Genomic studies in forest trees have long been hampered by the lack of high-quality genomics resources and affordable genotyping methods. This has dramatically changed in the last few years; the conference impressively showed how such tools are now being applied to study past demography, adaptation and interactions with associated organisms. Moreover, genomic studies are now finally also entering the world of conservation and forest management, for example by measuring the value or cost of interspecific hybridization and introgression, assessing the vulnerability of species and populations to future change, or accurately delineating evolutionary significant units. The newly launched conference series of EvolTree will hopefully play a key role in the exchange and synthesis of such important investigations.Rapid human-induced environmental changes like climate warming represent a challenge for forest ecosystems. Due to their biological complexity and the long generation time of their keystone tree species, genetic adaptation in these ecosystems might not be fast enough to keep track with conditions changing at such a fast pace. The study of adaptation to environmental change and its genetic mechanisms is therefore key for ensuring a sustainable support and management of forests. The 4-day conference of the European Research Group EvolTree (The online version contains supplementary material available at 10.1007/s11295-022-01542-1. Forests represent key ecosystems world-wide. They cover an estimated 30% of the Earth’s land surface, they harbour tremendous biodiversity at all levels  and play a prominent role in the global water and chemical cycles, notably carbon. Not the least, forests are economically important for their wood and non-wood products, for protection of infrastructure and for recreation, and as such they fulfil manifold functions for human well-being.https://www.evoltree.eu) has widely contributed to various aspects of forest genomic research. This self-supporting network of research institutes across mostly European countries has recently launched a new conference series to address a broad palette of topics in the context of genetic and genomic research in forest ecosystems, be it at the level of single species, communities or trophic interactions. The inaugural conference of this series was held at the Swiss Federal Research Institute WSL, Birmensdorf, in mid-September 2021, entitled “Genomics and Adaptation in Forest Ecosystems”. Under the restrictions given by the COVID-19 regulations, the conference organizers were challenged by establishing a hybrid event, allowing both on-site and online participation. This format enabled scientific exchange and personal contacts even across continents and the opportunities for interaction given by this conference were well received by the 132 participants from 27 nations. Over 4 days, the six topical sessions with 34 oral presentations and 23 posters .In recent years, genomic research has made tremendous progress in studying patterns and processes to elucidate aspects of evolutionary biology at several spatial and temporal scales. Among many others, the European Research Group EvolTree  studies or are associated to adaptive phenotypic variations using genome-wide association studies (GWAS). An example of the former was provided by Jill Sekely  that identified the main climatic drivers of adaptation of Nothofagus pumilio along a 2000-km latitudinal transect in the Andean. Domitille Coq--Etchegaray  used a GWAS on metabolomics data to evidence that micro-characters, such as leaf specialized metabolites that are notably involved in response to abiotic stress, can have an oligogenic architecture in sessile oak (Quercus petraea). Gaining insight into the relationships between genotypes, phenotypes and environments can help refine predictive models of species distribution under various climate change scenarios. Brandon Lind  compared the performances of various models of genetic offset by confronting their predictions with actual data from extensive common gardens of jack pine (Pinus banksiana) and Douglas fir (Pseudotsuga menziesii).John Kelly  opened the session by presenting a new approach to predict allele frequency change in natural populations using a model incorporating fitness-effect-estimates from millions of markers in the short-lived model plant Pinus brutia and Pinus halepensis resist drought better than their parental species.Species share not only environment but also history and a still open question is the extent of convergent adaptation. Pooja Singh  investigated such a question by comparing the genomic signatures of adaptation to the same climate variables in eight coniferous species from two continents. Genomic studies have also evidenced the extent of hybridization between sister species or ecotypes that can also allow for the introgression of adaptive alleles as shown by Rakefet David-Schwartz : Hybrids between To conclude, elucidating the relationships between the genomic level and higher levels of organization with the environment is of paramount importance to understand, or even predict and anticipate the impact of climate change on forest trees. Practical outcomes of climate change genomics notably include the development of genomically informed conservation and breeding strategies.Dothistroma needle blight in North American pine forests indicates spatial patterns of genotype–genotype–phenotype interactions, the knowledge of which might help predicting disease outbreaks in future climate as well as managing forests using assisted migration.Organisms do not live and evolve in isolation, but interact with various living beings of their own and other kinds throughout their life histories. Long-lived trees as the foundation species of forest ecosystems provide a matrix of resources and habitats for associated organisms, with interactions ranging from beneficial to detrimental. The session “Genomics of interactions” addressed these complex interplays at the intraspecific and inter-kingdom levels and at diverse spatial and temporal scales. At the intraspecific level, Matthieu Tiret  discussed implementing group selection in tree breeding programs, because intraspecific competition of neighbouring trees proved to affect stand performance. At the interkingdom level, focusing on the mycorrhizal symbiosis, the keynote of Annegret Kohler  highlighted how symbiotic lifestyle and interaction with host plants have shaped fungal genomes and transcriptomes. Besides a reduction in plant cell wall-degrading genes as a consequence of symbiosis, a heterogenous set of conserved genes that predate mycorrhizal evolution as well as new, lineage-specific genes were independently adopted for symbiosis function in diverse fungal lineages. This talk also showed that genes expressed in symbiosis setup seem not to point towards a mutualistic relationship, but rather resemble pathogenic interactions. For example, effector-like proteins are secreted also by mutualists and interfere with signalling pathways to reduce the hosts’ defence reactions. An elegant approach of finding the genetic basis of ectomycorrhizal traits was presented by Benjamin Dauphin . Progenies of a single fungal fruitbody interacting with a poplar clone revealed wide variation in phenotypic traits such as the proportion of roots colonized, ranging from incompatible to fully compatible strains. Transcriptome data from symbiotic tissues supported these strain-specific differences, and GWAS analyses are underway to detect responsible gene variants. Similarly, Isacco Beritognolo  presented an extreme-phenotype GWAS identifying genetic determinants that underlie the resistance of sweet chestnut to one of its most damaging pests, the Asian chestnut gall wasp. Such studies may assist in the genetic improvement of chestnut and development of effective methods to control this parasite. Renate Heinzelmann  finally made clear that not only genetic variation in host trees and associated organisms, but also the environment determines the outcome of plant–pathogen interactions. This session addressed the question of how past geological and ecological changes have affected the genetic diversity of forest trees at the molecular level. The answer, as highlighted by the presentations, is that the effect of past changes in habitat and distribution will depend on the spatial, temporal and phylogenetic scale. The presentations covered time scales from millions of years to just a few generations, from continental to local scale, and from tropical to boreal regions.Genome-wide methods are currently used in a large variety of tree species, such as exome capture of hundreds of genes across a whole subgeneric clade, across a large part of coding genes  or even the whole genome . Moving from organellar markers to large amounts of nuclear loci has also improved the spatial and temporal resolution of demographic analyses of forest tree species.Berlinia clade (Fabaceae) and resulted in several independent shifts from forest to savanna habitat . At the species level, there are indications of past population growth, e.g. in the widely distributed Pinus sylvestris, during the past million years and after the last glacial maximum . On the other hand, in species with a more restricted distribution and niche, like Pinus cembra, the current speed of change seems more rapid than the capacity of genomic change, and there is a risk of non-adaptedness over a short time scale  was that especially in compact genomes, inference of demography alone, without accounting for negative background selection in linked sites, easily results in mis-inference of population growth. The proposed solution is the joint inference of both demographic and selection parameters, e.g. using approximate Bayesian computation. In many tree species, this may be challenging because fragmented reference genomes limit the acquisition of informative linkage disequilibrium estimates and other statistics on physical proximity of different loci and genes. However, as genome assemblies get better with long-read sequencing techniques, this may be a passing problem.Studying the genomic basis of adaptation and understanding the dynamics of adaptation in times of climate change poses many challenges to forest geneticists due to the high complexity at the phenotypic and genomic level in many tree species. In this session, novel approaches for some of these challenges were presented. The keynote speaker Katie Lotterhos  discussed a new methodology to address covariance between genotype and environment, which is a result of the joint variability between genotypic and environmental effects on phenotypes. Moreover, she highlighted how genetic architecture and demography can result in the evolution of phenotypic clines without clines in causal allele frequencies. This suggests that commonly used methods to study GEA may be limited in their ability to discover the genetic architecture of adaptation.https://github.com/piyalkarum/rCNV) that allows running the whole workflow from the .vcf file to the detection of duplicates.Piyal Karunarathne  presented a statistical approach to detect and quantify copy number variations (CNVs), building on the HDplot approach previously introduced by McKinney et al. . He implSandra Cervantes  discussed the possibility that selection might affect genes differently when they are predominantly expressed in haploid vs. diploid tissues. For her study, she focused on the haploid conifer megagametophyte. While here results indicated that purifying selection is more effective in haploid tissue, she could not detect the expected reduced diversity of genes predominantly expressed in the megagametophyte  as potential candidates for redundancy in such integrative approaches that could negatively impact prediction accuracy.Using genomic data to predict a tree phenotype is a vital research field with high relevance for tree breeding. Abdou Rahmane Wade  presented a new approach that integrates genomic and gene expression data to predict tree phenotypes in Pinus pinaster  presented an approach that allows the study of selective mortality in large cohorts and shows that allele frequency changes occur during the period of high juvenile mortality in Since trees also pose challenges at the phenotypic level, individual-level data derived from tree rings are currently discussed as sources for descriptors of the tree’s reaction to past environmental stressors. Melania Zacharias  used tree-ring and climatic data to identify years during which trees suffered notably from summer drought, and she was able to identify a set of single-nucleotide polymorphisms (SNPs) shared among trees with similar reaction to drought.Picea omorika) illustrated the utility of genetic knowledge for practical conservation. Based on the patterns of genetic variation, a 10-year program was launched to save both the species and its genetic resources in face of impending dieback. This program, developed by scientists and conservation managers, has irregular funding through projects, a common problem that hinders long-term conservation efforts for both genetic resources and tree species as a whole.This session addressed the link between genetics, genomics and environment and the conservation of forest genetic resources. An inspiring keynote by Jelena Aleksič  on the Balkan endemic Omorika spruce  stressed in her talk. These measures can increase the richness of forest genetic resources, which in turn leads to a higher adaptive potential to environmental changes . Therefore, a network of sites is needed for in situ conservation of genetic resources, complemented by ex situ stands. In Europe, these are called gene conservation units and form the backbone of forest genetic resource conservation , and maternal effects can influence early fitness of Pinus sylvestris, with better survival strongly correlated with higher seed mass . Tree physiology, habitat and history must also be considered as exemplified for relict oak populations in Germany .Knowledge of patterns of genetic variation is crucial for the efficient use and conservation of forest genetic resources. However, there are still many open questions, e.g. about relevant evolutionary and ecological processes or related to species-specific selection pressures . In this session, we heard some answers: soil variation may play an important role in The session provided valuable insights into relevant research questions that need to be further addressed for effective conservation and use of forest genetic resources. It became clear that this cannot and should not be separated from forest management and the environment, while at the same time it is necessary to ensure a massive commitment of funding to obtain the knowledge needed and apply it on the ground.Pinus pinaster  opened the session with an enlightening keynote on how genomics can improve predictions of forest tree population response to climate change, exemplifying this in the case of a clonal trial of Pseudotsuga menziesii). These results will provide a basis to support future seed transfer and breeding strategies. Focusing on another North American conifer, red spruce (Picea rubens), Susanne Lachmuth  demonstrated how standardized genomic offsets can be used to inform climate-smart seed transfer. In particular, she illustrated how the presented AGF approach can maximize the representation of within-species adaptive genomic variation, thus increasing forest resilience in the face of climate change.Such trials are useful not only for addressing adaptive variation, but also for elaborating assisted gene flow (AGF) and breeding programs under changing climatic conditions. Based on a GWAS study, Rafael Candido Ribeiro  provided insights into the genetic basis of drought and cold stress hardiness in Douglas fir . In the case of the European sessile (Quercus petraea) and downy oak (Q. pubescens), highly informative sets of SNPs enable accurate species identification and assessment of genetic introgression. Oliver Reutimann  showed that not only species composition, but also the degree of admixture between these two interfertile species can be predicted using environmental and topographic variables. In the last talk of the session, Lucian Curtu  reported about genetic differentiation of the two subspecies Q. robur ssp. robur and ssp. pedunculiflora. Results suggest an adaptation of ssp. pedunculiflora to xeric site conditions. Both case studies with oaks emphasized the importance of understanding the dynamics of adaptive introgression in the context of climate-smart forestry.Provenance and taxonomic identification represent another application field where advances were made possible with the use of genetic and genomic tools. Due to this progress, analysis of thousands of SNP loci is feasible and has greatly improved origin assignment of forest reproductive material (FRM), as shown in the example of the Western Mediterranean In recent years, continuously growing genomic resources have enabled advances in studying forest ecosystem adaptation. New statistical and computational tools have been developed, while a large number of case studies have improved our understanding of evolutionary dynamics in forest ecosystems. The great variety of contributions in the conference reflected the progress made. As shown by the large interest in this EvolTree conference, the community is growing and genomics is finally a well-established part of forest science. Moreover, genomics is now also prominent among application-oriented studies, whether these focus on conservation or management.The above-described progress is obvious from previous reports on forest genomic conferences that have taken place in Europe. Around a decade ago, knowledge on candidate genes for adaptive traits made it possible to integrate genomics in studies of evolutionary response of forest trees to climate change . In these genera, considering a species as a fixed evolutionary unit is most likely not purposeful in view of climate-driven dynamics, because adaptive introgression from a sister species might actually facilitate adaptation to a changing environment. Hybridization and introgression will therefore be important topics in future research of climate change genomics.Genomics has become an integral part of application-oriented studies, as highlighted in the last two conference sessions. Both in conservation and forest management, the application of genomics greatly improves the resolution in identifying population structure, provenances or conservation and management units. Given the current developments, it is expected that genomics will increasingly support schemes for seed selection, assisted gene flow and adaptive forest management in a changing climate.This inaugural meeting of the new EvolTree conference series attracted a large number of participants and covered a wide range of aspects related to genomics and adaptation of forest ecosystems. It filled an important gap of interaction possibilities caused by the COVID-19 pandemic and we hope that it will stimulate further research in this dynamically developing research area.ESM 1(XLSX 13.9 KB)


Fst heatmap, the Heishuiguo population shifted from Southern-Northern Han cline to Northern-Northwestern Han/Hui cline with time, indicating genetic admixture between Yellow River immigrants and natives. By comparison, in maternal mtDNA views, the Heishuiguo population was closely clustered with certain Mongolic-speaking and Northwestern Han populations and exhibited genetic continuity through the Han Dynasty, which suggests that Heishuiguo females originated from local or neighboring regions. Therefore, a sex-biased admixture pattern is observed in the Heishuiguo population. Additionally, genetic contour maps also reveal the same male-dominated migration from the East to Hexi Corridor during the Han Dynasty. This is also consistent with historical records, especially excavated bamboo slips. Combining historical records, archeological findings, stable isotope analysis, and paleoenvironmental studies, our uniparental genetic investigation on the Heishuiguo population reveals how male-dominated migration accompanied with lifestyle adjustments brought by these eastern groups may be the main factor affecting the subsistence strategy transition along the Han Dynasty Hexi Corridor.The Hexi Corridor was an important arena for culture exchange and human migration between ancient China and Central and Western Asia. During the Han Dynasty (202 BCE–220 CE), subsistence strategy along the corridor shifted from pastoralism to a mixed pastoralist-agriculturalist economy. Yet the drivers of this transition remain poorly understood. In this study, we analyze the Y-chromosome and mtDNA of 31 Han Dynasty individuals from the Heishuiguo site, located in the center of the Hexi Corridor. A high-resolution analysis of 485 Y-SNPs and mitogenomes was performed, with the Heishuiguo population classified into Early Han and Late Han groups. It is revealed that (1) when dissecting genetic lineages, the Yellow River Basin origin haplogroups  reached relatively high frequencies for the paternal gene pools, while haplogroups of north East Asian origin  dominated on the maternal side; (2) in interpopulation comparison using PCA and  Human history can be seen as a history of dealing with new challenges caused by changes of factors including resource distribution and social relationships. To overcome them, human beings have been using extrasomatic ways, including subsistence-, socio-, and ideo-technologies to create new niches for survival . Among tShiji  to the Hanshu  stated that the Hexi Corridor was occupied by nomadic pastoralists  before the Han Dynasty, a claim supported by excavated relics and faunal remains from Shajing culture  and Shanma culture    sites. Tl yr BP) , while sl yr BP) . A wealtl yr BP) . These wl yr BP) , while al yr BP) . This stl yr BP) . This Hel yr BP) , who genl yr BP) . Finallyl yr BP) . We can l yr BP) .Located in an arid climatic transitional belt, the Hexi Corridor is extremely sensitive to changes in its environment. Previous studies have primarily attempted to explain shifting subsistence strategies through the mirror of environmental change . But we 14C dating, tomb morphology and grave good assemblages  and Late Han Dynasty (Phases 3–4), respectively. Heishuiguo individual sex was determined by pelvic  and skulWe extracted DNA from 31 samples using a dedicated aDNA facility at Fudan University, Shanghai, following the established precautions for working with ancient human DNA . NegativPrior to sampling, all samples were irradiated with UV-light for 30 min on each side and wiped with a 5% bleach solution. Teeth and other osseous materials were sandblasted to remove the outer surface before being ground to fine power with a mixer mill . A dense section of temporal bones was cut around the cochlea by first removing the outer part, then grinding the clean inner part into fine powder. A total of 100 mg of bone powder was then used to extract DNA. Pre-lysis methods included the addition of a 1 ml extraction buffer, containing 0.5 M EDTA, 0.25 mg/ml Proteinase K , pH 8.0, after which samples were rotated for 1 hour at a temperature of 37°C. After centrifugation, the supernatant was discarded and 2.5 ml extraction buffer added, followed by overnight rotation at 37°C. We mixed 20 μl magnetic beads  with 12.5 ml binding buffer containing 5 M GuHCl, 40% Isopropanol, 25 mM sodium acetate, and 0.05% Tween-20 , (PH 5.2). We then transferred the supernatant (∼2.5 ml) to a binding buffer/bead mixture prior to the robotic extraction  procedure. At last, the DNA underwent elution through a 50 μl TET buffer .We prepared double-stranded libraries in accordance with Meyer’s protocols , but witTarget enrichment of the mitogenome was performed on each amplified library using a MyGenostics Human Mitochondria Capture Kit  as described by Ancient DNA fragment lengths are generally skewed toward short fragments, the vast majority of which are typically shorter than 100 bp . Furtherhttps://github.com/statgen/bamUtil), we clipped four bases from both ends of each read to avoid an excess of remaining C->T and G->A transitions at the ends of the sequences.For shotgun and mtDNA capture data, we clipped sequencing adapters and merged using sequences by ClipAndMerge v1.7.8 . FollowiThe authenticity of the ancient genome sequence was mainly determined by the combination of two observations of the same specimen. Firstly, deep sequencing of the mitochondrial genome would show that the vast majority of the DNA fragments had come from a single individual. Second, the patterns of DNA degradation , in partFor mtDNA, we employed a log2fasta program implemented in Schmutzi  in orderhttp://isogg.org/) and Y-full (https://www.yfull.com/tree/) databases, and analysis performed in the case of a base and mapping quality exceeding 30. Haplogroup determination was performed with the script Yleaf.py in Yleaf software .Principal component analysis (PCA) was performed using FactoMineR package of R 3.6.3. Reference populations are listed in Y chromosome haplogroups of 30 Heishuiguo males were determined according to the ISOGG’s Y-DNA Haplogroup Tree 2019 . OverallMtDNA haplogroups of 27 Heishuiguo samples were determined based on PhyloTree mtDNA tree Build 17 . DiffereFst) heatmap was also visualized, to further explore population relationships  based on haplogroup frequencies . A genetionships . In thisionships  shows a ionships  reveals ionships . Our Earionships , suggestionships , mirroriIn summary, an interpopulation comparison reveals that the Heishuiguo population shows close affinity with Han Chinese in terms of paternal structure and Mongolic and Northwestern Han populations in terms of maternal structure. This is a clear indication of sex-biased population admixture.The above-mentioned PCA plot shows the eastern and western population cline according to PC1. We can make further use of PC1 values to generate genetic contour maps  and furtMultiple lines of evidence  have demonstrated how subsistence strategies along the Hexi Corridor shifted from a nomadic economy to mixed economy  from the Han Dynasty ; Li 2021Fst heatmap) with reference populations , we have been able to show closer paternal genetic affinity with Northern Han and Hui populations among the groups at Heishuiguo. Via PCA, we observed genetic structure changes from Southern-Northern Han cline to Northern-Northwestern Han/Hui cline with time  at an overall rate of over 50%, along with southern East Asian origin haplogroups (O1a and O1b) at ∼20% and northern East Asian origin haplogroups  at ∼30%. The matrilineal Heishuiguo population consisted of northern East Asian haplogroups , which accounted for ∼62.95%, alongside southern East Asian haplogroups  at 18.52%. By way of interpopulation comparisons (PCA and ith time , indicatith time , the Hanith time . Our vieith time , howeverith time , where mith time  people. In this study, by means of a uniparental genetic analysis, we have observed a male-dominated admixture event occurring during this period, one additionally supported by historical records and archaeological findings. That shifting subsistence strategy along the Hexi Corridor residents that kept pace with human migration cannot be coincidental. Mass migration of individuals and transplantation of subsistence lifestyles would have impacted the former subsistence strategy in Hexi Corridor during the Han Dynasty. This study provides new insights and possibilities into how population admixture serves as a key factor in changes of subsistence strategy.


Anopheles stephensi in the Horn of Africa (HOA) raises concerns about the impact of this mosquito on malaria transmission in the region. Analysis of An. stephensi genetic diversity and population structure can provide insight into the history of the mosquito in the HOA to improve predictions of future spread. We investigated the genetic diversity of An. stephensi in eastern Ethiopia, where detection suggests a range expansion into this region, in order to understand the history of this invasive population.The recent detection of the South Asian malaria vector COI) and cytochrome B gene (CytB) in 187 An. stephensi collected from 10 sites in Ethiopia in 2018. Population genetic, phylogenetic, and minimum spanning network analyses were conducted for Ethiopian sequences. Molecular identification of blood meal sources was also performed using universal vertebrate CytB sequencing.We sequenced the cytochrome oxidase subunit I  relative to the southeastern sites  in eastern Ethiopia. We observed population differentiation, with the highest differentiation between the northeastern sites compared to central sites  and the southeastern sites. Phylogenetic and network analysis revealed that the HOA An. stephensi are more genetically similar to An. stephensi from southern Asia than from the Arabian Peninsula. Finally, molecular blood meal analysis revealed evidence of feeding on cows, goats, dogs, and humans, as well as evidence of multiple (mixed) blood meals.Six An. stephensi is genetically diverse in Ethiopia and with evidence of geographical structure. Variation in the level of diversity supports the hypothesis for a more recent introduction of An. stephensi into southeastern Ethiopia relative to the northeastern region. We also find evidence that supports the hypothesis that HOA An. stephensi populations originate from South Asia rather than the Arabian Peninsula. The evidence of both zoophagic and anthropophagic feeding support the need for additional investigation into the potential for livestock movement to play a role in vector spread in this region.We show that The online version contains supplementary material available at 10.1186/s13071-021-05097-3. Anopheles) that transmit the malaria parasite, Plasmodium spp. Previous studies have shown that the movement of Plasmodium strains from one region to another can have serious population health consequences, such as the emergence of antimalarial resistance [Plasmodium strains have typically centered on the movement of their human hosts as carriers of the strains, especially asymptomatic individuals who act as reservoirs for Plasmodium transmission . With ta et al. , and giva et al. –8, invesPlasmodium falciparum and Plasmodium vivax [Anopheles stephensi, which is common in South Asia, was detected in the HOA for the first time in Djibouti [Anopheles arabiensis, the major malaria vector in the HOA, An. stephensi is known to transmit both major malaria parasite species, P. falciparum and P. vivax, and could threaten recent progress in reducing the prevalence of malaria in that area. After additional surveillance, An. stephensi was also detected in the Republic of Sudan and Somalia  and was revealed to have a broader distribution in Ethiopia [An. stephensi may spread to other parts of Africa. With molecular evidence that various Plasmodium strains evolve to be compatible with specific Anopheles species, it was previously unclear whether An. stephensi could transmit local HOA Plasmodium strains. There is now evidence that the HOA An. stephensi can transmit the local strains of P. falciparum and P. vivax in Djibouti [An. stephensi may play in increasing malaria transmission.The Horn of Africa (HOA), comprising Djibouti, Eritrea, Ethiopia, and Somalia, is classified as a malaria-endemic area, with the distinction compared to most other areas in Africa of having substantial transmission of both um vivax . In 2012Djibouti , 10, andDjibouti . PreviouEthiopia  and DjibDjibouti , validatAn. stephensi in the HOA complicates malaria control in the HOA in several ways. Until now, vector control strategies have centered on the detection and elimination of known major vectors like An. arabiensis which exhibit different breeding, feeding, and resting behaviors when compared to An. stephensi. Also, there is evidence of diverse insecticide resistance mechanisms among Anopheles species [An. stephensi in the HOA. The potential threat to progress in controlling malaria led the World Health Organization (WHO) to post a “vector alert” in 2019, characterizing An. stephensi as a “major potential threat,” and calling for enhanced surveillance in Africa [The expansion of  species –17. Given Africa .An. stephensi on malaria in the HOA and the rest of the continent, more information is needed on the pattern of spread of An. stephensi. Analysis of the genetic variation in An. stephensi populations can provide crucial information about the geographical range of the species and the frequency of introductions. Phylogeographic and population genetic analyses of the structure of variation and relationships between newly detected An. stephensi and An. stephensi from long-established populations outside of Africa can provide insight into the evolution of this population in Africa. Initial analysis of the mitochondrial COI  generated from An. stephensi in Kebridehar in eastern Ethiopia and An. stephensi sequence data from collections in South Asia, the Middle East, and the Arabian Peninsula taken from GenBank [An. stephensi sequence from Pakistan. Since the identification of An. stephensi in Ethiopia, this vector has been detected in 10 additional sites in eastern Ethiopia as far north as Semera and as far south as Godey [An. stephensi in Ethiopia. In addition to phylogeographic history, more information on factors that facilitate An. stephensi spread is needed. One potential factor of interest is the host preferences of An. stephensi in the HOA. Pastoralism is a common livelihood in Ethiopia and involves moving cattle, goats, sheep, and camels hundreds of kilometers every season [Anopheles stephensi has exhibited both zoophagic (common livestock species such as cattle) and anthropophagic behaviors in populations in South Asia [An. stephensi feeding preferences in Ethiopia can provide insight into the potential for extensive livestock movement as a vehicle for An. stephensi spread. Here we performed phylogeographic and population genetic analyses of An. stephensi at 10 sites and used sequence barcoding approaches to evaluate hosts on which An. stephensi feeds, to better understand vector movement.In order to better assess the potential impact of  GenBank  identifias Godey . Additioy season . Movemeny season , 21. Resy season , 23. Anouth Asia . Data onCOI and ITS2 sequencing. Overall, a total of 187 mosquitoes were analyzed in this study: 118 wild-caught reared from immatures and 69 wild-caught adults . To confirm amplification of the correct locus, sequences were submitted as queries to the National Center for Biotechnology Information's (NCBI) Basic Local Alignment Search Tool (BLAST) [Molecular analyses of specimens were conducted at Baylor University. Two fication , no genefication  and thussoftware , 30: Cyt (BLAST)  against An. stephensi collection overall and within each site, we calculated the number of polymorphic (segregating) sites (s), number of haplotypes (h), haplotype diversity (H), nucleotide diversity (Pi), and average number of nucleotide differences (k) using the DnaSP version 5 program [Fst (differentiation based on haplotype frequencies only) and Φst (differentiation accounting for genetic distances) in Arlequin version 3.5.2.2 software [Fst, 110 permutations were performed and P-values generated. Significance was set at alpha < 0.00001.To estimate the level of diversity of the  program . Geneticsoftware . To testAn. stephensi found in Ethiopia and to further elucidate the spread of the vector, we also performed phylogenetic analysis of the COI and concatenated COI+CytB An. stephensi sequences generated in this and previous studies.In order to determine the evolutionary relationships between the Alignments were created with MAFFT version 7  and unevCOI sequence data available in GenBank  confirm whether there was detectable vertebrate DNA present in the sample and then (ii) identify the vertebrate host based on querying the NCBI nucleotide sequence database. This primer set can be used to distinguish a broad range of vertebrate species including human, cow, and goat [DNA was extracted from abdomens of 59 wild-caught adult blood-fed and goat   across the sequence that contributed to six distinct COI-haplotypes. All polymorphisms were synonymous mutations. CytB had a single segregating site resulting in two haplotypes. Genetic diversity statistics were generated for each site including number of polymorphic (segregating) sites (s), number of haplotypes (h), haplotype diversity (H), nucleotide diversity (Pi), and average number of nucleotide differences (k)  and Godey in the south was the least diverse . When comparing regions, northern sites had the greatest level of diversity  and the southern sites had the least .We were interested in the number of haplotypes that would be detected in Fst and Φst reveal population differentiation among study sites  was observed between sites in the north and sites in the other two subregions, notably Bati (northern) compared to Kebridehar , Godey , and Erer Gota . Phylogenetic analysis supports population differentiation between the northern and southern sites with bootstraps > 90 for three major clades that carry haplotypes that vary in frequency across these subregions , the Middle East including Iran and the Arabian Peninsula , and the HOA   and COI-Hap2 . The minimum spanning network of the available population COI sequence datasets revealed that COI-Hap1 was the most central node, with the most proximal nodes representing country-specific haplotypes for Ethiopia, Sri Lanka, and Pakistan that differed from the central node by a single nucleotide , lacked the COI-Hap1 haplotype and did not share any haplotypes with Ethiopia or any of the other countries  were confirmed to be blood-fed based on the presence/absence PCR assay for vertebrate DNA. These originated in Semera (n = 27), Erer Gota (n = 4), Gewane (n = 2), Kebridehar (n = 2), and Godey (n = 1). Of the 36 blood-fed An. stephensi, 75.0% (27/36) had vertebrate DNA identifiable with sequencing. Of the 27 blood meals, 22 were from goat, three from cow, one from human, and one from dog. Of the 22 samples confirmed to have fed on goat, 68.2% (15/22) showed signs of intraspecies mixed feeding based on the presence of double peaks in sequencing data. Of the nine samples considered blood-fed but unidentifiable, four samples showed evidence of cross-species feedings that could not be resolved by sequence analysis, and five samples presented positive presence/absence PCR results for blood-feeding but produced unsuccessful sequencing results. Overall, we found evidence of both livestock and human feeding.Given the evidence of a recent spread of An. stephensi populations in Ethiopia. Higher genetic diversity was observed in the most northern sites, such as Semera, compared to the most southern, such as Godey. Lower genetic diversity can be a signature of a more recent population produced through range expansions or introduction [An. stephensi in the south represent a more recent population relative to the population in the north. The difference in the level of diversity may also reflect different degrees of gene flow between the An. stephensi origin outside of Ethiopia.Our analyses revealed multiple mitochondrial gene haplotypes in oduction –43. OfteAn. stephensi introduction(s) into Ethiopia. One subregion may have stronger international connectedness which would allow for influx of additional diversity, while another region with lower international connectedness would have lower diversity overall. Further sequencing representative of the genomic variation and the addition of more sites can help identify the relevant demographic and geographical factors that shape the diversity of An. stephensi.We also observed population differentiation between many sites, notably, differentiation of the northern sites from the central and southern sites. These differences may reflect landscape or other natural barriers that minimize gene flow between the populations. Notably, Semera, and Gewane are located in the Rift Valley, which may explain the within-subregion differentiation of Bati from Semera and Gewane. The population differentiation may also reflect geographical differences in An. stephensi in both Ethiopia and Djibouti are more closely related to An. stephensi from South Asia than those from the Arabian Peninsula (with the exception of one sequence from the United Arab Emirates). These results endorse greater support for South Asia as the place of origin for An. stephensi in the HOA. However, conclusions about the specific origin  require additional sampling and sequencing from An. stephensi populations from countries not well represented in the available database, including Afghanistan, Yemen, Oman, and China, as well as other underrepresented countries in East Africa including Sudan, Djibouti, Eritrea, and Somalia.Phylogenetic and network analysis Figs. , 4 reveaAn. stephensi was introduced in Ethiopia. The presence of the central COI-Hap1 (common in South Asia) at specific sites in Ethiopia may suggest strong connectedness to the source of An. stephensi into the HOA. In our analysis, we see the central COI-Hap1 haplotype in Semera and Bati in the northern subregion and Jigjiga in the central subregion  haplotypes in Ethiopia may provide insight into how An. stephensi in the HOA. Follow-up genetic studies should include the sites in this study with the strongest connection to S. Asia based on the mtDNA analyses completed here as potential sources for introduction into Ethiopia. More genetic analysis is needed that accounts for genome-wide variation and should also focus on underrepresented sites in the HOA and long-established An. stephensi populations outside the HOA. Increasing the number of sites will provide a basis for a formal association analysis between geographical location and the level of genetic diversity to test the hypothesis developed here that the An. stephensi population in the north is older than the population in the south. Also, additional samples from collections throughout the year could provide important information on seasonal differences in An. stephensi diversity.These preliminary results provide a framework for continued investigation into the origin of An. stephensi was introduced and could facilitate predicting how the vector could spread further. Studies should look into economic activities related to import and export practices via vehicle, aircraft, and maritime trade. In addition, pastoral activities may be relevant, given the high evidence of feeding on goats, which are common livestock in eastern Ethiopia. More investigations are needed to determine whether the high zoophilic pattern observed in our study is a trait of the HOA An. stephensi or is more likely shaped by the availability of livestock compared to humans as a feeding source. Still, the evidence for both zoophilic and anthropophilic feeding in this study supports the need for investigations into whether livestock movement plays a role in the spread of An. stephensi. While the livestock themselves are not likely to transport the mosquitoes, they may be an attractant, and the traveling water containers may serve as suitable and mobile breeding habitat. In addition, incorporating climate variables  and landscape characteristics would provide additional information on environmental factors that contribute to gene flow.Combining genetic analysis with relevant data related to anthropogenic and environmental factors would provide a holistic picture of how An. stephensi genetic diversity suggest a South Asia origin of the HOA An. stephensi and a pattern of spread indicating that the southern population in Ethiopia has resulted from a more recent expansion than the northern and central populations. Future studies with expanded genomic analysis will further inform our understanding of migration rates and the role of local adaption on the spread of An. stephensi into and throughout the HOA. Collaboration across countries where this mosquito is well established and countries where it is emerging can facilitate a complete understanding of the spread of An. stephensi into Africa.Our data on Ethiopian Additional file 1: Table S1. List of COI sequences retrieved from NCBI included in population genetic and phylogenetic analyses of An. stephensi.Additional file 2: Figure S1. Pairwise Fst between study sites based on genetic distance. Fst values are plotted below the diagonal and P-values above. Color gradient based on Fst values . Figure S2. Pairwise Fst between study sites based on haplotype frequencies. Fst values are plotted below the diagonal and P-values above. Color gradient based on Fst values .


Phyllostachys edulis) is an economically and ecologically important nontimber forestry species. Further development of this species as a sustainable bamboo resource has been hindered by a lack of population genome information. Here, we report a moso bamboo genomic variation atlas of 5.45 million single-nucleotide polymorphisms (SNPs) from whole-genome resequencing of 427 individuals covering 15 representative geographic areas. We uncover low genetic diversity, high genotype heterozygosity, and genes under balancing selection underlying moso bamboo population adaptation. We infer its demographic history with one bottleneck and its recently small population without a rebound. We define five phylogenetic groups and infer that one group probably originated by a single-origin event from East China. Finally, we conduct genome-wide association analysis of nine important property-related traits to identify candidate genes, many of which are involved in cell wall, carbohydrate metabolism, and environmental adaptation. These results provide a foundation and resources for understanding moso bamboo evolution and the genetic mechanisms of agriculturally important traits.Moso bamboo ( Moso bamboo is an economically and ecologically important nontimber forestry species. Here, the authors analyze 427 genomes collected from 15 representative geographic areas, and identify genes under balancing selection, putative patterns of historic demography, and candidate genes associated with important traits. Phyllostachys edulis) is the most important bamboo species worldwide, accounting for ~74% of the total bamboo-growing area (4.68 million ha)1, with production corresponding to 5 billion US dollars annually in China2. It is primarily an asexually reproducing perennial grass in subtropical areas and is mainly distributed in southern China (a relatively independent geographic population has been established in the area between ~23°30′ to 32°20′ N and 104°30′ to 122° E)3, and its growth status varies with latitude, longitude, and topography4. Human activities and environmental factors have caused some disturbance to spontaneous vegetation, resulting in habitat deterioration and germplasm loss5. A genome-scale investigation of the genetic diversity, population differentiation, and spatial structure of moso bamboo across the entire distribution range in China are essential for designing and implementing appropriate conservation strategies to harness its natural and domesticated biodiversity.Moso bamboo 7, inter simple sequence repeat (ISSR)8, and simple sequence repeat (SSR) markers9. However, a thorough understanding of the genetic diversity and population structure of moso bamboo is lacking due to the unavailability of a more comprehensive population analysis of genome-wide variations, especially when the reference genome is available11. Whole-genome resequencing (WGRS) has been widely applied to important plants to understand the extent/patterns of genetic variation and linkage disequilibrium and to reveal the unidentified genetic potential for critical agronomic traits15. With the advent of next-generation sequencing technology, WGRS has greatly facilitated the identification of sites associated with phenotypic traits17, such as plant disease resistance, yield, and property traits. Carrying out WGRS in moso bamboo will help to identify and utilize variants of different frequencies in the population that may contribute to crucial phenotypes, including bamboo property traits.Recent studies on the genetic diversity of moso bamboo have been performed using various types of molecular markers, such as random amplified polymorphic DNA (RAPD)In this study, we sequence 427 moso bamboo individuals from 15 representative geographic distribution areas of moso bamboo in China to identify genome-wide variations, including single-nucleotide polymorphisms (SNPs), small insertions, and deletions (InDels), structural variations (SVs), and copy number variations (CNVs). These variations are further analyzed to understand genome features and population structure to aid in further research and applications. The identified variations provide insight into the origin and evolutionary history of moso bamboo and reveal possible genetic loci related to the agronomic traits of moso bamboo.9  was also sequenced to be used as the outgroup. In total, we generated 16.60 Tb data (55.34 billion read pairs) and mapped these data to the reference genome10, resulting in an average sequencing depth of 20.91× (Supplementary Data Arabidopsis (one SNP per 11 bp)18 and rice (one SNP per 16 bp)19 . We found that approximately 93.97% of these SNPs are located in intergenic regions, compared to 3.18% in intronic regions and 2.85% in coding regions (Supplementary Table Arabidopsis20 (0.83), rice21 (1.20), and soybean21 (1.36). Overall, we found relatively low whole-genome diversity in the moso bamboo population, indicating a possible low effective population size and small genetic pool to be used for future breeding purposes.A total of 427 representative moso bamboo individuals from 15 major geographic distribution areas were selected for WGRS according to an SSR-based phylogenetic treep-value < 0.01). This reflected the functional importance of the SVs, indicating their involvement in pathogen responses. Similarly, we detected a total of 168,700 CNVs, and 92,684 CNVs per moso bamboo individual on average, with a minimum of 81,156 and a maximum of 104,588 CNVs  and copy number variations (CNVs)  and rice19 , respectively. During asexual reproduction, rare somatic mutations can accumulate, which would result in the accumulation of low-frequency heterozygous genotypes . In the moso bamboo population, low-frequency heterozygous genotypes were identified on 46.42% of the detected SNP sites, which was as expected  enriched in biological processes of pollen and reproduction recognition, as well as defense responses to fungi and bacteria   Fig. , indicat24 and derived allele frequency (DAF)25. We only found two potential regions under positive selection at the highest 1% significance level with one gene of unknown function , which play an essential role in responding to the environment28 vel Fig. , revealiPM1 Fig. , we founPM1 Fig. , revealiK = 1, and the unstable ancestry population allocation, indicating the rare slight population differentiation so that we could not reliably define some distinctly genetic subpopulations  of these phylogenetic groups were low, ranging from 7.00 × 10−4 to 7.06 × 10−4, and the pairwise Wright’s F statistics (FST) among groups ranged from 7.16 × 10−4 to 1.33 × 10−3, reflecting relatively low population differentiation  to elucidate the genetic population structure   with MS_WEST included  analysis and found a significantly positive correlation between geographic distance and genetic distance for the whole moso bamboo population using the Mantel test (CS) Fig. , indicatCS) Fig. , we obseD in the moso bamboo population  to identify associated variations and possibly related genes. Based on previous studiesPH02Gene04629.t1 and PH02Gene48149.t1, both annotated as encoding cinnamoyl-CoA reductase (CCR), which catalyze the conversion of cinnamoyl-CoAs to the corresponding cinnamaldehydes and were reported to cause significant changes in lignin levels and composition39. Another example is the PH02Gene46399.t1 gene, encoding a member of the GRAS  family. Its reciprocal best BLAST hit of AT1G07530.1 showed that this gene plays a role in adaptation to the environment40. Finally, the co-expression network showed that some property trait-associated genes were linked, suggesting that the genes controlling complex traits were often interconnected in regulatory networks  to prevent profound damage to the species. Additionally, abundant specific germplasms provide a source of great variation for establishing ecological moso bamboo forests, and unique alleles may result from populations adapted to their local environments. Such alleles have great value for the maintenance and evolution of the species in unfavorable subsistence environments. Moreover, as a mainly asexual species, the collection of moso bamboo genetic resources will not damage the original distribution. Therefore, efforts aimed at the ex-situ conservation and utilization of the significant germplasms of this species in various populations should be intensified.42. The availability of a comprehensive moso bamboo genome variation map has played an essential role in identifying possible connections between SNPs and agronomic traits. The next challenge will be to examine the associations of genetic variation with property-related phenotypes measured under various environmental conditions in the field and laboratory. This will guide and accelerate bamboo breeding on the basis of identifying genetic variations that will be useful in breeding efforts and future sustainable forests.We detected abundant genetic variation among individuals in the moso bamboo population. These genetic variations in different genes and alleles contribute to the flexibility and survival of moso bamboo populations in the face of changing environmental circumstances43, especially for the moso bamboo population, whose individuals have a long life cycle, strong nutritional and reproductive capacity as well as strongly affected by human activities. Additionally, the old and new individuals can be connected through a unique rhizome-dependent clonal multiplication system. First, to avoid repeated sampling, we sampled one single moso bamboo individual from nonconsecutive pieces of bamboo forest, or one dividual at a distance of more than 1 km. In this way, we sampled approximately 23–30 individuals from each bamboo forest. Second, for a population study, we need to sample natural individuals rather than cultivated individuals, while the natural distribution of moso bamboo may have been affected by human activities. Considering the difficulty of distinguishing natural and cultivated moso bamboo forests, we determined the natural forests based on consultations with local forestry authorities or bamboo farmers as mentioned before9. More importantly, we sampled based on the previous phylogenetic tree9 to improve the accuracy and efficiency of sampling. We documented the locations of each individual sampled. We obtained young leaves, quickly dried them in silica gel, and sealed them in plastic bags.A reasonable sampling strategy is critical for obtaining reliable results in population genetic researchPhyllostachys kwangsiensis which was closely related to moso bamboo44, was selected as an outgroup. The specimens of representative individuals from different habitats were deposited at the International Centre for Bamboo and Rattan, and detailed sampling information was provided in Supplementary Table Following our sampling procedure, we sampled 427 individuals from 15 moso bamboo geographic distribution areas, representing almost all of the moso bamboo habitats in China. 45. The libraries of insert sizes of ~450 base-pair (bp) were constructed from randomly fragmented genomic DNA, and 150 bp paired-end reads were produced using the Illumina sequencing platform. The raw sequencing data were filtered using SOAPnuke (version 2.1.5)46 with parameters “-J -l 10 -q 0.1 -n 0.05”. In detail, we filtered out low-quality reads  and poly-Ns (if there were more than 5% of the based to be Ns). Meanwhile, we removed any low-quality bases (Q ≤ 13) or adapters at both ends. After data filtering, we used the clean data for subsequent analyses.Young leaves at the vegetative growth stage were collected in August 2015 and August 2016, respectively. Total genomic DNA was extracted with the cetyltrimethylammonium bromide method10 using BWA47 (version 0.7.12-r1039) with the parameter “-M”. We then used SAMtools48 (version 1.3.1) to sort alignment (BAM files), used Picard49 (version 1.105) to remove duplicates, and used GATK50 (version 3.8-1-0-g15c1c3ef) to re-align the reads around InDels.The filtered whole-genome resequencing reads were aligned to the latest moso bamboo chromosome-level reference genome50 (version 3.8-1-0-g15c1c3ef) using the joint calling method. In detail, we first obtained the genomic variant call format (GVCF) in ERC mode for each sample based on reads with mapping quality higher than 20 , and then carried out the joint variant calling using the tool “CombineGVCFs” in GATK. In this step, low-quality mapping reads were removed (using the parameter of “-mq 20”) and we found 81.84% of the multiple mapping reads were filtered out here  with parameter “-assoc”.SNP and InDel calling was performed using GATK52 (version 1.6.0) to detect insertion (INS), deletion (DEL), and inversion (INV), and BreakDancer53 (version 1.1.2) to detect intra-chromosome translocation (ITX) based on individual sequencing data with default parameters  to merge individual SVs using the parameter “1000 1 1 1 0 50” to allow a maximum distance of 1 kb and no more than 50% difference in length. To reduce possible false-positive SVs, we further removed the variations overlapped with tandem repeats and ambiguous bases (Ns). Finally, we only retained variation with a frequency higher than 1% using VCFtools55 (version 0.1.17) with the parameters “-maf 0.01 -max-maf 0.99”. We detected genes affected by SVs by extracting genes overlapped with SVs using the in-house script (available in GitHub: https://github.com/BGI-Qingdao/moso_bamboo_resequencing). Gene Ontology (GO) and KEGG pathway enrichment analyses of these genes were performed using EnrichmentPipeline , and a Benjamini–Hochberg corrected p-value < 0.05 was considered significant.For SV identification, we used Manta version .6.0 to d56 (version 11.5) with default parameters. We filtered out the CNVs overlapped with ambiguous regions (Ns) and with frequencies in the population to be lower than 1%. We extracted the genes overlapped with CNVs using the in-house script (available in GitHub: https://github.com/BGI-Qingdao/moso_bamboo_resequencing) and carried out gene function enrichment using the same method described above.For CNV detection, we first calculated the GC-content profile in 1 kb bins along the genome and then detected CNVs using Control-FREEChttps://github.com/BGI-Qingdao/moso_bamboo_resequencing) to calculate the window-level heterozygous genotype frequency in non-overlapping sliding windows of 200 kb in length. The average 200-kb-window-level heterozygous genotype frequency was 37.82%, and the standard deviation was 20.12%. Therefore, one standard deviation above the mean (57.94%) and below the mean (17.70%) was used as thresholds to distinguish high-frequency and low-frequency heterozygous regions, respectively. To avoid false-positive discovery caused by random fluctuations, high-frequency and low-frequency heterozygous regions with a continuous length greater than 5 Mb were considered as long continuous high-frequency heterozygous regions (high-LCHRs) and low-frequency heterozygous regions (low-LCHRs). We obtained genes that overlapped with high-LCHRs and low-LCHRs and the gene enrichment was performed using the method described above.To depict the genome-wide pattern of the genomic heterozygosity, we calculated two statistics to reflect the heterozygosity level of genotypes at the single-site and window levels. The single-site-level heterozygosity frequency was defined as the number of heterozygous genotypes divided by the total number of called genotypes at each site. And the window-level heterozygous genotype frequency was the average of the site-level heterozygous genotype frequency across all sites in this window. We used an in-house script  to calculate the CLR for windows of 100 kb in length (setting the parameter of “-grid”) with default parameters. We calculated DAF25 using an in-house script (available in https://github.com/BGI-Qingdao/moso_bamboo_resequencing) in 100-kb windows along the genome. The regions with the top 1% CLR (24.32) and DAF (0.52) were determined as potentially positively selected regions. We then detected the balancing selection based on the B2 statistics using BalLeRMix26 (version 2.2) with default parameters, and we determined the regions with the top 0.5% B2 values (270.88) to be potentially under balancing selection. We extracted the genes overlapped with these potential regions under selection as genes potentially under balancing selection. The gene enrichment was performed using the mentioned method above.We applied several software to detect possible regions under selection in the moso bamboo population. First, we calculated the composite likelihood rate (CLR) and derived allele frequency (DAF) to detect possible regions under positive selection. The alleles with the status of homozygous genotypes in 51 (version 1.90) with the parameters “-indep-pairphase 100 10 0.2” to determine a pruned SNP set to be used in the population structure analysis. In this way, we used 1,432,873 SNPs for the phylogeny and population analysis. The Identity-By-State (IBS) genetic distance matrix was calculated to quantify the correlation between individuals using the “-distance 1-ibs flat-missing” parameter in PLINK. A neighbor-joining (NJ) phylogenetic tree was constructed using the “neighbor” parameter in PHYLIP57 (version 3.6) based on the distance matrix. Phyllostachys kwangsiensis was used as the outgroup to root the phylogenetic tree. For the principal component analysis (PCA), we used EIGENSOFT58 (version 7.2.1) with default parameters to extract the top 10 principal components (PCs). The top three PCs were plotted using package ggplot259 (version 3.3.0) in R (version 3.5.0). Maximum likelihood estimation of individual ancestries was performed using ADMIXTURE60 (version 1.3.0) with the parameters “-cv -j4” for multiple repeats with different random seeds. The results were visualized using the online tool CLUMPAK61 (accessed in July 2020).For all individuals, we first used PLINK62 (version 3) to color the phylogenetic tree. We defined five phylogenetic groups according to the phylogenetic tree. We calculated the genetic diversity (θπ and θw) using VCFtools55 (version 0.1.17) with the parameters “-window-pi 100000”. We used VCFtools to calculate the population differentiation statistics (FST) of different phylogenetic groups in 100-kb windows. We used VCFtools to calculate Tajima’s D in 100-kb non-overlapping windows with parameter “-TajimaD 100000”.We used the web tool EvolviewFST [(FST/(1 − FST))] and the matrix of geographic distance among the 13 geographic distribution areas  were used for performing the Mantel test using ade463 (version 1.7–17) package with 9999 permutations. We calculated the genetic Hamming distance matrix to quantify the relationship between individuals using the “-distance flat-missing” parameter using PLINK51 (version 1.90). The lowest 0.5% were visualized using Cytoscape64 (version 3.70).For the isolation-by-distance analysis, the matrix of 31 (version 0.6.5-r67) and SMC++33 (version 1.15.4). For PSMC, we used representative individuals from the five phylogenetic groups with high sequencing depth , MSMC mappability, and BEDTools65 (version 2.28.0) to prepare the input file  for SMC++. For both methods, we used an estimated mutation rate of 8.51 × 10−8 and the generation time of 67 years66. The nucleotide mutation rate (μ) was estimated following Eq. 1D is the observed frequency of pairwise differences between two species, T is the estimated divergence time, and g is the estimated generation time for the two species67. Olyra latifolia was selected as the comparison species. In this study, we first aligned the two genomes using NUCmer68 (version 4.0.0), and the median of the sequence divergence was 0.1069  was set to 67 years66, and the estimated divergence time was 42.1 million years ago69, so that a mutation rate of 8.51 × 10−8 mutations per site per generation was estimated.For the demographic analysis, we used PSMC71. For all measurements of the quantitative traits, we adopted the mean values of three independent measurements. In addition, to control the potential impact of the environmental factors on the traits, 12 environmental factors, including latitude, longitude, altitude, soil type, annual mean precipitation, annual mean temperature, nitrogen (N), phosphorus (P), potassium (K), magnesium (Mg), boron (B), and zinc (Zn) were collected from a previous study72. All phenotypic measurements were provided in Supplementary Data We investigated nine agricultural traits of the sequenced individuals, including three growth-related traits  and six property-related traits . We measured the growth-related and property-related phenotypes according to the standards for testing the physical and mechanical properties of bamboos73 (version 4.0.4). In the meantime, the principal components of genetic variations were also calculated based on pruned SNPs. We used the first three PCs of environmental factors and the first three PCs (Q) of genetic variations as fixed effects to correct for stratification. A kinship (K) matrix in the emmax-bin-intel package in EMMAX (version beta-07Mar2010)74 was used as a random effect to model the population relatedness in GWAS.For the genome-wide association study, we first removed individuals with high genetic correlations according to the pairwise IBS genetic distance (with the cutoff of 0.06), thus we remained 190 samples for the genome-wide association study. Furthermore, we used the common SNPs . In order to minimize possible effects of environmental factors, we carried out PCA on the twelve environmental factors using function “princomp” in R package “stats”75, MAGMA-based gene-level analysis (version 1.07bb)76, and mrMLM-based multi-locus association (ISI EM-BLASSO) (version 4.0)77 using the Q + K model with default parameters. To calculate the p-value threshold, we firstly estimated the effective SNP number using the genetic type I error calculator (GEC)78 (version 0.2) with default parameters. The p-value threshold was 2.10 × 10−8 for EMMAX and FarmCPU by Bonferroni correction method ). LOD (log of odds) value > 3 is a suggestive significance threshold by ISI EM-BLASSO77.To increase the statistical power of the association analysis, a comprehensive strategy was used based on four different methods  by merge these candidate SNPs within 10 kb distance. The genes within or the 5 kb upstream or downstream from the MTAs were considered as candidate genes. In addition, the related co-expression networks of moso bamboo were generated and visualized via the BambooNET website79 .Finally, we used an integrated approach of combining the above results to depict more candidate genes with sight genetic effect. In detail, we first picked up the SNPs above significant Further information on research design is available in the Supplementary InformationSupplementary DataDescription of Additional Supplementary FilesReporting Summary


STAT3 is an important transcription factor that regulates cell growth and proliferation by regulating gene transcription of a plethora of genes. This protein also has many roles in cancer progression and several tumors such as prostate, lung, breast, and intestine cancers that are characterized by strong STAT3-dependent transcriptional activity. This protein is post-translationally modified in different ways according to cellular context and stimulus, and the same post-translational modification can have opposite effects in different cellular models. In this review, we describe the studies performed on the main modifications affecting the activity of STAT3: phosphorylation of tyrosine 705 and serine 727; acetylation of lysine 49, 87, 601, 615, 631, 685, 707, and 709; and methylation of lysine 49, 140, and 180. The extensive results obtained by different studies demonstrate that post-translational modifications drastically change STAT3 activities and that we need further analysis to properly elucidate all the functions of this multifaceted transcription factor. Stat sequences in different eukaryotic organisms, from Hydra magnipapillata to Caenorabditis elegans, from Dictyostelium discoideum to Drosophila melanogaster, from Danio rerio to Homo sapiens . T sapiens . STAT3 f sapiens . STAT3 i sapiens ; wound h sapiens ; inflamm sapiens ,12; and  sapiens . Of note sapiens ,15. Howe sapiens ,17,18,19 sapiens ,21. WithKlf4), regeneration and wound healing (Il10), inflammation (Il8rb and Cxcl2), apoptosis (caspase-3), and many other important biological processes  residue. The mechanisms triggering this modification and the function of phosphorylated S727 are still debated. The kinases that are able to induce this modification are cell and stimuli specific  and theyStat3 transcript—and overexpressed a mutated form of Stat3 in which S727 had been replaced with an Alanine, hence, blocking the possibility of STAT3 being phosphorylated in the 727 position (Stat3 S727A)  . Interestroduced ) express protein .Stat3 S727A, there is upregulation of Y705 phosphorylation [In 2000, Decker and Kovarik  noticed rylation , but alsrylation ,35, theyrylation  supposedrylation , which wrylation .Stat3 gene . They used embryonic fibroblasts from homozygous Stat3SA/SA mice, and they discovered a halved transcriptional response in mutants as compared with wild type fibroblasts, hence, confirming the results described in Wen et al., [Stat3SA/SA and Stat3+/- mice did not show altered phenotypes, Shen and collaborators bred these two lines to generate Stat3SA/- mice. This composite heterozygous line showed perinatal lethality (about 75% of the offspring died for no specified reasons) and lower embryonic and perinatal growth. The authors proposed a connection between this early phenotype and the altered levels of insulin-like growth factor (IGF-1) in the serum of newborn mice. According to the aforementioned data, fibroblasts from Stat3SA/- foetuses showed no more than 25% of STAT3-dependent transcription after IL-6 stimulation. Finally, Stat3SA/- mice showed a decreased level of thymocytes and an increased apoptosis, suggesting the presence of defects in the thymocyte survival mechanisms. Although this study did not dissect the functions of S727 phosphorylation in different tissues and the authors analyzed only fibroblasts from foetuses, the Stat3SA/SA murine line represented a good tool to further investigate STAT3 S727 phosphorylation in an in vivo system.Further analyses on STAT3 S727 functions were carried out in vivo by Shen et al. , who gen et al., . Since SMore recently, Hazan-Halevy et al.  also disStat3C and Stat3 Y705F   could be a very effective therapeutic strategy against breast cancer. As previously mentioned, phosphorylation of both Y705 and S727 has been widely correlated to cellular growth control and cancer onset. For example, in these years, it was demonstrated that progestins were able to activate STAT3 in breast cancers by inducing phosphorylation of Y705 or S727 ,42. Proif Stat3) , ProiettPR gene knockdown (by siRNA) in C4HD cells or by stable PR knockout in T-47D cells (in which the inducibility was restored upon PR transfection). The authors hypothesized that S727 phosphorylation was induced by progestins through activation of the c-Src/p42/p44 MAPK pathway, inhibition of which (using either specific inhibitor or genetic mutations) blocks S727 phosphorylation after MPA stimulation. Tkach et al. also showed that phosphorylation of S727 increased STAT3 nuclear translocation and maximized STAT3 transcriptional activities. In detail, the S727 phosphorylation of STAT3 was fundamental for the full transcriptional activation of cyclinD1 gene (a key cell cycle regulator in breast cancer) through pSTAT3 S727 recruitment on its promoter. Finally, they demonstrated that phosphorylation of S727 was needed for progestin-induced tumor growth, both in vitro and in vivo (through the injection of C4HD cells in BALB/c mice). The proliferation of the cells was reduced by transfection of Stat3 S727A vector in both murine (C4HD) and human (T-47D) breast cancer cell as compared with the control cells transfected with wild type Stat3 or empty vector. Notably, mice also injected with C4HD cells transfected with Stat3 S727A vector showed a reduced growth of tumor, in which the levels of pSTAT3 S727 and of cyclinD1 mRNA were lower as compared with the control [According to Tkach et al. , treatme control .-/-Stat3 mESCs that could express either wild type Stat3, Stat3 Y705F, or Stat3 S727A. After inducing the different Stat3 forms and LIF stimulation, they showed that Stat3 expression was needed for cell survival and that Y705 phosphorylation was indispensable for the maintenance of pluripotency. In addition, their results showed that S727 phosphorylation was involved in cell survival and mitogenicity; cells expressing Stat3 S727A had reduced survival and proliferation rate as compared with cells expressing wild type Stat3. Moreover, also in mESCs, S727 was phosphorylated by ERK1/2 kinases. The role of S727 phosphorylation in the regulation of proliferation was probably connected to STAT3-dependent expression of Myc gene, which was abolished in mESCs expressing STAT3 Y705F and reduced in mESCs expressing STAT3 S727A. In addition, three other STAT3 target genes involved in the maintenance of pluripotency  had the same responsiveness of Myc, confirming the role of S727 phosphorylation as a transcription enhancer. The S727 phosphorylation also appeared to be involved in neuronal differentiation. Loss of pS727 resulted in a reduction in neuronal differentiation potential, recovered by the S727 phosphomimetic mutations, called Stat3 S727D, which substituted the serine with aspartic acid , which can dephosphorylate STAT3 residues. The mechanisms of PTP functions have only been partially clarified and are currently under investigation as possible targets for treatments against cancer . Stat3 WT, Stat3 Y640F, or Stat3 D661V. Finally, Kuusanmaki and collaborators concluded that Hsp90 inhibitors, also in combination with JAK or mTOR inhibitors, may be a very potent long-term therapeutic option for lymphoproliferative diseases characterized by STAT3 mutations.The central role of STAT3 in the development of a large number of tumors makes this protein an attractive target for studies of cancer therapy. Starting from the observation that activated STAT3 is detected in a large fraction of lymphoid malignancies, Kuusanmaki et al.  looked fStat3 mRNA in zebrafish determined an upregulation of both mt_nd2  and pcna (used as a marker of cell proliferation). Notably, the overexpression of Stat3 Y705F and Stat3 S727A did not stimulate expression of mt_nd2 and pcna, suggesting that phosphorylation of both Y705 and S727 was required for increased transcription of these genes. Hence, the authors decided to analyze the effects of a mitochondrially targeted form of Stat3 (named MLS_Stat3_NES) and demonstrated that phosphorylation of both Y705 and S727 was required for the correct activities of STAT3 in the mitochondrion. While Y705 appeared to be necessary for the proper localization of STAT3 in mitochondria, S727 was needed for the proper biological activities of this protein in the organelle. After underlining the roles of both pY705 and pS727 of STAT3 in the regulation of nuclear activities, it is worthwhile mentioning that STAT3 can localize in different subcellular compartments, and exert functions that are independent from canonical STAT3 transcriptional activities ,51,52. ASocs2, NanoG, and Klf4. In correlation to these assigned functions, it is not surprising that S727 phosphorylation is involved in v-Src-mediated transformation [In summary, Y705 phosphorylation is involved in the STAT3 canonical activation mechanism leading to dimerization and nuclear translocation of protein . This moormation ,39 and iormation . In addiormation . In concThe STAT3 protein can also be phosphorylated in other residues of transcriptional activation domain (TAD), in C-terminal of sequence: S691 , T714 5,55, T717hAGT) gene, because STAT3 mediates the acute-phase response (APR) of the hAGT gene in hepatocytes. These authors demonstrated that in HepG2 cells, STAT3 was acetylated by the p300 co-activator upon IL-6 stimulation. They mapped K87 as the major and K49 as the minor Ac-acceptor site and they suggested that nuclear acetylation of these residues increased p300-STAT3 binding on the promoter regions of hAGT gene, hence, inducing its transcription. Moreover, Ray et al. [hAGT, proposing HDAC-1 as a negative modulator of this PTM. Further studies by the same research group [HDAC-1 determine accumulation of STAT3 in the nucleus and enhance STAT3-dependent transcriptional response after IL-6 stimulation. These results confirmed that acetylation of STAT3 was required for proper nuclear localization of the protein and to potentiate its transcriptional activities. Another fundamental post-translational modification that usually affects the activity of nuclear transcription factors is acetylation. Acetylation and deacetylation modulate the mechanisms of transcriptional activity by regulating the chromatin accessibility through histone modification, and the interaction of transcription factors with their responsive elements on DNA. Interestingly, acetylation of both histone and transcription factors are carried out by histone acetyltransferases (HATs), the enzyme that is able to transfer an acetyl group from acetyl-coenzyme A to the ε-amino group of lysine residues ,58,59. Ty et al.  demonstrch group  have betAcetylation of K87 was also correlated to mitochondrial translocation of STAT3 by Xu et al. . In partThe SH2 domain of STAT3 can be acetylated. Ma and collaborators’  spectromStat3 together with CBP or p300 in HepG2 cells, showing that STAT3 + p300 or STAT3 + CBP generated increased levels of acetylated STAT3. They mapped the STAT3 acetylation sites using in vitro acetylation assay and identified K685 as the target of p300. The interaction was confirmed in vivo using FLAG-tagged mutant proteins and performing a transient transfection acetylation assay. They also hypothesized that the acetylation of STAT3 in the nucleus prevents its nuclear export, increases its transcriptional activity, and recruits CBP/p300 on the promoter region of STAT3 target genes, activating their expression. They also supposed that the acetylation of K685 could influence STAT3 phosphorylation modulating the formation of STAT3 dimers. The most studied acetylation of STAT3 C-terminal domain is on the K685 residue. In 2005, for the first time, Wang et al.  showed t12, and c-Myc proteins) to OSM stimulation, suggesting that acetylation of K685 changed the local charge of the protein and favored the formation of STAT3 homodimers. The same authors also showed that K685 acetylation was catalyzed by p300 and could be reversed by type I HDAC family members, even if the K685R mutation, which substituted Lysine with Arginine . Stat3 gene was induced promoting a persistent nuclear accumulation of U-STAT3. Interestingly, the authors correlated the accumulation of U-STAT3 in the nucleus to cardiac hypertrophy accompanied by pathogenic gene expression .U-STAT3 has been supposed to regulate the transcription of a set of genes which are not targets of pSTAT3 homodimer. Yang et al.  previousInterestingly, Dasgupta et al.  reportedp53 and PTPN6. Interestingly, the STAT3 K685R mutation reduced tumor growth through interruption of the STAT3–DNMT1 interaction and consequent reactivation of a set of tumor-suppressor genes. Hence, Lee et al. suggested that K685 acetylation helped STAT3 and DNMT1 to colocalize properly in tumor cells, methylate promoter regions of tumor-suppressor genes, and inhibited their expression. Among these genes, the estrogen receptor alpha (ERα) could be reactivated in triple breast cancer cells by using resveratrol, a non-flavonoid phenol that is able to dampen K685 acetylation. Moreover, the chromatin modification in the ERα promoter region predicted melanoma progression and the reactivation of this gene made tumor cells sensitive to antiestrogens . Additionally, Lee et al. confirmed that the K685 mutation had a small effect on STAT3 phosphorylation [As previously mentioned, STAT3 acetylation can have a pivotal role in the regulation of tumorigenesis. Lee et al.  reportedrylation . HDAC overexpression decreased AcSTAT3 K685 levels, while HDAC knockdown upregulated acetylation of STAT3. Finally, they demonstrated that the HDAC inhibitor panobinostat  was able to increase the acetylation level of endogenous STAT3 in a dose-dependent manner. In agreement with Wang et al. [Mcl-1 and c-Myc expression and an increase in PARP cleavage. Additionally, their data suggested that the IL-10 stimulation of STAT3 nuclear translocation was reduced by panobinostat treatment, pointing to a role of HDAC in mediating nuclear translocation. This compound dephosphorylates STAT3 Y705 in a dose dependent manner by the JAK2 independent mechanism. All in all, panobinostat increases STAT3 acetylation and results in decreased STAT3 accumulation in the nucleus along with a significant decrease in nuclear pSTAT3 Y705. Since K685 and Y705 residue are close to each other, Gupta et al. supposed that panobinostat-induced K685 acetylation prevented tyrosine phosphorylation. However, it is worthwhile noting that the results shown by Gupta and collaborators are in contrast to the observations by Wang et al. [In addition, Gupta et al.  studied g et al. , Gupta ag et al.  and Yuang et al. , suggestIDO mRNA elicited by HDAC inhibition; the direct link between IDO transcription and STAT3 action was confirmed by the discovery of STAT3 consensus elements in IDO gene promoter sequence which contained two gamma interferon activation (GAS) sites corresponding to STAT3 binding consensus elements on DNA. To demonstrate the direct link between STAT3 binding to the IDO promoter region and HDAC modulation activity on IDO, Sun and collaborators performed luciferase reporter assays using a mutated IDO promoter region. The results showed that IDO transcription was stimulated by treatment with SAHA (a HDAC inhibitor), but that this stimulation was blocked when the promoter region was mutated in the GAS. This induction was also blocked by JSI-124 treatment, demonstrating that both STAT3 phosphorylation and acetylation could affect the STAT3-dependent transcription of IDO. Furthermore, since K685R mutation blocked the SAHA-dependent promotion of IDO transcription in transfected cells, Sun and collaborators demonstrated a direct correlation between IDO transcriptional stimulation and the K685 acetylation induced by HDAC inhibition [HDAC inhibitors have also been identified as possible pharmacological treatments by Sun et al. , who hyphibition .Garcinia indica was used by Sethi and collaborators [c-fos promoter. Additionally, garcinol reduces HCC cells survival, suppresses proliferation, and increases apoptosis by downregulating the expression of STAT3-target genes involved in proliferation (cyclin D1), apoptosis , and angiogenesis (VEGF). Garcinol can also act in combination with other anticancer agents to enhance apoptosis and retard cellular proliferation in HCC. Finally, garcinol effects were also recapitulated in athymic mouse models bearing hepatic cancer xenografts. In particular, intraperitoneal injection of garcinol in these mice resulted in inhibition of STAT3 and a reduction in tumor growth [Another molecule of pharmaceutical interest targeting STAT3 post-transcriptional modification is garcinol. This polyisoprenylated benzophenone extracted from borators  as an inr growth .IDO induction in dendritic cells) [On the basis of the information reported in the literature, we can conclude that the main STAT3 acetylation sites are K87 and K685. K87 acetylation is mediated by p300 and promotes STAT3–p300 interaction leading to transactivation of STAT3 target genes . This moc cells) .EZH2 knockdown and EZH2 inhibition (with DZNep) caused a decrease of pSTAT3 Y705 levels. These data were confirmed also by a reduction in the expression levels of validated STAT3 target genes (like SOCS3 and c-MYC), as well as a reduced STAT3 reporter activity, upon DZNep treatment. The EZH2 role in the modulation of STAT3 activities has a significant clinical relevance mostly because EZH2 overexpression determines pro-tumorigenic effects in solid cancers, in which STAT3 is often constitutively activated [Xenopus laevis. Loreti and collaborators demonstrated that STAT3-EZH2 interaction resulted in methylation of STAT3 and in the consequent MeSTAT3-dependent regulation of dorso-ventral patterning during X. laevis development [STAT3 can be methylated in both its N-terminal domain (K49) and in adjacent coiled-coil domain (K140 and K180). Enhancer of zeste 2 polycomb repressive complex 2 (EZH2) is the histone-modifying enzyme identified as being responsible for K49 di-methylation and K180 methylation. Dasgupta et al.  suggestectivated . The STActivated ; Kim andctivated ,85,86. Nelopment . SOCS3, FGF21, IRF8, and IRF9) were upregulated in STAT3 K140R cells as compared with wild type cells, while other genes (such as HSF1 and CDCA1) were downregulated; conversely, another group of genes (such as CD14) did not show expression alterations. Interestingly, methylation of STAT3 on K180 and K49 residues have an opposite effect on the regulation of STAT3-dependent transcriptional activity as compared with K140 STAT3 di-methylation, which negatively regulates STAT3 dependent transcription. Yang et al.  identifiAll in all, the evidence mentioned thus far has demonstrated that methylation is fundamental for the regulation of STAT3 activity. MeSTAT3 K49, on the one hand, is induced by pSTAT3 Y705 and potentiates STAT3 transcriptional activity ; MeSTAT3In this review, we have described the most relevant PTMs of STAT3 which can significantly affect both the canonical and the non-canonical activities of this protein. First, we focused on the activities and functions of phosphorylation that were better described in the literature. The Y705 phosphorylation is required for canonical nuclear activity of STAT3, i.e., it appears to be indispensable for the correct dimerization of the protein and the interaction with STAT3 binding elements. The induction of most target genes cannot be triggered if Y705 is not phosphorylated. As a consequence, the accumulation of U-STAT3 in the nucleus seems to be a late response to IL-6/JAK/STAT3 axis stimulation ,89. TyroIt is worthwhile mentioning that STAT3 can interact with several different proteins such as glucocorticoid receptor (GR) , androge