Psammochloavillosa is an ecologically important desert grass that occurs in the Inner Mongolian Plateau where it is frequently the dominant species and is involved in sand stabilization and wind breaking. We sought to generate a preliminary demographic framework for P. villosa to support the future studies of this species, its conservation, and sustainable utilization. To accomplish this, we characterized the genetic diversity and structure of 210 individuals from 43 natural populations of P. villosa using amplified fragment length polymorphism (AFLP) markers. We obtained 1,728 well‐defined amplified bands from eight pairs of primers, of which 1,654 bands (95.7%) were polymorphic. Results obtained from the AFLPs suggested effective alleles among populations of 1.32, a Nei's standard genetic distance value of 0.206, a Shannon index of 0.332, a coefficient of gene differentiation (GST) of 0.469, and a gene flow parameter (Nm) of 0.576. All these values indicate that there is abundant genetic diversity in P. villosa, but limited gene flow. An analysis of molecular variance (AMOVA) showed that genetic variation mainly exists within populations (64.2%), and we found that the most genetically similar populations were often not geographically adjacent. Thus, this suggests that the mechanisms of gene flow are surprisingly complex in this species and may occur over long distances. In addition, we predicted the distribution dynamics of P. villosa based on the spatial distribution modeling and found that its range has contracted continuously since the last interglacial period. We speculate that dry, cold climates have been critical in determining the geographic distribution of P. villosa during the Quaternary period. Our study provides new insights into the population genetics and evolutionary history of P. villosa in the Inner Mongolian Plateau and provides a resource that can be used to design in situ conservation actions and prioritize sustainable utilization. Psammochloa villosa, but limited gene flow. 2. Within P. villosa, there is limited but noteworthy geographic structuring of populations, of which 64.2% show significant genetic variation. 3. The species experienced continuous range contraction since the last interglacial period, and the dry and cold climates were critical in determining the distribution of P. villosa during the Quaternary period.1. There is abundant genetic diversity in  The glaNitraria sphaerocarpa Maxim. (Nitrariaceae), and Xu and Zhang (Atraphaxis frutescens (L.) K. Koch (Polygonaceae).Quaternary climate change is known to have strongly affected the distributions of plants in Northern China   Bor, which was treated in a monotypic genus of tribe Stipeae in Poaceae. This species, commonly called sand whip, is a perennial rhizomatous herb that is primarily distributed in the desert grasslands of northwestern China, especially in the Inner Mongolian Plateau, the Hexi Corridor of Gansu, central and northern Ningxia, and Northern Shanxi   combined with ecological niche modeling (ENM) to compare past, present, and future environmentally suitable habitats for the species. We used AFLPs, which were multilocus markers, and their mode of inheritance was dominant, because they remained extremely efficient for investigating genetic diversity, genetic structure, and population demography due to their high levels of polymorphism, their reproducible, reliable results that were unaffected by the developmental stage of plant materials, and their universality among plant species  test whether historical genetic divergence occurred among populations in response to Quaternary climate oscillations, and (3) evaluate the abiotic factors that are most influential in driving the distributions of P. villosa through time. Moreover, because no assessment of the conservation needs of P. villosa had previously been accomplished, we performed a preliminary assessment based on extent of occurrence (EOO) with interpretation according to guidelines of the International Union for the Conservation of Nature (IUCN). We believe that, taken together, our results can provide a scientific basis for improved protection and sustainable utilization  of P. villosa within the fragile desert grassland ecosystems where the species occurs.In this study, we investigated the influence of aridification and climatic oscillations on the genetic structure and evolutionary processes of 22.1P. villosa in the field throughout its natural range in China and obtained a total of 210 individuals . We separated the fluorescently labeled fragments on an ABI PRISM 377 DNA Calibrator (Applied Biosystems) with an internal size standard, allowing visual inspection of all individual sites. As in Liu et al. , percentage of polymorphic loci (PPL), observed number of alleles (Na), effective number of alleles (Ne), Shannon's information index , expected heterozygosity (He), Nei's standard genetic distance (GD), total population diversity (Ht), genetic diversity within populations (Hs), genetic diversity between populations (Hb), and the population differentiation (FST). Meanwhile, we inferred the correlation between I and h, and I and He using spearman ranking in R 4.04 (http://www.r‐project.org/), and calculated the degree of genetic differentiation between populations (GST) as (Ht − Hs)/Ht /GST  using the Bayesian method in HICKORY v1.1  and determined the most suitable model based on the deviation information criterion (DIC)   ranging from one to ten. We applied 2 × 105 repetitions of the Markov chain Monte Carlo with a burn‐in of 25%. To determine the best value of K for the STRUCTURE analyses, we used the ΔK statistical method  juxtaposed with broader, regional patterns   to compare the potential distributions of P. villosa at the Last Inter‐Glacial , the Last Glacial Maximum , and the present. As input for the ENMs, we used the geocoordinates of the 43 populations of P. villosa that we sampled for this study as well as geocoordinates of specimens recorded in the Chinese Virtual Herbarium , the Global Biodiversity Information Facility (http://www.gbif.org), the China National Specimen Information Infrastructure (http://www.nsii.org.cn), and the Specimen Resources Sharing Platform for Education (http://mnh.scu.edu.cn/main.aspx). In total, after removing duplicate and ambiguous records, we obtained 155 georeferenced data points for using in the ENMs (Table In order to predict the effects of Quaternary climatic oscillations on the geographic distributions of Ms Table .www.worldclim.org) at 2.5 arc‐min resolution. This represented 22 total environmental variables for modeling. We followed Peterson and Nakazawa  as global information system (GIS) layers from the WorldClim database  of the receiver operating characteristic (ROC). The value of AUC ranges between 0 (randomness) and 1 (exact match), and values above 0.9 are generally regarded as indicating good model performance Swets, .p) based on the model results: highly suitable habitat (0.5 ≤ p ≤ 1.0), moderately suitable habitat (0.3 ≤ p < .5), poorly suited habitat (0.1 ≤ p < .3), and unsuitable habitat (0.0 ≤ p < .1). We performed projections based on all time periods: LIG, LGM, and the present. Additionally, in order to better assess the conservation needs of this species, we also projected the model into future times: the 2050s and 2070s. The data underlying the maps for future projections comprised inference of the effects of climate forcing factors (RCP8.5 and RCP2.6) according to the CCSM4 model  in ENMTools 1.3   Moat,  and follO) Moat, . EOO comO) Moat, . In the es IUCN, . Therefoes IUCN, .33.1P. villosa were all assigned correctly to the corresponding individual after amplification and scoring. The eight primer pairs yielded 1,728 clearly identifiable amplified bands, of which 1,654 (95.7%) were polymorphic (Table E‐ACG/M‐CTC) to 199 (E‐AGC/M‐CTG and E‐AAG/M‐CAC) with an average of 207. The highest rate of polymorphism for an individual primer was 99.1%, and the lowest was 92.1%. Overall, these eight primers showed high levels of polymorphism among individuals of P. villosa.The 43 populations of Na was 2.00 for each primer, while Ne ranged from 1.29 to 1.34 with an average of 1.32, h ranged from 0.19 to 0.21 with an average of 0.21, and I ranged from 0.32 to 0.34 with an average of 0.33. The primer pair E‐AGG/M‐CAC exhibited the highest diversity based on these indices, while E‐ACT/M‐CTT had the lowest. In general, each of eight primer pairs appeared to facilitate a robust assessment of genetic diversity in P. villosa.Our measurements of the genetic diversity indices based on the eight primer pairs revealed that average 3.2P. villosa showed that these populations could be assigned to two clusters that have high support (100% bootstrap support (BS), Figure K = 3)  Table . As with3) Table . HoweverHereafter, we refer to the two groups as Groups 1 and 2, which comprise P1‐12 and P13‐43, respectively. Populations of Group 1 occurred mainly in the central and eastern regions of the Inner Mongolian Plateau, while populations of Group 2 were distributed throughout the range of the species in China. Notably, the populations of Group 1 tended to be found at lower elevations compared to those of Group 2 Table .3.3Na), effective number of alleles (Ne), Shannon information index (I), Nei's genetic diversity (h), and expected heterozygosity (He) of 43 populations were from 25.7 to 54.8, 0.50 to 1.12, 1.19 to 1.38, 0.13 to 0.32, 0.10 to 0.22, and 0.13 to 0.22, respectively . In addition, we noted a strong correlation between I and h  and between I and He . Thus, hereafter, we use only h and He to discuss the genetic diversity of P. villosa.The percentage of polymorphic loci (PPL), observed number of alleles , genetic diversity within populations (Hs = 0.165), genetic diversity between populations (Hb = 0.035), the population differentiation , differentiation among populations (GST = 0.435), and historic gene flow (Nm = 0.661). Meanwhile, we found that the value of DIC for the Full model was the lowest, both the population level and group level (Table θB = 0.199) or Group2 (θB = 0.265) was lower than those of all populations (θB = 0.314). It was important to note that the genetic differentiation of Group2 was greater than that of Group1, which indicated that the genetic structure and genetic diversity of P. villosa would not be impacted by the consideration of HWE.Across all 43 populations of el Table , represeFST = 0.358, p < .001) than within populations (64.2%) , while most of genetic variation (56.1%) existed within populations . Overall, the genetic variation at the population‐ and local geographic‐scale was much higher than regionally in P. villosa. Additionally, the result of the neutrality test suggested the value of Tajima's D and Fu's Fs was positive, but nonsignificant for all populations of P. villosa  based on the 43 populations showed that the proportion of genetic variation among populations was lower   and a weak but significant positive correlation for Group 2 .The Mantel test revealed that there was a significant positive correlation between geographic distance and ) Figure . Similar3.4P. villosa yielded relatively high AUC, demonstrating reliable model performance , followed by temperature annual range (Bio 7) and precipitation of warmest quarter (Bio 18), whose contribution rates were 40.0%, 17.2%, and 16.7%, respectively   Figure . The nic44.1P. villosa (h = 0.21) and at the population level (h = 0.13). Compared to genetic diversity in other species of Poaceae assessed using AFLPs, genetic diversity in P. villosa was slightly lower than in Dactylis glomerata , Chascolytrum bulbosum (h = 0.10), and Leymus racemosus (h = 0.19)  Cai, , which aP. villosa frequently involves clonal reproduction via its rhizomes under harsh environmental conditions, although the species also reproduce sexually by seed following wind pollination   of 0.576. According to Wright's  and the Shilongmiao Ecological Station (two populations) and found greater genetic variation among populations. We suspected that the inconsistency between these studies and ours might be related to the numbers of populations and geographic location because population genetic structure arose from the interactions of the unique population‐ and species‐level processes  and large deserts in northwestern China  as well as range contraction and population fragmentation induced by climatic oscillations as also observed for Gymnocarpos przewalskii Maxim. and Helianthemum songaricum Schrenk . Based on this, extant populations of this species might originate from the genetic stock of Group 1, as geographic areas with both high genetic diversity and frequency of dominant genes usually represent centers of origins for source populations Vavilov, . HoweverP. villosa was the most extensive during the LIG period and included the northeast edge of the Qinghai‐Tibet Plateau, Tarim Basin, Tianshan Mountains, Inner Mongolia Plateau, and the western regions of DaXinggan Ling. The range became limited to the Inner Mongolia Plateau, Ordos Plateau, and the Yinshan‐Helanshan area during the LGM. The contraction of the range is likely the result of glaciation and climatic shifts within the Tianshan Mountains and Tarim Basin, where temperatures dropped significantly as glaciation developed on a large scale in the Northern Hemisphere during the early‐Middle Pleistocene , which occured in Northern China and adjacent desert areas of central Asia  based on EOO , habitat degradation may be an impending threat to the species and jeopardize its vital ecological role. Therefore, we advocate for continued ecological monitoring of this dominant, keystone desert grass.ion Cai, . After oPsammochloa villosa may have great potential for sustainable utilization as a forage plant for livestock. The sand whips have relatively long inflorescences with large spikes that make it suitable for forage. Moreover, its adaptations to drought may make this species a valuable source of genetic resources for molecular breeding of other crop and forage species as, presently, it is one of few forage species that can withstand the intensifying long‐term drought conditions in northwest China. Developing a sustainable use strategy for P. villosa will also help to ensure its continued availability as a keystone species within desert communities of the Inner Mongolian Plateau and adjacent areas.None declared.Ting Lv: Conceptualization ; data curation ; formal analysis ; investigation ; methodology (lead); writing‐original draft (lead); writing‐review & editing . AJ Harris: Conceptualization ; writing‐original draft (supporting); writing‐review & editing . Tao Liu: Formal analysis ; investigation ; methodology (supporting). Ruifang Liang: Data curation ; formal analysis ; methodology (supporting). Zilan Ma: Formal analysis ; investigation ; methodology (supporting). Yuping Liu: Conceptualization ; formal analysis ; funding acquisition (lead); methodology (supporting); writing‐review & editing . Xu Su: Conceptualization ; formal analysis ; investigation ; project administration (supporting); supervision (lead); writing‐original draft (supporting); writing‐review & editing .Fig S1Click here for additional data file.Fig S2Click here for additional data file.Table S1‐S5Click here for additional data file.Fig S1‐S2‐captionsClick here for additional data file.Supplementary File 1Click here for additional data file.


Small populations are often exposed to high inbreeding and mutational load that can increase the risk of extinction. The Sumatran rhinoceros was widespread in Southeast Asia, but is now restricted to small and isolated populations on Sumatra and Borneo, and most likely extinct on the Malay Peninsula. Here, we analyse 5 historical and 16 modern genomes from these populations to investigate the genomic consequences of the recent decline, such as increased inbreeding and mutational load. We find that the Malay Peninsula population experienced increased inbreeding shortly before extirpation, which possibly was accompanied by purging. The populations on Sumatra and Borneo instead show low inbreeding, but high mutational load. The currently small population sizes may thus in the near future lead to inbreeding depression. Moreover, we find little evidence for differences in local adaptation among populations, suggesting that future inbreeding depression could potentially be mitigated by assisted gene flow among populations. Highly endangered species like the Sumatran rhinoceros are at risk from inbreeding. Five historical and 16 modern genomes from across the species range show mutational load, but little evidence for local adaptation, suggesting that future inbreeding depression could be mitigated by assisted gene flow among populations. Over the past few decades, the role of genetic factors in the long-term viability of small populations has gained considerable attention3. A growing body of empirical studies on critically endangered species5 indicates that small populations are often exposed to genomic erosion, which reduces species viability via loss of genetic diversity, increase in inbreeding and in genetic load  through genetic drift8.Small and fragmented populations are vulnerable to several extrinsic and intrinsic threats, such as environmental effects , demographic stochasticity and detrimental genetic effects9. Predicting the degree of genomic erosion that threatened populations are exposed to is thus challenging, but has important implications for conservation, since quantifying levels of inbreeding and genetic load is crucial for developing management strategies aimed at mitigating the effects of genomic erosion9.The magnitude of these processes can vary among populations and species due to their different demographic histories , sensitivity to environmental changes or life-history traits. Moreover, population fitness and viability will also vary depending on the proportion of rare large-effect deleterious alleles and numerous small-effect deleterious alleles among the founding individuals of these populations10, contribute to breeding programmes by estimating relatedness among individuals and help identify the individuals most likely to lead to genetic rescue in translocation programmes11. Enhancing gene flow is considered a powerful conservation tool for reducing genomic erosion in a range of threatened species, because it can reduce the expression of recessive or partially-recessive deleterious alleles in hybrids of the receiving population12. There is empirical evidence for genetic rescue resulting in increased fitness, population growth, and increased heterozygosity in the first two or three hybrid generations16. Furthermore, while genomic data on the long-term effects of gene flow are currently limited, hybrid vigour can persist at least beyond the F3 generation and as far as the F16 generation20.Genetic data can, for instance, help define management units21. Thus, assisted gene flow among long-term isolated populations represents a risk of disrupting locally adapted gene complexes, a process referred to as outbreeding depression6. Previous work has highlighted factors likely to affect the risk of outbreeding depression, where adaptive differentiation has been identified as one of the major risk factors22. Indeed, concerns over potential disruption of local adaptation has been one of the main reasons why assisted gene flow has only rarely been used in conservation biology (~34 studies19).Populations that have evolved in isolation for thousands of generations may show evidence for positive selection and distinct allelic frequencies for genes under strong directional selection, which could indicate local adaptation23, they may also accumulate different levels of genetic load, and potentially carry private deleterious mutations that affect different genes. Consequently, gene flow from outbred populations into isolated populations could increase the genetic load of recipient populations and elevate their risk of extinction25. This is especially likely if the recipient population has purged a portion of its genetic load but remains small and inbred for several generations. Such a population will be vulnerable to the expression of deleterious alleles in homozygous state, and the effects of newly introduced deleterious alleles may not become apparent until several generations later26. In such situations, it could thus be preferable to avoid genetic rescue attempts or to select individuals with a lower genetic load from partially-inbred sources25. However, some have criticised this approach and argue that the benefits of genetic rescue  by far outweigh the risks of increase in genetic load27. It is therefore essential to weigh the positive and negative effects of this alternative approach when assessing the need for genetic rescue27.While populations can become locally adapted28. However, estimating genetic load is challenging without information on the fitness effects of deleterious mutations. An alternative approach is to estimate changes in mutational load , and to use it as a proxy for individual and population fitness. Determining individual inbreeding levels as well as mutational load can thus potentially be used to identify individuals particularly well suited for assisted gene flow.Recent advances in genomics have allowed the detection of genomic regions affected by natural selection and can also help identify genetic threats such as elevated inbreeding and genetic load in natural populationsDicerorhinus sumatrensis) is a browser that inhabits the rainforest of Southeast (SE) Asia and is currently listed as critically endangered by the International Union for Conservation of Nature (IUCN)29. Mitogenomic and genome-wide data indicate that periods of sea-level rise during the Pleistocene led to repeated isolation among populations31. A recent study using complete mitochondrial genomes estimated the divergence of the three main Sumatran rhinoceros populations at ~360 ka BP31 and additional substructure within the three main populations are roughly coinciding with the Toba super-eruption some 71 ka BP32, which may have restricted Sumatran rhinoceros populations to refugia after the eruption. At the end of the last glaciation, the species experienced a severe decline in effective population size (Ne), which may have eroded a large portion of its ancestral genetic diversity30.The Sumatran rhinoceros  and Borneo (D. s. harrissoni), whereas the Malay Peninsula (D. s. sumatrensis) population is most likely extinct39. Moreover, the species’ low breeding rate, in the wild due to low population density and due to female reproductive pathologies in captivity, makes it one of the most endangered rhinoceros species in the world40. On Borneo, the situation is especially dire since only one female survives in captivity and < 10 wild individuals remain in East Kalimantan41.Sumatran rhinoceroses were until recently widespread in SE Asia, from as far as the foothills of the Himalayas or Assam down to the islands of Sumatra and Borneo36. Consequently, the remaining populations may be exposed to intrinsic genetic threats such as reduced adaptive potential and inbreeding depression, which could accelerate its decline3.Consistent with the historical demographic decline since the 1930s, corresponding to approximately seven generations, the Sumatran rhinoceros is thought to have experienced a loss of genetic diversity both in the wild and in captivity40. However, the differentiation of these three genetic lineages possibly indicates a risk for outbreeding depression as a result of mixing populations, which implies that there may be a need to treat Sumatran rhinoceros subspecies as different conservation units . The risks of outbreeding depression may be outweighed by the risk of extinction due to inbreeding, demographic stochasticity, or environmental effects such as disease31, but concerns about outbreeding depression and the introduction of new deleterious alleles have not yet been addressed36. Thus, from a genetic perspective, the management of the remaining Sumatran rhinoceros populations represents a conundrum to conservation biologists, where the risks  have to be weighed against the benefits .With fewer than 100 individuals remaining, there have been recent proposals to manage the species as a single unit and to increase gene flow by translocation or exchange of gametes from different populationsHere, we aim to gain insights into the effects of population decline on the genetic conservation status of Sumatran rhinoceros by examining five historical and 16 modern whole-genomes from the two remaining populations on Sumatra and Borneo, and the most likely extinct population on the Malay Peninsula. We first investigate the population structure, past demography and timing of divergence among these three populations. Second, we estimate differences in genomic diversity and mutational load among the three populations, as well as temporal changes within two of the populations  using museum samples up to 140 years old. Finally, to evaluate the potential risks associated with assisted gene flow among modern populations, we examine the extent of private mutational load within each population, and whether signatures of positive selection, potentially associated with local adaptation, differ among the populations.GCA_014189135.1. Genome coverage ranged from 9X to 29X  Sumatran rhinoceros specimens from Sumatra, Borneo and the Malay Peninsula to a de novo assembly reference genome for Sumatran rhinoceros  revealed three distinct and reciprocally monophyletic clusters corresponding to the Sumatran, Malay Peninsula and Bornean populations . All three populations experienced similar demographic trajectories characterised by a decrease in Ne, with the most severe decline starting some 700–500 ka BP and by a subsequent more gradual decline to a Ne of ~2,000–1,000 at the end of the last glaciation  among the three populations using pseudodiploid X chromosome genomes for each pair of populations (see ‘Methods’)43. The PSMC indicated that the Bornean population started diverging from the Sumatran and Malay Peninsula populations ~300 ka BP  measured as the number of heterozygous sites per 1000 bp44 and inbreeding as the proportion of the genome found in runs of homozygostity46 (FROH) using 4,656,534 high-quality SNP calls (see ‘Methods’).We estimated the Sumatran rhinoceros’ spatial differences in genome-wide heterozygosity (ROH ≥ 2 Mb) among populations, with Sumatra and Borneo having ~71 and 78% higher heterozygosity  compared to the recently extinct Malay Peninsula population  ROH segments, the Malay Peninsula population had 30% shortly prior to its extinction.We found significant differences in heterozygosity and inbreeding  as well as Malay Peninsula , and a significantly higher relative mutational load on Sumatra compared to Malay Peninsula . We estimated mutational load using two complementary approaches. First, we estimated individual relative mutational load as the number of homozygous and heterozygous derived alleles at sites that are under strict evolutionary constraints using genomic evolutionary rate profiling scores . Genomic sites that have been strongly conserved for millions of years of evolution  are expected to be functionally important, and thus the fraction of mutations at such sites can serve as a proxy for mutational load . We identified sites carrying non-synonymous loss-of-function (LoF) variants, which are likely to be deleterious with a disruptive impact on protein function, and compiled a list of genes with such LoF variants. In total, we found 373 LoF variant sites across all three populations (Supplementary Table naverage = 213) compared to the other two modern populations , and that individuals on Sumatra have a significantly higher number of LoF variants (naverage = 186) compared to Malay Peninsula  during the past century, respectively  but no difference in the number of LoF variants per individual genome , we found that the Malay Peninsula population experienced a significant 1.5- and 3.84-fold increase in the proportion of all ROH  and estimated their frequencies in each population. We identified a total of 15,598 missense variants , which were associated with 6,490 identifiable genes . Out of 33,026 high-quality gene models, we found 61 genes with PBS values larger than the 99.8th percentile of the distribution of the PBS values of all genes , which incorporate the Fn = 6,490) and genes identified as under positive selection in the PBS analysis (n = 61) were related to various biological functions including cellular processes, biological regulation and metabolic processes (Supplementary Table Gene Ontology (GO) categories of all genes with missense variants  due to lowered sea levels52, our analyses of pseudodiploid X chromosomes suggest that the Bornean population started to become isolated already 300 ka BP, which is consistent with previous estimates based on mitogenome data31. At that time, the Sunda shelf was not completely submerged, with land linking mainland Asia with Sumatra and Borneo53. However, even though these regions were connected, a savannah corridor could have formed a geographical barrier for east-west dispersal of rainforest species such as Sumatran rhinoceros54, thereby limiting gene flow between Borneo and Sumatran/Malay Peninsula. In contrast, the populations on Sumatra and the Malay Peninsula appear to have become isolated from each other more recently, during the past 13–3 ka BP.The Sumatran rhinoceros has inhabited Southeast Asia since the beginning of the Pleistocene55, the relatively small Ne during the Holocene shown in the PSMC analysis, are consistent with a strong differentiation among the populations and with each population being reciprocally monophyletic. We also find evidence for a divergence between the northeastern and southwestern parts of Sumatra, most likely due to isolation caused by a mountain range stretching along the west coast of Sumatra. This subdivision is geographically different from the genetic divergence identified in Sumatran orangutans (Pongo abelii and Pongo tapanuliensis)56, with an initial divergence among orangutan populations north and south of Lake Toba starting ~3.38 mya and gene flow ceasing as a result of a volcanic eruption some 71 ka BP56. Additional sampling of rhinoceros specimens from north of Lake Toba would be needed to investigate the possibility of a similar deep subdivision in the Sumatran rhinoceros.While it may be difficult to distinguish between population structure and population decline with the PSMC approach58. These size differences and our results are thus consistent with the current taxonomy and subspecies delimitation. The level of genetic divergence in Sumatran rhinoceros is similar to what has recently been described for the white rhinoceros (C. simum sp.), where evidence for long-term divergence (80–10 ka BP) and limited post-divergence gene flow, as well as local adaptation, have been identified for the northern and southern subspecies59. However, it is worth noting that while long-term geographical isolation in Sumatran rhinoceros could lead to local adaptation, adaptive changes may not always occur, as indicated by our tests for positive selection in the three populations.Our PSMC analysis indicates that the Sumatran and Malay Peninsula lineages separated around 13 ka BP, whereas the Bornean and Sumatran lineages started separating much earlier, some 300 ka BP. Moreover, there are indications of body size differences among populations, with individuals from the Bornean population being smaller than individuals from other populationsNe over the past 10 ka BP, we also observe a large number of short ROH (< 2 Mb) within all three populations. Such a pattern is expected in populations with a long-term small population size due to repeated random mating between distant relatives, but is also common in populations that have experienced historical bottlenecks, since recombination breaks down long ROH into smaller ones60.Consistent with the inferred small 39, we find relatively little evidence for recent inbreeding in the populations on Borneo and Sumatra. When estimating inbreeding levels based on ROH ≥ 2 Mb, we found that, on average, < 10% of the genomes contain longer ROH segments. In addition, individual genome-wide heterozygosity was higher than in some other endangered taxa , as well as in white rhinoceros59. While these comparatively low levels of inbreeding and high levels of genetic diversity imply that the two surviving populations have not yet been affected by strong inbreeding depression3, even a small number of lethal equivalents could in theory lead to reductions in fitness62. Moreover, we note that there is a considerable amount of mutational load in these populations, especially on Borneo. In light of the current small census population sizes on Sumatra and Borneo, a future increase in inbreeding seems highly likely. This could, in turn, lead to increased exposure of recessive mutations in homozygous state63, which could pose a serious threat to the long-term persistence of these populations.However, even though the Sumatran rhinoceros has gone through a major decline in the past century, to the extent that fewer than 100 individuals currently remainNe, consistent with the observations of a long-term small Ne in mountain gorillas4 and island foxes64, which could have favoured purging of strongly deleterious alleles. We find some support for this in the PSMC, which indicated a slightly smaller Ne in the population over the past 30 ka in comparison to the two extant populations. Alternatively, since our temporal comparison with ca. 100-year-old samples from the Malay Peninsula indicates that inbreeding increased and mutational load decreased during the past century, the Malay Peninsula population may have experienced inbreeding depression during this period, which could have resulted in purging of mutational load prior to its extinction66. We caution here that even though we found a temporal decrease in mutational load, additional genomes from the Malay Peninsula population would be needed to fully resolve the timing and extent of temporal changes in mutational load in this population.In contrast to the extant populations, the recently extinct population on the Malay Peninsula had lower mutational load, but a higher proportion of the genome contained within longer ROH segments (30%). The comparatively low mutational load in the Malay Peninsula population could be a consequence of long-term small 40. Moreover, since the death of the last known captive male (Kertam) on Borneo, artificial insemination from its frozen sperm has been proposed as a promising tool to introduce new genetic diversity into the Sumatran population .The recent discovery of a wild female on Borneo  has intensified the discussions on assisted gene flow and the role of genetic rescue between Borneo and Sumatra in order to alleviate the negative consequences associated with small and isolated populations16. For the extant Sumatran rhinoceros populations, since most of the identified LoF variants were in heterozygous state, gene flow would probably not lead to a marked increase in the masking of deleterious alleles. However, if inbreeding increases in the near future, gene flow could counteract the increased risk for fixation of the existing LoF variants.Gene flow can improve the genetic status of an endangered species and result in an increase in fitness, known as hybrid vigour, through the masking of deleterious alleles22. While we found several genes with fixed missense variants in the populations on Borneo and Malay Peninsula, such mutations can also lead to a reduced protein effectiveness or even loss of protein function. Yet, it is worth noting that even if these missense variants have a negative effect on fitness, these would be masked in heterozygous state and at lower frequency in the recipient population, thereby reducing these potentially negative fitness effects. Nevertheless, it is unclear whether these variants represent any specific selective advantage in the local environment. Because of this, we also estimated population branch statistic (PBS) scores, which have been shown to have a high power to detect recent natural selection49 and should not be confounded by deleterious mutations. The results suggest that seven, two and zero genes have been uniquely selected in the Bornean, Malay Peninsula and Sumatran populations, respectively.One of the major risks of assisted gene flow is the disruption of local adaptation in the receiving population, which can cause outbreeding depression67. We caution, however, that behavioural changes in relation to captivity and/or translocation, or the risk of disease transmission, have not been considered in this study, but might also have an impact on the outcome of assisted gene flow. Despite the lack of evidence for local adaptation, long-term isolation between populations, with the estimated divergence between the Bornean population and the two other populations being at least 30 times older than the divergence between the Sumatra and the Malay Peninsula populations, suggests that the three populations could represent distinct evolutionary significant units (ESUs69). From the perspective of maintaining evolutionary processes, these should be ideally conserved as separate historically isolated ESUs69. However, given the high risk of extinction for the Sumatran rhinoceros, one could argue that the remaining populations should be managed as a metapopulation40, since increasing the evolutionary potential and chances of survival for the species through genetic rescue might outweigh the value of maintaining distinct evolutionary lineages70.Thus, we do not find strong support for local adaptation in these three populations, suggesting that the introduction of locally maladapted genes via gene flow from other populations is not very likely. The overall high genomic divergence between the two extant Sumatran rhinoceros populations instead suggests that gene flow could lead to an increase in adaptive potential by increasing the allelic diversity of the receiving population25. We found evidence for private mutational load in the form of specific genes having deleterious alleles in one population but not in the other two populations. Furthermore, our estimates suggested that gene flow of one individual from one population to the other would, on average, introduce ten new LoF variants into the recipient population. However, we also showed that the choice of donor would have a marked effect on how many deleterious alleles would be introduced, with estimates ranging from one to 75 new LoF variants depending on which individual was selected for assisted gene flow. Similarly, there is an asymmetry in the cost and benefit of gene flow among populations. For instance, gene flow from the Sumatran to the Bornean population would reduce the frequency of LoF variants in Borneo, whereas gene flow from Borneo to Sumatra would introduce new LoF variants in Sumatra. It is, however, noteworthy that in the absence of fitness effect estimates associated with these LoF variants, our estimates should only be considered as approximations of individual mutational load.While there seems to be little risk of introducing locally maladapted alleles, a potential by-product of gene flow could be an introduction of new deleterious variants into the recipient population25, which suggest that genetic rescue attempts should be avoided in some cases. However, this claim is in conflict with a large number of studies showing that assisted gene flow most often results in a genetic rescue effect27. Our analyses highlight the usefulness of genomic data to estimate individual mutational load, which subsequently can be used to assess the genetic consequences of assisted gene flow27.Recent genomic studies indicate that attempts at genetic rescue from outbred populations can have detrimental effects by increasing mutational load of small and inbred populationsth century, the Malay Peninsula population experienced an increase in inbreeding, and probably also inbreeding depression followed by purging of mutational load as indicated by the comparatively low level of mutational load shortly prior to its extinction. With little evidence for recent inbreeding in the two surviving populations and with few fixed deleterious alleles, the long-term survival of the Sumatran rhinoceros does not seem to be immediately threatened by detrimental genetic factors characteristic of small populations. However, given the extremely small sizes of the surviving populations on Borneo and Sumatra, it appears inevitable that inbreeding will increase in the near future, which in turn is likely to also expose the recessive deleterious alleles in homozygous state, thus reducing population viability even further. Assisted gene flow guided by genome sequencing has the potential to help mitigate such a process.In summary, our results suggest that from a conservation perspective, the current genetic status of Sumatran rhinoceros is at odds with the extremely small extant populations and associated concerns about inbreeding depression. However, the temporal changes observed in the Malay Peninsula population may serve as a warning of what might occur in the near future in the two surviving populations. Our results suggest that during the 20(D. sumatrensis harrissoniGCA_014189135.171) was used to map all re-sequencing data .The de novo reference genome for Sumatran rhinoceros data see . By blas73. Sixteen modern DNA extracts were sent to NGI Stockholm for library preparation and re-sequencing on an Illumina HiSeqX with a 2 × 150 bp setup in High Output mode. Utilization of samples was compliant with applicable regulatory procedures for CITES and the US Endangered Species Act. Export of blood and tissue samples for DNA extraction and genome sequencing from Sumatran rhinoceros individuals from Sabah to the Swedish Museum of Natural History, Stockholm, Sweden, was approved by The Sabah Biodiversity Council and the director of Sabah Wildlife Department in 2014 ). Exports of DNA extracts for genome sequencing from the San Diego Zoo Global Frozen Zoo®, USA, to the Swedish Museum of Natural History, Stockholm, Sweden, was between two CITES-registered institutions , as well as under Mutual Transfer Agreement (request number BR2016005).Thirty-one historical bone, skin and tooth samples from Borneo, Sumatra and the Malay Peninsula collected between 1868 and 1921 were obtained from five European natural history museums  and two X chromosome-linked scaffolds were excluded from the vcf files. All 21 rhinoceroses were included for population structure analyses , using 3,568,319 high-quality SNP calls. For all other analyses  the 18 rhinoceroses with coverage ≥ 9X were included, using 4,656,534 high-quality SNP.74 was performed, and genetic clusters K ranging from 1 to 675 were identified.An unrooted phylogeny was built by inferring genotype posterior probabilities for each individual, estimating pairwise genetic distances, and then estimating phylogeny from the distance matrix see . Second,42 model was used to infer fluctuations in Ne of the three major lineages of Sumatran rhinoceros over time  between each population pair of the Sumatran rhinoceros populations was estimated by assuming no coalescent events since divergence between the populations and using the PSMC approach applied to a pseudodiploid X chromosome genome.The pairwise sequentially Markovian coalescenttime see . 100 booθ) to approximate heterozygosity  under the infinite sites model44. Two-sided pairwise t-tests were used in R77 to statistically compare θ between groups.Individual genome-wide autosomal heterozygosity was estimated using mlRho, which uses the estimated population mutation rate  ROH ≥ 100 kb and (2) ROH ≥ 2 Mb. To statistically compare FROH between groups, two-sided pairwise t-tests were used in R77.Two different approaches were used to identify runs of homozygosity (ROH)47 within highly conserved regions of the genome  genome assembly and using its annotation of 33,026 genes (GCF_000283155.1 see 80. Variants were identified in three different categories: (a) Synonymous: mostly harmless or unlikely to change protein behaviour; (b) Missense: non-disruptive variants that might change protein effectiveness; and (c) LoF: variants assumed to have high (disruptive) impact on the protein, probably causing protein truncation, LoF or triggering nonsense-mediated decay 80. The variants in these four categories were also differentiated by homozygous and heterozygous state.Synonymous and non-synonymous nucleotide substitutions within coding regions as well as substitutions in proximity of coding regions were annotated for the 18 high-coverage modern and historical Sumatran rhinoceros genomes, by mapping the genomes to the white rhinoceros (n = 5) and the Malay Peninsula (n = 6) populations, and (2) among modern samples from the Bornean (n = 4), Malay Peninsula (n = 3) and Sumatran (n = 8) populations. The number of variants among populations was then compared using two-sided pairwise t-tests in R77. For the comparison among modern samples, the number of LoF variants shared among and unique to each population, as well as the estimated difference in frequency of LoF variants among populations were reported.Two types of comparisons were performed: (1) between the modern and historical specimens for the Bornean  in the other two populations.First, for each population, the frequency of variants characterised as missense to identify genes potentially involved in local adaptation in modern populations was estimated and the number of variants among populations statistically compared as described in the previous section. We also reported the number of missense variants common or unique to each population.ST between the target and the sister population is 1, with both populations fixed for a different allele, the PBS value can be infinite. Thus, infinite PBS values were replaced with the maximum value of the distribution of PBS values for that population. Finally, all genes with a PBS value larger than 3, ca. the 99.8th quartile of the distribution of the PBS values of all genes for each population, were reported.Second, the population branch statistic (PBS) was estimated to investigate adaptation to local environments in the three Sumatran rhinoceros populations see . Given tEquus caballus) as reference set (see We assessed the biological functions associated with LoF and missense variants as well as for genes identified with the PBS approach and tested for statistical overrepresentation for each of these categories using horse ( set see .Further information on research design is available in the Supplementary InformationPeer Review FileReporting Summary


Silurus glanis), and discuss the results in light of a recent microsatellite study of the same populations. The Swedish populations of the wels catfish have suffered from severe declines during the last centuries and persists in only a few isolated water systems. Fragmented populations generally are at greater risk of extinction, for example due to loss of genetic diversity, and may thus require conservation actions. We sequenced individuals from the three remaining native populations  and one reintroduced population of admixed origin (Helge å), and found that genetic diversity was highest in Emån but low overall, with strong differentiation among the populations. No signature of recent inbreeding was found, but a considerable number of short runs of homozygosity were present in all populations, likely linked to historically small population sizes and bottleneck events. Genetic substructure within any of the native populations was at best weak. Individuals from the admixed population Helge å shared most genetic ancestry with the Båven population (72%). Our results are largely in agreement with the microsatellite study, and stresses the need to protect these isolated populations at the northern edge of the distribution of the species.The use of genetic markers in the context of conservation is largely being outcompeted by whole-genome data. Comparative studies between the two are sparse, and the knowledge about potential effects of this methodology shift is limited. Here, we used whole-genome sequencing data to assess the genetic status of peripheral populations of the wels catfish ( Since genomic techniques have become more affordable and available, the field of conservation genetics has moved to conservation genomics  than Emån and Möckeln, while the number of alleles per locus was lowest in Båven and highest in Emån. Population differentiation (FST) estimates were high in all comparisons (0.34–0.57).Microsatellite markers applied in Triantafyllidis et al.  have recHere, we sequence and present a de-novo assembly of the wels catfish genome. In addition, we use whole-genome resequencing of individuals from four Swedish populations (three native and one reintroduced) to make inferences on genetic diversity, differentiation, and estimates of inbreeding in Swedish catfish. We use our data to compare with similar estimates obtained in a previously published genetic study using microsatellites  Table  into an A total of 66 samples were collected for whole-genome sequencing, including 20 from each native population  and six from the reintroduced, admixed population of Helge å  , following the provided standard protocol, with Nextera DNA CD Indexes to uniquely index each sample prior to pooling. Library quality was assessed using the High Sensitivity DNA Kit for the Agilent 2100 Bioanalyzer electrophoresis system . In the pooling step, an equal volume from each native sample was pooled . Pool quality and concentration were assessed using both a Bioanalyzer High Sensitivity DNA Kit and a Qubit 2.0 fluorometer  dsDNA HS (High Sensitivity) Assay Kit. Library quality of the Helge å samples was lower than that observed for native samples. Therefore, Helge å samples were added to the sequencing pool to give an approximate theoretical 5 × coverage. This final pool, containing 66 individually indexed samples, was sequenced on one S4 lane (150 bp paired-end reads) of an Illumina Novaseq 6000 by the SNP&SEQ Technology Platform in Uppsala.http://broadinstitute.github.io/picard), resulting in an unmapped BAM file. Reads were mapped to our de novo genome assembly using bwa mem v.0.7.17  using standard hard filtering parameters according to GATK Best Practices recommendations (https://gatk.broadinstitute.org/) . Briefly, the de novo genome reference fasta sequence was split in overlapping 150-mers and mapped back onto the reference genome. The result is a fasta-like mask file with a quality score from 0 to 3 for each position in the genome, where 0 indicates very poor mapping ability and 3 that the majority of overlapping 150-mers were mapped uniquely without mismatches. The mask file was converted to a bedfile using msmc-tools , which in addition to filtering out regions of spurious mapping also excluded the mitochondrial sequence. To further filter out low complexity or repetitive regions where reads may be falsely mapped, a mappability mask file was constructed using the SNPable Regions pipeline (https://github.com/lh3/seqtk) was implemented to subsample forward and reverse raw fastq reads separately, with number of reads set to 9,400,000 (approximately the number of reads in the sample with lowest read coverage divided by two) and random seed set to the same value (-s100) in both command executions to sample paired reads. The subsampled reads were then processed, mapped, and filtered in the same way as the full dataset, as described above, resulting in a second dataset containing samples from all four populations, hereafter referred to as the “downsampled SNP-set”.Samples from the reintroduced, admixed Helge å population were sequenced at a lower sequencing depth compared to the native samples. In order to account for this, we subsampled reads from the native samples in order to get similar coverage across all individuals for comparison to Helge å. Seqtk v.1.2  was calculated as the number of heterozygous sites divided by the total number of SNP sites  for all individuals. To test whether there were any significant differences in H between the populations, we ran a one-way ANOVA followed by a post-hoc Tukey’s test in R v. 3.6.1 (R Core Team P) was calculated for each population. For this purpose, we calculated π for each SNP in each population to get information on whether the site was variable . The number of sites where π was larger than 0 was then divided by the total number of SNPs  to get an estimate of the total variance that exists in each population.Diversity statistics from the filtered SNP sets were estimated by VCFtools 0.1.16  and Helge å population (N = 6) when these calculations were performed on the downsampled SNP-set, we performed 100 random resamplings of six individuals from each native population when calculating P, π and H, and report the average values (± sd). For the downsampled H values, we ran one-way ANOVA tests in R for all the 100 re-samplings and post-hoc Tukey’s tests for all of those where the ANOVA P-value was lower than 0.05.To adjust for the differing sample sizes between the native populations  in PLINK and a genetic ancestry analysis in the software ADMIXTURE . In order to do this, we first calculated the ROH analysis coverage across the genome for both these ROH lengths i.e. the length of the genome with sufficient SNP density for ROH detection, by constructing an artificial sample with homozygous genotypes across all SNPs in the dataset, following Meyermans et al.  , higher than both Båven at 0.20 (±0.01) and Möckeln at 0.20 (±0.02). A one-way ANOVA showed that there were statistically significant differences in H between the populations  = 19.36, P < 0.001), and the post-hoc Tukey’s test revealed significant differences between Emån and the two other native populations (P < 0.001 in both comparisons) while Båven and Möckeln did not differ significantly (P = 0.93).The highest genetic diversity of the three native populations was found in Emån, according to all three estimates Table . The popP (0.39) and H (0.096 ± 0.003), while π was highest in Båven (11.1 × 10−5 ± 0.1 × 10−5). In the majority (84) of the 100 random resamplings of six individuals per native population; however, population did not have a statistically significant effect on H.In the downsampled SNP-set, the diversity estimates of the three native populations were more similar to each other, while the reintroduced population of Helge å showed lower values in all three analyses Table . Also, iK = 4) and Emån (at K = 5). The structure appearing within Emån at K = 5 roughly corresponded to upstream and downstream sampling locations. Genetic differentiation between the native populations was similar across the three pairwise FST estimates. The weighted FST estimate between Båven and Emån was the highest at 0.196, followed by Båven and Möckeln at 0.195 and Emån and Möckeln at 0.170. The pairwise FST estimates across the genome displayed high variance between the populations without any obvious outliers displaying elevated levels of differentiation  and Möckeln (P = 0.008) while the difference between Båven and Möckeln was non-significant (P = 0.63), as found through a post-hoc Tukey’s test following a one-way ANOVA showing significant population differences  = 8.99, P < 0.001). Only four ROH segments over 1000 kb were found distributed across three individuals, all of which were just over 1000 kb in length. Thus, we did not specifically calculate FROH>1000kb as it was zero or close to zero across all individuals.The ROH analysis coverage from the native SNP-set was 647 Mb and 605 Mb for ROH lengths of > 100 Kb and > 1000 Kb, respectively, such that 98.7 % of the genome on scaffolds > 100 kb and 99.5% on scaffolds over 1000 kb were sufficiently covered by SNPs for ROHs to be called (i.e. lack of ROHs are not caused by insufficient SNP density). A large genomic proportion of native individuals consisted of ROH segments Fig. , althougven Fig. . In lineF = 5.70, P = 0.002), and the post-hoc Tukey’s test revealed that the samples from Emån still had significantly lower FROH>100KB values than Båven (P = 0.006) while the other comparisons among the native populations were non-significant (P > 0.17). The samples from Helge å had on average lower FROH>100KB than the native populations and were significantly differentiated from Båven (P = 0.008) but not from Emån and Möckeln (P > 0.23).We also ran a ROH scan on the down-sampled SNP-set, to infer the relative abundance of ROHs in Helge å compared to the native populations. ROH analysis coverage changed only marginally compared to the native SNP-set, resulting in analyzable lengths of 641 Mb and 601 Mb for ROHs > 100 Kb and ROHs > 1000 kb, respectively. As a consequence of the down-sampling, the heterozygosity was reduced in the native populations, leading to a larger proportion of the genome detected as ROH segments Fig. . The oneAll samples produced a mitochondrial haplotype with length of 16,524 bp. Overall, the mitochondrial diversity was low, with only five haplotypes found across all samples , heterozygosity (H) or proportion of polymorphic loci (P). This is in contrast to Palm et al.  who repoIt is clear from our data and the previous microsatellite study  prior to Emån (K = 5)  Fig. . Using FIS and extensive linkage disequilibrium) were only detectable in one of the populations (Emån) using microsatellites  found in our study are likely inflated in the comparisons involving the reintroduced Helge å population due to the lower quality of data from this population, which required down-sampling the native populations to appropriately allow comparisons. Given the shallow mapped read depth in this dataset, homozygosity is likely overestimated and should not be interpreted as absolute values. Instead, the relative levels of inbreeding across the populations should be considered, and as expected, the recently established reintroduced population  exhibited less inbreeding.With our resequencing approach, we could detect short ROHs in the native populations, indicative of a common past bottleneck  yielded remarkably similar results and conservation implications. Both approaches suggest marked genetic differentiation among the native populations, reduced genetic variation in isolated Swedish wels catfish populations as expected from a postglacial founder event, low levels of recent inbreeding in the native populations, and a major contribution of one of the founder populations in the restocked population of Helge å. Thus, it may be asked: what motivates a whole-genome resequencing project when the established microsatellite approach yielded similar results? First of all, we argue it is reassuring that different methods arrive at similar results and conservation recommendations. Different approaches have their different costs and benefits. A marker-based study, such as one based on microsatellites, yields data on a few loci from many fish while a resequencing approach yields many loci from fewer fish. Which is more reliable will depend on the specific research question: in this particular case, questions, results, and interpretation mostly converge. There may be circumstances, however, when one approach is more suitable than the other  indicates how much of the total variation is present in each of the subpopulations. The values of P indicate that the native populations each hold 62–73% (and thus lack 27–38%) of the total standing variation, such that genetic diversity could be substantially increased by translocations of individuals between populations. Caveats of translocations are risks of introducing alien diseases or parasites. One such example is a parasitic worm that has been reported on catfishes in Möckeln but not in Emån and Båven (Svensson et al. In line with Palm et al. , our resSupplementery FiguresSupplementery Table


Oncorhynchus nerka) in Kluane National Park and Reserve  that underwent a severe 12-year population decline followed by a rapid rebound. We genotyped archival scales sampled pre-crash and contemporary fin clips collected post-crash, revealing high coverage  and low genotyping error  despite the relatively poor quality of recovered DNA. We observed slight decreases in expected heterozygosity, allelic diversity, and effective population size post-crash, but none were significant, suggesting genetic diversity was retained despite the severe demographic contraction. Genotypic data also revealed the genetic distinctiveness of a now extirpated population just outside of KNPR, revealing biodiversity loss at the northern edge of the species distribution. More broadly, we demonstrated GT-seq as a valuable tool for collecting genome-wide data from archival samples to address basic questions in ecology and evolution, and inform applied research in wildlife conservation and fisheries management.Historical DNA analysis of archival samples has added new dimensions to population genetic studies, enabling spatiotemporal approaches for reconstructing population history and informing conservation management. Here we tested the efficacy of Genotyping-in-Thousands by sequencing (GT-seq) for collecting targeted single nucleotide polymorphism genotypic data from archival scale samples, and applied this approach to a study of kokanee salmon ( Generally defined as preserved hard or soft tissues collected within the past 200 years, data from archival samples have enabled comparisons of genetic diversity and changes in effective population size between past and present populations2. Furthermore these data can be used to include extirpated populations or extinct species within phylogenetic reconstructions5.Historical DNA analysis of archival samples has added new dimensions to population genetic studies, expanding our ability to reconstruct patterns and processes of evolution across time and space7 and response to climate-, population-, and fishing-related pressures11. In addition, microchemical analyses of these samples have been used to infer fish habitat use13, origin15, and exposure to pollutants17, as well as to reconstruct diet and trophic structure22. Such material also provides opportunities for recovering historical DNA. For example, mitochondrial DNA obtained from archival scales has been used to determine the genetic effects of historical stocking of Atlantic salmon  in northern Spanish rivers23, while microsatellite data from archival and contemporary pectoral fin samples allowed investigation of the temporal genetic consequences of river fragmentation for lake sturgeon (Acipenser fulvescens) in Ontario, Canada24. More recently, studies have employed single nucleotide polymorphism (SNP) genotyping of archival samples to examine temporal stability of Atlantic cod (Gadus morhua) at the northern range margin around Greenland26 and assess spatiotemporal genetic changes in Atlantic salmon populations across the Baltic Sea27. These studies and others have clearly demonstrated the value of historical DNA analysis and temporal population genomics for directly investigating population history and informing fisheries management.Calcified material from fish, such as scales, otoliths, and various types of bone, have been collected over the past century and effectively used to investigate individual growth history29, and a high percentage of exogenous DNA30. A range of approaches have been employed for successfully obtaining SNP genotypic data from archival fish samples, including TaqMan® genotyping assays31, Illumina GoldenGate assays26, SNP chips27, and shotgun whole genome re-sequencing32. One promising approach that has yet to be employed with archival samples is Genotyping-in-Thousands by sequencing (GT-seq)33. GT-seq is a multiplex amplicon sequencing method that uses species-specific primer probes to simultaneously target hundreds of loci for up to thousands of individuals, while also reducing amplification of non-target species DNA. Data collection can be conducted using a single library, making preparation simple and cost-effective compared to other methods34. Though amplification success can vary during multiplex PCR35, GT-seq has been found to amplify consistently with low genotyping error rates33. Moreover, GT-seq has been effective in obtaining genotypic data from low quality samples, such as those typically obtained through minimally or non-invasively collected starting materials36. Here, we test the effectiveness of GT-seq for genotyping archival samples using as a case study kokanee, the freshwater resident form of sockeye salmon (Oncorhynchus nerka), in Kluane National Park and Reserve (KNPR), Yukon, Canada.While archival DNA holds great promise for fisheries management, such historical samples can pose challenges as they may contain low DNA quantity, poor DNA quality37. Spawning numbers in KNPR have historically averaged ~ 3600 spawners each year, but a severe and prolonged population decline occurred between 2002–2014, reaching a low of just 20 observed spawners in 2009. The population rebounded in 2015 and 2016, with ~ 5550 spawners observed in those years, and has since fluctuated between ~ 400–3000 observed spawners annually  assess the effectiveness of GT-seq for genotyping archival scales; (2) quantify pre- and post-crash genetic diversity in KNPR; and (3) investigate spatial and temporal population structure in KNPR and Frederick Lake.41. Samples from Kathleen Lake were also collected July 13–22, 1973 (n = 22) during the same survey, and during subsequent creel surveys conducted May 26–June 22, 1980 (n = 18), and June 1 – July 23, 1981 (n = 47)42. Samples from spawning kokanee in Frederick Lake were collected by angling July 30–31, 1981 (n = 12)42. All samples were dried and stored in envelopes. Although carefully labelled and stored, these samples were largely forgotten until unearthed at the KNPR Warden Office, Yukon, Canada, during an office move in 2012 . Whole genomic DNA from dry scale samples was extracted following the protocol in43 within a dedicated historical DNA laboratory at the University of British Columbia Okanagan.Archival kokanee scale samples from Sockeye Lake were collected July 26–28, 1973 (n = 50) and July 15–August 26, 1975 (n = 13) as a part of a limnological survey of KNPR38 from Sockeye Lake and Sockeye Creek kokanee  originally sampled August 25–30, 2019 was used to represent the post-crash population. Also included was previously extracted kokanee DNA from the Whitehorse Rapids Fish Hatchery (n = 29) sampled August 31–September 18, 201938; this population was originally established from eggs and milt collected in Sockeye Creek in 1991–1994, 1999 and 2000 . Genomic DNA from two archival and two contemporary samples were subject to Genomic DNA ScreenTape® analysis on an Agilent Tapestation 4150 to assess DNA quality and quantity.Previously extracted genomic DNA33 as modified in36. Within library  and between library (n = 3) duplicates were included to allow for estimation of genotyping error rates. Each individual was prepared in two panels using separate sets of previously designed primer pools targeting ~ 100 base pair fragments, one including 288 SNPs44 and the other containing 342 SNPs45. PCR1 products were diluted 1:20 before use in PCR2. PCR2 products were quantified using PicoGreen™ , normalized manually to the concentration of the sample with the lowest concentration, and pooled. Pooled samples were purified using MinElute PCR Purification columns (Qiagen) and eluted into 24 μL nuclease-free water. Libraries were sequenced using a Mid Output Reagent Kit (300 cycles) on an Illumina MiniSeq within the Ecological and Conservation Genomics Laboratory at the University of British Columbia Okanagan.GT-seq libraries were constructed followinghttps://github.com/GT-seq/GT-seq-Pipeline). Individuals and SNP loci with > 30% missing data were removed using PLINK v1.90b6.1746. Monomorphic loci and those that had been previously identified as outlier loci45 were removed using VCFTOOLS47. Forty loci identified as duplicates between the two panels were also removed.Raw sequence data were genotyped using the GT-seq pipeline (Ho) and expected heterozygosity (He), effective number of alleles (Ae), and Weir and Cockerham’s θ (999 permutations)48 were estimated as implemented in GenoDive49. Effective population size (Ne) was estimated using the linkage disequilibrium method as implemented in NeEstimator v.250; Ne was only calculated for populations with n ≥ 40, as the linkage disequilibrium method provides the most reliable results the closer that sample sizes approximate the true Ne51. Population structure was visualized using Principal Component Analyses (PCA) as implemented in PCADAPT52; the number of principal components (PC) retained was identified using a graphical approach based on the scree plot53 as recommended by52. The Bayesian clustering approach implemented in STRUCTURE v2.354 was used to infer population structure. Run length was set to 500,000 MCMC (Markov chain Monte Carlo) iterations following a burn-in of 100,000 using correlated allele frequencies under a straight admixture model. STRUCTURE was run with the number of clusters (K) varying between 1–9, with 10 replicates for each value of K. The most likely K was chosen by plotting the log probability (ln Pr(X|K)) of the data across the K values and choosing the value at which ln Pr(X|K) leveled and variance was minimized as recommended in54. Bar plots were generated and visualized using CLUMPAK55.Observed , but substantially poorer quality, compared to DNA from contemporary samples based on Genomic DNA ScreenTape® analysis Fig. . AverageHo, He, Ae) from the archival samples were similar and stable across locations and sampling years in Sockeye  and Kathleen Lakes  (Table He and Ae was observed in the Sockeye Lake post-crash population (Table Ne in Sockeye Lake post-crash [2019: 86.8 (71.4–109.5)] compared to the pre-crash population [1973: 129.0 (104.1–166.8)], although confidence intervals overlapped (Table θ ≤ 0.009), and pre-crash compared to post-crash (θ ≤ 0.011)  from Sockeye and Kathleen Lakes  and low genotyping error  despite the substantially poorer quality of recovered DNA Fig. . These dθ values , as revealed by extremely low pairwise es Table  and lackes Table  and 4. THo, He, Ae) were similar temporally and spatially in Sockeye and Kathleen Lakes in pre-crash years, with a slight decrease in He and Ae observed in the post-crash population. There was a ~ 30% reduction in Ne in the post-crash population compared to the pre-crash population in Sockeye Lake, although there was some overlap of confidence intervals  in Europe and Peregrine falcons  in North America underwent severe bottlenecks and rapid recoveries as a result of dichlorodiphenyl-trichloroethane (DDT)-containing pesticides and their subsequent bans. However, neither showed a significant loss of genetic diversity as a result of these demographic bottlenecks61. While these periods of decline lasted decades, the species’ long lifespans likely helped maintain this diversity; in the case of white-tailed eagles, the population bottleneck lasted 20–30 years, which was only equivalent to ~ 2 generations61. As kokanee in KNPR have a documented generation time of ~ 4–5 years42, it is likely the demographic contraction in this system only lasted ~ 2–3 generations. Though severe, this duration of the bottleneck may not have been long enough to significantly erode genetic diversity within the population.Several factors may affect the genetic outcomes of a demographic contraction, including the severity and duration of the bottleneck, the latter of which can have an outsized effect. Genetic theory predicts that the bulk of genetic diversity can be retained, even during a severe bottleneck, as long as it is not prolongedθ > 0.450; Table 42. Yet, the high differentiation between these populations may suggest that they originated from separate ancestral populations over multiple events. Further research that includes sampling of anadromous sockeye salmon populations in the Alsek River and Klushu Lake would be required to test the single/multiple origin hypotheses. Regardless, the extirpation of Frederick Lake kokanee represents a loss of biodiversity, which may be even more pronounced given its northerly distribution, as small, isolated populations at the periphery of a species range,  may harbor unique traits not found in the core of a species range63.Our results revealed the extirpated Frederick Lake population to be genetically distinct from kokanee in KNPR, as evidenced by high levels of differentiation  per sample76. As such, GT-seq panels can be used not only as a means to compare genetic diversity and detect changes in effective population size and structure between populations past and present, but also to continually monitor these parameters into the future.Lastly, GT-seq can provide connectible data to monitor populations over time. Once designed, GT-seq panels can be employed by any lab or facility to directly target specific SNPs at specific locations in the genome. This is unlike more traditional markers, such as microsatellites, which are indirectly assayed using fragment analysis34. This approach has been previously shown to be effective for low quality DNA from minimally and non-invasively collected samples36. Here, we have demonstrated the utility of GT-seq for genotyping archival samples, further extending the temporal and spatial resolution this method can bring for addressing basic questions in ecology and evolution, as well as for informing applied research in wildlife conservation and fisheries management.Taken together, these advantages make GT-seq a valuable tool for implementing genomics into conservationSupplementary Information.