Phocoena phocoena phocoena). Yet, we identified important departures from random mating and restricted dispersal forming a highly significant isolation by distance (IBD) at both mtDNA and nuclear markers. A ten times stronger IBD at mtDNA compared with nuclear loci supported previous evidence of female philopatry. Together with the lack of spatial trends in genetic diversity, this IBD suggests that migration–drift equilibrium has been reached, erasing any genetic signal of a leading‐edge effect that accompanied the predicted recolonization of the northern habitats freed from Pleistocene ice. These results illuminate the processes shaping porpoise population structure and provide a framework for designing conservation strategies and forecasting future population evolution.Understanding species responses to past environmental changes can help forecast how they will cope with ongoing climate changes. Harbor porpoises are widely distributed in the North Atlantic and were deeply impacted by the Pleistocene changes with the split of three subspecies. Despite major impacts of fisheries on natural populations, little is known about population connectivity and dispersal, how they reacted to the Pleistocene changes, and how they will evolve in the future. Here, we used phylogenetics, population genetics, and predictive habitat modeling to investigate population structure and phylogeographic history of the North Atlantic porpoises. A total of 925 porpoises were characterized at 10 microsatellite loci and one quarter of the mitogenome (mtDNA). A highly divergent mtDNA lineage was uncovered in one porpoise off Western Greenland, suggesting that a cryptic group may occur and could belong to a recently discovered mesopelagic ecotype off Greenland. Aside from it and the southern subspecies, spatial genetic variation showed that porpoises from both sides of the North Atlantic form a continuous system belonging to the same subspecies ( PorpoisP. p. vomerina, P. p. phocoena, and P. p. relicta, respectively. Porpoises from the upwelling zones off Iberia and Mauritania have been recently identified as genetically divergent as P. p. phocoena and P. p. relicta, based on DNA sequence analysis of a quarter of the mitogenome . Demo‐genetic inferences suggested that the three lineages in the North Atlantic and the Black Sea split during the LGM and were following independent evolutionary trajectories making them distinct evolutionary significant units  that porpoises on each side of the North Atlantic could have evolved independently, recolonizing their current ranges from distinct source populations living in distinct southern refugia during the LGM  could be that suitable habitats were shifted southward without any loss of connectivity between populations from each side of the North Atlantic, therefore leading to no lineage split between each side of the North Atlantic and to limited population contraction. These two hypotheses are expected to leave distinct signatures on the genetic variation of natural populations. Under hypothesis 1 (two distinct refugia), two divergent genetic lineages would be expected, one on each side of the North Atlantic, similar to what was previously observed around the Mediterranean Sea  of the mitochondrial control region harbored limited phylogenetic information, as shown by the previous shallow and poorly resolved phylogenetic trees and networks  evaluated the postglacial population responses and recolonization routes from the analyses of spatial patterns of genetic variation and whether porpoises recolonized their present range from one or multiple refugia; (3) assessed the impact of environmental changes in the distribution of harbor porpoise by modeling the evolution of suitable habitats at present, during the LGM, and by the year 2050; and (4) analyzed dispersal behaviors at the North Atlantic scale and whether restricted dispersal could generate isolation‐by‐distance patterns as previously reported in NEA .Specifically, we (1) assessed whether distinct mtDNA lineages were present in 22.1We combined previous nuclear microsatellite genotype data at ten loci for the 768 samples from central and eastern North Atlantic populations  following the manufacturer's recommendations. DNA quality and quantity of the extraction products were checked by electrophoresis on an agarose gel stained with ethidium bromide and using a fluorometric quantitation procedure using a Qubit v.3.0 (Thermo Scientific). The microsatellite genotyping procedure followed the protocol described in Fontaine et al. , FontainCyt‐B, ATP6, ATP8, ND5, and COXI) was obtained for a subsampling of 55 individuals from NWA . The 55 newly sequenced NWA samples were combined with 81 previously generated mtDNA sequences from central and eastern North Atlantic porpoises , which allows displaying distances among haplotypes in a number of mutational steps and reticulations among them. Finally, we also summarized genetic relationships among haplotypes using a nonmetric multidimensional scaling (nMDS) based on the Jukes–Cantor genetic distances between pairs of sequences. We used MEGA v.7.0  approach of 2.3Adegenet v2.1.1 R package  maximizing the difference between NWA and NEA or among geographical subgroups in order to assess fine‐scale population structure. Then, we displayed genetic variance with a spatial structure using a sPCA, which accounts for spatial autocorrelation among allele frequencies. We used the Delaunay triangulation as a connection network on a subset of 729 individuals with no missing data in both geographic coordinates and microsatellite genotypes. We used both “global” and “local” test procedures based on the Monte Carlo permutations (104 permutations) to interpret the significance of the spatial principal components in the sPCA  and Northeast  Atlantic at the microsatellite and mitochondrial loci. For the microsatellite dataset, we first assessed the patterns of missing data and heterozygosity deficit at the local scale Table  to identJombart,  on centeSTRUCTURE v.2.3.4  expectations among loci. Therefore, contrary to multivariate methods, STRUCTURE identifies genetic clusters by minimizing departures from HWLE. It estimates the genetic ancestry proportions of each individual multilocus genotype to K ancestral clusters. STRUCTURE was performed for a dataset with and without missing data. We used the locprior admixture model with correlated allele frequencies, which is capable of detecting weak genetic structure when it exists without forcing it  ranging from 1 to 5. Each run used 1 × 106 iterations after a burn‐in of 1 × 105 iterations. To evaluate the convergence of the Monte Carlo Markov chains (MCMCs), we performed 10 independent replicates for each K value and checked the consistency of the results using CLUMPAK v.1.0  of the predominant solution for the best K by computing the spatial interpolation of Q values among sampling locations using the script provided at http://membres‐timc.imag.fr/Olivier.Francois/TESS_Plot.html. We also ran STRUCTURE focusing only on P. p. phocoena individuals, as it has been suggested that rerunning STRUCTURE on identified clusters may reveal finer‐scale genetic structuring  among microsatellite loci within putative groups using a st Weir,  implemenRousset, . We alsoAr), private allelic richness (pAr), and observed (Ho) and expected (He) heterozygosity. The calculation of Ar and pAr was performed in ADZE  were discarded. Ho and He were first computed with diveRsity without applying any rarefaction standardization. Differences in genetic diversity between geographical regions were tested using a Wilcoxon signed‐rank test for paired samples. Bonferroni's corrections were applied to adjust significance levels for multiple tests. For the mtDNA genetic variation, we estimated nucleotide diversity (π), Watterson's θW, and haplotype diversity (Hd) using DnaSP.Genetic variation at microsatellite loci was estimated per geographical regions Figure  and subgAr and pAr with ADZE already implement a standardization to account for differences in sample size among groups, calculations for the other statistics did not. Differences in sample size can significantly impact the values of genetic diversity estimators  Rousset, . IBD desFST/(1−FST), which is expected to increase linearly with increasing geographical distance under IBD  to test specifically for IBD, excluding individuals south of the northern Bay of Biscay to avoid the effect of inter‐subspecies comparison. We used a Mantel test to assess the correlation significance between genetic and geographic marine distances using 1 × 106 permutations in the R package ade4 v1.7  between groups  in each geographical region were estimated with NeEstimator v2.1.3  between the geographical regions and the subgroups was estimated by combining Ne and m estimates.We further quantify the amount of dispersal, connectivity, and contemporary gene flow between geographical regions and subgroups that included at least 10 individuals using the “ics Nei, , to infe.1 Dyer,  in R. No.1 Dyer, . Contemp2.7Ne) changes based in mtDNA data, we estimated Tajima's D and Fu and Li's D* in each geographical region using DnaSP. These two statistics assess the deviation from the site frequency spectrum from the pattern expected under a neutral constant size model. For microsatellite loci, evidence of Ne changes in each geographical region was assessed using the Garza and Williamson ratio (MGW)  was identified as best fitting the data according to the BIC criterion. The maximum‐likelihood tree confirmed previous reports of how deep genetic divergence was between Pacific and Atlantic porpoises and that no haplotype was shared between the two ocean basins  IBMA, which included two distinct sublineages in the upwelling waters of Iberia (IB) and Mauritania (MA); (iii) P. p. phocoena composed of the porpoises sampled from the North Sea to the Arctic waters of Norway, and westward across the mid‐North Atlantic waters, off Iceland, Western Greenland, and then southwards along the North American coasts of Canada, and Gulf of Maine in the United States; and (iv) a fourth not previously reported lineage carried by a single individual from WGLD (Hap 47). We resequenced this WGLD sample twice to ensure this was not an artifact. This lineage was equally divergent from the three other lineages identified in the Atlantic and Black Sea waters  between this Hap_47 haplotype and the other three lineages ranged from 0.45% to 0.67%  lineage. Hap_47 was excluded for downstream analyses of mtDNA genetic diversity because it was clearly not closely related to any of the other NAT individuals and would bias the estimates of genetic diversity.The mtDNA alignment of 148 sequences (excluding the outgroup) contained 359 segregating sites, including 118 singletons and 241 parsimony informative sites defining 110 distinct haplotypes Table . Among 8s Figure . Within s Figure   was observed within the BS, MA, IB, and NBB groups with overall fixation index FIS values ranging from −0.018 to 0.047  IBMA including the two subgroups IB and MA; and (iii) P. p. phocoena. The first principal axis of variation or discrimination . By contrast, none of the negative sPCs were significant in the local sPCA test  individuals, none of the sPC were significant . Likewise, the DAPC did not reveal any evidence of population subdivision within the P. p. phocoena (NAT) subspecies  tested and was consistent with the multivariate analyses. The probability of the data greatly increased until K = 3, which showed the highest values on average  in Western Greenland (WGLD) could not be distinguished from other NAT porpoises based on the microsatellite data. This may just be due to the fact that only one individual of a distinct cluster has been sampled or this individual may also share most of its genetic ancestry with the NAT group at the nuclear loci, but not at the mtDNA locus.p‐value <0.001) and much higher than the comparisons among demes within each subspecies  subspecies, microsatellite FST values among the geographical regions , IBMA, or P. p. relicta (BS) subspecies is not simply an effect of the increasing geographic distance , low in the hybrid NBB (Ne = 217), intermediate in P. p. relicta (Ne = 504), and larger in P. p. phocoena . Furthermore, Ne differed substantially among demes within P. p. phocoena. Demes in central North Atlantic  displayed slightly smaller Ne than in the Eastern  and Western  waters.We quantified gene flow using microsatellite markers by estimating local effective population sizes . Likewise, the two lineages IB and MA of IBMA in the upwelling waters showed very limited amount of gene flow between them  in both directions. Gene exchanges from NBB to P. p. phocoena ranged from 0.083 to 0.174 and were larger than those from NBB to IBMA (from 0.021 to 0.064). Finally, although not statistically significant, m values from NBB to IBMA were two to three times lower than the converse. Among P. p. phocoena (NAT) demes, we detected a clear signal of migration with m varying from 0.18 to 0.9  and two estimators of nucleotide diversity (π and θw), was lowest in the two populations of IBMA, slightly higher in P. p. relicta, and highest in P. p. phocoena. At the contact zone between IBMA and P. p. phocoena, NBB displayed the highest mtDNA diversity of all geographical regions, which is expected given the mixture of divergent haplotypes from the two subspecies in that region. North of the Bay of Biscay, the genetic diversity was more homogeneous across the North Atlantic among P. p. phocoena demes. It was slightly higher in NS, IC, and WGLD. However, when accounting for difference in sample sizes, standard errors of all estimates overlapped , private allelic richness (pAr), and expected heterozygosity (He) . These subspecies displayed significantly lower diversity than the admixed porpoises (NBB) and those from P. p. phocoena . NBB porpoises showed lower Ar and He than P. p. phocoena  and lower pAr than USA, NS, and CA, similar to IC and NN and higher than WGLD . While Ar and He statistics were comparable among P. p. phocoena demes, pAr was significantly higher in USA  and lower in WGLD . NS also displayed significantly higher pAr than WGLD, IC, and NN . The remaining geographical regions showed no significant difference in pAr .The level of microsatellite diversity was comparable between P. p. relicta (BS) and IB population within IBMA as shown by significant negative values for both Tajima's D and Fu & Li's D* statistics . Noteworthy is the increase in habitat suitability during the LGM  and another one (IBMA) in the upwelling waters of Iberia and Mauritania , displayed the same level of divergence as the three other subspecies previously identified in the North Atlantic and Black Sea Figure  ruled ouP. p. phocoena populations. Moreover, Nielsen et al.  without being broken down by recombination and thus without being impacted by homogenizing effects of gene flow with other lineages. We cannot completely rule out that this divergent mtDNA haplotype may reflect past population divergence that does not exist anymore. The haplotype may still persist at low frequency in the population without being broken down by recombination due to incomplete lineage sorting. This could explain the lack of distinctiveness of this individual at the nuclear microsatellite markers, despite the persistence of a divergent mtDNA haplotype. Future studies with a larger sample size and genome‐scale genetic markers shall examine in greater detail the genetic structure and evolutionary history of this peculiar group.This new mtDNA lineage in Western Greenland is reminiscent of the recent discovery of a cryptic ecological group of harbor porpoises in the exact same area by Nielsen et al., . Satellin et al.  found, bRaja clavata (L.), Rajidae)    that conditions the strength of genetic drift. We showed recently using simulations that such a “gray zone” would be short in cetacean species such as porpoises, displaying relatively low fecundity and small Ne  to be able detect highly significant FST values using 10 diploid nuclear microsatellite markers and four time less with haploid markers such as the mtDNA. Therefore, the lack of genetic fracture between eastern and western North Atlantic demes of P. p. phocoena at both mtDNA and nuclear microsatellite markers is not the result of a population gray zone effect. It rather suggests this subspecies remained unfragmented during the LGM or that any subdivisions that previously existed were erased by dispersal during the postglacial colonization of northern waters progressively freed from Pleistocene ice.It was originally hypothesized that harbor porpoises on each side of the North Atlantic could have been isolated from each other in distinct glacial refugia, recolonizing northern waters from different southern refugia Gaskin, . Our resy Figure . One couy Figure , includiy Figure . This peP. p. phocoena during the LGM. This agrees with our previous results based on coalescent‐based inferences that showed a steady increase in effective population size of P. p. phocoena porpoises in the Northeast and central North Atlantic since the time of the MRCA (TMRCA) more than 50 kyr ago without any evidence of historical population contractions  and the variance of intergenerational parent–offspring's dispersal distance (σ2). Both parameters combined (Dσ2) form the neighborhood size (4πDσ2). This neighborhood size reflects the local effect of genetic drift and gene flow in a stepping stone population model  and thus to an increase in IBD strength at the maternally inherited mtDNA locus. In contrast, male‐biased dispersal would create highly variable father–offspring's intergenerational dispersal distances, thus increasing σ2microsatellites. Direct observations of such female‐restricted dispersal driven by female philopatry in harbor porpoise were recently demonstrated by satellite tracking in West Greenland, the central North Atlantic, and the North Sea , estimated for the mtDNA locus is thus also four times smaller than for microsatellite loci. Hence, genetic drift is increased in the first compared with the second type of marker. Therefore, the combined effect of reduced intergenerational mother–offspring's dispersal distance driven by female philopatry and the reduced effective mtDNA population size may explain the dramatic differences observed between the two types of genetic markers.Interestingly, IBD at the mtDNA locus was ten times stronger than at the nuclear microsatellite loci. Previous studies reported analogous evidence by observing significant genetic differentiation at the mtDNA locus that was weak or absent at microsatellite loci among demes in the Northwest Atlantic , but by‐catch mortalities in commercial gillnet fisheries are by far the most immediate threat to the species  or indirect estimations such as those provided by population genetics. This would allow assessing the resilience of harbor porpoises in the face of observed by‐catch rates. Such simulations would be a valuable tool to assess the status of local demes across the North Atlantic, to design tailored conservation strategies, and identify areas of the species distribution range that are at high risk of local depletion that could disrupt gene flow and fragment populations.Previous definitions of MUs proposed by the IWCs and ASCOBANS were recently reviewed by the IMR and NAMMCO report  and stilAll the individuals used in this study were sampled between 1990 and 2000. The genetic structure depicted here may thus just represent a temporal snapshot and may have already changed with the accelerated environmental changes we are experiencing. Ongoing environmental changes for instance have triggered profound reorganization of the North Atlantic ecosystems with impacts first upon primary production and in turn influenced top predators including harbor porpoises  concluded that despite the absence of clear genetic discontinuities between porpoise demes across the  conclude5e.g., Azorean waters). These distinct ecotypes likely display specific adaptations, as suggested by their distinct behaviors, feeding ecology, habitat use, and genetic ancestries. Future genomic studies will certainly refine the evolutionary history of each ecotype and shed light on how natural selection may have contributed to their distinctiveness (Cammen et al., In the present study, we confirmed the undoubtedly deep separation existing between Pacific and Atlantic harbor porpoises that was previously identified as well as the acknowledged distinct ecotypes or subspecies of harbor porpoises previously reported in the Northeast Atlantic, Iberian, and NW African upwelling waters, and Black Sea. However, we also discovered a new divergent mitochondrial lineage in one individual from West Greenland waters, suggesting that a fourth ecotype may exist. It may be related to the new oceanic group of porpoises recently identified in that area, which could have emerged during the LGM in an offshore glacial refugium (The authors declare that they have no conflict of interest.MCF designed and supervised the study; PR coordinated the sampling in NWA and made them available for the present study; JT and RL performed the laboratory work and collected the data with help from MCF; YBC and RL analyzed the data; KK and CG generated the habitat models with help from YBC and MCF; YBC, RL, and MCF interpreted the results and wrote the manuscript with input and final approval from all the coauthors.Supplementary MaterialClick here for additional data file.


Phoenix dactylifera L.) is a perennial monocotyledonous plant belonging to the Arecaceae family, a special plant with extraordinary nature that gives eminent contributions in agricultural sustainability and huge socio-economic value in many countries of the world including Ethiopia. Evaluation of genetic diversity across date palms at DNA level is very important for breeding and conservation. The result of this study could help to design for genetic improvement and develop germplasm introduction programmes of date palms mainly in Ethiopia.Date palm tree  to 0.374 (MPdCIR016); effective number of alleles with a mean value of 6.61, private alleles ranged from 0.0 to 0.65; observed heterozygosity ranged from 0.355 to 0.726; expected heterozygosity varied from 0.669 to 0.906, polymorphic information content with a mean value of 0.809; fixation index individuals relative to subpopulations ranged from 0.028 for locus MPdCIR032 to 0.548 for locus MPdCIR025, while subpopulations relative to total population value ranged from − 0.007 (MPdCIR070) to 0.891 (MPdCIR015). All nine accesstions, neighbour-joining clustering analysis, based on dissimilarity coefficient values were grouped into five major categories; in population STRUCTURE analysis at highest K value, three groups were formed, whereas DAPC separated date palm genotypes into eight clusters using the first two linear discriminants. Principal coordinate analysis was explained, with a 17.33% total of variation in all populations. Generally, the result of this study revealed the presence of allele variations and high heterozygosity (> 0.7) in date palm genotypes.Microsatellites (SSR) are one of the most preferable molecular markers for the study of genetic diversity and population structure of plants. In this study, we found the presence of genetic variations of date palm genotypes in Ethiopia; therefore, these genetic variations of date palms is important for crop improvement and conservation programmes; also, it will be used as sources of information to national and international genbanks.The online version contains supplementary material available at 10.1186/s43141-021-00168-5. Phoenix dactylifera L.) is a diploid plant with 2n = 36 chromosome number, a perennial monocotyledonous plant belonging to the Arecaceae family [Date palm tree , and information related to data collection of all samples is available in detail as additional file with a manuscript  primers developed by  were useK1 to K10). The admixture ancestry model and correlated allele frequency model were used to perform a Markov chain Monte Carlo simulation algorithm (MCMC). The length of the burn-in period was set to 100,000; MCMC after the burn-in period was set to 200,000, and was run 10 times for each K to estimate K values. Optimal K value among K groups was determined based on [K drawn as coloured box plots.Amplified DNA fragments produced in each microsatellite locus was manually recorded , DST2 , D'ST2  and D'IS2  using Popgen32 version 1.31.In addition to STRUCTURE analysis, we performed DAPC, an assumption-free multivariate clustering method  using thA wide range of allele variants were observed from each locus Table . A totalP < 0.001. The highest (7.0) and the lowest (4.7) mean values of the number of different alleles with a frequency ≥ 5% was in Mego and Legaharae, respectively. The mean of number of locally common alleles with a frequency ≥ 5% found in 25% of the total populations was ranged from 0.2 (in Errer Gota) to 0.7 (in Mamulae) whereas, the mean number of locally common alleles with a frequency ≥ 5% found in 50% of the total population ranged from 0.8 (in Kerebuda) to 1.7 (in Mamulae) , expected heterozygosity (He) and fixation index ; these are presented in Table K value had the highest peak, at K = 3 . The S= 3 Fig. c and rev= 3 Fig. a as wellIT2 was 0.04681. A total average of D'IS2 (0.0435) was larger than D’ST2 (0.0033). Besides, the average value of DST2 (0.0265) was greater than the average of DIS2 (0.0201). From the total pairs of loci, only 30 pairs of loci was shown in the dual relationships of DST2 > DIS2 and D'IS2 > D’ST2 in Table ST2 < DIS2 and D'IS2 < D’ST2; this is because gametes with favorable combinations of alleles would increase in every population [Using the Bayesian model-based approach, the membership probabilities of each date palm individual for the different groups were obtained from DAPC and the results of DAPC analysis. The DAPC separated date palm genotypes into eight clusters based on the first two linear discriminants Fig.  Table 3.IS2 0.043 was largpulation , 37.FigThe purpose of the present study is to determine the genetic diversity and relationship between date palm genotypes and populations using SSR markers. All of the SSR primers tested in this study demonstrated PIC values from 0.509 to 0.899; these are considered to be highly informative markers and the occurrence of allele variations among populations; this is also supported by previous studies , 39. A tkebele, five individuals from Mamulae kebele, three individuals from Alassabolo kebele and one individual from Errer Gota were clustered together with these early introduced cultivated date palm varieties . Other cultivated varieties  were found in cluster two with mixed individuals from Legaharae, Berga, Humodoyta, Error Gota, Alassabolo and Mamulae populations. Barhee cultivated variety was only found in cluster five incorporated with individuals from other populations. Half of date palm genotypes from Kerebuda population mainly observed in the subcluster of a clade four categories. This result was also supported with results in PCoA and population STRUCTURE analysis . The present result of PCoA showed certain match with the previous studies reported by [K = 3, the most probable clustering of populations was observed at this K level and showed admixture structure among populations. This result displays the date palm populations that have a common genetic background and also they shared common alleles between them. The most differentiated population in this study was observed in Kerebuda population, which showed fewer admixtures than the other populations. Generally, the structure result had shown shared ancestry between unknown date palm genotypes and known date palm cultivars that were early introduced. The admixture result of the present study at K = 3 is in agreement with those reported by [K = 3 using different SSR as well as four date palm groups at K = 4 using SNPs. In both markers, they reported the admixture population structure of date palms at best K value of each cluster that was collected from different parts of the world. Intermixing clustering results of date palm genotypes in structure analysis of the present study to some extent coincides with the previous finding at five different K groups that were studied using different SSR primers [In this study, NJ tree and principal coordinate analysis outcomes provided clear genetic relationship between unknown date palm varieties and early introduced cultivated date palm varieties. The dendrogram generated five major clusters. Generally, in this study, there was no clear separation among genotypes according to their geographical locations. In cluster one, eight individuals from Humodoyta orted by , 41, conorted by –40, 42. orted by , 40, 43.orted by  revealed primers . Due to  primers . DAPC wa primers .Overall, the AMOVA result of expected heterozygosity revealed high genetic differentiation within date palm genotypes and the outcome of the NJ tree; PCoA and structure analysis of this study are dominated by admixture structure patterns among populations. This might be due to the codominant nature of microsatellite markers contributed to have high allele’s variations per locus as well as high heterozygosity within date palm genotypes due to DNA slippage during the process of DNA replication. DNA slippage is the mutation of microsatellite length during enzymatic replication of microsatellite regions that are usually the result of insertion and deletion of repeats in DNA strands , 47. On Preliminary research on genetic diversity of plant species is the most essential issue for long-term plant improvement and conservation and development of mechanisms for reduction of plant vulnerability. SSR markers used in the present study revealed high genetic diversity within date palm genotypes and date palm populations. Therefore, this finding contributes input information in genetic relationship between known cultivated date palm varieties and unknown date palm varieties for improvement and conservation programmes. Generally, this study will be an eminent evidence and source of information on genetic diversity of date palms in Ethiopia to regional and international genbanks.Additional file 1: Table 1 Data information of date palms in Ethiopia during the time of sample collection and cods of samples that were used for analysis.Additional file 2: Table 2 Microsatellite genotypic data of 124 date palm genotypes using 10 SSR markers.Additional file 3: Table 3 Proportion of individuals assigned in each DAPC cluster.Additional file 4: Figure 1 Examples of PCR products obtained by the following SSR primers: a) MPdCIR016, b) MPdCIR050, c) MPdCIR085 and d) MPdCIR093 e) M: 50 base pairs molecular weight markers used as a reference for scoring in this study.


This paper investigates the associations of income segregation with homicide mortality across 152 cities in Brazil. Despite GDP increases, an important proportion of the Brazilian population experiences poverty and extreme poverty. Segregation refers to the way that different groups are located in space based on their socioeconomic status, with groups defined based on education, unemployment, race, age, or income levels. As a measure of segregation, the dissimilarity index showed that overall, it would be necessary to relocate 29.7% of urban low-income families to make the spatial distribution of income homogeneous. For the ten most segregated cities, relocation of more than 37% of families would be necessary. Using negative binomial models, we found a positive association between segregation and homicides for Brazilian cities: one standard deviation higher segregation index was associated with a 50% higher homicide rate when we analyze all the socioeconomic context. Income segregation is potentially an important determinant of homicides, and should be considered in setting public policies. •The Dissimilarity index has a strong association with the number of homicides in large Brazilian cities.•The more segregated cities are, the greater the indicators of inequality and poverty.•The socioeconomic context matters for the reduction in the number of homicides.•Brazil is one of the most violent countries in the world, therefore reducing inequality and segregation is urgent. In different countries throughout Latin America and the Caribbean, about 80% of the population is living in urban areas; it is a dramatic increase from only 41.8%, in 1950 . This trAn important issue related to a fast and disorganized process of urbanization is income segregation. Segregation refers to the way that different population groups are located in space based on their socioeconomic status, whereby groups are defined by the education, unemployment, race, age, or income levels. Segregation, as a social phenomenon, started being investigated in the early 1920's, especially in the United States, by the so-called Chicago School including work by As a multidimensional phenomenon, the effects of income segregation are differently felt by distinct social groups and have a collective and lasting impact on the lives of the most vulnerable groups through, essentially, the spatial segregation of poverty . The authors also state that segregation implies that low-income families will generally live in neighborhoods with a lower average income than high-income families and this fact could be a result of perpetuation effect of an already existing socially discriminatory structure of inequality.Income segregation and income inequality differ because inequality deals with how unequal resource allocation is in society among all individuals, with high inequality leading individuals to marginalization. On the other hand, segregation deals with spatial inequality in resource allocation. Socioeconomic segregation mainly affects the population of large cities, due to the lack of urban planning and the market effects on urban land and housing allocation .Although limited, available evidence suggests that segregation may weaken social connections and increase violence rates . In a ciRegarding Brazil, Marques (2016) examined the relationship between segregation, poverty and social connections in two large metropolises. The research concluded that sociability among individuals within cities is conditioned by variables such as housing, income and employment. Segregation can deep patterns of inequalities and income concentration already accentuated in Latin America and Brazil . Thus, iThe high numbers and rates of homicides remain one of the majors health problems worldwide and especially in Latin America . Brazil,Few studies have investigated the links between income segregation and violence or homicides . UnderstWe included a direct association between segregation and homicides to emphasize that there is a strong relationship between them . HoweverThese mediators are relevant, as analyzing the social context within cities is essential for elaborating political agendas. Moreover, society needs actions that will require collective efforts by institutions in order to deepen investigations and point out plausible solutions for reducing violence in urban centers.In addition to this introduction, the paper is organized into 3 more sections. Section 2The analytic dataset includes 152 Brazilian cities of 100,000 residents or more, as defined by the Urban Health in Latin America  project. The project identified Latin American cities with more than 100,000 inhabitants across 11 countries. These cities are composed of one or more contiguous municipalities, as described in 2.1outcome variable is the total count of homicides in each city during the year 2010. The mortality dataset was originally obtained from the Brazilian Mortality Health Information System  and it was harmonized and consolidated by the Data and Methods Core team of the SALURBAL project. Homicides were defined using Global Health Estimates (GHE) code 1580 (violence) and 1600 , which includes all deaths resulting from aggressions and its aftermath, specifically the international classification of diseases (ICD-10) categories X85 to Y099 and the Y871, and Y35. Mortality data were corrected for undercounting, using estimates of undercounting based on Campos de The variables used in the regression analysis as potential city-level confounders and mediators are listed in The cross-sectional ecological analysis is based upon area-level linkage of homicide counts to 2010 population census data from the Brazilian Institute for Geography and Statistics . The Socioeconomic Status (SES) 2.2The key explanatory variable is the income-based dissimilarity index henceforth referred to as the socioeconomic segregation index (SSI). We obtained the SSI by using income data of each census tract in a city. That is, there is an aggregation of spatial levels. The indicator is calculated taking into account residents in a specific census tract, then in the neighborhood and, finally, in the city.The dissimilarity index by i is In equation The dissimilarity index measures the evenness with which poor and non-poor households are distributed across the census tracts that make up a city. Following the process presented by 32.3The outcome is the count of homicides in each city in the year 2010. Thus, we implement a set of binomial negative regression models to examine the relationship between segregation and homicides, considering a group of socioeconomic variables. All variables are aggregated at the city level, as defined by the SALURBAL project. The dataset is a cross-section for the year of 2010. The negative binomial regression is more adequate to obtain unbiased estimates since our outcome variable seems to be over-dispersed: the unconditional mean (247.2) of the number of homicides age-adjusted in 2010 is lower than its variance (351685.3).i represents each city, Equation E[homicidβ units in the dependent variable, assuming all the other variables in the model are held constant.All continuous independent variables, including the dissimilarity index, were converted in z-scores to simplify the interpretation, so that a change of 1 standard deviation (SD) in these predictors leads to an expected change of 33.1The most populous cities in Brazil in the last Census in 2010 were São Paulo, Rio de Janeiro in the Southeast region, Salvador in the Northeast region, and Brasília in the Midwest region, with 19.8, 11.9, 3.1 and 3.2 million inhabitants, respectively. The main indicators for the regions can be consulted in Appendix A. The cities with the highest homicides rates are mainly concentrated in the Northeast region, the country's most impoverished region. The Northeast region notably has the country's largest unemployment rates, as is shown in 3.22 = 0.25), as we show in A descriptive analysis of SSI and Gini Index, for the 5 Brazilian macroregions and according to cities size, is shown in When looking at the issues of regional inequality in Brazil, we observe that great disparities have perpetuated over time between the poorest and wealthiest regions of the country . Measuring the degree of inequality and socioeconomic segregation constitute current challenges for applied and social sciences, as they permeate areas of political and social conflict, violence, health-related issues, among many others , p. 376.3.3This result reinforces Brazilian cities' unequal characteristics concerning the lack of public policies aimed at protecting individuals in conditions of social vulnerability. Such a situation leads to an increase in violence and can lead to serious consequences such as the high level of homicides observed throughout Brazil. This also means that beyond segregation, the entire social adverse context impact on the level of interpersonal violence in large Brazilian cities.The observed correlation between socioeconomic segregation and homicides also strengths the findings of other similar works suggesting that segregation is harmful to health . In larg4The search for understanding the relationship between socioeconomic segregation and homicides in cities can inform the design of public security policies aimed to improve public health. For this reason, we aimed to measure segregation in the 152 Brazilian cities with a population of over 100,000 inhabitants to investigate its relationship with homicide rates. It is an effort to provide relevant evidence to urban policymaking to promote social inclusion and improve population's health. The results suggest that a reduction in the current levels of segregation may play an important role in policies aimed to reduce violent crimes. Cities with a higher socioeconomic segregation level experienced higher homicide rates, with minimally adjusted estimates suggesting a nearly 50% increase in homicides per 1 SD greater segregation.Additionally, variation in the socioeconomic segregation index itself showed it would be necessary to relocate 29.7% of the households in a typical large Brazilian city to reach a homogeneous spatial distribution concerning income across urban areas. In the 20 most segregated cities, at least 32.8% of low-income families would need to be relocated to achieve a homogeneous spatial distribution. We consider that this finding could have important implication for public policies in the large Brazilian cities.Urban land use is limited by availability, affected by public housing policies, and subject to housing market pressures that may lead to gentrification and displacement . HomicidThis study has essential strengths related to the data source and the analytic approach. However, the used cross-section approach makes us cautious about making causal claims from reported findings of a possible effect of socioeconomic segregation on homicides. However, our results add to the well established causal relationship between inequalities and homicide. Segregation (measured by SSI) showed to be correlated with inequalities (measured by the Gini Index) in the studied Brazilian cities. But, while inequalities express the income-related social distances between a population, the segregation expresses the physical distance and the level of connection between social groups in the constrained urban space.In a large and diverse country, such Brazil, the lack of planning and governance in large cities and urban areas has led the country to rates of lethal violence that are historically among the highest in the world , p. 116.In Brazil, social class in part determines the neighborhood of residence and the eventual opportunities for leisure and employment. The exclusion of peripheral populations is based on labor relations, poverty, and the generation of inequalities , 2005. SSegregation contributes to the degradation of spaces and the lack of physical, economic, and social infrastructure. These elements intensify the discrimination suffered by people living in needy areas, with the potential to generating interpersonal violence. For Cufré (2019), segregation itself is a form of symbolic violence, the effect of discrimination and inequality. Furthermore, the urban space is the result of social practices that are crucial for achieving social welfare. The lack of infrastructure in deprived neighborhoods can fuel violence. That is why it is so important that public authorities have medium and long-term plans to reduce segregation and inequalities among neighborhoods.The social fragmentation caused by segregation and, consequently, the formation of new urban spaces around large cities creates “symbolic limits” for a given population, in which, on the one hand, the symbolic enclosure can be protective and on the other hand, given the power imbalance the poor can feel trapped. However, according to Alonso and Hita (2013), space alone does not generate violence. Specific social conditions, such as political, cultural, and economic issues are essential to foster marginalization, aggression, brutality, and even violent deaths.In addition to these issues, problems related to violence and homicides need to be seen in the context of public health. Factors that promote violent deaths directly impact the population's health, health services demand and costs, institutional issues, social losses, physical and psychological trauma to individuals, etc. Violence is multifactorial and will only be resolved through the development of coordinated actions by government sectors and society to prevent its harmful effects. Therefore, based on the results presented here, we reinforce that policies that foster inclusion and desegregation may be promising to reduce the high rates of homicides in Brazilian cities.We declare no competing interests.Maria Izabel dos Santos: Conceptualization, Methodology, Software, Data curation, Formal analysis, Writing – original draft, preparation, Visualization, and, Validation. Gervásio Ferreira dos Santos: Conceptualization, Formal analysis, and, Supervision. Anderson Freitas: Software, Visualization, Writing – review & editing. J. Firmino de Sousa Filho: Software, Formal analysis, Visualization, Writing – review & editing. Caio Castro: Writing – review & editing. Aureliano S. Souza Paiva: Software, Writing – review & editing. Amélia A. de Lima Friche: Writing – review & editing. Sharrelle Barber: Writing – review & editing. Waleska Teixeira Caiaffa: Writing – review & editing. Maurício L. Barreto: Conceptualization, Writing – review & editing, and, Supervision.


Manihot esculenta ssp. esculenta) is one of the world’s major food crops and has the potential to help achieve food security in the context of on-going climate changes. We evaluated single nucleotide polymorphisms in traditional Brazilian manioc varieties conserved in the gene bank of the Luiz de Queiroz College of Agriculture, University of São Paulo. We assessed genome-wide diversity and identified selective signatures contrasting varieties from different biomes with samples of manioc’s wild ancestor M. esculenta ssp. flabellifolia. We identified signatures of selection putatively associated with resistance genes, plant development and response to abiotic stresses that might have been important for the crop’s domestication and diversification resulting from cultivation in different environments. Additionally, high neutral genetic diversity within groups of varieties from different biomes and low genetic divergence among biomes reflect the complexity of manioc’s evolutionary dynamics under traditional cultivation. Our results exemplify how smallholder practices contribute to conserve manioc’s genetic resources, maintaining variation of potential adaptive significance and high levels of neutral genetic diversity.Knowledge about genetic diversity is essential to promote effective use and conservation of crops, because it enables farmers to adapt their crops to specific needs and is the raw material for breeding. Manioc ( It is, however, an enormous challenge due to the accelerated increase in the world’s human population and on-going global climate changes3. Better strategies to conserve and use crop diversity are effective ways to address this issue, and, although often regarded as descriptive, the study of genetic diversity is fundamental to this end5.Food security—the regular access to enough high-quality food with sufficient protein and energy—is one of the major goals of the United Nations’ 2030 Agenda for Sustainable Development to promote a fairer world6. The maintenance of agrobiodiversity provides humans with a wealth of intraspecific crop diversity selected in different cultural and geographical contexts8. This agrobiodiversity is associated with valuable traditional knowledge and practice systems, which play a key role to conserve biological and cultural diversity9. Additionally, the management of landraces with high genetic diversity by farming communities has collaborated to keep reasonable levels of food production in many areas of the developing world8. However, factors such as globalization, degradation of natural landscapes, changes in agricultural production systems, and landrace displacement by modern cultivars threaten the conservation of plant genetic resources8.Genetic diversity is used by farmers to adapt their crops to current and future climate changes and is also the raw material of formal breedingManihot esculenta Crantz) is currently one of the major food crops, ranking eighth in estimated global production10, and its roots are the main source of energy for more than 800 million people11. Manioc is also widely known as cassava, but here we use the former term because it derives from a Tupi word that means cultivated plant, while the latter derives from an Arawak word that means bread12. The crop has an immense diversity of varieties which are cultivated around the Tropics, mainly by low-income smallholder farmers14, and it is considered one of the most promising crops to promote food security in developing countries14. This is because manioc is well-adapted to marginal areas with poor soils and can be produced efficiently even on small scales, with low inputs and without mechanization14.Manioc 16, in what is now the Brazilian state of Rondônia and adjacent regions. Populations of ssp. flabellifolia currently occur in the Amazonia-Cerrado ecotones of southern Amazonia, as well as on the Guiana shield15. The wild progenitor grows as highly branched shrubs in open vegetation or as climbing vines amid denser vegetation, while cultivated manioc grows as little-branched shrubs21. After its initial domestication, manioc was probably available in most parts of the Neotropics by 6500 ybp23. Manioc started to be globally spread after the European conquest of South America in the sixteenth century, which introduced the crop in Africa, tropical Asia and Oceania13.Morphological and genetic evidence support the hypothesis that manioc was domesticated from 24. Sweet manioc can be safely consumed after simple processing , while bitter manioc needs more elaborate detoxification 25. Although sweet and bitter manioc cannot be separated by morphological traits, they are genetically divergent and farmers’ traditional knowledge categorize them clearly13.Cultivated manioc has two major groups of landraces that differ in their contents of cyanogenic compounds . Sweet manioc has lower cyanogenic potential (< 100 ppm fresh weight) than bitter manioc (> 100 ppm fresh weight), but the variation in the content of cyanogenic compounds is continuous across these two groups11. Manioc is allogamous, and crossings may occur between plants from different varieties producing fruits that disperse sexual seeds in the swiddens13. The seeds have elaiosomes that attract ants, which further disperse and bury them26. The sexual seeds in the soil seed banks may sprout when the swidden is cleared, or the vegetation of an abandoned field is burnt to start a new cycle of cultivation27. Farmers may consciously or inadvertently let sexual seedlings grow in the swiddens until harvesting time, when they may decide to use stem-cuttings of sexual plants for clonal propagation29. Farmers may either incorporate these stem-cuttings into an existing variety or start a new variety, increasing the crop’s genetic diversity30. This management of high genetic diversity extends beyond family units into extensive exchange networks of cultivated varieties32. These networks vary according to the cultural context, but are a common feature of traditional cultivation in Amazonia and throughout the world36. By exchanging varieties that were selected and managed in the same or different regions, traditional farmers maintain high levels of genetic diversity in the crop at both local and wider geographical scales37.Manioc is a clonal crop, but its evolutionary dynamics is much more complex than the establishment of varieties consisting of unique clones. Under traditional cultivation, farmers propagate manioc varieties by stem-cuttings, but the plants can produce flowers13. In the Neotropics, bitter landraces predominate where manioc is the major staple crop cultivated in swiddens far from household units, while sweet landraces predominate where manioc is part of multi-crop systems and is often cultivated in backyards13. These same patterns may be observed in most parts of Africa, but are much more variable in Asia and Oceania38. Farmer’s interest in experimenting with sexual seedlings also seems to vary greatly across locations outside the Neotropics13. Variable degrees of cultural appropriation may also influence the farmers’ ability to properly detoxify bitter manioc before safe consumption, which contributes to epidemics of Konzo, a chronic paralytic disease, in some African regions13. These differences in the crop’s management influence how manioc evolves under distinct geographical and cultural contexts and have a significant impact in the crop’s potential to contribute to food security39.The evolutionary dynamics outlined above is typical of manioc cultivation in Amazonia, but the crop’s dispersals around the world were not always accompanied by cultural appropriation, i.e., not all the original aspects of its cultivation can be observed outside Amazonia40 and to support breeding43. More recently, approaches assessing genome-wide diversity of domesticated varieties and wild relatives46 advanced rapidly after the release of a genome for manioc47. Indeed, the characterization of genome-wide diversity collaborated tremendously for the valorization and utilization of wild species and cultivated varieties conserved in gene banks throughout the world50. Given the agronomic importance of manioc, these studies were mostly developed to support breeding. However, the genomic approaches also offer opportunities to further investigate evolutionary aspects related to the crop’s domestication and diversification52.Genetic studies have greatly contributed to our understanding about the evolution of the cropIn this context, we assessed selective signatures and the genome-wide diversity of manioc varieties from different Brazilian biomes Fig. , based oNsiI-MspI) and 240,176,492 (PstI-MseI) raw reads. After demultiplexing and quality filtering, 153,858,282 reads for NsiI-MspI  and 118,476,082 reads for PstI-MseI  were used for SNP identification. The NsiI-MspI library resulted in 4790 SNPs  while the PstI-MseI library resulted in 10,121 SNPs . After merging these data sets and pruning markers with high LD we obtained a final set of 11,782 high-quality SNPs  , of which 698 SNPs were identified by at least two different methods , of which 169 SNPs were identified by at least two different methods , while the bitter varieties had a slight deficit of heterozygotes , although its small positive inbreeding coefficient (f = 0.047) was not significant. The varieties from different biomes had similar levels of genetic diversity (Table f = 0.062), but it had the greatest number of private alleles (PA = 153).The analyses below were performed considering the 10,917 putatively neutral SNPs that were not identified as outliers by more than one test of selection. We report the results based on all the 92 samples evaluated, but similar results were observed when considering only the varieties conserved in the gene bank , followed by the divergence between the groups of biomes when compared to wild manioc . The divergence among different biomes was small, yet significant . Pair-wise estimates of FST between cultivated and wild manioc were high (Table FST = 0.357) than the sweet varieties (FST = 0.344), and the divergence between bitter and sweet varieties was much lower (FST = 0.045), yet significant. All the biomes were highly divergent from wild manioc, with FST ranging from 0.34 (Amazonia) to 0.43 . The divergence between biomes ranged from non-existent  to moderate (Amazonia vs. Cerrado = 0.065). Amazonia had the greater and significant estimates of divergence in relation to the other biomes, although FST was low to moderate  that is found in cultivation areas throughout the world and is one of the most serious diseases affecting the crop62. We also identified outlier SNPs (Nsi_172 and Pst_4209) in genes similar to proteins involved in resistance to powdery mildew fungus, which in manioc is known as ash disease and is caused by Oidium manihotis Henn62. Although ash disease is widespread, it is not considered of great importance due to its superficial lesions62. Agronomic trials would be important to confirm if some of the varieties conserved in the gene bank may be sources of resistance alleles for these diseases. Pest and disease resistance may be the principal weakness of manioc to adapt to climate change63.The reduction of genetic diversity associated with domestication bottlenecks, or resulting from multiple founding effects during crops’ dispersals64 including signaling and plant defense responses66. Other outlier SNPs were in genes related to general cellular processes, such as ubiquitination  and transcriptional regulation . These processes are central in the expression and regulation of several other genes, and therefore are likely to be involved in adaptations, including domestication traits68.Most of the putative manioc resistance genes had other functions probably due to their catalytic kinase domains, which play many key roles in eukaryotesNsi_2393, Nsi_3361, Pst_4290, Pst_8996 and Pst_9959), organ size (Nsi_3361) and shape (Pst_1010), and in starch metabolism (Pst_5701). These SNPs may be of agronomic importance because the current major objectives of breeding for food and industrial uses include increasing the root/stem ratio, improving starch quality, and increasing starch content in roots70. We also found outlier SNPs in genes putatively involved in the development of shoots (Nsi_3361 and Nsi_3540) and branching (Pst_6259). Domestication often resulted in changes in shoot architecture that facilitate plant growth and harvesting72. Contrasting with the highly branched habit of ssp. flabellifolia21, farmers prefer sparsely branched manioc plants because they may provide thicker stem cuttings73. Some outlier SNPs were in genes putatively involved in flower development , fertilization (Nsi_172 and Pst_4209), and gametogenesis (Nsi_3361). These selective signatures may result from the relaxation of selective pressures on sexual fertility caused by domestication for vegetative propagation74. Flowering is variable in manioc and about 60% of the pollen produced may remain viable, although manioc cultivars commonly have male sterility and low seed/flower ratios11. We also identified outlier SNPs putatively involved in cotyledon development (Nsi_2289 and Nsi_4509); this was in a manioc gene similar to Arabidopsis thaliana STY46, a protein kinase involved in chloroplast biogenesis and differentiation in cotyledons75. The seedlings of domesticated and wild manioc have contrasting functional differences76. The cotyledons are hypogeal in the seedlings of ssp. flabellifolia, providing additional opportunities for plant regrowth after damage. In domesticated manioc, cotyledons are epigeal, foliaceus, and photosynthetically active, collaborating with rapid plant growth76.Outlier SNPs in genes putatively involved with development may be genetic signatures of manioc domestication and selection for different traits of interest in response to distinct human preferences. Manioc was domesticated for its starchy roots, and we identified SNPs in genes putatively involved in root formation  possibly involved in cell proliferation and elongation. Genes controlling cell division are frequently associated with domestication and diversification processes because they often resulted in increased organ sizes79. The roots of cultivated manioc have greater amounts and larger starch granules, but not larger cell sizes, than the wild relatives80. However, the cessation of cell division and expansion may play an important role during manioc response to drought stress82. Another outlier SNP (Pst_7007) was in a gene that may act in responses to salt, drought, and cold stresses. Responses to abiotic stresses were important crop adaptations for the ecological shifts from the wild to the cultivation environment and when they started to be dispersed71. In the specific case of manioc, abiotic resistance is relevant to crop adaptability to marginal areas and might be key for manioc adaption to harsher future climates63.Growth resilience under distinct environments was essential for the spread and adaptation of crops to regions outside their domestication centers84. Although the groups of manioc varieties are not true populations, some aspects, such as the possibility of crossings and incorporation of sexual plants into clonally propagated varieties, make these groups biologically meaningful. Moreover, genetic approaches provided interesting results even when using generic groups of manioc varieties86 and limited sample sizes in other study systems88. The selective signatures discussed above should be regarded as initial hypotheses and further genome-wide association studies and quantitative trait loci mapping are required to confirm their biological significance89. Nonetheless, this new information may guide future bottom-up approaches to characterize the genomic changes and their associated phenotypic effects90 relevant to manioc evolution under domestication and to assist breeding strategies, contributing to our understanding about adaptive genes in crops.We recognize that the type of genomic library and the limited sampling number of some groups of varieties may have introduced bias in the analysesHE ranges from 0.285 to 0.312) was similar to that observed in previous studies and suggests that the gene bank conserves high levels of genetic diversity, despite its limited size. Within Embrapa Brazilian manioc germplasm bank, Albuquerque et al.49 reported an overall HE = 0.29  and Ogbonna et al.91 found HO ranging from 0.26 to 0.39 across genetic groups. Similar results were observed for the gene banks of the International Institute of Tropical Agriculture  and the International Center for Tropical Agriculture 43. This high genetic diversity is explained by the complex evolutionary dynamics of the crop under traditional cultivation, that results in varieties consisting of a predominant clone plus individuals morphologically similar, but genetically distinct28. Although smallholder farmers propagate manioc exclusively by stem cuttings, crossings between different varieties may occur producing sexual seeds that become part of the soil seed bank and may sprout amid clonally propagated plants92. After harvesting, the farmers may incorporate stem cuttings of these sexual plants into their clonal stocks leading to the amplification and maintenance of genetic diversity in the local scale30. The high genetic diversity observed in the different biomes may be explained by the widespread occurrence of the incorporation of sexual plants to clonal varieties, as well as by the selection for distinct human preferences under diverse ecological and cultural contexts93. Genetic evidence for different human preferences in distinct ecogeographic contexts has already been reported in different regions of South America for manioc94 and other crops96.The genetic diversity of varieties from different biomes (FST ranging from − 0.025 to 0.065) and the high admixture observed in clustering analyses . We used these samples as references for the crop’s closest wild relative, and for the major groups of cultivated manioc, respectively. The collections of these samples were registered in the Brazilian National Council for Genetic Patrimony CGEN (numbers A7994B4 and AEA71DE), according to Brazilian Law 13123 (20 May 2015). These registers also characterize our study as basic scientific research, enabling the experiments that we performed. The plant materials and methods employed in the present study are in compliance with local and national regulations. Because the manioc varieties are conserved in vivo in the gene bank, they were not deposited in herbarium, however DNA vouchers are stored in our laboratory. In addition, because all manioc varieties have been cultivated for a long time in local communities of smallholder farmers, no formal taxonomic identification was performed at the time of sampling to establish the gene bank.We sampled apical leaves of the 78 manioc varieties (1 plant/accession) from the gene bank at the Luiz de Queiroz College of Agriculture, University of São Paulo, Piracicaba, São Paulo, Brazil . These varieties were originally collected in smallholder farmer communities in six Brazilian states, located in four different biomes: Amazonia (16), Cerrado (30), Atlantic Forest (27) and Pantanal (5) Fig. . Of thes106 and inspected DNA quality with electrophoresis in agarose 1% (w/v) gels stained with ethidium bromide. We estimated DNA concentrations with dsDNA BR Assay quantification kit for Qubit3 fluorometer (Invitrogen), and normalized DNA concentrations to 25 ng∙μL-1.The leaves were dehydrated with silica gel in paper bags and stored at -20 °C. We obtained total genomic DNA from 50 mg of leaf samples following the protocol described by Doyle and Doyle107. Briefly, 175 ng of genomic DNA were digested with PstI and MseI for one library, and NsiI and MspI for the other . The restriction fragments were ligated to adaptors complimentary to each of the restriction sites (including 96-plex PstI or NsiI adaptor sets with unique 4–9 bp barcode sequences). Ligation products of each sample were pooled and enriched for fragments containing different adapters in both ends through PCR. The concentrations of the ddGBS libraries were estimated using the NEBNext Library Quant kit for Illumina (New England Biosciences) through real-time PCR, and the libraries’ profiles were inspected using the DNA 12000 Analysis kit for Bioanalyzer 2100 (Agilent). Each ddGBS library was sequenced twice in the NextSeq550 (Illumina) platform .We prepared two double-digest genotyping-by-sequencing (ddGBS) libraries as described by Poland et al.108, and due to a large amount of 3’-end adaptors we trimmed the reads to 100 and 80 bp for PstI-MseI and NsiI-MspI libraries, respectively. We performed read trimming and demultiplex according to specific barcodes using the module process_radtags of Stacks 1.42109. We aligned the demultiplexed reads against the manioc genome Manihot esculenta v6 (NCBI PRJNA234389)47 using Bowtie 2.2.1110 with the “end‐to‐end” and “sensitive” configurations. We identified SNPs separately for each library using SAMtools 0.1.19112 and VCFtools 0.1.17113, retaining only biallelic markers and only one SNP per read to avoid explicit linkage. Candidate SNPs had sequence depth ≥ 5X, minor allele frequency ≥ 0.05, mapping quality ≥ 13 and were present in at least 90% of the samples. The SNPs identified in each library were merged using MergeVcfs from Picard (http://broadinstitute.github.io/picard). Then, we used VCFtools 0.1.17113 and SAMtools 0.1.19111 to filter out SNPs within 100 bp and within windows of 1000 SNP sites with linkage disequilibrium (LD) r2 ≥ 0.8, and to retain the SNPs observed in Manihot esculenta v6 chromosomes.We inspected the quality of raw reads using FastQCpcadapt, FST, FLK, hapFLK, and XP-EHH) with distinct underlying models to detect putative selective signatures (outlier SNPs). These analyses were performed considering two scenarios: i) the groups of wild versus cultivated manioc , and ii) the groups of varieties per biomes . With this design we aimed to identify loci with putative selective signatures related to either the domestication of manioc or the diversification of the crop in different cultivation environments.We used five different methods  based on the calculation of Reynold’s120 distances from our data.Pcadapt is based on a principal component analysis (PCA) without assuming any explicit genetic modelhapFLK and XP-EHH) considering “long-range haplotypes” that account for variation in recombination rates by comparing haplotypes to other alleles in adjacent loci121. HapFLK was built upon FLK for the detection of positive selection, including incomplete sweeps, from multiple populations and is robust in the presence of bottlenecks and migration116. Complimentarily, the cross-population extended haplotype homozygosity (XP-EHH) detects loci that have swept to near fixation (hard sweeps) within a specific population121. The hard sweeps detected based on XP-EHH estimates assume one ancestral and one derived population. While this makes sense in the case of the groups of wild and cultivated manioc, it might not be straightforward when contrasting different biomes. Even if we considered manioc varieties from Amazonia as ancestral to the varieties from the other biomes, we would follow a different criterion (pairwise comparisons among biomes) in relation to the other tests performed for the identification of selective signatures that considered the overall genetic divergence between biomes. For that reason, this analysis was performed only considering the groups of cultivated and wild manioc. For these two analyses, we used fastPHASE 1.4122 to estimate missing data and reconstruct haplotypes. We used a perl script (https://github.com/lstevison/vcf-conversion-tools) to convert VCF files to fastPHASE input format and then performed 20 runs of the expectation–maximization (EM) algorithm with default configurations. We estimated hapFLK simultaneously with FLK considering the same Reynold’s distance matrix and using 15 EM runs. We estimated XP-EHH using the functions scan_hh, ies2xpehh and calc_candidate_regions in rehh 2.0123 for R115. We set the functions to use unpolarized data, and to consider the XP-EHH estimates in the direction of wild to cultivated manioc .The three methods above are based on individual markers, and we also applied two tests , and the loci at the top 5% of the FLK, hapFLK and XP-EHH estimates. Then, we considered as loci putatively under selection those SNPs that were detected in at least two of the five (four) methods used for the groups of wild versus cultivated manioc (groups of varieties per biome).We considered as outlier SNPs the loci with 124. We recovered the Gene Ontology (GO) annotations, which summarize the information about biological processes, molecular functions, and cellular components125 of the gene sequences with outlier SNPs extracted from Manihot esculenta v6 with BEDTools 2.30.0126. Genes with outlier SNPs were tested for enrichment of gene function descriptions using topGO 2.44.0127 for R115 based on default configurations and a threshold of p < 0.01 for Fisher’s exact tests. We compared the amino acid sequences of the predicted manioc genes with i) the predicted protein sequences of 2609 manioc R-genes from the Plant Resistance Gene database (PRGdb 3.0)128; and ii) the Swiss-Prot database from UniProt (www.uniprot.org) using blastp from blast 2.7.1129. Then, we further assessed putative functional annotations described in UniProt for the blastp hits with the arbitrary threshold of identity ≥ 90% (PRGdb) or ≥ 60% (Swiss-Prot).We evaluated the predicted effects of outlier SNPs using SnpEffA), percentage of polymorphic loci (%P), number of private alleles (PA), observed (HO) and expected (HE) heterozygosities] and the inbreeding coefficients (f) using diveRsity118 and PopGenKit130 for R115. HO, HE, and f confidence intervals were obtained with 1000 bootstraps.We performed the analyses of genetic diversity and structure considering only the putatively neutral SNPs (those that were not detected as outliers by at least two of the tests described above). We estimated the genetic diversity [total number of alleles (ST) among groups, and obtained their associated significance based on 20,000 permutations using Arlequin 3.5131. We investigated the patterns of genetic structure using sparse non-negative matrix factorization (sNMF)132 and discriminant analysis of principal components (DAPC)133. sNMF assumes that the genetic data originate from the admixture of K unknown parental populations and estimates ancestry coefficients from multilocus genotypes132. This analysis is similar to other model-based approaches, such as Structure134, with the advantage of being robust to departures from traditional population genetic model assumptions132. We tested from 1 to 10 K ancestral populations with 200,000 iterations, ten repetitions for each K value, and used the cross-entropy criterion to visualize the results of the simulations. We performed this analysis using LEA135 for R115. Complimentarily, DAPC summarizes information from large datasets (like genotypes from thousands of SNPs) to assign individuals to clusters without a pre-defined genetic model133. DAPC is useful for the assessment of genetic structure based on SNP datasets because it maximizes the variation among groups while minimizing the correlations between the original variables (such as LD)133. We performed DAPCs in adegenet136 for R115 based on the groups of wild and cultivated manioc from different biomes, and only for the groups of varieties per biomes (without wild samples). We opted to use these groups in DAPC because sNMF was performed without any a priori classification and suggested no clear number of ancestral populations  that reduced over-fitting of DAPCs membership coefficients136. After this procedure we retained nine PCs in the analysis considering the four biomes plus wild manioc, and 11 PCs in the DAPC considering only the four biomes.We evaluated the genetic variation within and among groups of varieties with analyses of molecular variance (AMOVA), estimated pairwise genetic divergence (Fons see “”. We useSupplementary Information 1.Supplementary Information 2.


To test this hypothesis, populations of simulated embodied biorobots and their developmental systems were evolved under steady directional selection as equivalent rates of random mutation and random transcriptional error were covaried systematically in an 11 × 11 fully factorial experimental design. In each of the 121 different experimental conditions (unique combinations of mutation and transcription error), the same set of 10 randomly created replicate populations of 60 individuals were evolved. Selection for the improved locomotor behavior of individuals led to increased mean fitness of populations over 100 generations at nearly all levels and combinations of mutation and transcription error. When the effects of both types of error were partitioned statistically, increasing transcription error was shown to increase the final genetic variance of populations, incurring a fitness cost but acting on variance independently and differently from genetic mutation. Thus, random epigenetic errors in development feed back through selection of individuals with masquerading genomes to the population’s genetic variance over generational time. Random developmental processes offer an additional mechanism for exploration by increasing genetic variation in the face of steady, directional selection.Given that selection removes genetic variance from evolving populations, thereby reducing exploration opportunities, it is important to find mechanisms that create genetic variation without the disruption of adapted genes and genomes caused by random mutation. Just such an alternative is offered by random epigenetic error, a developmental process that acts on materials and parts expressed by the genome. In this system of embodied computational evolution, simulated within a physics engine, epigenetic error was instantiated in an explicit genotype-to-phenotype map as transcription error at the initiation of gene expression. The hypothesis was that transcription error would create genetic variance by shielding genes from the direct impact of selection, creating, in the process,  Understanding the evolutionary dynamics of embodiedmasquerading genome hypothesis (MGH): The presence of noise in the gene transcription process of the G-P map can shield genes from the direct impact of selection, thus increasing genetic variance in populations over generational time. Moreover, the MGH is distinct from genetic mutation, acting independently and differently on variance. There is, however, a fitness cost that accompanies the increased variance resulting from masquerading genomes. These results typify embodied computational evolution (ECE), the employment and study of evolutionary methods using embodied robots, virtual or material—an approach distinct from other evolutionary computation approaches, for which embodiment is not integral. These ECE results provide novel insight into living systems using computational methods; these results may also be of interest to evolutionary robotics, for which increased variance may help avoid convergence on local optima . The reAs the “cryptic” in its name denotes, CGV increases genetic variation by “hiding” genes from selection; in the simplest case, if genes aren’t expressed—a process that begins with the transcription of DNA into messenger RNA—then they cannot be selected. Thus CGV aids diversification in the long run by decoupling a subset of the connections in the G-P map. For the connections that remain, their mappings can be altered by epigenetic processes. When noise is introduced into the G-P map for the neurocontrollers of simulated quadrupedal robots, the resulting stochastic ontogenesis (SO), a developmental process, can have surprising and positive evolutionary consequences . As is tThus we hypothesize that the epigenetic SO mechanism increases genetic variation in populations under selection, hiding some genes from selection in a manner that is functionally similar to CGV. To test this hypothesis, we evolve populations of simulated embodied robots under directional selection, covarying levels of genetic noise created by random mutation with levels of epigenetic noise created by random transcriptional error. We then select for improved locomotor behavior while tracking both genetic and phenotypic variation in the populations.We chose to manipulate the bioinspired mechanism of transcription because it is the first and arguably the most important stage of gene expression and development. In the context of evolutionary robotics, transcription has been used as an explicit factor in body-brain evolution  and trana priori knowledge about the desired result to those that only reward agents for how well they completed a task, independently of how they achieved a given level of performance  are operating, these nondeterministic processes can change the ωi and create a MG.By altering the G-P map, SO creates what one can think of as masquerading genomes (MG). In our model, the developmental mechanism of SO is transcription error, which creates MG by hiding the deterministic fitness of the genome. Sharing motivation with Stanton , though ωi is measured as the Euclidean distance that the robot locomotes from start to stop. Selection was directional and constant; populations that undergo adaptive evolution have higher mean fitness, a result of their collective improvement in locomotion.With evolutionary experiments that systematically covary τ and μ, our model shows that by adding a nondeterministic SO component to the deterministic process of the G-P mapping, transcription errors create MGs. MGs, in turn, increase both genetic and phenotypic variance of the population. The evolutionary experiments were conducted with an 11 × 11 factorial design, with the independent variables τ (11 levels) and μ (11 levels), producing 121 different conditions. Each condition has ten replicates: ten different populations of 60 robots evolved over 100 generations. In every population and every generation, each individual robot is tested in a dry terrestrial world, a simple flat plane in which 6 individuals. For each individual, we tracked 11 properties: identification, parentage, generation, fitness, genetic variance (two types), and number of body parts: joints, neurons, sensors, and wires. This yielded an enormous database of nearly 8 × 107 points. With a data set of this size, the opportunities for analysis are manifold. In this initial work, we develop the ECE model and present a high-level examination of MGs, specifically the influence of μ and τ on genetic variance, H, of the population. Unlike the additive genetic variance that must be inferred in biological populations, we can measure genetic variance directly using the Hamming distance between every pair of individual genomes in a given population. The sum of all pairwise Hamming distances, H, serves as our measure of the genetic variance of the population.These experiments produced 7.26 × 10This ECE modeling system consists of three bioinspired models that work in concert: 1) a genetic system that encodes morphological and regulatory traits as triplet codons, mutates the genomes, and replicates the genome for reproduction; 2) a developmental system that expresses over time the genome as sets of transcripts, creates random errors in the transcripts, processes those transcripts to create finished parts, and then uses a fixed set of rules to assemble the parts into individual robots; and 3) an evolutionary system that tests the behavioral performance of the individuals in a population with a physics simulator and selects the best for reproduction.The robotic genome was designed to mimic certain properties of biological genomes. The biological genome uses the codon, a triplet of quaternary digits defined in the biological case by the classic A, T, G, C nucleotide bases. Each codon is expressed as an RNA transcript; each transcript maps to a particular building block (amino acid) from which an organism is constructed during development. Because there are only 21 amino acids but 64 possible quaternary triplets, redundancy in coding occurs when mapping from codons to components. We used a similar structure, substituting digits from 0 to 3 for the nucleotides .start and stop codons are not expressed; they delimit the beginning and end of a gene. Only codons inside of the start-stop boundaries are expressed. The genome is mutated only during reproduction, which follows selection and occurs before the development of the next generation of robots (see Evolutionary Experiments section). For each digit in the genome, the mutation operator uses a random number generator and, based on the mutation rate for that population, alters the digit.In generation 0, each genome was initialized as a random string of 6,000 codons . Codons fall into four categories : part, fIn each gene there may be one or more part codons. Only the first part codon after the start codon was expressed. In contrast, all feature and magnitude codons in the gene were expressed, and they formed a pool of regulatory elements. The interaction of the pool of expressed regulatory elements with the expressed part type determined the final size and configuration of the part.In development, the genotype-to-phenotype (G-P) mapping began with the expression of each gene as a set of transcripts based on the triplet codons. These transcripts specified the protoparts and regulatory elements to be used in building the robot . At thisAs in biological systems, the set of transcripts, the transcriptome, is used by the developmental process to build the agent over time, where time is represented by update cycles. The G-P mapping unfolds in time by taking each gene’s protopart and growing it into the finished part, with the duration of the growth and functional properties of the part determined by the transcribed regulatory elements . Every tsphere: size+ and sphere: size-  it ihttps://bulletphysics.org; v2.82) were used to simulate the robots and the environment. Simulations were run on a system76 Gazelle Professional computer with an Intel® Core™ i7-4710MQ CPUs @ 2.50 GHz. The work of the model was split between two applications: a Python (v2.7.6) program handled development, selection, and reproduction; and a C++ program (compiled with g++ v4.8.4 using gnu++11) simulated robots in the physics engine environment. The random number generators used were RandomState instances from Numpy (v1.8.2).Bullet Physics libraries  of 100 generations produced 7.26 × 10 spheres . The mos spheres . Compari, the mean fitnesses To test the hypothesis that the rate and pattern of adaptive evolution could be altered by the two independent variables, mutation rate μ and epigenetic error rate τThe analysis did not detect a statistically significant interaction term for μ and τ on the B, C, and D coefficients of ; the intent ways . Most imleration . The seccts of μ .To test for the presence of epistasis—the non-additive interactions of genes—third-order polynomial regression was performed on fitness and the number of genes, grouped by μ and then τ . No mattp < 0.05), with the effects size test ηpartial for τ nearly twice that of μ (0.295 v. 0.136). The interaction effect was not significant. To illustrate the nature of the independent effects, the estimated marginal means were regressed against the error rates; as error rates of μ and τ increase, To investigate the evolutionary outcomes in more detail, the final generation, 99, was examined. For statistical analysis, the conditions with 0 μ and τ were removed because they were outliers by more than 3 SE relative to the nearest values from other conditions; their removal does not alter the qualitative results that follow. To further assess the effects of μ and τ on ecreases . Note thH, a 10 × 10 fully factorial ANOVA was performed on the final genetic variance, H99. Both μ and τ were significant main effects (p < 0.05), with the effects size test ηpartial for μ an order of magnitude greater than for τ (0.223 v. 0.021); the interaction effect was not significant. To illustrate the nature of the independent effects, the estimated marginal means were regressed against the error levels. Results show that as error levels of μ and τ increase, H99 increases , with the effects size test ηpartial for μ three times that for τ (0.176 v. 0.054). The interaction effect was significant as well with an ηpartial of 0.133. To show the independent effects, the estimated marginal means were regressed against the error levels; as error levels of μ and τ increase, SDω increases , is consistently high across the range of τ for the three lowest μ; the smallest costs across levels of τ are the populations with the highest μ  system develops individuals and evolves populations of embodied and behaviorally autonomous robots using bioinspired features and mechanisms. Each individual possesses a genome of 18,000 quaternary bases encoding information in triplet codons . DevelopIn building this system, we were guided by a foundational question in evolutionary disciplines from evolutionary biology to evolutionary robotics: How has biological evolution created an enormous variety of lifeforms? Workers in evolutionary robotics have shown that the action and interaction of selection and mutation are insufficient 1) to avoid premature convergence on adaptive peaks and 2) to expand the diversity of behaviors and morphologies . EvolutTo test this hypothesis we evolved populations of embodied robots under directional selection, covarying levels of genetic noise created by random mutation, μ, and levels of epigenetic noise created by random transcriptional error, τ. The μ and τ were of the same range and magnitude, which facilitated meaningful comparisons between the two different types of random error-making processes. We selected for improved locomotor behavior while tracking mean fitness, phenotypic variation, and genetic variation in the populations. We ran 121 different pairwise combinations of μ and τ in 10 different starting populations of 60 individuals over 100 generations. The results were clear: random errors in transcription increase genetic variation .As verified by the experimental results , transcrWhile it is tempting to think of this cryptic genetic variation as solely neutral in the classical sense of a point mutation in a redundant position in a codon, the effect of cryptic genetic change—deleterious, neutral, or beneficial—depends on how that genotype is mapped through development. In the case presented here, if the nondeterministic effects of transcriptional errors are present, then the phenotypic effect of the genetic change—whatever its valence—is randomized with respect to the individual’s fitness . With hiAs predicted by the mutational robustness hypothesis, MGs in this ECE system and their cryptic genetic variation incur a cost: as the magnitude of τ increases, the mean fitness, ecreases , 9. Thisecreases  and 2) pecreases . Increasecreases . Like trecreases  and phenecreases  varianceecreases . Indeed,ecreases ; recall ot for μ . We did Even with these costs, populations under steady selection retain the ability to explore, avoid final convergence, and find new solutions. First, the parallel adaptation of 121 types of population, differentiated by the magnitude of τ and μ, shows a variety of evolutionary trajectories that probe the search space in different ways . Second,We note that random transcription error is but one possible type of developmental epigenetic error. Stanton  added GaThe importance of epigenetic errors in adaptive exploration signals the general importance of modeling an explicit relationship between the genotype and the phenotype as mediated by development and its feedback effects on evolution. This relationship unfolds over developmental time as the G-P mapping process. By including genetically encoded regulatory elements . In organisms, population size often fluctuates wildly, with small numbers creating bottlenecks that dramatically reduce genetic variance and effective population size, key parameters in extinctions , a total of 100 generations were run. It is important to recognize that 100 generations is an arbitrary window. At the same time, natural populations of locomoting vertebrates show rapid and significant adaptive changes in a few to tens of generations (erations .Related to the issue of the number of generations (see previous paragraph) is the lack of equilibrium or convergence of any of the populations over generational time . While iEpistasis and the evolution of genes. Epistasis, the interaction between genes, is a ubiquitous phenomenon in living systems, but one that makes it daunting to understand the role of individual genes . These coded epistatic effects were held constant in our experiments manipulating τ and μ. We therefore had anticipated that they would be a constant factor in the evolutionary system. Indeed, as measured by the relation of the number of genes to fitness, epistatic effects are similar across the experimental treatments  a genetic system that encodes morphological and regulatory traits; 2) a developmental system that expresses over time the mapping between genotype and phenotype, allowing for epigenetic errors in the process; and 3) an evolutionary system that tests the behavioral performance of the individuals in a population and selects the best for reproduction. The explicit dynamics of this system take place on all three temporal scales of evolution : behavioEvolutionary and developmental mechanisms balance and adjust the adaptive and exploratory behavior of populations. Mutation, the sole genetic operator modeled here, and transcription error, the sole epigenetic operator, are independent and complementary mechanisms—they adjust the rates of adaptation, as measured by the change in mean fitness of the population, with lower levels of both errors associated with higher initial rates of adaptation . When coArmed with epigenetic transcription errors, the evolving populations not only counteract the tendency of directional selection to remove genetic variance, but they can also increase that genetic variance. Systematic exploration of those epigenetic errors demonstrates a new mechanism to be used in conjunction with selection and mutation for the exploration of the adaptive landscape.