Rhinoptericola megacantha (Trypanobatoida) and the shark-hosted Callitetrarhynchus gracilis (Trypanoselachoida). Adults of R. megacantha are more host-specific and less broadly distributed than adults of C. gracilis, allowing correlation between these factors and genetic structure. Replicate tapeworm specimens were sequenced from the same host individual, from multiple conspecific hosts within and across geographic regions, and from multiple definitive host species. For R. megacantha, population structure coincided with geography rather than host species. For C. gracilis, limited population structure was found, suggesting a potential link between degree of host specificity and structure. Conspecific trypanorhynchs from the same host individual were found to be as, or more, genetically divergent from one another as from conspecifics from different host individuals. For both species, high levels of homozygosity and positive FIS values were documented.Theory predicts relaxed host specificity and high host vagility should contribute to reduced genetic structure in parasites while strict host specificity and low host vagility should increase genetic structure. Though these predictions are intuitive, they have never been explicitly tested in a population genomic framework. Trypanorhynch tapeworms, which parasitize sharks and rays (elasmobranchs) as definitive hosts, are the only order of elasmobranch tapeworms that exhibit considerable variability in their definitive host specificity. This allows for unique combinations of host use and geographic range, making trypanorhynchs ideal candidates for studying how these traits influence population-level structure and genetic diversity. Multiplexed shotgun genotyping (MSG) data sets were generated to characterize component population structure and infrapopulation diversity for a representative of each trypanorhynch suborder: the ray-hosted  While it is intuitive to assume that relaxed host specificity should lead to reduced genetic structure in parasites, this theory has yet to be tested in a population genomic framework. In this study, multiplexed shotgun genotyping data sets were generated for a species each of shark and ray-hosted tapeworms that demonstrate different degrees of host specificity, and population structure was found to coincide with geographic region—rather than definitive host species—in the more host-specific of the two species. These first population genomic data for shark and ray tapeworms provide a primary foundation on which future investigations of parasite population genomics can build.It has long been suggested that relaxed host specificity and increased host movement should each contribute to reduced genetic structure in parasites, while more host-specific species, as well as those that parasitize less wide-ranging and/or vagile hosts, should exhibit greater degrees of structure . Though Hemionchos is highly host-specific and is known to parasitize only a single species of devil ray (family Mobulidae) , the whitespotted wedgefish, Rhynchobatus djiddensis, and a species of requiem shark (family Carcharhinidae), collectively from Australia, Singapore, and Sri Lanka  as adults . As a grbulidae) , but indr orders , 2014. Tri Lanka .Rhinoptericola megacantha (family Rhinoptericolidae) in the suborder Trypanobatoida, and Callitetrarhynchus gracilis (family Lacistorhynchidae) in the suborder Trypanoselachoida. Both species demonstrate relaxed host specificity, or are euryxenous sensu R. megacantha are known from three species of cownose rays (family Rhinopteridae) and a species of stingray (family Dasyatidae), and they are restricted to the Atlantic Ocean   , and froiakidae)  and dasyiakidae) . These rsta Rica .The goal of this investigation was to leverage next generation sequencing methods and previous global collections of trypanorhynchs from elasmobranchs with an emphasis on broad and deep sampling to address the following questions: 1) Is population-level genetic diversity in trypanorhynch tapeworms that demonstrate relaxed host specificity structured by definitive host species or geography? 2) Does the degree of host specify correlate with observed patterns of population structure? 3) Are conspecific trypanorhynchs more genetically similar within a host individual than between host individuals?R. megacantha, 39 specimens were sequenced. They were collected from specimens of Rhinoptera bonasus (South Carolina), Rhinoptera brasiliensis , and Rhinoptera marginata  , and from three additional geographic localities from which it is known  were unavailable  see  online. able see  online. ntha see  online.C. gracilis, 47 specimens were sequenced. They were collected from specimens of Carcharhinus brevipinna , Carcharhinus isodon (Gulf of Mexico), Carcharhinus limbatus , Carcharhinus cf. limbatus sensu Rhizoprionodon terraenovae   see  online. ilis see  online. ined see  online.R. megacantha, after filtering, 29 (of 39) and 26 (of 34) specimens were retained in the complete and no-Senegal data sets, respectively  and 21 (of 43) specimens were retained in the complete and no-Senegal data sets, respectively  data sets were generated for population genomic analyses . For each species, these include: 1) a data set containing all specimens of sufficient data quality (hereafter a “complete” data set); 2) a complete data set additionally filtered for minimum minor allele count; 3) a complete data set excluding the specimens collected from Senegal ; and 4) a no-Senegal data set additionally filtered for minimum minor allele count. The number of specimens, number of loci, and programs used to analyze each of the eight final filtered SNP data sets are given in ectively  online. fig. 1A,  online. ectively  online. DAPC) for both species are presented in R. megacantha with DAPC, both Bayesian information criterion (BIC) and Akaike information criteria (AIC) preferred a K-value of 2, separating specimens collected from the eastern Atlantic  from those collected from the western Atlantic (hosted by R. bonasus and R. brasiliensis) (A). A K-value of 2 was also preferred by both AIC and BIC for the no-Senegal data set for R. megacantha, separating specimens from Belize (hosted by R. brasiliensis) from those collected from South Carolina and the Gulf of Mexico (hosted by R. bonasus and R. brasiliensis) (B).Results from discriminant analysis of principal components (liensis) A. A K-valiensis) B.C. gracilis with DAPC, BIC preferred a K-value of 2 (C) while AIC preferred a K-value of 3 (D). At K = 2, one cluster comprised six specimens collected from Florida Atlantic, the Gulf of Mexico, and Australia , while the second cluster comprised the remaining 26 specimens collected from South Carolina, Florida Atlantic, the Gulf of Mexico, Senegal, and the northern Atlantic Ocean  (C). At K = 3, the clustering pattern was identical to that recovered at K = 2, with the exception of the single specimen from Senegal (hosted by C. brevipinna) recovered in its own cluster (D). For the no-Senegal data set for C. gracilis, a K-value of 2 was preferred, recovering the same two multispecimen clusters described above for the complete data set at K = 3 (E).For analysis of the complete data set for lue of 2 C while Alue of 3 D. At K =aenovae) C. At K = cluster D. For that K = 3 E.STRUCTURE analyses for R. megacantha are presented in R. marginata) from those collected from the western Atlantic (hosted by R. bonasus or R. brasiliensis) (A), thus mirroring the results from the DAPC analysis. A K-value of 5 had the greatest likelihood value for this data set. Obvious patterns of clustering by host individual, host species, or geographic sampling locality were not revealed by K-values of 3–4 for the specimens collected from the western Atlantic, but at K = 5, the three specimens from Belize are distinguishable from nearly all specimens from the more northern western Atlantic localities. For K-values of 4 and 5, nine of ten STRUCTURE replicates binned genetic diversity into only three and four groups, respectively (A). Results from the single iteration for each of the K = 4 and K = 5 runs that returned genetic diversity binned in as many groups as specified by the K-value are presented in R. megacantha with STRUCTURE, the Evanno ΔK method preferred a K-value of 2, separating specimens from Belize (hosted by R. brasiliensis) from those collected from South Carolina and the Gulf of Mexico (hosted by R. bonasus and R. brasiliensis) (B), again mirroring the results of the DAPC analysis. No obvious patterns of clustering by host individual, host species, or geographic sampling locality were evident for the specimens collected from South Carolina and the Gulf of Mexico for K-values of 3 and 4 for the no-Senegal data set (B).Results from liensis) A, thus mectively A. Resultliensis) B, again data set B.STRUCTURE analyses for C. gracilis are presented in fig. 4A). For K = 2, the individual from Australia hosted by C. cf. limbatus, the individual from Florida Atlantic hosted by R. terraenovae, and four individuals from the Gulf of Mexico hosted by C. cf. limbatus, C. brevipinna, and R. terraenovae were recovered as sharing similar genetic backgrounds , echoing the results of the DAPC analyses . These individuals were also consistently recovered as sharing similar genetic backgrounds for K-values 3–5 , with the specimen from Australia hosted by C. cf. limbatus and the specimen from C. brevipinna from the Gulf of Mexico identified as most similar to one another at K = 6 . Additionally, for K-values 4–6, the specimen from Senegal hosted by C. brevipinna was consistently recovered as distinct from specimens from the western Atlantic and Australia. No obvious clustering by host individual or host species was evident for any K-values tested for the complete data set for C. gracilis, but for K-values 4–6, a general pattern of genetic similarity shared between specimens from the Gulf of Mexico, Florida Atlantic, and the northern Atlantic Ocean—to the exclusion of specimens South Carolina, and the group of six specimens discussed above—was evident (fig. 4A).Results from C. gracilis with STRUCTURE, the Evanno ΔK method preferred a K-value of 2, and the greatest K-value tested  had the greatest likelihood value (B). Only a single specimen was excluded to create the no-Senegal data set for C. gracilis, and overall, comparable patterns of genetic similarity for the remaining specimens at K = 2–5, as described above for the complete data set, were recovered (B).For analysis of the no-Senegal data set for od value B. Only aecovered B.R. megacantha and 1,501 sites for C. gracilis. The most likely topologies as inferred by RAxML are presented in figure 5A for R. megacantha and figure 5B for C. gracilis. For R. megacantha, the most likely topology showed two well-supported clades with BS ≥99: a clade containing the three specimens from Senegal  sister to a clade containing all 26 specimens from western Atlantic . Within the western Atlantic clade, specimens from Belize (hosted by R. brasiliensis), formed a well-supported subclade . For C. gracilis, beyond the fact that two of the three specimens sequenced from the host individual CH–50 (C. limbatus from South Carolina) were recovered as sister to one another with strong support (BS = 100), no pattern of grouping by host individual, host species, or geographic sampling locality was evident (B). The single specimen from Senegal hosted by C. brevipinna was recovered as subtended on a relatively long branch (B).Following concatenation of different loci and removal of invariant sites from complete SNP data sets for both species, final alignment lengths were 1,843 sites for BS = 99; A. For C. evident B. The sig branch B.IS, nucleotide diversity [π]) for both species for the four iterations of populations run are presented in ST values for both species are presented in ST values for comparisons involving a subpopulation containing a single specimen are not reported. For R. megacantha, the three specimens from Senegal (hosted by R. marginata) had a high proportion of private alleles  despite comprising a relatively small proportion of the total data set   between specimens of R. megacantha from Senegal (hosted by R. marginata) and other subpopulations in both the by–geography (A) and by–host species (B) comparisons. For C. gracilis, FST values ranged from ∼0.04 to 0.14 in the by–geography comparisons (C) and from ∼0.05 to 0.11 in the by-host species comparisons (D). Observed homozygosity was elevated  for all subpopulations tested for both species, and values of FIS ranged from ∼0.01 to 0.2 for R. megacantha and from ∼0.03 to 0.23 for C. gracilis for all subpopulations containing more than a single specimen  . Additioeography A and by– species B compariparisons C and froparisons D. Observspecimen .R. megacantha from each of three specimens of R. marginata from Senegal, and one specimen of C. gracilis from one individual of C. brevipinna from Senegal; see Results of pairwise distance calculations within and between infrapopulations for both species are presented in R. megacantha (A) and C. gracilis (B), the lowest pairwise distances were recovered between specimens from different infrapopulations . Based on range, variability, and statistical comparison, pairwise distances within an infrapopulation were indistinguishable from those representing comparisons between two infrapopulations , it is predictable that less genetic structure was recovered for C. gracilis overall  from those collected from the western Atlantic   while R. bonasus and R. brasiliensis are sympatric for most of their range, collectively the waters are found only off the eastern coasts of North, Central, and South America  more genetically similar to one another than to specimens collected from R. bonasus, all SNP-based analyses suggest that specimens from R. brasiliensis from Belize comprise a subpopulation that is genetically distinct from specimens collected from South Carolina and the Gulf of Mexico hosted by either R. brasiliensis or R. bonasus . After filtering, three (of six) specimens of R. megacantha hosted by two (of four) individuals of R. bonasus were included in SNP data sets, versus 20 specimens hosted by seven individuals of R. brasiliensis. However, only three specimens each were sampled from both Senegal  and Belize , and analyses still recovered distinct genomic signatures for these sets of specimens. Thus, despite limits in sampling, geography—rather than definitive host species—appears to be the primary driver of population structure in R. megacantha.Within the western Atlantic, results suggest geography to play a more important role than definitive host species in structuring genetic diversity in R. megacantha align with those of previous studies, a comprehensive explanation for them may prove challenging. Given that this study is the first of its kind for elasmobranch tapeworms, potential explanations for the observed patterns are worth exploring despite sampling limitations and the lack of knowledge about the life history of R. megacantha.Few studies have probed the population genetics of parasites, and even fewer have focused on tapeworms specifically. There is, however, some evidence from restriction fragment length polymorphism, single locus, and microsatellite data sets to support a predominant role of geography in genetic structure for tapeworms that are not strictly host-specific . While fA, 2B, and 3B). This pattern is intriguing considering studies for a wide range of marine taxa document phylogeographic breaks between populations in the Gulf of Mexico and the Atlantic (R. megacantha (the only free-living stage of the life cycle) between these localities, and so maintain genetic homogeneity between all three subpopulations.The genetic difference observed between subpopulations on either side of the Atlantic Ocean was expected given the vast distance between these two regions, and, concurrently, the use of a different species of definitive host in each region. Potentially more challenging to explain is the genetic differentiation between specimens from the Caribbean  versus more northern collecting localities despite apparent panmixia between subpopulations in the eastern Atlantic and the Gulf of Mexico  utilized in the northern Atlantic and the Gulf of Mexico is/are sufficiently vagile to allow for connectivity between the two regions. R. megacantha is clearly needed.The diets of cownose rays in North America have been relatively well-studied . Rhinopt Bay see  and the  Bay see . . Unfortunately, comparable data for other species of trypanorhynchs are not available. To date, the work that has been done to examine intraspecific genetic divergence in trypanorhynchs has been restricted to data for only single loci  and has focused mainly on establishing boundaries between intra- and interspecific divergence. The results of this body of work are summarized by Diplostomum pseudospathaceum (Class Trematoda: Order Diplostomida) and found that, in natural populations, the majority of D. pseudospathaceum released from a single snail first intermediate host were genetic clones, but that fish second intermediate hosts were typically infected with a diverse array of eye-fluke genotypes. They therefore argued for the maintenance of more than one intermediate host in a parasite's life-cycle as a strategy for increasing genetic diversity at the level of the definitive host, thereby reducing the risk of inbreeding during a reproductive event. Thus, the presence of genetically diverse infrapopulations of R. megacantha in single cownose rays likely results from gradual accumulation of dissimilar tapeworm genotypes within host individuals at each subsequent step in the life cycle.For the seven instances where SNP data for more than one specimen of fig. 7A;  online. kgrounds B and 5A.R. brasiliensis—and specifically the 20 specimens from this species from the Gulf of Mexico—encompassed the greatest proportion of genetic diversity sampled for R. megacantha, as reflected in high proportions of polymorphic sites and private alleles reported for the subpopulations that include these specimens (R. bonasus–hosted and R. marginata–hosted subpopulations (in the by–host species comparison). Thus, population summary statistics—and particularly FST values—for each of these subpopulations should be evaluated with caution. Nevertheless, the FST values reported herein are corrected AMOVA FST values, and are thus not biased by differences in sample sizes between subpopulations, and recent simulations show that FST values are not artificially inflated by small sample sizes if the number of biallelic markers sampled is sufficiently great  .The large proportion of specimens  collected from pecimens . Filteri herein) . In all,iliensis A and B.IS values were recovered across subpopulations of R. megacantha  and positive Fgacantha . The fewgacantha . In factoduction .C. gracilis, results from DAPC, STRUCTURE, and RAxML analyses indicated no apparent genomic structure aligned with definitive host species or geographic locality beyond a distinction in some analyses between the single specimen collected from Senegal and its remaining 31 conspecifics collected from Australia or the western Atlantic   . ParasitC. brevipinna , C. isodon , C. limbatus , and R. terraenovae  suggest that these four species are quite vagile across their range (or at least within the waters off the Eastern Seaboard)  . The limR. megacantha, it is important to consider the complex, multihost life cycle of C. gracilis, for the distributions and movements of intermediate hosts may be just as important, if not more important, than those of definitive hosts when considering tapeworm population structure. C. gracilis, with copepods servings as first intermediate hosts, clupeids (herrings) serving as second intermediate hosts, scombrids (mackerels and tunas) and epinephelids (groupers) serving as third intermediate hosts, and carcharhinids (requiem sharks) serving as definitive hosts. Unlike R. megacantha, for which no data on intermediate host use are available, reports of larvae of C. gracilis abound in the literature. Over 140 species of teleosts representing tens of families worldwide have been reported as intermediate hosts of C. gracilis —which has been reported as an intermediate host of C. gracilis , the higher K-values tested in STRUCTURE analyses (A), and the comparisons of pairwise distances between infrapopulations , further supporting this assessment. These results for infrapopulation-level genetic diversity for C. gracilis essentially mirror those recovered for R. megacantha. Possible explanations, including context from other tapeworm systems, are discussed in detail for R. megacantha; those considerations are similarly applicable for C. gracilis (see above).For the seven instances where SNP data for more than a one specimen of analysis B, furtheC. gracilis as compared to R. megacantha  encompassed the greatest proportion of genetic diversity sampled for C. gracilis in the by–geography and by–host species comparisons, respectively. High proportions of polymorphic sites and private alleles were recovered for both of these purported subpopulations . Regardless, summary statistics and FST values for possible subpopulations of C. gracilis generally support the same pattern as DAPC, STRUCTURE, and RAxML analyses  and those from ulations . SamplinIS values were found for all subpopulations of C. gracilis .Additionally, consistently high levels of homozygosity  and positive Fgracilis , mirroriR. megacantha and C. gracilis   inferred for both ilis see  have theum (HWE) . STRUCTUlly real . Howeveranalyses  and 4  and positive FIS values for both species suggest in both cases that individuals commonly engage in inbreeding, including even kin–mating and/or selfing. Finally, despite its reputation as an extremely euryxenous species, adults of C. gracilis may be restricted to species of requiem sharks (family Carcharhinidae) as definitive hosts.This study is the first to leverage genome-scale data to investigate the correlation between host specificity and geographic range and parasite population generic structure. Component population-level genetic structure in As discussed, limited sampling necessitates cautious interpretations of these first insights into the population genomics of trypanorhynch tapeworms. Nevertheless, the results of this study mirror those from studies of other species of tapeworms and other parasite-host systems. The role of intermediate hosts in creating and/or maintaining genetic structure in trypanorhynch populations should not be underestimated, and moving forward, studies that reveal whether patterns of structure observed at the level of the definitive host are maintained in line with, or in spite, of intermediate host use will be compelling. Ultimately, the results of this study provide a foundation on which future investigations of marine tapeworm populations genomics can build. This work also supplements the growing body of literature highlighting the complex interplay between biological, ecological, and oceanographic factors in structuring marine parasite populations.To assess genetic structure of infrapopulations sensu , multiplElasmobranch intestines or intestinal contents fixed in 95% ethanol resulting from global collections of tapeworms made over recent decades were examined for tapeworms. Prior to examination, spiral intestines had been removed from the body cavity and opened with a longitudinal incision. Intestines and their contents were either fixed entirely in 95% ethanol, or intestines were fixed in 10% seawater-buffered formalin and a portion of their contents (including tapeworms) were fixed in 95% ethanol. All ethanol-fixed material was transferred to the University of Kansas (KU) or the University of Connecticut (UConn) and stored in a freezer prior to examination for tapeworms.R. megacantha, sampling was informed by the comprehensive summary of its known host species and geographic localities compiled by C. gracilis, sampling was informed by reports from the literature of adults from elasmobranchs, summarized herein in For www.elasmobranchs.tapewormdb.uconn.edu) , disk width (rays) or total length (sharks), sex, collection date, collection locality, number of tapeworms recovered, and number of tapeworms recovered that were ultimately included in final data sets are given in onn.edu)  to accesonn.edu)  online.R v. 4.0.3  via RStudio v. 1.3.1093  using the packages maps v. 3.4.0 , Belize. Material from Florida was collected under the auspices of the University of Southern Mississippi Gulf Coast Research Laboratory and/or the National Marine Fisheries Service, Southeast Fisheries Science Center, Panama City, FL, USA. Collections in the Gulf of Mexico were made under the auspices of the University of Southern Mississippi Gulf Coast Research Laboratory. Material from the northern Atlantic Ocean was collected under the auspices of the National Oceanic and Atmospheric Administration and the National Marine Fisheries Service. Material from Senegal was collected under permit no. 006087 issued by the Ministère de L’Éducation, Dakar, Senegal. Collections in South Carolina were made under the auspices of the South Carolina Department of Natural Resources (Bryan Frazier and Ashley Shaw) and the College of Charleston (Isaure de Buron).Prior to DNA extraction, each tapeworm was photographed using a Lumenera INFINITY3–6UR 6.0 megapixel USB 3 microscopy camera  attached to a Leica MZ16 dissecting microscope . Microscissors were used to remove a piece of the strobila and/or scolex of each specimen for DNA extraction. To ensure accurate genotyping, DNA was intentionally not extracted from gravid proglottids . Methods for DNA extraction follow Python v. 2.7.16 (Rhinoptericola megacantha (∼351 Mb) and Pseudolacistorhynchus heroniensis (∼1 Gb) . As a genome for C. gracilis is not available, the draft genome of P. heroniensis—a member of the same family, Lacistorhynchidae—was used. Results of virtual digestions indicated MseI as the most suitable enzyme based on cut site frequency in repetitive versus nonrepetitive genomic regions and the size distribution of fragments generated. Physical test digestions using MseI were then performed at the University of Kansas Genome Sequencing Core (KU GSC) using extracted genomic DNA for one specimen of each species of interest  data sets was informed by virtual simulation of enzyme digestion using custom python scripts  in . 2.7.16 . The cutExtracted genomic DNA for all specimens was used to generate two MSG libraries using MseI and the protocol of Stacks v. 2.53  data sets from raw next generation sequence data for each of the two species of interest,  v. 2.53  was used v. 0.39  to remov. 0.11.7  and MultC v. 1.7 . Through 2.1.1.5  unless oR. megacantha allowed for use of a reference-guided alignment approach in Stacks. An index database was built from the reference genome using Bowtie 2 v. 2.3.5.1  files using the ––vcf flag: one data set containing all 39 specimens (hereafter the “complete” data set) and one data set excluding the six specimens collected from Senegal  (see populations module.Availability of the above-mentioned reference genome for  2.3.5.1 . For eacs v. 1.9  was usedset) see  online. R v. 4.0.3 via RStudio v. 1.3.1093 using the packages SNPfiltR v 0.1.1 , the number of mismatches allowed between stacks to merge them into a putative locus in the ustacks module (–M) and the number of mismatches allowed between putative loci during catalog construction in the cstacks module (–n) were varied. In addition to default settings , values of –m   and –n –M  (–m 3) were tested, with the minsamplesperpop 0.80 flag employed and all specimens specified as belonging to a single population. Following parameter testing, –m 4, –M 4, –n 4 was determined to be the most optimal combination of parameter settings.As a reference genome is not available for populations module of Stacks was used generate exploratory SNP data sets, both with the –r 0.4 flag enforced and without an –r flag specified, for each of the following combinations of specimens: 1) all 47 specimens, 2) the six specimens collected from South Carolina, 3) the seven specimens collected from Florida Atlantic and the northern Atlantic Ocean, 4) the 29 specimens collected from the Gulf of Mexico, and 5) the four specimens collected from Senegal  were assembled into stacks using the ustacks module with the –m 4, –M 4, and ––deleverage flags specified. The cstacks module was then used to create a catalog of consensus loci with the n 4 flag and default settings. The sstacks, tsv2bam, and gstacks modules were used with default settings to match individual stacks to the catalog, transpose data from orientation by specimen to orientation by locus, and genotype specimens at each SNP for each locus. The populations module was used to export two unfiltered SNP data sets as VCF files using the ––vcf flag: one “complete” data set containing all 36 specimens, and one “no-Senegal” data set excluding the three specimens collected from Senegal , additional filtering was performed iteratively in R v. 4.0.3 via RStudio v. 1.3.1093 using the packages SNPfiltR and VCFR v. 1.12.0. For both data sets, minimum and maximum read depths of 5 and 100, respectively, and a minimum genotype quality score of 30, were enforced. All loci were constrained to be biallelic, and heterozygous genotypes falling outside of an allele balance range of 0.25–0.75 were excluded. Four additional specimens with ≥96% missing data (of 36 retained specimens) were removed from the complete data set and two additional specimens with ≥96% missing data (of 33 retained specimens) were removed from the no-Senegal data set   1–5 , and 1–4 . For each K-value for each data set, ten independent STRUCTURE runs were completed, each with 1,000,000 generations with the first 50,000 generations discarded as burn–in. For DAPC analyses, the most likely number of populations was determined using the Bayesian information criterion (BIC) and the Akaike information criteria (AIC) and the number of retained principal components was determined through ascore optimization. For STRUCTURE, the most likely number genetic bins  was determined using likelihood scores and the Evanno ΔK method   implemenadegenet , and witv. 2.3.4  implemen. 1.3.10 . For DAPngletons , data sengletons , data seK method  implemenr v. A.2 .RAxML v 8.2.11  in Python v. 3.9.7  for the discrete Γ model of rate heterogeneity was specified with the –u flag. As outgroups were not included in either RAxML analysis, the resulting most likely topologies were rooted to maximize subtree balance. Nodal support was assessed with 1,000 rapid bootstrap replicates via the –f a and –# 1000 flags. Bootstrap values (BS) were displayed on the most likely tree topology using SumTrees v. 4.5.2  implemented in DendroPy v. 4.5.2  specifying the specimens from Senegal, the specimens from Belize, and the specimens from South Carolina and the Gulf of Mexico as three separate populations and 2) specifying the specimens from R. brasiliensis, R. bonasus, and R. marginata as three separate populations. The iterations run for C. gracilis were 1) specifying six separate populations for the specimens from Senegal, Australia, South Carolina, Florida Atlantic, the Gulf of Mexico, and the northern Atlantic Ocean, and 2) specifying five separate populations for the specimens hosted by C. brevipinna, C. limbatus, C. cf. limbatus, C. isodon, and R. terraenovae.The adegenet in R v. 4.0.3 via RStudio v. 1.3.1093. For each species, distances were calculated separately for both the complete and no-Senegal data sets not filtered for minimum minor allele count. Comparisons graphed include distances between members of the same infrapopulation for all infrapopulations where SNP data for more than a one specimen was available, and distances between members of each unique pair of infrapopulations.To visualize levels of genetic divergence between conspecific specimens within and between infrapopulations, pairwise distances were calculated and plotted separately for both species using the package Genome Biology and Evolution online .evad190_Supplementary_DataClick here for additional data file.


Trialeurodes vaporariorum (Westwood) (Hemiptera: Aleyrodidae), is a destructive pest that affects protected cultivation worldwide. The Indian Himalayan region is particularly vulnerable to GWF introduction, invasion, and spread due to the expansion of protected cultivation and climate change. In this study, we collected 32 naturally occurring GWF populations, mainly from the Uttarakhand state in the Indian Himalayan region, to investigate the distribution pattern and genetic diversity of T. vaporariorum. Our sampling was representative of the region's vegetation diversity and geographical location, and we collected samples from multiple sites within each locality to account for local variations. The mtCOI gene was used to accurately detect and identify GWF and to sequence haplotypes prevalent in the Uttarakhand state. The maximum likelihood method used for phylogenetic studies revealed that all 32 whitefly samples in this study belonged to T. vaporariorum and were prevalent in all the collected localities. Our population genetic study using mtCOI showed variation within T. vaporariorum populations, with 20 distinct haplotypes present. Notably, haplotype 2 (H2) was the most dominant haplotype among the sampled populations. These results provide fundamental knowledge for understanding the geographical distribution and ecology of T. vaporariorum in the Uttarakhand state of the Indian Himalayan region. The discovery of geospatial and genetic diversity of GWF in the Himalayan region underscores the importance of pest alertness, research prioritization, and the development of sustainable management strategies to protect crops.The Greenhouse whitefly (GWF),  Unfortunately, the Indian Himalaya is vulnerable to climate change, which poses a risk of species emergence, outbreak, and extinction, and threatens food security in the region2. Protected agriculture, which creates favorable microclimates to protect crops from biotic and abiotic stresses, has emerged as a new paradigm to improve food security, income, and crop protection in the region3. Polyhouse structures have been used extensively for commercial cultivation of high-value and off-season vegetables in the Himalayas, but the microclimate under these structures can favor the growth and development of pests, diseases, and soil-borne nematodes, which can threaten crop productivity6.The Indian Himalaya is a biodiverse region, hosting 30,377 species of protozoa and animalia, representing about 30.16% of the total Indian fauna, with arthropods contributing 26,393 speciesTrialeurodes vaporariorum (Westwood) (Hemiptera: Aleyrodidae) is a destructive pest problem for protected cultivation globally, infesting over 800 species of plants8. The wide host range comprises tomato, egg-plant, pepper, cucumber, chrysanthemum and other agriculturally important crops.Greenhouse whitefly (GWF), 7. These molds affect photosynthesis in leaves, leading to significant economic loss to the crops9.Due to its polyphagous nature and potential to act as a virus vector, GWF has become a major scourge for protected cultivation practicing farmers. Adult and nymph of the GWF reduce plant vigor by sucking the sap from foliage, flower, seeds, secreting honey dew, which attracts the development of soot molds fungi10 and successively has been reported in other parts of the country14. The increase in area under protected cultivation and climate change in the Uttarakhand states of Indian Himalayan region are critical factors in vulnerability to introduction, invasion, and emergence of GWF in new areas. Therefore, updating the status of GWF, mapping the geospatial distribution pattern, and intraspecific genetic diversity of the burgeoning population is obligatory to ensure timely mitigation of insect pests through suitable pest management operations. Additionally, keeping an eye on GWF springing into new regions is key in sending alertness to the farming community, safeguarding crops, and ensuring maximum returns to farmers. However, the geospatial distribution and genetic diversity for GWF is unknown from the Uttarakhand states of Indian Himalayan region. Moreover, identification of genetic variation in populations of GWF is a key objective to formulate any management plan and pest management decision making.From India, GWF was first recorded from Nilgiri hills of Tamilnadu, southern state of India17. DNA barcoding-based species identification utilizing mitochondrial cytochrome C oxidase subunit I (mtCOI) offers rapid, reliable detection and study of genetic variation among GWF18. Therefore, in this study, we aimed to use mtCOI gene markers to unravel the distribution pattern and genetic diversity among GWF (T. vaporariorum) for monitoring, tackling the pestilence to protect the protected cultivations.Traditional identification of GWF is based on morphological traits, which has several drawbacks, including reliance on expert taxonomists, time-consuming, low resolution in presence of conspecific character, presence of cryptic population, and ergonomic issues20, no populations and genetic diversity study has been conducted for Uttarakhand states, where protected cultivation is an important agricultural enterprise on a large scale. Therefore, we conducted extensive geographical sampling of GWF from protected cultivations, collecting 32 naturally occurring GWF populations representing Uttarakhand states of India. We aimed to identify the mtCOI gene sequence variation-based haplotypes most commonly representing in the sampled geographical region to formulate any management plan and pest management decision making.Despite a few genetic diversity and distribution studies on GWF from IndiaT. vaporariorum whitefly samples were collected from commercial host crops including tomato, capsicum, french bean, brinjal, cauliflower, snake guard, okra, bottle guard, garden pea and ornamentals like salvia, marigold. These crops provided a significant food source and habitat for the greenhouse whitefly (GWF) population in the study area. These crops were widely grown in open and protected structures and were heavily infested by GWF. While the chosen host crops may not be exhaustive in terms of their contribution to the genetic variation of GWF, they were important sources for the pest species. The extensive geographical sampling of GWF populations from protected cultivations conducted in this study aimed to capture a wide range of genetic diversity and distribution patterns among GWF in the Indian Himalayan region. The combination of the chosen host crops and the extensive geographical sampling approach was expected to provide a comprehensive understanding of the genetic diversity and distribution patterns of GWF in the study area.A total of 32 mtCOI gene were successfully amplified and sequenced for molecular identification and phylogeny estimation. The identity of T. vaporariorum in collected samples was supported by morphological and molecular diagnostic technique. The result suggests the frequent occurrence of T. vaporariorum in the surveyed locality including open and protected structures on range of host crops. The surveys were conducted for the first time in few districts like Chamoli, Dehradun, Nainital and Pithoragarh of Uttarakhand state and greenhouse whitefly infestation was recorded for the first time in commercial crops like Tomato, Capsicum, French bean, Brinjal and Cauliflower.Most of the samples were collected from Uttarakhand and three samples from Himachal Pradesh, one each from Delhi and Tripura. The partial mtCOI gene sequences of collected individuals have been submitted in GenBank database citing the information of locality, host range, geospatial data etc. and the accession numbers have been received and summarized in Table T. vaporariorum accessions viz., AY521265, NC006280, LN614547 to exploit as ingroups whereas the Genbank accessions viz., KU761949 Aleurocanthus camelliae, NC029155 Aleurocanthus spiniferus, AY572538 Aleurochiton aceris, NC005939 Aleurodicus dugesii, MT880225 Aleyrodes shizuokensis, KR819174 Bemisia afer, MH205754 Bemisia tabaci, AY572539 Neomaskellia andropogonis, NC006292 Tetraleurodes acacia were used as outgroups. Phylogenetic studies based on maximum likelihood method reveals that all the 32 whitefly samples from the study belonged to T. vaporariorum and it is found prevalent in all the collected localities . The number of haplotypes, total number of variable sites, and haplotype diversity, and nucleotide diversity, average number of nucleotide differences, G+C content and total number of mutations were represented in Table The variations within the haplotypes of T. vaporariorum belongs to India were represented in Table Nucleotide diversity of the Uttarakhand observed to be 0.00346 whereas in Himachal Pradesh it was 0.00233 and the group-others (one sequence each of New Delhi and Tripura) was 0.00349. In the same way, haplotype diversity observed higher in others 1.000) followed by Uttarakhand (0.843) and Himachal Pradesh (0.667) , is a highly destructive pest of cold climate greenhouses21. It has been reported to infest over 102 herbaceous plants belonging to 36 families across the world22. The infestation of greenhouse whitefly in the Indian Himalayas was first reported in the 1990s; however, its impact on commercial cultivation of vegetable crops and ornamental plants under protected and open field conditions was only reported after 2000s23. Currently, T. vaporariorum is classified as one of the key pests of tomato, cucumber, capsicum, french bean, gerbera, salvia and gladiolus under protected environment in the Indian Himalayan region6. During our surveys, we observed mixed populations of T. vaporariorum and B. tabaci in open field conditions; however, T. vaporariorum was the predominant species under protected cultivation systems in the Alpine and Humid subtropical climatic zones of the northwestern Indian Himalayas in the states of Uttarakhand and Himachal Pradesh. We also found that T. vaporariorum infestation was consistently recorded on all ornamental plants in high elevation locations, such as the Valley of Flowers (Chamoli), with an average pest infestation rate of 15–30%. Given the potential economic impact of T. vaporariorum infestations on various crops, it is crucial to develop effective management strategies for this pest. Integrated pest management approaches that combine cultural, physical, biological, and chemical control methods have been found to be effective in controlling T. vaporariorum infestations24. In addition, the development of resistant plant varieties could also serve as an effective long-term management strategy25. It is also important to note that T. vaporariorum infestations have been reported in other regions with similar climatic conditions, such as parts of Europe and the United States27. Overall, our findings highlight the need for continued monitoring and research on T. vaporariorum infestations in the Uttarakhand state of Indian Himalayas and other regions with similar climatic conditions.The polyphagous whitefly species, T. vaporariorum populations. Whitefly survey using aspirator tools are widely used tools to collect whitefly for phylogeography study28. The molecular diagnostic technique deployed was convenient to identify whitefly populations and expanding our knowledge of T. vaporariorum occurrence and diversity in Uttarakhand state.In the present study, the Uttarakhand state located in Indian Himalayan region of India, was surveyed to detect diversity of 29, biotypes30, cryptic species31 and haplotypes32. The presence of T. vaporariorum was recorded most frequently from all the surveyed plant host and respective locations. We have detected T. vaporariorum from all the regions ranging from the 300 AMSL (Pantnagar) to the highest altitude 2400 AMSL (Chamoli) of survey. In our study, populations of T. vaporariorum were recorded for the first time from higher altitudes having temperate climate including Almora, Nainital, Bageshwar and Chamoli districts. The finding of T. vaporariorum in all the thirty-two locations, shows the frequent occurrence (100%) and prevalent of GWF in Uttarakhand state compare to the survey in Karnataka, Tamil Nadu and Andhra Pradesh states of India19, Costa Rica33. This study suggests that T. vaporariorum have successfully colonized and spread in the surveyed region of Uttarakhand irrespective of sampled crop in polyhouses as well open fields. In the Indian Himalayan region, incidence of T. vaporariorum have been recorded long back from protected crops of Himachal Pradesh23. The presence of T. vaporariorum may have harmful impact on yield of protected crops grown in the regions due to agility in adaptiveness, colonization in newer habitats and development of insecticidal resistance35.Molecular diversity techniques have been proven useful in unravelling diverse insect pest of agricultural importance including new speciesmtCOI gene sequence amplification found useful for the detection of whitefly species. mtCOI gene have been used as potential marker in the past for discrimination of white fly species complex, evolutionary and genetic diversity study with accuracy and reliability38. The phylogenetic tree reconstructed by retrieving and aligning mtCOI sequences with the expansion of mtCOI supports the relatedness and validity of the molecular identification of collected T. vaporariorum.The mtCOI suggest the high variation with presence of 20 haplotype in the T. vaporariorum populations. Most of the haplotype differs with single nucleotide mutations with their corresponding haplotypes except the haplotype number 1, 13, 15, 16. Haplotype 2 represents the primitive population and most frequent among all haplotypes. This suggests that the most of the populations are descendants of Haplotype 2 populations. Most of the populations are recently introduced in the area and their dispersal agents haven’t had time to disperse. Since these populations are recently introduced, the decision on regular monitoring of these areas may be recommended before the population reaches economic injury level. Presence of twenty haplotype suggests the high diversification among all the haplotypes. However, mtCOI based phylogeny showed the close relation. The obtained results are in consensus with the results of Wainaina et al. and Barboza et al. who reported sampled sequences grouped in monophyletic clade39. Similarly, Despoina et al., 2015 have shown limited sequence divergence among T. vaporariorum populations37. Hence, low level of genetic variation may exist in mtCOI sequences around the world for T. vaporariorum.Population genetic study using T. vaporariorum in Uttarakhand. The host factor and ecological adaptability may be the reason for high abundance in different area33. However, the effect of several other factors such as altitudinal variation, temperature effect, crop cycle, rainfall pattern, wind directions, wind speed, dispersal through planting material and existence of natural population could be explored for future studies to get real scenario and cause of distribution. We have revealed here, the wide distribution pattern of T. vaporariorum on different host at different altitudes exhibiting uniformity in genetic level. The detection of the whitefly population in Uttarakhand state areas may help us to extend surveillance, monitoring and decision making about T. vaporariorum management initiative in the identified areas. Additionally, the present study attracts special attention to study the associated viruses being vectored by T. vaporariorum on different host plants.The result of this study gives fundamental knowledge on understanding of geographical distribution and ecology of Trialeurodes vaporariorum (Westwood) is a serious concern for farming community. The spread of GWF into new area may cause mayhem to the crops. Therefore, regular survey, identification, documentation on geospatial distribution of GWF is urgent need. Present study, suggest the frequent occurrence of GWF from Indian Himalayan states. Population genetic study using mtCOI suggest the high variation with presence of 20 haplotype in the T. vaporariorum populations, where haplotype 2 (H2) was found most dominant. The obtained result draws attention of researchers, policy makers and farmers for pest alertness, decision making research prioritization, development and adoption of sustainable management strategies of GWF to safeguard the crops.Global distribution, polyphagous nature and virus vector potential of Greenhouse whitefly (GWF) A total of 32 greenhouse whitefly samples were collected from Uttarakhand, Himachal Pradesh, New Delhi and Tripura states during 2019–2021 from both protected cultivation systems as well open field conditions Table . Both Th40. Each individual whitefly was properly rinsed in sterile distilled water, crushed and homogenized using a hand-held homogenizer (Sigma Aldrich). 120 μl of CTAB solution  to extract the genomic DNA and ice-cold isopropyl alcohol was used to precipitate the DNA at − 20 °C for 30 min. The DNA pellet obtained after centrifugation at 10,000 rpm for 7 min was washed with 70% chilled ethyl alcohol to remove the excess salts and was suspended in 20 μl of TE buffer. DNase-free RNase A treatment was followed for 20 min at 37 °C to remove the RNA residues. Electrophoresis with 0.8% agarose gel was carried out to visualize intact genomic DNA. Furthermore, the DNA concentration were quantified in Nanodrop (NanoDrop™ 2000/2000c) subsequently used as template for PCR amplification. The segments of mtCOI gene were amplified using pair of universal primers (COX1: LC01490- “5′-GGTCAACAAATCATAAAGATA-3′” and HC02198 “5′-TAAACTTCAGGGTGACCAAAAAA-3′”) with 710 bp product41. The PCR reaction programme was set using 25 µl reaction mixtures including 12.5 µl of ready to use PCR master mix (Promega M750A), 5.5 µl of nuclease free water, 1 µl each of forward and reverse primer and 5 µl of DNA template. The thermo-cycler programme was run with the following cycles; 94 °C for 5 min as initial denaturation followed by 35 cycles of denaturation at 94 °C for 45 s, annealing at 52 °C for 45 s, extension at 72 °C for 45 s and the final extension step for 10 min at 72 °C. The presence of amplified PCR product was visualized and confirmed in the gel documentation system  by 1.2% agarose-EtBr 10 mg/ml gel electrophoresis with 2.5 μl PCR product. Gel elution columns (Sigma) were used for purification of the amplified products of the target gene. The purified products were sequenced directly by an automated DNA sequencer (ABI 377) following manufacturers guidelines for the Big Dye terminator kit (Applied Biosystems).The standard methodology of CTAB as described by Subbanna et al. was followed for extraction of genomic DNA from an individual whitefly specimenmtCOI gene sequence were assembled using Clustal Omega (1.2.2) multiple sequence alignment programme42. The sequences were exported to NCBI and BLASTn similarity search performed with default parameters. All the available whitefly sequences from databases were retrieved and aligned with ClustalW and bases were edited in BioEdit v7.2.5. Phylogeny was estimated with Mega X44 following Kimura 2-parameter model and the maximum likelihood approach. To test the phylogenies, a bootstrap replication of 1000 was performed45. Genbank accessions Bemicia tabaci AY057182.1 was included as outgroups. All the generated sequences from this study have been submitted to the NCBI GenBank with respective accession numbers  are shown next to the branches. Initial tree(s) for the heuristic search were obtained automatically by applying Neighbor-Join and BioNJ algorithms to a matrix of pairwise distances estimated using the Maximum Composite Likelihood (MCL) approach, and then selecting the topology with superior log likelihood value. This analysis involved 50 nucleotide sequences. Codon positions included were 1st + 2nd + 3rd + Noncoding. There was a total of 883 positions in the final dataset. Evolutionary analyses were conducted in MEGA X45.The evolutionary history was inferred by using the Maximum Likelihood method and Tamura-Nei modelT. vaporariorum is not an endangered species that threatens biodiversity. So, no permits were required for collecting it from the field.Supplementary Information 1.Supplementary Information 2.Supplementary Information 3.Supplementary Information 4.Supplementary Information 5.


Globally, genetic testing has become increasingly used over the last two decades. As a result of the rapid development of genetic tests, the Genetic Testing Registry was created in the United States to provide transparent information on genetic tests and the corresponding laboratories. Using publicly available data from the Genetic Testing Registry, we analyzed trends in the availability of genetic tests in the United States over the last decade. As of November 2022, a total of 129,624 and 197,779 genetic tests in the US and globally, respectively, including updated versions of previously existing tests, have been made available and submitted to the genetic testing registry. Over 90% of tests submitted to GTR are for clinical rather than research purposes. Worldwide, 1081 and 6214 new genetic tests had been made available in 2012 and in 2022, respectively. In 2012, only 607 and in 2022, 3097 new genetic tests were made available in the US, with 2016 seeing the biggest increase in availability of new tests during the study period. Over 90% of tests can be used for diagnosis. In the US, 10 of >250 laboratories account for 81% of new genetic tests in GTR. As more genetic tests become available, further international collaboration is required for a comprehensive understanding of the available genetic tests worldwide. Since the completion of the Human Genome Project, the use and development of genetic testing has dramatically increased . PrecisiIn response to the growth in both number and complexity of genetic tests, the Genetic Testing Registry (GTR) was created in 2008 by recommendation from the United States’ Secretary’s Advisory Committee on Genetics, Health, and Society (SACGHS) . GTR wasGTR was developed by the National Center for Biotechnology Information (NCBI) under the guidance of the National Institutes of Health (NIH) and is maintained through a collaborative effort between federal agencies, health care providers, researchers, testing laboratories, advisory groups, insurance companies, and other key stakeholders ,8. SubmiThe objective of this study was to describe the availability of genetic tests in the United States from 2012–2022 through publicly available, downloadable data and through the interactive platform on the GTR website .To accurately examine new and existing tests in the US, we used both publicly available downloadable data and GTR’s interactive webpage .Genetic test submission to the GTR is broken down into three categories: minimal, recommended, and optional . All labFirst, we gathered a baseline understanding of the current genetic test availability worldwide. The GTR website illustrates the current landscape of global genetic tests by offering an interactive database to filter and search for registered tests. To begin, we calculated the total number of genetic tests globally and their relative categories. We then filtered tests by country to generate the total number of current clinical and research tests in the US. We then limited the results to only clinical tests and filtered the database by laboratories to generate the number of laboratories who perform genetic testing. From this filter, we were able to gather the number of tests related to each test purpose category. Finally, we compared the results from the interactive database to those from the downloadable dataset.We then downloaded a publicly available, comprehensive dataset including all currently existing genetic tests on the registry . First, GTR accepts genetic test submissions worldwide and indicates where each genetic test is developed. Once published on the registry, genetic tests are given a unique identifying number in the format “GTR000000000.x”. The number after the decimal relates to the test version, as tests are edited and updated over time. We then limited the dataset to include only first versions of each test to create a time trend analysis of new genetic tests in the United States.We were also interested in understanding the number of laboratories creating new genetic tests. Using the laboratory’s corresponding CLIA number, we calculated the number of new and current tests developed by each laboratory. CLIA certification relates to the type of testing performed at each laboratory. To receive CLIA certification, genetic tests must be evaluated for analytic validity; clinical validity; clinical utility; and for ethical, legal, and social implications . LaboratFinally, we linked the summary dataset with each genetic test purpose category to examine the number of newly introduced and current tests per purpose category. We then separated the tests by clinical or research test type to further understand the use of current genetic tests. Because some tests can be used for multiple purposes, the test purpose categories are not mutually exclusive. However, the purpose categories provide insight into how genetic testing may be used.As of November 2022, there were 76,326 current genetic tests on GTR worldwide., where 76,083 (99.7%) tests were clinical and 243 (0.3%) were for research purposes. Of the 76,326 current tests, 37,289 (48.91%) belonged to laboratories in the US; 37,124 (99.56%) and 165 (0.44%) tests were for clinical and research purposes, respectively.In the US, 200 laboratories performed 37,124 current clinical tests on the interactive database; 29 laboratories performed whole exome sequencing (WES) and 17 laboratories performed whole genome sequencing (WGS).Worldwide, a total of 197,779 genetic tests were developed and submitted to the genetic testing registry as of November 2022, including updated versions of previously existing tests. In the US, a total of 129,624 genetic tests were developed and submitted to the genetic testing registry as of November 2022, including updated versions of previously existing tests. Genetic tests in the US account for about 66% of all genetic tests and subsequent versions on GTR.Each year, laboratories improve many of their existing tests and discontinue older versions. As of November 2022, there were 76,302 and 37,271 current genetic tests worldwide and in the US, respectively. Worldwide, 1081 new genetic tests were made available in 2012 and, cumulatively, there were a total of 106,007 new genetic tests introduced and registered in GTR between January 2012 and November 2022. Over the past 10 years, a total of 51,803 new genetic tests were made available in the US, an increase from the 607 new genetic tests in 2012. In the publicly available datasets, test type is not indicated for every iteration of test. Of 51,803 new genetic tests, 13,315 had a clinical or research indication. Of those tests, 13,276 (99.7%) were clinical and 39 (0.3%) were for research. Of the 51,803 new genetic tests, 92.93% of these  were developed by 31 CLIA-certified laboratories and 80.79%  were developed by only 10 CLIA-certified laboratories across the US.From 2012 to 2022, 32,185 (62.13%) new genetic tests registered to the GTR in the US are diagnostic. Diagnosis is the largest genetic test purpose category on the registry. After diagnosis, 5646 (10.9%) new genetic tests are for risk assessment, 5410 (10.4%) new genetic tests are for pre-symptomatic testing, and 5370 (10.4%) are for screening. Each year, new tests for different purposes are introduced, and This is a longitudinal study describing the trends in newly available and current genetic tests in the United States from 2012 to 2022. The number of new genetic tests increased from 607 tests in 2012 to 51,803 tests in 2022. The largest increase in new genetic tests was between 2015 and 2016 when 21,952 genetic tests were developed and added to GTR. Of the 21,952 new tests introduced in 2016, 19,561 were from Fulgent Clinical Diagnostics and their associated labs. Fulgent Clinical Diagnostics is one of 10 labs performing over 80% of all genetic tests in the US.We found a significant shift in genetic test purpose in the US throughout our study period. Among all pre-symptomatic tests, 66.97% were introduced between 2012–2015. Similarly for tests for risk assessment and for screening, more than half were made available between 2012–2015 . Less than half of these tests were made available in more recent years: 33.03%, 39.35%, and 44.16% of pre-symptomatic tests, risk assessment tests, and screening, respectively, between 2016 and 2022. In contrast, of all the diagnostic tests, only 26.63% were made available between 2012 and 2015 compared with 73.37% between 2016 and 2022. This trend mirrors the global trend in overall diagnostic testing. Because of external factors such as an ageing population and the increased prevalence of chronic and infectious disease, in conjunction with scientific advances in diagnostic testing, the global diagnostic test industry is expected to have a compound annual growth rate of 8.63% by 2030 . The oveThe increase in genetic test availability and use in the US is not wavering. In January 2015, President Barack Obama launched a Precision Medicine Initiative investing $215 million dollars (USD) to support research, development, and innovation of precision medicine . The samOne strength of this study is very little research has been conducted using the genetic testing registry database that captures test information from the US and worldwide. Our analysis provided critical insight into the patterns of genetic test availability in the last decade and identified that the development and availability of diagnostic tests dominated the global market in recent years. Future research using this publicly available data can provide insight into possible gaps in test availability. In contrast, there are some limitations worth discussing. Our results may underestimate the total counts of available genetic tests given the voluntary nature of the database, and very likely underestimate available genetic tests in other countries. Nevertheless, genetic testing availability has undoubtedly exploded in the last decade, even if our analysis likely underestimated the magnitude of this growth because of the incomplete capture of tests by the GTR database.In the US, only specified federal agencies considered “regulatory” can require organizations to provide information and adhere to policies set forth by the agency. The National Institutes of Health (NIH) is not a regulatory agency and thus cannot require laboratories to submit genetic test data. When a laboratory does choose to submit genetic test data, they are not required to complete all portions of the submission application. Each application is separated into three parts—minimal, recommended, and optional. Laboratories are only required to fill out the minimally required information, which may result in incomplete data.Moreover, the GTR database is not confirmed by the NIH. Test submitters are required to adhere to a code of conduct regulated by the NIH, and the NIH has incorporated quality assurance measures to ensure accurate information. Despite these measures, however, genetic test data may be inaccurate or incomplete. Finally, although the database provides health care providers and patients with a tool to better understand the available genetic tests, its data are ultimately incomplete given its voluntary nature. This analysis likely underestimates the magnitude in which genetic tests exist in the US, but undoubtedly genetic testing availability has exploded in the last decade. Mandatory reporting from labs and greater international collaboration are needed for a better understanding of the genetic testing availability in the US and globally, and for identifying gaps in testing development.An increasing number and range of genetic tests have been made available in the US and worldwide between 2012 and 2022, based on our analysis of the Genetic Testing Registry, a voluntary database created by the NIH. The US accounts for over 60% of the tests registered on GTR. Most of the tests registered on GTR are for clinical purposes. Over 90% of available genetic tests can be used for diagnosis, with huge increases in such tests since 2016. In the US, 10 of >250 laboratories account for 81% of new tests in GTR. As more genetic tests become available, required test reporting to GTR is needed for a clear understanding of the genetic testing landscape. Further international collaboration is required for a greater understanding of the available genetic tests worldwide.


However, little is known about their connection to early Holocene hunter-gatherers, how this may have contributed to different historical pathways and the processes through which late Holocene ceramists came to rule the coast shortly before European contact. To contribute to our understanding of the population history of indigenous societies on the eastern coast of South America, we produced genome-wide data from 34 ancient individuals as early as 10,000 yr bp from four different regions in Brazil. Early Holocene hunter-gatherers were found to lack shared genetic drift among themselves and with later populations from eastern South America, suggesting that they derived from a common radiation and did not contribute substantially to later coastal groups. Our analyses show genetic heterogeneity among contemporaneous Sambaqui groups from the southeastern and southern Brazilian coast, contrary to the similarity expressed in the archaeological record. The complex history of intercultural contact between inland horticulturists and coastal populations becomes genetically evident during the final horizon of Sambaqui societies, from around 2,200 yr bp, corroborating evidence of cultural change.Sambaqui (shellmound) societies are among the most intriguing archaeological phenomena in pre-colonial South America, extending from approximately 8,000 to 1,000 years before present (yr  The authors report genome-wide data from 34 ancient individuals spanning the Holocene, from what is now Brazil, illuminating connections and disjoints between Sambaqui shellmound societies and preceding and later peoples. Sambaquis are the product of planned and long-term deposition of shells, fish remains, plants, artefacts, combustion debris and local sediments, and they were used as territorial markers, dwellings, cemeteries and/or ceremonial sites. On the southern Brazilian coast, funerary shellmounds can reach monumental heights (of up to 30 metres) and often contain hundreds of human burials, suggesting a high demographic density unparalleled in the South American lowlands11. In a singular enclave south of São Paulo State, further inland from the coast , sambaqui sites are within the Atlantic Forest15. Here there is evidence of early Holocene settlement in the riverine sambaqui of Capelinha, as revealed by a male individual directly dated to ~10,400 years before present (yr bp) 10. This individual was named ‘Luzio’, as a reference to ‘Luzia’, a final Pleistocene female skeleton found in the Lagoa Santa region in east-central Brazil17. Both individuals are at the centre of long-lasting debates for exhibiting the so-called paleoamerican cranial morphology that differs from that of present-day indigenous peoples18. The earliest evidence of human settlement on the Atlantic coast starts between ~8,700 and 7,000 yr bp with an intensification of sambaqui construction between 5,500 yr bp and 2,200 yr bp19. The relationship between riverine and coastal sambaquis is still a matter of debate, although bioarchaeological studies point towards a biological link23, and some researchers suggest a late Pleistocene/early Holocene cultural connection that faded through time27.The settlement of the Atlantic coast by maritime societies is a central topic in South American archaeology. Across ~3,000 km of the coast of Brazil, semi-sedentary populations, with seemingly large demography, produced thousands of shellmounds and shell middens, locally known as sambaquis , for over 7,000 years. Subsistence was based on a mixed economy, combining aquatic resources and plants, complemented by hunting of terrestrial mammals and horticulture31. This abrupt change in the archaeological record is concomitant with environmental and ecological changes related to coastal regression and climatic events36 that had an irreversible impact on the availability of key resources. Between 1,200 and 900 years ago, thin-walled non-decorated pottery (Taquara-Itararé tradition) appeared for the first time on the southern Brazilian coast39. The makers of Taquara-Itararé ceramics were horticulturists that arrived in the southern Brazilian highlands about 3,000 years ago, lived in pit houses and cremated their dead in funerary mounds. They are considered to be the ancestors of present-day Jê-speaking indigenous peoples of southern Brazil , a language family of the Macro-Jê stock43. The dispersal of Taquara-Itarare ceramics on the southern coast was first interpreted as resulting from the demographic expansion of inland horticulturists. However, evidence points to a complex scenario of social interaction between inland and coastal populations, with changes in funerary practices and post-marital residence patterns after the introduction of ceramics, biological continuity and maintenance of mobility patterns , persistence in the exploitation of aquatic resources, and development of sophisticated fishing technologies49. Ceramics appear in the southeast coast about 2,000 years ago but are associated with the Una tradition, also probably produced by speakers of the Macro-Jê language stock51.The disappearance of Sambaqui societies started 2,000 years ago, when funerary fishmounds replaced shellmounds in the territory where they previously thrived57. While on the southern coast of Brazil a late Tupi-Guarani chronology is well defined52, on the southeast coast a much earlier arrival  has been proposed on the basis of the archaeological record of the Araruama region (Rio de Janeiro State)60. European colonists encountered thousands of Tupi-Guarani peoples both on the Atlantic coast and along major rivers and their tributaries in southern Brazil and northeastern Argentina . The Tupi-Guarani produced painted ceramics (red and black on white painting), applied a diversity of plastic decorations and made pots with complex and composite contours that are archaeologically defined as Tupiguarani, Tupinambá and Guarani, depending on the geographical location61.Shortly after the appearance of southern proto-Jê ceramics, another major transformation occurred on the Atlantic coast. This is documented by the arrival of speakers of the Tupi-Guarani language family (of the Tupi stock), a forest-farming culture who migrated from southern Amazonia more than 2,500 years ago in one of the largest expansion events in the indigenous history of South America. Although still a matter of debate, the Tupi-Guarani would have dispersed southwards from southwestern Amazonia (homeland of the Tupi stock) across the core of South America, reaching the La Plata basin, and almost simultaneously from southeastern Amazonia across the Atlantic coast of Brazil63. Early Holocene individuals from Lapa do Santo in the Lagoa Santa region, dated between ~9,800 and 9,200 yr bp, carried a distinct affinity to the oldest North American genome, which is associated with the Clovis cultural complex 64. A genetic signal of 3–5% Australasian ancestry—known as the Population Y signal—was found in present-day indigenous individuals from southwestern Amazonia, Central Brazil and the northwestern South American coast66 and in one early Holocene individual from Lapa do Sumidouro 62. However, this signal was not detected in the early Holocene burials from Lapa do Santo, located only four kilometres from Lapa do Sumidouro63. The complete absence of ancient DNA data for Amazonia and Northeast Brazil and the low-coverage data from the south/southeast Brazilian coast have prevented an assessment of whether the Population Y signal survived in those regions through time.Ancient DNA data from Brazil are still very sparse, with only 19 published individuals with analysable genomic coverage63. The analysed Jabuticabeira II individuals carried a significant affinity to present-day Kaingang (Jê speaking) from the southern Brazilian highlands. Although based on low-coverage genome-wide data, this supports a shared ancestry between the Sambaqui societies and the speakers of proto-Jê63.Regarding Sambaqui societies, three previously published middle Holocene individuals from Laranjal and Moraes (both riverine shellmounds from the southeast coast of Brazil) and five individuals from the late Holocene site of Jabuticabeira II  showed some level of genetic continuity with present-day indigenous populationsbp and the appearance of ceramics associated with an intensification of contacts with inland populations? Finally, are there genetic connections between Sambaqui groups and other archaeological and present-day indigenous populations from Amazonia and central and northeastern Brazil?The long-term permanence, cultural similarity and rapid disappearance of Sambaqui societies, plus their archaeological and seemingly genetic disconnection from early Holocene hunter-gatherers, raise numerous questions about their origins and demographic history. First, were Sambaqui individuals genetically different from hunter-gatherers from the hinterland ? Second, were the riverine Sambaqui groups genetically related to the ones on coastal sites? Third, was there genetic homogeneity across Sambaqui groups from the south and southeast coast of Brazil? Fourth, was the demise of sambaqui construction after 2,000 yr 67. We also captured the entire mitochondrial genome (mtDNA) to assign mtDNA haplogroups and to estimate contamination levels, which were found to be low for all cases (<2%). Nuclear DNA contamination estimated for 20 male individuals on the basis of X-chromosome heterozygosity levels68 was also low (<3.5%). Principal component analysis (PCA) and a cluster analysis including worldwide populations further confirmed that all individuals fall within Native American genetic diversity  . Conversely, the Lapa do Santo_9600BP and Sumidouro_10100BP groups share a higher genetic affinity with each other than with any other ancient Brazilian group  . The morphological similarity of this male individual to paleoamerican features observed in early Holocene groups from the Lagoa Santa region, and the chronological gap of almost 3,000 years with other burials from the same site, call into question his association with riverine Sambaqui societies69 to estimate the minimum number of streams of ancestry necessary to explain the genetic variation observed among early Holocene hunter-gatherers across South America. Our results show that Capelinha_10400BP and Loca do Suin_9100BP cannot be distinguished from other early Holocene populations as part of a distinct wave of ancestry (P > 0.01) , while the other tested groups show different proportions without reaching significance  and Moraes 63 , located in the State of Espírito Santo. The south coast Sambaqui are represented by individuals from three shellmounds—Jabuticabeira II , Cabeçuda  and Cubatão I —and one individual from the fishmound Galheta IV , representing the final horizon of Sambaqui societies.To investigate the affinities between riverine and coastal Sambaqui groups, we analysed our newly produced data alongside previously published individuals from the riverine sambaquis Laranjal  > 0). Individuals from the riverine sites also show genetic similarities to individuals from the southern coastal sambaquis of Cubatão I (CubatãoI_2700BP), Cabeçuda (Cabeçuda_3200BP) and Jabuticabeira II (JabuticabeiraII_~2400BP), indicating some level of genetic continuity through time between riverine shellmound builders and Sambaqui societies from the southern coast. Interestingly, this genetic similarity is not observed between the riverine shellmounds and the sambaqui do Limão, located further north ; and (3) the most recent individual, dated to ~1,300 yr bp (JabuticabeiraII_102_1300BP). This skeleton was found in the topmost shell deposit and exhibited a different funerary pattern from the older burials, including an extended rather than a flexed position and the absence of grave goods  ~ 0 (Z = 0.47).To improve our knowledge on the genetic interactions among Sambaqui groups, we co-analysed all individuals from the five coastal sites, which are located up to 1,500 km apart along the southeast and south coasts  the oldest individual (Limão_2700BP), (2) a cluster of four temporally intermediate individuals (Limão_~1900BP) and (3) the most recent individual (Limão_500BP). The Limão_~1900BP group shows the highest genetic affinities to Limão_2700BP and to a possibly early to middle Holocene hunter-gatherer from the northeastern site of Pedra do Alexandre (Pedra Do Alexandre2_undated)71 , showing distinctive affinity with present-day southern Kaingang; and (2) the Human Origins dataset73.The significance of Taquara-Itararé ceramics (associated with proto-Jê speakers) at coastal sites after the final horizon of sambaqui construction has been at the centre of recent academic debates. According to some scholars, an intensification in contacts with proto-Jê-speaking groups after ~2,000 yr f4 tests: (1) f4 and (2) f4. The results from the first test reveal an excess of genetic similarity between present-day Kaingang and JabuticabeiraII_102_1300BP. The second test expands this finding by showing that JabuticaberiaII_111/112_~2200BP and even more so JabuticabeiraII_102_1300BP are genetically closer to present-day and twentieth-century Kaingang, when compared with not only the JabuticabeiraII_~2400BP group but also the Taquara-Itararé-pottery-associated GalhetaIV_1200BP individual  also points at a different provenance for this female individual, possibly from another coastal location, when compared with the JabuticabeiraII_~2400BP group   revealed that all Sambaqui individuals show a significant genetic attraction to the Xavánte (Jê-speaking) in contrast to the other available indigenous populations   (|Z| < 1.71). This suggests that the specific Jê-related ancestry contributing to southern Sambaqui groups is missing in our ancient and present-day genetic dataset. More genomic data from other Jê-speaking groups are needed to accurately assign a specific genetic contribution.With the Human Origins dataset, we first expanded the previous findings using ics Fig. . Moreove59. While we cannot determine the exact arrival time of this ancestry, its absence in the older groups from sambaqui do Limão (Limão_2700BP and Limão_~1900BP) indicates that it occurred after the initial settlement of the site by Sambaqui groups.The Limão_~1900BP individuals also show genetic affinity to the present-day Jê-speaking groups from central Brazil (Xavánte) when compared with other linguistic families, such as Karib (Arara and Aparai) or Tupi . Interestingly, we observed a genetic link between the latest burial at the site, Limão_500BP, and the Zoró (a population related to the Tupi-Mondé language) in comparison to other present-day Tupi-speaking peoples  Fig. . This sp76, and the latter is associated with the Koriabo tradition , a late pre-colonial/early colonial archaeological culture  that may represent the southernmost Karib expansion in South America63.To investigate the chronological depth of the shared ancestry between Sambaqui and Jê-, Tupi- and Karib-speaking groups, we sequenced individuals from late Holocene archaeological sites in the Cerrado of northeastern Brazil and the lower Amazon Forest. The former is associated with the Una tradition (Vau_Una_600BP), a ceramic type made by horticulturists that occupied a vast territory in central and northeastern Brazilf4 tests on Vau_Una_600BP and present-day Native American populations from the Human Origins dataset show strong evidence of genetic similarities between the Una-context individual and Xavánte, when compared with Tupi  and Karib populations  , indicating some level of shared genetic drift in the most recent past.f4 statistics of the form f465. The only ancient Brazilian group showing significant affinity to Onge, compared with present-day Mexicans, is the JabuticabeiraII_~2400BP group. The signal is mainly driven by one individual , but it remains for the entire group even after the exclusion of JBT009. Similarly, there is significant genetic attraction between Onge and one individual from the Cabeçuda_3200BP group , while all other tests do not reach values close to significance . Only the JabuticabeiraII_~2400BP group reaches significant attraction to both Onge and Papuans, and only in comparison to LapaDoSanto_9600BP (ref. 63). This suggests either that the Population Y signal is equally widespread in most tested ancient individuals from Brazil or that previously reported attractions to non-American ancestries78 are exacerbated by the use of present-day Mexican populations in comparison to ancient groups  (Supplementary Data 63). This pattern of uniparental markers, considered alongside the generally low pairwise mismatch rate, could be compatible with a scenario of consanguinity among Jabuticabeira II individuals  in the JabuticabeiraII_~2400BP group, suggesting a smaller effective population size  than for younger burials from the same site  show lower heterozygosity levels than those at the southeast coast site (sambaqui do Limão) and even lower than late Sambaqui individuals from the south coast  Fig. . The inc63. However, we caution that this result could be affected by the lack of statistical power, and another potential scenario would involve early South American settlers carrying different proportions of this genetic component. Additional genomes from other regions of South America would be necessary to assess whether populations carrying Anzick-1-related ancestry were replaced by or intermixed with other early Holocene groups.The oldest individual newly sequenced in this study, Capelinha_10400BP, does not carry a distinct genetic similarity to any other early Holocene or younger populations but shows a generalized affinity to ancient Brazilian and present-day South American groups. This suggests that his source population had a basal placement among the initial radiation event into South America. Moreover, both Capelinha_10400BP and Sumidouro_10100BP lack a significant affinity to Anzick-1-related ancestry  are strongly related, confirming a local genetic structurebp and ~1,300 yr bp) display an incremental genetic attraction to southern Jê ancestry represented by both recent and present-day Kaingang , a fishmound with Taquara-Itararé ceramics, is genetically similar to the JabuticabeiraII_~2400BP group and Cabeçuda_3200BP. This suggests some level of demic continuity after the arrival of ceramics in the region , Instituto de Biociências da Universidade de São Paulo, Superintendência no Espírito Santo do Instituto do Patrimônio Histórico e Artístico Nacional, Universidade Federal do Amapá, Museu Amazônico da Universidade Federal do Amazonas, Museu Paraense Emílio Goeldi, Scientia Consultoria Científica, Museu de Arqueologia do Xingó da Universidade Federal de Sergipe, Museu Arqueológico do Carste do Alto São Francisco, Grupo de Pesquisa em Educação Patrimonial e Arqueologia, Instituto Goiano de Pré-História e Antropologia da Pontifícia Universidade Católica de Goiás, Museu Histórico de Lins, and Universidade Federal de Pernambuco.For the early twentieth-century sample originating from a Kaingang funerary context , we reached out for approval to the indigenous community at TI Vanuíre, an Indigenous Land recognized by the 1988 Brazilian Constitution that is located ~65 km from the archaeological burial mound (The present study is part of a collaborative agreement between the Max Planck Institute for Evolutionary Anthropology (MPI) and the University of São Paulo. The collaboration includes the training of Brazilian students by the MPI staff in techniques of extraction and analysis of ancient DNA. The agreement also includes the establishment of an ancient DNA laboratory at USP under the technical guidance of the MPI and financed by the Fundação de Amparo à Pesquisa do Estado de São Paulo. A Max Planck Partner Group was established by A. Strauss to fund early career researchers working in the ancient DNA laboratory at USP.84. We sampled 82 skeletal elements from 24 sites: Capelinha (4), Cabeçuda (4), Cubatão I (5), Sambaqui do Limão (11), Estreito (1), Galheta IV (5), Hatahara (1), Jabuticabeira II (21), Jêrimum (2), Justino (4), Lapa do Santo (2), Laranjal (2), Loca do Suin (4), Moraes (3), Palmeiras-Xingu (2), Pavão XVI (1), São José II (1), Pedra do Alexandre (2), Marajoara Anthropomorphic Urn t-8 (1), Gruta das Caretas (1), Marabaixo-Macapá (AP) (1), Ramuse Nóbrega (GO-RS-01) (1), Kaingang burials (2) and Vau-Una (1)  and 75 μl of H2O and rotated for 14–16 hours at 37 °C. The extraction lysates were transferred into a new tube and mixed with 10 ml of binding buffer  and 400 µl sodium acetate. The solution was spanned through into silica columns for high volumes  and purified using the wash buffer provided in the kit. The purified DNA was then eluted in 2 × 50 μl of Tris-EDTA-Tween (TE buffer and 0.05% Tween 20), and the DNA extracts were stored at −20 °C (ref. 85).The collected bone/dentin powders were digested using 25 μl of 0.25 mg ml87. The libraries were indexed using a unique combination of two indexes that were incorporated into the library molecules as a sample-specific DNA barcode88. The indexed libraries of each sample were then amplified using different PCR cycles to reach 1.5 × 1013 copies. The amplified products were then purified using MinElute spin columns following the manufacturer’s protocol and quantified on the Agilent 4200 TapeStation System. The quantified indexed libraries were pooled equimolarly to reach 10 nM, and shallow shotgun sequencing was performed on Illumina NextSeq500 or HiSeq 4000 instruments.We produced double-stranded libraries treated with uracil-DNA glycosylase (UDG) using 25 μl of extract in 50 µl per reaction 89). Sequencing quality filtering (min. 20), length filtering (min. 30 bp) and adapter clipping (min. 1 bp) were performed with AdapterRemoval v.2 (ref. 90). The resulting reads were mapped against the human genome reference hg19 with the Burrows–Wheeler aligner91, duplicated reads were masked using MarkDuplicates (Picard) and damage patterns were calculated with mapDamage2.0 (ref. 92).The shallow shotgun sequencing data were used to estimate the preservation of ancient DNA extracted from the archaeological skeletal remains. A percentage of endogenous human DNA above 0.1% and DNA damage at the molecule termini of above 5% were used as authenticity criteria, estimated using the software EAGER v.1.92.55  and dnaClust v.3.0.0 (ref. 93).After shallow shotgun screening, libraries with values above the previously described thresholds were re-amplified and captured for ~1.24 million SNPs across the human genome (1240k SNP capture) and the entire mtDNA91. Damage pattern, coverage depth and DNA capture efficiency were estimated using published tools integrated within the EAGER pipeline89. We measured the level of X-chromosome contamination using ANGSD68 for male individuals and mtDNA contamination using schmutzi94 for all individuals . We trimmed three base pairs at both ends of the reads for the double-stranded UDG-half libraries. After independent calls on the untrimmed and trimmed sets, we combined the genotype calls, selecting transitions from the trimmed genotype files and transversions from the untrimmed ones. Since the published individuals from Lapa do Sumidouro were processed using a library protocol without UDG treatment65, we processed the bam files separately, calling only transversions from the untrimmed data. We excluded 4 individuals with less than 40,000 SNPs overlapping the 1240k panel for a total of 34 individuals with newly generated genome-wide data usable for further analyses.Genotype calls were performed using pileupCaller96 on the 1240k dataset. All ancient individuals from Brazil fall in a cluster with present-day Native Americans, which also includes the ancient Central and South American individuals published in Posth et al.63  1240k Allen Ancient DNA Resource v.32.7, (2) the Illumina panel72 and (3) the Human Origins panel98 (Supplementary Data f statistics were performed using the Mbuti population from Africa with diploid genotypes (.DG) as the outgroup.We created three datasets for genome-wide analyses combining the newly and previously generated data from ancient Brazilian individualsf3 outgroup statistics 69.To assess genetic affinities among ancient groups and between ancient groups and present-day indigenous populations from Brazil, we measured shared genetic drift using f4 statistics 69 in the forms f4 and f4, where X represents the tested present-day or ancient Brazilian individuals/groups. The 1240k dataset was used to investigate the affinities among ancient Brazilian individuals/groups. The Illumina and Human Origins panels were used to describe the genetic affinities with present-day groups  with the following formula:To investigate the proportion of Anzick-1-related ancestry  in the ancient South American genomes, we calculated 69 with the following settings: allSNPs, YES; significance threshold, ‘taildiff’ < 0.01. The left population was a combination of different pairs of ancient individuals/groups. The first set of right populations was previously used in Posth et al.63 and consisted of Mbuti.DG, Onge.DG, French.DG, Han.DG, Russia_MA1.SG and USA_Anzick.SG. Furthermore, we included additional shotgun data  and present-day Mexican groups (Zapotec and Mixe). To identify an informative set of right populations, we prepared an array of comparisons using different combinations. We started with a set of outgroups composed of non-Native Americans and Anzick-1 (outgroup 1) and progressively added one individual or group at the time to this growing list, estimating each time the minimum number of streams of ancestry. The most informative combination of right populations to distinguish the genetic ancestry of the analysed ancient individuals/groups is presented in Supplementary Data We also tested the minimum number of streams of ancestry necessary to explain the genetic variation observed in the South American ancient genome-wide data. The tests were computed using qpWave software100. To reconstruct the mtDNA consensus sequences, we applied four quality thresholds  to the likelihood estimated for each position by schmutzi. We used the YhaploCaller101 to assign Y-chromosome haplogroups followed by manual checking to verify the called SNPs for each male individual.To gain an overview of the mtDNA diversity of ancient individuals from Brazil, we produced mtDNA capture data for each sample, and we assigned mtDNA haplogroups using Haplogrep 2.0 and HaplofindFST presented in Extended Data Fig. 102) and manually inspected/edited. The mtDNA indels and mutational hotspots under the nucleotide positions 309.1C(C), 315.1C, AC indels at 515–522, 16182C, 16183C, 16193.1C(C) and C16519T (ref. 103) were removed from the alignment.The pairwise 95 to produce pseudo-diploid genotype calls and calculated using the ratio between the number of sites in heterozygosity and the total number of covered sites, multiplied by two. The individual values were grouped in three broad regions/temporal intervals. To investigate the magnitude of the differences in the heterozygosity levels, we performed the non-parametric Kruskal–Wallis test. Conover’s post-hoc analysis was performed to determine the differences between groups using a correction for multiple comparisons (R v.3.6.0 tidyverse104 and conover.test105 packages)  Fig. .80 to estimate the length of segments in homozygosity for individuals with coverage higher than 190,000 SNPs , freeze-dried and combusted to CO2 in an elemental analyser. The CO2 was catalytically converted to graphite, and the dating was performed using a MICADAS-AMS machine. The resulting 14C ages were normalized to d13C = −25‰ and calibrated using OxCal v.4.4 software110 with the SHCal20 curve111  of skeletal material is commonly used to detect geographic provenance and mobility among mammals, including humans113. The tooth enamel records the isotopic signal of when it was formed during the earliest stages of life, whereas the bone isotopic signal reflects a period closer to the time of death of the individual114. Since the radiogenic isotope 87Sr forms by radioactive decay from rubidium (87Rb), the 87Sr/86Sr signature of a specific location is determined by the underlying bedrock age and its content of Rb115. A specific geological strontium signature is incorporated into the hard body tissues by direct substitution for calcium116 since strontium enters the ecosystem without fractionation117.Strontium isotopic analysis  regression equation built with SRM987 standard from NIST . Strontium was isolated with 200μl of Eichrom Sr.Spec resin loaded in Bio-Spin Disposable Chromatography Bio-Rad Columns following the method of (ref. 119). The separated strontium fraction for each sample was dried down, dissolved in 2 ml 0.2% bi-distilled HNO3 and diluted to 200 ppb Sr concentrations for isotope analysis. 87Sr/86Sr ratios were measured using a NuPlasma HR multicollector inductively-coupled-plasma mass spectrometer (MC-ICP-MS). Sample analyses were referenced to bracketing analyses of SRM987, using a 87Sr/86Sr reference value of 0.710255 from NIST. All strontium isotope data are corrected for isobaric rubidium interference at 87 amu using the measured signal for 85Rb and the natural 85Rb/87Rb ratio. Instrumental mass fractionation was corrected using the measured 86Sr/88Sr ratio and the exponential law, and a true 86Sr/88Sr value of 0.1194 (ref. 120). Results for repeat analyses of an in-house carbonate standard  and an in-house ocean island basalt standard  processed and measured with the batches of samples in this study are in agreement with long-term results for these two in-house standards  . For every two batches one blank was added to assess the cleanness of the process; there was no peak and, thus, no contamination from external Sr in any of the batches. The 87Sr/86Sr values from the Jabuticabeira II individuals have an average of 0.710 ± 0.006 (1σ), with minimum and maximum values of 0.709 and 0.711. These values are within the range of sea water and within the range previously established for other shellmound individuals from the southern coast of Brazil121, indicating that all analysed individuals grew up in a coastal environment. Nevertheless, the average 87Sr/86Sr ratios differ for the three genetic groups identified at Jabuticabeira II. The 87Sr/86Sr ratio increases over time with averages of 0.7095 ± 0.000096 (n = 7) for the JabuticabeiraII_~2400BP group, 0.7104 ± 0.00025 (n = 2) for JabuticabeiraII_111/112_~2200BP and 0.7111 (n = 1) for JabuticabeiraII_1300BP.We measured the bp; middle Holocene, ~7,000–4,000 yr bp; and late Holocene, ~4,000–0 yr bp), cultural assemblages  and geographical regions .The terminology used here to classify ancient Brazilian societies does not represent the entire diversity of indigenous peoples in the country, nor should it be understood as reflecting a shared identity. The archaeological information indicates a complex demographic history (see The cultural assemblages are part of a diverse record of pre-Columbian material culture and help contextualize the settlement of the southern and southeastern Brazilian coast. The term ‘tradition’ is applied in Brazilian archaeology to refer to common technological and stylistic traits in the production of ceramics with chronological persistence in the archaeological record. The ceramic traditions from the late Holocene are directly associated with present-day ethnolinguistic groups and represent a putative connection between ancient individuals and present-day indigenous peoples. However, the present-day populations in our dataset represent only a small fraction of the diversity of indigenous peoples currently living in Brazil.Further information on research design is available in the Supplementary InformationSupplementary Discussion, Figs. 1–15 and Tables 1–40.Reporting SummarySupplementary Data 1Archaeological information, radiocarbon dating and ancient DNA summary statistics.Supplementary Data 2f4 and f3 outgroup statistics 1240k dataset.Supplementary Data 3qpWave analysis.Supplementary Data 4Anzick-1-related affinity.Supplementary Data 5f4 statistics Human Origins and Illumina datasets.Supplementary Data 6Zoro-related affinity.Supplementary Data 7Population Y tests.Supplementary Data 81240k and Human Origins comparative datasets.Supplementary Data 9Pairwise mismatch rate results.Supplementary Data 10Details radiocarbon dating.