Understanding the complex interaction and relative contributions of factors involved in species and trait diversification is crucial to gain insights into the evolution of Neotropical biodiversity. Here, we investigated the drivers of morphological variation in bromeliads along a latitudinal gradient in a biodiversity hotspot.Atlantic Forest, Brazil.Vriesea (Bromeliaceae).A species complex in the genus matK and trnL‐F) from 89 individuals to assess genetic diversity, population structure and phylogenetic relationships. We tested the influence of climate, altitude and genetic distance on morphological traits using linear statistical models.We measured shape and size variation for 208 floral bracts and 176 leaves in individuals from 14 localities using geometric morphometrics. We compiled data for two chloroplast regions , leaves are larger and floral bracts are wide‐elliptic, making them better suited for increased water accumulation. In contrast, at less seasonal sites , leaves are narrower and floral bracts are lanceolate‐shaped, facilitating water drainage. The biogeographical break we identified suggests a role of tectonic activity and climatic oscillations in promoting species divergence and diversification. The Vriesea incurvata complex is widely and continuously distributed across the Atlantic Forest. A recent taxonomic revision using morphological multivariate analysis showed a north–south gradient in the width and length of both leaves and floral bracts and identified five taxa, including a new variety V. taritubensis var. patens  if shape is less labile than size , Neves et al.  and altitudinal  variation. Along the study area, the climate ranges from tropical with dry winter at Serra dos Órgãos to humid subtropical with hot summer or temperate summer towards the south, with no distinct dry season. Warmer temperatures are registered in the southeast ranges of both varieties of ns Table .2.2V. incurvata and V. taritubensis. We randomly sampled 8–19 individuals per locality.To explore shape and size variation we sampled and georeferenced individuals from 14 localities, 208 individuals for floral bract and 176 individuals for leaf datasets Figure . We seleWe scanned one floral bract from the middle of the inflorescence and one leaf from the middle of the rosette of each specimen. We then characterized shape by a set of seven landmarks for bracts profile (bracts in side view) and nine for leaves. We discriminate landmarks into anatomical, when located at homologous points with biological meaning; mathematical, when located at extreme points with some geometrical property; and pseudo‐landmarks, when located between other landmarks  plot. We also tested for digitization error using Procrustes ANOVA in two sets of data  following Klingenberg and McIntrye . We anal2.3trnL‐trnF intron and intergenic spacer and matK gene for 89 individuals in 15 localities. Among the 15 localities, we have morphological data for nine of them. We collected genetic data independently from the morphological data, individuals were randomly sampled according to availability in the field. We used plastidial data (trnL‐trnF and matK) from V. incurvata sequenced by Zanella, Palma‐Silva, Goetze, and Bered  and nucleotide (π) diversity . We then performed an analysis of molecular variance to assess the partition of genetic diversity among taxa and localities, using ARLEQUIN with 10,000 permutations.To assess genetic diversity and population structure, and to infer the relationships among individuals, we concatenated sequences from two chloroplast regions: nd Bered  and fromis Table . Data wea et al. . We perfa et al. , implemea et al. . Mononucity Nei,  for eachity Nei, . The sofity Nei,  was usedAlcantarea imperialis (Carrière) Harms, Goudaea chrysostachys (É. Morren) W. Till & Barfuss and Goudaea ospinae (H. Luther) W. Till & Barfuss were included as out‐group. The HKY nucleotide substitution model was used for each marker separately in MEGA. The uncorrelated lognormal relaxed clock and the birth‐death model , (b) Alcantarea + Vriesea s.s. clade (8 ± 2 Mya) as enforced monophyletic group and (c) Vriesea s.s. (5 ± 1.5 Mya). We evaluated that effective sample sizes for all main parameters were above 200 in Tracer 1.6  was then incorporated to the model.To investigate the correlation of the genetic structure, bioclimatic variables and altitude with morphometric traits variation, we ran multiple linear models and to identify the best model in explaining traits variation, we performed model selection based on AIC . We identified a shift from lanceolate to wide‐elliptic along the Atlantic Forest latitudinal gradient. In the north, individuals of V. taritubensis var. brevisepala present elliptic bracts ; further south individuals of V. taritubensis var. taritubensis and V. taritubensis var. patens have lanceolate bracts ; and individuals of V. incurvata, spread throughout the southern portion of Atlantic Forest, with wide‐elliptic bracts  and among localities . Differences in size separated V. taritubensis var. patens, with the smallest bracts , of V. incurvata, with the largest ones. The locality III presented the longest bracts and localities X‐XX had the largest medium centroid size due to the wider bracts  and localities  was indicated. The PCA showed shape changes from narrow‐obovate to linear along the first PC, which accounted for 75% of the total variance , but differed among localities . The strongest differentiation was among the individuals of V. taritubensis var. taritubensis  and within V. incurvata   resulting in 27 haplotypes from the cpDNA dataset Table . Vrieseaty Table . We founon Table . Two maiV. taritubensis and V. incurvata likely diverged around 5 million years ago (Mya) during Late Quaternary (Pliocene), and V. taritubensis varieties more recently  and V. incurvata (PP = 1) specimens. Vriesea taritubensis individuals tend to cluster in two major subclades splitting V. taritubensis var. taritubensis and V. taritubensis var. brevisepala, with few exceptions. While individuals V. taritubensis var. patens are spread along the two subclades. However, the clade comprising most individuals from V. taritubensis var. taritubensis lacks strong posterior probability support . Annual precipitation, temperature seasonality and genetics were recovered as drivers of leaf size changes and our best fit model for leaf size explained 28% of overall variation. Only a small portion of the variation was predicted by bract size and leaf shape models  and both traits correlated with genetics and altitude Table . For com4V. taritubensis and V. incurvata likely diverged around 5 Mya. Divergence was likely a consequence of tectonic events that continued shaping the complex topography of the Serra do Mar at that time, resulting in marked habitat heterogeneity  in the southern, subtropical portion of the Atlantic Forest , where climate is hot most of the year and annual precipitation reaches the highest levels in the studied area . The high rainfall availability throughout the year selects for narrow bracts and leaf blades, behaving like gutters for water drainage. An intermediate morphology of elliptic bracts is found at the northernmost distribution , where annual precipitation is moderate  and there is little seasonal temperature variation  along PCo 2  and also coincides with the divergence of other widely distributed Atlantic Forest lineages such as reptiles and amphibians  Almeida, . These gV. incurvata and V. taritubensis occurs in this region (between 15° and 23°S) and was reported for other Vriesea species, although at different locations  and vegetative (leaves) traits respond in similar ways to abiotic factors, contradicting previous suggestions. Temperature seasonality and rainfall regime are associated with the morphological diversification of these bromeliads as they drive traits variation that are diagnostic for taxa and have an ecological role. Morphological variation and genetic structure patterns coincided with recurrent biogeographical breaks in space  and time (Late Pliocene) with other widely distributed Atlantic Forest organisms. We shed new light on the species delimitation of one of many species complexes of morphologically similar taxa within Beatriz Neves is interested in the evolution and diversification of bromeliads in the Neotropics. The research team studies systematics of Bromeliaceae, population genetics of Neotropical plants, and the past, present and future of biodiversity.Author contributions: B.N. collected the morphological data, and C.M.Z. the genetic data. A.F.C., B.N., C.D.B. and A.A. conceived the ideas. B.N. and C.M.Z. performed the analyses. I.M.K. built the phylogeny. All authors contributed to interpreting and discussing results and writing the manuscript. Click here for additional data file. Click here for additional data file. Click here for additional data file.


We investigated a likely scenario of COVID-19 spreading in Brazil through the complex airport network of the country, for the 90 days after the first national occurrence of the disease. After the confirmation of the first imported cases, the lack of a proper airport entrance control resulted in the infection spreading in a manner directly proportional to the amount of flights reaching each city, following the first occurrence of the virus coming from abroad.We developed a Susceptible-Infected-Recovered model divided in a metapopulation structure, where cities with airports were demes connected by the number of flights. Subsequently, we further explored the role of the Manaus airport for a rapid entrance of the pandemic into indigenous territories situated in remote places of the Amazon region.The expansion of the SARS-CoV-2 virus between cities was fast, directly proportional to the city closeness centrality within the Brazilian air transportation network. There was a clear pattern in the expansion of the pandemic, with a stiff exponential expansion of cases for all the cities. The more a city showed closeness centrality, the greater was its vulnerability to SARS-CoV-2.We discussed the weak pandemic control performance of Brazil in comparison with other tropical, developing countries, namely India and Nigeria. Finally, we proposed measures for containing virus spreading taking into consideration the scenario of high poverty. From 17th to 18th March, Brazil had an increase of 31% in 1 day, with only four capitals exhibiting community transmission, which was the same in India. Nonetheless, a very distinct pattern in the ascending starting point for the reported disease exponential curve was observed in each country. By enlarging the comparison to another developing tropical country in the Southern Hemisphere , we selected Nigeria since it was the first country to detect a COVID-19 case in sub-Saharan Africa  formed a metapopulation structure.Each person in a city was taken as a component of a superorganism, that is, an interdependent entity where living individuals are not biologically independent between them in various subtle ways. By doing so, we dealt with cities as the sampling units, not the people, and, therefore, our model is slightly different from classic bolsonic models . FlightsR2 = 0.76; p < 0.0001) and, thus, a good proxy of city size. Similarly, to our purpose the time when the collective infection stage was reached inside each city was irrelevant. Thus, we assumed that the city was fully infected and became infectious to the whole system, and, therefore, became a source and not a sink of infection events, after a certain amount of arriving contaminated people sums up. Hence, the SIR model started having cities with only susceptible events and change of these to the infected stage was counted as proportion of the population. Infected events only appeared by migration, that is, travelers only from Italy and Spain, for sake of simplicity and proximity to the early facts.In order to describe the pattern of air transportation and its role in the spreading of the disease, we built a Susceptible-Infected-Recovered (SIR) model  split amAfter the first occurrence having been recorded in the country, infected people started to spread through the national airlines, and this spreading is proportional to the amount of infected people accumulating in a city (see the model explanation below). Because of that, the model causes a transient timing, when the amount of infected people arriving is greater than the community transmission. Afterwards, the city started to disseminate to other places by probability rules. As the transmission is quite likely to happen by the simple proximity person-to-person, due to the resistance of the virus in air droplets and surfaces, as hands or metals, we assumed that a simple encounter will cause infection. However, this became an inner trait of each city that after having local transmission, starts to transmit to other cities as explained above. In addition, the model assumes that there is no public control in people circulation after arriving of an infected person. Ethical approval was not necessary as human participants were not involved in the study.S) encounters an infected one (I). Conversely, the model has a probability of an infected one get recovered (R) given by a parameter γ. Analytically:t and t + 1 represent the present time and the next time, respectively, and N = S + I + R is the total constant population. In this work, we proposed two modifications of the SIR model. The first one is related to the fact that we considered all the Brazilian cities that have an airport as subpopulations, meaning that each city has its own SIR variables set. Thus, we had Si, Ii, and Ri where i was a given city. In our case study, 1 ≤ i ≤ 154. The second important modification was related to the connections among the cities, which we used as a network of disease dissemination. This city network is given by the domestic flights among all the airports in Brazil, taking into account the number and the direction of flights. Therefore, we have a weighted network, where the weighted closeness centrality of each city was measured. Thus, the flights provided a dependent mechanism by which the between-cities connections caused a coupling of SIR equations based on the network flight structure. This coupling is provided by the last equation and is mediated by the new introduced parameter alpha. Using We used a modified version of the SIR model, which took into account the topology of how the cities-demes were linked by domestic flights. In the SIR original model, the infection of susceptible cities occurs by probability β of a healthy being . Divided between each infected city, this makes mathematically small numbers, and thus resistance becomes demographically irrelevant to our output of early disease dissemination. Furthermore, by dealing with only the infected portion of the population (proportion of infected), we avoided the uncertainties related to the little known COVID-19 resistance development (The modified version of SIR model is then described as follows:elopment .https://coronavirus.jhu.edu/map.html), which leads to β = 0.3035  were reached; however, it occurred with a distinct intensity . There wThe first ten cities to ascend infection rates  will actually reach this point about the same time, which is a concerning pattern for the saturation of the public health services. Moreover, this peak in those cities will saturate all the best hospitals in the country simultaneously.Therefore, we defined the average proportion of infected people for the 90 days as a measure of the vulnerability to COVID-19 dissemination. Henceforth, we found the more a city shows closeness centrality within the air transportation network, the greater was its vulnerability to disease transmission . This schttps://covid.saude.gov.br/, 2020), and it is a node that is one or two steps to all the Amazonian cities. Thus, according to our model, Manaus may reach 1% of the infected population by the 44th day, while, for instance, the far west Amazonian Tabatinga will take 61 days to reach the same 1% of the population infected. By day 60, Manaus may have an average of 50% of its population infected if nothing is done to prevent it. Tabatinga may also reach the aforementioned value by day 78, if nothing is done to avoid it. To sum up, within 46 days, all the Amazonian cities will have 1% of their population infected and a mean of 50% by day 70.Herein, we showed that an uncontrolled complex airport system made a whole country vulnerable in few weeks, allowing the virus to reach the most distant and remote places, in the most pessimistic scenario. According to our model, any connected city will be infected after 3 months. As the number of flights arriving in a city is the driver for the proportion of infected people, Manaus, which is a relevant regional clustering, was infected sooner. Indeed, on the 17th of March, Manaus was the first Amazonian city with confirmed cases . Clearly, one country is doing much better in preventing the entrance of cases and the spreading of the disease by controlling infected citizens. Indeed, according to the WHO, the Ministry of Health and Family Welfare (MoHFW) of India has taken an early action, and “aggressively stepped up the response measures—find, isolate, test, treat and trace”  against 47 days after the first Indian case (January 30th), Brazil has already had 5.4 more confirmed cases than India  than Brazil  but with a similar population , had impIn order to find and isolate is, from an ecological perspective, the most efficient way to reduce the carrying capacity of a new disease, and thus, restrict its wide spreading, and this must start at the airports. As Brazil is just struggling to impose social distancing, a State-to-State decision with little support from the Federal Government, the scenario is evolving more severely. Regardless of flaws in the comparisons of confirmed cases between the countries, by 16th April, India still had 12,380 cases and 414 deaths while Brazil had 25,262 cases and 1,532 deaths . NigeriaBesides the within-city pattern of virus spreading, one must take into account the pattern of dispersion between cities after the virus has invaded. Additionally, for the Brazilian case, one cannot ignore that, eventually, the occurrence of the first case may have occurred nearly 1 month before official records, during the carnival period. This is the largest popular street party on the planet, with 6.4 million people in Rio de Janeiro, and 16.3 million in Salvador, and the Without a social distancing policy, virus propagation may result in chaotic dynamics, sensu The consequences of this uncontrolled SARS-CoV-2 spreading is particularly serious if one takes into consideration the chances of a mutant virulent strain appearing and spreading into poorer and little monitored places of the world. Specifically, for the Amazon region, the lack of any control will make the city of Manaus a very sensitive cluster for public health, due to predominantly poor and indigenous-dominated cities in the region, which are connected to Manaus and will be rapidly infected. Reaching isolated regions means reaching indigenous or traditional communities, whose individuals are classically more susceptible to new pathogens than western-influenced or mixed urban populations. Therefore, a way to prevent such spreading, if still there is time, would be to deal with airports as entrances that need severe infection barriers.The Brazilian media and the Ministry of Health have announced that 50 days from the introduction of SARS-CoV-2 in the country, it has spread across the regions and cities quite like we had predicted, even slightly faster. For instance, the time taken for Manaus to be compromised by the disease was as short as we predicted. A combination of being an important regional clustering in the airport network, and relatively limited hospital capability, resulted in a fast saturation of intensive care units, in cities as Manaus, Recife, and São Luis. As Manaus will disseminate the disease across the region, quickly reaching far remote indigenous communities, it should be on lockdown right now, to cause an invasion threshold, sensu An eventual lesson to take for the whole country is that inflexible, severe, and easy to repeat protocols must be applied to all the cities with airports. Likewise, the follow-up monitoring of suspicious individuals and their living network should be reinforced as a national strategy to prevent a large territory to be taken over by a pandemic in a short period of time. In other words, internationally accepted procedures must be taken and even be reviewed to adjust to complex national flight networks of any country. Such procedures must be considered as a priority for national remote airports too, in order to keep poorer and worse equipped cities away from a rapid spread of a pandemic disease.It is clear, at this point, that a fast spread of the SARS-CoV-2 is a reality in Brazil, and across most of the country. We proposed this model in order to emphasize the fragility of Brazilian surveillance in the airport network, in an attempt to cause some policy change in time to preserve at least the most remote regions, which are also the most vulnerable, with a weaker health service. Moreover, most of the Eastern part of the country must stay in social distancing in order to prevent a health public collapse by mid-May, as the Brazilian Ministry of Health predicted. So far, this has been a State-to-State decision, similarly to the United States, and those States that have been stronger in isolation measures, are indeed delaying the peak. Moreover, even if it is too late for the first wave of infection in many cities, one must be prepared for a second likely wave, mainly considering the lack of a central government policy for social distancing.In addition, we also could consider the generalized poverty of Brazil as a further problem that our model did not deal with. The chances to produce home-to-home isolation, even legally imposed, is impossible for these poor communities. Nonetheless, considering the few main entrances of most of the Brazilian shanty towns and communities, a similar to airport entrance severe control must be considered to protect a larger but closely connected set of people, eventually following the protocols used for the control of Ebola during the last epidemic in Africa .10.7717/peerj.9446/supp-1Supplemental Information 1The code was developed in C, and it works as a modification of SIR model running along with the topology of the domestic flight network. After initiating all variables to an initial condition, that is, S , I (infected) and R (recovered) of each city, the code starts loading the network and calculates the total number of flights among all the cities. This information is used to feed the classical SIR model introducing in the variable I, the information regarding infected travelers and non-travelers, and the model calculates the next S, I and R of all the cities. This calculation is done in a loop time representing days, the time step that the model was calibrated.Click here for additional data file.10.7717/peerj.9446/supp-2Supplemental Information 2The spreadsheet presents all the 120 cities with airport(s), their state, latitude and longitude, followed by the closeness centrality in the network. The columns t0 to t90 are the times from 0 to 90 days. Lines for the time columns are the percentage of infected people per city per time.Click here for additional data file.10.7717/peerj.9446/supp-3Supplemental Information 3This file has a short movie describing the dynamics of SARS-Cov-2 dissemination across Brazil, in two versions.Click here for additional data file.


Otocyon megalotis) and the aardwolf (Proteles cristatus), both having subspecies with similar disjunct distributions in Eastern and Southern Africa. First, we obtained reference genomes with high contiguity and gene completeness by combining Nanopore long reads and Illumina short reads. Then, we showed that the two subspecies of aardwolf might warrant species status  by comparing their genome-wide genetic differentiation to pairs of well-defined species across Carnivora with a new Genetic Differentiation index (GDI) based on only a few resequenced individuals. Finally, we obtained a genome-scale Carnivora phylogeny including the new aardwolf species.In a context of ongoing biodiversity erosion, obtaining genomic resources from wildlife is essential for conservation. The thousands of yearly mammalian roadkill provide a useful source material for genomic surveys. To illustrate the potential of this underexploited resource, we used roadkill samples to study the genomic diversity of the bat-eared fox ( In the context of worldwide erosion of biodiversity, obtaining large-scale genomic resources from wildlife is essential for biodiversity assessment and species conservation. An underexploited, but potentially useful, source of material for genomics is the many thousands of annual wildlife fatalities due to collisions with cars. In particular, mammalian roadkill is unfortunately so frequent that several citizen-science surveys have been implemented on this subject in recent decades . For exaRecent advances in the development of high-throughput sequencing technologies have made the sequencing of hundreds or thousands of genetic loci cost-efﬁcient and have offered the possibility of using ethanol-preserved tissues, old DNA extracts, and museum specimens . In the Otocyon megalotis, Canidae) and the aardwolf . These two species are among several African vertebrate taxa presenting disjunct distributions between Southern and Eastern Africa that are separated by more than a thousand kilometres  and the Eastern bat-eared fox  (P. cristatus cristatus) and the Eastern aardwolf   , and theionalis) . Howeverionalis) , no geneionalis) . Here, wO. megalotis and P. cristatus, we first sequenced and assembled two reference genomes from roadkill samples by combining ONT long reads and Illumina short reads using the MaSuRCA hybrid assembler. The quality of our genome assemblies was assessed by comparison to available mammalian genome assemblies. Then, to estimate the genetic diversity of these species and to perform comparative genome-scale species delineation analyses, two additional individuals from the disjunct South African and Tanzanian populations of both species were resequenced at high depth-of-coverage using Illumina short reads. Using these additional individuals, we estimated the genetic diversity and differentiation of each subspecies pair via an FST-like measure, which we called the genetic differentiation index (GDI), and compared the results with the genetic differentiation among pairs of well-established carnivoran sister species. Based on measures of genetic differentiation, we found that the two subspecies of P. cristatus warrant separate species status, whereas the subspecies of O. megalotis do not show such differentiation. Our results show that high-quality reference mammalian genomes could be obtained through a combination of short- and long-read sequencing methods providing opportunities for large-scale population genomic studies of mammalian wildlife using (re)sequencing of samples collected from roadkill.To evaluate the taxonomic status of the proposed subspecies within both P. cristatus, the two subspecies of O. megalotis, Parahyaena brunnea, Speothos venaticus and Vulpes vulpes, plus the sequences extracted from Ultra Conserved Elements (UCE) libraries for Bdeogale nigripes, Fossa fossana, and Viverra tangalunga , comprised 142 species or subspecies representing all families of Carnivora. Maximum likelihood (ML) analyses reconstructed a robust mitogenomic phylogeny, with 91.4% of the nodes (128 out of 140) recovered with bootstrap support higher than 95% (Vulpes vulpes) and the fennec (V. zerda) (0.029) or the steppe polecat (Mustela eversmanii) and the Siberian weasel (M. sibirica) (0.034)  see .O. megalotis and 10 P. cristatus individuals, respectively. After adding the corresponding sequences from the newly assembled mitogenomes, ML phylogenetic inference was conducted on each dataset. The patristic distances between all tips of the resulting phylogenetic trees were measured and classified into two categories: (i) intraspecific variation (polymorphism) for distances inferred among individuals of the same species and (ii) interspecific divergence for distances inferred among individuals of different species. Despite an overlap between polymorphism and divergence in both mitochondrial genes, this analysis revealed a threshold between polymorphism and divergence of approximately 0.02 substitutions per site for Carnivora (Proteles ssp.) was higher than the majority of the intraspecific distances observed across Carnivora. However, with patristic distances of 0.020 for COX1 and 0.032 for CYTB, the genetic distances observed between the two subspecies of bat-eared fox (Otocyon ssp.) were clearly in the ambiguous zone and did not provide a clear indication of the specific taxonomic status of these populations.To further assess the genetic distances between the two pairs of subspecies and compare them to both polymorphism and divergence values observed across Carnivora, two supplemental datasets, including at least two individuals per species, were assembled by retrieving all COX1 and CYTB sequences, which are the two widely sequenced mitochondrial markers for carnivorans, available on GenBank. These datasets include 3,657 COX1 sequences for 150 species and 6,159 CYTB sequences for 203 species of Carnivora, including 5 arnivora . With a O. megalotis ssp. and ~1.3 [CI: 1.88–0.93] Mya for P. cristatus ssp.; Finally, to test whether the two pairs of allopatric subspecies diverged synchronously or in two different time periods, Bayesian molecular dating inferences were performed on the 142-taxon ML mitogenomic tree. The resulting divergence times were slightly different depending on the clock model used  despite the convergence of the MCMC chains for all models. Cross-validation analyses resulted in the selection of the LN and UGAM models as the models with the best fit based on a higher cross-likelihood score than that of CL (LN and UGAM versus CL mean scores = 35 8). Unfortunately, these two statistically indistinguishable models provided different divergence times for the two pairs of subspecies, with LN favoring a synchronous divergence : 6.72–0.43]; P. c. cristatus) and 33.0 Gb using 13 flow cells for the Southern bat-eared fox   was about two times higher than the N50 of the DNA fragment size obtained for O. megalotis . The quality of the reads base-called with the high accuracy option of Guppy was significantly higher than the quality of those translated with the fast option, which led to better assemblies  . Owing tlies see . Complemquencing .P. cristatus) and 11,081 scaffolds and an N50 of 728 kb for the bat-eared fox   . Our twogalotis)  and (ii)P. cristatus and O. megalotis, the number of shared heterozygous sites, unique heterozygous sites, and homozygous sites between individuals was computed to estimate an FST-like statistic . Since we were in possession of two individuals for the Southern subspecies and only one for the Eastern subspecies of both species, the genetic differentiation between the two individuals within the Southern subspecies and between the Southern and Eastern subspecies was computed. To account for the variation across the genome, 10 replicates of 100 regions with a length of 100 kb were randomly chosen to estimate genetic differentiation. Interestingly, in both species, the mean heterozygosity was higher in the Southern subspecies than in the Eastern subspecies. For the aardwolf, the mean heterozygosity was 0.189 per kb (sd = 0.010) in the Southern population and 0.121 per kb (sd = 0.008) in the Eastern population. For the bat-eared fox, the mean heterozygosity was 0.209 per kb (sd = 0.013) in the Southern population and 0.127 per kb (sd = 0.003) in the Eastern population. This heterozygosity level is low compared to that of other large mammals  and thus that these two subpopulations are likely panmictic  to 0.137 for lion (Panthera leo). As expected, comparing the polymorphisms of two individuals between closely related species led to a higher interspecific GDI ranging from 0.437 on average for the wolf/golden jackal (Canis lupus/Canis aureus) pair to 0.760 for the lion/leopard (Panthera leo/P. pardus) pair (C. lupus) and the golden jackal (C. aureus) averaged 0.44, indicating that the two subspecies of aardwolf (GDI = 0.533) are genetically more differentiated than these two well-defined species, and only slightly less differentiated than the brown bear (Ursus arctos) and the polar bear (Ursus maritimus). Conversely, the genetic differentiation obtained between the bat-eared fox subspecies (GDI = 0.294) was lower than the genetic differentiation estimates obtained for any of the four reference species pairs evaluated here , we chose a comparative approach and applied the same analyses to four well-defined species pairs of carnivorans, for which similar individual sampling was available. The genetic differentiation estimates between the two individuals belonging to the same subspecies (Southern populations in both cases) were on average equal to 0.005 and 0.014 for anmictic . In contes pairs . First, us) pair . The gented here . We verited here . We alsoted here .Ne) trajectory over time for each sequenced individual. For both the aardwolf and the bat-eared fox, the individual from Eastern African populations showed a continuous decrease in Ne over time, leading to the recent Ne being lower than that in Southern African populations (Ne trajectories for the aardwolf populations did not synchronize over the whole period (~2 Myrs). Interestingly, the Southern populations of both species showed a marked increase in population size between ~10 and 30 kya before sharply decreasing in more recent times  model to estimate the ancestral effective population size , representing all but two families of the Carnivora (Nandiniidae and Prionodontidae). The non-annotated genome assemblies of these different species were annotated with a median of 18,131 functional protein-coding genes recovered for each species. Then, single-copy orthologous gene identification resulted in a median of 12,062 out of the 14,509 single-copy orthologues extracted from the OrthoMaM database for each species, ranging from a minimum of 6305 genes for the California sea lion  and a maximum of 13,808 for the dog (Canis familiaris) (P. c. cristatus), 12,050 for the Eastern aardwolf , and 11,981 for the Southern bat-eared fox  (Phylogenetic relationships within the Carnivora were inferred from a phylogenomic dataset comprising 52 carnivoran species (including the likely new iliaris) . Our newgalotis) . These gP. cristatus and P. septentrionalis) were the sister-group of a clade composed of the carnivorous spotted (Crocuta crocuta) and striped (Hyaena hyaena) hyaenas. Congruent phylogenetic relationships among Feliformia families and within hyaenids were also retrieved with the mitogenomic data set , Pinnipedia , and Musteloidea, composed of Ailuridae (red pandas), Mephitidae (skunks), Procyonidae (raccoons), and Mustelidae . Within the Arctoidea, the ML phylogenetic inference on the concatenation provided support for grouping the Pinnipedia and the Musteloidea to the exclusion of the Ursidae (bears) with maximum bootstrap support  values . To furtdata set . The shodata set , includi support , as in t support . However support . In the  support . Finally support .high accuracy option rather than the fast option of Guppy 3.1.5 leads to more contiguous assemblies by increasing the N50 value. By relying on this protocol, we were able to generate two hybrid assemblies by combining Illumina reads at relatively high coverage (50-60x) and MinION long reads at relatively moderate coverage (11-13x), which provided genomes with high contiguity and completeness. These represent the first two mammalian genomes obtained with such a hybrid Illumina/Nanopore approach using the MaSuRCA assembler for non-model carnivoran species: the aardwolf (P. cristatus) and the bat-eared fox . Despite the use of roadkill samples, our assemblies compare favorably, in terms of both contiguity and completeness, with the best carnivoran genomes obtained so far from classical genome sequencing approaches that do not rely on complementary optical mapping or chromatin conformation approaches. Overall, our carnivoran hybrid assemblies are fairly comparable to those obtained using the classic Illumina-based genome sequencing protocol involving the sequencing of both paired-end and mate-paired libraries  and several individuals of the same species (polymorphism) based on the COX1 and CYTB genes across Carnivora, we were able to pinpoint a threshold of approximately 0.02 substitutions per base separating divergence from polymorphism, which is in accordance with a recent study of naturally occurring hybrids in Carnivora . Conversely, for O. megalotis, this first genetic indicator seems to confirm the distinction at the subspecies level. However, mitochondrial markers have some well-identified limitations  compared to the population at large (p between) is measured with several individuals per population . Such an index of genetic differentiation, by measuring the level of population structure, could provide support to establish accurate species boundaries. In fact, delineating species has been and still is a complex task in evolutionary biology  or between two closely related species (divergence) allowed us to define a threshold between genetic polymorphism and genetic divergence across the Carnivora (P. cristatus (1) present more genetic differentiation between each other than the two well-defined species of golden jackal (Canis aureus) and wolf (C. lupus), and (2) present more genetic differentiation than the more polymorphic species of the dataset, the lion (P. leo). Despite known cases of natural hybridization reported between C. aureus and C. lupus  the taxonomic level for the two subspecies of O. megalotis be maintained.As proposed by C. lupus , the tax process . The subontinuum  and are P. c. septentrionalis  as a very pale yellowish cream, almost white ventrally and on the forehead. This contrasts with the grizzled gray of the forehead of P. c. cristatus . However, fur length and hence stripe distinctiveness may just be a phenotypic response to lower temperatures at higher latitudes compared with equatorial East African specimens. P. c. septentrionalis than P. c. cristatus but revealed no significant differences between other skull measurements including condylobasal length of skull  analyses revealed that the Southern and Eastern African populations have different effective population-size estimates over time, confirming that they have been genetically isolated for several thousand years, which is more so for the aardwolf than for the bat-eared fox. This supports the hypothesis of two separate events leading to the same disjunct distributions for the two taxa, in accordance with mitochondrial dating. Nevertheless, the population trends are rather similar and are characterized by continuous declines between 1 Mya and 100–200 kya that are followed by an increase that is much more pronounced in the Southern populations of both species between 30 and 10 kya. The similar trajectories exhibited by both species suggest that they were under the influence of similar environmental factors, such as climate and vegetation variations.Aardwolves and bat-eared foxes live in open environments including short-grass plains, shrubland, and open and tree savannas, and both are highly dependent on herbivorous termites for their diet. Therefore, the fluctuation of their populations could reflect the evolution of these semi-arid ecosystems determining prey abundance during the last million years. However, the global long-term Plio-Pleistocene African climate is still debated. For Eastern Africa, some studies have suggested an evolution toward increased aridity , whereasSouthern populations exhibit a similar decreasing trend between 1 Mya and 100 kya. Once again, the relevant records appear contradictory. This could be the result of regional variation across South Africa, with aridification in the Southwestern part and wetter conditions in the Southeast . FinallyScleroptila gutturalis), the greater kestrel , the double-banded courser (Smutsornis africanus), the red-fronted tinkerbird (Pogoniulus pusillus), the Cape crow (Corvus capensis), and the black-faced waxbill (Estrilda erythronotos), supporting the role of the environment in the appearance of these disjunct distributions. Finally, these new demographic results, showing recent population size declines in both regions in both species, might be taken into account when assessing the conservation status of the two distinct aardwolf species and bat-eared fox subspecies.The global decrease in population size detected in the Southern and Eastern populations could also reflect the fragmentation of a continuous ancestral range. The global trend toward a wetter climate may have favored the development of the tropical rainforest in central Africa, creating a belt of unsuitable habitat. This is in line with previous studies describing diverse biogeographical scenarios involving the survival and divergence of ungulate populations in isolated savanna refuges during Pleistocene climatic oscillations . In thisP. septentrionalis). The resulting phylogeny is fully resolved with all nodes supported with UFBS values greater than 95% and is congruent with previous studies  and the spotted hyaena (C. crocuta), in accordance with previous studies (Parahyena brunnea)  .O. megalotis) is grouped with the red fox (Vulpes vulpes) and the other representative of the Vulpini, but with a very short branch, and concordance analyses indicate conflicting signals on this node. Regarding the Arctoidea, historically the relationships between the three superfamilies of arctoids have been contradictory and debated. The least supported scenario from the literature is that in which the clade Ursoidea/Musteloidea is a sister group of the Pinnipedia  and the Southern bat-eared fox . This cost-effective strategy provides opportunities for large-scale population genomic studies of mammalian wildlife using resequencing of samples collected from roadkill and opportunistic field collection. Indeed, by defining a genetic differentiation index  based on only three individuals, we illustrated the potential of the approach for comparative genome-scale species delineation in both species for which subspecies have been defined based on disjunct distributions and morphological differences. Our results, based on both mitochondrial and nuclear genome analyses, indicate that the two subspecies of aardwolf warrant elevation to species level , but the O. megalotis subspecies do not warrant this status. Hence, by generating reference genomes with high contiguity and completeness, this study shows a practical application for genomics of roadkill samples.The protocol developed here to extract the best part of the DNA from roadkill samples provides a good way to obtain genomic data from wildlife. Combining Illumina short-reads and Oxford Nanopore long-reads using the MaSuRCA hybrid assembler allowed us to generate high-quality reference genomes for the Southern aardwolf , and two Southern aardwolves . As aardwolf specimen NMB 12641 was still very fresh, we also sampled muscle and salivary gland and preserved them in RNAlater stabilization solution (Thermo Fisher Scientific). These roadkill specimens were sampled under standing permit number S03016 issued by the Department of National Affairs in Pretoria (South Africa) granted to the National Museum, Bloemfontein. These samples have been sent to France under export permits (JM 3007/2017 and JM 5042/2018) issued by the Free State Department of Economic, Small Business Development, Tourism and Environmental Affairs (DESTEA) in Bloemfontein . All tissue samples collected in this study have been deposited in the mammalian tissue collection of the National Museum, Bloemfontein . Additional tissue samples for an Eastern aardwolf  male neonate (NMS.Z.2018.54) stillborn from Tanzanian parents in 2015 at Hamerton Zoo Park (UK) have been provided by the National Museums Scotland , and for an Eastern bat-eared fox (O. m. virgatus) from Tanzania (FMNH 158128) by the Field Museum of Natural History . As these two species are classified as Least Concern by the IUCN, and thus do not require CITES permits for international transport, the samples were transferred to France under import permits issued by the Direction régionale de l'environnement, de l'aménagement et du logement (DREAL) Occitanie in Toulouse (France).We conducted fieldwork in the Free State province of South Africa in October 2016 and October 2018. While driving along the roads, we opportunistically collected tissue samples from four roadkill specimens, from which we sampled ear tissues preserved in 95% ethanol: two Southern bat-eared foxes , P. c. septentrionalis (NMS Z.2018.54), O. m. megalotis (NMB 12639), O. m. virgatus (FMNH 158128), Speothos venaticus (ISEM T1624), Vulpes vulpes (ISEM T3611), and Parahyaena brunnea (ISEM FD126), prepared Illumina libraries following the protocol of Viverra tangalunga, Bdeogale nigripes, and Fossa fossana. Additional read mappings were done with Geneious (Manis javanica) to use as an outgroup.In order to assemble a mitogenomic data set for assessing mitochondrial diversity among quencing . BrieflyGeneious  to closeadjustdirection--. A nucleotide supermatrix was created by concatenating protein-coding and ribosomal RNA genes for the 142 taxa (140 species and two subspecies). Phylogenetic inferences were performed with Maximum likelihood (ML) as implemented in IQ-TREE 1.6.8  and the parameter values were used to compute the likelihood of the second part of the dataset (10%). This procedure was repeated 10 times for each model. Finally, the likelihood of each repeated test was computed and summed for each model with the readcv and sumcv subprograms, respectively. The molecular clock model with the highest cross-likelihood scores was considered as the best fitting.Mitochondrial protein-coding genes were individually aligned using MACSE v2  with defEE 1.6.8  with theEE 1.6.8  with strEE 1.6.8 . Three iO. megalotis and P. cristatus, respectively. After aligning each barcoding dataset with MACSE v2, ML phylogenetic inferences were performed with IQ-TREE 1.6.6 using the optimal substitution model as determined by ModelFinder  following manufacturer’s instructions. A total amount of 1.0 μg DNA per sample was sent as input material for Illumina library preparation and sequencing to Novogene Europe . Sequencing libraries were generated using NEBNext DNA Library Prep Kit following manufacturer’s recommendations and indices were added to each sample. Genomic DNA was randomly fragmented to a size of 350 bp by shearing, then DNA fragments were end-polished, A-tailed, and ligated with the NEBNext adapter for Illumina sequencing, and further PCR enriched by P5 and indexed P7 oligos. The PCR products were purified (AMPure XP system) and the resulting libraries were analysed for size distribution by Agilent 2100 Bioanalyzer and quantified using real-time PCR. Since the genome sizes for these two species was estimated to be about 2.5 Gb, Illumina paired-end 250 bp sequencing was run on HiSeqX10 and NovaSeq instruments to obtain about 200 Gb per sample corresponding to a genome depth-of-coverage of about 80x.Considering the DNA quality required to perform sequencing with Oxford Nanopore Technologies (ONT), a specific protocol to extract DNA from roadkill was designed . First, high accuracy option, which takes longer but is more accurate than the standard fast model (https://github.com/rrwick/Porechop). To take advantage of both the high accuracy of Illumina short reads sequencing and the size of MinION long reads, assemblies were performed using the MaSuRCA hybrid genome assembler (https://www.ncbi.nlm.nih.gov/assembly) on August 13th, 2019 with filters: ‘Exclude derived from surveillance project’, ‘Exclude anomalous’, ‘Exclude partial’, and using only the RefSeq assembly for Homo sapiens. Finally, we assessed the gene completeness of our assemblies by comparison with the 63 carnivoran assemblies available at NCBI on August 13th, 2019 using Benchmarking Universal Single-Copy Orthologs (BUSCO) v3  v3  with theUSCO) v3  through USCO) v3 .P. cristatus, we sampled an additional roadkill individual of the South African subspecies P. c. cristatus (NMB 12667) and an individual of the East African subspecies P. c. septentrionalis (NMS.Z.2018.54) born in a zoo from wild Tanzanian parents  and an individual of the East African subspecies O. m. virgatus (FMNH 158128) from Tanzania (To assess the genetic diversity in  parents . A similTanzania . DNA extp within) compared to the population at large (p between).In a panmictic population, alleles observed in one individual are shared randomly with other individuals of the same population and the frequencies of homozygous and heterozygous alleles should follow Hardy-Weinberg expectations. However, any structure in subpopulations leads to a deficiency of heterozygotes (relative to Hardy-Weinberg expectations) in these subpopulations due to inbreeding  and thusp within and p between of the two subspecies of each species , we compared the heterozygous alleles (SNPs) of two individuals of the same subspecies and the SNPs of two individuals of different subspecies by computing a FST-like statistic  (To assess the ex: GDI) . In factp within A) and the total polymorphism of the two individuals (p between A) was estimated to control that no genetic structure was observed in the Southern subspecies. Then, a global GDI comparing the private polymorphisms of individuals from the two populations (p within AB) and the total polymorphism of the species  was estimated with one individual from each population  were aligned with their reference genome using BWA-MEM . BAM filpulation . FinallyCanis lupus / Canis aureus  the two species had to be as closely related as possible, (2) they had both reference genomes and short reads available, (3) their estimated coverage for the two species had to be greater than 15x, and (4) short-read sequencing data had to be available for two individuals for one species of the pair. Given that, four species pairs were selected: (1) Ursus maritimus/Ursus arctos, for which sequencing data were available for 10 individuals of each species, genetic differentiation indexes were estimated using all possible combinations, using either two individuals for Ursus arctos or one individual for each species (i.e. 45 Ursus arctos/Ursus arctos and 100 Ursus arctos/Ursus maritimus). Given the number of possible combinations, estimates were performed on only five replicates (instead of 10) of 100 regions of 100,000 bp for each combination  (https://github.com/lh3/psmc).Historical demographic variations in effective population size were estimated using the Pairwise Sequentially Markovian Coalescent (PSMC) model implemented in the software PSMC (h3/psmc) . As desch3/psmc)  and genoh3/psmc)  for the h3/psmc)  with a bOtocyon megalotis. We chose to present the results obtained using the parameters -t15 -r4 -p ‘4+10*3+4’. For this parameter setting, the variance in ancestral effective population size was estimated by bootstrapping the scaffolds 100 times. To scale PSMC results, based on several previous studies on large mammals, a mutation rate of 10−8 mutation/site/generation (https://doi.org/10.5061/dryad.0618v/4)   modifed 0618v/4)  and cowp0618v/4) .https://www.dnazoo.org), and the OrthoMaM database (https://www.dnazoo.org/post/the-first-million-genes-are-the-hardest-to-make-r). In the absence of available transcriptomic data, this method leveraged the power of homology combined with the thorough knowledge accumulated on the gene content of mammalian genomes. As advised, a mammal-specific subset of UniProtKB/Swiss-Prot, a manually annotated, non-redundant protein sequence database, was used as a reference for this annotation step (P. c. cristatus) were used to assemble those of the Eastern aardwolf  by mapping the resequenced Illumina reads using BWA-MEM . This ensures our orthology predictions for the newly annotated CDSs to be robust. Then, the cleaning procedure of the OrthoMaM database was applied to the set of orthologous genes obtained. This process, implemented in a singularity image (OMM_MACSE.sif (PhylteR (https://github.com/damiendevienne/phylter). This software allows detection and removal of outliers in phylogenomic datasets by iteratively removing taxa in genes and optimising a concordance score between individual distance matrices.Orthologous genes were extracted following the orthology delineation process of the OrthoMaM database (OMM) . First, ty image  named OMACSE.sif , is compACSE.sif , refininACSE.sif , cleaninACSE.sif . FinallyACSE.sif  with thePhylogenomic analyses were performed using maximum likelihood (ML) using IQ-TREE 1.6.8  on the szenodo.org (DOI: 10.5281/zenodo.4479226).Genome assemblies, associated Illumina and Nanopore sequence reads, and mitogenomes have been submitted to the National Center for Biotechnology Information (NCBI) and will be available after publication under BioProject number PRJNA681015. The full analytical pipeline, phylogenetic datasets (mitogenomic and genomic), corresponding trees, and other supplementary materials are available from  In the interests of transparency, eLife publishes the most substantive revision requests and the accompanying author responses.Acceptance summary:Otocyon megalotis) and aardwolf (Proteles cristatus) subspecies from Eastern and Southern Africa. Their novel “genetic differentiation index” (GDi) analysis in particular is thoughtfully done, with the resulting having implications for applied conservation work. In the process, the paper emphasizes roadkill as a potentially valuable resource for genomic survey studies.Allio et al. provide a conservation genomics, demographic history, and phylogenomic analysis of bat-eared fox . First, because many researchers have temporarily lost access to the labs, we will give authors as much time as they need to submit revised manuscripts. I believe that the reviews will be automatically uploaded to bioRxiv as part of the preprint review process. In addition, if you choose, you may update your bioRxiv submission with this decision letter and a formal designation that the manuscript is "in revision at eLife. However, we felt that the approximately equal balance at present between the roadkill genomics assembly pipeline and the phylogenetic and genetic diversity results was not justified, and we request an shift accordingly as described below. Second, we require several analytical updates to the manuscript to ensure robustness of the main genetic diversity results. Following the overview list of essential revisions, please find the full individual reviews that contain corresponding details along with additional individual comments for your consideration during the revision process.Collectively, we liked a lot about your paper and we would accordingly like to encourage its continued evolution for further consideration at Essential revisions:1) Please rebalance the paper (and your approach to it) to focus disproportionately heavily on your analytical results , with de-emphasis on the roadkill genome assembly pipeline results. In brief, we ultimately considered the roadkill parts as a valuable bonus rather than a technical feat. In slightly more detail, we were not surprised by the quality of the assemblies from these  samples. We also did not feel that the assembly methods or results were out ahead of the field. We had also envisioned a roadkill population sample size based on the setup of the manuscript. We do not wish for the promise of roadkill sampling to be removed entirely from the paper. Rather, some of those results would be better presented as methods. Also, as the possibility of expanded roadkill sampling is presented, there are some discussion points that we would like you to consider .2) We require additional analyses to help affirm the robustness of your genetic differentiation estimate. First, please use a permuted subsampling approach, drawing from a larger dataset (e.g. with different species with two pops of n=20 genomes each available), to show consistency down to the sample sizes analyzed in the present paper. Second, please subsample your read data to precisely match sequence coverage distributions across species. You may also want to consider creating a subset of length-matched contigs across the different species, in a confirmatory analyses. In our own experiences these variables can make large differences in results.Reviewer #1:The manuscript by Allio et al. tries to justify that roadkill can be a useful source for genomic sequencing and even genome assembly level data. The authors cover all aspects of using this resource, from a new protocol to extract DNA, through generating a hybrid short- and long-read genome assembly and to various applications, showing that this data can be used in phylogenomic and population genomic analyses. Although I think that the manuscript is useful in highlighting how this resource can be analysed, it covers a lot of different topics and covers them in varying depth, which makes it difficult to follow and understand the real importance of the different sections.– Overall, this manuscript left me a bit confused about what is the main scope. It covers a lot of different topics from the laboratory-end of the spectrum, e.g. protocol used to get good DNA out of roadkills and how to assemble these genomes with a hybrid genome assembly, and crossing into a phylogenomic analyses making taxonomic suggestions and an analyses of the complete carnivora group, plus a demographic analyses showing the changes of population size over time.I was left with an impression that the authors tried to cover a lot of different topics but did not go deep enough in any of those. As a consequence, the Results section ends up sounding somewhat shallow, while the Discussion takes up a lot of space.What I would suggest if this manuscript is indeed to serve as a roadmap to roadkill genomics, is to add a figure showing the pipeline and then adjust the structure of the manuscript accordingly. For example, one box in the figure would correspond to one heading in the Results/Materials and methods, where the DNA analyses is explained – reasoning why a special protocol is needed, what is the main difference to existing methods, how does the yield compare to other methods, etc.And then the different topics explored in this manuscript could be shown as different example of the application – taxonomic questions on intra-/inter-species level, higher level taxonomic analyses (of the whole Carnivora), population genomic analyses, etc. Highlighting this as examples of the potential use of the roadkill genomes would make it understandable why is this paper trying to cover aardwolf and bat-eared fox genomics from so many ends.– Even though showing that roadkill samples can be useful for analysing particularly species for which obtaining samples is difficult in other way, I'm missing a discussion of how difficult it is to obtain roadkill samples and what are the ramifications. Can this approach be generally applied due to legislation reasons, do you need permits, do you find enough roadkill to rely on this source or do you only see it as an opportunistic sampling scheme?– Genome assembly is not exactly my field of expertise; therefore, I would like the authors to better explain how is their hybrid, short- and long-read genome assembly approach novel. My impression was that such hybrid assemblies are now a rather common and well-established practice. But a lot of space is dedicated to explaining this topic in the Introduction and again in the Discussion, which to me is something obvious and reads more like a review than a research article. But maybe I'm missing something obvious here, in which case I'd like the authors to make it clearer.Reviewer #2:This manuscript from Allio is an interesting mix of approach demonstration (population genomic sampling via roadkill) and application . There are some valuable results from the application component of the paper. In particular, I appreciate the comparative approach for studying patterns of intra- vs. inter-species genetic diversity. However, there is some rework to fully normalize those comparisons, that I feel is required.I would suggest the authors be more immediately forthcoming about the sizes of their samples, and perhaps consider changes to the introductory text to avoid giving any mis-impressions to readers about what data are ultimately presented in the manuscript. I had envisioned more of a landscape genetics-level sample and analyses, rather than n=3 individuals per each of the two species. Furthermore, while I think the reporting of the genome assembly qualities is important from confirmatory and quality control perspectives, and while presenting the new assemblies, in my view this shouldn't be set up to be a surprising result. These are very high-quality DNA samples, so we expect to be able to achieve DNA assembly qualities to whatever the invested level using current best-practices data generation and analytical methods.On the general genetic diversity and taxonomic questions, from my own experience I know that genetic differentiation metrics are not necessarily precisely comparable between a new study based on genome sequence data and an existing published dataset. Sample size affects false positive and false negative SNP calling error rates and sequence coverage and the variation among samples can also make a difference. Thus, especially since this leads to a key result/conclusion (i.e. that the two subspecies of aardwolf may deserve species status), it isn't sufficient that "similar individual sampling was available" for the carnivoran comparative datasets. The datasets should be equalized with sample number and individual sequence coverage (using downsampling) and then SNPs re-called using the same approach, before making the comparison. From the Materials and methods it wasn't clear to me the extent to which this all was done. It does appear that the same number of samples were used, and that the SNP calling approach was likely re-done from the read data . However, it doesn't appear that the sequence read data were subsampled for equivalency across the samples, which should be incorporated. Hopefully the results are similar, but there can be big changes that affect interpretation, so a careful approach is required.The study design and propose expanded use of roadkill samples in population genomics led me to think of this study, one of my all-time favorites: Brown and Bomberger Brown, 2013, Where has all the road kill gone?, Current Biology. For the present study, the question of potential biases in the sample for similar or related reasons is beyond the scope of investigation; this is not relevant for the sample sizes collected and analyses conducted. However, the importance of keeping this possibility in mind should at least be noted given the more expansive promotion of the wider inclusion of roadkill samples in population genomic studies. E.g. could the sample be biased towards individuals with genetically-mediated and/or culturally learned behavioral tolerance of human-disturbed habitats, etc., rather than a truly random sample representative of the overall landscape.In the Materials and methods section, the collection process and permits for the four samples from South Africa are described in detail. . However, the same information is not provided for the two East African samples that were included in the study . Please provide these details or expanded explanation.Reviewer #4:The manuscript "High-quality carnivore genomes from roadkill samples enable species delimitation in aardwolf and bat-eared fox" is mostly well written and demonstrates an interesting and useful method for sequencing genomes from low-quality samples. They also provide a comprehensive overview of the state of genomics across the Carnivora clade, with some improved species/subspecies designations. I think the work is of broad interest. The analyses are mostly clear and I think a few additional analyses and small improvements could be made prior to publication, but otherwise have no issues.The additional analyses/clarification I would recommend regards the Genetic differentiation estimate: This is a really interesting statistic! For some of the species you have multiple individuals it seems? Can you explain this a little more in the text. I am just not entirely convinced that the statistic is robust, but I think would be with a few more analyses. My concern is primarily due to having only two individuals in some of your comparisons, because of population structure/relatedness the random regions you sample could have correlated histories. I think this could be addressed by varying window sizes and replicates across comparisons where you have multiple individuals for both the intraspecific and interspecific calculations. Collectively, we liked a lot about your paper and we would accordingly like to encourage its continued evolution for further consideration at eLife. However, we felt that the approximately equal balance at present between the roadkill genomics assembly pipeline and the phylogenetic and genetic diversity results was not justified, and we request an shift accordingly as described below. Second, we require several analytical updates to the manuscript to ensure robustness of the main genetic diversity results. Following the overview list of essential revisions, please find the full individual reviews that contain corresponding details along with additional individual comments for your consideration during the revision process.eLife. In line with your editorial suggestion, we did our best to improve the balance of our manuscript by now focusing on our genetic diversity, demographic history, and phylogenomic results without losing clarity. Also, we found the reviewers’ methodological comments really constructive and performed the requested additional analyses accordingly. Finally, we also added a preliminary morphological comparison between the two potentially distinct aardwolf species  to further discuss our proposed taxonomic change.Thank you for the opportunity to continue to be considered to be published in Essential revisions:1) Please rebalance the paper (and your approach to it) to focus disproportionately heavily on your analytical results , with de-emphasis on the roadkill genome assembly pipeline results. In brief, we ultimately considered the roadkill parts as a valuable bonus rather than a technical feat. In slightly more detail, we were not surprised by the quality of the assemblies from these  samples. We also did not feel that the assembly methods or results were out ahead of the field. We had also envisioned a roadkill population sample size based on the setup of the manuscript. We do not wish for the promise of roadkill sampling to be removed entirely from the paper. Rather, some of those results would be better presented as methods. Also, as the possibility of expanded roadkill sampling is presented, there are some discussion points that we would like you to consider .We did our best to rebalance the manuscript towards its biological side by focusing on the genetic diversity, demographic history, and phylogenomic results without losing clarity. To do so, we (1) significantly reduced the description of the comparison of our genomes to the available mammalian and carnivoran genome assemblies, (2) moved the corresponding Figures 3 and 4 to Appendix 1—figures 2 and 3, and (3) deleted an entire Discussion paragraph on long-read sequencing and the hybrid-assembly strategy.2) We require additional analyses to help affirm the robustness of your genetic differentiation estimate. First, please use a permuted subsampling approach, drawing from a larger dataset (e.g. with different species with two pops of n=20 genomes each available), to show consistency down to the sample sizes analyzed in the present paper. Second, please subsample your read data to precisely match sequence coverage distributions across species. You may also want to consider creating a subset of length-matched contigs across the different species, in a confirmatory analyses. In our own experiences these variables can make large differences in results.To confirm the robustness of our genetic differentiation statistics, we performed the two requested additional analyses. Firstly, we subsampled the reads of each individual for each species to obtain homogeneous coverage (15x) among all individuals considered in the study. We then re-estimated the genetic differentiation index (GDI) for each group comparison and obtained almost identical values. This shows that the results of our analysis are not affected by heterogeneity in depth of coverage among individuals .Ursus arctos/Ursus maritimus, for which ~10 individual replicates per species with similar depth-of-coverage (~15x) were available from SRA, we estimated the GDI for each pair of individuals and found that variation among individuals did not affect the GDI values estimated both within and between species . Interestingly, we recovered the described subspecies of Ursus arctos with values of GDI ranging between 0.2 and 0.3 for comparisons between European and North American individuals, or between an individual from Montana and individuals from Alaska. Some variation was observed between individuals from Alaska, but many putative subspecies are present in this region . Importantly, all comparisons between the brown bear and the polar bear led to high GDI (~0.6) without much variation between the different individuals. These results show that randomly picking only three individuals is sufficient to accurately estimate the level of genetic differentiation between the two bear species.Secondly, for the pair Reviewer #1:The manuscript by Allio et al. tries to justify that roadkill can be a useful source for genomic sequencing and even genome assembly level data. The authors cover all aspects of using this resource, from a new protocol to extract DNA, through generating a hybrid short- and long-read genome assembly and to various applications, showing that this data can be used in phylogenomic and population genomic analyses. Although I think that the manuscript is useful in highlighting how this resource can be analysed, it covers a lot of different topics and covers them in varying depth, which makes it difficult to follow and understand the real importance of the different sections.Thank you for your constructive comments and helpful feedback. The revised manuscript now focuses more on the speciation observed between the two populations of aardwolves and less on the methodology used to generate high-quality genomes from roadkill samples.– Overall, this manuscript left me a bit confused about what is the main scope. It covers a lot of different topics from the laboratory-end of the spectrum, e.g. protocol used to get good DNA out of roadkills and how to assemble these genomes with a hybrid genome assembly, and crossing into a phylogenomic analyses making taxonomic suggestions and an analyses of the complete carnivora group, plus a demographic analyses showing the changes of population size over time.I was left with an impression that the authors tried to cover a lot of different topics but did not go deep enough in any of those. As a consequence, the Results section ends up sounding somewhat shallow, while the Discussion takes up a lot of space.What I would suggest if this manuscript is indeed to serve as a roadmap to roadkill genomics, is to add a figure showing the pipeline and then adjust the structure of the manuscript accordingly. For example, one box in the figure would correspond to one heading in the Results/Materials and methods, where the DNA analyses is explained – reasoning why a special protocol is needed, what is the main difference to existing methods, how does the yield compare to other methods, etc.And then the different topics explored in this manuscript could be shown as different example of the application – taxonomic questions on intra-/inter-species level, higher level taxonomic analyses (of the whole Carnivora), population genomic analyses, etc. Highlighting this as examples of the potential use of the roadkill genomes would make it understandable why is this paper trying to cover aardwolf and bat-eared fox genomics from so many ends.In accordance with the Editor's request, we have now rebalanced the manuscript to focus more on population genetic and phylogenomic aspects of the study (see above). We hope it is now less confusing.– Even though showing that roadkill samples can be useful for analysing particularly species for which obtaining samples is difficult in other way, I'm missing a discussion of how difficult it is to obtain roadkill samples and what are the ramifications. Can this approach be generally applied due to legislation reasons, do you need permits, do you find enough roadkill to rely on this source or do you only see it as an opportunistic sampling scheme?Thank you for this interesting comment. There are actually a number of ongoing projects surveying roadkill for ecological and population monitoring in mammals. Despite this growing interest, roadkill are still rarely used in population genomic studies, whereas they are frequently encountered in animal tissue collections of natural history museums. Our roadkill samples were actually opportunistically sampled while commuting between natural reserves in the Free State (South Africa) under permits issued by the local authorities and deposited in the National Museum Bloemfontein . Of course, roadkill samples are not exempt from legislation, but coordinating with ongoing monitoring and citizen-science projects might help implementing large-scale sampling, if needed. We added two sentences to the Discussion section to address this point.– Genome assembly is not exactly my field of expertise; therefore, I would like the authors to better explain how is their hybrid, short- and long-read genome assembly approach novel. My impression was that such hybrid assemblies are now a rather common and well-established practice. But a lot of space is dedicated to explaining this topic in the Introduction and again in the Discussion, which to me is something obvious and reads more like a review than a research article. But maybe I'm missing something obvious here, in which case I'd like the authors to make it clearer.Using a hybrid assembly strategy is indeed becoming more and more usual. Our intention was to illustrate that this strategy is particularly suitable for roadkill samples, from which it can be difficult to obtain DNA of sufficient quality for long-read sequencing at high depth of coverage. However, given that the manuscript covers several topics, we have now refocused the manuscript on the population genetics and phylogenomic aspects of the study. The methodological aspects have been significantly reduced in both the Introduction and Discussion sections as suggested.Reviewer #2:This manuscript from Allio is an interesting mix of approach demonstration (population genomic sampling via roadkill) and application . There are some valuable results from the application component of the paper. In particular, I appreciate the comparative approach for studying patterns of intra- vs. inter-species genetic diversity. However, there is some rework to fully normalize those comparisons, that I feel is required.I would suggest the authors be more immediately forthcoming about the sizes of their samples, and perhaps consider changes to the introductory text to avoid giving any mis-impressions to readers about what data are ultimately presented in the manuscript. I had envisioned more of a landscape genetics-level sample and analyses, rather than n=3 individuals per each of the two species.In the new version of the manuscript, we now specify that only 3 individuals for each pair of species or subspecies were used and show that it is sufficient to accurately estimate the genetic differentiation between these populations.Furthermore, while I think the reporting of the genome assembly qualities is important from confirmatory and quality control perspectives, and while presenting the new assemblies, in my view this shouldn't be set up to be a surprising result. These are very high-quality DNA samples, so we expect to be able to achieve DNA assembly qualities to whatever the invested level using current best-practices data generation and analytical methods.We respectfully disagree with this point. The DNA of most roadkill samples is actually not of sufficient quality and purity for long read sequencing and for de novo assembly using only long reads. Our first attempts using the Oxford Nanopore MinION instrument were far from being optimal both in terms of read length and sequencing yield. That's the reason why we designed the optimized protocol to extract roadkill DNA that could be efficiently sequenced. We were indeed quite surprised by the quality of the assemblies obtained with the hybrid assembly approach and we hope our results will encourage the use of roadkill as an underexploited resource in genomics.On the general genetic diversity and taxonomic questions, from my own experience I know that genetic differentiation metrics are not necessarily precisely comparable between a new study based on genome sequence data and an existing published dataset. Sample size affects false positive and false negative SNP calling error rates and sequence coverage and the variation among samples can also make a difference. Thus, especially since this leads to a key result/conclusion (i.e. that the two subspecies of aardwolf may deserve species status), it isn't sufficient that "similar individual sampling was available" for the carnivoran comparative datasets. The datasets should be equalized with sample number and individual sequence coverage (using downsampling) and then SNPs re-called using the same approach, before making the comparison. From the Materials and methods it wasn't clear to me the extent to which this all was done. It does appear that the same number of samples were used, and that the SNP calling approach was likely re-done from the read data . However, it doesn't appear that the sequence read data were subsampled for equivalency across the samples, which should be incorporated. Hopefully the results are similar, but there can be big changes that affect interpretation, so a careful approach is required.Thanks for raising this important point. First, we would like to confirm that we have indeed applied the same SNP calling approach to all comparisons. Briefly, we used N=3 individuals, starting from the raw reads and then, i) cleaning with fastp, ii) mapping with BWA and iii) genotype calling with FreeBayes . As suggested, we now made the description of the method more explicit in the main text. However, as rightly pointed out, in the first version we haven’t controlled for potential variation in coverage between comparisons, which was rather extensive (from 15 to >80X). To control for this parameter, we followed your advice and randomly down-sampled the reads of each individual to obtain an homogeneous coverage among individual comparisons (~15X). We then re-estimated the genetic differentiation index (GDI) for each group and found that the results remain basically unchanged.Ursus arctos/Ursus maritimus, for which we found ~10 replicates per species with similar depth of coverage (~15x) available in SRA, we estimated the GDI for each pair of individuals. We found no variation among individuals , demonstrating that randomly selecting only three individuals is sufficient to accurately estimate the level of genetic differentiation between these two bear species. Our approach even allowed us to retrieve differences between described brown bear subspecies .Next, we carried out a second additional analysis to control for the variation among sampled individuals. For the pair The study design and propose expanded use of roadkill samples in population genomics led me to think of this study, one of my all-time favorites: Brown and Bomberger Brown, 2013, Where has all the road kill gone?, Current Biology. For the present study, the question of potential biases in the sample for similar or related reasons is beyond the scope of investigation; this is not relevant for the sample sizes collected and analyses conducted. However, the importance of keeping this possibility in mind should at least be noted given the more expansive promotion of the wider inclusion of roadkill samples in population genomic studies. E.g. could the sample be biased towards individuals with genetically-mediated and/or culturally learned behavioral tolerance of human-disturbed habitats, etc., rather than a truly random sample representative of the overall landscape.We agree with this point that was indeed overlooked in the first version of our manuscript. We have included the suggested reference in the Discussion section to insist on the potential non-representativeness of roadkill samples for population genomic studies but also on their usefulness for generating reference genomes and species delimitation in non-model species.In the Materials and methods section, the collection process and permits for the four samples from South Africa are described in detail. . However, the same information is not provided for the two East African samples that were included in the study . Please provide these details or expanded explanation.We now mention the IUCN status of the two species and specify that CITES permits were not required to transfer the samples to France. We also added the information on the additional samples provided by museums in the same main “Biological samples” section.Reviewer #4:The manuscript "High-quality carnivore genomes from roadkill samples enable species delimitation in aardwolf and bat-eared fox" is mostly well written and demonstrates an interesting and useful method for sequencing genomes from low-quality samples. They also provide a comprehensive overview of the state of genomics across the Carnivora clade, with some improved species/subspecies designations. I think the work is of broad interest. The analyses are mostly clear and I think a few additional analyses and small improvements could be made prior to publication, but otherwise have no issues.The additional analyses/clarification I would recommend regards the Genetic differentiation estimate: This is a really interesting statistic! For some of the species you have multiple individuals it seems? Can you explain this a little more in the text. I am just not entirely convinced that the statistic is robust, but I think would be with a few more analyses. My concern is primarily due to having only two individuals in some of your comparisons, because of population structure/relatedness the random regions you sample could have correlated histories. I think this could be addressed by varying window sizes and replicates across comparisons where you have multiple individuals for both the intraspecific and interspecific calculations.Ursus arctos/Ursus maritimus for which we ~10 replicates per species could be performed, we estimated the GDI for each pair of individuals, and demonstrated that randomly selecting only three individuals (out of 10) is sufficient to assess genetic differentiation between the two species. Finally, in these computations, the randomly selected genomic regions were different from the regions originally used in the manuscript. Hence, 100 additional replicates were estimated and we found the same results for the differentiation between the two bear species.Indeed, the random regions that we sampled could have correlated histories and that’s why we used large regions (100 Kb) and 100 replicates (10x10). Given that the variance in the estimates obtained is relatively low, we are confident that the effect of using one or another region has no significant effect in our case. Additionally, as requested by several comments in this reviewing round, we decided to test the robustness of our genetic differentiation index to the random sampling of 3 individuals. To do so, we selected the pair


Galičnik village is a population isolate located in the northwest region of the Republic of North Macedonia, established around the 10th century. Alport syndrome-linked nephropathy with a complex inheritance pattern has been described historically among individuals in the village. In order to determine the genetic basis of the nephropathies and to characterize the genetic structure of the population, 23 samples were genotyped using a custom-made next generation sequencing panel and 111 samples using population genetic markers. We compared the newly obtained population data with fifteen European population data sets. NGS analysis revealed four different mutations in three different collagen genes in twelve individuals within the Galičnik population. The genetic isolation and small effective population size of Galičnik village have resulted in a high level of genomic homogeneity, with domination of R1a-M458 and R1b-U106* haplogroups. The study explains complex autosomal  Studying population isolates in the context of genetic and phenotypic variation can provide a unique insight into genetic differentiation of isolated populations and phenotypic expressions, especially when phenotypically important variants arise either uniquely within that population or begin to exhibit frequency differences across populations. The genetic and phenotypic differentiations between and within populations are often complex and can be the result of a combination of various population effects, such as isolation, selection, migration, bottleneck, adaptation, and genetic drift. Over time, all these effects shape the population genetic structure, making it more homogenous internally and more differentiated from neighboring populations ,2,3,4.COL4A3, COL4A4, and COL4A5, which affect the synthesis, assembly, deposition, or function of the collagen IV alpha3, alpha4, and alpha5 molecules. Collagen molecules are the major collagenous constituent of mature mammalian glomerular basement membrane (GBM) [COL4A5 gene and are the cause of X-linked Alport syndrome (XLAS) (OMIM301050), a semi-dominantly inherited renal disease. XLAS is clinically characterized by severely affected males with persistent hematuria, proteinuria, and commonly hearing loss and ocular anomalies, leading to end-stage renal disease (ESRD), usually during the second or third decade. Females usually have a milder phenotype, with only urinary abnormalities [COL4A3 and COL4A4 genes are the cause of autosomal recessive Alport syndrome (ARAS) (OMIM203780), with symptoms similar to those in male XLAS patients and autosomal dominant thin basement membrane disease, with a varying but usually milder phenotype [COL4A3, COL4A4, or COL4A5 genes, has recently been described, simulating autosomal recessive inheritance (digenic mutations in trans) or autosomal dominant inheritance (mutations in in cis mode) [Galičnik is an isolated mountainous village in the northwest region of the Republic of North Macedonia . It is one (GBM) ,7. The mmalities . Mutatiohenotype ,9,10. Gehenotype . A new fis mode) . The aim of this study was (i) to determine the genetic basis of the nephropathies found among individuals in the Galičnik population, (ii) to assess the influence of population isolation on the genetic structure and inheritance pattern of nephropathies in the Galičnik population, and (iii) to develop a detailed characterization of the genetic structure of the Galičnik population using genetic markers.Overall, 111 saliva samples were collected from North Macedonian individuals with a paternal and/or maternal origin from Galičnik village. Informed consent for genetic analysis was obtained from every individual participating in the study. No biopsy tissue nor biopsy results were available. Saliva samples were collected in Oragene-DNA tubes  and genomic DNA was isolated using a QIAamp DNA midi kit . The quantity and quality of DNA samples were determined using a NanoDrop ND-1000  spectrophotometer. Galičnik samples were subsequently merged with population data from available sources ,28,29,30COL4A3, COL4A4, and COL4A5 mutations, an AmpliSeq custom-made panel was developed using Ion AmpliSeq designer software (Thermo Fisher Scientific). The assay amplifies all coding exons and flanking regions of the three collagen genes (192 amplicons covering 153 coding exons and flanking regions) in a two-tube multiplex PCR reaction. The final multiplex PCR products were pooled together according to the manufacturer’s instructions and used to prepare a barcoded library suitable for use with an Ion S5 sequencer (Thermo Fisher Scientific). Torrent Suite 2.2 (Thermo Fisher Scientific) software was used to map and align the sequences to the reference sequence . Variants were detected using Ion Reporter software (Thermo Fisher Scientific) using a custom Ion Reporter filter chain (5000 Exomes and location filter). All filtered variations were visualized and manually inspected using the IGV tool [For the detection of IGV tool ,32, and IGV tool . The patIGV tool . The folhttp://www.isogg.org/tree/). The following set of markers was examined: M215, M78, P15, M198, M434, M458, M334, M343, M269, L23, M412, L11, S116, U152, M126, and U106. The biallelic markers were analyzed using high-resolution melt (HRM) analysis, as described previously [For the purposes of Y-chromosome analysis, 44 unrelated male samples were obtained from the Galičnik data set. A total of 16 Y-chromosome biallelic markers were analyzed, following the genealogical hierarchy and considering the recommendations of the Y Chromosome Consortium  and the eviously . PCR ampAn AmpFlSTR Yfiler PCR Amplification Kit (Thermo Fisher Scientific) was employed to amplify 17 Y-STR loci  in a single PCR step, according to the manufacturer’s recommendations. The obtained PCR products were loaded onto a SeqStudio capillary sequencer (Thermo Fisher Scientific) and analyzed using GeneMapper 5 software (Thermo Fisher Scientific).Hypervariable regions I and II  were amplified via PCR, purified, and analyzed through sequencing on a SeqStudio capillary sequencer, in combination with BigDye Terminator v.1.1 chemistry (Thermo Fisher Scientific). Specific haplogroups were determined on the basis of differences from the Cambridge Reference Sequence (rCRS) associated with major Eurasian lineages, and considering the Global Human Mitochondrial DNA (mtDNA) Phylogenetic Tree. http://www.fluxus-engineering.com/). The networks were calculated using the median-joining method, with e set to zero, and microsatellite loci weighted according to the estimated variance. To visualize the genetic relationships among populations, principal component analysis (PCA) was performed based on the raw frequency data for major haplogroups, using XLSTAT 2018.7 software . Microsatellite-based genetic differences between populations were calculated through analysis of molecular variance (AMOVA) and Rst distance matrices, using Arlequin 3.5 software . The calCOL4A3 gene, resulting in a novel in-frame deletion of three amino acids . The second mutation was detected in exon 13 of the COL4A4 gene, resulting in a glycine substitution within the Gly-X-Y triple helical domain , the third was detected in exon 20 of the COL4A4 gene, resulting in a large 53 nucleotide deletion (c.1321_1369 + 3del), and the fourth mutation was detected in exon 25 of the COL4A5 gene, resulting in a glycine substitution in the non-collagenous domain . Novel mutations were submitted to ClinVar . Among the four above-mentioned mutations, three were detected within a single family  analysis of the collagen genes was performed on affected individuals and their family members to assess the genetic cause of nephropathy. All together, twenty-three individuals of the Galičnik population were genotyped for collagen gene mutations. The analysis revealed four different heterozygous mutations in twelve individuals (10.7%) affecting autosomal chromosome 2 and sex chromosome X. The first mutation was detected in exon 38 of the e family . Segrega  belonged to haplogroup R1a1a1b1a1 (M458), with the second most common haplogroup being R1b1a1a2 , which further divides into R1b1a1a2a1a1  and R1b1a1a2a1a* . The remaining individuals belonged to haplogroup G2a  or haplogroup E1b1b .To visualize the genetic relationships between populations, we performed principal component analysis on the basis of raw frequencies of biallelic markers of 1824 individuals from 14 European populations . The firRelationships between populations were also determined by calculating a pairwise Rst matrix. A heatmap , based oGenetic relationships among the 15 populations were further investigated on the basis of Y-STR markers, encompassing 3891 individuals. To visualize genetic differences among populations, an Rst pairwise matrix was constructed and multidimensional scaling (MDS) analysis was performed . The firTo investigate further the haplotype structure within the R1a1a (M198) haplogroup, a median-joining network was constructed , based oThe most common haplogroup detected in the Galičnik population was haplogroup H (28.4%). Further division of haplogroup H revealed four haplogroups in the Galičnik population, with H11 having the highest frequency. Samples that could not be assigned to any of the specific H haplogroups were designated H * haplogroup. The second and third most prevalent haplogroups in the Galičnik population were haplogroups U and N . The frequencies of other detected haplogroups in the Galičnik population are listed in Centuries of restricted gene flow and endogamy influence the patterns and prevalence of diseases, shaping phenotypes in specific patterns. With the combined effects of endogamy and genetic drift, isolates have been shown to potentially exhibit an increased incidence of recessive disorders . No geneCOL4A4 (p.Gly252Asp) and COL4A3 (p.Pro1103_Ser1105del) genes supports the hypothesis of two independent mutations, merged on the same chromosome through recombination events within the small isolated community. This hypothesis is additionally supported by the inheritance pattern, in which we detected only one of the two autosomal mutations in four of the family members , with the other mutation being lost through a recombination process during transmission from one generation to another. While the COL4A4 (p.Gly252Asp) mutation has already been described in the literature as a mutation linked to ARAS [COL4A3 (p.Pro1103_Ser1105del) and COL4A4 (c.1321_1369 + 3del) mutations were not previously described. We consider both mutations pathogenic, since they result in an in-frame deletion within the Gly-X-Y collagenous domain and a large deletion. Additionally, a similar in-frame deletion in close proximity has already been described in a 32-year-old woman with microhematuria, proteinuria, and short segments of thinning of the GBM and segmental glomerulosclerosis [in cis produces moderately expressed autosomal recessive Alport syndrome. Previous studies have shown that Alport patients with mutations in two different collagen genes usually display a more severe phenotype than those with a single mutation [COL4A4 (p.Gly252Asp)  developed benign family hematuria without the development of renal function impairment or hearing loss. In addition to the two detected mutations in autosomal chromosome 2, we also detected a mutation in sex chromosome X within the COL4A5 gene (p.Gly624Asp)  within the same family. Among tested individuals, only female carriers with the X-linked COL4A5 mutation (p.Gly624Asp) were detected . The COL4A5 (p.Gly624Asp) mutation in female cases was manifested by the development of early childhood hematuria with normal hearing, which is consistent with X-linked Alport syndrome in females. The COL4A5 (p.Gly624Asp) mutation has previously been described in different populations [COL4A5 (p.Gly624Asp) mutation is located in the short 12th non-collagenous conserved interruption in exon 25. These interruptions are thought to give natural flexibility to the collagenous structures, and mutations within that region usually cause milder phenotypes than mutations in the Gly-X-Y domain. However, all cases presented in this study carrying the COL4A5 (p.Gly624Asp) mutation exhibited a remarkably similar phenotype, suggesting modifier genes influencing the phenotype expression between different families as suggested in previous studies [COL4A5 (p.Gly624Asp) and COL4A3 (p.Pro1103_Ser1105del) mutations (case IV/2) than in COL4A5 (p.Gly624Asp)-only mutation carriers. Interestingly, this was not observed in this case, since at the age of 71 only hematuria has been detected, with no hearing loss or ocular changes. Possible mosaicism and/or favorable modifier genes could explain the relatively mild phenotype in this digenic female carrier. Furthermore, a more profound effect of modifier genes in an isolated community is expected, since the modifier allele is more likely to be located on fewer haplotypic backgrounds in a more inbred population, with considerably lower numbers of haplotypes for a specific locus, thereby enhancing its influence. To determine further the complex interaction between disease-causing genes and their modifiers, a further genome-wide association study within Galičnik individuals should be performed.Our results clearly resolve the complex inheritance pattern for nephropathies in the Galičnik population, revealing four different pathogenic mutations in three different collagen genes. To the best of our knowledge, this is the first study in which three different collagen mutations in three different genes have been described within one family. This unique combination of mutations within different family members is probably a result of the genetic isolation of the community and possible endogamy. It seems that the segregation pattern of the two autosomal mutations in the  to ARAS , the COLclerosis . As showmutation . In our c.1321_139 + 3del ulations ,41, wher studies ,43,44. TY-STR and mtDNA analyses were performed to determine the degree of genetic variability within the Galičnik population. Analysis of genetic variability within the population based on a Y-STR Rst difference matrix  suggestsIn conclusion, this is the first study to describe an Alport syndrome family with three different collagen gene mutations within a highly homogenic population structure. The results of classical population genetic markers reflect historical migration and settlements in the Galičnik region.