Elymus sibiricus as an important forage grass and gene pool for improving cereal crops, that is widely distributed in West and North China. Information on its genetic diversity and relationships is limited but necessary for germplasm collection, conservation and future breeding. Start Codon Targeted (SCoT) markers were used for studying the genetic diversity and relationships among 53 E. sibiricus accessions from its primary distribution area in China. A total of 173 bands were generated from 16 SCoT primers, 159 bands of which were polymorphic with the percentage of polymorphic bands (PPB) of 91.91%. Based upon population structure analysis five groups were formed. The cluster analysis separated the accessions into two major clusters and three sub-clusters, similar to results of principal coordinate analysis (PCoA). The molecular variance analysis (AMOVA) showed that genetic variation was greater within geographical regions (50.99%) than between them (49.01%). Furthermore, the study also suggested that collecting and evaluating E. sibiricus germplasm for major geographic regions and special environments broadens the available genetic base and illustrates the range of variation. The results of the present study showed that SCoT markers were efficient in assessing the genetic diversity among E. sibiricus accessions. Elymus L. is the largest genus of the tribe Triticeae and includes about 150 species worldwide [Elymus sibiricus (Siberian wild rye) is one of the most important species of the genus. It is a perennial, self-pollinating and allotetraploid forage grass indigenous to northern Asia, but its geographic distribution extends from Sweden to Japan and even to parts of Alaska and Canada [E. sibiricus is widely used in natural grassland and cultivated pastures due to excellent cold tolerance, good forage quality and adaptability, and it therefore plays an important role in Chinese animal husbandry and sustenance [d Canada . As a costenance .E. sibiricus accessions is limited but necessary for germplasm collection, conservation and breeding program. Several previous studies have examined E. sibiricus accessions and populations from Qinghai-Tibet Plateau [E. sibiricus accessions from its primary distribution area including Qinghai-Tibet Plateau, Sichuan, Gansu, Inner Mongolia, and Xinjiang Provinces have not been well characterized. Thus, further analysis of the genetic diversity and variation of Chinese wild E. sibiricus accessions, cultivars and breeding lines from species range and their comparison may produce new insights and give a better understanding of the distribution of genetic diversity.Genetic diversity is the foundation of species diversity and an important precursor in a study of any species, because its quantity and distribution has an effect on the evolutionary potential of species or populations . Informa Plateau ,6,7 and  Plateau  with theetc. In recent years, many new alternative and promising markers techniques have emerged. Start Codon Targeted (SCoT) polymorphisms are dominant and reproducible markers that are based on the short conserved region in plant genes surrounding the ATG translation start (or initiation) codon and use a single 18-mer primer in the polymerase chain reaction (PCR) assays and higher annealing temperature (50 °C) [Traditional DNA markers have numerous applications in plant genetic diversity research. These markers include inter simple sequence repeat (ISSR) markers , sequenc (50 °C) . Markers (50 °C) . Lower r (50 °C) . SCoT ma (50 °C) ,17,18,19E. sibiricus accessions from five geographic regions in China. The purposes of this study were: (a) to assess the genetic diversity and phylogenetic relationship among 53 E. sibiricus accessions; and (b) to examine the effectiveness of the SCoT markers in E. sibiricus genetic diversity study. These results could facilitate E. sibiricus germplasm collection, conservation and future breeding.The present study examines the level of genetic diversity and its molecular variation of 53 E. sibiricus accessions from the species range in China  varied from 0.20 (SCoT54) to 0.50  with an average of 0.45 for this species. The resolving power (Rp) of the 16 SCoT primers ranged from 1.40 (SCoT54) to 6.49 (SCoT41). These primers  with higher PIC and Rp values have more potential for further study, allowing investigating more individuals or sampling sites with a reduced number of primers.E. sibiricus due to several advantages to other marker techniques: easier development of species-specific primers than SSR [E. sibiricus accessions.SCoT markers were used for the first time in than SSR , lower cthan SSR  and highthan SSR . The resetc. In many species, genetic variation is often positively associated with population size [et al. [Elymus species. For example, accessions from the QX group originated from Qinghai and Tibet. The wider geographical range and diverse weather conditions may have contributed to higher estimate of genetic diversity among accessions in QX group. Therefore, in order to broaden the genetic base and sample the full extent of available variation, collecting and evaluating E. sibiricus germplasm from wide geographic regions and special eco-environment is important.The NPB values ranged from 52 (NM) to 97 (QX), with an average of 65.8. The PPB values ranged from 30.06% (XJ) to 56.07% (QX), with an average of 37.63% . The Shaion size . Differe [et al.  found thE. sibiricus populations and other self-pollinating species such as Elymus glaucus and Elymus trachycaulu [E. sibiricus populations, respectively.AMOVA analysis showed that 50.99% of variation was apportioned within geographic regions and 49.01% was apportioned among geographic groups . Similarchycaulu ,27. Prevchycaulu , ISSR machycaulu , and Glichycaulu  detectedE. sibiricus germplasm are usually located in distant mountains, strongly isolated from each other by plateaus and valleys. These mountain and river valleys could serve as genetic barriers for pollinator movement and seed dispersal. The results of the present study suggested that more genetic variation of the species could be captured when sampling a larger number of plants from populations or geographic regions.Previous reports revealed that self-pollinating species have relatively less within-population genetic variation than out-crossing species . But othThe population structure of the 53 accessions was estimated using the Hardy-Weinberg Equilibrium by using STRUCTURE V2.3.4 software. Based on maximum likelihood and delta K (ΔK) values, the number of optimum groups was five . Among tE. sibiricus, but this trend isn’t absolute. For example, nine Sichuan accessions were divided into two clusters. Six accessions were grouped with Gansu accessions with 76% bootstrap support. Ma et al. [E. sibiricus populations from the eastern Qinghai-Tibet Plateau regions using ISSR markers, which showed that there was no distinct geographical tendency in the distribution of the genetic diversity. Some geographically close accessions were clustered in different groups and geographically distant ones were clustered in the same groups. The various selection forces tend to produce genetic heterogeneity under the different small niches [A dendrogram was constructed using data from UPGMA cluster analysis based on the genetic similarity matrix from all the accessions . The 53 l niches . Moreovel niches ,24. QingE. sibiricus accessions and demonstrated an effective tool for the future tasks of genetic analysis, germplasm collection and conservation. The high degree of genetic variation and distinct geographical differentiation of E. sibiricus had been documented in this study. The ecological factors such as climatic types and eco-environment played a pivotal role in the divergence. Therefore, more attention should be paid to special eco-geographical groups  with regard to the E. sibiricus germplasm collection and conservation.A major limitation of plant improvement programs is the lack of plant materials exhibiting rich genetic variation [E. sibiricus cultivars: “Tongde”, “Qingmu 1” and “Chuancao 2”. Thus, these accessions could be used as important genetic resources for genetic improvement of E. sibiricus in future breeding program.It is critical to understand the genetic diversity and variation among and within accessions to choose the effective strategy for conservation and sampling management. In this study, SCoT provided significant information on the genetic variation of ariation . Past stariation  and orchariation  have demE. sibiricus accessions were from the species range in China, comprising cultivars, breeding lines, cultivated and wild collections . DNA quantity and quality were determined using a Nanodrop spectrophotometer  and agarose gel electrophoresis.2O. PCR amplification was performed under the following conditions [A total of 16 SCoT primers were randomly selected . These pnditions : denaturPIC = 1 − p2 − q2 [b = 1 − (2 × |0.5 − p|)I [b [E. sibiricus accessions was analyzed using STRUCTRE v2.3.4 software [The amplified bands were scored as presence (1) or absence (0), and only reproducible bands were considered. Polymorphic information content (PIC) values were calculated for each SCoT primers according to the formula:  p2 − q2 ; where p.5 − p|) , where p− p|) [b . The res− p|) [b . Number − p|) [b . A dendr− p|) [b . A princ− p|) [b . Populatsoftware  with thesoftware ,42.The isoftware .E. sibiricus accessions.In the original research of Collard and Mackill  the use


Genetic diversity is a fundamental level of biodiversity. However, it is frequently neglected in conservation prioritization because intraspecific genetic diversity is difficult to measure at large scales. In this study, we synthesized population genetic or phylogeographic datasets of 33 seed plants in subtropical China into multi-species genetic landscapes. The genetic landscapes identified 18 evolutionary hotspots with high within-population genetic diversity (WGD), and among-population genetic diversity (AGD), or both. The western subtropical China is rich in AGD (possessing four major AGD hotspots), deserving a high conservation priority. We found that WGD was positively correlated with longitude, with most WGD hotspots locating in east subtropical China. The results showed that the locations of 12 of 18 evolutionary hotspots corresponded approximately to those of previously identified species diversity (SD) hotspots, however, a positive and significant correlation existed only between AGD and SD, not between WGD and SD. Therefore, spatial patterns of species richness in plants in subtropical China cannot generally be used as surrogate for their intraspecific diversity. This study identified multi-species evolutionary hotspots and correlated multi-species genetic diversity with SD across subtropical China for the first time, providing profound implications for the conservation of biodiversity in this important ecoregion. To protect biodiversity within the constraints of limited conservation funding, it is essential to prioritize conservation efforts. The concept of biodiversity hotspots provides a strategy for conserving the greatest biodiversity at the least cost . TraditiGenetic diversity within a species represents a fundamental level of biodiversity  and is aChina is a mega-diverse country, harboring more than 30,000 vascular plant species and about 2,340 terrestrial vertebrate species . Yet, ChIn this study, using the method of In addition, as the distribution of plant species richness in China has been reported in previous studies e.g., , it is fTable 1), while limiting inclusion to studies that sampled at least 10 populations in STC. For the included studies, populations less than three individuals were excluded from further analyses to reduce parameter bias due to small population size. The resulting datasets included 15 deciduous broadleaved trees, eight evergreen broadleaved trees, five perennial herbs, two conifers, two perennial deciduous vines and one annual herb. These species vary in habitat preference and ecology, including not only rare and endangered species but also dominant trees in EBLF of subtropical China.The genetic datasets for 33 different plant species distributing in subtropical region of mainland China were gathered from published literature or dissertations (permitted by the authors) from 2006 to 2016 (Table 1). The other genetic markers, e.g., AFLP, RAPD and ISSR, have been applied much less frequently in previous phylogeographical studies of STC plants  and haplotype diversity (dH), as well as pairwise population differentiation (STF). For microsatellite data, expected heterozygosity (EH) were estimated in GENALEX 6 (STF) were calculated in ARLEQUIN 3.0  and create divergence landscape. The estimates were firstly used to map a single species genetic divergence landscape for each species using ‘Genetic Landscapes Toolbox’ in ArcGIS 10.0 as follows. Pairwise genetic divergence values were mapped to the midpoints between collection locations. A surface was interpolated from the midpoints using Inverse Distance Weighted (IDW) interpolation . Then the genetic landscapes for all taxa were averaged into a multiple species genetic landscape to highlight areas of congruence. The final map was divided into classes by the classification method of standard deviation, which had a middle class centered on the mean with a range of 1 standard deviation (0.5 standard deviation to either side of the mean) (The statistics he mean) . Regionshe mean) .dH for sequence data and EH for microsatellite data are equivalent for both estimate the probability that two randomly chosen alleles or genotypes are different for diploid organisms  and sequence diversity (π) within a population was used to create diversity landscapes, respectively. Using IDW interpolation as described above, we firstly created gene diversity or sequence diversity landscapes for each species. Diversity values (dH/EH or π) were mapped to the actual collection locations, rather than to the midpoints between locations as done in divergence mapping. Finally, we calculated the average diversity multi-species genetic landscape for the two datasets, respectively. Based on the range of values present, we considered the areas with gene diversity or sequence diversity values greater than 1.5 standard deviations from the mean as the diversity hotspots.Within-population genetic diversity was calculated in two ways. rganisms . These tTo facilitate comparison between GD hotspots and SD hotspots, each of the above three genetic landscapes was clipped to the spatial extent of subtropical evergreen broadleaved forest in mainland China . FinallySpecies diversity data from 2 after clipping to the eco-region boundary. The mean normalized divergence value was 0.549 (SD = 0.091) and ranged from 0.181 to 0.945 . The areas with highest divergence (categorized as greater than 1.5 standard deviations above the mean) encompassed 135,141 km2 or 6.4% of the analyzed area. Nine regions were identified as AGD hotspots with highest levels of genetic divergence .The average divergence landscape covered 2,115,705 kmdH/EH) was averaged across all 33 species. The scaled gene diversity multi-species landscape encompassed 2,146,124 km2 after clipping. The mean normalized gene diversity was 0.347 (SD = 0.086) and ranged from 0.002 to 0.748 . The areas with highest gene diversity covered 80,767 km2 or 3.8% of the study area. We identified 10 locations as WGD hotspots with highest levels of gene diversity .Gene diversity (π) was averaged across 28 species. The scaled sequence diversity multi-species landscape covered 2,120,862 km2 after clipping. The mean normalized sequence diversity value was 0.150 (SD = 0.055) and ranged from 0.001 to 0.565 . The areas with highest sequence diversity encompassed 817,63 km2 or 3.9% of the analyzed area. We identified 12 locations as WGD hotspots with highest levels of sequence diversity . Seven of these sequence diversity hotspots overlapped with regions of high gene diversity .Sequence diversity (Table 3) for the five indices used in r = -0.280, -0.215, -0.270, -0.213, and -0.214, respectively, p < 0.001, Table 3). The spatial pattern of among-population diversity (AGD) was similar. We observed a significant west-east trend of decreasing AGD in STC region  for normalized average genetic divergence. On the contrary, there was a significant west-east trend of increasing within-population diversity (WGD) for normalized gene diversity  and normalized sequence diversity .There was a general and significant west-east trend of decreasing SD in STC . However, the latitudinal trend of WGD was positive and highly significant for sequence diversity  but negative and not significant for gene diversity .There also was a significant south-north trend of decrease of AGD .We found a strong biogeographical congruence between the areas with highest genetic diversity and the major biodiversity areas of the STC region. Geographically, 12 of 18 hotspots correspond approximately to the previously identified SD hotspots . However, the correlation between WGD and SD was significantly negative because the value of regional average gene diversity decreased significantly with five SD indices, respectively , and the relationship between regional average sequence diversity and three SD indices, i.e., WE, PE and BED, was also significantly negative .Correlation analysis showed the value of AGD increases significantly with increasing value of five indices of SD, respectively . Three hotspots have consistently high values of genetic divergence, gene and sequence diversity . These three mountainous regions are the important famous geographic division in China’s topography and phytogeography  is consistently high, 10 gene diversity hotspots and 12 sequence diversity hotspots where within-population genetic diversity is high. These hotspots were grouped into 18 geographic areas and most distributed at the periphery of subtropical China , both of them feature a high level of orographic heterogeneity and has several physical barriers that restrict east-west plant migration and genetic interchange, thereby facilitating genetic differentiation among populations. For example, three of the four hotspots  are transected by the ‘Tanaka-Kaiyong Line’ (TKL), a major phytogeographic boundary in southwest China separating Sino-Himalayan and Sino-Japanese Floras of East Asia , which could be interpreted by fewer physical barriers to gene flow. China is well-known with its three-step terrain from the west to the east. Although there are numerous mountains or hills in east China, they seldom exceed 2000 m above sea level and thus rarely function as barriers . This pattern is not unexpected because the western STC is much more complex in topography and environmental heterogeneity than the eastern STC. Spatial environmental heterogeneity always has a strong positive effect on SD by allowing coexistence of species with fitness optima at different positions along an environmental gradient , and nine of 14 WGD hotspots are also spatially congruent with the SD hotspots . High genetic divergence among populations may accelerate the speciation, differentiation and preservation for the species living in these areas , a common solution to overcome these difficulties is to find a reliable surrogate for genetic diversity and the relationship between SD and genetic diversity has recently gained renewed interest . In thisas e.g., . Moreoveas e.g., . The hybas e.g., . Therefoas e.g., .Table 4), except for sequence diversity and ER and PD. These results are at odds with the theoretical predictions that local habitat characteristics such as area, isolation, and spatial/temporal heterogeneity possibly induce parallel effects on species and genes via migration, drift and selection (Another component of genetic diversity (WGD), however, is negatively correlated with five SD indices in subtropical China  is rich in among-population genetic diversity, possessing four major AGD hotspots. It is well known that the areas surrounding the east and southeast of Qinghai-Tibetan Plateau (QTP) comprise one of the key high-latitude biodiversity hotspots in the world . The uplSecond, we found that WGD is positively correlated with longitude, with most WGD hotspots locate in east STC. This pattern suggests that eastern STC may represent an intraspecific genetic reservoir. However, protected areas in eastern STC are fragmented, largely as a result of urbanization and administrative division . EstabliThird, the importance of intraspecific diversity for ecosystem functioning and for preserving the evolutionary potential of species demands that genetic diversity should not be neglected when designing conservation strategies and networks of protected areas . HoweverDF and ZZ conceived this study and wrote the manuscript. JH, ZS, and SC analyzed the data. DF, HH, and YK drew the figures. All the authors read and approved the final manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Signal transducer and activator of transcription (STAT) 3 plays a central role in the host response to injury. It is activated rapidly within cells by many cytokines, most notably those in the IL-6 family, leading to pro-proliferative and pro-survival programs that assist the host in regaining homeostasis. With persistent activation, however, chronic inflammation and fibrosis ensue, leading to a number of debilitating diseases. This review summarizes advances in our understanding of the role of STAT3 and its targeting in diseases marked by chronic inflammation and/or fibrosis with a focus on those with the largest unmet medical need. Signal transducer and activator of transcription (STAT) 3 is one of a seven-member family of proteins that transduce peptide hormone signals from the cell surface to the nucleus . STAT3 iTLR activation leads, in many instances, to the activation of the master regulator of the mammalian inflammatory response, NF-κB. NF-κB upregulates a variety of pro-inflammatory mediators, including TNF-α, IL-1α, and IL-6. IL-6 binding to its heterodimeric receptor composed of IL-6Rα (membrane bound or soluble) and IL-6Rβ (gp130) results in heterodimer receptor oligomerization, transphosphorylation and activation of gp130-associated Jaks, notably Jak2, which phosphorylate gp130 at tyrosine (Y) residues within its cytoplasmic tail. The Src-homology (SH) 2 domain of STAT3 binds to gp130 pY residues within the gp130 with the consensus amino acid motif, YXXQ  STAT3 itself becomes phosphotyrosylated on Y705, homodimerizes through reciprocal pY-peptide/SH2 binding interactions, and accumulates in the nucleus where it binds to the promoters of genes containing specific binding elements, which leads to gene activation or repression and reprograms the cell acutely to resist apoptosis ,5,6. HowAsthma affects 10% of the population worldwide and its prevalence has been increasing over the last decade . It is aGata3, Maf, Batf, and Irf4) known to drive Th2 immune related activity [Early studies indicated that STAT3 may be important for the regulation of immune cell recruitment, specifically Th2 cells during allergic inflammation. These studies demonstrated the role of STAT3 in house dust mite (HDM)-mediated allergic inflammation in which they showed that targeted deletion of STAT3 in the airway epithelium or upstream inhibition of STAT3 activation prevented HDM-mediated allergic inflammation and airway hyper-responsiveness (AHR) . Subsequactivity . Interesactivity . Howeveractivity . TogetheThe role of STAT3 in the generation of Th17 cells is well known as is its activation by several cytokines, including transforming growth factor-β (TGF-β1), IL-1β, IL-6, and IL-23, which lead to increased expression of Th17 specific transcription factors, retinoic acid-related orphan receptor gamma (RORγ) and RORα ,19. DysrPharmacological targeting of STAT3 activity by inhibiting upstream kinases has been shown to significantly reduce HDM-induced lung inflammation. This observation is in agreement with available genetic data, and strongly supports the idea that STAT3 is a crucial mediator of Th2-driven allergic responses in the lung . The valOther signaling pathways associated with asthma appear to rely on STAT3 as a downstream factor; for instance, overproduction of sphingosine-1-phosphate (S1P) has been shown to lead to chronic inflammation associated with various diseases including asthma and colitis-associated cancer through the hyper-activation of NF-κB and STAT3 ,67. The Direct targeting of STAT1 and STAT3 using decoy oligonucleotides (dODN) was shown to reduce airway inflammation and AHR in lungs of mice challenged with HDM . The oveIBD is an idiopathic disease of the gastrointestinal tract with an estimated prevalence of 3.1 million in the United States . The twoThe etiology of IBD is unclear, although genetic susceptibility, immune responses, environmental triggers, and the luminal microbiota have been linked to disease pathogenesis ,83. Genoβ/Δβ transgenic mice, which express only the STAT3 α isoform, generated in Valeria Poli’s lab [We examined the effects of genetic modulation of STAT3 in whole animals, in mouse models of UC and CD (manuscripts in preparation). Two isoforms of STAT3 , derived from one gene by alternative mRNA splicing, are expressed in most cells in a 4:1 ratio (α:β). STAT3α is pro-inflammatory and anti-apoptotic, while STAT3β has opposing effects on STAT3α. Using STAT3 Δli’s lab  we deterli’s lab ,46).β/Δβ mice [β/Δβ mice probably due to the higher concentrations and duration of DSS that was used to induce UC, 5% DSS (for 7 days) versus 2.5% DSS (for 5 days).Several cytokines that are elevated in patients with IBD are known to activate STAT3 and or its downstream targets, including IL-6, IL-15, IL-21, IL-23, IL-17, IL-18, IL-10, IL-11, IL-22, IFNα/β /γ and matrix metallopeptidase 9 (MMP9) ,108,109./Δβ mice . In addiAntibodies against some STAT3-activating cytokines and/or their receptors implicated in IBD pathogenesis in mouse IBD studies have demonstrated benefit in patients with IBD. For example, use of a humanized anti-IL6R monoclonal antibody, tocilizumab, has completed phase 2 trials in humans with CD and has shown beneficial effects . Phase IA strategy that has been pursued to treat IBD is targeting of signaling pathways shared by cytokines implicated in disease pathogenesis. For example, the receptors of cytokines IL-2, IL-7, IL-9, IL-15, and IL-21 share a common subunit , which s+ T-cells, and reduced colon levels of IL-17-positive cells in both models. C188-9 treatment also down-modulated levels of DSS-induced STAT3 gene transcripts involved in inflammation, apoptosis-prevention, and colorectal-cancer metastasis, while upregulating genes associated with prevention of CRC. These findings with C188-9 provide proof-of-principle that small molecule targeting of STAT3 deserves consideration as a new approach to treatment of IBD, particularly in patients refractory to current therapies.We determined that administration of C188-9, a small-molecule direct inhibitor of STAT3 we developed (see above) was beneficial in pre-clinical models of IBD ,46. All Cachexia is a metabolic syndrome characterized by intractable muscle and fat storage wasting that is a major cause of mortality in patients with chronic low-grade inflammation such as those with end-stage heart failure, chronic kidney disease, chronic obstructive pulmonary disease (COPD), rheumatoid arthritis and cancer . CachexiCachexia, a disease of dysregulation of metabolic homeostasis, results from impaired regulation of the balance between anabolic and the catabolic states leading to loss of fat and skeletal muscle mass. Patients present with signs of metabolic dysfunction, such as increased insulin and Insulin-Like Growth Factor-I (IGF-1) resistance, induction of mitochondrial uncoupling proteins and fat tissue browning . MaintenAlthough factors contributing to cachexia are complex and multifactorial, Inflammation appears to be a central aspect underlying its pathophysiology . SeveralDespite some conflicting studies in mice concerning a direct role of IL-6 in cachexia , the preResults from early experiments demonstrated that muscles of mice that transgenically overexpressed IL-6 displayed a significant loss of muscle mass akin to cachexia. Inhibition of IL-6 activity using anti–mouse IL-6 receptor (mIL-6R) antibody reversed all the changes associated with atrophy . FindingNumerous functional and mechanistic studies have been done to elucidate the link between muscle and adipose tissue atrophy and IL-6 signaling. These studies have shown a strong association between phosphorylation of STAT3 at Y705 and muscle atrophy. It has been established in various mouse models of cachexia that IL-6 catabolic signaling in cachexia is exerted through the transcription factor STAT3 ,147.IL-6-mediated cachexia has been shown to be associated with increased proteolytic activity in skeletal muscle cells. Recent studies have uncovered how STAT3 signaling engages the muscle specific proteolytic pathways in cachexia to induce muscle mass loss. Insights into how STAT3 activation leads to protein degradation in cachexia came from studies that looked into the effects of catabolic conditions such as CKD and streptozotozin-induced acute diabetes on muscle metabolism in muscle-specific STAT3 knock out mouse . The datAutophagy is another potential mechanism by which muscle mass is modulated in cachexia. Autophagy is an evolutionarily conserved process that is deployed under stress as a survival mechanism to maintain homeostasis. The role of autophagy in maintenance of proper muscle function is complex. Basal levels of autophagic activity may be necessary for the maintenance of muscle mass, as evidenced by data in mice with muscle specific deletion of a gene required for autophagy, autophagy related 7 (ATG7); these mice suffer significant loss of muscle mass. In fact, diminished autophagy has been linked to certain forms of muscle myopathies . On the The role of STAT3 in autophagy is equally complex and varied, as STAT3 has both anti and pro-autophagy roles depending on the context . Recent Rapid loss of white adipose tissue (WAT) is a defining feature of cachexia and usually precedes muscle wasting. In addition to white adipose tissue depletion, cachectic patients also gain brown adipose tissue (BAT) that is rich in mitochondria that are uncoupled from ATP production . This prLipid homeostasis is maintained through the balanced control of lypolytic and lypogenic pathways, which are subject to external modulatory factors such as hormones and cytokines. For example, Jak2 seems to play an important role in adipose tissue catabolism as shown by bodyweight gain due to adiposity in Jak2 adipose specific knockout mice . The incAs discussed above, available data identify STAT3 as a target for cachexia intervention. Several known STAT3 inhibitors, designed to directly target hyper-phosphorylated STAT3 in cells, have been used as chemical probes to corroborate genetic experiments that highlight the role of STAT3 in cachexia. A majority of compounds that show inhibitory activity toward STAT3 activation also reduced markers of cachexia in cell culture models. For instance, treatment of C2C12 myotubes for 48 hours with a cell-permeable STAT3 SH2 domain mimetic peptide (SIP) resulted in modest myofiber hypertrophy and prevented IL-6-induced fiber atrophy .We have shown that treatment of the CDK cachexia mouse model with the small molecule STAT3 inhibitor, C188-9, antagonized catabolic signaling by decreasing myostatin expression and the activation of its downstream signaling mediators, p-Smad2 and p-Smad3 . In addiOther modalities of STAT3 inhibition have also been investigated in cachexia with promising results. For example, there are reports that the histone deacetylase (HDAC) inhibitor, AR-42, is a potent inhibitor of STAT3 activity . Recent Tissue fibrosis is a pathological condition that affects almost every organ in the body. It imposes a significant worldwide disease burden with very few effective therapies available. Estimates show that in developed countries alone, approximately 45–50% of deaths are attributable to fibrosis ,165. FibMyofibroblasts have long been identified as the chief culprit in fibrosis development. The persistent expansion and activation of tissue myofibroblasts is a salient feature of fibrosis and a major driver of disease progression . MyofibrBecause improper regenerative healing is closely linked to inflammation, anti-fibrosis strategies have traditionally focused on inhibiting upstream pro-fibrotic cytokines and growth factors with the aim of blocking persistent myofibroblast generation, expansion and activation. Several important signaling pathways have been identified as frequently activated in fibrosis, including the Transforming Growth Factor (TGF)-β, Wingless/INT (WNT) and Yes-associated protein (YAP)/ transcriptional coactivator with PDZ-binding motif (TAZ) components of the hippo signaling pathway . TGF-β sSTAT3 activation during tissue repair has been extensively studied because of its prominent role following tissue injury. STAT3 is activated as a result of the inflammatory reaction that constitutes the first stage of wound healing . MoreoveIt is known that under normal conditions STAT3 plays a positive role in cell survival and proliferation. However, it has deleterious effects when persistently activated, contributing to a wide variety of pathological conditions . SimilarSeveral studies show that STAT3 contributes to fibrosis by inducing the production of the ECM. Collagen type I (COL1), which consists of two α1 (COL1A1) chains and one α2 chain (COL1A2), is a hallmark of fibrosis. TGF-β through its downstream effectors has a major influence on the production of the ECM and is by far the predominant signaling network driving fibrosis. Several non-canonical transcription factors have been shown to bind the COL1A2 gene promoter to enhance its transcription in response to TGF-β stimulation, including STAT3. Recent findings demonstrate that, in conjunction with JunB, STAT3 is able to directly control COL1A2 enhancer activation . SimilarAnother mechanism for STAT3 modulation of fibrosis is through the transcriptional control of matrix metalloproteinases (MMPs) and their cognate inhibitor proteins—tissue inhibitors of metalloproteinases (TIMPs)—that are important in the maintenance of the ECM. Although MMPs are mainly known to mediate degradation of the extracellular matrix and hence, thought to be anti-fibrotic, they have also been linked to a variety of other cellular processes that modulate fibrosis . In fact4. In addition, the levels of TIMP-1 in the liver and serum after chronic CCl4 treatment were markedly diminished in hepatocyte-specific STAT3 knockout mice [On the other hand, TIMP-1 is an important player in ECM maintenance that binds to and inhibits activity of MMPs. It is a known downstream gene target of STAT3  and playout mice .Apoptosis of ECM-producing cells also is important for resolution of the wound-healing process. Because STAT3 is known to confer strong proliferative effects and resistance to apoptosis , it is tUnderstanding the molecular mechanisms behind the biogenesis of ECM-producing myofibroblasts is thought to be of great importance and has powerful implications in the development of effective anti-fibrotic treatments. There still is an ongoing debate regarding the lineage of myofibroblasts found in fibrotic tissues. Based on genetic lineage tracing, ECM-producing myofibroblasts in almost all organ systems appear to arise from a diverse origin involving organ resident cells such as, mesenchymal stem cell (MSC), fibroblast and pericytes. The transition to myofibroblast occurs in response to numerous growth factors and cytokines, predominantly TGFβ and others including WNT, epidermal growth factor (EGF), and IL-6 that are locally produced ,171. TheAlthough data are emerging that challenge the idea that some myofibroblasts have an epithelial lineage, it still remains a widely held view that mesenchymal cells arising from aberrant epithelial-to-mesenchymal transition (EMT) contribute significantly to the population of myofibroblasts in fibrosis. STAT3 is known to play an important role in EMT. For example, kinases such as Fyn and Src have been known to activate STAT3 and drive EMT in many tumor systems ,190. IntSTAT3 and TGF-β1 are involved in a complex interplay that appears to have broad functions in different biological contexts. Data on the effects of STAT3 activation on TGF-β signaling are not always straightforward and, at times, are paradoxical. For example, most studies suggest that STAT3 activation drives the induction of TGF-β1 and is one of the mechanisms by which STAT3 enhances organ fibrosis. Another study by O′Reilly et al also showed that STAT3 activation by IL-6 in dermal fibroblasts leads to TGFβ activation through an indirect mechanism mediated by Gremlin-1 . HoweverBlocking STAT3 activity can be accomplished indirectly through targeting of upstream components of JAK/STAT signaling network, which can be problematic because of the redundant and adaptive nature of the fibrotic signaling , or direWe tested our small molecule inhibitor of STAT3, C188-9, in several animal models of fibrosis ,65. In aC188-9 also showed efficacy in two models of scleroderma—the subcutaneous bleomycin (BLM) model and the tight-skin mouse (Tsk-1) model. Reduction in pY-STAT3 levels by C188-9 reduced fibrosis in both models as measured by loss of collagen accumulation and decrease in dermal and hypodermal thickness in each respective model . Similar4) model of fibrosis, cucurbitacin-B mitigates fibrosis through inhibition of STAT3. STAT3 inhibition coincided with diminished levels of hydroxyproline in liver tissue as well as expression of collagen-1α, α-SMA and TGF-β [Pten knockout (HepPten-) mice, a mouse model of nonalcoholic steatohepatitis (NASH), reduced liver steatosis and hepatic fibrosis in addition to blocking progression of hepatocellular carcinoma [In the hepatic carbon tetrachloride  activation and is a critical point at which signals from both pathways converge . FurtherAnother example of the role of STAT3 as an integrator can be seen in a phenomenon referred to as ′TGF-β switch′ in which TGF-β appears to have tumor suppressive effects in epithelial cells, whereas in tumor cells it is pro-tumorigenic. Other data show that K-ras mutations alter the STAT3 interactome leading to the switch that induces non-canonical STAT3-mediated production of Snail, leading to EMT and tumor progression .Recent work by Chakraborty et al. provides concrete evidence that STAT3 integrates TGF-β signaling in fibrotic skin cells. They show that STAT3 is activated by various kinases, including JAK, Src, c-ABL, and JNK, in response to TGF-β stimulation and that genetic and biochemical blockade of STAT3 activity prevented TGF-β-induced fibroblast-to-myofibroblast transition and mitigated skin fibrosis in two mouse models of scleroderma . In addiThere also are examples of STAT3 serving as a signal integrator in other inflammatory diseases. For example, the collaboration between STAT3 and NF-κB pathways has been shown to modulate IFN-γ/TNF-α-induced muscle wasting, suggesting that inflammatory signaling acts through integrated networks of downstream effectors, such as STAT3 and NF-κB to induce cachexia .Crosstalk between multiple signaling networks is integral to the pathogenesis and progression of many inflammatory associated diseases. The concept of STAT3 as a signal integrator can help in understanding the role that it plays in a broader context, especially as a crucial mediator of a wide variety of inflammatory diseases.These are frustrating times for patients with chronic inflammatory diseases refractory to current treatments, such as steroid-resistant asthma, or those with diseases for which no truly effective treatments exist, including patients with cachexia and fibrosis. The evidence reviewed above unequivocally implicates STAT3 in each of these diseases. Strategies aimed at IL-6, its receptor, or members of the JAK kinase family, all of which target STAT3 indirectly, show promise. There is hope that one or more of these strategies may lead to a treatment that becomes standard of care. However, based on the findings for C188-9, there is reason for even greater hope of developing a safe and broadly effective agent that directly targets STAT3 to treat these diseases.As the number of STAT3 inhibitors in development increase and some are tested in clinical trials, there are potential pitfalls to be considered in the clinical development of these agents. For instance, most STAT3 inhibitors have been designed to target protein/protein or protein/DNA interactions, which pose considerable challenges with respect to specificity, considering that there are close structural similarities among STAT proteins. It is not surprising that many STAT3 inhibitors suffer from lack of specificity ,68. WhatIn addition, because of the important role that STAT3 plays in normal cell function, for example, in wound healing and Th17-related immune defense, there is a potential risk of impaired wound healing and immunosuppression that needs to be taken into account during clinical trials and in Phase IV evaluations, should an agent be FDA-approved. Presently, some STAT3 inhibitors have advanced into Phase I/II/III studies. Thus far, negative impacts on wound healing and immune function have not been reported. Clearly, further study is necessary to definitively determine the full impact of STAT3 inhibition, including any adverse effects that may arise.Another area of interest with regard to STAT3 inhibition involves its well-known role in mitochondrial function; STAT3 is required for optimal function of the electron transport chain . Thus, t


Although habitat loss has large, consistently negative effects on biodiversity, its genetic consequences are not yet fully understood. This is because measuring the genetic consequences of habitat loss requires accounting for major methodological limitations like the confounding effect of habitat fragmentation, historical processes underpinning genetic differentiation, time-lags between the onset of disturbances and genetic outcomes, and the need for large numbers of samples, genetic markers, and replicated landscapes to ensure sufficient statistical power. In this paper we overcame all these challenges to assess the genetic consequences of extreme habitat loss driven by mining in two herbs endemic to Amazonian savannas. Relying on genotyping-by-sequencing of hundreds of individuals collected across two mining landscapes, we identified thousands of neutral and independent single-nucleotide polymorphisms (SNPs) in each species and used these to evaluate population structure, genetic diversity, and gene flow. Since open-pit mining in our study region rarely involves habitat fragmentation, we were able to assess the independent effect of habitat loss. We also accounted for the underlying population structure when assessing landscape effects on genetic diversity and gene flow, examined the sensitivity of our analyses to the resolution of spatial data, and used annual species and cross-year analyses to minimize and quantify possible time-lag effects. We found that both species are remarkably resilient, as genetic diversity and gene flow patterns were unaffected by habitat loss. Whereas historical habitat amount was found to influence inbreeding; heterozygosity and inbreeding were not affected by habitat loss in either species, and gene flow was mainly influenced by geographic distance, pre-mining land cover, and local climate. Our study demonstrates that it is not possible to generalize about the genetic consequences of habitat loss, and implies that future conservation efforts need to consider species-specific genetic information. In spite of ample evidence showing that habitat loss has large, consistently negative effects on biodiversity , very feImportant limitations constrain the quantification of habitat amount effects on genetic variation. Firstly, habitat loss and fragmentation are often confounded, so disentangling the relative contribution of habitat amount requires controlling for fragmentation . SecondlFew studies have attempted to quantify the impact of habitat loss on both genetic diversity and gene flow, and none has yet accounted for all the methodological limitations outlined above . Here weBrasilianthus carajensis (Melastomataceae) and Monogereion carajensis (Asteraceae), were among the easiest to find and identify in the field. Since both species seem to be pollinated by insects and their seeds dispersed by the wind . Samples were collected in the main Canga plateaus of our study area, comprising the entire occurrence range of both species. Care was taken to sample individuals at or around iron ore mines and separated by at least 20 m from each other to avoid collecting siblings . Our study area harbors some of the world’s largest iron ore mines, one located in Serra Norte, comprised of an archipelago of Canga plateaus, and one in Serra Sul formed by a large continuous plateau. While in Serra Norte we collected 103 and 120 individuals, in Serra Sul we sampled 17 and 49 individuals of B. carajensis and M. carajensis respectively. To ensure high DNA quality and concentration, we preserved B. carajensis samples in silica and M. carajensis samples in 10 ml of a NaCl-saturated solution of 2% cetrimonium bromide (CTAB) (B. carajensis was extracted using a CTAB 2% protocol (M. carajensis. DNA concentration for both species was quantified using the Qubit High Sensitivity Assay Kit (Invitrogen), and DNA integrity assessed through 1.2% agarose gel electrophoresis. All DNA samples were adjusted to a final concentration of 5 ng/µl in a final volume of 30 µl. We used flow cytometry to estimate genome size in both species. Nuclei were obtained from fresh leaf tissues chopped along with references in general purpose buffer with 1% Triton X-100 and 1% PVP-30  , and stoprotocol  followedprotocol ; whereas% PVP-30 . The who1.98 pg, ].http://snpsaurus.com/) for sequencing and bioinformatic analyses of raw reads . Briefly, nextRAD genotyping-by-sequencing libraries were prepared . Fragmented DNA was then amplified for 25 cycles at 75°, with one of the primers matching the adapter and extending 8 nucleotides into the genomic DNA with the selective sequences GTGTAGAA (B. carajensis) and TGCAGGAG (M. carajensis). Thus, only fragments starting with a sequence that can be hybridized by the selective sequence of the primer will be efficiently amplified. The nextRAD libraries were sequenced on a HiSeq 4000 with four lanes of 150 bp reads (University of Oregon). Genotyping analysis used custom scripts  that trimmed the reads using bbduk : bbmap/bbduk.sh in = $file out = $outfile ktrim = r k = 17 hdist = 1 mink = 8 ref = bbmap/resources/nextera.fa.gz minlen = 100 ow = t qtrim = r trimq = 10. A de novo reference was created by collecting 10 million reads in total, evenly from the samples, and excluding reads that had counts fewer than 5 or more than 700 for B. carajensis; and fewer than 6 or more than 1,000 for M. carajensis. The remaining loci were then aligned to each other to identify allelic loci and collapse allelic haplotypes to a single representative. All reads were mapped to the reference with an alignment identity threshold of 90% using bbmap (BBMap tools). Genotype calling was done using Samtools and bcftools . The variant call format (vcf) file was filtered to remove alleles with a population frequency of less than 3%. Loci were removed that were heterozygous in all samples or had more than two alleles in a sample . The absence of artifacts was checked by counting SNPs at each read nucleotide position and determining that SNP number did not increase with reduced base quality at the end of the read. A total of 43,887 contigs were generated for B. carajensis (sequencing depth ranged between 18 and 239), and 36,040 for M. carajensis (depth ranging between 14 and 246). Geographic coordinates in decimal degrees, genotypes in vcf and sequences in FASTA format for both species are provided here: https://figshare.com/articles/Habitat_loss_does_not_always_entail_negative_genetic_consequences/8224175.DNA samples were shipped to SNPSaurus (prepared  using Nehttps://github.com/nspope/r2vcftools)—A Wrapper for Vcftools (https://github.com/rojaff/r2vcftools_basics). We excluded loci containing more than 30% missing data, and filtered them for quality (phred score > 50 both species), read depth (30–240 both species), linkage disequilibrium , and strong deviations from the hardy weinberg equilibrium  (FST outlier tests were applied after assessing population structure with the snmf function from the LEA package (Q = 0.05) was used to correct for false discovery rates (http://membres-timc.imag.fr/Olivier.Francois/LEA/files/LEA_snmf.html). The resulting sets of neutral and independent loci were then used in all subsequent analyses.The R package r2vcftools (Vcftools —was usedspecies) . Additio package . The genry rates , see exafind.cluster, which runs successive k-means clustering with an increasing number of clusters, and then determined the best-supported number of genetic clusters using the Bayesian Information Criterion (BIC). Considering the ancestry coefficients assigned by Admixture, we then estimated expected heterozygosity (HE) and inbreeding coefficients (F) for each genetic cluster using the “het” option in VCFtools implemented in r2vcftools (loess in R (span = 0.75). At each permutation a LOESS model was re-fitted using the permuted relatedness and geographic distance matrix, and 95% percentiles of the permutation-derived LOESS predictions were used to generate confidence envelopes around the null expectation (see example script here: https://github.com/rojaff/Lplot).We used two complementary genetic clustering method to assess population structure: Admixture  and discvcftools . Additiovcftools . To do sLandsat 2 images  were used for year 1979, Landsat 7 images  for year 2011, and Sentinel images  for years 2014 and 2016. Images were downloaded from the Earth Explorer Server (https://earthexplorer.usgs.gov/), selecting scenes from the month of July to minimize clouds. All images were converted to ground reflectance in percentage using the Atmospheric and Topographic Correction algorithm of the PCI Geomatica 2016 software. The scenes were joined to create a mosaic of the study area and derive the Normalized Difference Vegetation Index—NDVI , comprising pre-mining maps (1979). dex—NDVI . We thenH and f), estimated with “het” option in VCFtools  are affected by demographic processes, we explicitly accounted for demography either by analyzing individuals belonging to the same cluster or by including genetic cluster identity as a random effect in our models. In Serra Norte, which comprises an archipelago of Canga plateaus, we fit linear mixed-effect models, using each plateau as a random effect to account for site-specific characteristics and spatial autocorrelation. In the case of B. carajensis from Serra Norte, we also included a random effect specifying the genetic cluster containing each individual (see genetic structure results using the Admixture software). In Serra Sul, which comprises a single large plateau, we used generalized least-squares models (GLS) fitted with different correlation structures  to explicitly model spatial autocorrelation. The “weight” argument was used in some cases to account for heteroscedasticity. Raw f and logit-transformed H were used as response variables and models fitted using the nmle R package (α = 0.05), and all models were validated by plotting residual vs. fitted values and by checking for residual autocorrelation. Relative variable importance was calculated summing the Akaike weights of the best-fitting models in which the variable of interest was present . Model averaging across the set of best models was used to compute parameters estimates that account for uncertainty in model selection . These were minimum temperature of coldest month (bio06) and precipitation of wettest (bio16) and coldest quarter (bio19) for B. carajensis; and minimum temperature of coldest month (bio06), precipitation of wettest quarter (bio16), and temperature seasonality (bio04) for M. carajensis.To assess the effect of habitat loss on gene flow, we first optimized gene flow hypotheses and then tested them by modeling isolation by resistance . Yang’sResistanceGA package to generate optimized resistance surfaces for each one of these variables . The whole process was iterated until no significant change was found in the objective function  was implemented through the ariables . The advariables . Moreovefunction . We thenfunction . Ten indfunction . All rasfunction . Land cohttps://github.com/nspope/corMLPE; . To evaluate the incidence of time-lag effects potentially masking mining effects on gene flow, we first fitted uni-variate models for each species and region using resistance distances from land cover surfaces for all years, plus those from geographic distance surfaces. The best models were selected using the Akaike Information Criterion (ΔAIC < 2), and whenever geographic distance was found among the best models we considered IBD as the most parsimonious gene flow model . Yang’sow model . To evalow model Table S2edge_mc; ], and beedge_mc; , and reladegenet .® paper, Canga topsoil, forest topsoil, and mining waste substrate) placed in plastic boxes (Gerbox—11 x 11 x 4 cm) and kept in a growth chamber  under continuous darkness, constant temperature (20°C) and air humidity (60%) for 33 consecutive days, from September 4th to October 7th 2018. Substrates received distilled water until the retention capacity, and water losses by evaporation were replaced daily. All treatments were carried out with five replicates for each substrate in each species. Each replicate contained 25 seeds from B. carajensis and 12 seeds from M. carajensis. The number of germinated seeds was recorded daily, with germination defined as the emission of 2 mm of primary root.To evaluate if seeds from both study species are able to germinate inside iron ore mines, we ran a set of germination experiments. Seeds from both species were sown over four different substrates  indicated the presence of three clusters in rajensis S6. ClusH) and inbreeding (f) were not influenced by habitat loss, either in Serra Norte nor in Serra Sul, as the set of best-fitting models always included null models or historical (pre-mining) habitat amount , additional covariates modeled along with land cover included geographic distance, terrain roughness, elevation, and bioclimatic variables. The optimization of resistance surfaces revealed that Canga was the land cover class representing lowest resistance to gene flow in both species, whereas mining areas and evergreen forests imposed higher resistance S10. HowM. carajensis showed similar germination in Canga and mining substrates, germination rates of B. carajensis were higher in Canga topsoil (Germination experiments revealed that seeds from both species are able to germinate in mining waste substrates. Whereas B. carajensis and by pre-mining land cover and local climate in M. carajensis.Our study is the first to assess the genetic consequences of habitat loss while accounting for all the major limitations constraining the quantification of habitat amount effects on genetic variation. Our results reveal that habitat loss driven by mining did not affect genetic diversity or gene flow in two endemic herbs from Amazonian savannas. Whereas historical habitat amount was found to influence inbreeding, heterozygosity and inbreeding were not affected by habitat loss in either species. Finally, gene flow was mainly influenced by geographic distance in B. carajensis mirrored that from the co-occurring perennial morning glory Ipomoea maurandioides (M. carajensis only presented one cluster in Serra Norte and another one across the remaining distribution range. This genetic structure was considered when assessing landscape effects on genetic diversity and gene flow in order to control for historical demographic processes. Additionally, since open-pit mining in our study region did not usually result in decreased structural connectivity between habitat patches (since these were already separated, The genetic structure in ndioides , showingI. maurandioides (The maintenance of genetic diversity in spite of extreme habitat loss suggests that our study plants are able to colonize mining environments and maintain gene flow across open-pit mines. Germination experiments revealed that seeds from both species can indeed germinate in mining waste substrates. Additionally, both plant species showed extensive gene flow across mining areas, and mining neither enhanced nor hindered gene flow. Similar results were found for a threatened orchid and the American pika, which showed analogous levels of genetic diversity in mining and natural habitats , althougndioides , and sinndioides . Our resndioides . A possindioides .B. carajensis and M. carajensis populations, respectively. Considering the strong winds characterizing Montane savanna ecosystems from the Carajás Mineral Province (M. carajensis populations from Serra Sul better than IBD, suggesting mismatches in flowering periods (Both species presented spatial autocorrelation in genetic relatedness in Serra Norte but not in Serra Sul, indicating a more restricted gene flow in the Canga archipelago of Serra Norte than in the large continuous plateau of Serra Sul. Additionally, geographic distance was weakly correlated with recent land cover resistance in Serra Norte but not in Serra Sul, where it was strongly correlated with land cover resistance from all years (Province , and theProvince , we posiProvince , suggest periods  or diffe periods . We neveThe absence of an effect of habitat loss on genetic variation can be attributed to time-lags between the onset of disturbances and genetic responses . We overThe incidence of time-lag effects on the response of genetic diversity to habitat loss is nevertheless more difficult to assess, since different metrics respond at different rates. Empirical and simulations studies have shown changes in inbreeding and allelic richness immediately after the onset of disturbances, whereas heterozygosity is usually lost more slowly, over subsequent generations . We therUsing thousands of genetic markers to study two annual endemic plants in replicated landscapes, we found that extreme habitat loss driven by mining did not result in any detectable genetic consequences. Since our results are largely unbiased by the effect of habitat fragmentation, the underlying genetic structure of plant populations, the resolution of spatial data, or time-lag effects, they reveal that habitat loss does not always entail negative genetic consequences. Although habitat fragmentation has been shown to disrupt gene flow and increase inbreeding across plants species, regardless of their characteristics , our stuInstituto Tecnológico Vale is a non-profit and independent research institute, and the choice of questions, study organisms and methodological approaches were exclusively defined by the authors, who declare no conflicting interests.https://figshare.com/articles/Habitat_loss_does_not_always_entail_negative_genetic_consequences/8224175. All the mentioned R scripts have been deposited in GitHub and their url addresses provided in the text.Geographic coordinates in decimal degrees, genotypes in Variant Call Format and sequences in FASTA format for both species are provided here: RJ conceived, designed, and coordinated the project. RJ and PLV coordinated the field work and sampling. ÉCML, ARS, CFC, NCF and MG performed laboratory work. RJ, ÉCML, CSC, ARS, WNJ and CFC performed the data analysis. The first draft of the paper was written by CSC and ÉCML with input from RJ. All authors contributed to discussing the results and editing the paper.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Mage = 26.74, SD = 7.56). It was found that perfectionistic strivings may promote the development of identity by supporting adaptive exploration and identity commitment. This relationship was only partly mediated. On the other hand, perfectionistic concerns were associated with significant difficulties with identity formation. This relationship was largely indirect, and indecisiveness proved to be the main mediator of the perfectionistic concerns–identity relationship. High indecisiveness, which disturbs decision-making processes, seems to explain why maladaptive perfectionists have problems with identity formation. These mediational effect was observed in both analyzed domains.The objective of the study was to assess the relationships between two dimensions of perfectionism, that is, perfectionistic strivings and perfectionistic concerns, and identity processes in the domains of future plans and education. It was hypothesized that such consequences of perfectionism as worry, rumination, indecisiveness, and guilt and shame proneness would be mediators of the perfectionism–identity relationship. A total of 696 students took part in the study ( Personal identity is a personality structure that arises from identification with selected values, social roles, and lifestyles . Accordicommitment formation cycle, in which an individual explores broadly  and makes commitments (commitment making process: refers to enacting choices in different identity domains often as a result of exploration in breadth) and (2) a commitment evaluation cycle, in which the commitments undertaken are thoroughly assessed , which opens the way to identification with these commitments (identification with commitment: the level of certainty with regard to commitments made). However, sometimes, mainly for individual reasons , exploration processes take a maladaptive form called ruminative exploration , and instead of supporting identity commitment, they may even hinder it (in-depth exploration (similar to exploration in-depth from the Luyckx model), in which the individual focuses on better understanding of the area of commitment, and (2) reconsideration of commitment, based on comparing alternative decisions . In these two models, identity formation in adolescence and adulthood is a continuous process of making commitments, assessing them, and changing (if they prove unsatisfactory) or identifying with them . Research conducted within these two models showed that adaptive exploration processes focused on obtaining information , and strong commitments and identification with them, are associated with better adaptation, while people with high ruminative exploration and strong reconsideration of commitment are characterized by lower quality of life, high anxiety, low self-esteem, and increased risk of mental problems  and perfectionistic concerns  and identity processes. These two studies on the perfectionism–identity relationship indicate that perfectionists, especially those high on perfectionistic concerns  and with higher commitment and identification with commitment, while perfectionistic concerns would be associated primarily with difficulties in identity formation .The present study is the first one devoted to identification of mediating factors in the relationship of perfectionism and identity processes. It was anticipated that in line with the perfectionism cognition theory such consequences of perfectionism, especially of perfectionistic concerns, as worry, indecisiveness, and rumination, and proneness to experience such negative emotions as guilt and shame , 2018 woM = 26.74, SD = 7.56). All participants were Polish, full-time or part-time psychology students, and Caucasian; 85% of the respondents were women. All participants were informed of the purpose of the study and about the voluntary nature of participation. The students received credits for participation, which they needed to complete their studies . All participants provided informed consent.The study included 696 participants, aged 18 to 42 years (It is important to me that I be thoroughly competent in everything I do), while perfectionistic concerns were assessed with the sum of two other subscales: Concern over Mistakes  and Doubts about Actions . The remaining subscales were not included in the analyses as they do not constitute core facets of perfectionism , exploration in depth , ruminative exploration , commitment making , and identification with commitment . Answers were given on a five-point Likert scale, from 1-strongly disagree to 5-strongly agree. Cronbach’s alphas were 0.79, 0.71, 0.87, 0.92, and 0.90, respectively. The second identity measure was the Utrecht-Management of Identity Commitments Scale, in the version used to measure educational identity , in-depth exploration , and reconsideration of commitment . The answers were given on a five-point Likert scale, from 1-completely untrue to 5-completely true. Cronbach’s alphas were 0.89, 0.72, and 85, respectively.Identity processes in the future plans domain were assessed using the Dimensions of Identity Development Scale DIDS; . The sca U-MICS; . The U-Mfeeling humiliated, feeling laughable), and 6 assess proneness to feeling guilt ; the other items were not included. The respondent indicates the frequency of experiencing individual emotional states on a scale from 0-never to 4-continuously or almost continuously. Cronbach’s alphas were 0.88 and 0.83, respectively.Proneness to shame and guilt was measured with the Personal Feelings Questionnaire-2 PFQ-2; . The scaWorry Domains Questionnaire-Short Form , Lack of Confidence, Aimless Future, Work, and Financial. All items were rated on a five-point scale, from 0-not at all to 4-extremely. As the DIDS questionnaire also concerns assessment of the future plans, two WDQ-SF items related to the future were not included in the analysis. The general score was used, being the sum of the eight remaining items. Cronbach’s alpha was 0.90.The  WDQ-SF;  was usedI try to put off making decisions), assessed on a Likert scale from 1-strongly disagree to 5-strongly agree. Cronbach’s alpha was 0.91.Indecisiveness was measured with the Frost Indecisiveness Scale FIS; . The meaMy attention is often focused on aspects of myself I wish I’d stop thinking about). Items were rated on a Likert scale from 1-disagree, to 5-strongly agree. Cronbach’s alpha was 0.84.The tendency to ruminate was measured by one of the scales of the shortened version of the Rumination-Reflection Questionnaire RRQ; . The scaPearson’s correlation was used to evaluate bivariate correlations between all variables. The analyses were performed using SPSS 25. Then, a mediation analysis was carried out  using pa2  = 4.38, p > 0.05, CFI = 0.99, RMSEA = 0.04, SRMR = 0.02. Perfectionistic strivings were positively associated with exploration in breadth , exploration in depth , commitment making , and identification with commitment , and negatively with ruminative exploration . Perfectionistic concerns were related negatively with commitment making  and with identification with commitment , and positively with ruminative exploration . The model explained 2% of the variance in exploration in breadth, 6% of the variance in exploration in depth, 24% of the variance in ruminative exploration, 15% of the variance in commitment making, and 18% of the variance in identification with commitment.The first step was the direct effects model test (A), in which the two dimensions of perfectionism were treated as predictors of the five identity processes from the Luyckx model . This mo2  = 47.15, p < 0.001, CFI = 0.99, RMSEA = 0.07, SRMR = 0.03. Finally, in the third step, model C was evaluated . The partial mediation model proved to be better fitted than model B, SBS-χ2  = 2.49, p > 0.05, CFI = 1.00, RMSEA = 0.02, SRMR < 0.01 . Model C explained 6% of the variance in exploration in breadth, 11% of the variance in exploration in depth, 37% of the variance in ruminative exploration, 23% of the variance in commitment making, and 23% of the variance in identification with commitment. Taking all this into account, it was assumed that the partial mediation model (C) was the most optimal. The direct relations between variables from model C are shown in In the next step, the full-mediation model (B) was tested, where guilt, shame, worry, indecisiveness, and rumination were placed as mediators. Both dimensions of perfectionism were treated as predictors of the mediators, and the mediators as direct predictors of identity dimensions. Model B was also well fitted to the data, SBS-χPerfectionistic strivings were significantly negatively related to shame, worry, and indecisiveness. In turn, perfectionistic concerns were positively associated with all mediators, with the strongest relationships observed for worry and indecisiveness. The results also revealed the suppressor effect described in the literature on perfectionism . If the After taking into account the mediators, the initial, negative relationship between perfectionistic strivings and ruminative exploration was completely reduced. Relationships with other dimensions of identity remained significant, but in two cases they were clearly weakened: exploration in breadth, from 0.32 to 0.10, and identification with commitment, from 0.36 to 0.22. In the case of perfectionistic concerns, their initial relationship with ruminative exploration and commitment making was completely reduced, while the negative relationship with identification with commitment remained significant, although it was weakened (from −0.33 to −0.10). 2  = 0.42, p > 0.05, CFI = 1.00, RMSEA < 0.01, SRMR < 0.01. Perfectionistic strivings were positively associated with commitment  and in-depth exploration , and negatively with reconsideration of commitment . Perfectionistic concerns were negatively connected with commitment  and positively with reconsideration of commitment . The dimensions of perfectionism explained 11% of the variance in commitment, 4% of the variance in in-depth exploration, and 12% of the variance in reconsideration of commitment.Model A, as in the previous case, was saturated, but because perfectionistic concerns were not significantly associated with in-depth exploration, the value of this parameter was set to 0. The model thus created proved to be very well fitted to the data: SBS-χ2  = 28.33, p < 0.001, CFI = 0.99, RMSEA = 0.07, SRMR = 0.02. Finally, in the third step, the partial mediation model (C) was evaluated, in which a direct relationship between perfectionism and identity was added (the path that was insignificant in model A was set to 0). The partial mediation model proved to be better fitted to the data than model B, SBS-χ2  = 0.74, p > 0.05, CFI = 1.00, RMSEA = 0.02, SRMR < 0.01 . Model C explained 15% of the variance in commitment, 5% of the variance in in-depth exploration, and 16% of the variance in reconsideration of commitment. The path coefficients in model C are shown in In the next step, a full-mediation model (B) was tested, which was also very well suited to the data, SBS-χFurthermore, in the educational domain, some of the mediators were positively associated with in-depth exploration (worry), while others were negatively related (shame). Among the mediators, indecisiveness was the only significant specific predictor of lower commitment and, together with worry, was a predictor of higher reconsideration of commitment. On the other hand, rumination was negatively related to reconsideration of commitment.The present study focused on the relationships between perfectionism and identity. It was suggested that perfectionistic strivings would support coping with identity issues  while perfectionistic concerns would be a risk factor in this processes increasing the risk for identity diffusion . The findings confirm these hypotheses and previous observations . PerfectIt was also suggested that cognitive processes  and negative emotional experiences characteristic for perfectionists (shame and guilt) can be responsible for the observed relationships between perfectionism and identity processes . This asThe results of the mediation analysis suggest that the relationship between perfectionistic strivings and identity is mainly direct, and the very fact that some people set very ambitious and demanding goals facilitates coping with an identity crisis. Admittedly, it has been observed that perfectionistic strivings also contribute to better cognitive and emotional functioning , which indirectly support identity formation, but this indirect effect does not seem to play a key role here. Similarly, maladaptive perfectionism). Perfectionistic concerns lead to characteristic changes in the areas of cognitive and emotional functioning (The mediators analyzed, however, explained to a large extent the negative impact of perfectionistic concerns on identity. This observation is in line with the perfectionism cognition theory and supports using this approach for studying the link between perfectionism and identity development in adulthood. Perfectionistic concerns are the dark side of perfectionism and are not prominent in every perfectionist . Settingctioning . Perfectctioning . The obtThis study was also the first to analyze the relationship between perfectionism and identity processes in the educational domain. The results suggest that these relationships are similar to those of other identity domains such as the future plans and parental domains studied earlier . This fiThe relationships between perfectionism, cognitive and emotional functioning, and identity formation described in the present article also have clinical value, especially for clinical psychology and psychotherapy. Perfectionism is not a disorder but it is a transdiagnostic process involved in occurrence and maintenance of many mental health problems such as anorexia, bulimia, depression, bipolar disorder, anxiety disorders, and personality disorders . As receAlthough the present study provided new knowledge, its limitations must also be considered. First, the study mainly included women. Although there were few differences between them and men, and gender was controlled in structural equation models, caution should be exercised in generalizing the results. Second, the study was cross-sectional and requires verification in longitudinal studies. The results of this cross-sectional study do not exclude that other models can also be true. Hence, the observed relationships, even if theoretically justified, should not be treated as a definitive proof that the relations are exactly as shown – they should only be treated as plausible and verified in future longitudinal studies. Third, the mediators chosen were quite homogeneous and it is worth considering more diverse variables in subsequent studies. This could be why mediation effects were less visible for perfectionistic strivings. It is worth conducting further analyses with another set of mediators.Perfectionistic strivings and perfectionistic concerns seem to have different effects on identity development. The obtained results indicate that the positive impact of perfectionistic strivings is largely direct, while the negative impact of perfectionistic concerns seems to be predominantly mediated by cognitive and emotional difficulties resulting from perfectionism. High indecisiveness seems to be the important factor responsible for problems with identity formation among perfectionists, which disturbs decision-making processes.The datasets generated and/or analyzed in this study are available from the corresponding author.The studies involving human participants were reviewed and approved by the Departmental Ethics Committee, University of Social Sciences and Humanities, Poznañ, Poland. The patients and participants provided their written informed consent to participate in this study.The author confirms being the sole contributor of this work and has approved it for publication.The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Pityogenes chalcographus , focusing on two Apennine  and two Central European (Austrian) locations to assess the influence of the Apennines in the evolutionary history of the beetle, particularly during the Pleistocene. We analysed a part of the mitochondrial COI gene and a set of 5470 informative genome-wide markers to understand its biogeography. We found 75 distinct mitochondrial haplotypes, which are structured in three main clades. In general, the Apennine locations harbour a higher number of mitochondrial clades than Central European sites, with one specific clade exclusively detected in the Apennines. Analysis of our genome-wide, multi-locus dataset reveals a clustering of P. chalcographus by geography, with Italian individuals clearly separated from Austrian samples. Our data highlight the significance of the Apennines for the genetic diversity of P. chalcographus and support the hypothesis that this area was an important refugium during unfavourable conditions in the Pleistocene. We discuss additional life-history traits and processes that shaped the evolution of this widespread beetle.The Apennine Mountains in Italy are an important biogeographical region and of particular interest in phylogeographical research, because they have been a refugium during Pleistocene glaciation events for numerous European species. We performed a genetic study on the Eurasian bark beetle  The Apennine Peninsula is an interesting biogeographical region and a significant source of diversity for numerous European animal and plant species . In partBark beetles (Coleoptera: Curculionidae: Scolytinae) are a diverse and species-rich insect group  (Coleoptera: Curculionidae) is a widespread bark beetle in Eurasia. It infests several conifer species, with Norway spruce, Picea abies [L.] Karst., as preferred host plant, reflected by geographical range overlaps of insect and host , with clade PcIII being highly diverse, reflected by four sub-clades (PcIIIa–PcIIId)  and Italy/Pavullo (ITPA)] and two Central European [i.e. Austria/Prinzersdorf (ATPR) and Austria/Rothwald (ATRO)] locations  were analysed  and ~50 ng template DNA. The PCR conditions were 94 °C for 3 min, followed by 33 cycles of 94 °C for 30 s, 48 °C for 60 s and 68 °C for 90 s, followed by a final extension step at 68 °C for 10 min.In total, 190 individuals  and sequenced by a commercial provider . Sequences were edited in  v.7.0.5  and aligCOI data were performed in MEGA6  and from one Austrian site  were studied   . In brieStacks v.1.35 by applying ustacks  . Thirty-four haplotypes were found only once. By applying an ML approach, the haplotypes were found to be structured in six clades/subclades [Analysing an 869 bp fragment of the mitochondrial The distribution of mitochondrial clades shows geographical differences . IndividIn contrast, haplotypes of PcI and PcIIIa were rarely detected in both Apennine locations  with differences in their spatial distribution across locations. Furthermore, it is noteworthy that a certain clade, PcIIIc, is private for the Apennines, supporting the hypothesis that this mountain range served as a glacial refugium. Analysis of a set of genome-wide SNPs revealed a distinct genetic structure across geography, with Apennine P. chalcographus clearly separated from Central European individuals. Taken together, our results support the hypothesis that this bark beetle survived Pleistocene ice ages in the Apennine Mountains, followed by postglacial range expansion, for example, to Central Europe.We performed a comparative population genetic study on the bark beetle COI gene assessed the genetic structure of P. chalcographus  were found at lower frequencies. The results from ATRO resemble previous findings . This is underlined by the presence of various mitochondrial haplotypes per population and overlaps of individuals among locations in the DAPC analysis. This pattern was also found in other bark beetle species, such as the European spruce bark beetle Ips typographus   that this mountain range was a refugium during glacial periods. Moreover, P. chalcographus from Italy and Austria clearly clusters by geography, with overlaps of individuals among geographically close locations. Together with the presence of multiple mitochondrial clades per site, this suggests that beetles of different origins contributed to the genetic structure we observe today.In conclusion, we showed the importance of the Apennine Mountains for the genetic structure of European Additional Supporting Information may be found in the online version of this article at the publisher's web-site:Table S2SI1, Table S1, Table S2, Table S3


Forest trees can occupy extensive geography and environmentally highly variable areas which result in high genetic variability in the direction of pressure from natural selection. At the same time, the majority of conifer species are wind-pollinated from both short and long distances, resulting in wide-spread gene flow, which can lead to maladaptation to local conditions. Quantitative analyses of provenance/progeny tests correct for genetic differences between populations to ensure unbiased genetic parameters are obtained. Commonly, the provenance effect is fitted as a fixed term or can be implemented as a contemporary group in the pedigree.The use of a provenance effect, either as a fixed term or as the same contemporary groups in both maternal and paternal sides of the pedigree, resulted in fairly similar precision of genetic parameters in our case. However, when we developed a phantom contemporary group for the paternal side of the pedigree that considered a different genetic quality of pollen compared with the maternal contribution from trees in the local environment, the model fit and accuracy of breeding values increased.Consideration of the mating dynamics and the vector of gene flow are important factors in modelling contemporary genetic groups, particularly when implementing pedigrees within a mixed model framework to obtain unbiased estimates of genetic parameters. This approach is especially important in traits involved in local adaptation. Forest tree species usually occupy large geographical areas and are exposed to a wide range of environmental conditions. These large geographical ranges predetermine large genetic changes along the environmental gradients, such as latitude or altitude, through natural selection. The discovery of factors driving natural selection is essential for understanding a species’ adaptability and for the development of population management strategies suitable for changing climate conditions . Common Forest tree breeding populations are mostly in the initial stage of domestication, and thus the history of evolutionary processes involved in local adaptation such as migration, genetic drift, mutations and selection greatly affect the results of any initial genetic evaluations. The geographical differences in these processes should be included in these evaluations through the inclusion of a provenance effect, fitted either as a fixed or random effect . Ugarte Pseudotsuga menziesii (Mirb.) Franco) is divided into two varieties: coastal Douglas-fir (Pseudotsuga menziesii var. menziesii) and interior Douglas-fir (Pseudotsuga menziesii var. glauca) [ST∼ 0.24) in Douglas-fir compared with other conifer species [Douglas-fir ( glauca) . A previ species , and 51% species . Another species . Earlier species  investigThe aim of our study was to investigate the fitting of the provenance effect either as a fixed effect or as a contemporary group in the pedigree within a mixed model framework to reflect the best model (data) fit. In addition, the modelling of contemporary groups in the pedigree was included to reflect differences in the genetic composition of maternal and paternal contributions in species with long-distance pollen flow.ST produced by ABLUP-R model  to 0.25 (DBH1) at Gowan Hill and from 0.00 (VEL1) to 0.27 (DBH1) at Kaingaroa (Table ST). However, the level of heritability remained similar to other scenarios and reached values from 0.11 (BR2) to 0.46 (VEL1) at Gowan Hill and from 0.06 (MAL1 and AC2) to 0.74 (VEL1) at Kaingaroa  or random effect (ABLUP-R). Both had the poorest model fit in terms of Akaike’s Information Criterion (AIC). ABLUP-R mostly resulted in a better model fit compared to ABLUP-F with the exception of traits that showed statistically significant Q l Tables  and 2. Ll Tables  and 3, Al Tables . SimilarST (DBH and NR). The accuracy of breeding values for these traits was lowest in the ABLUP-F model, where values ranged from 0.32 to 0.55. Similar accuracy was reached in ABLUP-CG2, with values ranging from 0.17 to 0.58. When the ABLUP-CG1 model was implemented, the accuracy of breeding values increased, and values ranged from 0.41 to 0.71. For example, the accuracy of breeding values for DBH1 at Gowan Hill increased from 0.53 (ABLUP-GC2) to 0.68 (ABLUP-GC1). Similarly, the accuracy of breeding values for NR2 at Kaingaroa increased from 0.17 (ABLUP-GC2) to 0.41 (ABLUP-GC1)  to 0.65 (STR2) at Gowan Hill and from 0.14 (VEL1) to 0.56 (DBH1) at Kaingaroa (Tables  to 0.65 eumannii . The neeA bivariate mixed linear model was implemented for the estimation of pair-wise genetic correlations using ABLUP-F (the default model) and ABLUP-CG1 . Both models resulted in similar genetic correlations with slightly lower estimates in the ABLUP-CG1 model. The results show a negative genetic correlation of DBH1 to all other tested traits using both models, with the exception of positive genetic correlations to DBH2 and NR2 at Kaingaroa. Both STR1 and STR2 traits showed strong positive genetic correlations to other stem form traits such as MAL1, MAL2, and BR2, ranging from 0.34 to 0.93 at Gowan Hill and from -0.09 to 0.97 at Kaingaroa. BR2 is the only trait that showed an opposite pattern between sites. While strong positive genetic correlations between BR2 and form traits such as STR1, MAL1 and STR2, ranging from 0.06 to 0.50, were observed at Gowan Hill, only moderate correlations ranging from -0.21 to 0.58, were observed at Kaingaroa. VEL1 did not show any statistically significant genetic correlations to any other traits, probably due to low sample size . The traits measured at both ages  showed strong age x age correlations, ranging from 0.86 to 0.96 at Gowan Hill and from 0.23 to 0.97 at Kaingaroa, indicating the stability of these traits’ expression levels across the investigated developmental stages  and foliar disease resistance (to SNC) measured by needle retention (NR2). Similar levels of between-population differentiation were found for other potentially adaptive traits in conifers such as bud set, bud flush and cold injury [ST values ranging between 0.006 and 0.071 [ST) indicates a high level of local natural selection and thus adaptive potential in traits related to productivity [∘ N at Gowan Hill and around 40∘ N at Kaingaroa  can be attributed to the reduced needle retention of the southern provenances . However, it is worth to mention that the resulting effect of population structure modelling depends on the extent of genetic variation included in the tested sample. Ideally, it should include a sample representing the whole natural distribution of the species. In our case, the sample represented populations from only part of the natural distribution .Correlation analysis discovered strong positive genetic correlations between NR2 and DBH at Kaingaroa. This relationship was more pronounced at later age, which indicates that reduced productivity depends on the first occurrence and frequency of foliar diseases. The correlations were mostly similar between implemented methods. However, some correlation estimates were stronger at Kaingaroa when contemporary groups were implemented in the pedigree compared with a model using provenance as a fixed term. Nevertheless, the Mantel test found high agreement between correlation matrices from tested models, reaching 0.99 in Gowan Hill and 0.97 in Kaingaroa. Appropriate modelling of population structure is critical to obtain reliable estimates of genetic correlations which can be implemented in evolutionary response to selection . AdditioIn contrast to the testing of provenance effect as a fixed term in mixed models, the implementation of contemporary groups in the pedigree allows greater flexibility in the modelling of differences in evolutionary forces, such as migration and natural selection between seed and pollen. This is important, especially in wind-pollinated species showing long-distance gene flow across heterogeneous environments, which could potentially cause maladaptation to local environmental conditions. Our study found a positive impact on model fit and accuracy of breeding values from biologically relevant modelling of population structure through contemporary groups implemented in the pedigree. Additionally, the proposed model resulted in changes in genetic correlations between the investigated traits. Such changes affect inference, not only the evolutionary response to selection, but also organismal modularity and phenotypic integration.The appropriate modelling of population structure in genetic evaluations is critical for unbiased estimates of genetic parameters. Ignorance or inappropriate modelling of population structure can produce an inferior fit of the models and lower accuracy of genetic parameters. Our study found a positive impact on model fit and accuracy of breeding values from biologically sensible modelling of population structure through contemporary groups implemented in the pedigree. The appropriate modelling of population structure was found especially critical for traits involved in local adaptation. This approach is suitable especially for wind-pollinated species with extensive long-distance pollen flow. Additionally, the proposed model resulted in changes in genetic correlations between the investigated traits. Such changes can affect inference, not only about the evolutionary response to selection but about organismal modularity and phenotypic integration.∘ 17’ S, and Gowan Hill, latitude 45∘ 52’ S) in 1996 were collected from populations in two US regions , ranging in latitude from 36∘ to 48∘ N along the western coast of the USA. Each experiment includes 30 replications of 7 sets. Each set contains 34 open-pollinated families and 2 controls. The provenances were represented equally within each of the set. A detailed description of the material is provided in a previous study [y is the vector of measurements, β is the vector of fixed effects such as intercept and control, g is the vector of random individual tree additive genetic effects following var(g) ∼N ∼N is the vector of random set nested within replication effects following var(r(s)) ∼N ∼N used as a fixed term (ABLUP-F), and considered as the default model; 2) implemented as contemporary genetic groups directly in the pedigree and modeling paternal contribution coming from an independent genetic group (phantom group) common across all provenances (ABLUP-CG1); 3) implemented as contemporary genetic groups directly in the pedigree, modeling both maternal and paternal origin from the same genetic group (ABLUP-CG2) [ST) (ABLUP-R) [Y is the matrix of measurements, g is the random vector of individual tree additive genetic effects following var(g) ∼N, where G1 is the additive genetic variance-covariance structure following G1= A, where st and 2nd trait, st and 2nd trait, and r is the random vector of replication effects following var(r) ∼N, where G2 is the replication variance-covariance structure following G2= I, where st and 2nd trait, r(s) is the random vector of the set nested within replication effects following var(r(s)) ∼N, where G3 is the set nested within replication variance-covariance structure following G3= I, where st and 2nd trait, e is the random vector of residual effects following var(e) ∼N, where R is the residual variance-covariance structure following R=I, where st and 2nd trait, st and 2nd trait. The narrow sense heritabilities for traits following normal distribution were estimated as follows: Coastal Douglas-fir was introduced in New Zealand during the 1950s through the establishment of a provenance test covering genetic material from Washington, Oregon, and limited representation from California . The resus study . Tree dius study . Variancp matrix  and \docABLUP-R) . Geneticθ is the over/under dispersion coefficient and π is 3.14159.where The genetic divergence in quantitative traits was estimated as follows: th and ith trait, and th and jth trait. The standard errors for variance components and genetic parameters were estimated by using Taylor series approximation. Agreement between the correlation matrices obtained from the investigated model was tested through a Mantel test by using the ’MantelCor’ function implemented in the ’evolqg’ R package [where  package . Modular package  by using package . Breedinvariance , estimatAdditional file 1 MS Excel workbook containing all data used in the analyses