Mixornis gularis, in the heavily urbanized island of Singapore to determine if two centuries of fragmentation have led to signs of isolation and loss of population-genetic diversity in different parts of the island. We obtained a high-quality complete reference genome with 78x coverage. Using almost 4000 SNPs from double-digest RAD-Sequencing across 46 individuals, we found that the population has likely experienced a recent contraction in effective population size and presently exhibits low population genetic diversity. Using empirical and simulation-based landscape genomic analyses, we also found that the subtle population genetic structure observed in the Striped Tit-Babbler population in Singapore is likely driven by isolation by distance resulting from limited dispersal. Our results demonstrate that population genetic impoverishment and subdivision can accumulate at relatively rapid rates in edge-tolerant bird species such as the Striped Tit-Babbler as a result of fragmentation, and that subtle spatial genetic structure can be detected over fine spatial and temporal scales using relatively few multilocus genomic SNPs.Although edge-tolerant species are known to benefit from habitat fragmentation, less is known about the population genetic impacts fragmentation may exert on edge-tolerant species. We examined the landscape genomic structure of an edge-tolerant forest-dependent bird species, the Striped Tit-Babbler  Organisms living in fragmented landscapes experience reduced gene flow between remnant habitat patches4, which may result in reduced genetic diversity, increased likelihood of inbreeding depression, higher susceptibility to stochastic environmental change, and an elevated risk of localised extirpation4.Anthropogenic habitat fragmentation is a key driver of biodiversity loss worldwide8. Sensitive species often go rapidly extinct after initial habitat loss, followed by the gradual decline of less sensitive species due to the effects of isolation and other ecological factors12. Assessing and predicting fragmentation impacts is therefore challenging as organisms respond differentially depending on their life history traits, as well as the spatial and temporal scale of fragmentation.The time lag between physical fragmentation and the manifestation of deleterious effects and localised extirpation results in fragmented landscapes incurring an extinction debt that may only be realised after decades16 – few have explored the population genetic impacts of fragmentation on these ostensibly resilient species, especially at fine spatial and temporal scales . The time lag between fragmentation and the detection of its effects, compounded by the relative abundance of edge-tolerant species, may result in (1) allele frequency-based efforts using few marker loci failing to detect subtle signals of isolation and genetic divergence at shallow temporal and spatial scales and (2) edge-tolerant species being overlooked in long-term conservation plans.While edge-tolerant species are assumed to be well-adapted to habitat fragmentation – many studies show a positive correlation between the abundance of edge-tolerant species and fragmentation effects18 with whole-genome sequencing and individual-based landscape genomic approaches20 to investigate the impact of fragmentation on the population genetic structure of an abundant edge-tolerant passerine, the Striped Tit-Babbler (Mixornis gularis), in Singapore. A highly social insectivore, the Striped Tit-Babbler is a widespread resident of dense scrub and secondary woodland habitats across Southeast Asia21. Its affinity for disturbed and degraded habitats means that the species is abundant across its range and is not considered a species of conservation concern22. Although little is known about the species’ breeding or dispersal ecology, it is thought that the Striped Tit-Babbler breeds cooperatively23, and like other babblers  is a weak disperser on account of its short wings and sedentary habits24, which should increase the species’ susceptibility to fragmentation. The city-state of Singapore provides an ideal landscape for investigating this owing to its history of intensive habitat fragmentation spanning approximately 200 years, with agriculture-driven fragmentation dominating for the first 150 years, followed by urbanisation-driven secondary fragmentation25. This has given rise to a heterogeneous landscape consisting primarily of a heavily streetscaped urban matrix with young and maturing secondary forest fragments interspersed throughout. As one of the few woodland-dependent songbird species to have maintained healthy population levels in Singapore  of the Striped Tit-Babbler population in Singapore, and calculated individual and population-based divergence statistics to investigate the degree of genetic subdivision within the population. These results were compared against models of landscape structure to assess how landscape configuration affects genetic connectivity between forest fragments. To test the robustness of our SNP dataset and the informativeness of multilocus SNPs, we also assessed if varying the number of SNPs used would affect downstream population genetic inferences.Using thousands of genome-wide SNPs and a newly-sequenced genome, we analyzed 46 Striped Tit-Babblers sampled from forest patches across Singapore’s north-south axis Fig.  to charaWe ringed a total of 66 Striped Tit-Babblers across 19 unique sampling localities. Accounting for historical ringing records , 26 individuals were recaptured across 37 recapture events between the years 2010 and 2014. All recaptures occurred at the original locality of capture, suggesting a highly sedentary lifestyle. One recapture occurred eight years after the original ringing, suggesting that the species is relatively long-lived in the wild.de novo assembly of the Striped Tit-Babbler genome, and assembly quality and completeness were assessed for each assembly by checking read pair coverage and supporting evidence  was obtained for ce Table . Based oce Table . In addiWe obtained 386,020,580 paired-end Illumina reads of 100 base-pair length each across 47 individuals, of which 325,488,846 reads (84.3%) were retained after quality control, filtering, and trimming. The number of retained reads per individual ranged from 4,225,764 to 14,316,443, and applying further quality control and aligning these reads to the reference genome resulted in 3,017,218 to 9,898,116 reads per individual successfully mapping to the reference genome. Assembling mapped reads into loci, calling SNPs, filtering for no missing data, and filtering for linkage disequilibrium resulted in an output SNP matrix containing 3849 loci. Bayescan did not detect any loci under selection, and while some SNP loci may nonetheless be closely linked to loci with fitness effects, we assumed that all loci were neutral absent better methods for testing this. Filtering for half-sibs resulted in 11 individuals being pruned, giving a reduced SNP matrix comprised of 35 individuals. Comparing inbreeding coefficients showed that most individuals exhibit relatively low levels of inbreeding  indicate that most of the Striped Tit-Babblers sampled fall into a single cluster with little to no substructure Fig. , due to ST = 0.023, p = 0.001), indicative of low levels of population genetic subdivision. Within-subpopulation inbreeding was barely statistically significant, and accounted for only 0.6% of the total genetic variation , suggesting relatively low levels of non-random mating within subpopulations.The AMOVA results show that 97.1% of the genetic variation was contained within individuals, while 2.3% of genetic variation occurred among subpopulations (Fobs) was 0.2269, with within-subpopulation values ranging from 0.2096  to 0.2294   to 0.0026 , while Hobs was 0.0025 with a within-subpopulation range of 0.0023  to 0.0025   for polymorphic loci was 0.2311, with within-subpopulation π values ranging from 0.2093  to 0.2306  (Table obs (Table 0 (1 − F), assuming the Central Catchment subpopulation to be H0 on account of it being the most genetically diverse subpopulation in Singapore, solving for F for both the unfiltered and kin-filtered datasets gives 0.09 and 0.10 respectively, both of which are close to the empirically derived TrioML mean inbreeding coefficient of 0.101  SNP matrix ranged from 0.0124  to 0.0606 , with relatively low pairwise FST values between the Central Catchment and the Southern subpopulation indicative of overall low population subdivision between the two largest forest patches along the north-south axis of Singapore  to 0.0261 , although relative pairwise differences between subpopulations remained largely the same  within the Southern subpopulation and one from Admiralty Park (sample K1104), both of which were inferred to have originated from the Central Catchment. This pattern is indicative of recent gene flow from the Central Catchment toward peripheral subpopulations.e is three orders of magnitude lower than the ancestral Ne , and that the population has suffered a recent decline approximately half a century ago  dataset results in a population-wide Ne of 101.5 (95% CIs: 100.8–102.2). Using the kin-filtered (n = 35) dataset results in a population-wide Ne of 596.1 (95% CIs: 569.4–625.4).Independently estimating N24. Spatial autocorrelation in the second and third distance classes did not differ significantly from zero  and significantly negative spatial autocorrelation for the fourth, and the seventh to twelfth distance classes Fig. , consistero Fig. . The spaero Fig. .Figure 32adj = 0.0343) outperforms the preliminary model, with resistance values of 60 and 40 respectively (R2adj = 0.0231). The proportion of genetic variation explained by spatial factors for the optimised resistance model  was higher than the Euclidean model  and preliminary resistance model , indicating that the optimised landscape resistance model provides a marginally better explanation for the spatial genetic signal observed in the Striped Tit-Babblers , which may inflate the likelihood of type I error.Optimising landscape parameters showed that the optimised model with urban resistance set to 90 and managed vegetation resistance set at 50  (Ne/N = 0.3)28 and Darwin’s Medium Ground Finch (Geospiza fortis) (Ne/N = 0.31)29, suggesting that the Striped Tit-Babbler population is likely more susceptible to the impacts of fragmentation than other species with similar life histories.The population-wide N31. However, significant pairwise FST values between subpopulations and reduced Hobs and π values in the Admiralty Park subpopulation points toward the existence of some population genetic subdivision between the forest patches along the north-south axis of Singapore.AMOVA and principal component analyses Fig.  indicateobs, as well as the presence of one individual exhibiting an inbreeding coefficient one order of magnitude higher than the mean Singapore-wide inbreeding coefficient  and the relatively recent isolation of Admiralty Park 35 obtained from radio telemetry methods (200–700 m)36. Limited dispersal and highly sedentary behaviour in this species (inferred from recapture data) likely contributes to the statistically significant signal of IBD observed in the dbMEM analysis. Simulating the effects of IBD using forward-in-time landscape genetic simulations further shows that a pattern of relatively stronger population differentiation from the Central Catchment emerges in the Admiralty Park subpopulation within relatively few generations compared to the Southern subpopulation , even after the potentially aberrant Admiralty Park individuals are excluded Fig. . While eion Fig. , consiste , and the paucity of forest patches within dispersing distance of other proximate source forests  per the manufacturer’s protocol for blood and body fluid DNA extraction, with minor modifications for samples stored in 100% ethanol. For muscle and liver tissue samples, we extracted DNA as per the Animal Tissue protocol for the Exgene Clinic SV kit. Extracted DNA samples were eluted into molecular-grade water and stored at −20 °C.et al.41 and Tin et al.33, using combinatorial barcodes derived from Peterson et al.18 and the restriction enzymes EcoRI (NEB) and MspI (NEB). We conducted triplicate PCR reactions per sample to reduce the likelihood of PCR bias highlighted by Tin et al.33 and to maximise the yield of adapter-ligated fragments. We produced 47 successful double digest RAD-Seq libraries, inclusive of one replicate specimen, pooled in equimolar volumes. Pooled libraries were sequenced on one Illumina HiSeq2000 lane at BGI Shenzhen, producing 100 bp paired-end reads.We prepared double digest RAD-Seq libraries for each sample based on a modified FASSST protocol developed by Tay de novo genome were performed by Science for Life Laboratory (SciLifeLab) in Stockholm. Short-insert-sized (180 bp) and mate-pair (5 and 8 kb) DNA libraries were constructed. All libraries were sequenced on the Illumina HiSeq2500 platform with a 2 × 126 setup in RapidHighOutput mode. Paired-end sequence data from the genomic DNA libraries were quality-checked, assembled, and evaluated using the NouGAT pipeline42.Genomic DNA was extracted from fresh tissue from one Striped Tit-Babbler individual using the KingFisher™ Duo extraction robot (Prime Magnetic Particle Processor) and the KingFisher Cell and Tissue DNA Kit, following the manufacturer’s protocol. Preparation of libraries, sequencing and the assembly of the process_radtags pipeline in Stacks v1.344 to demultiplex sequence reads, filter out low quality reads, and trim raw sequence reads to 90 bp. Single nucleotide errors within the barcode were corrected by the software. We used Bowtie2 v2.2.545 to align the RAD reads to the Striped Tit-Babbler reference genome. Successfully aligned reads were processed with SAMtools v1.046 to filter out reads with mapping quality score <25, exclude improperly paired reads, and convert the files to BAM format.We analysed raw sequence reads with FastQC to determine average quality scores across all reads. We used the ref_map.pl pipeline in Stacks v1.3 to assemble reference-aligned reads into loci for SNP calling, ensuring that only loci with no missing data were reported in the output SNP matrix. We used default parameters in Bayescan47 to detect loci under selection, and used PLINK v1.948 to identify loci in linkage disequilibrium for subsequent filtering.We used the 49 to determine the relatedness coefficients between individuals as well as the inbreeding coefficients for all 46 individuals. We filtered out one individual from each pair with an inferred relatedness greater than half-sibs (Queller and Goodnight)50 relatedness coefficient >0.25) using GenoDive51. We used the TrioML method52 to estimate inbreeding coefficients as it performs better than other estimators, especially for populations with high inbreeding and closely related individuals53.We used Coancestry54 in R v3.2.2 . The results of the PCA were plotted using the dudi.plot function in the R package Momocs55.To explore inter-individual differentiation, we performed a PCA with the kin-filtered SNP matrix using the dudi.pca function in the ade4 packagepopulations module in Stacks. We calculated pairwise Weir and Cockerham’s FST56 using the R package diveRsity. As the removal of kin may improve the performance of FST estimations at the expense of precision57, we calculated pairwise FST values using both the full (n = 46) SNP matrix and the kin-filtered (n = 35) SNP matrix.To calculate genetic diversity statistics, we grouped the 46 samples into three putative subpopulations based on the PCA results Fig. , comprisST values (using the R package diveRsity) and mean TrioML values (using Coancestry via the R package related)58 for each subpopulation.To test the robustness of our population genetic inferences, we used custom bash scripts to randomly subset the original SNP matrix for 2 to 3,500 loci, and recalculated population genetic statistics based on these reduced-loci SNPsets for a total of 100 independent subsamples per number of SNP loci being tested. The subsampled SNPsets were further used to calculate pairwise F59 to identify first generation immigrants within each putative subpopulation. We used the L_home likelihood statistic since some source populations may not have been sampled.To detect the presence of gene flow between subpopulations, we used GENECLASS260. We assigned all samples to a single population and performed simulations to test three population demographic scenarios: (1) the Striped Tit-Babbler population in Singapore has maintained a uniform Ne, (2) experienced recent decline, and (3) recent expansion  and kin-filtered (n = 35) SNP matrices without pruning for loci under linkage disequilibrium (5481 loci), to explore the range of possible Ne values for the Striped Tit-Babbler population.We used NeEstimator v2.01To explore changes in forest contiguity over time, we conducted a supervised classification of LandSat 5 TM and LandSat 8 OLI/TIRS imagery (USGS), using the maximum likelihood method in ArcMap 10.0 to produce four land use maps of Singapore for the years 1989, 1997, 2005, and 2013.63 to model connectivity between extant forest patches in 2013. We defined preliminary resistance parameters of each habitat type along a scale of 1 (no resistance) to 100 (maximum resistance)  analyses using the R package MEMGENE66, which account for potential spatial autocorrelation in the data, to determine the proportion of the spatial genetic signal explained by isolation by distance (IBD) and isolation by resistance (IBR) models.We used GenAlExurban >resistancemanagedvegetation, and using Circuitscape v4.0.5 and MEMGENE to select the optimal model for which the proportion of genetic variation explained by the corresponding resistance distance matrix was highest. We used the optimised resistance model to generate the final landscape connectivity map using Circuitscape v4.0.5.We refined the resistance model by generating 45 alternative models such that resistance67 to simulate the effects of landscape structure on the population genetic structure of the Striped Tit-Babbler.To test for false positive signals of IBR and assess the validity of our population genetic analyses, we used CDPOPWe defined relaxed life history parameters based on the known biology of the Striped Tit-Babbler and closely related species, which should result in a slower accumulation of intrapopulation differentiation, for a spatial dataset of 5761 Striped Tit-Babblers  and simulated the effects of IBD on the population for 99 randomly-generated neutral loci, for 100 generations, sampled every 10 generations, with 100 MCMC replicates per simulation.ST between putative subpopulations using the R package diveRsity for all sampled generations. We also conducted dbMEM analyses using MEMGENE for generations 10 to 50, excluding MCMC replicates for which an entire subpopulation goes extinct, to compare the variance explained by IBD and IBD + IBR models and ascertain the Type I error rate.We sampled individual genotypes at the locations of the original 46 individuals and calculated the change in pairwise FWe acknowledge the National Parks Board of Singapore for facilitating fieldwork under permit NP/RP13-019-2. All field and lab work was conducted in accordance with regulations outlined by the National University of Singapore’s Office of Safety, Health, and Environment.Supplementary Information


Aedes aegypti is a public health concern in the USA, especially in the wake of emergent diseases such as Zika and chikungunya. Aedes aegypti populations dwindled after the invasion of Aedes albopictus in the 1980s and many populations were extirpated. However, in some areas Ae. aegypti persisted in small populations and there are reports of recent resurgences of Ae. aegypti in Florida, Louisiana, Nevada and California. We assessed the population genetic structure of Ae. aegypti in Florida and Georgia, which has concomitant consequences related to mosquito dispersal, pesticide resistance and vectorial capacity.The yellow fever mosquito, Ae. aegypti across Florida and in Georgia using ovitraps. We hatched the eggs and reared them to adults, and after sacrifice we extracted their DNA. We then probed each individual for variation in 6 microsatellite markers, which we used to address population genetic characteristics.We collected Ae. aegypti and genotyped seven Florida populations and one Georgia population using microsatellite markers. We found evidence of isolation by distance model of gene flow supported by driving distance among cities within Florida and two theoretic genetic clusters.We collected Ae. aegypti in Florida. This study provides information on the genetic exchange between populations of Ae. aegypti in the southeastern USA and suggests potential routes of spread of this species.Significant genetic structure between some populations with substantial gene flow between geographically distant cities suggests regional genetic structuring of  Aedes aegypti shifted after the introduction of the Asian tiger mosquito Aedes albopictus in 1985 [Ae. aegypti was distributed throughout a large proportion of the southeastern USA in cities, small communities and rural areas [Ae. albopictus [Ae. aegypti was likely due to asymmetric satyrization of Ae. aegypti females by Ae. albopictus males [Ae. albopictus [Aedes albopictus also typically outcompetes Ae. aegypti as larvae in shared containers, though the outcome of competition is context-dependent [One of the fundamental questions in ecology is how invasive species affect closely related native species and in the case of mosquito ecology, what the implications are for the spread of disease . Interac in 1985 . Althougal areas , it was bopictus , 4. The us males , resultibopictus , 7. AedeAe. aegypti remained in areas that ecologically favored Ae. aegypti, particularly in urban areas of southern Florida [Ae. aegypti eggs persisted and Ae. albopictus eggs could not [Ae. aegypti could help inform management strategies.Despite invasion and subsequent extirpation, remnant populations of  Florida –13. A coould not , 15. In ould not . Given tAe. aegypti density, like South Florida, are most at risk of local disease transmission [Ae. aegypti as a vector for human viruses in the USA, as well as the need for mosquito control to mitigate disease transmission [Ae. aegypti may be spreading out of remnant populations in urban areas of southern Florida, suggesting a reinvasion of its naturalized range [Ae. aegypti is capable of rapidly evolving resistance to interspecific mating with Ae. albopictus [Ae. aegypti is a superior vector for many of the viruses that cause human diseases. Therefore, the genetic structure within the southeastern USA, particularly in Florida where Ae. aegypti driven outbreaks of human disease have occurred, could help us understand potential routes of reinvasion and disease transmission.Areas with high smission . Recent smission , 19. In ed range , 20. A rbopictus . AvoidanAe. aegypti are influenced by its close association with humans [Ae. aegypti to overcome barriers it otherwise could not, as Ae. aegypti typically does not disperse much farther than 10–800 m within its lifetime [Ae. aegypti habitat suitability and growth, and roads within an urban network play an important role in the rapid spread of Ae. aegypti [Ae. aegypti, particularly within Florida, will elucidate population differentiation and possibly identify genetic corridors.The spatial distribution and genetic structure of h humans , 22. Humlifetime , 24. Urb aegypti . Roadway aegypti , Pakista aegypti  and Viet aegypti , and alt aegypti . Previou aegypti , 28, 29. aegypti , 29, tho aegypti . Given tAe. aegypti in the southeastern USA. Specifically, we focused our sampling on remnant populations of Ae. aegypti mosquitoes in Florida and Georgia. Nine highly polymorphic microsatellite loci provided information on the standing genetic structure of this species, how connected isolated populations are to each other and potential mechanisms of dispersal and spread as this species reinvades its naturalized range.In this study, we use a population genetic approach to clarify the contemporary genetic structure of Ae. aegypti from June to July in 2014  according to manufacturer instructions, with the exception that we used 30 µl of proteinase K, digested the samples for 72 h and eluted DNA in UltraPure 100 µl DNase/RNase-free distilled water . We quantified template DNA using a fluorometer  and tested a suite of polymorphic microsatellite loci. Loci that amplified reliably include four polymorphic loci described by Slotman et al. [We extracted total nucleic acids from 225 individual n et al.  and two n et al.  , expected heterozygosity (HE) and inbreeding coefficient (FIS) using GENEPOP and GenAlex v. 6.5 [poppr v. 2.8.3 [We used GENEPOP v. 4.2  to test x v. 6.5 . We estix v. 6.5  and calcv. 2.8.3 .F-statistics, including estimates of FST. We measured genetic differentiation  in GENEPOP. We conducted regression analyses of isolation by distance by cluster using linear pairwise We assessed genetic structure among populations using n = 9) for each K = 1 to 9 using an initial ‛burn-inʼ period of 40,000 and 100,000 iterations of the MCMC method. We selected the optimal K using the ΔK method [via Structure Harvester v. 0.6.94 [To identify likely genetic clusters and ancestry, we used a population admixture model in a Bayesian assignment tests implemented by STRUCTURE v.2.3.4 , 40. We K method  via Stru. 0.6.94 . We used. 0.6.94 . We also. 0.6.94 . We usedTo address a hypothesis about the direction of gene flow between two sample locations connected by Interstate 95  after corrections for multiple comparisons; five showed heterozygote deficiency and one heterozygote excess  and expected heterozygosity (HE) were not significantly different  among the eight populations , despite a geographical distance of roughly 640 km  = 13.43, P = 0.001) and driving distance  = 23.19, P < 0.001), although for Euclidean distance the residuals violated the assumption of a normal distribution. This violation was driven by a single pairwise comparison between Columbus and Key West  for the one-way directional model of gene flow out of Miami to Daytona. The log Bayes Factor (LBF) was highest for the out-of-Miami model at 34,210 and next for the into-Miami model at 4561. These results supported the hypothesis of gene flow from the major urban center of Miami to Daytona  as opposed to the other three models of gene flow into Miami, bi-directional gene flow or panmixia.Aedes aegypti showed significant genetic structuring among all populations, with the exception of the comparison between Daytona Beach and Miami. In addition, we found evidence of the isolation-by-distance model of gene flow supported by driving distance among cities within Florida and two theoretical genetic clusters. The genetic clusters of the two populations within the Southeast appear to visually correspond to major roadways in eastern Florida  and western Florida , public domain, original copyright 2017.Additional file 2: Table S1. Microsatellite loci used in study. Loci pairs are based on non-overlapping size ranges. Size range is derived from a literature review [e review –32, 55. Additional file 3: Text S1. Microsatellite data used in analyses in Genpop format. Microsatellite data are from all populations indicated in Table Additional file 4: Table S2. Population-by-locus genetic diversity of microsatellite markers in eight Aedes aegypti populations. N is the number of individuals, NA is number of alleles, HO is observed heterozygosity, HE is expected heterozygosity, and P is P-value of an exact test. Note that * indicates P < 0.05 with corrections for multiple comparisons; d is heterozygote deficiency and e is heterozygote excess.Additional file 5: Figure S2. Signature of isolation by distance for both Euclidean distance and driving distance. Scatterplots of Euclidean distance (a) and driving distances (b) by pairwise linear FST with fitted linear regressions superimposed.Additional file 6: Figure S3. Delta K analysis of the true number of clusters following the Evanno method.Additional file 7: Figure S4. Discriminant analysis of principal components (DAPC). Analysis with 40 principal components and a cross-validation of 100 iterations .


Sorbus is an example of a genus where active diversification and speciation are ongoing and, as such, represents an ideal model to investigate the roles of hybridization, polyploidy and apomixis in a reticulate evolutionary process. To elucidate breeding systems and evolutionary origins of a complex of closely related Sorbus taxa, we assessed genotypic diversity and population structure within and among taxa, combining data from nuclear DNA microsatellite markers and flow cytometry. Clonal analysis and low genotypic diversity within the polyploid taxa suggest apomixis is obligate. However, genetic variation has led to groups of ‘clone-mates’ within apomictic taxa that strongly suggest mutation is responsible for the genotypic diversity of these apomictic lineages. In addition, microsatellite profiles and site demographics suggest hybridization events among apomictic polyploid Sorbus may have contributed to the extant diversity of recognized taxa in this region. This research demonstrates that both macro- and micro-evolutionary processes are active within this reticulate Sorbus complex. Conservation measures should be aimed at maintaining this process and should therefore be prioritized for those areas of Sorbus species richness where the potential for interspecific gene flow is greatest.Hybridization and polyploidy are major forces in the evolution of plant diversity and the study of these processes is of particular interest to understand how novel taxa are formed and how they maintain genetic integrity.  Hybridization between species resulting in the formation of new polyploid populations that are distinct and reproductively isolated from the parental taxa is the most common mechanism for sympatric speciation . HoweverRubus L.  is often associated with polyploidy  and effeRubus L. , Taraxacaraxacum , Crataegaegus L. , and Sororbus L. . HybridiSorbus (Rosaceae) is a suitable study group to test the extent of hybridization among species of varying ploidy and elucidate the role of breeding system in creation of novel polyploids and establishment of polyploid populations as the ongoing speciation in Sorbus is well described, particularly in Britain  Crantz and S. aria L., exist at low densities or are not currently native to the region, respectively.Several important United Kingdom sites for et coast . This stSorbus rupicola (Syme) Hedlund and S. porrigentiformis E.F. Warb. are thought to be the oldest polyploids in our study group based on their wide distribution , which makes them well suited for the identification of hybrid parentage . We useda Figure .The principal aims of this study were to elucidate evolutionary relationships among the study taxa and to determine breeding systems within this species complex; in addressing these aims, we explored patterns of genetic structure and diversity. Specifically we addressed the following questions: (1) what are the most likely hybrid origins of the polyploid taxa?; (2) are single or multiple origins evident for the polyploid taxa?; (3) is the apomictic breeding system of polyploid taxa obligate or facultative?; (4) what is the source of genetic diversity within and among the polyploid taxa? Finally, we draw on our genetic findings to make robust recommendations for conservation and management of this often rare and complex group of taxa.Sorbus species collected from 35 sites  following the manufacturer’s protocol.Malus × domestica  and fragment analysis was performed using CEQ 8000 Genetic Analysis system (Beckman Coulter), followed by a manual verification of each call to ensure proper peak designation. To determine a standard genotype for each polyploid taxon, a reference selection of all study species was subjected to three PCR repeats and used as an internal standard against which all mutations and scoring errors were checked. Any subsequent inconsistent samples were repeated to ensure observed allele sizes were not artifacts of PCR amplification or scoring error.S. aria and S. torminalis individuals . Therefore, analyses that included both diploid and polyploid taxa were based on 10 loci. The additional three loci were included for analysis of polyploids only. Locus MS14 and locus CH01F09 were genome specific for S. torminalis and S. aria, respectively, and were used to study inheritance patterns and infer the route of formation for those species in subgenus Tormaria which are putative hybrids between members of subgenus Aria and S. torminalis.Thirteen primer pairs successfully amplified across all polyploid taxa; however, primers for three loci  failed to amplify alleles in many Oryza sativa [‘IR36’, 2C = 1 pg; Sorbus species analyzed previously  and a pairwise distance matrix was constructed. Patterns of genetic structure among these genotypes were examined using a principal coordinate analysis (PCoA). The results of the PCoA were visualized in 3D using the R package ‘pca3d’ . To summTo determine whether the polyploid taxa analyzed had single or multiple origins, to identify the breeding systems prevalent within the group of study species and to identify potential sources of genetic diversity within the polyploid taxa, we analyzed the genotypic diversity within and among our study taxon group.S. torminalis, with random sub-sampling of the 33 S. torminalis samples to match the sample size of S. aria . Total number of different alleles (A) for each species was calculated from the 10 loci that amplified in all taxa. The total number of MLGs (Ng) was determined using the ‘assign clone function’ in POLYSAT with zero as the threshold; thus, all pairs of individuals with a non-zero genetic distance were considered as separate MLGs. Genotypic diversity for each of the polyploid species was determined as the complement of The following diversity calculations, implemented in POLYSAT, were carried out for the microsatellite data for the 10 loci that amplified successfully in all taxa. As sample size is known to affect allelic diversity statistics , rarefacTo determine whether any of the diversity seen within polyploid taxa could be explained by genetic recombination, either as a result of an interspecific or intraspecific hybridization, or through somatic mutation, we assigned each polyploid sample to a clonal lineage, within which any diversity was considered to be due to mutation using the method of To assess the most likely hybrid origins for each polyploid species, we matched its allele sizes at 10 loci to those of putative parental species . Where aS. rupicola and S. vexans.The majority genotype was used for each apomictic polyploid species where >80% of individuals had identical MLGs and small allele variations were only observed in the minority. The exception to this was the highly variable locus SA06 where several allele size variants were included for For the sexual parental species, all alleles from all samples were considered together as a pool of potential alleles, since the original genotype was presumed extinct.S. aria and S. torminalis genomes to study members of subgenus Tormaria, we used the genome specific loci CH01F09 and MS14, with alleles matched to either S. torminalis or S. aria. The proposed genome contributions are shown in Figure To identify the relative contributions of post hoc Tukey comparisons of means to determine where any differences lay. The normality of the data distributions was tested using the Shapiro–Wilk test and the homogeneity of variances using Levene’s test. All statistical analysis was performed using R  confirming their status as hybrids between subgenus Aria and S. torminalis.Thirteen microsatellite loci were amplified successfully across the seven polyploid species, with 10 of these loci amplifying successfully across all nine study species. The two genome-specific loci, CH01F09 and MS14, yielded alleles for all three members of subgenus Sorbus samples, ranging between eight (MSS13 and SA03) and 24 (SA14) alleles per locus. S. torminalis had the highest allelic diversity with 122 alleles recorded in 33 samples . In 161 polyploid samples screened at 13 loci, 123 alleles were amplified, with SA06 yielding the highest number  and SA03 the lowest . The allele sizes observed at each locus for each species are given in Supplementary Table S. torminalis; this particular sample had three alleles at two loci: SA19.1 and SA1 .The 10 core loci  yielded a total of 202 alleles from 207 The investigation of genetic structure revealed that each of the study species is genetically differentiated, although clustering patterns varied between the two subgenera.S. aria and S. torminalis were differentiated from each other and from all polyploid taxa in the PCoA and NJ tree , were closely grouped in the PCoA, particularly the two tetraploids. Their separation was also weak in the NJ tree where, although distinct clusters are observed, they were positioned on relatively short branches. Individuals of S. vexans (4x) and S. rupicola (4x) were also tightly grouped in the PCoA, with the exception of two samples within S. vexans that clearly occupied an intermediate position between S. vexans and S. margaretae (4x) and are referred to hereafter as vex2; this intermediate position mirrors that seen in the NJ tree analysis  samples all grouped together in single, highly differentiated clusters in both analyses.The sexual diploid taxa  Figures , 4. SampS. aria and S. torminalis. In contrast, the polyploid taxa had approximately half the number of alleles, despite their larger genome sizes. Across the 10 loci, no private alleles  were observed in any of the seven polyploid taxa, while high levels of allele sharing were noted across all species. Only four of the 95 alleles present in the polyploid taxa were not sampled within the diploid species. The polyploid taxa contained 62% of the total alleles observed. When using a zero threshold to identify unique MLGs (Ng), the number of MLGs observed in the diploids equaled the sample number, as would be expected for sexual, outcrossing taxa. In contrast, low numbers of MLGs were detected within the apomictic polyploid species, although all showed more than one MLG, except S. admonitor. The complement of Simpson’s diversity (1 - λ) for the 10 loci also reflected this pattern, with members of subgenus Tormaria ranging from 0 (S. admonitor) to 0.27 (S. subcuneata). Sorbus margaretae showed the lowest genotypic diversity in subgenus Aria, and S. vexans s.l. the highest; diversity statistics are summarized in Table The outcrossing diploid species showed high levels of genotypic variation in comparison to the polyploid species that were characterized by few MLGs. The total number of alleles (A), measured across 10 loci, was highest for the diploid, sexual species S. vexans that had two different clones, each of which conformed to a distinct genotype; these two genotypes differed at all 13 loci analyzed. This result is inconsistent with only mutational variation and suggests a separate sexual origin for each S. vexans clone; vex2 formed the second clone, consisting of two identical samples. Diversity statistics for S. vexans were calculated with and without vex2, as S. vexans s.l. and S. vexans s.s., respectively.A frequency histogram of all pairwise distances was multi-modal Figure , with a S. torminalis and members of subgenus Tormaria, with two alleles amplified for each of the tetraploid species S. devoniensis and S. admonitor, and one allele for the triploid S. subcuneata. Two alleles were amplified at locus CH01F09 for these three species, indicating an even contribution of alleles from S. aria and S. torminalis for the tetraploids and a 2:1 ratio of alleles for S. subcuneata, respectively. S. subcuneata, S. devoniensis and S. admonitor shared alleles with each other and diploid S. torminalis at 10 loci. For these three polyploid species, pairwise comparisons  generated multiple genotype matches, including a match of S. margaretae × S. torminalis.Locus MS14 amplified only in Aria all had four alleles at the Aria genome-specific locus CH01F09 and no alleles at locus MS14. Thus, S. torminalis and members of subgenus Tormaria cannot be considered as potential parents of any member of subgenus Aria studied. Only S. margaretae and the second S. vexans clone (vex2) had alleles matching those of any other taxa studied with 10 loci. Pairwise comparisons identified no exact matches indicative of potential parentage between members of subgenus Aria and the taxa studied. For partial parentage matches, all missing alleles were subsequently checked against the minority genotypes for each potential (unresolved) progenitor. Consequently, the next best match was recorded with a score for the number of missing allele matches against each pairwise cross , triploid (3x) and tetraploid (4x). The Sorbus samples and the internal size standard (Oryza sativa) produced clear histogram peaks with low coefficients of variation  displayed significantly larger genome sizes than those of the four subgenus Aria tetraploids .The ratios between the sample peaks and internal size were used to infer the ploidy of each sample based on previous results for Sorbus . Compariloid see . S. subcSorbus species revealed that each currently described species is readily genetically differentiated. In contrast to other studies . If so, this could suggest a greater level of phenotypic variation than that detected with the microsatellite loci used in this study. The small site of Neck Wood  or could indeed be the vex2 variant, also found at Neck Wood.Our study has revealed genetic variability in six of the seven apomictic polyploid taxa. Although the levels of variation were low, polymorphisms at a number of loci were sufficient to identify divergent ‘clone mates’ associated with particular sites. In the absence of recombination events, mutation plays a key role in the generation of genetic variation in apomictic lineages . Sorbus  repeats . Nonetheribution  could coTormaria showed little mutational variation compared to subgenus Aria. Such a finding suggests they may be of more recent origin than the members of subgenus Aria, particularly S. admonitor that has the most restricted distribution of all the species included in the current study. Indeed, the genetic variation within the apomictic taxa was in marked contrast to that found in similar taxa from the Avon Gorge, which showed consistently invariable genotypes using the same genetic markers , S. porrigentiformis or S. rupicola is strongly suggestive of missing intermediate parental genotypes , and the absence of either S. aria or S. torminalis at many of the study sites, although the latter may not always have been the case, as discussed below.The presence of several alleles shared in the endemic polyploids that were not found among the diploids  are distinct from –but intermediate to– S. torminalis and subgenus Aria, in line with the hybrid origins proposed by S. admonitor and S. devoniensis, when compared to the tetraploid members of subgenus Aria, adds weight to their probable hybrid origin, with S. torminalis as an ancestral parent  in the PCoA suggested S. margaretae may be the male ancestral parent of these representatives of subgenus Tormaria, rather than S. aria or S. rupicola, as proposed by S. margaretae, S. devoniensis, S. admonitor and S. subcuneata and is in accordance with results from the pairwise matches in Table Tormaria formed a tight group of very closely related taxa in all our cluster analyses. Sorbus subcuneata, a triploid taxon, shared all its alleles with both tetraploids, S. devoniensis and S. admonitor, across all 13 loci, implying a common recent origin for the group, possibly with S. subcuneata as an ancestral species for S. admonitor and S. devoniensis. The additional alleles present in both tetraploids were also found in some of our samples of S. torminalis   could indicate a more recent origin, since mutations accrue over time since divergence  represents a separate genotype resulting from interspecific hybridization rather than sexual reproduction, since alleles common to other taxa were identified. The intermediate position of vex2 between S. vexans and S. margaretae in the PCoA, suggests it may be a hybrid involving these two tetraploids, especially since the ancestral diploid progenitor for subgenus Aria, S. aria, is not present in the locality. This origin is also supported by the pairwise matching  Pers., a non-native that has become naturalized. The vex2 variant is genetically unique and its possible derivation from polyploid taxa in the absence of parental diploid forms indicates that this is a possible route for polyploid Sorbus formation and provides strong evidence of on-going diversification via introgression in the region. This finding also raises the likelihood that there may be other cryptic taxa on sites in the region with multiple Sorbus taxa where heterospecific pollen pressure is high, further increasing the chances of interspecific hybridization (The second clone vex represenclone vex represendization .Sorbus porrigentiformis shares alleles with S. rupicola at 11 of the 13 amplified loci, so it seems likely that S. porrigentiformis is also derived from S. rupicola, maybe indirectly (denoted as y in Figure S. aria and S. torminalis are clearly differentiated from each other and from the polyploid taxa in all our cluster analyses. The triploid form of S. torminalis clusters with its diploid forms (Figures S. aria samples. However, the triploid S. torminalis was found located close to tetraploid S. devoniensis (Sorbus cannot be ruled out since they share many alleles. Indeed, wide-scale screening of Sorbus seed ploidy has shown this to be the most likely scenario (The sexually reproducing  Figures , 4, sugg Figures  and are  Figures . Indeed,oniensis ; thus, tscenario .sensuS. torminalis in the formation of members of subgenus Tormaria. At this time, S. torminalis is not of conservation concern, however, this research demonstrates why it should be included in any actions to conserve the complex genetic mosaic characteristic of this species group. The formation routes of the constituent members of subgenus Aria are less clear, most likely due to a combination of mutation and missing or unsampled parental genotypes. Both these factors indicate that genetic diversity in this group may be higher than our sampling suggests and that process-based conservation action plans should focus on sites of high species diversity –for example, Neck Wood– in order to preserve current Sorbus diversity in this region of southwest England.Strategies developed for the conservation of polyploid complexes that contain threatened species need to encompass any local adaptations of particular groups, together with the long-term ability of the complex to evolve through natural selection in a changing environment. There should be some assessment of the status of parental taxa, however, common, to ensure they are protected from detrimental human activities. A process-based approach to conservation measures sensu should bTH carried out the fieldwork. TH carried out the molecular work and statistical analysis under the supervision of RK, NdV, JC, and JS. The flow cytometry was performed by JP, assisted by TH under the supervision of MF. TH and JS drafted the manuscript, and all authors contributed to the final version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


But often, this population assignment is unknown and assumptions about assignment can lead to erroneous estimates of genetic relatedness. I develop a generalized method of estimating relatedness in admixed populations, to account for (1) multi-allelic genomic data, (2) including all nine Identity By Descent (IBD) states, and implement a maximum likelihood based estimator of pairwise genetic relatedness in structured populations, part of the software, InRelate. Replicated estimations of genetic relatedness between admixed full sib (FS), half sib (HS), first cousin (FC), parent-offspring (PO) and unrelated (UR) dyads in simulated and empirical data from the HGDP-CEPH panel show considerably low bias and error while using InRelate, compared to several previously developed methods. I also propose a bootstrap scheme, and a series of Wald Tests to assign relatedness categories to pairs of individuals.Estimating genetic relatedness, and inbreeding coefficients is important to the fields of quantitative genetics, conservation, genome-wide association studies (GWAS), and population genetics. Traditional estimators of genetic relatedness assume an underlying model of population structure. Each individual is assigned to a population, depending on  Estimating genetic relatedness is an important problem in biological statistics and population genetics. For instance, paternity or maternity assignment see , and forX and Y can be defined in terms of the probability that their alleles are Identical By Descent (IBD). X and Y may sire  estimating a coefficient of relatedness between two individuals using multilocus genotype data, and linkage data to inform the length of IBD tract sharing; or (2) assigning sib-ship partitions, reconstructing pedigrees, and using the pedigrees to estimate relatedness; or (3) directly estimating relatedness from known pedigrees . This dee.g., θ, In the presence of population genetic structure though, localized inbreeding makes individuals within the same subpopulation ‘more related’, than as suggested by their pedigree. Pervasive or specific inbreeding in recent generations past between two related individuals can be quantified though, if sufficient information is available on the existing genetic subpopulation structure. The estimated inbreeding coefficients e.g., θ,  affect ta priori knowledge of existing subpopulations within a total population. Thus estimates of relatedness using the inbreeding coefficient θ in its formulation could be potentially biased.Not accounting for such ‘shared’ allelic ancestry by utilizing true, or estimated subpopulation allele frequencies leads to incorrect estimates of genetic relatedness. θ. This assumption can be problematic because we do not know the precise number of ancestral subpopulations. However, the number of ancestral subpopulations can be approximated by the current subpopulation structure in a reference population.Several other methods also utilize current population allele frequencies as proxies for ‘ancestral’  allele at a locus l in individual i. The data can then be reduced to sufficient statistics. Specifically, let a observed at locus l in individual i.The observed genotype data from diploids can then be combined into a three-dimensional matrix K subpopulations. Each subpopulation is characterized by its allele frequencies: alkK subpopulations: each allele of individual ik with probability i, and k and locus l.The admixture model i.e., shared alleles that are identical by descent (IBD). As shown in The likelihood of the observed multilocus genotype data, δ, and hence their relationship.We only know if alleles are identical in state (IBS), and each IBD state is consistent with one or more of the nine IBS states, i and j. We observe their IBS state, l, where i and j, the likelihood of the observed data arei.e., sensuConsider two individuals l, in individual i is l, in individual j is X is the observed data, and L independent loci, this likelihood can be written as a product of individual locus likelihoods asR , for the estimators of I also implemented the methods of θ, for other previously derived estimators , and hence were not used for comparison in this manuscript.Other estimators that were compared include those of X and Y are independent, we can obtain variance in estimation of relatedness by bootstrapping over loci. For every pair of individuals, loci are sampled with replacement to construct bootstrap replicates, and relatedness is estimated under the maximum likelihood framework. I then construct 95% confidence intervals of the estimated relatedness values. Simulated bootstrap standard errors are calculated as:B is the number of bootstrap replicates and:Under the assumption that sampled loci between two individuals Five separate sets of multi-allelic genomic data were simulated to test the performance of relatedness estimates using InRelate , against other estimators. In all scenarios, subpopulations from which individuals were sampled from were assumed to be the ‘true’ subpopulation, for comparison with other methods. Admixture proportions and subpopulation allele frequencies for all analyses were obtained by performing runs of MULTICLUST . MULTICLK) to be one of 3, 5, 10, or 15. To allow for genetic admixture, I specified relatively greater levels of gene flow of 0.01 total proportion of migrant females and males per generation, between subpopulations inside each population, and relatively lower gene flow of 0.001 total proportion of migrant females and males per generation, between populations. Subpopulation sizes of 25 males and 25 females per subpopulation were held constant across generations. A forward-time simulation was performed for 3000 generations, and I utilized the last generation’s allele frequency distribution for all further simulations. All populations at generation 3000 were tested for Hardy-Weinberg Equilibrium (HWE).Under Scenario 1, all initial allele frequencies were simulated at 50 diploid, codominant, multi-allelic , unlinked loci, using Easypop v.1.7 . The HieUnder Scenario 2, I simulated multi-allelic genomic data using the same demographic parameters as in scenario 1 using a single Island Model , Deviation from true relatedness was examined by calculating the Mean Square Error (MSE). MSE is measured as:For bootstrap analyses, I simulated another dataset from the above data set of H1048H1048 dataset for individuals reportedly related from within the African continent. The African continent was represented in this data set by 115 individuals, classified as Bantu (South Africa), Bantu (Kenya), Mandenka, Yoruba, San, Mbuti Pygmy, or Biaka Pygmy, and were genotyped at a total of 783 microsatellite loci. Average differentiation, measured as Nei’s a priorihttps://github.com/arunsethuraman/inrelate.All simulated data, and R scripts can be accessed at In general, in all scenarios that measured genetic relatedness among FS, PO, and HS dyads, the InRelate estimator MC2013) performed better, or comparably with the AW2007  and Wang performeThe other estimators that did not account for population structure consistently over-, or under-estimated genetic relatedness between dyads, with large mean squared errors (MSE). It was also noted  that allCorrespondingly, MC2013 had the lowest MSE in the estimation of relatedness in FS, PO, and HS dyads, while the methods of AW2007 and Wang2011 had the lowest MSE for FC and UR dyads. The Ritland  estimatoIn the absence of population structure, under a panmictic island model, all methods performed comparably, with low MSE and bias for all FS, PO, HS dyads. The method of Bias and MSE estimates of pairwise genetic relatedness in FS dyads showed a trend of decrease with an increase in the number of loci , 18, 19 The methods of InRelate estimators do not have problems with ‘label-switching’, since population assignment is determined by the clustering method, and hence the ancestry proportions and allele frequencies are recomputed every time. On the other hand, both the methods of tion See .Out of the 5 dyads of FS, HS, PO, FC and UR categories were correctly assigned after 200 bootstrap iterations in 44% of pairs. All Parent-Offspring pairs were correctly assigned, while two each of FS, FC, and UR pairs were correctly assigned. None of the HS pairs were significantly assigned to any category. Plots of confidence intervals around estimates using both the MC2013 and MC2013WI estimators are shown in Across 24 dyads which were either identified as FS, HS (or Avuncular), or PO by The presence of ancestral subpopulation structure affects estimates of pairwise genetic relatedness between individuals from the same subpopulation, owing to pervasive inbreeding, and non-random mating in recent ancestral generations.X and Y, while accounting for the ‘true’ genetic subpopulation structure in the population. This ‘true’ genetic subpopulation structure is unobserved and can be inferred from the data. Since the proposal of an admixture model by K, admixture proportions  outperform several previously developed methods for relatedness estimation in admixed populations with considerably less error and bias. This accuracy is more pronounced particularly in between pairs of full siblings, parent-offspring, or half-siblings. The previously developed methods of Of note though are general difficulties in estimation of relatedness between first cousins, second cousins, and other more distantly related or unrelated pairs. These are also seen and reported by other likelihood methods see , other eθ , as against biasing all estimates using a single non-varying parameter, a priori as in all other methods. Correspondingly, all allele frequencies, and ancestry proportions are re-calculated with switched labels, which are then used in estimates of relatedness. While all my analyses have inferred admixture proportions at the assumed ‘true’ subpopulation structure , perhaps the true utility of this method would be if this K was inferred from the data, and the corresponding inferred admixture proportions and allele frequencies used in the estimation of relatedness. However, this is a statistical problem (K (InRelate estimators do not have problems with ‘label-switching’, since the subpopulation structure is inferred from the data and not assumed oblem (K . InRelatInRelate methods are of best utility when dealing with multi-allelic data, generated from individuals that are sampled from populations that are ancestrally structured, and generally outdo the methods of


While the utility of parasite genotyping for malaria elimination has been extensively documented in low to moderate transmission settings, it has been less well-characterized in holoendemic regions. High malaria burden settings have received renewed attention acknowledging their critical role in malaria elimination. Defining the role for parasite genomics in driving these high burden settings towards elimination will enhance future control programme planning.Plasmodium falciparum loci, Pfama1 and Pfcsp, at two timepoints in June–July 2016 and January–March 2017 in a high transmission region along the international border between Luapula Province, Zambia and Haut-Katanga Province, the Democratic Republic of the Congo (DRC).Amplicon deep sequencing was used to characterize parasite population genetic diversity at polymorphic High genetic diversity was observed across both seasons and in both countries. No evidence of population structure was observed between parasite populations on either side of the border, suggesting that this region may be one contiguous transmission zone. Despite a decline in parasite prevalence at the sampling locations in Haut-Katanga Province, no genetic signatures of a population bottleneck were detected, suggesting that larger declines in transmission may be required to reduce parasite genetic diversity. Analysing rare variants may be a suitable alternative approach for detecting epidemiologically important genetic signatures in highly diverse populations; however, the challenge is distinguishing true signals from potential artifacts introduced by small sample sizes.Continuing to explore and document the utility of various parasite genotyping approaches for understanding malaria transmission in holoendemic settings will be valuable to future control and elimination programmes, empowering evidence-based selection of tools and methods to address pertinent questions, thus enabling more efficient resource allocation. Plasmodium falciparum malaria transmission since the early 2000s, due in part to massive distributions of insecticide-treated bed nets (ITNs), increased coverage with indoor residual spraying (IRS), and the introduction of artemisinin-based combination therapy (ACT) [Significant progress has been made in reducing py (ACT) , 2. In fpy (ACT) , 3. Whilpy (ACT) . Despitepy (ACT) , 6. AcknPlasmodium falciparum molecular epidemiology has emerged as a tool to genetically track transmission patterns [patterns –10. Popupatterns –19. Parapatterns –22 and spatterns . Parasitpatterns . With reP. falciparum prevalence by microscopy among children under 5 years old declined from 19.4% in 2015 to 9.1% in 2018 [® 300CS), since 2014 [® led to a moderate decrease in P. falciparum prevalence by 25% in the sprayed regions within Nchelenge District; however, the effect was short-lived, lasting only for 6 months after spraying, and did not impact unsprayed areas [Zambia, a malaria-endemic country in southern Africa, aims to eliminate malaria from every district by 2021. As a country, Zambia has made great strides towards achieving this goal. In fact,  in 2018 . Unfortunce 2014 . IRS wited areas , 26.Across Lake Mweru from Nchelenge, situated along the international border, are two villages, Kilwa and Kashobwe in Haut-Katanga Province, the DRC. The most recent Demographic and Health Survey (DHS) from the DRC conducted in 2013–2014 reported that 23.1% of children ages 6 months to 5 years tested positive for malaria by microscopy in Haut-Katanga Province . This PrP. falciparum genetic diversity at two time points in June-July 2016 and January-March 2017 in Nchelenge District, Zambia and Kilwa and Kashobwe, the DRC is described. Genetic relatedness of parasites from northern Zambia and southern DRC were compared in order to assess whether this border region represents one contiguous transmission foci. The impact of declining parasite prevalence in Haut-Katanga Province on parasite population genetics was evaluated over the two time periods of the study. Finally, methods for detecting epidemiologically relevant genetic signals amidst high genetic diversity in a holoendemic transmission setting are discussed.In high transmission settings including Nchelenge District, Zambia and Kilwa and Kashobwe, the DRC, individuals are typically infected with multiple genetically distinct parasites. Classic population genetic approaches that utilize neutrally-evolving SNPs or microsatellites across the genome inadequately address high polyclonality. Amplicon deep sequencing enables each parasite clone in an infection to be enumerated, but typically only at specific, high-diversity and non-neutral amplicons in the genome. Given the interest in molecular epidemiology for malaria control in high burden regions and the limitations of classic population genetic analysis in these settings, the performance of amplicon deep sequencing to enhance the understanding of malaria epidemiology in a key region for malaria elimination and control was evaluated. P. falciparum specific DNA was quantified by qPCR targeting a fragment of the Pfldh gene using previously published primers [At two timepoints, between June and July 2016 (dry season) and between January and March 2017 (rainy season), randomly selected households in Nchelenge District, Zambia and two villages, Kilwa and Kashobwe, in Haut-Katanga Province, the DRC were enrolled in a cross-sectional survey. Consenting individuals living within enrolled households participated in a demographic survey and had finger prick blood collected as dried blood spots (DBS) on filter paper (Whatman 903™ Protein Saver Card). DBS were stored with desiccant in sealed plastic bags and transported to the Johns Hopkins Bloomberg School of Public Health in Baltimore, Maryland, USA. DNA was extracted from the DBS using 20% Chelex and the concentration of  primers  with SYBPlasmodium falciparum positive DNA extracts were amplified at the Pfama1 and Pfcsp loci. Pfcsp amplicon generation in 2016 was previously described [Pfama1 amplicons in 2016 were similarly generated. In brief, primers  were fused with Illumina adapter sequences and were used to amplify a 454-basepair (bp) region of Pfama1 [Pfama1 amplification reaction components included 9.25 μL of the extracted template DNA, 12.5 μL KAPA Hifi HotStart ReadyMix , 0.25 μL of the 20 μM reverse primer, 1.0 μL of the 5 μM forward primer, and 2 μL of 25 μM magnesium chloride. Amplicon generation cycling conditions were: 95 °C for 5 min, then 32 cycles of 98 °C for 30 sec, 58 °C for 1 min, and 72 °C for 1 min, followed by 72 °C for 5 min, and 4 °C thereafter. Amplicon sizes were confirmed using TapeStation  and purified using AMPure beads . Unique Nextera  indexes were added to amplicons in a subsequent PCR reaction described by Illumina [escribed . Pfama1 f Pfama1 . Pfama1 Bioinformatic processing was done for both sequencing runs at the same time using the same parameters. Forward and reverse read pairs were stitched, sorted by primer sequence, filtered for quality , and collapsed into unique parasite haplotypes within an individual using SeekDeep  . HaplotyPfcsp or Pfama1 haplotypes for each individual.Sequencing was performed in two different facilities in 2016 and 2017. In order to ensure that potential differential read depth by sequencing facility did not bias these estimates of population diversity by year, the R package, RTK, was used to perform a rarefaction analysis . RarefacPfama1 and Pfcsp haplotypes in each country, nucleotide diversity (π) within each country and among all samples, and the average number of nucleotide differences between samples from within and between countries. DnaSP was used to calculate haplotype diversity (Hd), which equals 1 in a population where every haplotype is unique and 0 in a population where every haplotype is identical. Genetic diversity metrics were compared across years and sampling locations.Software DnaSP (version 6.11.01) was used to calculate the number of unique https://www.geneious.com). Geneious was used to calculate pairwise relatedness between parasite pairs as the proportion of identical single nucleotide polymorphisms (SNPs). Pairwise comparisons were then grouped into two categories depending on whether they occurred between two parasites isolated from individuals living in the same country or between two parasites within individuals residing in different countries. Mean within-country relatedness was compared between parasite pairs to the mean between-country relatedness between parasite pairs, both in an unstratified analysis as well as an analysis stratified by age. To detect signatures of population structure between parasites from Zambia and the DRC, the R package, adegenet [ST and test for population differentiation between P. falciparum isolates from Zambia and the DRC at each of the Pfama1 and Pfcsp loci.FASTA files containing sequences for each parasite haplotype were aligned using Geneious (version 9.1.5)  resulted in sequencing reads passing quality filtering for Pfama1 and 144  for Pfcsp. In total, 554 P. falciparum sequences representing 117 unique haplotypes were characterized at the Pfama1 locus and 592 sequences representing 83 unique haplotypes at the Pfcsp locus . Additional file Pfama1 regression R2 = 0.99; Pfcsp regression R2 = 0.99)  or Pfcsp (p = 0.15) loci. Together, these observations are consistent with the hypothesis that parasites from Zambia and the DRC represent a single, highly genetically diverse population.Further, after calculating pairwise genetic relatedness between all pairs of parasites, there was no significant difference in relatedness comparing parasites from within the same country to parasites from different countries for either csp Fig. . Age strcsp Fig. . DAPC anPfama1 isolates and n = 106 Pfcsp isolates in the DRC 2016) and after (n = 170 Pfama1 sequences and n = 197 Pfcsp sequences in the DRC 2017) the ITN distribution. There was no evidence of an allele frequency mode-shift indicative of a population bottleneck comparing the DRC isolates from 2016 and 2017. Similarly, a mode-shift was not detected from the haplotype frequency distributions either , but consistent with the other findings of this study, MOI did not decrease among individuals from the DRC in 2017 following the ITN distribution   between Pfcsp sequences from Zambia and the DRC  and not indicative of population differentiation  found among a randomly selected group of samples of increasing size (X-axis). Curves on the left were generated using the raw (unrarefied) dataset, while curves on the right were generated from the dataset rarefied to a depth of 200 reads per sample. Fig. S2. For each amplicon , we performed 1000 re-sampling replicates of rarefaction. For each replicate we estimated MOI in each individual using the rarefied data. The distribution of MOI estimates across all rarefaction re-sampling replicates are plttoed along the Y-axis. The X-axis shows the MOI estimate from the raw data. The red dashed line is the Y = X line, or what would be expected if there was no difference between the estimate using rarefied data and the true estimate. Fig. S3. Pairwise genetic relatedness  is plotted for all pairs of parasites from different countries or from the same country for each amplicon, Pfama1 (left) and Pfcsp (right). Comparisons between two parasites from individuals both under 5 years old are shown in pink. Comparisons between two parasites from individuals both 5 years or older are shown in blue. Comparisons between parasites from an individual 5 years or older and an individual under 5 years are shown in yellow. Fig. S4. Haplotype frequency distributions are plotted for the haplotypes present in each population . Fig. S5. Left: plots the proportion of haplotypes within the four country-year “populations” considered to be rare. Here rare haplotypes are those represented at 2% or less in the “population.” Right: plots the proportion of haplotypes within the four country-year “populations” that were observed only once (singletons). Fig. S6. Dicriminatory analysis of principal components (DAPC) was performed using R package, adgenet. DAPC performs linear discriminat analysis on principal components in order to maximize separation of a priori groups. A, B: Pfama1; C, D: Pfcsp. A, C: DAPC performed using all sequences regardless of population frequency shows no linear function that can classify the principal components of the parasite seqeunces reliably by country. B, D: DAPC using only rare haplotypes (singletons) results in more refined population discrimination for Pfcsp. Fig. S7. Dicriminatory analysis of principal components (DAPC) was performed using R package, adgenet. DAPC performs linear discriminat analysis on principal components in order to maximize separation of a priori groups. A, B: Pfama1; C, D: Pfcsp. A, C: DAPC performed using all sequences regardless of population frequency shows no linear function that can classify the principal components of the parasite seqeunces reliably by country. B, D: DAPC using only rare haplotypes (2% or less frequency) results in more refined population discrimination for Pfcsp.


Theileria annulata infection is a significant livestock disease affecting cattle health and productivity resulting in substantial monetary losses in several countries. Despite the use of an effective vaccine for disease control still, a high incidence of infection is reported from India. One of the many reasons behind the ineffective disease control can be the existence of genetically diverse T. annulata parasite population in India. Therefore, studies focusing on understanding the genotypes are warranted. In this study, we have performed a genetic analysis of the Indian T. annulata field cell lines and the vaccine line using microsatellite markers, Genotyping based sequencing (GBS) and tams1 gene polymorphism. The degree of allelic diversity and multiplicity of the infection was determined to be high in the Indian population. No geographical sub-structuring and linkage disequilibrium were observed in the population. High population diversity was found which were similar with countries like Oman, Tunisia, and Turkey in contrast to Portugal and China. The presence of multiple genotypes as determined by microsatellite marker genotyping, GBS analysis and tams1 gene polymorphism point toward a panmictic parasite population in India. These findings are the first report from India which would help in understanding the evolution and diversity of the T. annulata population in the country and can help in designing more effective strategies for controlling the disease.Tropical theileriosis caused by  Theileria annulata belonging to the phylum apicomplexan, its life cycles requires a vector (ixodid tick) and host . Currently, a live attenuated schizont lymphocyte cell line is used as a vaccine for controlling the T. annulata infection in India   . The genike Oman , Sudan, ike Oman , 2011 Poike Oman , and Chiike Oman . Howevers1 genes . With silciparum . Genotyplciparum .T. annulata parasite for developing new vaccines, new therapies, and designing more effective disease controlling strategies. In this study, we have used the T. annulata live attenuated vaccine line and parasite cell lines isolated from animals infected by T. annulata for understanding the antigenic, allelic, and genotypic diversity of the Indian parasite population. Our study will not only help in understanding the genetic diversity in the Indian T. annulata parasites but also provide a comparative account with parasites from different countries and vaccine line currently in use.It is significant to study the genetic diversity of the Theileria annulata infected lymphocyte cell lines were established by culturing the peripheral blood mononuclear cells (PBMCs) isolated from the whole blood of the infected cattle from the states of Telangana and Andhra Pradesh in India. The infected animals were cross breed (Jersey breed) and had never been vaccinated against tropical theileriosis. The cell lines were grown in the RPMI 1640 medium at 37°C as per standard protocol (T. annulata surface protein (Tasp) primers as mentioned in Table 1.protocol . The vacT. annulata parasites , VD (Variance of the pairwise differences), LMC (Upper 95% confidence limits of Monte Carlo simulation), and LPARA (parametric tests) were calculated using Lian 3.7  and minisatellite  markers were used for genotyping arasites . The 5′ arasites , 2011. TTable 2; , 2011. TTable 2; . The genLian 3.7 .T. annulata genome specific reads were separated through alignment using Bowtie2, and aligned reads from each of the samples were used for variant identification. A merged FASTQ file was generated for all the six samples using the good reads for the organism. This merged FASTQ file was aligned to the reference genome of T. annulata (GCF_000003225.3) using Bowtie2. The alignment quality was checked using Qualimap software. To filter out low-quality SNPs/variants, the TASSEL-GBS pipeline was used for filtering minor allele frequency (MAF) and inbreeding coefficient. The consensus sequence generated from the run for each cell line was used for performing a multiple sequence alignment using ClustalW algorithm. The Ankara genome sequence was also included in the analysis as a control. Gblocks program was used to identify the conserved stretches in the genomes. Finally, MEGA7 program was used to calculate the phylogenetic distance between the parasite strains and for drawing a phylogenetic tree using the consensus sequence  was checked for its quality and quantity using Nanodrop and Qubit. Genomic DNA (300 ng) was digested by double digestion using Pstl-HF and MluCl restriction enzyme at 37°C for 4 h. The resulting digested fragments were directly ligated to a pair of restriction site-specific adapters at 20°C for 1 h using T4 DNA ligase. The adapter-ligated fragments were subjected to PCR amplification (10 cycles) to amplify the adapter-ligated fragments and to add sample specific dual index barcodes . The amplified Illumina-compatible sequencing library was quantified by Qubit fluorometer  and its fragment size distribution was analyzed on Agilent 2200 Tape Station. The library was used to run the Illumina single-end sequencing  for all the samples. The raw reads quality from the Illumina run were checked using FastQC. sequence . The evotams1 gene using for and rev primers (Table 1). The purified PCR products of 858 bp were then cloned into the pBSK vector using the TA cloning method followed by Sanger’s sequencing to confirm the tams1 gene. The sequencing results were further confirmed by checking the specificity of the sequence using blast analysis. The previously published tams1 gene sequences from the three continents Asia, Africa and Europe were used for calculating the phylogenetic relationship between the strains using MEGA7 software  was observed for TS6 marker. Whereas low polymorphism (n = 1) was observed against markers TS16, TS12, TS5, and TS25 in C2, C6, C4, and C1 cell lines (Table 2).Microsatellite analysis was done for the seven parasite cell lines  using the 10 markers. All the markers showed high polymorphisms in the Indian parasites although in few cell lines a single allele was observed for TS16, TS12, TS5, and TS25. The diversity of alleles ranged from one to twenty among the Indian parasite cell lines. In C3, C4, and V, highest polymorphism . The MOI range of the Indian population was higher when compared to the parasite from Sudan, Oman, China, Portugal, and Turkey which ranged from 1.0 to 5.78.The MOI for the Indian parasitic cell lines ranged from 3.3 to 7.8, with an average MOI of 5.31 (e) for the Indian population was found to be 0.82041 which was determined by using the predominant allele dataset for each marker and averaged across all ten loci (Table 3). For understanding the Indian population differentiation, linkage analysis was performed by calculating values of ISA = 0.0191 and VD = 0.4571 which was found to be less than LMC = 0.6571 and LPARA = 0.5732 indicating linkage equilibrium (LE). The PCoA analysis showed no specific geographical distribution between the Indian parasites when compared to the parasites from other countries like Oman, Sudan, Tunisia, and Turkey. The analysis showed C1 and C2 parasites cluster with Sudan while C5 and C6 with Tunisia and Oman suggesting allelic similarities. The C3 and V clustered together in a separate cluster while C4 and parasite from Turkey didn’t cluster with anyone. The variation among the samples was found to be 53.11 and 29.27% for the first and second coordinates of the graph, respectively .The allelic profiles were used to create MLG data set for each marker using the predominant allele for the Indian population. The MLG data was further used for calculating heterozygosity, linkage disequilibrium and the genetic distance between the parasite strains. The estimated heterozygosity . The distribution of SNP call rate for the samples ranged from 7.87 to 23.61% and was represented for the individual samples . The SNPs were well distributed among the four T. annulata chromosomes (Chr) with Chr 1 having the highest number 3210 SNPs followed by Chr 2, 3, 4, and mitochondrial DNA in all the samples . The phylogenetic relationship between the Indian parasites (n = 6) were calculated based on the SNPs detected in the GBS sequences including the Ankara parasite sequence. The analysis identified C1 and C6 close to the Ankara sequence based on the genetic polymorphisms in the respective sequences. C4 and C5 were clustered together while C2 showed similarity with V .The Illumina reads generated after sequencing were aligned with the tams1 gene sequences of seven Indian parasites (GenBank accession IDs MK034698-MK034704) and 25 previously reported parasites. The clusters were divided into two groups on the basis of previously published data . The Indian isolates were distributed in both groups along with other countries like Spain, Italy, Tunisia, Iran, Bahrain, Turkey, and Iraq.The phylogenetic analysis was performed based on the neighbor-joining method using the hed data . C1, C2,T. annulata, theileriosis is frequently reported in India (Theileria infected bovine lymphocyte cell lines were utilized for understanding the parasite diversity in India using microsatellite markers, tams1 gene-based antigenic diversity and GBS analysis. The vaccine strain from India and the already published data for other worldwide T. annulata strains were used for understanding and comparing the diversity among the parasite cell lines.Despite the availability of a vaccine against in India . The genP. falciparum (The microsatellite data analysis showed high population diversity among Indian parasites, which is in line with previous findings from Oman, Tunisia, and Turkey though less diversity was reported from Portugal and China . The prelciparum . The MOIlciparum . The alllciparum . The smatams1 gene has been shown to be a promising candidate for carrying antigenic diversity studies in T. annulata parasites (tams1 gene sequence with some suggesting no geographic specificity and other showing region specificity based on the gene polymorphism (The arasites . There amorphism . Our resmorphism .T. annulata parasites is tricky as it is difficult to separate the pure parasite from the host lymphocyte cell. The presence of host DNA in the sample has led to low SNP call rate for the parasite in our GBS study. In future, we plan to use more powerful techniques like WGS with high coverage to better understand the genetic diversity and the genome of the Indian parasite strains.The GBS analysis also confirmed the genetic diversity among the Indian parasites. The analysis showed few strains from India to be similar to Ankara strain from Turkey based on the diversity in the parasite genome. The phylogenetic tree showed a panmictic parasite population in India based on the genetic diversity. The major limitation associated with next-generation sequencing methods like GBS is the purity of the DNA sample, which in case of T. annulata but also compares it with the isolates reported from other countries. It also sheds light on the genetic and allelic diversity among the Indian parasite and the vaccine by the use of microsatellite marker, tams1 sequencing and GBS. These findings indicate that a heterogeneous parasitic population is prevailing in India causing theileriosis and may render the vaccine ineffective due to high diversity. It is essential to perform genetic diversity studies including the parasite population from different parts of India to map the diversity among the overall natural parasite population. It will help in identifying new vaccine targets and policy to control the disease.The current study not only highlights the genetic and allelic diversity present among the Indian PS designed the study. SR, VB, DD, and SM performed the experiments. SR, VB, and PS compiled and analyzed the data. VB and PS wrote the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.