated into three haplogroups, suggesting multiple genetic lineages. The presence of haplogroups in each sampling location implies that migration downstream is random but parallel when the fish enter two river tributaries bifurcating from the main Mekong River. Individuals can also migrate along the coast, far from the estuaries, suggesting a longer migration path than previously reported, which is crucial for maintaining diverse genetic origin and migration pathways for P. krempfi.Population genetic structure of migratory fishes can reflect ecological and evolutionary processes.  b to quantify the genetic diversity and to elucidate historical origins and migratory patterns of Pangasius krempfi. Fish were sampled along the Mekong tributaries and coastal areas in the Mekong Delta (Vietnam) and referenced to samples in Pakse (Laos). The results indicate moderate levels of genetic diversity, confirm long migration distances, and suggest multiple historical origins of the species inferred from their delineation into three haplogroups.We used the control region and cytochrome  Howevers Baird, . Such a b (Cytb) have been commonly used to study intraspecific genetic diversity in fish  markers were utilized to test genetic differentiation between populations from two estuaries of the Tien and Hau Rivers (the main Mekong tributaries in the Mekong Delta of Viet Nam). The differentiation between the two populations suggested that they were from separate spawning groups  and protein‐coding gene Cytochrome b, for estimating the genetic diversity of P. krempfi. This approach was used to test a prediction of genetic divergence among migrating populations for this species and provide genetic evidence of its migration pathway, especially downstream, in the Mekong Delta. This information has important implications for the management of this vulnerable species.In this study, we used two mtDNA loci, D‐loop and Cyt22.1All of the fish samples utilized in this investigation were obtained from fishermen or market vendors. The fish were dead at the time of sampling; therefore, no ethical approval was required.2.2A total of 91 fish samples Table . Specifi2.3b and D‐loop genes. Cytochrome b was amplified using a universal primer pair L15803/H16461 . Extracted DNA was amplified for mitochondrial Cyt2.4b were aligned using the ClustalW function in MEGA 7 , edited, and trimmed before further analyses. The fitting nucleotide substitution models that describe the substitution patterns were tested using the statistical model of maximum likelihood, implemented in MEGA 7. Based on the lowest Bayesian information criterion (BIC) scores  were reported. Additionally, DnaSP 5.0 . One sample of a sister species Pangasius mekongensis Gustiano, Teugels & Pouyaud, 2003 (GenBank accession number for COI: KT289880) was used as an outgroup in the phylogenetic trees of P. krempfi. Data for D‐loop and Cytb were initially analyzed separately, followed by analysis of the concatenated sequences  had 36 segregating sites, including 5 singleton variable sites and 31 parsimony informative sites. The Cytb segment, with the length of 652 bp, had 5 variable sites (2 singleton and 3 parsimony sites). The D‐loop nucleotide diversity of all samples (0.0083 ± 0.0005) was greater than (13.2‐fold) the Cytb‐based nucleotide diversity (0.00063 ± 0.00011). The three samples in Laos were composed of two D‐loop haplotypes and three Cytb haplotypes  of b. ST and CM had the highest nucleotide diversity, followed by AG, while the BT and TV populations had the lowest nucleotide diversity. The pattern of haplotype diversity across populations was slightly different between D‐loop and Cytb data. The D‐loop haplotype diversity values were high in four populations (excepting AG). However, values based on Cytb were lowest in the BT and TV populations. The results of genetic diversity based on the concatenated sequences were highly correlated with the D‐loop data  for D‐loop and higher for Cytb . AMOVA analyses show that genetic variation is mainly contributed from within populations, 99% for D‐loop and 94% for Cytb .Among the 32 D‐loop haplotypes, 14 (43.8%) were shared in at least two populations. Hap‐2 was the most common in the MD populations with a sequence frequency of 19.1%. The ST population had the highest number of unique haplotypes (9/15 D‐loop haplotypes), followed by TV (4/12 D‐loop haplotypes). The lowest numbers were found in AG (1/7 D‐loop haplotypes). Despite the high proportion of population‐specific haplotypes, the phylogenetic relationship of the fish was not structured by population but by three groups of haplotypes (haplogroups) Figure  was 1.63b haplotypes were shared by all the MD populations . The other five haplotypes differed from the dominant H_2 by one nucleotide and from each other by 2 nucleotides.Two (out of 6) Cyts Figure , of whicb yielded 37 haplotypes, which were also segregated into three haplogroups (data not shown), similar patterns to D‐loop haplotypes network in Figure The concatenated sequences combining D‐loop and Cyt3.4D values ranged from negative −0.543 (CM) to positive 0.974 (ST), and the range of Fu's Fs from −3.553 (BT) to 1.252 (AG). None of these numbers, nor the sum of squared deviation (SSD) or the raggedness index, are significant (p > .05), showing that there is no evidence of demographic expansion in either geographic population. The statistical tests based on Cytb showed similar results, except for the TV population with significant negative Fu's Fs .Neutrality tests Table  for popuD  and Fs . Haplogroups 1 and 3 had a unimodal distribution of pairwise nucleotide differences between individuals and no significant difference between the observed and expected data. Haplogroup 2 had a flattened distribution  was low in both haplotype (Hd < 0.50) and nucleotide diversity (π < 0.005) for Cytb, high in both for the D‐loop , with high Hd and moderate π for the concatenated sequences , two populations in Thailand and Cambodia had D‐loop haplotype diversity (Hd: 0.89 and 0.79) and nucleotide diversity  . Two migratory catfish, Pseudoplatystoma corruscans and Pseudoplatystoma reticulatum, also had similar levels of D‐loop Hd  and π (0.007) to those of P. krempfi; however, Pseudoplatystoma spp. populations were found to be more abundant. Other catfish species had lower genetic diversity than P. krempfi, such as the threatened freshwater catfish Tandanus tandanus in Australia with a D‐loop Hd = 0.672 and π = 0.006  between Laos and Vietnamese populations (D‐loop and Cytb) suggests a long migration distance for the species with a projected longest path (based on samples collected in the present study) from Paske (Laos) to Ca Mau (Vietnam) of approximately 1070 km. This genetic evidence is consistent with findings based on isotope analysis and microchemical signals of the otolith, which showed that P. krempfi can migrate at least 720 km , about 330 kilometers from the sea, where the river splits into two  to the Tien River's other two populations (BT and TV). This result is consistent with a previous study using ISSR markers, which found a low genetic structure between the two fish groups in Tien and Hau estuaries  of Cytb, while haplogroups 1 and 3 shared the same haplotype (H_2) of Cytb. The three haplogroups are distinct and differ from the others with high FST values . In addition, genetic distance between haplogroups was much higher (1.63‐fold) than that between sampling populations. These results suggest multiple genetic lineages of the species. Because of the small sample sizes from some locations, it is possible that the three haplogroups would become less differentiated as more individuals were added. However, the three distinct D‐loop haplogroups were observed in each of all downstream sampling populations  constructed based on the D‐loop show that s Figure . Concates Figure , in eachs Figure , each yes Figure  or in sis Figure . These aD and Fs . However, haplogroups 1 and 3 had higher numbers of haplotypes Figure  and sequFs Table , indicatFs Table  reportedFs Table , while mFs Table . The exiFs Table . Other f4.3b  based on Cytb across populations , estimated from D‐loop and Cytb, was positively correlated. Page and Hughes , except for D‐loop vs. ATP in genera Melanotaenia  and Retropinna . Like the above studies, positive relationships between D‐loop and Cytb were found in estimates for all genetic parameters of P. krempfi. These concordant outputs from D‐loop and Cytb analyses strengthen our findings.To date, few studies have focused on comparing genetic distance estimates from D‐loop and Cytd Hughes  comparedP. krempfi has moderate‐to‐high levels of genetic diversity. Low genetic differences and haplotype sharing across populations confirm a long migration pathway from the upstream Mekong River in Laos to estuaries and coastal areas in the Mekong Delta. Three high‐divergence haplogroups suggest multiple genetic lineages for this species with variable historical demography.In conclusion, P. krempfi. Biasness in mtDNA evolution could also occur. Thus, it would be prudent to include other unlinked genetic markers, such as microsatellite, single‐nucleotide polymorphism (SNP), and restriction site‐associated DNA (RAD) sequencing in future studies.The findings from the current study can be tested in a further work with more samples and more upstream sampling locations along the Mekong River, especially between Vietnam and Laos. In addition, mtDNA sequence variation alone may not represent the precise or comprehensive evolutionary history of Thuy‐Yen Duong: Conceptualization ; data curation ; formal analysis ; funding acquisition ; investigation ; methodology ; project administration ; writing – original draft ; writing – review and editing . Ngoc‐Tran Thi Nguyen: Data curation ; formal analysis ; investigation ; writing – original draft ; writing – review and editing . Dac Dinh Tran: Conceptualization ; investigation ; methodology ; writing – review and editing . Thanh Hoa Le: Conceptualization ; methodology ; writing – review and editing . Siti Azizah Mohd Nor: Conceptualization ; methodology ; writing – original draft ; writing – review and editing .The authors declare no conflicts of interest.Appendix S1–S2.Click here for additional data file.


Rhinogobius candidianus is a freshwater goby distributed in north, northwest, west, and south Taiwan, but this species has been introduced to east Taiwan and became dominant. To investigate its native population genetic diversity and structure and evaluate the sources and diversity of translocated populations, the mitochondrial DNA control region and cytochrome b gene (1981 bp) from 220 specimens were analyzed. These results indicated that (1) the east populations originated from two sources in west Taiwan; (2) translocated populations exist in east Taiwan and south Taiwan; (3) many populations have likely been moved secondarily by human intervention; (4) the effective size of the populations had declined greatly; (5) within the native populations, the ancestral populations colonized Taiwan during the land bridge phase in the Pleistocene through north Taiwan; (6) the landform changes in Taiwan shaped the population structure; and (7) the landforms of the coastline during glaciation also shaped the native range. The low‐level genetic diversity, high population differentiation, and population decline greatly suggest the need for resource management and conservation interventions. Four clades (α–δ) should be managed as four distinct evolutionarily significant units, while the translocated populations should be managed as separate management units. Moreover, the translocated populations in east Taiwan should be evaluated and monitored carefully. The phylogeography of Rhinogobius candidianus in Taiwan Island is uncertain. This study provides the evidence to confirm the populations in east Taiwan and Miaoli Plateau as translocation populations, and some specimens in native populations from secondarily moved by human intervention. Most species are primarily freshwater fishes, and very few species are amphidromous. In the Catalog of Fishes  Taiwan, but Leander et al.  the demography and genetic diversity of native R. candidianus, and (3) the genetic structure and colonization history of native R. candidianus in Taiwan. To achieve the above aims, the genetic variability was analyzed using mitochondrial DNA (mtDNA) cytochrome b gene (cyt b), and control region (CR or d‐loop). The regions of the mtDNA are often analyzed in studies of animal phylogeography  the native, translocated, and released populations of 2The care and use of experimental animals complied with Taiwan's animal welfare laws, the Taiwan Council guidelines and policies as approved by MOST 106‐2611‐M‐291‐007. Taiwan's government does not require any license to work with dead animals from fisheries. All methods and the handling of fish were performed and approved by the National Museum of Marine Biology and Aquarium.2.1R. candidianus were collected from 21 localities across Taiwan (Table b gene and CR region were amplified by polymerase chain reaction (PCR) using primers from Xiao et al.  by running 106 generations. The molecular clock was calibrated using a divergence rate of 1.33% per million years for the concatenated data set    was employed to determine statistical support for ancestral range reconstructions  and the first 10% of samples for each chain were discarded as burn‐in. We used the same setting for two independent runs to check for convergence with 3 × 107 and sampling every 1 × 103 generations. Plots for each analysis were drawn using Tracer.The past demographic expansions were examined using three different approaches. First, Tajima's  Tajima,  and Fu's, Fs Fu,  tests weThe Approximate Bayesian Computation (ABC) framework was used to determine the population history with the software DIYABC ver. 2.0  and 840 bp of the CR ] from 220 specimens were analyzed. In the cyt b data set, a total of 55 haplotypes were obtained  of mtDNA sequences . The TMRCA values of the four clades . This suggested a significant relationship between phylogeny and geography. The overall FST was 0.840. The average pairwise FST within north, northwest, west, and southwest regions was 0.634, 0.415, 0.538, and 0.637, respectively, and the pairwise FST among these four regions was 0.853, with a range from 0.794 to 0.883 , revealed similar results , northwest (clade β), west (clade γ), and southwest (clade δ) Taiwan, respectively. The highest posterior probability was found for the North scenario . Four population history scenarios with the DIYABC program were proposed. The ancestral populations of colonized north . However, Leander et al.  and did not find R. candidianus in Tzengwen River (TW). However, the population TW displayed a higher number of private haplotypes relative to the other populations, and an interior position in the network  Taiwan , but this population did not belong to clades β and γ and it was closer to population TW  to 0.948 (WS) (data not shown). Population HL was likely one source of the translocated populations in east Taiwan considering all haplotypes of population HL were private , agreeing within previous observations , Caridina pseudodenticulata (Decapoda), Pararasbora moltrechti (Cypriniformes), and R. rubromaculatus; and some species are only distributed east of the Central Range, for example, R. delicatus, and Hemimyzon taitungensis. The present study revealed that the native R. candidianus was distributed west of the Central Range  uplifted the longitudinal Central Range to nearly 4000 m at 2 mya Teng, . The dis Figures  and 5. Ts Figure .R. candidianus colonized Taiwan through north Taiwan, and then southward to west and southwest Taiwan in 0.94–0.85 mya  diverged . Chang et al.  and translocated populations in east Taiwan   Figure , Table 3) Figure .δ, the analyses of BSP displayed that the results in the two data sets, including and excluding the translocated populations , revealed the similar effective population sizes  is a released population, its population history needs to be tested further. The effective population size of R. candidianus declined greatly. The population differentiations were shaped by the complex geological history of Taiwan island. These results could be useful for the evaluation of the resource management and conservation of R. candidianus. Besides, our study considered that translocated populations in east Taiwan need to be carefully evaluated and monitored. It is necessary to make an evaluation about whether these introduced populations damaged other native species. In future studies, we need more samples of other Rhinogobius species worldwide, and more molecular characters to examine the origin of R. candidianus.The phylogeography of Bin Kang: Conceptualization ; software ; writing – original draft . Kui‐Ching Hsu: Conceptualization ; methodology ; software ; writing – original draft . Jui‐Hsien Wu: Investigation ; resources ; validation . Yuh‐Wen Chiu: Investigation ; methodology ; resources . Hung‐Du Lin: Conceptualization ; software ; writing – review and editing . Yu‐Min Ju: Conceptualization ; funding acquisition ; software ; writing – review and editing .The authors have no conflicts of interest to declare.https://www.ncbi.nlm. nih.gov/) under the accession numbers OK375877–OK375931, and OK375932–OK376009.This article has earned Open Data, Open Materials and Preregistered Research Design badges. Data, materials and the preregistered design and analysis plan are available at GenBank (


Aedes aegypti is thought to be the principal vector for arboviral diseases such as dengue, yellow fever, zika, chikungunya, and others. Aedes aegypti, which is believed to have its origins in Africa, is known to have two subspecies or forms that are differentiated from one another in terms of behavior, transmitting power, and dispersal. The study of genetic structure and variations among different forms/subspecies of disease vectors sheds important light on their biology, behavior, genetic mixing, and capacity to spread disease. To better understand the genetic polymorphism of the two forms of Aedes aegypti, this study looked at various populations of the mosquito in different locations in Sudan. The findings revealed that the genetic variance between the two subspecies was insignificant, and they shared some components in the gene/marker we used in the study. This information will be required to improve the control strategies against the Aedes aegypti vector in the area.Arthropod-borne viruses (arboviruses) place a heavy social and economic burden on society by infecting millions of people and causing widespread animal and human sickness. These viruses are often transmitted to their vertebrate hosts by arthropod vectors. The mosquito Aedes aegypti subspecies (Aedes aegypti aegypti (Aaa) and Aedes aegypti formosus (Aaf)) from Sudan using the NADH dehydrogenase subunit 4 (ND4) mitochondrial gene marker. Nineteen distinct haplotypes of the ND4 were identified in female Aedes aegypti mosquitoes from the study sites. The phylogenetic relationship of the 19 ND4 haplotypes was demonstrated in a median-joining haplotype network tree with Aaa and Aaf populations found to share three haplotypes. The genetic variance  was estimated and found to range from 0.000 to 0.811. Isolation by distance test revealed that geographical distance was correlated to genetic variation  = 0.43). The Polar maximum likelihood tree showed the phylogenetic relationship of 91 female Aaa and Aaf from the study sites, with most of the Aaf haplotypes clustered in one group while most of the Aaa haplotypes gathered in another group, but there was an admixture of the subspecies in both clusters, especially the Aaa cluster. The Spatial Analysis of Molecular Variance (SAMOVA) test revealed that the eight populations clustered into two phylogeographic groups/clusters of the two subspecies populations. The 2 Aedes aegypti subspecies seemed not to be totally separated geographically with gene flow among the populations.This study investigated the genetic differences between  Arboviral infections have been identified as a global health issue, including life-threatening diseases such as dengue fever, yellow fever, zika, chikungunya, and others. Dengue viruses infect an estimated 400 million and kill 10,000–20,000 people per year . Aedes aegypti has played a principal role in arboviral disease outbreaks in Sudan since the 1950s, and it is widely distributed in all arboviral disease locations in the country [Aedes aegypti formosus (Aaf), has only been documented from Sub-Saharan Africa [Aedes aegypti aegypti (Aaa), which is lighter in color, is distributed in tropical and subtropical countries [ country . It is bn Africa , whereasountries . Aaa distributed in eastern and central Sudan east of the Nile River and Aaf distributed in western Sudan and west of the Nile River [CO1), and their geographical distribution might be one of the reasons for the genetic separation.Our recent study revealed the presence of both forms in Sudan, with le River . The stuAaa) having a higher vector competence in transmitting both yellow fever and dengue viruses than the wild form (Aaf) [Ae. aegypti populations [Ae. aegypti populations across the globe [The two subspecies/forms are known to have varied vector competence in spreading arboviruses, with the domestic form (rm (Aaf) ,10 The vulations ,12,13. Mhe globe ,15,16.CO1) gene was found to be an effective genetic marker for genetic differentiation studies. The mitochondrial NADH dehydrogenase subunit 4 (ND4) gene marker in Ae. aegypti has also been widely used for genetic variation studies around the world, including Brazil [ND4 to study the genetic variation between sylvan and domestic Ae. aegypti populations in Cameron and discovered that the two populations are structured by limited gene flow between them.In a study by Ashfaq et al. , the mitg Brazil ,19, Perug Brazil  and Bolig Brazil . Paupy eg Brazil  used mtDAe. aegypti using CO1 mitochondrial marker [ND4.Recently, our research group studied the subspecies diversity of l marker . HoweverAe. aegypti subspecies are found in outbreak locations in Sudan, implying that they are involved in disease outbreaks. In this work, we studied the genetic differences among the Ae. aegypti forms Aaa and Aaf in Sudan using ND4 mitochondrial marker.The two Ae. aegypti and outbreaks of arboviral diseases as outlined in Abuelmaali et al. [The current study was conducted in eight study sites spread across Sudan. Selection of the sites was based on the prevalence of i et al. . The sitAedes eggs, larvae and pupae were sampled from different breeding habitats  in the study area from 2014 to 2017. At each site, there were five sampling points (inter-point distance of at least 1 km) to avoid sibling bias in the sample collection. The samples were transferred to the insectarium for sorting and morphological identification [fication  (Table 1fication  based onGenomic DNA (gDNA) of each female mosquito was extracted  using DNeasy Blood and Tissue Extraction System  according to the producer’s procedures. Nanodrop Quawell UV spectrophotometer Q3000  was used to assess the quality of the gDNA. The extracted gDNA was preserved at −20 °C prior to use in the amplification process.ND4) was utilized to investigate genetic variations among the Aedes aegypti subspecies (ND4-F) 5′-ATTGCCTAAGGCTCATGTAG-3′ and the reverse primer (ND4-R) 5′-TCGGCTTCCTAGTCGTTCAT-3′ were used to amplify a 400 bp partial ND4 gene fragment as described by Da Costa-da-Silva et al. [2, 0.5 μL of 25 mM dNTP, 0.3 µM of each of the primers ND4-F and ND4-R, 0.25 μL of Taq polymerase, and 1 μL (>50 ng) of sample DNA. Thermal cycling conditions were as follows: a 2-min denaturation stage at 94 °C, followed by 35 cycles at 94 °C for 1 min, 56 °C for 30 s, 72 °C for 1 min and a 10 min final extension at 72 °C [The mitochondrial marker NADH dehydrogenase subunit 4  stained with Red Safe dye  for one hour and visualized using the UV light gel documentation system. The amplified products were purified using the QIAquick PCR purification kit  according to the manufacturer’s procedure before being sent to NHK Bioscience Solutions Sdn. Bhd  for DNA Sanger sequencing on an ABI3730XL DNA Analyzer.The sequences were aligned using ClustalW in the Molecular Evolutionary Genetics Analysis software (MEGA) v7.0  and usedAedes aegypti subspecies for the ND4 mitochondrial gene [https://www.ncbi.nlm.nih.gov/nuccore/OM321307 (accessed on 22 October 2022)DNAsp v5.10.1 software was used to identify distinct haplotypes for the ial gene  and wereh), number of polymorphic sites (S), haplotype diversity (Hd), and nucleotide diversity (π) indices were assessed in all populations using Arlequin v3.5 [STF) and their significance between the various populations were calculated. The geographical inter-site distance was determined using Google Earth TM’s ruler feature.The haplotypes number (uin v3.5 . The Anauin v3.5 . The paiSTF to generate a linear regression relationship.Computation of the Genetic isolation by distance (IBD) with the Mantel test was used to determine the inter-site correlation between genetic variations and geographical distance in Arlequin v3.5 . PairwisA polar unrooted maximum-likelihood phylogenetic tree was generated in IQ-TREE1.6.9  and consThe phylogenetic relationship of the nineteen haplotypes was further examined using Neighbor-Joining method  performeCT (inter-group diversity), which was maximum when the groups were two. Accordingly, we inferred that two-group clustering is the best grouping (best homogeneity among groups). Following that, the results of the SAMOVA were used for the Analyses of Molecular Variance (AMOVA) using Arlequin v3.5. Arlequin v3.5 was also used to detect population growth and deviation from neutrality using Tajima’s D and Fu’s F statistics [SAMOVA  v2.0 was used to understand the genetic barriers on population groups and their structure . It was atistics .Aedes aegypti. Subspecies identification revealed the distribution of the samples among the 2 Aedes aegypti subspecies, as indicated in A hundred samples from each site were morphologically identified as ND4 amplified gene fragment resulted in a 172 bp sequence which was then subjected to haplotype analysis.Cleaning and trimming the sequenced samples of the 400 bp ND4 mitochondrial gene were detected in this study. The haplotype number and their diversity are described in Overall, 19 distinct haplotypes of the The number of haplotypes varied from eight in Tokar, five in Kadugli and Kassala, four in Nyala and Al Junaynah, with the least being two in Port Sudan and Barakat, and one in Al Fasher .Aaa subspecies had a higher number of polymorphic sites as well as nucleotide diversity compared to Aaf . The haplotype diversity was different and inconsistent within Aaa and Aaf populations, the highest in the Tokar site (0.956), followed by Nyala (0.75) and the lowest also among Aaf populations (0.00 in Al Fasher) which had only one haplotype in its population followed by Barakat Aaa population (0.2). In Aaa populations, the haplotype diversity was moderate to high in Kassala (0.539) and relatively low in Port Sudan (0.286) (The  (0.286) .ND4 haplotypes was demonstrated in a median-joining haplotype network tree , in addition to Hap 11, which appeared in Port Sudan, Tokar and Kassala and was found in 19.5% of all the Aaa samples.Hap 1 showed higher frequency and included mosquitoes from all Aaa and Aaf populations shared three haplotypes  ranged from 0.000 to 0.811 , as shown in Aaa) and Nyala (Aaf) had no genetic differences between them, with a pairwise STF value of 0.000 .The to 0.811 . Pairwisof 0.000 . In contp = 0.02) relationship between genetic variation and geographical distance (correlation coefficient = 0.43)  and , respectively. Some populations also had high STF values despite being geographically closer, such as Port Sudan and Barakat  and Port Sudan and Kassala   . Convers 489 km) .Aedes aegypti ND4 from the study sites clustered in two groups with a mixture of the two subspecies populations in the two groups . The neighbor-joining phylogenetic tree was bifurcated to yield two clades with an admixture of the subspecies haplotypes  for the o groups .SF results were recorded in Port Sudan, Kassala, Barakat, Kadugli and Nyala, indicating a recent population bottleneck or over-dominant selection. The Al Fasher site had no value because there was only one haplotype present, whereas Tokar and Al Junaynah had negative values, indicating a recent population expansion or genetic hitchhiking. . On the other hand, variations between some Aaa populations were very high . This finding contrasts our previous study, which indicated high genetic variation between most of the subspecies’ populations, although, in both studies, the Tokar and Barakat Aaa populations showed the least variations with Aaf populations. This might be attributed to their geographical distance (closer) to the western parts of the country where the Aaf populations are distributed. Moreover, the high STF values between many Aaf and Aaa populations, such as at the Port Sudan and Al Fasher sites (STF = 0.811), may be attributed to their geographical isolation (1424 km between them). The significant correlation between the geographical distance and the genetic variation revealed in isolation by distance tests in both studies is probably one of the main reasons for the high genetic variations between populations.The findings of this study, using the Ae. aegypti subspecies seemed not to be totally separated (structured) in the phylogenetic tree, and the results showed gene flow among their populations. The two subspecies are clustered into two groups on the polar phylogenetic tree, with Aaa samples from Kassala mixing with the Aaf populations cluster and many samples of Aaf populations clustered with the Aaa cluster, as shown in Generally, CO1 mitochondrial gene [SAMOVA analysis revealed that the percentage of variation between the two subspecies groups was only 26.64% which is lower than the percentage variation (39.2%) in our last study using the ial gene . This coAe. aegypti populations found that the two subspecies are genetically distinct. Hence the findings of our study indicate that there is probably a recent gene flow between the two subspecies as Aaf encroached into human territories where Aaa already exists. Powell et al. [In accordance with Abuelmaali et al. , the popl et al.  determinAaf showed relatively lower genetic variations compared to Aaa populations, which agreed with the findings of Brown et al. [Aaf population collection sites were generally drier than these authors’ sites. The severe aridity, when combined with the huge physical distances between our study locations, inhibits migration and gene exchange between the populations.It is worth mentioning that n et al.  and Powen et al. . Some ecAe. aegypti populations varied by location, as AMOVA revealed a percentage of 48.83% for population variations. The Aaa population in the coastal city of Port Sudan had the lowest variation in the CO1 gene, with five haplotypes reported at the site [CO1 mtDNA gene. The persistent high humidity by the Red Sea all year round lessens the effect of aridity on the mosquito populations and could explain the decreased genetic variation at Port Sudan. Despite belonging to the same subspecies, Port Sudan (Aaa) and Barakat (Aaa) displayed genetic differentiation from one another, according to examinations of the genetic differentiation  between sites. Additionally, there were no genetic differences between the Tokar Aaa population and some Aaf populations. It may be possible to split individuals/populations within a group into a smaller group or subpopulation in light of the high levels of diversity among individuals and populations within groupings.In this study, the genetic variation in the the site  reportedCO1 [The haplotype numbers from this study were different from our previous study using CO1 . Al FashThe Tajima D and Fu’s F statistics predicted a stronger natural selection impact at some sites across the country, such as the Tokar site, which showed a positive Tajima value.CO1 mitochondrial gene [Finally, this study reveals uncertainties about the distinctiveness of the genetic structure of the two subspecies, contrary to our previous study using the ial gene , which rAedes aegypti-borne diseases. An understanding of the ecological factors that influence the distribution and abundance of the subspecies, as well as control measures for the viruses transmitted by them, are also worth investigating.In Sudan and other African Sahelian countries, more research is needed to decipher the role of the subspecies in the spread of


Hemileia vastatrix, to estimate the possible original source(s) and subsequent migration pathways of wind-borne and human-aided spores in three main coffee production regions  in Vietnam. In southern Vietnam , Coffea canephora covers the majority area, while Catimor lines of C. arabica accounts for 95% of the coffee plantations in northwestern Vietnam. Field surveys conducted at eighty-five plantations, show coffee leaf samples infected by the rust fungus across forty-one plantations. Catimor varieties exhibited high levels of susceptibility with severe rust symptoms, while robusta varieties had varying degrees of susceptibility. We analyzed 863−869 base pairs of internal transcribed spacer (ITS) region from 83 samples ; and fifty-two haplotypes consisting of 123 polymorphic sites were detected. Although the analysis of molecular variance (AMOVA) indicates significant genetic differentiation in the H. vastatrix populations in Vietnam, there was no clear genetic structure with respect to the three geographic areas surveyed. Based on the haplotype network, NeighborNet analysis, and geographical distribution patterns of the haplotypes, five haplotypes were identified as early established, from which most other haplotypes in Vietnam were derived. The early established haplotypes were found in the highest frequency in Northwest Vietnam. This finding corresponds to the earliest record of CLR in Vietnam. The phylogenetic network analysis also illustrated that H. vastatrix had expanded from the northwest to southern Vietnam. Pairwise genetic distance analysis and the geophylogenetic tree also suggests that CLR was first established in the Northwest. In addition, some scattered individuals on the principal coordinate analysis (PCoA) diagram and several separated haplotypes in the phylogenetic networks indicated that other branches of CLR in Vietnam were initiated in the Central Highlands. Hemileia vastatrix from these branches have been spreading in southern Vietnam.This research focused on the incidence and population genetics of coffee leaf rust (CLR) fungus,  Hemileia (Zaghouaniaceae P. Syd. & Syd.) (Coffea (Rubiaceae) produce coffee beans—the most valuable and traded tropical agricultural product, which is severely affected by the rust disease . They are obligate parasites of vascular plants and cause rust diseases in several important crops worldwide . Managem & Syd.)  is chara & Syd.)  and comp disease . Even if disease . TherefoCoffea arabica and C. canephora, which was resistant to all races of the coffee rust fungus, Hemileia vastatrix, in the 1950s. The hybrids Catimor and Sachimor have also been considered resistant to H. vastatrix  investigate the occurrence of CLR in the main coffee-producing regions in Vietnam, (ii) evaluate the current genetic diversity and population structure of the coffee rust fungus based on sequencing of internal transcribed spacer (ITS) region, and (iii) estimate the geographic region where H. vastatrix first established as well as the migration direction of CLR between main coffee-growing areas in Vietnam.ionaries . Some dentations . Severally 1900s . In the astatrix . After WH. vastatrix. Ten coffee leaves with orange-colored rust sori were collected from three trees at each collection site, packed in a plastic bag, and referred to as one sample. Photographs of the rust-infected leaves were also taken, and the severity of the coffee leaf rust estimated using the method of Coffee species were identified based on morphology , according to the descriptions of 2, 50 mM KCl). The protocol can be summarized as follows: A coffee leaf with fully matured, seemingly clean sori on the lower surface was chosen for DNA extraction from each sample (one sample consisted of ten leaves from three different trees). Urediniospores were collected from several pustules on a single leaf and immersed in a 200 μl tube containing 30 μl buffer-1. The tubes were then vortexed and incubated at 95°C for 15 min and immediately transferred to a deep freezer (–80°C) for 10 min. Subsequently, the spore suspension was defrosted at room temperature (25 ± 2°C) and centrifugated at 15,000 rpm for 1 min. Finally, the supernatant was transferred to a new 200 μl tube. The nucleic acid concentration and 260/280 and 260/230 ratios were estimated using a DS-11 spectrophotometer .DNA extraction from herbarium specimens requires special methods, in which only a small amount of spores must be picked to avoid possible cross-contamination. The thermal-shock method given by ® Touch . The PCR process was as follows: initial denaturation at 95°C for 5 min, followed by 35 cycles of denaturation at 95°C for 1 min, annealing at 54°C for 30 s, and extension at 72°C for 1 min, followed by a final extension at 72°C for 10 min.The ITS region was amplified using ITS5 and ITS4 primers . A 25 μl1.The amplification was confirmed using electrophoresis. The amplified products were purified using FastGene™ Gel/PCR extraction kit  and consigned to Eurofins Genomics  for sequencing. The obtained sequences were edited and assembled using ATGC software . Finally, the sequences were aligned and compared with other sequences in the National Center for Biotechnology Information database using the BLASTn programH. vastatrix from a few Central and South American countries , and those from Portugal’s Coffee Rust Research Centre (CIFC: Centro de Investigação de Ferrugens do Cafeeiro) were downloaded from the NCBI Genbank  within each population and among different populations were calculated using GenAlEx 6.51b2 (PT)   between H. vastatrix populations. First, a map figure was generated using GeoMapApp 3.6.122 . From the 86 sequences (41 sequences from Vietnam), 123 polymorphic (segregating) sites (77 singleton variable sites and 46 parsimony informative sites) were detected. In total, 52 haplotypes (36 haplotypes from Vietnam) were identified (p < 0.05). The value of Tajima’s neutrality test (D) for the whole population of H. vastatrix was −0.19518. Although almost all populations in Vietnam had a negative value of Tajima’s D ; however, the values were not significant  and did not show any geographic patterns, except the Caldas-Chinchiná population from Colombia, which showed a much lower value (0.500) than others . When weH. vastatrix populations from the six countries  was low (STF = 0.175) but significant (p < 0.01). Only 17% of the total variation was found among populations, while 83% of the differences were among individuals within a population (PT) between the Vietnamese–Thai and Central and South American populations, and the Brazilian and Caldas-Chinchiná population (Colombia) was high  revealed that most individuals were closely gathered, while some from the Central Highlands and Southeast were distantly scattered   were included in the third group and were mainly from the Central Highlands and the Southeast of Vietnam.Analysis of the genetic structure of the whole d 30118) . Haplotyd 30118)  and Neigd 30118)  networksThe map-based phylogenetic tree highlighted the close genetic relationship of some populations in Mexico and Brazil with the Northwest (Vietnam) populations. Populations from Oaxaca, Chiapas, and Puebla (Mexico) were directly related to populations from Son La and Dien Bien (Northwest of Vietnam) . BesidesCoffea arabica cv. Catimor, HdT, and Sachimor were known to be rust-resistant  and those from Central and South American countries (Mexico and Brazil) have very close relationships. However, we cannot ascertain that the H. vastatrix population in Vietnam spread from these countries just because the first rust detection in Vietnam was in 1890, while the first confirmation of rust establishment in Brazil and Mexico was in the 1970s and 1980s, respectively . At that time, rust-infected coffee seedlings or materials from infected areas in Africa (where H. vastatrix is native) might have been carried to Vietnam by the French. However, confirming the origin of CLR in Vietnam necessitates further studies with larger rust samples from other countries, especially African countries. For these reasons, this discussion only focused on the first establishment of CLR in the three main coffee growing regions in Vietnam. Three main inferences regarding the origin and migration route of H. vastatrix can be gathered based on the present study. Firstly, because ΦPT was previously measured only based on the genetic drift  in the haplotype network and the NeighborNet . Because of this limitation, we could only discover two possible migration pathways of H. vastatrix in Vietnam. In future, we intend to conduct population genomic studies on H. vastatrix in Vietnam to reveal more information regarding the genetic structure, population demography, origins, and migration pathways of H. vastatrix in Vietnam.This study sheds new light on the genetic diversity of the CLR fungus, 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 in the article/CL collected the samples, designed and performed the experiments, and wrote the manuscript. YO, IO, YT, YY, and CL conceived and directed the study. CL, YT, IO, and YO analyzed and biologically interpreted the data. YO, YT, and YY revised and approved the final version of the manuscript. All authors contributed greatly to the present manuscript.All the specimens in this study were collected under the permission of the Vietnamese Government. In this study, all experiments were performed with the current laws of Japan.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.


Population genetic studies of North Asian ethnic groups have focused on genetic variation of sex chromosomes and mitochondria. Studies of the extensive variation available from autosomal variation have appeared infrequently. We focus on relationships among population samples using new North Asia microhaplotype data. We combined genotypes from our laboratory on 58 microhaplotypes, distributed across 18 autosomes, on 3945 individuals from 75 populations with corresponding data extracted for 26 populations from the Thousand Genomes consortium and for 22 populations from the GenomeAsia 100 K project. A total of 7107 individuals in 122 total populations are analyzed using STRUCTURE, Principal Component Analysis, and phylogenetic tree analyses. North Asia populations sampled in Mongolia include: Buryats, Mongolians, Altai Kazakhs, and Tsaatans. Available Siberians include samples of Yakut, Khanty, and Komi Zyriane. Analyses of all 122 populations confirm many known relationships and show that most populations from North Asia form a cluster distinct from all other groups. Refinement of analyses on smaller subsets of populations reinforces the distinctiveness of North Asia and shows that the North Asia cluster identifies a region that is ancestral to Native Americans. Since then microhaps have been studied by many forensic researchers with clear demonstration of their potential in such areas as ancestry inference, kinship studies, identifying individuals, detecting mixture samples from multiple individuals, and ecological studies of non-human species. Many of these areas are of great potential interest to physical anthropology. A few papers are starting to use microhaps for anthropology applications: kinship5 and ancestry9.Microhaplotypes  are defined as small genomic regions of less than ~ 300 bp with two or more variants, usually SNPs, resulting in at least three common haplotypes. They were first proposed in 2013n)10 measures the ability of MHs to infer ancestry as has been shown to be quite good for several different panels of MH loci11, rivaling the Informativeness of the standard forensic STR loci12. Pakstis et al.13 showed that minihaplotypes of 10 kb or smaller were very informative for population differentiation, i.e., ancestry inference of individuals. The same is true for the relatively few studies of microhaplotypes that have been focused on ancestry inference for populations other than those in the 1000 Genomes (1 KG) dataset14 such as15 although some panels would certainly provide relevant ancestry information16 were the analyses done. The general pattern seen in almost all studies is that major continental groups are easily differentiated. In part, this pattern is so distinctive because the sets of populations studied, such as those in the 1000 Genomes (1 KG)14, are often clustered geographically with large geographic distances between the clusters.Informativeness  Similarly, other than our genetic studies of the Tsaatan19 we have found only one study of this population20. We have combined data on samples of 75 populations  from our lab along with data from the 1000 Genomes (1 KG)14 and the GenomeAsia 100 K (GA100)21 datasets. We examined the biogeographic clustering of 122 population samples while focusing on the North Asia population samples in relation to the existing data on many Eurasian populations and populations from other continents as represented by the specific samples of each. We show that with this set of microhaplotype loci the North Asia populations do not cluster with any of the major biogeographic clusters but have unique global relationships generally unique between the Europeans to the West and the East Asians.We have accumulated microhaplotype data on recently available population samples from North Asia, including populations from Mongolia and Siberia Table . These n22. All 58 microhaps are among the 198 microhaplotypes with population frequency data in the ALFRED database. Individuals missing genotype data for > 20 (i.e. > 34.5%) of the 58 MH were omitted from the analyses presented here. The full set of microhaplotypes is defined in Supplemental Table Choice of the specific microhaplotypes was determined by maximizing the number of Kidd Lab populations to be studied so that all populations had nearly complete data for all SNPs in all microhaplotypes. Some of the data were included in previous papers19.All markers typed in the Kidd Lab used TaqMan assays obtained from Thermo Fisher. The individuals with sufficient amounts of DNA available (approximately 50 ng per reaction) were typed following manufacturer’s protocols with reaction volumes reduced to 3 μl, run in 384-well plates, and read on an AB9700HT using Applied Biosystems’ SDS (sequence detection system) software. To maximize the number of SNPs that could be typed on the small amounts of DNA available for some populations, a preamplification protocol was employed as describedWe did not exclude microhaps that showed little variation among the populations previously studied. Table 24. Phasing runs only included the individuals with genotype data for all the SNPs defining the particular microhap being analyzed. Since the decision about which individuals to include was made separately for the phasing of each microhaplotype, individuals varied in the number of haplotype genotypes present.Haplotypes were inferred using PHASE version 2.1.1The present study involved laboratory genotyping of previously collected DNA samples and then analyses of the data. The samples were anonymized before they were sent to the Yale lab for genotyping. None of the DNA samples was collected for this specific study. No human subject was directly involved in the current research.19 data on individual SNPs and some minihaplotypes for a sample of ethnic Mongolians and a sample of the Tsaatan from Northern Mongolia. We have now collected microhaplotype data on samples of six North Asian populations: the Altai Kazakhs from western Mongolia, two other populations from Mongolia , and three Siberian populations . We now have data on 58 microhaplotypes for these six North Asia populations and many other populations  data on a sample of 87 Buryats, originating in Mongolia, and on many other populations from Asia. Given our present focus on North Asia, we extracted the GenomeAsia data on Buryats for comparison with our Mongolian and Siberian samples. To provide a global context for these seven North Asia populations we included the data on the populations available in our lab along with the data extracted for these 58 microhaplotypes from 22 of the populations in the GenomeAsia project and from the 26 populations of the 1000 Genomes dataset. In total, we have included data on 122 populations  for these 58 microhaplotypes. Table The GenomeAsia 100 K25 applying the standard admixture model assuming correlated allele frequencies. The input data consisted of the microhaplotype genotypes for all individuals in the relevant populations. In the STRUCTURE analyses, individuals lacking phased genotypes for more than 20 of the 58 (i.e. > 34.5%) microhaplotypes were excluded from the input files. After censoring, the 122-population dataset included a total of 7107 individuals in the STRUCTURE analyses; 61% of the 7107 individuals have all 58 microhap genotypes present; 90% of the individuals have 52 or more genotypes. The program was run 20 times at each K level from K = 2 to K = 11 with 10,000 burn-in and 10,000 Markov Chain Monte Carlo (MCMC) iterations.We employed version 2.3.4 of the STRUCTURE softwarehttp://www.xlstat.com/en/about-us/company.html) on the matrix of haplotype allele frequencies for all 58 microhaplotype loci and the populations relevant to each analysis.For the Principal Component Analyses (PCA) we used the XLSTAT 2019 software (26 and generated a tree using the Neighbor Joining (NJ) utility that is part of the PHYLIP software package28. A NJ tree gives an approximate Least Squares fit of an additive tree structure to pairwise genetic distances. This tree was then evaluated by exact Least Squares and many possible trees were examined for their fit to the additive model using a heuristic method of successively altering the tree structure29. The Drawtree utility (version 3.69) in PHYLIP was employed to plot the postscript images of the best population trees.Phylogenetic population trees for the 74 and 15 population datasets were generated using a Least Squares solution for an additive model. We calculated tau genetic distancesAll subjects gave permission for collection of samples and for their use in general population studies of which this is one. The present study involved laboratory genotyping of previously collected DNA samples and then analyses of the data. The samples were anonymized before they were sent to the Yale lab for genotyping. None of the DNA samples was collected for this specific study. No human subject was directly involved in the current research. All samples in this study are anonymous and therefore this study, per se, is not considered human subjects research by NIH and by Yale University review committee. The various population samples studied in the Kidd laboratory since 1985 have all been collected with informed consent under a general Yale University protocol  which was also reviewed and approved by the NIGMS  and by CEPH (Center for the Study of Human Polymorphisms in Paris) as well. One third of the samples in the CEPH-HGDP (Human Genome Diversity Project.) collection came from the Kidd lab. In this report the newly collected Altai Kazakhs are the only population sample not previously included in any publication. Signed informed consent for the Altai Kazakh individuals who volunteered to give saliva samples for population studies was obtained by Dr. Ariunaa Togtokh, (cf. co-author affiliation) in Mongolia and Dr. Janet Roscoe, (cf. co-author affiliation) in Canada. The samples were collected under protocols approved by the Ethics Review Board of the Ministry of Health in Ulaanbaatar, Mongolia and by The Scarborough Hospital Research Ethics Board in Scarborough, Ontario, Canada.https://alfred.med.yale.edu) does contain the allele frequencies for 56 of the 58 microhaps for 91 of the 122 populations in this report, including some of the 1 KG populations. ALFRED is freely accessible online but has been static since 2019; thus, the frequencies for the 31 newest populations, especially those from the GenomeAsia database, are not available in ALFRED.Data for 22 populations  were extracted from the GenomeAsia 100 K database for the SNPs in these 58 microhaps Table . Data foHardy–Weinberg ratios. The observed and expected genotype counts for each of the 171 SNPs defining the microhaps studied in the 75 Kidd lab population samples were compared for goodness of fit to Hardy–Weinberg ratios via a likelihood-ratio chi-square test. The deviations from Hardy–Weinberg ratios detected at nominal thresholds (such as 5% or 1%) were those one expects to find by chance when conducting a large number of tests. A total of 11,921 out of the 12,825 theoretically possible tests (171 SNPs × 75 populations) could be carried out; when a single fixed genotype occurs for a particular SNP by population combination, there is nothing to test.30.Phasing Accuracy and Data Completeness. Genotypes were assigned with the PHASE program for individuals having SNP genotypes for all the defining SNPs of a microhap. When the probability of phasing fell below 0.98, the assignments were checked to determine whether the genotype should be omitted. In the current dataset, these follow-up checks typically involved rare and very low frequency haplotypes occurring in the Sub-Saharan African population samples and the genotypes were not omitted. For the 7107 individuals analyzed in the 122- population dataset, 3.17% of the 411,800 possible MH genotypes were missing. The missing genotype rate was similar at 3.20% for the 15-population subset and is only 1.66% for the 74- population subset. PHASE software yields a statistically accurate estimate of allele frequencies for populations and provides maximum likelihood estimates of the haplotype genotypes of individuals when each SNP is typed individuallye value is 2.72 in the dataset of 122 populations; this is equivalent to an average heterozygosity of 0.632. Thus, these 58 loci are, on average, more heterozygous than is possible for 58 di-allelic SNPs. The frequency distribution of Ae values is shown in Fig. Locus characteristics. The populations in this study show high average heterozygosity for the 58 microhaps. The average An) values, 0.215 and 0.221, respectively, differ little. The In values range from 0.055 to 0.432. Figure e and the In values for each of the 58 microhaps. Strong differentiation (In > 0.2) among the populations studied occurred across the full range of average Ae values. However, 4 of the 58 microhaps only differentiated weakly (with In < 0.10) among the 122 populations and so they were not contributing very much to population differentiation in the PCA and STRUCTURE results.The average and median informativeness . Of those, 35 had no internal negative segments and the best of them is illustrated in Fig. The pattern in these 74-population analyses for the North Asian populations was for the Komi to cluster with the other Europeans, the Khanty to show attribution to both the European and the North Asian clusters, and the remaining populations to be primarily allocated to a distinct North Asia cluster. Given these results, we have focused our additional analyses on the allele frequency variation in just a subset of 15 populations: the seven North Asian populations, the Irish and Hungarians on the European side, the two Korean samples, the Kidd Lab Japanese, and the Beijing Han on the East Asian side, and the Plains American Indians and Mexican Pima in the New World.The STRUCTURE analysis of those 15 populations Fig.  showed tThe PCA results on the subset of 15 populations Fig.  show, asIncluding the Neighbor Joining tree, 54 different exact Least Squares trees were examined for the 15 populations Fig. . Of thes36. Those relationships show a West to East cline in genetic similarity and distinction of the Siberian populations from the Europeans to the West (typified by Irish and Russians) and Asians to the East . Also, our results show, as other studies have shown, that those major East Asian populations form a very tight cluster21. Our analyses show that the major East Asian populations are, as a cluster, very distinct from the North Asia samples  showed that, using ADMIXTURE software, the Uralic speakers resembled their neighbors rather than forming a cluster unto themselves. Based on STRUCTURE our Komi sample from Western Siberia was predominantly part of the European cluster until K = 6 using the highest likelihood result for the 74 population analyses. At the higher K values the Komi remained distinct from the European populations but there was still considerable attribution to the European cluster for many individuals. The conclusion of both PCA and STRUCTURE analyses of the Komi is consistent with the larger Komi ethnic group being essentially a European population spanning the northern boundary between Europe and Asia.The North Asia population samples we have studied generally show different patterns of relationship depending on the method of analysis and set of populations considered. The one consistent result is for the Komi. The Komi sample we have studied is part of a Northwestern Siberia enclave of what is essentially a European population. Our sample of the Komi is geographically relatively close to our sample of the Northern Khanty but genetically they are proportionately much more distant. In Fig. 37 analyses the Khanty were in a different cluster than the Komi. The Khanty were somewhat intermediate between the Komi and the Yakut. Greater density of population samples studied for these autosomal markers will be necessary to integrate the Khanty into the genetic pattern of Siberian populations. A similar comment is warranted for the Altai Kazakhs. This sample clusters with the other North Asian samples using STRUCTURE  the PCA and tree analyses agree that the Buryat, Yakut, and both Mongolian samples form a clear cluster of closely related populations. For example, Kilinc et al.44 fit to the HGDP dataset45 a model of successive founder effects as modern humans spread from origins in Africa to occupy the rest of Eurasia. The result is consistent with the cline from West to East of loss of heterozygosity and increasing genetic distance correlated with distance from human origins in Africa46. As seen in, e.g., Fig. Liu et al.47 carried out whole genome sequencing on 175 ethnic Mongolians to improve genetic sampling of Northern Asia. Five of the tribal/location samples out of six groups they studied were from Inner Mongolia, China. One sample of Khalkha was from Ulaanbaatar. Their six Mongolian population samples clustered with the East Asian populations using ADMIXTURE until, at K = 9 and K = 10, they became a distinct cluster. Their maximum likelihood tree includes three of their Mongolian populations and places them at the base of the branch into East and Southeast Asia. The selection of ethnic population samples by Bai et al. is sufficiently different that detailed comparisons are not possible. To the degree comparison is possible the results are compatible with our results.Bai et al.The three different methods used in this study provide different views of the data based on different statistics with different underlying assumptions. The STRUCTURE software groups individuals to form Mendelian populations, i.e., K-clusters of individuals each of which approximates a population showing Hardy–Weinberg ratios of the genotypes. When an individual does not fit well into one of the K populations, it can be assigned partial membership in different “ancestral” populations. This can be considered admixture but could also just reflect the intermediate nature of an individual or population given the fixed number of K clusters allowed. This distinction between “admixed” and “distinct” clusters can be seen for the North Asians in Fig. We emphasize that the STRUCTURE analyses are done by individual microhap genotype profiles and our representations in the Figures have the individuals grouped by population  frequencies rather than the individual genotypes and as a result have plots of points representing the population samples. The points along the orthogonal axes represent the centroids of the individuals assigned to the population. We note that, as in STRUCTURE analyses, the specific populations included in PCA can alter the relationships shown for other populations. Thus, the relationships of the populations in the 15-population analysis Fig.  are some48. An NJ tree is an approximate additive tree, meaning that the pairwise distances between populations are apportioned so that they are additive across all the tree segments between the population pairs. The statistic approximated is a least-squares fit to the series of equations representing the tree structure29. An exact least-squares (LS) fit to a distance matrix is a reasonable representation of the data to the degree that the assumption of an additive distance between populations is met. Consistent with that assumption, we have used a genetic distance measure that estimates the pairwise distance in units of t/2Ne, i.e., time in generations divided by twice the effective population size. This assumes random genetic drift is the cause of the differences among populations. This distance measure is then additive across the correct tree structure with the objective being to identify the best fitting tree structure. As noted in METHODS, an iterative approach was used to find the best fitting LS tree structures. Because of the very large number of tree structures possible for any large set of populations, it is convenient to start with the NJ tree which is usually similar to the better LS trees. A major difference in our experience is that the NJ tree typically has many negative segments while the best LS tree has fewer or none. A negative segment clearly identifies a region of the tree that violates the additivity assumption.A common form of tree analysis in the literature is the Neighbor Joining (NJ) tree50. An independent study of Y chromosome variation and mitochondrial DNA variation51 reached essentially the same conclusion that southern Altaians are the closest to the ancestors of Native Americans. Other studies including Northern American Natives 52 argued for a more eastern Siberian origin of those populations. Our studies are limited to those Native Americans classified as Amerind speaking.Although our focus in this study was on North Asia, other interesting findings emerged in our analyses of the large amount of information. We are not giving them much attention because additional data will likely become available for many of these other populations and more certainty will then be possible with more data. However, these analyses do support some conclusions on other populations beyond the North Asia populations. The most distinctive of these interesting other findings is support for the ancestry of the Native Americans originating from the middle of North Asia. This is not a new conclusion. Studies of Y-chromosomes argued for the Altai region of Siberia as the origin of Amerind speaking Native Americans53 provide extensive independent autosomal data. The STRUCTURE analyses , provide separate patterns of genetic relationships that can differ from the mult-locus estimates of the autosomal MHs.The current results illustrate the information provided by autosomal markers. MHs provide an overall level of genetic relationship that the sex-specific markers (Y DNA and mt DNA) do not. Each of the sex-specific types of markers provides a single gene tree of the Y or mtDNA for each individual independently whereas each MH provides a separate and independent view of history and relationships of populations. MHs differ from the other category of autosomal loci with multiple alleles, short tandem repeat (STR) loci, in that MHs have much greater mutational stability with mutation rates on the order of 1054. Logic argues that fewer microhaplotypes will be required because of their multiallelic nature55. The tradeoff in numbers will require more study. This large dataset with multiple MH loci supports the global distinctiveness of the North Asia populations in a way that has not been shown previously. Similarly, some of the MHs and analyses show variation among the several North Asia populations in ways that highlight the use of different methods with different underlying assumptions. We have used three of the most commonly used methods of analyzing population relationships based on autosomal markers: STRUCTURE, PCA, and Tree analysis. Other approaches to data analysis usually involve both different underlying genetic models44, such as specific patterns of admixture56, and more computer intensive methods; they are beyond the scope of this study. However, with all the data publically available it is possible for others to consider such analyses.Showing relationships among a sample of individuals in a population requires large numbers of SNPs for accuracyOur analyses confirm with microhaplotypes the general finding of 6 large “continental” biogeographic clusters of human populations. The analyses based on this set of 58 multi-allelic polymorphisms demonstrate the potential value of microhaplotypes to explore genetic relationships of populations within these “continental” clusters. These particular loci demonstrate distinct clusters of populations within Northern Europe, within North Asia, and within East Asia. More refined population relationships will certainly emerge as more and better microhaplotypes are identified that can help differentiate populations within and between the diverse geographical zones inhabited by human populations and illuminate their historical relationships. Panels of microhaplotypes have much to offer in a variety of genetic, anthropological, forensic, and medical applications.https://alfred.med.yale.edu. ALFRED Supplementary Information.


Hyporhamphus intermedius is an anadromous, brackish‐water halfbeak that is widely distributed in coastal areas and hyperdiverse freshwater systems in China, making it an interesting model for research on phylogeography and local adaptation. Here, 156 individuals were sampled at eight sites from heterogeneous aquatic habitats to examine environmental and genetic contributions to phenotypic divergence. Using double‐digest restriction‐site‐associated DNA sequencing (ddRAD‐Seq) in the specimens from the different watersheds, 5498 single nucleotide polymorphisms (SNPs) were found among populations, with obvious population differentiation. We find that present‐day Mainland China populations are structured into distinct genetic clusters stretching from southern and northern ancestries, mirroring geography. Following a transplant event in Plateau Lakes, there were virtually no variations of genetic diversity occurred in two populations, despite the fact two main splits were unveiled in the demographic history. Additionally, dorsal, and anal fin traits varied widely between the southern group and the others, which highlighted previously unrecognized lineages. We then explore genotype–phenotype‐environment associations and predict candidate loci. Subgroup ranges appeared to correspond to geographic regions with heterogeneous hydrological factors, indicating that these features are likely important drivers of diversification. Accordingly, we conclude that genetic and phenotypic polymorphism and a moderate amount of genetic differentiation occurred, which might be ascribed to population subdivision, and the impact of abiotic factors.Species differentiation and local adaptation in heterogeneous environments have attracted much attention, although little is known about the mechanisms involved.  Hyporhamphus intermedius is widely distributed in in Mainland China, making it an interesting model for research on phylogeography and local adaptation.ddRAD‐Seq reveals evolutionary insights into population differentiation and the cryptic phylogeography of Hyporhamphus intermedius in heterogeneous environments in Mainland China SeveralFish are ideal organisms for studying local adaptive divergence and phenotypic plasticity. Given the complex geomorphic conditions in China, with dramatic climate changes at high altitude and latitude, the hyperdiverse freshwater systems  show remarkably high levels of fish diversification and are prone to endemism. These independent areas separated by long distances probably also facilitated the differentiation of fishes and formation of the genetic landscape  , an anadromous halfbeak, is likely to be considered a novel system for this study, with a large geographic range in the estuaries of Mainland China from the East China Sea to the South China Sea  What is the spatial population structure of H. intermedius and genetic diversity at the genomic level? (2) What is the historical demography and phylogeography of H. intermedius in Mainland China? (3) What are the drivers of local differentiation of H. intermedius associated with environmental factors?In heterogeneous environments, local abiotic parameters may have stronger effects on genetic diversity and drive the spatial distribution of freshwater species. The genetic structure and relative strength of selection are hypothesized to influence the distribution of genomic variation on different spatial scales , Fu Xianhu (FXH) in the plateau waters of Yunnan Province; Sanshui (SS), Gaoming (GM), Doumen (DM) in the Pearl River; Chongming (CM) near the estuary, Suzhou (SZ) in the Taihu Lake, and Jining (JN) in Weishanhu Lake Figure . The mapH. intermedius, we integrated phenotypic, environmental, and genomic data  were selected for processing to ensure sufficient sample size, and Hyporhamphus quoyi (n = 3) were collected as outgroup. The living samples were transferred into 10 L aquaria, which was dissolved with a high concentration of 150 mg/L MS‐222 . All individuals appeared deep anesthesia or death behaviors  during 1–2 min, and the surgery and sampling were made after a respiratory arrest. We measured their standard length (SL), weighed them on an electronic balance (body weight: BW), and then took a lateral photograph of the left‐hand side of body shape to measure 10 morphological traits and perform geometric‐morphometric analyses with Digimizer v.4.5.1 (http://www.digimizer.com)  and the protocol consisted of initial denaturation at 98°C for 30 s, 14 cycles , followed by a final step at 72°C for 5 min. DNA libraries were quantified using a 2100 Bioanalyzer (Agilent Technologies). Finally, pools were combined in equimolar concentration to form a single genomic library and sequenced on an Illumina HiSeq 2500 using 150 bp pair‐end reads.2.3ustacks with a minimum depth of coverage required to create a stack (m) of five and four maximum. The catalog of loci was assembled using cstacks and matching rad‐tags used the sstacks program. Finally, populations program was used to filter and output the SNP sites of all samples. Loci were considered as valid if they were present in at least 75% of individuals with a minor allele frequency (MAF) > 0.05. The population script was applied to calculate population genetic diversity parameters such as nucleotide diversity (π), expected and observed heterozygosity (He and Ho), and F‐statistics including genetic differentiation (FST) and average genetic differentiation between individuals within their sampling locations (FIS) were estimated with Stacks v1.46 . Then, TreeMix 1.12  using the R package “adegenet” Jombart, , which w1” generations ago (based on book recording), while the Northern and Southern groups were separated from each other at t2 generations ago. The ancestral native northern, southern, and plateau populations are NT, ST, and PL; NA is their common ancestral population. Priors for bottleneck duration and the effective number of founders were broad as no prior information is available.We examine neutrality test to detect past demographic expansion, and Tajima's D values Tajima,  were cal7 simulated data sets were used with uniform prior distributions of Ne  was considered as potential drivers of spatially varying selection  to evaluate associations among the genotype, phenotype, and environment  in driving spatial genetic differentiation Rao, . Standaron Table .rda function in the “vegan”  with 1000 permutations to evaluate the significance of the global RDA. Finally, we used scaling = 3  on the first two constrained ordination axes for the ordination plots  and the explanatory variables . In our case, the set of 5498 SNPs markers were converted from .vcf to. raw format using “plink”  in the dataset containing 5498 SNPs. All analyses were conducted with 20 pilot runs for 5000 iterations, followed by 100,000 iterations with a burn‐in of 50,000 steps. The default value of prior odds (10) was used. Loci with alpha‐values significantly >0 were considered as loci under directional selection while those with alpha <0 were considered as loci under balancing selection  and GPA (genotype–phenotype association) methods to detect loci putatively under selection based on correlations with environmental variables and morphological traits. This approach can detect multilocus signatures of selection based on locus scores from significant axes  that were ± 3 SD from the mean loading on the first two constrained ordination axes. It may have very limited power in identifying spatially diversifying selection and we also could not align candidate loci against no genomic resources for nonmodel species. In addition, the SNP loadings were stored as species in the RDA object and extracted from the three significant constrained as described above. The program parameters followed Forester's setting  raw sequence reads per sample. After removing poor‐quality sequences, an average of 15,046,821  raw reads were available for sequence mapping and finding SNPs. Of the total 32,744 SNPs detected from 13,684,154 tags, 27,246 were discarded due to excessive missing data in >80% fish in collection, retaining 5498 high‐quality SNPs with minor allele frequency (MAF) > 0.05 across the entire sequence dataset.3.2IS were lowest within the plateau populations (0.0254–0.0265). We have test percentage of loci in Hardy–Weinberg disequilibrium per population   compared to the remaining groups  of the 5498 SNPs showed significant genetic variation among groups (56.70%) and within populations 43.01%)  formed a distinct clade that was separated from the other populations with 100% bootstrap. The individuals from the Northern and Plateau Lakes systems were assigned to close clades, suggesting a close relationship between the two systems Figure . NotablyPrincipal components analysis and ADMIXTURE analyses produced a similar phylogenetic topology. The first two principal component axes clearly separate three distinct lineages from each other in PCA plot Figure , which wTreeMix analyses were used to estimate the direction and magnitude of gene flow among taxa. The unrooted phylogenies revealed two key results: first, within the two main clades, the Southern group were well separated from the remaining sites, while the Plateau and northern groups were admixtures with similar groupings of taxa to those found in the secondary optimal structure Figure . Next, a3.4H. intermedius had a significant positive value . As predictive of genetic variation, all variables excluding dissolved oxygen (DO) were completely negative correlation to axis 1 in the RDA, whereas DO have the largest squared constraint score in the second RDA axis  of climatic and environmental variables showed that the first two components explained, respectively, 82.1%, 8.96% of the variation Figure , and fouH. intermedius genotype–phenotype association (GPA) models, ten phenotypic traits identified using RDA exhibited statistical association , supporting a role for anal and dorsal differences facilitating divergence between ecotypes.Pearson analysis distinguished pronounced changes in shape associated with the bases of the dorsal and anal fins Figure , indicat3.6FST than the background of the genome  and 49 have significantly lower FST than the background of the genome . Furthermore, the pairwise FST analysis revealed high differentiation in the Southern group, possibly cryptic subspecies  between the native and introduced populations (the North and the Plateau). Strong divergence in H. intermedius appeared along the north–south axis based on genetic analysis, whereas Collette and Su  mold phylogeography and diversification at large scales. Genome‐wide SNP data gave insights into the complex spatial genetic structure (three clusters) and the demographic history of Gongpei Wang: Conceptualization (lead); data curation (lead); formal analysis (lead); investigation (lead); methodology (lead); software (lead); validation (lead); visualization (lead); writing – original draft (lead); writing – review and editing . Han Lai: Data curation ; investigation ; validation ; visualization . Sehng Bi: Investigation ; methodology ; resources . Ding‐Li guo: Conceptualization ; investigation ; software . Xiaopin Zhao: Methodology ; validation ; writing – original draft . Xiaoli Chen: Data curation ; resources ; validation . Shuang Liu: Investigation ; methodology ; writing – original draft . Xuange Liu: Methodology ; validation . Yuqin Su: Methodology ; validation . Huadong Yi: Methodology ; validation . Guifeng Li: Conceptualization ; funding acquisition ; investigation ; project administration ; resources ; supervision ; validation ; writing – review and editing .The authors declare that they have no competing interests.Figure S1 The PCA results of pre‐evaluation of each scenario. Each  dot represents a simulated dataset from the reference table and the large yellow dot represents the observed data set. The initial components of datasets are the values of the summary statistics from which the principal components are computed.Click here for additional data file.Figure S2 Phylogenetic networks of H. intermedius represented with the maximum‐likelihood method. The NJ tree was constructed using SNPs dataset. The bootstrap values (>0.7) are given above/below the branches.Click here for additional data file.Figure S3 SNPs in the unit sliding window corresponds to Tajima’s D value. Blue line represents the average of Tajima’s D value of SNPs, Tajima’s D = 1.936; Red line represents a dividing line, Tajima’s D = 0 observed variation equal to expected variation.Click here for additional data file.Figure S4 Pearson correlation of 13 standardized phenotypic variables.Click here for additional data file.Table S1Names of sites sampled, abbreviations of their names, location, and numbers of Hyporhamphus intermedius used in the genomic analysesClick here for additional data file.


Dolichonyx oryzivorus) breed in grasslands across northern North America and migrate from their breeding grounds toward the eastern Atlantic Coast and then proceed through the Caribbean to South America. However, a small but regular number of Bobolinks have been recorded on the Galapagos Islands. We collected genetic samples from nine Galapagos Bobolinks and performed double‐digest restriction site‐associated sequencing. We compared them with samples from seven locations across their breeding distribution to determine their population of origin. Galapagos Bobolinks shared the genetic structure of a cluster in the eastern portion of the breeding range that includes New Brunswick and Ontario, Canada, and Vermont, United States. Genetic assignment tests largely corroborated this finding, although slightly different results were obtained for the two methods. All individuals were assigned to the Ontario breeding population using AssignPop, while Rubias assigned six of the migrants to Ontario and three to a Midwest breeding population. Low average relatedness among Galapagos individuals indicates that they are not more related to one another than to individuals within a breeding population and are therefore likely not from a single, small isolated population. Our results do not support the probability hypothesis—that Galapagos Bobolinks originated from the region that includes the greatest proportion of their breeding range (Great Plains)—or the vagrant hypothesis—that migrants are displaced onto Galapagos due to weather events. Instead, our findings support the proximity hypothesis, where migrants originate from the geographically closest‐breeding populations.Little is known about the causes and consequences of alternative pathways flown by long‐distance migratory birds. Bobolinks ( Little is known about the causes and consequences of alternative pathways flown by long‐distance migratory birds. Using population genetic analyses, we compared samples from migratory Bobolinks stopping over in Galapagos with samples from seven locations across their breeding distribution to determine the migrant's breeding population of origin. Galapagos Bobolinks shared the genetic structure of a cluster in the eastern portion of the breeding range in North America that includes New Brunswick, Vermont, and Ontario. For example, morphological traits that favor higher maneuverability can enable individuals to take a less risky but more energetically challenging route  tracked from three populations across their European breeding distribution took detours from the shortest route possible, and the detour extent varied among populations and between spring versus fall migration , a grassland obligate songbird in the blackbird family (Icteridae), migrates between North and South America each year. Its breeding range spans nearly coast to coast in Canada and the United States. Populations from British Columbia to Nova Scotia migrate through the Caribbean and the Llanos of Venezuela and Colombia to and from their wintering grounds in Bolivia and Argentina  The vagrant hypothesis suggests that Bobolinks are in Galapagos as a result of weather events that have displaced them from their usual migration route. Under this hypothesis, we expect that Bobolinks that stop on Galapagos would originate from multiple breeding populations. This hypothesis could also be supported if Galapagos Bobolinks originate from only one region, and by chance, the weather events affect this region only. (3) The proximity hypothesis predicts that Galapagos birds originate from the part of the breeding range that is the shortest orthodromic distance from Galápagos. Under this hypothesis, we expect that Galápagos Bobolinks would originate from the southern part of midwestern or eastern breeding populations. (4) Under the alternate non‐breeding range hypothesis, Bobolinks stopping in the Galápagos Islands are passing through on their way to spend the austral summer in Ecuador, potentially on the islands themselves, in Ecuador west of the Andes, or in Peru (areas outside of their main wintering range).We propose four main hypotheses, not mutually exclusive, to explain why some Bobolinks migrate through Galapagos. (1) Under the Here, we use genetic analyses to examine the breeding origins of Bobolinks that stop in Galápagos during their southbound migration. We assign individuals to their breeding region based on the known genetic population structure of Bobolink across its breeding range  sequencing libraries for the nine Galápagos samples in this study and the 174 Bobolink breeding population samples, following the Peterson et al.  protocolBioinformatic data processing and SNP identification are also described in Renfrew et al. . In summm = 3  and M and n = 5 . We used program Populations in STACKS to group individuals into eight geographic sampling locations , from which we identified polymorphic SNPs. We required an SNP to be present in 70% of individuals and six populations to be called. We also required a minimum minor allele frequency of 0.01 and maximum observed heterozygosity of 0.5 to process a nucleotide site at a locus. Only the first SNP per stack was used to avoid linkage in the dataset. This resulted in a final SNP panel of 3234 SNPs. We tested for conformance to Hardy–Weinberg equilibrium and validated that missing data in our final dataset had no effect on inference of population structure  pipeline to identify SNPs from these filtered sequences. We optimized parameters for the de novo assembly, as described in Renfrew et al. , resulti2.3K value (K = 1–8). We used the LocPrior model . To assess the results of STRUCTURE and determine the best‐supported model, we used a combination of the delta K method  with the Adegenet package in program R as an additional method to assess genetic differentiation among the samples Jombart,  and deteFis values) for each of the seven breeding locations and the nine Galápagos migrants, in the program Populations of STACKS. We calculated pairwise individual relatedness values for each bird using ‐‐realtedness2 function in VCF tools  in fisheries, and it is powerful for estimating mixture proportions and individual assignments in other systems as well . After de novo assembly , we werK method, STRUCTURE analysis supported a k = 3 solution; however, the plateau in the estimated log probability of the data (LnP(D)) suggested a model of k = 4  were similar among all the sampling locations , while Nebraska exhibited the highest value (0.147). Mean pairwise relatedness within populations was low for all sample locations  for the four regional breeding population groups , with all groups having >89% correct assignment Table . Self‐asFor the simulated mixtures in Rubias, the average P of Z was consistently high across regional breeding population simulations , regardless of the method of resampling, ranging from 99% to 100% with the gene copy method and 91%–100% with the full multilocus method  for the analysis with the seven breeding populations matched the results of the assignment testing, with approximately 0.606 proportional assignment to Ontario, 0.315 to Nebraska, and 0–0.019 to the other five populations. Bootstrap correctedproportions were largely similar to the uncorrected mixture proportions, albeit slightly higher to Nebraska and Ontario, thereby further strengthening the evidence for these assignments Table . Uncorre4Using genetic data in conjunction with assignment testing and mixture analysis, we identified the breeding population of origin of individual Bobolinks that use an alternate migratory pathway through the Galápagos Islands. Comparing the genotypes at 3234 SNPs of nine Bobolinks captured in Galápagos during their southbound migration to population genetic data for seven locations in the Bobolink breeding range, we determined that the Galápagos migrants were genetically most similar to Bobolinks from the eastern portion of the breeding range. The two different assignment testing approaches that we used gave largely similar results, however, there were slight discrepancies. The AssignPop method assigned all nine migrants to the Ontario location within the eastern breeding population with high confidence. Rubias assigned six of the migrants to the Ontario population with high confidence and three to Nebraska (in the midwestern breeding group). When mixture analysis was conducted with the four genetically distinct breeding groups, rather than all seven breeding locations, the bootstrap corrected mixing proportions corroborated the AssignPop results, with nearly the full mixture assigned to the eastern population. Taken together, these results best support the eastern breeding population as the origin of most or all of the Galápagos migrants, although it cannot be ruled out that some individuals may have originated in the Midwest.Fis and negative relatedness values for the Galápagos Bobolinks  is the same as the longitude where the Mississippi River divides southern Wisconsin and southern Minnesota, approximately 4900 km from the Galápagos Islands. The Mississippi River basin would therefore be the location that is the shortest orthodromic distance from the Galápagos Islands. If this region of the Midwest is genetically similar to the eastern breeding population (particularly Ontario), it would provide evidence supporting the origin of Galápagos Bobolinks in the Mississippi River basin, thereby supporting the proximity hypothesis. Alternatively, the proximity hypothesis would also be supported if the Galápagos Bobolinks originated from the southeastern portion of the breeding range , although the Bobolinks would have to fly a portion of that route along a declination counter to that of the main route through the Caribbean. Under the vagrant hypothesis, individuals from the eastern part of their breeding distribution could have been forced west by weather events prior to southbound migration and did not correct their migratory declination accordingly. There is support for such a lack of correction: a Bobolink breeding in North Dakota that was experimentally displaced to California prior to migration did not adjust its migration declination, and instead flapped in the direction of the coast of California, toward the Pacific Ocean ; funding acquisition (lead); investigation (lead); methodology ; project administration (lead); resources ; writing – original draft (lead); writing – review and editing (lead). Logan M. Maxwell: Formal analysis ; investigation ; methodology ; visualization (lead); writing – original draft ; writing – review and editing . Adrienne Kovach: Conceptualization ; formal analysis ; funding acquisition ; investigation ; methodology ; resources ; writing – original draft ; writing – review and editing . Patricia Parker: Conceptualization ; writing – original draft ; writing – review and editing . Rosalind B. Renfrew: Conceptualization ; investigation ; writing – original draft ; writing – review and editing .Benefits from this research accrue from the sharing of our data and results on public databases as described above.Appendix S1Click here for additional data file.