This review focuses on the Sahel/Savannah belt, a large region of Africa where two alternative subsistence systems , nowadays, interact. It is a long-standing question whether the pastoralists became isolated here from other populations after cattle began to spread into Africa  or, rather, began to merge with other populations, such as agropastoralists, after the domestication of sorghum and pearl millet (~5 kya) and with the subsequent spread of agriculture. If we look at lactase persistence, a trait closely associated with pastoral lifestyle, we see that its variants in current pastoralists distinguish them from their farmer neighbours. Most other  genetic polymorphisms do not, however, indicate such clear differentiation between these groups; they suggest a common origin and/or an extensive gene flow. Genetic affinity and ecological symbiosis between the two subsistence systems can help us better understand the population history of this African region. In this review, we show that genomic datasets of modern Sahel/Savannah belt populations properly collected in local populations can complement the still insufficient archaeological research of this region, especially when dealing with the prehistory of mobile populations with perishable material culture and therefore precarious archaeological visibility.  In the Sahel/Savannah belt of Africa (henceforth ‘the Sahel belt’), we can observe a mosaic of different ethnic groups, where various types of population interactions take place, including those between peoples of two distinct subsistence systems: nomadic pastoralists and sedentary farmers. With some simplification, one can say that farmers supply the market with grains and vegetables, while the pastoralists contribute meat and dairy products . It shouEver since the colonial era, Sahelian pastoralists have been viewed as a source of instability and even blamed for the ecological crises caused by overgrazing. It was somewhat related to a theory called the ‘tragedy of the commons’ developed in the 1960s by the American environmentalist Garrett James Hardin . AccordiNowadays, from an ethnolinguistic point of view, we can distinguish between two main groups of pastoralists in the Sahel: the Fulani called Woɗaaɓe or Mbororo’en, who inhabit mainly the western part of the Sahel, mostly west of the Lake Chad or around it ,6, and tInterestingly, pastoralism in the Sahel achieves an even higher level of protein production per hectare of land than livestock farming in climatically similar rainfall conditions abroad: while farmers in the US and Australia produce 0.3–0.5 kg of live weight per hectare of land, for Sahelian pastoralists practising traditional transhumance, it is 0.6–3.2 kg per hectare . MoreoveSkeletal remains found in southern Egypt, at the site of Nabta Playa and Bir Kiseiba in the western part of the Nile Valley, are considered to be the oldest evidence of the domestication of cattle in Africa ,21. ExpeAfrican food-production strategies have been studied by various archaeological methods, often with the help of natural sciences . It now Pennisetum glaucum. Nevertheless, it is also possible that nomadic pastoralism was added to the cultural repertoire of west Africa only at the beginning of the Common Era [Around 5.5 kya, however, traces of nomadic pastoralists gradually began to disappear. This disappearance was associated with a climate change that led to the desertification of the Sahara. Dating of archaeological sites in the northern part of Africa clearly shows that cattle spread from the northeast to the southwest over a relatively long period of time (~5000 years) . In westmmon Era . Some armmon Era . In factmmon Era .We can therefore pose the following three ‘taphonomic’ questions: Was pastoralism abandoned when the Green Sahara dried up around 5.5 kya? Was Sahelian pastoralism (re)invented only recently, in the 19th century, when it reappears in historical sources? Or is it rather so that its traces from the period between these time points simply do not survive? In fact, while farmers construct houses whose foundations remain archaeologically detectable for a long time, pastoralists build only simple mobile tents, which leave hardly any trace see . The issSince preservation of ancient DNA is in the Sahel environment with its high fluctuations in temperature and humidity highly unlikely, research tends to focus on the genetic diversity of modern populations, which is a hidden witness to their history. For instance, in genetic studies of microsatellite, mitochondrial DNA, and Y-chromosome data, the signature of some phylogenetic distances within pastoralist populations and the evidence of a gene flow between their local populations and the populations of farmers suggest that the groups may have coexisted in the past ,33,34. IWhen studying genetic adaptations, biological and cultural processes sometimes go hand in hand. An illustrative example is lactase persistence (LP), a trait genetically determined by several genetic variants, whose bearers can digest milk sugar even in adulthood. It was a considerable advantage for pastoralists with LP variants, as evidenced by the fact that it quickly began to spread in their populations through positive selection ,36. Acrop-values estimated using the Kruskal–Wallis test confirmed this finding). The difference between eastern and western pastoralists was due to the different frequencies of five well-known genetic variants [To illustrate this here, we have gathered the data of 38 populations analysed for LP in previous studies A 37,38,. We splivariants , which evariants ,41. Western Sahelian pastoralists, especially the Fulani from Ziniaré in Burkina Faso, have LP variant –13,910*T, which is common in Europe . It has A similar situation can be observed in the eastern Sahel, where we find a high frequency of a different LP variant , previously described as an independent mutation associated with the domestication and milking of camels in the Arabian Peninsula ~4 kya . This spDARC gene, which confers resistance against malaria caused by Plasmodium vivax [P. vivax is no longer present, and in the east it is declining, but other species of Plasmodium remain in the Sahel belt, such as P. falciparum. Malaria seems to have affected in a particular way also the genetic diversity of HLA genes of Sahelian populations, because the presence of alleles B*53:01:01 and B*78:01 closely correlates with environments where malaria is endemic [Another study dealing with genetic adaptations in the Sahel showed the importance of the um vivax . While i endemic . These a endemic ,48 becau endemic . Further endemic .Another potential target for exploring ancient gene flows between Sahelian groups of different subsistence strategies is the genetic diversity of uniparental systems. Both mitochondrial DNA (mtDNA) and nonrecombinant regions of the Y-chromosome (NRY) can exhibit sex-biased gene flow , as evidResearch into uniparental genetic systems across the Sahelian populations suggests that there might be an asymmetric gene flow between the pastoralists and the farmers on the level of mtDNA, i.e., the part of genome transmitted along the maternal line . In the Joint analyses of uniparental genetic systems in conjunction with linguistics and geography might, therefore, help us better understand the sex-biased gene flow and, specifically, the asymmetrical migrations of men and women for both the pastoralists and the farmers. Further research could also shed light on the distribution of diversity of the X-chromosome. Unlike the autosomal chromosome, the X-chromosome has a sex-specific inheritance pattern, where females inherit two copies (one from the mother and one from the father) while males inherit only a single copy (from the mother). Although the X-chromosome plays a significant role especially in admixed populations, it is often neglected in population genetics ,57,58. IFurther insights into genetic diversity, admixture history, and population structure come from the analyses of genome-wide SNP data of African and West Eurasian populations A 40,45,,45,59. EPrincipal component analyses (PCA) can indicate population structure and distinguish between continental and subcontinental ancestries, such as sub-Saharan African populations and other populations with North African, Middle Eastern, or European ancestry in PC1, and between western and eastern African populations in PC2 C. To revROH = 0.08 ± 0.03 SD) [Other differences between the pastoralists and the farmers in the Sahel belt can be demonstrated in the degree of inbreeding. The farmers tend to practice exogamy, while the pastoralists practice endogamy, which manifests itself among other things by a reduction of several genetic diversity measures in the mtDNA genome  of pastoralists analysed so far . This fi0.03 SD) . The Ras0.03 SD) .It is generally accepted that past demographic events—such as expansion, often accompanied by gene flow or admixture—have formed the genetic architecture of modern populations. Researchers who work with aDNA have direct material from historical populations but their research sometimes shows that these samples come from groups which did not substantially contributed their genetic heritage to present populations ,72. ConsOne possible reason why traces of the middle Holocene Saharan pastoralists disappeared in the archaeological records could be linked to their secondary use of animals for transportation. It is possible that they established trans-Saharan trade networks. Copper, iron, and later also gold became the main drivers of their economy ,74. ThisIt is also interesting to note that, in contrast to other regions of the world, citadel-type buildings are not documented in the Sahel belt, although some places, such as Djenné in the inner Niger Delta, did sustain very large populations . From thIn this context, it is important to mention the so-called Baggarization, i.e., a trans-formation of Arab camel herders into cattle breeders, which took place after Arabic-speaking populations penetrated into the wetter environment east of the Lake Chad , where tNone of the ethnic components of this country can claim to have always been there: all, without exception, have at one time or another in the past originated outside the geopolitical triangle that is Cameroon today’ [We should bear in mind that the social identity  of current populations in the Sahel does not necessarily indicate a shared cultural and genetic background. In this connection, let us recall the words of Eldridge Mohammadou, reflecting upon his own research in Cameroon: ‘n today’ . A collaLast but not least, we ought to emphasise that the maintenance of harmonic population interactions between pastoralists and farmers in the Sahel region is a most important but also highly complex matter. Fortunately, current disputes  are mostly resolved at the local level. Sometimes, though, they can escalate to a regional scale and even lead to humanitarian crises . In suchUnfortunately, current climate predictions are not optimistic. It is expected that by 2040, temperatures in the Sahel will increase on average by 2 °C and precipitation will decrease. According to some economists, this will lead to an increase in the market prices of cattle and consequently also other items . There iThe genetic landscape of human populations across the Sahel belt has been shaped by past migrations, diverse linguistic groups, and complex social dynamics. Despite their complex demographic history, the genetic diversity of Sahelian populations is seldom explored in genomic research. Future research of underrepresented African populations from this region will thus improve our understanding of not only the populations of the Sahel belt but also of the patterns of genetic variation observed in Africa today. Socioeconomic and anthropological factors play an important role in shaping the admixture patterns and population structure observed in nomadic pastoralists and sedentary farmers. Due to this variety of relevant factors in populations with different subsistence systems, genetic results of the Sahelian populations should be interpreted with caution and always in conjunction with archaeological, linguistic, and historical sources. Such multidisciplinary studies of Sahelian populations can contribute to our knowledge of their population history and improve our understanding of human genetic diversity and health in Africa.Last but not least, it should be noted that our research concerns only a relatively small part of the Sahelian metapopulation. There are many local groups which have not been properly sampled yet. In fact, numerous studies have shown that sub-Saharan Africa has the highest genetic diversity in the world, and almost every new research project that uses newly collected samples yields some unknown DNA sequences or haplotypes not present in current genomic datasets ,89. In t


Aedes aegypti and Aedes albopictus are important vectors of human arboviruses, transmitting arboviral diseases such as yellow fever, dengue, chikungunya and Zika. These two mosquitoes coexist on Hainan Island and the Leizhou Peninsula in China. Over the past 40 years, the distribution of Ae. albopictus has gradually expanded in these areas, while the distribution of Ae. aegypti has declined dramatically mainly due to the ecological changes and some other factors such as heavy use of insecticide indoor based on endophagic bloodfeeding of the species.kdr) genes of both mosquitoes, investigated their mutations, and analyzed their haplotype and evolutionary diversity combined with population genetic features based on the ND4/ND5 genes to further elucidate the molecular mechanisms underlying the development of insecticide resistance in both mosquitoes.This study focused on the knockdown resistance  of the F1534 locus are found in Ae. albopictus populations, with the three common mutations F1534C, F1534S and F1534L all having multiple independent origins. The F1534W (TTC/TGG) mutation is thought to have evolved from the F1534L (TTC/TTG) mutation. The F1534S (TTC/TCG) mutation has evolved from the F1534S (TTC/TCC) mutation. The most common form of mutation at the F1534 locus found in this study was S1534C, accounting for 20.97%, which may have evolved from the F1534C mutation. In addition, a new non-synonymous mutation M1524I and 28 synonymous mutations were identified in Ae. albopictus populations. Correlation analysis showed that the genetic diversity of Ae. aegypti and Ae. albopictus populations did not correlate with their kdr haplotype diversity (P>0.05), but strong gene flow between populations may have contributed to the evolution of the kdr gene.Three mutations, S989P, V1016G and F1534C, were found to be present in kdr gene evolution in the two mosquito species may help to identify the evolutionary trend of insecticide resistance at an early stage and provide a theoretical basis for improving the efficiency of biological vector control and subsequent research into new insecticides.The study of  Ae. aegypti and Ae. albopictus are vectors of four major arboviruses, dengue, chikungunya, yellow fever and Zika viruses, which have caused severe health burdens and economic losses worldwide. Many years ago, these vectors and viruses were endemic but confined to specific regions; however, in just over 200 years, they have spread to new tropical, subtropical and temperate regions, expanding their global distribution and likely contributing to coordinated outbreaks of arboviral disease epidemics  is a form of mosquito resistance to pyrethroid insecticides, mainly due to changes in one or more amino acids in the mosquito’s voltage-gated sodium channel (VGSC), which leads to a change in the conformation of the VGSC, reducing the ability of the pyrethroid molecule to bind as efficiently and further avoiding the toxic effects of the insecticide  climate with high temperatures and rainfall throughout the year. The natural conditions of high temperature and humidity are conducive to the breeding of vector mosquito including of diseases . There hdiseases . In 1988diseases . Howeveramethrin . In 2005ethroids . In 2010rmethrin . In 2015eninsula . In receentified . However problem . In partAe. aegypti and Ae. albopictus. In order to collect more samples of both mosquito species, areas where the presence of Ae. aegypti had been reported were selected for extensive sampling. Five geographic strains of Ae. aegypti and twenty-two geographic populations of Ae. albopictus were collected. Of these, five geographical populations were sampled for Ae. albopictus sympatric with Ae. aegypti  according to the instructions and the extracted DNA was stored at -20°C.From June to October 2021, the group visited Hainan Island and the Leizhou Peninsula to collect samples of  aegypti Table 1.Ae. aegypti populations worldwide, with the majority of mutations in Ae. albopictus populations occurring in domain III  The primers for the 585 bp IIS6 fragment of Ae. aegypti were named AII-F:5’GGTGGAACTTCACCGACTTC3’ and AII-R:5’ GGACGCAATCTGGCTTGTTA3’ , 1 ul of forward primer and 1 ul of reverse primer , followed by 2 ul of DNA template. The PCR program consisted of one cycle at 94°C for 5 min pre-denaturation, followed by 35 cycles of amplification , 60 s; 72°C, 60 s) and a final extension at 72°C for 5 min . Amplification products were subjected to 2% agarose electrophoresis. Positive amplification samples were sent to BGI for sequencing. Samples containing intron insertion/deletion fragments of Ae. aegypti IIS6 were cloned, and positive clones selected for sequencing.Mutations closely related to pyrethroid resistance have been found in both II and III of the VGSC domain in various main III . TherefoTTGTTA3’ ; (2) TheTTGTTA3’ ; (3) TheTCTTC 3’ . The ampAe. aegypti and ND5 genes of Ae. albopictus were amplified for population genetic diversity and dispersal analysis, and the primers were as follows: (1) The 380 bp ND4 primers were named AE-F:5’ GTDYATTTATGATTRCCTAA3’ and AE-R:5’ CTTCGDCTTCCWADWCGTTC3’ , 1 ul of forward primer and 1 ul of reverse primer (synthesized by Biotech), followed by 2 ul of DNA template. The PCR program consisted of one cycle at 94°C for a 5 min pre-denaturation, followed by 35 cycles of amplification , 60 s; 72°C, 60 s) and a final extension at 72°C for 5 min . Amplification products were subjected to 2% agarose electrophoresis. Positive amplification samples were sent to BGI for sequencing.The ND4 genes of WCGTTC3’ ; (2) theWCGTTC3’ . The ampkdr genes of Ae. aegypti and Ae. albopictus in the sympatric areas, it was divided all samples into two large groups for analysis. First, five geographic populations of Ae. aegypti and five geographic populations of Ae. albopictus that sympatric with them were analyzed as a group; Second, the remaining 17 geographic populations of Ae. albopictus were analyzed as a group. All sequences were reviewed in BioEdit software and mutation sites were identified. Sequences were then collated separately in Mega v7  and homogeneous (C1534C) forms, with the highest mutation frequency in the homogeneous form (86.85%). The S989P and V1016G mutations were synergistic and were only present in the HW and WS populations, with both heterozygous (S989P+V1016G) and homogeneous (P989P+G1016G) forms. Both forms were present in the HW population and only one heterozygous form (S989P+V1016G) was present in the WS population  and 5 in the WS population (S989P+V1016G+F1534C). These 18 samples were sequenced after cloning due to the presence of both of the above mutations, with base insertions or deletions at intron positions. A clonogenic sequence was randomly selected for data analysis. In addition, as the F1534 locus was mutated in all Ae. aegypti populations and was the only SNP locus for the IIIS6 fragment. Therefore, subsequent Ae. aegypti kdr genotyping studies analyzed only the IIS6 fragment and focused on the S989P and V1016G mutant loci.A total of three non-synonymous mutations  were detected in the kdr gene of the five Ae. albopictus populations sympatric with Ae. aegypti, but the mutation frequencies were significantly different . The YGH and WS Ae. albopictus populations had only one mutation from F1534S.Only one non-synonymous mutation (F1534C/S/L) was detected in the Ae. albopictus populations. This mutation form was found in the FHJC Ae. albopictus population, which occurred in concert with the F1534S mutation. The most common type of mutation at the F1534 locus was S1534C, where there were two base mutations at the same locus, TTC/TTC and TCC/TGC. It was found in all 14 Ae. albopictus populations except ZJJC, SSXX and HQMT populations, with a total mutation frequency of 20.97% (99/472). Among them, the LPC Ae. albopictus population had the most types of kdr gene mutations, with almost all types of mutation forms. In addition, another F1534S mutation (TTC/TCG) was detected in several populations; another F1534L mutation (TTC/CTC) was detected in the NYSS Ae. albopictus population; and the F1534W mutation (TTC/TTG) was found in three populations . In addition, an additional 28 synonymous mutations were detected in the IIIS6 segment of the kdr gene in all Ae. albopictus populations. The P1516 locus had the highest mutation frequency at 14.12%, followed by the L1540 and N1541 loci at 10.30% and 10.47%, respectively, and the mutations at the latter two loci occurred synonymously in all populations except one sample; in addition, the F1528 locus also had a high mutation frequency of 9.97%.In addition to the non-synonymous mutation (F1534C/S/L/W) at the F1534 locus, a non-synonymous mutation M1524I (ATG/ATT) was also detected in 17 other kdr gene for the five Ae. aegypti, 5 sympatric Ae. albopictus and the 17 Ae. albopictus populations are displayed in kdr gene was low in the Ae. aegypti population , but very high in the sympatric Ae. albopictus population . In addition, the remaining 17 Ae. albopictus populations had a lower haplotype diversity than the sympatric Ae. albopictus populations . The kdr gene haplotype TCS network showed that the most frequent haplotype in the Ae. aegypti populations was Hap_1, from which 12 other haplotypes evolved  and the evolutionary relationships were more complex, with the more common haplotypes being Hap_5, Hap_3 and Hap_11  and sympatric Ae. albopictus populations (Hd=0.00000-0.51282). Four haplotypes and five haplotypes were detected from 140 Ae. aegypti and 130 Ae. albopictus individuals, respectively  and 19 haplotypes were detected, with Hap_1 and Hap_4 being the dominant haplotypes and the other haplotypes all evolved from these two haplotypes , accounting for 72.26% (101/136) (The AMOVA results indicated that the main variation across populations Table S1101/136) . Howeverkdr gene, Pearson’s correlation analyses of the genetic diversity and kdr gene haplotype diversity was conducted, and found that there was no correlation between these two indices among the Ae. aegypti populations . The same results were also found in populations of sympatric Ae. albopictus  and the 17 Ae. albopictus .To verify whether population genetic diversity affected the evolution of the Ae. aegypti over the past 40 years was closely linked to vector control efforts in Hainan Island and the Leizhou Peninsula, and the heavy use of insecticides had inevitably led to a reduction in mosquito populations and the development of insecticide resistance . On the other hand, the other two mutations (S989P and V1016G) accompanied the heterozygous form of the F1534 locus mutation (F1534C); no cases of S989P or V1016G alone were found, and the mutation frequency was low (13.14%), which was consistent with the report by Cosme et al. . The S989P and V1016G homozygous mutation types were also found in the HW Ae. aegypti population. In addition, the HW population had the highest kdr haplotype diversity of the Ae. aegypti populations, suggesting that the HW Ae. aegypti population may have undergone greater insecticide selection. The genetic differentiation data also showed that only the HW Ae. aegypti population was less genetically distinct from all four other populations, with a strong gene flow  was performed. It was found that neither was correlated. The suggested that the high genetic diversity of these two mosquito species did not affect the evolution of the kdr genes.In contrast to  in 2016 . These m in 2016 3B. CompAe. albopictus populations was significantly higher compared to the five sympatric Ae. albopictus populations , F1534L (TTC/CTC), F1534W (TTC/TGG) and S1534C (TCC/TGC) mutation forms were also found at the F1534 locus. Among them, the F1534S (TTC/TCG) mutation was first identified in the Ae. albopictus population in Haikou, Hainan Island, in 2018  have low genetic differentiation and strong gene flow, and the ASZX Ae. albopictus population has high genetic exchange (Nm>1) with the other three populations in the city  (kdr gene in Culex quinquefasciatus suggested that the distribution of kdr mutations may be the result of widespread insecticide use and frequent population movements (The LPC ulations . The WDGulations . In addind ZJJC) Table S3ovements , and theAe. albopictus population. This mutation type has not been previously reported. It had been reported that any non-synonymous mutation on a protein targeted by a chemical insecticide could reduce the affinity of the insecticide for its target protein and lead to resistance  were found in Ae. albopictus populations, with the three common mutations F1534C, F1534S and F1534L all having multiple independent origins, and the F1534W mutation likely evolving from the F1534L mutation. The most common F1534 locus mutation found in this study was S1534C, which may have evolved further from the F1534C mutation. In addition, a new non-synonymous mutation M1524I and 28 synonymous mutations were identified in the Ae. albopictus population. A comparative analysis with genetic diversity showed that the genetic diversity of Ae. aegypti and Ae. albopictus populations did not correlate with their kdr gene haplotype diversity, but a strong gene flow between populations could contribute to the evolution of the kdr gene. The study of kdr gene mutations in the two mosquito species can help to identify the development trend of insecticide resistance at an early stage and provide a theoretical basis for improving the efficiency of biological vector control and subsequent research on new insecticides.This study analyzed the mutations and haplotypes in the The original contributions presented in the study are included in the article/MZ: Conceptualization, Formal Analysis, Investigation, Methodology, Software, Writing – original draft, Writing – review & editing. XR: Formal Analysis, Investigation, Writing – review & editing. DX: Investigation, Resources, Writing – review & editing. YL: Methodology, Writing – review & editing. WL: Resources, Writing – review & editing. YB: Methodology, Writing – review & editing. QZ: Methodology, Writing – review & editing. KC: Resources, Writing – review & editing. LL: Methodology, Writing – review & editing. MW: Resources, Writing – review & editing. ZM: Software, Writing – review & editing. JG: Software, Writing – review & editing. HZ: Conceptualization, Formal Analysis, Resources, Software, Writing – original draft, Writing – review & editing. TZ: Conceptualization, Formal Analysis, Resources, Writing – original draft, Writing – review & editing.


Anthropogenic climate change leads to increasing temperatures and altered precipitation and snowmelt patterns, especially in alpine ecosystems. To understand species’ responses to climate change, assessment of genetic structure and diversity is crucial as the basis for the evaluation of migration patterns, genetic adaptation potential as well as the identification of adaptive alleles.Achillea clusiana Tausch and Campanula pulla L. Genotyping-by-sequencing was employed to assemble loci de novo, call variants and perform population genetic analyses. Populations of either species were distinguishable by mountain, and to some extent by elevation. We found evidence for gene flow between elevations. Results of genome-environment associations suggested similar selective pressures acting on both species, emanating mainly from precipitation and exposition rather than temperature.We studied genetic structure, diversity and genome-environment associations of two snowbed species endemic to the Eastern Alps with a large elevational range, Given their genetic structure and amount of gene flow among populations the two study species are suitable to serve as a model for genetic monitoring of climate change adaptation along an elevation gradient. Consequences of climate change will predominantly manifest via changes in precipitation and, thus, duration of snow cover in the snowbeds and indirectly via shrub encroachment accompanied by increasing shading of snowbeds at lower range margins. Assembling genomes of the study species and studying larger sample sizes and time series will be necessary to functionally characterize and validate the herein identified genomic loci putatively involved in adaptive processes.The online version contains supplementary material available at 10.1186/s12870-023-04187-x. Anthropogenic climate change will lead to a projected increase in global mean temperature of 1.4–4.4 °C compared to pre-industrial levels by the end of the century . For insA wealth of studies and meta-analyses confirm that climate change is already affecting biota e.g., –8). Thei. Thei8])Nevertheless, climate change can also trigger genetically based adaptive evolution, which may proceed rapidly e.g., , 18). Th. Th18]).To understand species responses to climate change, in particular genetic adaptation, it is essential to consider differences in the evolutionary ecology of edge versus central populations. Range limits may be caused by Allee effects, temporal or spatial variation in dispersal , biotic interactions, environmental gradients, and interactions between these factors (reviewed in ). Selecti.e., latitudinal [Besides monitoring over time, one approach to infer species’ responses to climate change  is baseditudinal  or elevaitudinal  gradientitudinal ). Alpineitudinal  and agriGenetic structure and diversity of alpine species have also been shaped by past climatic fluctuations during and after the Pleistocene . During Achillea clusiana Tausch and Campanula pulla L. Endemic species were chosen in order to be able to cover a substantial part of their distribution area with a limited number of populations. Snowbeds are patchily distributed within the alpine grassland and the subalpine Pinus mugo krummholz belt on sites with a long-lasting snow cover. This patchiness implies natural fragmentation of the species’ habitat, and population dynamics influenced by patch size and – to a lesser degree – connectivity and habitat suitability [Here, we study genetic structure and diversity, as well as genome-environment associations, of two snowbed species endemic to the Eastern Alps with a large elevational range, tability . As the tability .Genetic structure, diversity and rarity: Suitable habitats are discontinuously distributed along the elevational gradient for both species, so we expect genetic differentiation among populations. We also expect the highest genetic diversity in the uppermost populations, where suitable habitats are more abundant, and decreasing genetic diversity with decreasing elevation in both species. Additionally, we aim at quantifying the proportion of private alleles in the populations at the lower (trailing) range edge, which have the highest risk of disappearing due to shrub encroachment and upwards advancement of the tree line [Gene flow among mountains is expected to be limited and to follow an isolation-by-distance (IBD) pattern. Within a mountain, we expect seed dispersal mainly from the upper to the lower populations, following gravity and the flow of water. Upward gene flow, which would be necessary to keep pace with the changing climate, could be accomplished by upwinds or dispersal and/or pollination through animal vectors. (3) Genome-environment associations: We aim at identifying loci under selection correlated with temperature-related abiotic variables  and precipitation, which both are important determinants of snow depth.The aim of our study was to assess the suitability of the two chosen species to serve as a model for genetic monitoring along an elevation gradient. Specifically, we address the following questions and hypotheses drawing on the elevational gradient as a space-for-time substitute : (1) Genree line . (2) GenAchillea clusiana and Campanula pulla, were sampled from three Austrian mountains located in the Northeastern Calcareous Alps, at three different elevations in July 2019. From each sampling site, five individuals were collected. The three mountains were Schneeberg , Lower Austria, Hochschwab , Styria, and the Admonter Kaibling , Styria. On each mountain three populations covering the elevation range of the two species were sampled, i.e., at the "lower" , "medium" , and "upper"  part of their vertical distribution area. In total, 92 samples from 90 individuals were analyzed  in a moA. clusiana and a mean of 9.0 million for C. pulla, respectively  was generated by Illumina sequencing. Demultiplexing and filtering resulted in 8.1 million read pairs on average per sample (range: 3.3–13.8 million) with a mean of 7.1 million for  × 150 ntnQuire [Intraspecific variation in ploidy occurs in a wide range of species and polyploidy can accelerate evolutionary adaptation by increasing the genetic diversity. Ploidy can be inferred directly by measuring DNA content or from read mappings to a reference genome. If inferred from sequencing data, ploidy levels can be distinguished based on distribution of base frequencies at biallelic variable sites that are characteristic for each ploidy level. nQuire  was usednQuire –53.The assembly and variant calling steps were performed using the program Stacks  with seqA. clusiana sample and 117,558 loci with 19-fold mean coverage were obtained for each C. pulla sample, respectively .First, putative alleles were built for each sample separately by de novo aligning forward reads into exactly-matching stacks. By comparing the stacks, sets of putative loci were formed and variants were identified using a maximum likelihood framework . On averly Fig. S. The meaA. clusiana, only 0.66 million consensus loci were built for C. pulla. The relation of the size of the locus catalogs contrasted with the relation of input reads comprising 106 million for A. clusiana and 129 million for C. pulla  for each species was built by comparing the combined sets of stacks from all samples of either species and merging alleles. While 1.53 million consensus loci were built for la Fig. S, and canA. clusiana and 24 in C. pulla. Contigs of A. clusiana had an average length of 144 bp and those of C. pulla had an average length of 149 bp.Thereafter, the sets of stacks (putative loci) were searched against the respective species locus catalog for each sample separately. Read-pair information was then integrated; paired-end reads were assembled into a contig and merged with the single-end locus. Inclusion of paired-read information led to an increase of the mean effective per-sample coverage to 17 in Stacks it may happen that reverse-complementary contigs are retained, subsequently leading to duplicated variant calls. This was the case for around one third of the genotyped loci and variant calls. Homologous loci were thus identified with BLAST (> 90% identity) and duplicates were discarded. We further filtered for genotype quality and mapping depth  at a time, reads from each individual in the dataset were aligned to that contig and each individual was genotyped at each identified variant. We considered only loci that were represented in all nine populations. We kept only polymorphic loci and required a locus to be covered by at least 80% of the samples of a population to be processed for that population and a minimum minor allele frequency of at least 5% to process a variant. When assembling contigs using th Fig. S. These fA. clusiana and 18,236 variants in C. pulla, respectively, on average per population , nucleotide diversity (π), and inbreeding coefficient . In C. pulla, lowest HI (0.0013) was observed in the medium population of Admonter Kaibling and highest HI (0.0019) in the upper population from Schneeberg. Mean expected heterozygosity ranged from 0.0011 in the upper Admonter Kaibling population to 0.0016 in the lower Hochschwab population. Campanula pulla populations from Admonter Kaibling had lower than average HI and HS values. HI was higher than HS in all populations of both species, with the difference being most pronounced in the upper population of C. pulla at Schneeberg.Inbreeding leads to increased homozygosity and can be estimated using the inbreeding coefficient A. clusiana, π was rather similar across the three mountains. In C. pulla, π was lowest on Admonter Kaibling and highest on Hochschwab. There was no clear elevational pattern in heterozygosity levels nor π in neither species.In C. pulla than within A. clusiana was observed, reflected in higher per-site FST values  population in C. pulla, were the most diverged and thus showed the highest pairwise FST values with all other populations.Higher divergence within es Fig. S and consns Fig. S. While dhp-rare [A. clusiana, and 0.0218 ± 0.0032 in populations of C. pulla, respectively. In A. clusiana, private allelic richness was in a similar range on all three mountains, whereas in C. pulla, it was approximately twice as high on Schneeberg as on the other two mountains  showed a separation of populations from the three mountains in both species  to identify structure in our data based on the variation detected with ies Fig. .Fig. 3ThA. clusiana, PC1 and PC2 clearly distinguished the individuals sampled from the three mountains, with an east-to-west gradient (Admonter Kaibling – Hochschwab – Schneeberg) on PC1. Consistent with FST results . In contrast to A. clusiana, we observed a stronger pattern of IBD rather than a clear differentiation by elevation in C. pulla  under selection were significantly correlated with an environmental factor: 31 with September–May precipitation, 29 with northness, 23 with eastness and 12 with elevation , the vast majority of which (209) were significantly correlated with eastness (82 of which were private to the upper population of Schneeberg and 1 to middle Hochschwab population), followed by September–May precipitation (150), northness (9) and elevation  was employed to detect loci under selection and multilocus adaptation . In A. cA. clusiana had p < 0.002, all others had p < 0.001) of the RDA show SNVs (dark grey points), individuals (colored symbols) and environmental variables  and the upper Schneeberg population . In C. pulla we found an even more different pattern. The Hochschwab populations did not form a separate group at all but were laddered between populations from Schneeberg and Admonter Kaibling. Successful genetic monitoring requires that both the three mountains and the three populations along the elevation gradient within a mountain have an independent genetic profile. The former could be clearly affirmed, even if the Hochschwab populations of C. pulla had a higher level of admixture. The second was only partially affirmed, since not all elevation levels showed an equally independent profile. Our expectation that the upper populations would have higher genetic diversity due to a more extensive habitat was not confirmed, as populations from all elevation levels had similar diversity. We assume that the fragmented nature of the snowbed habitat of the two species is responsible for this pattern. Similarly, other studies found that within-population genetic diversity was mostly not related to elevation (and population size) in alpine plants [Our results clearly show, on the one hand, that the three mountains studied harbored a distinct gene pool for each of the two model species and, on the other hand, that the populations were mostly differentiated within a mountain range along the elevation gradient. Populations from Schneeberg and Admonter Kaibling showed the same pattern of elevational differentiation in e plants , 64. Gene plants .A. clusiana, all three mountains appear to have played a similarly important role as refugia, as the populations from each mountain had a similarly high value of private allelic richness [C. pulla, Schneeberg even appears to have provided two separate refugia, one whose gene pool was represented by all but one individual from the upper population (CSU141–CSU144), and a second whose gene pool was represented by the remaining Schneeberg individuals. For C. pulla, Schneeberg thus seems to have played a more important role than the other two mountains, which is reflected in the twice as high private allelic richness of Schneeberg populations.To interpret current diversity and differentiation among populations, it is also necessary to consider the history of the populations. All three of the studied mountain ranges were located east of the completely glaciated area of the Alps during the last ice age and are considered refugial areas for alpine plants . This virichness . For C. A. clusiana, the lower and/or middle populations have the highest private allelic richness and the upper the lowest. At Admonter Kaibling, where the middle population has the highest private allelic richness, the situation is special in that the lower population is at the bottom of a steep ravine. Due to frequent and intensive disturbance by debris flows, the population appears to have been repeatedly destroyed and re-established. In C. pulla, the expectation of highest private allelic richness in the lower population  was confirmed only at Hochschwab. We interpret the pattern at Schneeberg as an indication of two separate refugia, each with a comparatively high private allelic richness, suggesting large refugial populations, possibly favored by the location on the edge of the Alps. At Admonter Kaibling, on the other hand, all three populations are relatively uniform, also in terms of private allelic richness. However, although they had the smallest population sizes (pers. obs. M. Winkler & K. Tremetsberger), the lower populations harbored a substantial proportion of the private alleles . Another explanation for our observation that populations from upper elevations are closer to each other would be gene flow directly between the summit regions of the mountains. Although neither study species is specifically adapted to wind dispersal, it is conceivable that infrequent diaspore dispersal between mountain tops could occur with blustery winds. Furthermore, pollinator insects already loaded with pollen may be displaced by stormy winds or diaspores may be transported by birds.Interestingly, in her Fig. . AchilleC. pulla populations were more complex. The upper Schneeberg population  was the most differentiated from all other populations. The population is located on the southern flank of Schneeberg, which is not oriented towards the other two mountains. If we disregard the upper Schneeberg population, we can observe the same pattern of decreasing pairwise FST between populations of the same elevation from lower to upper elevation as in A. clusiana. We interpret this as another result of smaller population sizes and stronger drift in the lower populations growing in a shaded doline in the subalpine krummholz zone on Hochschwab, in a steep rock face on Schneeberg, and in the "Eisloch" at the bottom of a steep ravine on Admonter Kaibling. At Hochschwab, the stronger differentiation between the lower population (located on the north-eastern part of the Hochschwab massif) and the middle and upper populations (in the center of the Hochschwab massif) was evident in both A. clusiana and C. pulla  may be a descendant of a recent migrant that dispersed from the middle population at Schneeberg to the upper population a few generations ago and interbred with the local individuals there. The presumed dispersal was from near the middle Schneeberg population, i.e., from about 1860 m a.s.l. about 800 m in an SSE direction to an SE-exposed scree slope immediately below the ridge and not far from a dirt road (2030 m a.s.l.). Another way to look at our result is that individuals CSU141–CSU144 may have recently immigrated from an unsampled, genetically divergent population. If they arrived through a clustered migration event , this would explain their striking genetic proximity. In any case, a mixture of two divergent gene pools was observed in the upper Schneeberg population, apparently the result of a recent migration event. No presumed descendants of recent migrants were sampled in A. clusiana. The results show that the GBS method is very sensitive to detect recent migration events and that such events occur between populations of a mountain. However, to estimate the frequency of such events, it would be necessary to genotype many more individuals.One of the 45 studied individuals of A. clusiana showing a negative relationship with northness, and C. pulla a positive relationship with eastness. The lower Schneeberg populations, which also showed a divergent pattern, cannot be meaningfully compared as the two species were sampled in different localities more than 100 altitudinal meters apart from each other.The populations of the two species showed an almost identical pattern of correlation of SNVs under selection with environmental variables, with September–May precipitation being most important for Admonter Kaibling middle and upper populations, and exposition (eastness or northness) for all other populations suggesting similar selective pressures on the two snowbed species. The only exception to this common pattern was the upper Schneeberg population, with Both September–May precipitation and exposition influence snow depth and the timing of snow-melt. At high elevations, precipitation outside the vegetation period predominantly falls in the form of snow, with snow accumulating in depressions formed in the Karst landscape of the calcareous study sites. The exposition on the other hand determines exposure to wind, and has also thermic consequences. In the Alps, (north)westerly winds prevail, with snow accumulating at the lee side . Further.  predict.  have shulations . TherefoA. clusiana and C. pulla as model species and of GBS as a method for genetic monitoring. The biological characteristics of the species, such as a diploid chromosome set and low levels of inbreeding, indicate that the species are suitable. For genetic monitoring of climate change adaptation, it is necessary to detect rare recent dispersal events. The GBS method seems to provide sufficient resolution for this in most cases. The population histories of the two species differ to some extent, but this is not a hindrance to studying the question of adaptation to climate change. However, because GBS reveals only a small portion of the genome and predominantly neutral variation, other genetic methods are needed to trace the spread of adaptive variants with climatic change. One would have to assemble the genomes of the two species. Meanwhile, it would also be  feasible to re-sequence the entire genomes of hundreds of individuals.The aim of the present study was to evaluate the suitability of The results obtained herein suggest that a mere space-for-time substitution approach helps drawing some conclusions but may not be sufficient to assess the consequences of climate change on the evolutionary potential of alpine plant species as the genetic signature is not only formed by present environmental and demographic factors but also by population history . Follow-Achillea clusiana Tausch (Asteraceae), a species endemic to the Northeastern Calcareous Alps, belongs to Achillea sect. Anthemideae and is closely related to the more widespread A. atrata. Both species are reported to have a diploid genome . Acaromatic . The spearomatic  and pollaromatic . Achillesnowbeds .Campanula pulla L. (Campanulaceae) is an endemic of the Northeastern Alps, where it occurs in the same habitat types as A. clusiana [Campanula pulla is perennial with limited clonal growth. Approximately 56% of the individuals are fertile, each producing on average 173 small seeds with no apparent specialized dispersal mechanism [clusiana . Campanuechanism .CHELSA provides high-resolution datasets for temperature and precipitation on a ~ 1 km grid worldwide , 77, 78.ApeKI enzyme and the library was amplified with 18 PCR cycles. Combinatorial bar codes were used to generate the libraries, and 150 nucleotides long paired end reads were generated by Illumina sequencing.Collected leaf samples were dried in silica gel. DNA was extracted from 15–30 mg dried leaf tissue using the DNeasy Plant Mini Kit extraction kit  following the manufacturer’s protocol, but adding two sorbitol washing steps after leaf tissue disruption. DNA quality was checked on agarose gels. DNA concentrations were quantified with a DS-11 FX Fluorometer , using the dsDNA Broad Range Assay Kit (DeNovix) according to the manufacturer’s manual. DNA was dried and shipped for library preparation and sequencing to The Elshire Group Ltd., New Zealand. The sequencing data was generated following a modified version of the protocol by  that incaxe-demux [Raw sequencing data were demultiplexed to obtain per-sample data files. As recommended by , axe-demxe-demux  was usedcutadapt  to ensuFastQC [BLAST [FastQC report and bwa mem [SAMtools [FastQC showed that no overrepresented sequences remained in the data.FastQC  was usedC [BLAST , 86 reve bwa mem  was usedSAMtools , 89 was Stacks [Trimmomatic [For analysis with Stacks  it was nmmomatic  using thStacks can be used to analyze RAD-seq data either with or without a reference genome. In the case of a missing reference sequence, Stacks assembles reference loci de novo from RAD-seq data and then uses these loci to call variants from the sequencing data. Several population genetic analyses are implemented in Stacks, but can also be performed individually with other tools as Stacks is able to print different output formats. For analysis with Stacks a series of sub-programs has to be run for sequencing reads trimmed to equal length, which in our case were 90 nt , -M (default 2) and -N (default M + 2) and cstacks -n . Performance of these parameter combinations was tested for each population parameter-pair -r from 0.4 to 1.0 in 0.2 increments and -p from one to nine. In the end, slightly modified Stacks assembly and variant analysis settings according to the recommendation from [ustacks -m 3, -M 2 and -N 2 and cstacks -n 2 and populations -r 0.8, -p 9 and -min-maf 0.05), as described in detail below.Different ion from  were appustacks; -N determined the maximum distance allowed to align secondary reads to primary stacks and was lowered compared to the default in order to stronger punish secondary reads, that is reads that did not form putative Stacks loci; -M 2 determined the maximum distance allowed between stacks and -m 3 determined the minimum depth of coverage required to create a stack.Except for -N 2 (default: M + 2), default settings were used to run cstacks; -n determined the number of mismatches allowed between sample loci when building the catalog.gstacks was used to incorporate the paired-end reads, as fetched by tsv2bam, and to assemble paired-end reads into contigs (non-overlapping read pairs are connected via an N-decamer by Stacks), to merge contigs with the respective single-end locus, to align reads from individual samples to the locus, to identify SNVs and to genotype each individual at each variant.Except for -n 2 default settings were used to run gstacks were used as input for populations to obtain estimates of heterozygosity, diversity and fixation indices and the variant and allele frequency files that were used for phylogenetic and admixture analysis and PCA and EAA. Except for -p 9, -r 0.8 and -min-maf 0.05 default settings were used; -p determined the minimum number of populations a locus must be present in to process a locus, -r determined the minimum percentage of individuals in a population required to process a locus for that population and -min-maf specified the minimum minor allele frequency required to process a SNV.Output files from FST were robust and consistent between results obtained using different Stacks parameters and independent of the populations parameter -write-random-SNV, which can be useful to avoid effect of linkage disequilibrium (LD) on downstream analyses that are sensible to this phenomenon, like FST calculations, by randomly selecting only one variant site per locus for the estimations.The patterns observed in pairwise The resulting quality filtered variants were used to perform phylogenetic and admixture analysis and PCA and EAA as described below.nQuire [Stacks locus catalog of the respective species. The denoise option was used to counteract noise resulting from mismappings, which reduced the number of considered sites by 65% in A. clusiana and by 61% in C. pulla. Visual inspection of the ploidy levels clearly supported the diploid status of all tested individuals independent of denoising, i.e. base frequency peaks in results from the histo command were always at 0.5 and the diploid model always had best fit between ideal and empirical histograms as characterized by lowest sums of squared residuals of empirical vs. ideal histograms, positive slope with low standard error and highest correlation coefficients of the regression of y-values in results from the histotest command (averages for the denoised runs were r2(2N) = 0.12, r2(3N) = 0.01, r2(4N) = 0.02 in A. clusiana and r2(2N) = 0.14, r2(3N) = 0.02, r2(4N) = 0.02 in C. pulla, respectively).nQuire  was usedPetroselinum crispum (Mill.) Fuss, 1C = 2.23 pg; [Pisum sativum L. ‘Kleine Rheinländerin’, 1C = 4.42 pg; [A. clusiana and three individuals of C. pulla  were measured. One individual of each species was measured twice, one time with parsley as standard, one time with pea as standard. The remaining individuals were measured once, with pea as standard in the case of A. clusiana and with parsley as standard in the case of C. pulla.To measure the genome size of the two model species by flow cytometry, we used the CyStain PI Absolute P kit  according to the manufacturer's instructions with leaf tissue of the sample and parsley  or pea 4.42 pg; ) as inteStacks were printed with populations -vcf in.vcf format and further used to perform PCA with smartPCA [smartPCA were generated with bcftools query [R.PCA is a dimension-reducing method that summarizes the variation observed in the data as linear combinations of multivariate observations. For each component, PCA assigns weights to the traits (variants) that contribute most to the variation observed in the data. Samples can then be plotted along the resulting orthogonal axes to identify clusters that represent biological groups. PCA has become a popular tool for exploring multilocus population genetics data to study population structure and identify migrants and hybrids or polyploids. The quality filtered variants called with smartPCA  to detecls query  and custRAxML to study phylogenetic relationships in the data. bcftools query was used to extract genotypes and then bash and python were used to generate pseudohaploid multifasta alignments by randomly sampling allele 0 or allele 1 in case of heterozygous sites, and to convert the file to a format readable by RAxML. The GTRCAT model was used and the resulting bootstrap values of 1,000 bootstrap replicates annotated to the respective maximum likelihood trees. The resulting trees with bootstrap values were midpoint-rooted and visualized in figtree.The quality filtered variants (see above) were used as input to generate maximum likelihood trees with STRUCTURE [k ancestral populations is assumed where k in general is unknown. Individuals get probabilistically assigned to each k based on sets of observed allele frequencies at each locus. Depending on the level of admixture, individuals thus are assigned to one population in case of no mixing, or jointly to two or more populations if their genotypes indicate that they are admixed. Within populations, Hardy–Weinberg equilibrium is assumed and weak linkage between alleles is accounted for. STRUCTURE is implemented in a Bayesian framework and for each tested k a likelihood is obtained that is then compared to other settings of k to get an estimate of the k that best represents the true number of ancestral populations represented by the analyzed individuals.A well-established approach to effectively study population structure in biological multilocus genotype data is implemented in TRUCTURE , 59. In populations -structure command was used to get the Stacks variants in a format readable by STRUCTURE. We used an admixture model, accounted for linkage and tested k three to nine for each species. We ran five independent Markov chain Monte Carlo (MCMC) operations  for each k. The best k for each species was evaluated using the Evanno method [CLUMPAK [The o method  as imple[CLUMPAK , 95.A. clusiana and C. pulla a total of 3.5% and 2.3%, respectively, were missing values. As RDA does not allow any missing data the analysis was restricted to only a proportion of the total variation observed . Environmental variables we considered were elevation, eastness, northness, and the following downscaled climate variables: annual precipitation, precipitation in the vegetation period (Jun–Aug) and in the rest of the year , mean annual temperature, and minimum, maximum and mean monthly temperatures of June to September. To minimize collinearity we reduced the set of variables entered in the analysis to elevation, eastness, northness and precipitation outside of the vegetation period , a multivariate method to detect loci under selection and multilocus adaptation . In the Additional file 1:Table S1. Environmental variables characterizing populations of A) Achillea clusiana and B) Campanula pulla analyzed in the study. MAT… mean annual temperature, T… temperature.Additional file 2:Table S2. Minimum, maximum and average number of reads in million left per sample after the different filtering steps per species and in total. Filter1 is demultiplexing, filter2 is removing adapter sequences, filter3 is removing ApeKI restriction enzyme overhangs (CWG), filter4 is removing reads with overrepresented sequences as identified with FastQC and filter5 is trimming reads to 90 nt length such that they can be used with Stacks.Additional file 3:Table S3. Per sample and species summary statistics of the sequencing data and after each of the five filtering steps. Columns show basecount, readcount, % of bases left, % of reads left. Filter1 is demultiplexing, filter2 is adapter removal, filter3 is trimming of ApeKI cutting enzyme overhangs (CWG), filter4 is removal of overrepresented sequences and filter5 is trimming to 90 nt.Additional file 4:Table S4. Summary statistics of the Stacks analysis per sample and species. Columns show the number of input reads used to run Stacks per sample and in total per species, the number of stacks generated by Stacks (ustacks) and the stacks coverage per sample and on average per species and the per sample min., average, max. and SD per species.Additional file 5:Table S5. Summary statistics of the Stacks analysis per population. Average values per species and of populations from each elevation and mountain per species and in total are given. The number of polymorphic sites and private alleles are listed as well as several population genetics statistics: observed and expected heterozygosity (HI and HS), nucleotide diversity (π) and inbreeding coefficient (FIS). The other six columns show the number of polymorphic loci and sites and private alleles after each of the two variant filtering steps. First it was filtered for genotype quality and read depth. The second filter included removal of duplicated Stacks loci.Additional file 6:Table S6. Summary statistics of all variants significantly correlated with an environmental variable for A) Achillea clusiana and B) Campanula pulla. Analysis based on Redundancy Analysis with the environmental variables eastness, elevation, northness and precipitation outside of the vegetation period . Columns show significant axis, variant coordinate, variant loading, correlation with each predictor and correlation of predictor that most strongly correlates with variant. Variants that are private to a population are marked. Genotypes for all samples are listed. Sample and population names: A ... A. clusiana, C ... C. pulla; H ... Hochschwab, K ... Admonter Kaibling, S ... Schneeberg; L … population at lower elevational range limit, M … intermediate, U … upper elevational range limit.Additional file 7:Table S7. Pearson correlation coefficients between environmental variables of nine populations of Achillea clusiana  and Campanula pulla  in the Northeastern Calcareous Alps. Climate variables were downscaled from CHELSA data 1979–2013. MAT… mean annual temperature, T… temperature.Additional file 8:Figure S1. Percentage of raw reads left after the different filtering steps for samples of each A) Achillea clusiana and B) Campanula pulla population. Filter1-3 corresponds to 100% and is the data after demultiplexing, adapter removal and trimming of CWG overhangs from ApeKI digestion, filter4 is removal of overrepresented sequences and filter5 is trimming to 90 nt. For each species the per-sample average per filtering step is included as dashed line. Population names consist of species , mountain  and elevation .Additional file 9:Figure S2. Distribution of read lengths after applying filter1-3  for A) Achillea clusiana and B) for Campanula pulla. Mean and median read lengths are indicated.Additional file 10:Figure S3. Stack coverage of stacks per population of A) Achillea clusiana and B) Campanula pulla. Stacks were generated with the ustacks step of the Stacks pipeline. The per-species average coverage is indicated with a dashed red line. Population names consist of species , mountain  and elevation .Additional file 11:Figure S4. Distribution of observed stack read depths  and C)) and observed genotype qualities  and D)) for the variants detected in Achillea clusiana in the upper panel and Campanula pulla in the lower panel, respectively. Thresholds for genotype quality and read depth filtering of the variants were set per species according to these plots: GQ 32 and DP 4–36 in case of A. clusiana and GQ 33 and DP 4–53 in case of C. pulla, respectively.Additional file 12:Figure S5. Length distribution of final quality filtered de novo assembled polymorphic Stacks contigs for Achillea clusiana in A) and for Campanula pulla in B), respectively. Mean and median read lengths are indicated.Additional file 13:Figure S6. Distribution of per-site FST values for each quality filtered variant for A) Achillea clusiana and B) Campanula pulla. Mean and median FST values are indicated.Additional file 14:Figure S7. Pairwise FST values  for all populations based on variants obtained with Stacks for A) Achillea clusiana and B) for Campanula pulla. Numbers of shared variants are shown in grey above the diagonal. Population names consist of species , mountain  and elevation .Additional file 15:Figure S8. Midpoint-rooted maximum likelihood tree based on quality filtered variants for A) Achillea clusiana and B) for Campanula pulla. Branches are supported by bootstrap values obtained from 1,000 replicates. Sample names consist of species , mountain , elevation  and the individual sample ID.Additional file 16:Figure S9. Admixture results obtained with STRUCTURE assuming k three to nine ancestral populations and using allele frequencies for variants obtained with Stacks for Achillea clusiana. Samples are sorted from left to right starting with the westernmost mountain Admonter Kaibling, over Hochschwab to the easternmost mountain Schneeberg and populations of each mountain are sorted by elevation in increasing order from left to right. Ancestry proportions for each sample are shown on the y-axis. Sample names consist of species (A for A. clusiana), mountain , elevation  and the individual sample ID.Additional file 17:Figure S10. Admixture results obtained with STRUCTURE assuming k three to nine ancestral populations and using allele frequencies for variants obtained with Stacks for Campanula pulla. Samples are sorted from left to right starting with the westernmost mountain Admonter Kaibling, over Hochschwab to the easternmost mountain Schneeberg and populations of each mountain are sorted by elevation in increasing order from left to right. Ancestry proportions for each sample are shown on the y-axis. Sample names consist of species (C for C. pulla), mountain , elevation  and the individual sample ID.Additional file 18:Figure S11. Allele frequencies for quality filtered variants for A) Achillea clusiana populations and B) Campanula pulla populations. Allele frequency range was split into ten bins of bin size ten with stepsize ten. Population names consist of species , mountain  and elevation .Additional file 19:Figure S12. Triplots of the first three significant axis of the Redundancy Analysis (RDA) show variants (grey open circles) and environmental variables ) for Achillea clusiana (A–C) and for Campanula pulla (D–F), respectively. Variants are colored depending on which environmental variable they significantly correlate with.


Suaeda aralocaspica, which is an annual halophyte, grows in saline deserts in Central Asia with potential use in saline soil reclamation and salt tolerance breeding. Studying its genetic diversity is critical for effective conservation and breeding programs. In this study, we aimed to develop a set of polymorphic microsatellite markers to analyze the genetic diversity of S. aralocaspica. We identified 177,805 SSRs from the S. aralocaspica genome, with an average length of 19.49 bp, which were present at a density of 393.37 SSR/Mb. Trinucleotide repeats dominated (75.74%) different types of motifs, and the main motif was CAA/TTG (44.25%). We successfully developed 38 SSR markers that exhibited substantial polymorphism, displaying an average of 6.18 alleles with accompanying average polymorphism information content (PIC) value of 0.516. The markers were used to evaluate the genetic diversity of 52 individuals collected from three populations of S. aralocaspica in Xinjiang, China. The results showed that the genetic diversity was moderate to high, with a mean expected heterozygosity (He) of 0.614, a mean Shannon’s information index (I) of 1.23, and a mean genetic differentiation index (Fst) of 0.263. The SSR markers developed in this study provide a valuable resource for future genetic studies and breeding programs of S. aralocaspica, and even other species in Suaeda. Suaeda spp., which has more than 100 species, is a genus of flowering plants that belongs to the family Amaranthaceae [Suaeda plants are highly adapted to extreme salt and water conditions [Suaeda are used for reclamation of degraded saline lands, as well as in the production of biofuels due to their high oil content [Suaeda represents a significant ecological and economic resource for many countries around the world [nthaceae . Suaeda nditions . They handitions . In addi content . Suaeda he world .Suaeda aralocaspica is a plant species with succulent leaves that belongs to the family Amaranthaceae. This annual halophyte plant is native to Central Asia and can be found in the salty deserts of the region. In China, this plant is found in the cold desert regions of the Junggar Basin in Xinjiang [4 photosynthesis within individual cells but lacks the characteristic leaf anatomy of other C4 plants. These features make it potentially valuable in biotechnology of higher photosynthetic efficiencies in agriculturally important C3 carbon fixation species such as rice [S. aralocaspica, as its population is rapidly diminishing, requiring urgent protection against further decline and potential extinction.Xinjiang ,7. It ca as rice . Seed he as rice ,10,11,12Genetic diversity, also known as gene diversity, is the total range of genetic variation present in different individuals among various populations as well as within the same population . It is cThere are several methods for studying genetic diversity, such as morphological tests, cytological markers, biochemical markers, and molecular markers ,18. HoweSuaeda species [Suaeda genus have not been extensively developed. Genetic diversity of S. corniculata from Bunge in Eastern Siberia was analyzed by using five inter-simple sequence repeats (ISSRs) markers [S. maritima from coastal and inland areas of Central Europe were compared using 10 polymorphic microsatellite markers. The findings revealed that there were significant differences in the genetic diversity between populations of S. maritima from coastal and inland areas. This suggests that the addition of anthropogenic salt sites may have a facilitative effect on gene flow in inland populations of saline plants [S. maritima. These polymorphic markers were also found to be cross-amplifiable across related species, such as S. glauca and S. salsa. Of the 12 markers, 11 were shown to be reproducible and effective for conducting genetic analyses of Suaeda populations [Suaeda species suggests moderate to high levels of genetic diversity within populations and variable levels of diversity among populations. The genome of S. aralocaspica, comprising 452 Mb, has been sequenced to provide a data base for the analysis and development of SSR markers for S. aralocaspica and even the genus Suaeda [There have been limited research efforts focused on exploring the genetic diversity of  species ,23. This markers . In a ste plants . Prinz , followed by AT/AT (10.08%), AAAT/ATTT (2.85%), AAAAT/ATTTT (0.54%), and AACAAT/ATTGTT (0.15%). Among all the repeat motifs, di-, tri-, and tetranucleotide repeats were found to be the most prevalent types, while the proportion of five- and six-nucleotide repeats was considerably smaller, accounting for only 3.79% of the total 309 nucleotide repeats  in the S. aralocaspica populations was found to be the highest, at 0.654. On the other hand, the genetic identity between Fukang-Shawan and Fukang-Shihezi pairs was lower, at 0.438 and 0.548, respectively , Solanum melongena (120 SSRs/Mb), and Triticum aestivum (36.68 SSRs/Mb) [S. aralocaspica. Dinucleotide and trinucleotide repeats were the most common SSRs in the genome of S. aralocaspica, similar to Tartary buckwheat [S. aralocaspica (75.74%).After performing the analysis, we discovered that the frequency of SSRs in SSRs/Mb) ,28,29. Tuckwheat . HoweverS. aralocaspica using 38 pairs of SSR primers developed for various populations. We found that the expected heterozygosity (He) and Shannon’s information index (I) values for the three populations ranged from 0.288 to 0.805 and 0.642 to 1.085, respectively. A comparison of our results with those obtained for other species, such as S. maritima  [S. corniculata subsp. mongolica (I = 0.1688), S. “jacutica” (I = 0.0878), and S. corniculata s. str [Nuphar submersa (He = 0.42), Pedicularis kansuensis , Ruta oreojasme (He = 0.687), Vincetoxicum atratum (He = 0.67), Ammi seubertianum , Ammi trifoliatum , and Tapiscia sinensis , revealed some variation in values [In this study, we examined the genetic diversity of  = 0.97) , S. corna s. str . Nuphar n values ,34,35,36S. aralocaspica populations from three distinct regions revealed differences in their genetic diversity. Specifically, the genetic diversity of S. aralocaspica populations in Fukang was significantly greater than that of populations in Shihezi and Shawan. This may be due to the different habitats of the three populations. For instance, the S. aralocaspica population in Fukang is located near a protected reservoir, making it less susceptible to human activities and boasting relatively stable conditions. It also has a larger habitat area and population size compared to those in Shihezi and Shawan. Conversely, the S. aralocaspica populations in Shihezi and Shawan are more frequently impacted by human activities and experience greater environmental volatility. This may explain the significant differences in genetic diversity observed between the three populations.The genetic diversity analysis of S. aralocaspica populations. Our findings revealed that the S. aralocaspica populations of Shihezi and Shawan had the closest geographic distance and the highest genetic identity. Conversely, the Fukang and Shawan populations showed the greatest geographic distance and the lowest genetic similarity. These results indicate an inverse relationship between genetic identity and geographic distance among the three S. aralocaspica populations. This suggests that geographic distance may play a vital role in influencing gene flow among different S. aralocaspica populations.In this study, we compared the genetic identity and actual geographic distance of three distinct S. aralocaspica indicate greater genetic differentiation, with mean Fst values above 0.25. This suggests that S. aralocaspica may have undergone local adaptation due to high selection pressure, which can occur even in the presence of high levels of gene flow, according to Endler et al. [S. aralocaspica [Gene flow has a reducing effect on genetic differentiation between populations, particularly where gene flow is greater than 1 number of migrants (Nm). However, when Nm is less than 1, local differentiation between populations tends to occur. Despite this, the collected samples of r et al. . In combocaspica . FactorsS. aralocaspica, its monoecious annual nature and inbreeding coefficients exceeding 0.5 in all three populations suggest a likelihood of more pronounced inbreeding. Further analysis is necessary to determine the exact mating system. Mating among close relatives in small populations often happens out of necessity and results in high inbreeding coefficients and a decline in genetic diversity [S. aralocaspica populations exhibit high genetic diversity and this may be attributed to natural or anthropogenic factors that have caused severe habitat fragmentation and a significant reduction in population size, with the small populations inheriting a fraction of the genetic variation from the original large populations. Further investigation is needed to establish the exact causes of this phenomenon.Heterozygous species typically exhibit greater genetic diversity than self-incompatible species ,40. Althiversity . S. aralS. aralocaspica , 17 individuals from Shihezi , and 18 individuals from Shawan ) in July 2021 from Xinjiang, China. Fresh leaves of S. aralocaspica within different habitats were collected using the quadrat method. After collection, the samples were carefully wrapped in tinfoil and preserved in liquid nitrogen to maintain their freshness. Subsequently, the plant materials were stored in an ultra-low-temperature refrigerator at −80 °C until they were utilized for subsequent experiments.The 52 fresh plant samples utilized were obtained from three distinct populations of S. aralocaspica, obtained from the open access data of NCBI (with project registration number PRJNA428881), as a basis for developing a set of SSR primers with high polymorphism. In order to achieve this, our study considered microsatellite markers with a standard size of 2–6 bp, excluding single nucleotides. To determine the microsatellite loci, the MISA software was utilized, focusing on nucleotide microsatellites with a minimum repeat number of 4. We then used Primer 3 software to design primers specific to flanking genomic sequences based on the read parameters of the microsatellite regions. The expected amplicon length of our design ranged from 100 to 300 bp.This study utilized whole genome sequencing results of S. aralocaspica plant material was extracted using the DNAsecure Plant Kit , following the manufacturer’s guidelines. From all genomic SSRs, 100 candidate primer pairs were randomly selected based on the minimum lengths of 14, 18, and 20 bp for di-, tri-, and tetranucleotide repeats [2O 9.5 μL. The amplification reaction procedure consisted of three stages: pre-denaturation at 94 °C for 3 min in the first stage and, in the second stage, 30 cycles of denaturation at 94 °C for 30 s, annealing at 58 °C for 30 s, and extension at 72 °C for 30 s. Successful amplification was confirmed by analyzing at least eight or more of the ten individuals’ bright bands using 2% agarose gel electrophoresis. Alleles (.FSA) generated after the PCR amplification experiment were analyzed using GeneMarker v2.2.0  genotyping software. Primers with good polymorphism were selected for amplification of the collected S. aralocaspica population material by data analysis, followed by analysis of the amplification results.Genomic DNA from  repeats ,43, respS. aralocaspica samples using Mega6 [Various genetic diversity indices were computed using different software packages. Popgene 32 , Cervus ng Mega6 . Principng Mega6 .S. aralocaspica, this study has successfully developed a large set of polymorphic microsatellite markers that can be used for the genetic diversity analysis of halophyte S. aralocaspica. The results of the genetic diversity analysis showed that the populations of S. aralocaspica had moderate levels of genetic differentiation and high levels of genetic diversity within each population. The microsatellite markers developed in this study provide a valuable tool for future population genetics studies and conservation efforts, not just for this species but also for other Suaeda species. Overall, this study highlights the importance of genetic diversity analysis in understanding the adaptive potential and conservation of halophyte species in changing environments.Based on the sequencing of the whole genome of


Mytella strigata is a highly adaptable invasive alien species that has been established in coastal China since 2014. Mitochondrial DNA (mtDNA) is an important tool for studying the evolution and population genetics of invasive species. In this study, the mitochondrial genome of M. strigata from China was sequenced by Illumina high-throughput sequencing and characterized with 13 protein-coding genes (PCGs). By assessing the selective pressure of 13 PCGs, the nad2 gene had the fastest evolutionary rate and was finally selected for population genetic analysis. A total of 285 nad2 sequences from seven M. strigata populations in China were analyzed and showed obviously T-rich and C-rich characteristics. According to population genetic diversity analysis, all the seven populations had haplotype (gene) diversity (Hd) ≥ 0.5 and nucleotide diversity (Pi) < 0.005. Haplotype networks showed a “star” distribution. Population historical dynamic analyses showed that Fu’s Fs and Tajima’s D values of all populations were negative except the Qukou (QK) and Beihai (BH) populations. The Zhangzhou (ZJ) and Xiamen (XM) populations were unimodal while the other populations were multimodal. These results suggested that the population of M. strigata in China may have passed the bottleneck period and is currently in a state of population expansion. Mytella strigata  ), a marine invasive bivalve [M. strigata is mainly transmitted over long distances through human activities such as ships’ ballast water, while ocean currents and coastal currents promote its spread in a small range [Perna viridis  [Along with the global shipping industry’s vigorous development, invasive marine species are more likely to be introduced into new environments where they begin to establish a population . The est bivalve ,8. Studill range . Its strll range . Moreoveus,1758) . The ecous,1758) . At the us,1758) . This cous,1758) . TherefoRuditapes philippinarum  [Mytilus galloprovincialis  [M. strigata were also shown to possess atypical DUI, as M-COI was found in the adductor muscle [Mitochondrial DNA (mtDNA) is an important tool in researching evolution and population genetics of invasive species due to its relatively high mutation rate and apparent simplicity of maternal inheritance . In moste, 1850)  and Mytik, 1819) . In prevr muscle ,22. Becar muscle ,22. At tr muscle  and as aM. strigata from China. Selective pressure was analyzed on a mitochondrial protein-coding gene (PCG) to choose the best mitochondrial marker for population genetic analysis. Then, the population genetic diversity and population history dynamics of seven populations of M. strigata in coastal China were carried out. The aim of this study was to (1) select more suitable mitochondrial PCGs for population genetic analysis, (2) evaluate the invasive status of M. strigata populations in coastal areas of China, and (3) provide molecular biological data for assessing the expansion and determine the need for control measures of M. strigata.Here, Illumina high-throughput sequencing was performed on the mitochondrial genome of M. strigata according to the morphological descriptions , Beihai (BH), Shanwei (SW), Zhangzhou (ZZ), Qukou (QK), Gangbei (GB), and Xiamen (XM) , Table 1riptions  [10,11,2https://www.ncbi.nlm.nih.gov/orffinder, accessed on 13 October 2023), and then they were corrected manually and annotated by comparison with the previous mitochondrial genomes of M. strigata (Genbank accession nos.: MT800514 and MT991018).One sample from ZJ was chosen for mitochondrial genome sequencing. Total DNA was extracted from the adductor muscle using a TIANamp Marine Animals DNA kit  according to the reagent instructions. The genomic library was constructed with the whole-genome shotgun approach and sequenced on the Illumina NovaSeq platform  at Shanghai Personal Biotechnology Co., Ltd. using the 2 × 150 bp paired-end sequencing mode. A5-miseq v20150522 software  and SPAdM. strigata. Based on the selective pressure results, the PCG with highest variation, nad2, was selected as the marker gene for genetic analysis.PhyloSuite v1.2.2 software was employed to perform the preparation of the PCG sequences from mitochondrial genomes sequenced in this study . The remnad2 gene: forward primer 5′-GGTGATAAGAATAATAATAAGACCTTTG-3′, reverse primer 5′-CCACTCTTATGACCACTATTATC-3′. The PCR reaction mixture contained 0.5 µL of each primer, 1.0 µL of DNA, 12.5 µL of 2× Taq PCR MasterMix , and 10.5 µL of ddH2O in a total volume of 25 µL. The PCR procedure involved initial denaturation at 95 °C for 3 min; 32 cycles of 95 °C for 30 s, 48 °C for 1 min, and 72 °C for 1 min; and a final extension at 72 °C for 5 min. Finally, agarose gel electrophoresis was used to detect the purity of PCR products and the Applied Biosystems 3730xl Genetic Analyzer  was used for sequencing.The total DNA of individuals from all seven populations was extracted from the adductor muscle using a TIANamp Marine Animals DNA kit . Then, PCR primers were designed using primer premier v5.5.0 software for the mitochondrial nad2 gene sequence. DnaSP v6.12.03 [h), number of polymorphic (segregating) sites (S), haplotype (gene) diversity (Hd), nucleotide diversity (Pi), and the average number of nucleotide differences (K) of nad2 sequences from the seven populations. MEGA v7.0.26 software was used to align and evaluate the inter- and intra-population genetic distances of nad2 sequences from the seven populations with the Maximum Composite Likelihood model. The software of Arlequin v3.5 was used to perform the analysis of molecular variance (AMOVA) of the populations. PopART v1.7 [FST) of inter-population and its significance, as well as Tajima’s D and Fu’s Fs, were also calculated using Arlequin v3.5 [MEGA v7.0.26 software was employed to analyze the base composition and sequence variation of the v6.12.03  softwareART v1.7  and ArleART v1.7  were useuin v3.5 . Finallyuin v3.5  software12s and 16s), 22 tRNA genes, and 13 PCGs, including atp6, cox1, cox2, cox3, cytb, nad1, nad2, nad3, nad4, nad4l, nad5, nad6, and atp8.The mitochondrial genome measured in this study had a double-stranded circular structure, with GenBank accession No. OR666116. The mitochondrial genome consisted of 2 rRNA genes  and 31 polymorphic (segregating) sites were charactered (h and 19 S) had the most haplotypes and polymorphic (segregating) sites, while the BH population (7 h) and QK population (9 S) had the fewest haplotypes and polymorphic (segregating) sites, respectively. The Hd, Pi, and K of all populations were 0.869, 0.00384, and 2.652, respectively. Similarly, the ZJ population had the highest Hd (0.898), Pi (0.00403), and K (2.783). The difference was that the BH population had the lowest Pi (0.00301) and K (2.077), while the GB population occupied the lowest Hd (0.712).All 285 ractered . Among tM. strigata is shown in p < 0.05). In QK-ZJ (0.07061), QK-BH (0.05826), QK-SW (0.07391), QK-GB (0.13784), and GB-XM (0.14683), there was a moderate genetic differentiation (0.05~0.15) (p < 0.05). The results of AMOVA  and the mismatch distribution analysis (p > 0.05). The mismatch distribution of the BH, ZZ, QK, and GB populations showed bimodal or multimodal distribution. In addition, the Tajima’s D values of the QK population were positive, while those of other populations were negative. There were no statistically significant values of Tajima’s D test in all populations (p > 0.05).The results of the neutrality test  showed tanalysis  showed tM. strigata belongs to, is faster than that of other infraclasses in bivalves [cox1 tend to have more genetic diversity than the nuclear genes such as its1 [M. strigata taken from coastal areas of China and 13 PCGs were identified. Selective pressure analysis showed that the selective pressure of all 13 PCGs was Ka/Ks < 1, indicating that all the PCGs are subject to purifying selection. Purifying selection acts to weed out harmful mutations from the population and helps maintain the fitness of the species [nad2, suggesting that nad2 is subject to the least selective pressure and has the highest variation. Therefore, the nad2 gene was selected as the most appropriate genetic marker to analyze the population genetics of M. strigata. The only molecular marker used in the previous population genetic analysis of M. strigata was cox1 [cox1, the nad2 gene has no sex-related haplogroup, which is the second reason it was chosen.Compared to the more conserved nuclear genome, the mitochondrial genome has a faster rate of genetic mutation. In primates and mollusks, the mutation rate of mtDNA genomes is about 5–10 times and 4 times than nuclear DNA, respectively ,35. In bbivalves . On the  as its1 ,37,38. D as its1 . Therefo species . The maxwas cox1 ,22. Howenad2 gene of M. strigata. The result showed a CG bias. Base bias is a characteristic of sequence evolution, which may result from natural mutation [nad2 occurs mostly between a purine and a purine or between a pyrimidine and a pyrimidine.In this study, the A + T base content was slightly lower than the G + C base content in the mitochondrial mutation . Althougmutation , the nucmutation . Meanwhimutation . In genemutation . In the Hd ≥ 0.5 and Pi < 0.005, suggesting that M. strigata has crossed the bottleneck effect in coastal China [M. strigata in China began around 2014 [M. strigata in China had experienced or was currently experiencing a population bottleneck during 2020~2021 [M. strigata in 2023 is in the stage of population expansion after the bottleneck effect. The phenomenon of the population expansion of M. strigata in China could also be seen in practical production. In 2019, a survey revealed that M. strigata has been present in farming ponds of Meretrix petechialis  in Taiwan and caused serious impact [M. strigata was found attached to an oyster farming facility in Hainan [M. strigata surpassed that of the native species P. viridis in Donghai island [M. strigata was first found in mainland China, has the highest genetic diversity. This corresponds to the greatest genetic distance within the ZJ populationIn the results, all the seven populations had al China . It is cal China . The invund 2014 . Zuo et 020~2021 , and this impact . In 2020n Hainan . In 2022nad2 sequences, the genetic distance between populations of M. strigata ranged from 0.00328 to 0.00467. The genetic distance between the BH population and the XM population was the nearest, indicating a closer relationship [M. strigata was mainly from within the population rather than between the populations. This was also evidenced by genetic differentiation. It is generally believed that genetic differentiation between populations is small, moderate, and larger when STF is 0~0.05, 0.15~0.25, and 0.15~0.25, respectively [M. strigata began to expand after experiencing bottleneck [Based on tionship , while tectively . Except ectively . The “stttleneck . HoweverNeutrality tests and mismatch distribution are two effective tests to study the historical dynamics of populations . A populnad2 was ultimately selected as the best mitochondrial marker for population genetic analysis by assessing the selective pressure of 13 mitochondrial PCGs. Population genetic analysis showed that the seven M. strigata populations in China could be expanding after the bottleneck. Among them, recent expansion and sustained growth events had occurred in the ZJ population. Therefore, relevant measures, including removal  and utilization (human food and feed), need to be taken to prevent the formation of large and stable invasive populations of M. strigata in the future.In this study, gene