Alcohol abuse is among the top causes of preventable death, generating considerable financial, health, and societal burdens. Paradoxically, alcohol... HSF-1 played in determining a stimulatory phenotype of Caenorhabditis elegans in response to physiologically relevant concentrations of ethanol . Using genetic techniques, we demonstrate that either RNA interference of hsf-1 or use of an hsf-1(sy441) mutant lacked the enhancement of locomotion in response to acute ethanol exposure evident in wild-type animals. We identify that the requirement for HSF-1 in this phenotype was IL2 neuron-specific and required the downstream expression of the α-crystallin ortholog HSP-16.48. Using a combination of pharmacology, optogenetics, and phenotypic analyses we determine that ethanol activates a Gαs-cAMP-protein kinase A signaling pathway in IL2 neurons to stimulate nematode locomotion. We further implicate the phosphorylation of a specific serine residue (Ser322) on the synaptic protein UNC-18 as an end point for the Gαs-dependent signaling pathway. These findings establish and characterize a distinct neurosensory cell signaling pathway that determines the stimulatory action of ethanol and identifies HSP-16.48 and HSF-1 as novel regulators of this pathway.Alcohol is a potent pharmacological agent when consumed acutely at sufficient quantities and repeated overuse can lead to addiction and deleterious effects on health. Alcohol is thought to modulate neuronal function through low-affinity interactions with proteins, in particular with membrane channels and receptors. Paradoxically, alcohol acts as both a stimulant and a sedative. The exact molecular mechanisms for the acute effects of ethanol on neurons, as either a stimulant or a sedative, however remain unclear. We investigated the role that the heat shock transcription factor  Alcohol is one of the most prevalent addictive substances and its overuse produces a severe burden on society . Acute eDrosophila, studies of acute ethanol intoxication have implicated a large number of proteins and signaling pathways  whose absolute values would be physiologically consistent with blood alcohol limits for impaired driving  or loss-of-function mutations of hsf-1 increase stress sensitivity, but also accelerate ageing  signaling pathway within the IL2 sensory neurons and identifies the exocytotic protein UNC-18 as a downstream effector for PKA. Although individual components of the Gαs pathway have been linked previously to the neuronal effects of ethanol, this study uniquely characterizes the entire signaling pathway in ethanol-dependent stimulation.Heat shock activates a transcriptional response to toxic insults whereby protective cellular chaperone (heat shock protein) expression is increased under the control of the heat shock transcription factor (HSF1) . The HSFC. elegans were cultured under standard conditions at 20° on Nematode Growth Media (NGM) agar plates with OP50Escherichia coli as a food source as previously described (N2 (wild-type), PS3551hsf-1(sy441), KG524gsa-1(ce94), KG421gsa-1(ce81), MT363goa-1(n363), NM1380egl-30(js126), KG1180lite-1(ce314), and NL2099rrf-3(pk1426). To investigate effects of single-copy transgenic rescue of hsf-1(sy441) mutants, we analyzed the OG532 (hsf-1(sy441);drSi13[hsf-1p::hsf-1::GFP::Cbr-unc-119(+)]unc-54 3′UTR + ) and OG580 (hsf-1(sy441);drSi28[hsf-1p::hsf-1(R145A)::GFP::Cbr-unc-119(+)]unc-54 3′UTR + ) strains (hsf-1(sy441) mutant. Basal locomotion rates for each strain can be found in Supplemental Material, Table S1 in File S1. Transgenic animals were derived by germline injection as previously described ;ulvEx[Phsf-1::hsf-1], hsf-1(sy441);ulvEx[Prab-3::hsf-1], hsf-1(sy441);ulvEx[Pmyo-3::hsf-1], hsf-1(sy441);ulvEx[Pglr-1::hsf-1], hsf-1(sy441);ulvEx[Punc-17::hsf-1], hsf-1(sy441);ulvEx[Posm-6::hsf-1], hsf-1(sy441);ulvEx[Pgcy-8::hsf-1], hsf-1(sy441);ulvEx[Pklp-6::hsf-1], hsf-1(sy441);ulvEx[Prab-3::hsp-16.48], hsf-1(sy441);ulvEx[Prab-3::hsp-16.48 Δ38-44], and hsf-1(sy441);ulvEx[Pklp-6::hsp-16.48]. Transgenic constructs in Bristol N2 were coexpressed with either a sur-5P::GFP or a rab-3P::GFP marker. To indicate appropriate cellular expression for additional cell–tissue-specific promoters, each of these transgenics used a GFP coexpression marker under the control of the same promoter. IL2 neurons were visualized with the promoter::GFP reporter hsf-1(sy441);ulvEx. To examine cell-specific RNAi, Bristol N2 worms were injected with the plasmid klp-6P::kin-1::klp-6P, which drove cell-specific expression of kin-1  in both the forward and reverse direction  strain. RNAi was induced by feeding  or cDNA (hsf-1), cloned into pDONR201 and recombined into DEST vectors to create tissue-specific expression vectors, as previously described  as per the manufacturer’s instructions. The unc-18 S322A expression vector was created using the Gene Tailor mutagenesis kit  from a vector carrying the unc-18 cDNA under the control of the unc-18 genomic flanking regions  . For glutathione-S-transferase (GST) fusion protein production, unc-18 was subcloned into pGEX-6p-1 as previously described  in place of Pmec-7. These vectors were converted into Gateway DEST vectors using a conversion cassette (Life Technologies). rab-3P , myo-3P , and hsf-1P are previously described . The klp-6P::kin-1 PCR fragment was then amplified from this construct and again subcloned into the same Pklp-6 construct as before, but in reverse orientation. Correct construction was confirmed by PCR and sequencing. Primers used were as follows:The kin-1 RNAi forward: 5ʹ-CTATCGATTCGCGGCCATCACAAGTTCGAATCGGA-3ʹ.kin-1 RNAi reverse (step 1): 5ʹ-CTTGTGGGCTTTTGTATAGTTCGTCCGGATAAC-3ʹ.kin-1 RNAi reverse (step 2): 5ʹ-CTATCGATTCGCGGCCATCACAAGTTGGATAACTAC-3ʹ.in vitro biochemistry, recombinant proteins  were produced as described previously  in a 50 μl final reaction volume of 2-(N-morpholino)ethanesulfonic acid (MES) buffer . Reactions were incubated at 30° for 3 hr before termination. To determine phosphorylation, 20 μl of the kinase reaction was separated by SDS-PAGE, stained with Coomassie Blue dye, destained overnight in a destainer , air-dried in Hoeffer Easy Breeze plastic frames (Thermo Fisher Scientific), exposed to a phosphor screen for 2–4 hr, and scanned by a PhosphorImager 425 (Molecular Dynamics). For in vitro phosphorylation site determination, phosphorylated samples were separated on NuPAGE 4–12% Bis-Tris precast gels (Invitrogen) and stained with Coomassie Blue dye before excision of protein bands. Gel plugs were destained in 50% acetonitrile (v/v)/50 mM ammonium bicarbonate and dried before incubation in trypsin (5 ng/μl in 50 mM ammonium bicarbonate) for 16 hr at 37°. Peptides were then extracted by sonication of gel plugs in 60% (v/v) acetonitrile/1% (v/v) trifluoroacetic acid. Extracts were thoroughly dried and ZipTipped  before electrospray ionization mass spectrometry (MS). Residual peptides were resuspended in 50% (v/v) acetonitrile/0.05% trifluoroacetic acid, and 5 μl of suspension was delivered into a QStar Pulsar I hybrid quadrupole time-of-flight MS (AB Sciex) by automated in-line liquid chromatography . A gradient from 5 to 48% acetonitrile/0.05% trifluoroacetic acid (v/v) in 60 min was applied at a 300 nl/min flow rate and survey scans of 1 sec were acquired for m/z 400–2000. The most intense ions were selected for tandem MS with 2 sec accumulation times and a dynamic exclusion of 30 sec. Identification and analysis was performed using MASCOT software (Matrix Science).For klp-6P in pPD117.01 (detailed above) via Gibson Cloning techniques (New England Biolabs). The optogenetic vectors were then transformed by germline injection into C. elegans as described above. The vectors were expressed in the lite-1(ce314) background to prevent any potential photophobic responses . Thrashing assays were performed under the dim red light in Dent’s solution , in the presence or absence of 17 mM ethanol, using a Leica MZ10F-stereomicroscope  equipped with a pE-300 light-emitting diode (LED) fluorescence light source . To activate opsin, worms were illuminated with a single flash of a 100% power green LED through the ET GFP filter set for 5 sec. For hRh1, opsin activation occurred as soon as they were placed in the Dent’s solution and thrashing was quantified after 10 min acclimation (as below). For JellyOp, worms were illuminated following the 10 min acclimation in Dent’s solution just prior to thrashing quantification, as the JellyOp activation is more transient  and a negative control (distilled water) were pipetted on opposite sides of the plate. The number of worms on either side of the plate was calculated following 90 min. The chemotaxis index (C.I.) was calculated as C.I. = (# worms at attractant − # worms at control)/total number of worms. For worm avoidance assays, a 0.9-cm ring of a substance was made by a stamping procedure on unseeded NGM plates. Immediately after stamping, 30 worms were placed within the center of the ring, completed within 2 min. Following 10 min exposure, the number of worms that had crossed the ring was counted. In preliminary experiments, 0.9 cm was found to be sufficient to permit most worms to cross a neutral substance (distilled water) within 10 min. All data are expressed as mean ± SE. As indicated, significance was tested by Student’s t-test, Mann–Whitney U-test, or ANOVA with Tukey post hoc comparisons where appropriate.Phenotypic analysis was performed in a temperature-controlled room on young adult hermaphrodites from sparsely-populated plates grown at 20°. Unless otherwise indicated, experiments were conducted at an ambient temperature of 20°. Here, locomotion rate was measured as thrashing  allele is a viable loss-of-function point mutation in the hsf-1 gene that acts as an inhibitor of HSF-1 transcriptional activity  mutation would also hypersensitize worms to the effects of low concentrations of ethanol. Surprisingly, we found that the stimulatory effect of 17 mM external ethanol was completely absent in worms containing the hsf-1(sy441) mutation (hsf-1(sy441) mutant is well established to have a temperature-sensitive phenotype and we verified that the low-dose ethanol phenotype was not affected by the ambient temperature  in the hypersensitivity to 400 mM external ethanol is dependent upon pan-neuronal hsf-1 expression (hsf-1(sy441) mutant was also pan-neuronal in nature by tissue-specific transgenic rescue. To allow for a direct comparison of the stimulatory effects of ethanol independent of basal locomotor rates, the data are presented as thrashing rate normalized to untreated worms of the same strain as done in previous studies  under its own promoter (hsf-1P::hsf-1) or specifically under the control of a pan-neuronal promoter (rab-3P::hsf-1) completely rescued the stimulatory ethanol phenotype (hsf-1(sy441) using a body wall muscle promoter (myo-3P::hsf-1) was insufficient to rescue. As a complementary approach to investigate hsf-1 function in the ethanol phenotype, we cloned and overexpressed hsb-1 in Bristol N2. hsb-1 is a negative regulator for hsf-1 transcriptional function and its overexpression in C. elegans results in similar phenotypes to loss-of-function of hsf-1  also resulted in a loss of ethanol stimulation of locomotion similar to that seen in the hsf-1(sy441) mutant (hsf-1 function.henotype . However) mutant . From thrab-3 promoter drives expression throughout the nervous system, we next determined whether the stimulatory ethanol phenotype could be localized more precisely in the nervous system. Intriguingly, the 17-mM ethanol stimulatory phenotype of hsf-1(sy441) worms could be reestablished by transgenic expression of wild-type hsf-1 specifically in cholinergic neurons (unc-17P::hsf-1) or in ciliated sensory neurons (osm-6P::hsf-1), but not in interneurons (glr-1P::hsf-1) or the AFD thermosensory neurons (gcy-8P::hsf-1)  could be reversed by transgenic expression of wild-type hsf-1 specifically in the IL2 neurons. For this, we cloned the promoter region of the klp-6 gene, which in hermaphrodites is expressed specifically in the IL2 neurons  mutant (hsf-1 in the IL2 neurons (klp-6P::hsf-1) alone could restore the stimulatory ethanol phenotype of the hsf-1(sy441) mutant to a level indistinguishable from wild-type worms (IL2-specific overexpression of hsb-1 (klp-6P::hsb-1), the negative regulator for hsf-1, was able to block the ethanol-induced stimulation in Bristol N2 (As the ::hsf-1) . The loc-1)  mutant , althougpe worms . The comistol N2 .hsf-1(sy441) worms have a slightly lower basal locomotor rate (File S1). For example, IL2 neuron overexpression of hsb-1 in Bristol N2 does not reduce basal locomotion rate at all, but does block the low-ethanol phenotype. Alternatively, overexpression of wild-type hsf-1 in IL2 neurons in the hsf-1(sy441) mutant background does not rescue the locomotor defect of the mutant, but did restore the low-ethanol phenotype. Notwithstanding this lack of correlation, we were interested in determining whether the reduced locomotor rate in the hsf-1(sy441) mutant was a consequence of the point mutation. The hsf-1(sy441) strain was originally isolated in a genetic screen of suppressors of heat shock-induced expression, where it was both backcrossed and outcrossed (File S1) and elsewhere  . The incomplete rescue of the locomotion defect was reminiscent of a reported incomplete rescue of the hsf-1(sy441) temperature-sensitivity  to a level similar to that seen with transgenic overexpression. In contrast, the OG580 strain, a single-copy rescue of hsf-1(sy441) with a DNA-binding defective mutant hsf-1 (File S1) and did not rescue the ethanol phenotype . These data indicate a potentially complex role for hsf-1 in basal locomotor rate, which is perhaps unsurprising given the broad cellular functions of the HSF-1 transcription factor and its downstream transcriptional targets. Critically, however, our results show that the basal locomotor rate is unrelated to the ethanol stimulatory effect and is instead a consequence of the hsf-1(sy441) mutation.tor rate ; however1(sy441) . The OG5sitivity . Reassurnt hsf-1 , impaireHSF-1 and its effect on sensitivity to 400 mM external ethanol indicated that the main effector for HSF-1 was the small heat shock protein HSP-16.48  mutants. Finally, overexpression of hsp-16.48 greatly reduced wild-type worm sensitivity to high external ethanol in a manner dependent upon an intact seven amino acid region of the N-terminus (amino acids 38–44)  or in IL2 neurons specifically (klp-6P::hsp-16.48) was sufficient to restore completely the stimulatory ethanol phenotype in the hsf-1(sy441) mutant (hsp-16.48 in Bristol N2 wild-types (rab-3P::hsp-16.48) increased the effect of 17 mM external ethanol, whereas the N-terminal truncation mutant (rab-3P::hsp-16.48 Δ38-44) appeared to act as neomorphic or as dominant-negative (hsf-1(sy441) background did not result in an enhancement of the ethanol-dependent reduction in locomotion in comparison to hsf-1(sy441) alone  mutant . Finallynegative . However1) alone . TherefoHSF-1/HSP-16.48 was acting in a chemosensory neuron to increase locomotion, we were interested to determine whether this increase in motility was reflective of either positive or negative chemotaxis. Indeed, the performed thrashing assays immersed the animals directly into ethanol where it would be impossible to determine any directionality to movement. We tested for this possibility by a performing a chemotaxis assay on wild-type animals toward or away from ethanol. Ethanol has been previously reported to have mild to negative effects on chemotaxis only at very high concentrations  as has been previously described . In contrast, worms were averse to octanol at concentrations as low as 1%.As IL2 chemosensory neurons to stimulate nematode motility through a G-protein-coupled receptor (GPCR)-dependent signaling mechanism. Physiological effects of ethanol are known to be modulated by various GPCRs, for example the GABAB or G-protein-coupled corticotropin-releasing factor (CRH) 1 receptors  and Gαq (egl-30) mutants, but was absent specifically for mutants of Gαs, gsa-1(ce81) and gsa-1(ce94)  .αs is a G-protein that, upon activation, stimulates adenylyl cyclase to synthesize the cAMP signaling molecule from ATP  mutants, but was completely restored in both the full (hsf-1P::hsf-1) or IL2 neuron-specific transgenic rescues (klp-6P::hsf-1)  or in IL2 neurons specifically (klp-6P::hsb-1) in Bristol N2 worms. As seen with ethanol, the effect of forskolin was restored in the OG532 single-copy rescue of hsf-1(sy441), but not in the OG580 DNA-binding defective rescue . The forskolin effect was also blocked in the Gαs gain-of-function mutants gsa-1(ce81) and gsa-1(ce94) (rab-3P::hsp-16.48) or IL2-specific (klp-6P::hsp-16.48) overexpression of hsp-16.48 alone could completely rescue the forskolin phenotype of the hsf-1(sy441) mutation (hsp-16.48 in Bristol N2 controls (rab-3P::hsp-16.48) enhanced the effect of forskolin, whereas the N-terminal truncation mutant (rab-3P::hsp-16.48 Δ38-44) appeared to act negatively (hsf-1(sy441) background  mutant.Next, as previously shown for the stimulatory effects of ethanol, we verified that stimulation by forskolin was also dependent upon ::hsf-1) . Complem-1(ce94) . Furthermutation . Also idgatively . The truckground . Taken tαs in IL2 neurons by 17 mM external ethanol; however, our evidence was obtained by pharmacological activation of the entire nematode. We next wanted to activate Gαs in the IL2 neurons directly. To accomplish this, we genetically expressed a photoactivatable Gαs-linked jellyfish opsin, JellyOp  . The created transgenic worms appeared qualitatively normal and had only a small quantitative reduction in basal locomotion rate (Table S1 in File S1). While we cannot quantify definitive cell specificity of the RNAi, if the PKA knockdown had spread greatly to other cells it would be expected to be lethal . These data support the interpretation that the effects of ethanol to stimulate C. elegans locomotion are regulated in IL2 neurons by a Gαs signaling pathway.The data thus far pointed to an activation of Gexposure . In cont pathway . Next, wn (hRh1) , which a ethanol . As an aαs-cAMP-PKA signaling pathway. PKA is a serine/threonine kinase that would be expected to phosphorylate many downstream targets in response to activation. Sec1-Munc18 (SM) proteins are essential components of the exocytotic machinery thought to function primarily through interactions with soluble N-ethylmaleimide-sensitive factor receptor proteins (C. elegans SM protein UNC-18 (D214N) was also able to block the low-ethanol phenotype , which act in a dominant fashion to endogenous unc-18  or in IL2 neurons specifically (klp-6P::unc-18 S322A) was able to block completely the stimulatory effects on motility of either ethanol or forskolin  whose absolute values are physiologically consistent with blood alcohol limits for impaired driving. Through a combination of genetics, pharmacology, and optogenetic manipulation, we have uniquely delineated the entire cell signaling pathway in response to ethanol specifically in IL2 chemosensory neurons  and not sensory neurons such as the IL2 neurons. Our data use combinations of optogenetic, genetic, and pharmacological manipulation to trace the involvement of the entire Gαs -cAMP-PKA signaling pathway in the IL2 neurons in ethanol-dependent stimulation. Additionally, we extend this pathway to the downstream phosphorylation of the exocytotic protein UNC-18 and implicate HSP-16.48 as a novel regulatory protein.Our data support the interpretation that a Gin vitro. Phosphorylation of Munc18 has been demonstrated in vivo, primarily by Protein Kinase C  mutant phenotype (hsp-16.48 can completely restore the stimulatory phenotype for the hsf-1(sy441) mutant. Although there is little constitutive HSP-16.48 expressed, even in response to 400 mM ethanol, our RNAi experiments show that these small quantities are sufficient to affect whole-animal behavior. Small HSPs can be directly phosphorylated by PKA (HSP-16.48 regulates the Gαs -cAMP-PKA signaling pathway. It may be that HSP-16.48 is acting simply as a chaperone to preserve either structural conformation of individual proteins, protein–protein interactions, or possibly to assist in the phosphorylation event itself. Alternatively, HSP-16.48 may directly interact with specific components of the signaling pathway independent of its chaperone ability. Nonetheless, the correct functioning of HSP-16.48 in ethanol-dependent phenotypes explicitly required a seven amino acid region of the protein’s N-terminus, a region not found in other small HSPs linked to temperature stress tolerance (Our data demonstrate that the α-crystallin ortholog C. elegans on agar (Our experiments have used thrashing as a measure of locomotion (IL2 neurons, with dendritic projections directly to the exterior of the body (C. elegans in response to ethanol at levels that would be seen in intoxicated humans. The stimulation of locomotion has been reproducibly demonstrated in C. elegans (Drosophila (C. elegans increase their movement in response to 17 mM ethanol? The ecology of the species is not fully understood; however, some evidence points to C. elegans feeding on bacteria associated with decomposing material. However, unlike longer chain alcohols, evidence for ethanol acting as a chemotactic cue signaling a potential nutrient source is not well supported. Although we were unable to reproduce the results, some data point to ethanol acting as a low-level chemorepellent (The internal concentration of ethanol in nematodes is reported to be ∼10% of external experimental levels due to poor penetration through the cuticle (HSP-16.48 and both the sedative (HSP-16.48 expression biphasically both enhances ethanol-induced stimulation and decreases ethanol-induced sedation. Importantly, the expression of the α-crystallin chaperone is upregulated in mice strains with a high alcohol intake preference (UNC-18, therefore presents novel targets for future pharmacological intervention that could be exploited to control the devastating physiological effects of alcohol.Alcohol acts paradoxically as both a depressant and as a stimulant. These stimulatory effects in humans are thought to be more rewarding than sedative effects and thus may play a more prominent role in determining addiction. The differentiator model for risk to alcoholism is associated with a trade-off between stimulant and sedative effects (www.genetics.org/lookup/suppl/doi:10.1534/genetics.117.300119/-/DC1.Supplemental material is available online at Click here for additional data file.Click here for additional data file.Click here for additional data file.Click here for additional data file.Click here for additional data file.


Salvelinus alpinus) population from Lake Geneva (Switzerland and France), which has initially been restocked with allochtonous fishes in the early eighties, followed by supportive breeding. In this context, we conducted a genetic survey to document the evolution of the genetic diversity and structure throughout the last 50 years, before and after the initiation of hatchery supplementation, using contemporary and historical samples. We show that the introduction of exotic fishes was associated with a genetic bottleneck in the 1980–1990s, a break of Hardy–Weinberg Equilibrium (HWE), a reduction in genetic diversity, an increase in genetic structure among spawning sites, and a change in their genetic composition. Together with better environmental conditions, three decades of subsequent supportive breeding using local fishes allowed to re‐establish HWE and the initial levels of genetic variation. However, current spawning sites have not fully recovered their original genetic composition and were extensively homogenized across the lake. Our study demonstrates the drastic genetic consequences of different restocking tactics in a comprehensive spatiotemporal framework and suggests that genetic alteration by nonlocal stocking may be partly reversible through supportive breeding. We recommend that conservation‐based programs consider local diversity and implement adequate protocols to limit the genetic homogenization of this Arctic charr population.Artificial stocking practices are widely used by resource managers worldwide, in order to sustain fish populations exploited by both recreational and commercial activities, but their benefits are controversial. Former practices involved exotic strains, although current programs rather consider artificial breeding of local fishes (supportive breeding). Understanding the complex genetic effects of these management strategies is an important challenge with economic and conservation implications, especially in the context of population declines. In this study, we focus on the declining Arctic charr ( Yet, the artificial propagation of exogenous wildlife can pose a severe threat on local biodiversity, leading to population declines and biological invasions  and the implementation of protocols accounting for broodstock numbers, relatedness, sex‐ratio, and life‐history traits can minimize such adverse effects  is a circumpolar stenothermal cold water salmonid. This species demonstrates a high potential for local adaptation, which can lead to genetically and ecologically divergent sympatric morphs  samples covering more than 50 years of fishing history from different parts of the lake. Our results have strong relevance for the design of future management strategies for this species.22.1n = 218, coded in blue color throughout the figures) were collected in 2007 (fish farms) and during the winter 2009–2010  when the fishes breed. Tissue samples were obtained from adipose fins  or tail tips (juveniles in fish farms), stored in 80% ethanol. One site (MF) was sampled first in December 2009 (MFa) and a second time later in February 2010 (MFb), to control that fishes are not genetically structured locally due to disruptive breeding periods among individuals. For three sites , we gathered series of historical samples  from two main time periods: before  and few years after the beginning of the stocking program in 1979 .We included a total of 378 individuals from the eight known natural spawning sites of Lake Geneva  or the Qiagen DNAeasy Blood & Tissue Extraction kit . Historical samples  were processed in a separate laboratory dedicated only to the extraction of low copy‐number DNA samples and preparation of pre‐PCR reagents. Negative controls were employed during all extraction and amplification experiments.2.2We analyzed eight microsatellite markers polymorphic in the Arctic charr , which was genotyped eight times.2.3Ho), allelic richness (Ar), and inbreeding coefficient (Fis) in Fstat  in Fstat, and used TreeFit  in Arlequin 3.5  and statistical comparisons  were performed in R  of 0.65 among spawning sites (0.16–0.95) and a total number of alleles per marker (k) of 15 (5–29). Signs of null alleles or allele dropouts were detected in only nine of 160 instances, involving both contemporary (five instances) and historical samples (four instances), and mainly affecting two loci: Sfo23  and MTS‐85 . Therefore, this might rather reflect true null alleles segregating at low frequencies, or disequilibrium resulting from drift, rather than dropout due to degraded historical DNA. Details on each locus are provided in Table Our microsatellites were highly polymorphic in the studied population, with an average heterozygosity  than before the initiation of the traditional restocking program . Contemporary sites, including the two hatcheries, were not genetically structured . These patterns are also illustrated by the PCA on allele frequency , as well as compared to original ones . Accordingly, the first axis of the populational PCA , and the tree of genetic distances mainly distinguished samples according to their time series rather than their geographical origin   and observed heterozygosity (Ho) were significantly lower in the early years of stocking  than prior to it , and nowadays  , but sites from the 1980 to 1990s show significant excesses of heterozygotes compared to HWE in three of five instances , but one hatchery (FVCH) shows a clear deficit of heterozygotes .Allelic richness  and outbreeding (negative Fis). During the period of supportive breeding (1983‐present), initial diversity levels and HWE were restored and genetic structure was suppressed.Closer inspection of the three spawning sites for which genetic data was available at several time points  confirmed the general patterns observed over the main time periods Figure . For all4Our study provides a comprehensive temporal and spatial framework to understand the evolution of genetic diversity and structure of the Arctic charr in Lake Geneva, in the context of two different stocking practices applied in turns: the traditional stocking using artificially reared exotic fishes (from Denmark) from 1979 to 1982; followed by the continuous supportive breeding of wild spawners from 1983 until now. However, this intense restocking program did not allow this population to reach self‐sustainability, the species being declining for two decades despite habitat recovery. Our results provide new insights about the controversy of these practices. Importantly, these findings are based on wild spawners, effectively contributing to the next generation.4.1Fis). This pattern likely reflects a situation where many fishes are the product of admixture between exotic and local fishes  caused significant changes in the genetic structure, nature, and diversity of the lake's population. First, the diversity within sites decreased right after the initiation of the restocking, potentially due to strong founder effects or initially low diversity of the introduced fishes. The common practice is to raise and release the offspring of few adults , yielding a disproportionate amount of siblings among released stocks and thus low effective size and genetic diversity. The present pattern supports that very few breeders contributed to the imported eggs or that their diversity was low to begin with. In addition, it is not excluded that demographic processes  may have contributed to this genetic bottleneck. Second, despite low intrinsic diversity, these early restocked sites (1980–1990s) are also the only ones with an excess of heterozygotes . Accordingly, decades of supportive breeding involving local broodstock seem to have had little impact on the genetic composition in other fishes , have been clearly demonstrated (see Fst): even if the original genetic structure was low to begin with, it is virtually inexistent nowadays. This pattern is in line with previous studies on salmonids , probably following rearing practices. This might translate into an intrinsically lower fitness of artificially bred individuals and compromise their fate in the wild.Thus, from our results, the genetic factors could be one plausible cause. First, although diversity seems back to its original level, the altered genetic composition and strong homogenization we observe across the lake might have diminished the fitness of fishes, through maladaptation and outbreeding depression following admixture (e.g., Le Cam et al., In addition to restore and/or maintain suitable spawning conditions (fresh gravel and oxygen availability at deeper layers of the lake; Mari et al., 5Our study presents a comprehensive genetic survey reporting the long‐term effects of two different stocking practices of the Arctic charr in Lake Geneva, applied in turns. Our fine spatial and temporal resolutions allowed to dissect the detrimental genetic effects of historical restocking by nonlocal fishes, in accordance with previous work. Importantly, we could further show that supportive breeding of local fishes allowed to partially restore the genetic integrity of this altered population, but that current practices could be optimized to improve the restocking actions, and thus for this population to reach self‐sustainability.None declared.http://dx.doi.org/10.5061/dryad.f776h.Data for this study are available at the Dryad Digital Repository:  Click here for additional data file.


SWA), however, there are scarce records of bottlenose dolphins differing in external morphology according to habitat preferences that resemble the coastal‐offshore pattern observed elsewhere. The main aim of this study was to analyze the genetic variability, and test for population structure between coastal (n = 127) and offshore (n = 45) bottlenose dolphins sampled in the SWA to assess whether their external morphological distinction is consistent with genetic differentiation. We used a combination of mtDNA control region sequences and microsatellite genotypes to infer population structure and levels of genetic diversity. Our results from both molecular marker types were congruent and revealed strong levels of structuring  and much lower genetic diversity in the coastal than the offshore ecotype, supporting patterns found in previous studies elsewhere. Despite the opportunity for gene flow in potential “contact zones”, we found minimal current and historical connectivity between ecotypes, suggesting they are following discrete evolutionary trajectories. Based on our molecular findings, which seem to be consistent with morphological differentiations recently described for bottlenose dolphins in our study area, we recommend recognizing the offshore bottlenose dolphin ecotype as an additional Evolutionarily Significant Unit (ESU) in the SWA. Implications of these results for the conservation of bottlenose dolphins in SWA are also discussed.Due to their worldwide distribution and occupancy of different types of environments, bottlenose dolphins display considerable morphological variation. Despite limited understanding about the taxonomic identity of such forms and connectivity among them at global scale, coastal (or inshore) and offshore (or oceanic) ecotypes have been widely recognized in several ocean regions. In the Southwest Atlantic Ocean ( Such plasticity makes the species to vary geographically in a significant number of biological traits. Despite limited understanding about the taxonomic identity of geographical forms and connectivity among populations, coastal (or inshore) and offshore (or oceanic) ecotypes have been widely recognized in several ocean regions , bottlenose dolphins occur in both coastal and offshore zones. In coastal regions, they are commonly seen in shallow waters (<20 m) within 3 km from the coast , in southern Brazil, to Bahía San Antonio (BSA), in the Patagonian Argentina (25°18–54°40′S)  to the slope  off southeast and southern Brazil (~23°S to ~34°S)  are the same used in a recent study that investigated the fine‐scale genetic structuring of these dolphins in the SWA  were preserved in 20% dimethyl sulphoxide (DMSO) saturated with sodium chloride . We used GenAlEx 6.5 .All 48 samples were subsequently used for microsatellite amplification. Samples were genotyped at 16 microsatellite loci . Individual membership coefficient (q) to each cluster is also estimated providing valuable information on the similarity between individuals based on shared ancestry. We assumed correlated allele frequencies , assuming values of K varying between 1 and 4 . As recommended by Gilbert et al. (K (∆K), was used to determine the most likely value of K over multiple runs, as implemented in STRUCTURE HARVESTER . The Evanno method was used because it reveals the highest hierarchical level of structure, which seems appropriate to test for genetic differentiation between ecotypes of bottlenose dolphins.We used STRUCTURE 2.3  and nucleotide diversities (π) , expected (HE) and observed (HO) heterozygosity, and inbreeding coefficient (FIS), and was calculated using GenoDive 2.0  per population was estimated in FSTAT 2.9.3.2  were performed to assess population structure between inferred clusters using ARLEQUIN 3.5.1.2  Nei,  using AR(π) Nei, . For mic Goudet, . All sta Goudet, . Convent and Nei  model wi and Nei  to run a and Nei  was cons33.1FIS = 0.05, p = .02). No linkage disequilibrium was found between any locus pair.Microsatellite genotypes and mtDNA sequences were identical in replicated samples , and no samples were identified as duplicates for the 48 new samples analyzed in this study. Thus, the final new dataset consisted of 25 males and 20 females for offshore samples and two males and one female for the three dolphins sampled along the coast of BSA Table . Examina3.2K = 2 when applying the Evanno method for the genetic profile of 172 dolphins, including coastal and offshore ecotypes  based on the analysis of 11 microsatellite loci confirmed the patterns of genetic structure revealed by STRUCTURE, with all offshore dolphins grouped toward one side of the ordination plot and the first and second axis explaining 54.4% and 17.5% of variation, respectively . High genetic differentiation was also observed when comparing each of the coastal ESU with the offshore ecotype, and FST was higher for offshore‐SBU than for offshore‐BSA comparisons . Results were similar for both ΦST and FST, but in general, ΦST had greater values differentiating populations. The highest levels of differentiation were found between SBU and offshore and between SBU and BSA when considering ΦST and FST, respectively ; (B) all coastal samples plus four offshore dolphins (n = 128), with two of the later grouping closely to the most common coastal haplotype; and (C) two offshore dolphins plus the three individuals resembling the offshore ecotype sampled in coastal waters of Argentina  in the SWA and estimated genetic diversity for offshore dolphins from this region. We found strong levels of structuring and contrasting levels of genetic diversity between the two bottlenose dolphin ecotypes. Results were concordant for mitochondrial and microsatellite DNA markers, supporting patterns found in previous broad‐scale studies that used similar markers (as described below). Results from the Bayesian clustering method implemented in STRUCTURE (with no a priori information) and the PCoA analysis were highly congruent, suggesting that the strong genetic differentiation is not linked to analytical artifacts potentially produced by significant inbreeding coefficients. For the coastal ecotype, a significant deviation of HWE may be due to a combination of further substructuring  as well as inbreeding in one of the populations  were higher than that reported for the offshore ecotype in a worldwide perspective  and for Mediterranean  bottlenose dolphins . In Bahía San Antonio, for example, Vermeulen and Cammareri  reportedOrcinus orca), for example, feeding strategies are believed to have played a crucial role in shaping genetic structuring in sympatric and parapatric populations , there is only one study that explicitly tested for forces driving ecotype differentiation and population structure , while the offshore ecotype preferentially inhabits deeper waters albeit some incursions to coastal areas can occur occasionally in the north limit of the distribution of the coastal ecotype. Despite opportunity for gene flow in this possible “contact zones” our results suggest negligible interbreeding between ecotypes, even in an area where dolphins of both ecotypes were observed to associate (Vermeulen & Cammareri, None declared.Pedro F. Fruet contributed substantially to the conception, acquisition of samples, analysis, interpretation and drafting the work; Eduardo R. Secchi contributed substantially to the conception, acquisition of samples of the work, drafting, and revising it critically for important intellectual content; Juliana C. Di Tullio, Fábio G. Daura‐Jorge, Paulo César Simões‐Lopes, Els Vermeulen, Paulo A. C. Flores, Rodrigo Cezar Genoves, and Paula Laporta contributed substantially to the acquisition of samples, drafting, and revising it critically for important intellectual content; Ana P.B. Costa contributed substantially to data analysis, drafting, and revising the work critically for important intellectual content; Luciano B. Beheregaray and Luciana Möller contributed substantially to the conception, data analysis, interpretation, drafting, and revising it critically for important intellectual content. Click here for additional data file. Click here for additional data file.


Pyrrhura orcesi) endemic to the Ecuadorian Andes. Specifically, we assessed the genetic divergence between three sites separated by small geographic distances but characterized by a heterogeneous habitat structure. Although geographical distances between sites are small (3–17 km), we found genetic differentiation between all sites. Even though dispersal capacity is generally high in parrots, our findings indicate that dispersal is limited even on this small geographic scale. Individual genotype assignment revealed similar genetic divergence across a valley (~ 3 km distance) compared to a continuous mountain range (~ 13 km distance). Our findings suggest that geographic barriers promote genetic divergence even on small spatial scales in this endangered endemic species. These results may have important implications for many other threatened and endemic species, particularly given the upslope shift of species predicted from climate change.Tropical montane ecosystems are biodiversity hotspots harbouring many endemics that are confined to specific habitat types within narrow altitudinal ranges. While deforestation put these ecosystems under threat, we still lack knowledge about how heterogeneous environments like the montane tropics promote population connectivity and persistence. We investigated the fine-scale genetic structure of the two largest subpopulations of the endangered El Oro parakeet ( Habitat loss and fragmentation have been identified as the major threats to species extinction . Habitatper se low mobility, like understorey birds [Mobile organisms like birds are usually expected to disperse over large distances and show corresponding low levels of genetic differentiation between neighbouring populations –12. In cey birds –23, wherIn addition to ecological specialization, landscape characteristics, like mountains, valleys or water bodies influence dispersal decisions of species and thus are reflected in their genetic population structure –27. AlloPyrrhura orcesi). The El Oro parakeet is endemic to southwest Ecuador and is considered to have undergone a severe bottleneck during the last decades [2. Because of that small range, it is important to understand whether natural and human-induced landscape characteristics influence population genetic structure in El Oro parakeets on a narrow geographic scale.In this study, we investigate the fine-scale genetic structure in the endangered El Oro parakeet . This permission allowed for the collection of blood samples. No animals were killed for this study and handling time was kept to a minimum. Field work was carried out in the protected area of the reserve Buenaventura and a privately owned area at Cerro Azul. Permission to conduct field work in these areas was granted by the Fundación Jocotoco and the land-owner of the area at Cerro Azul, respectively. Sample collection was reviewed and approved by the Ministerio de Agricultura, Ganadería, Acuacultura y Pesca, Ecuador .The El Oro parakeet is a facultative cooperative breeder usually nesting in extended family groups with one central breeding pair . The disEcuador exhibits the largest deforestation rate of South America with no more than 4% of the original forest cover remaining at the western coastal areas and the pre-montane regions . This imcensu Cesar Garzon). The regions of Buenaventura (BV) and Cerro Azul (CA) are connected by a continuous mountain range that lies within the typical elevational range of El Oro parakeets (North) and southern (BVSouth) areas of Buenaventura are divided by a valley with an elevation of 450–500 m, which is clearly lower than the current parakeet’s elevational range. Note, however, that El Oro parakeets were observed in the valley at just slightly higher elevations (~ 600 m) when they were discovered 30 years ago. Throughout the valley, a narrow, continuous forest patch connects the northern and southern slopes of BV. The valley provides the shortest dispersal pathway between BVNorth and BVSouth (approximately 3 km) and parakeets could potentially cross it in a continuous forest layer (Sampling took place at the Buenaventura reserve (2200 ha) and at Cerro Azul (~1600 ha), which is located approximately 17 km northeast of Buenaventura . In 2006arakeets . The arest layer . In contBVNorth = 126; nBVSouth = 107). Of these individuals, 52  were breeders in the study population. In CA, 16 individuals were banded and blood sampled in the years 2010 and 2011. GPS points were taken from every location where parakeets were captured. All parakeets were captured at an elevation between 800–1300 m  also reside in the area between CA and BV, poor infrastructure and rough terrain impeded capturing them. All samples were taken from the large populations at CA and BV. Parakeets were captured with mist nets or within nest boxes equipped with trap doors. Because of intensive population monitoring over a study period of four years (2009–2012), the majority of individuals of the Buenaventura population have been sampled. We banded and took blood samples of 233 individuals in Buenaventura  captured in CA was used in addition to the complete data set of n = 249 for analysing genetic divergence on the population- and the individual-level. As sample sizes among our study sites were similar for the reduced data set, this procedure also ensured that our results were not biased by sample size effects. Because results were consistent irrespective of which data set was used, most results inferred from the reduced data set are given in the supporting information section. If not stated otherwise, individuals that were captured several times were assigned to the location where they were captured last. This procedure ensured that all dispersal events observed between our study sites entered the analyses.Blood samples were stored in 96%-Ethanol at -22°C. DNA was extracted with the DNeasy Blood and Tissue Kit  following customers instructions. We used a set of 18 microsatellite markers for genotyping of individuals. Genotyping was performed with an ABI Sequencer 3130xl  using the software GeneMapper ID-X 1.1 (Applied Biosystems). For description of the polymerase chain reaction (PCR) procedure as well as detailed information about marker characteristics see . We did o), the expected heterozygosity (He) and the fixation index (FIS) with the software GenALEx 6.5 [To estimate the genetic diversity maintained within the northern and southern parts of Buenaventura as well as within Cerro Azul, we calculated the observed heterozygosity . Genetiiversity  which caa priori assumptions about the population structure. It thus gives an unbiased estimation of potential genetic sub-structuring within the study sample [6 MCMC (Markov Chain Monte Carlo) steps discarding the first 2 ∙ 105 steps. Simulations were run with and without prior information on sampling location. If sample location was used as prior, individuals were assigned to their hatching place or, if hatching place was unknown, to the place where they were captured first. The most likely number of clusters was inferred by the highest mean posterior likelihood and the highest delta K [We tested the extent of genetic sub-structuring within our study population by applying a Bayesian clustering algorithm implemented in the software STRUCTURE ver. 2.3.4 . This iny sample . The sim delta K  calculat delta K . The ave delta K  and illu delta K .5 iterations with a thinning interval of 100 iterations and a burn-in period of 200 iterations. The number of K was then inferred from the modal number of K given by these ten runs. In a second step, we made 30 runs keeping K fixed to the modal number of K to assign each individual to one of the genetic clusters. For this second step, we lowered the number of MCMC iterations to 1 ∙ 105 with a thinning interval of 100 iterations and a burn-in period of 200 iterations. From these 30 runs, we chose the five best runs according to their mean log posterior probability. The average probability of membership to a specific cluster was then calculated based on these five runs for each individual over 1000 iterations with the software CLUMPP ver. 1.1.2 [Additionally to the Structure analyses, we applied a spatially explicit model implemented in the software GENELAND ver. 4.0.5 , which ir. 1.1.2  and illur. 1.1.2 .To further test whether genetic differentiation between the study sites can be explained by geographic distance, we tested for a correlation between geographic and genetic distance separately for individuals of Buenaventura and for individuals of Buenaventura and Cerro Azul. We measured the extent of isolation by distance (IBD) by conducting a Mantel test using pairwise linear genetic distance and geographic distance as implemented in GenALEx ver. 6.5 . GeograpDispersal rates between the study populations were estimated based on genetic as well as observational data. Given that the Buenaventura population was monitored intensively during 2008–2012 with a considerable proportion of individuals of known origin, we were able to estimate dispersal rates between our study sites reliably based on our observational data. This is particularly so because individuals are sedentary within an area of 100–120 ha . Moreove7 MCMC steps, a thinning interval of 104 steps and a burn-in period of 106 steps varying the random seed number in each run. The mixing parameter for allele frequencies was set to a = 0.2 to guarantee reasonable acceptance rates and good mixing of chains. Convergence of each chain was further checked with the software Tracer ver. 1.5 [Dispersal rates based on genetic data were assessed with the software BayesAss ver. 3.0 . This sover. 1.5 .th century accompanied by the loss of potential breeding places and foraging trees led to a strong reduction of the global population of the El Oro parakeet [North and CA to one cluster (n = 142) and individuals of BVSouth to a second cluster (n = 107), for the whole BV population (n = 233) and for the whole data set (n = 249) including individuals of CA. All three available mutation models were used: infinites alleles model (IAM), the single step mutation model (SMM) and the two-phase mutation model (TPM). For TPM, default values were used with 70% single step mutations and 30% multistep mutations with a variance of σ2 = 30. Probability of heterozygosity excess was estimated with the sign test and with the Wilcoxon test based on 105 bootstrap iterations.Increasingly high deforestation rates since the beginning of industrialisation in the mid 20parakeet . Ever siparakeet , its gloparakeet ,55. Giveparakeet . Both ofparakeet . Because0 and ancestral N1 effective population size and the time T since the population size started changing. Probability estimates of parameters are assessed through MCMC simulations based on allele frequencies assuming a SMM model with mutation rate θ = 2N0μ where μ is the per locus mutation rate. Three models were run with wide priors set to a log-normal scale assuming different scenarios of population size change , we found significant genetic differentiation between these two areas . This pattern was found irrespective of model assumptions, for example correlated or uncorrelated allele frequency, and is probably due to the high relatedness and the spatially clustered structure within this data set.The Geneland analysis based on the reduced data set revealed similar results as the Structure analysis with results based on the mean likelihood estimation. All ten runs showed a modal number of K = 4 genetic clusters for the reduced data set, which also corresponds to the second peak found using the Evanno´s deltaK method with Structure . Individf origin . In contNorth and BVSouth: r = 0.19, p < 0.001, n = 233) as well as for individuals between BV and CA . In both cases, the IBD results were similar to the correlation found for individuals from BVSouth and CA  indicating that even on these small spatial scale, geographic distance may hamper genetic exchange between individuals.Birds were genetically more differentiated the more distant their origins were. This is true for individuals within Buenaventura  suggesting that the differentiation is not a result of the high relatedness within breeding groups, but may indeed be due to low dispersal rates and isolation by distance. We detected no correlation between geographic and genetic distance for breeders within subpopulations , showing that the variance in geographic distance within our sampling locations did not influence our results.A Mantel test conducted for breeders of BVNorth and BVSouth are rare. During four years, we only detected five individuals crossing sites within the Buenaventura reserve: two females dispersed from BVSouth to BVNorth and two females and one male dispersed from BVNorth to BVSouth. Taking only recruited individuals into account (n = 148), this corresponds to a dispersal rate of 3.4% in four years. Importantly, only the two females which dispersed to BVNorth bred and produced one chick each. Hence, the proportion of dispersal events actually resulting in gene flow and admixture between BVNorth and BVSouth decreases to 1.4%  during the study period of four years. These findings indicate existing but probably low rates of gene flow across a 3 km wide valley.Our observational data revealed that dispersal events between BVNorth and BVSouth. Based on the complete data set, the proportion of migrants per generation was 0.02 for both dispersal directions within Buenaventura  for the current population size and N1 = 3.68 (3.19–4.21) for the ancestral population size. This corresponds to a median current population size of approximately 750 individuals and an ancestral median population size of approximately 5000 individuals, which indicates a 7-fold decrease in population size. Time since population size started decreasing was estimated to approximately 380 years with a mode of T = 2.72 (0.22–4.94). Median mutation rate was 3 ∙ 10−4 corresponding to a mode of θ = -3.53 (-3.94 - -3.12). Large confidence intervals particularly for parameter estimates of the timing of population decline but also for parameter estimates of the current population size indicate some uncertainty in the estimation of these parameters. Yet, the analyses give strong support for a decline of the El Oro parakeet population.We obtained similar results of a population contraction using MSVAR simulations. Gelman-Rubin statistic indicated good convergence of all chains with point estimates of potential scale reduction factors < 1.1 . Modal vWe detected low but significant genetic differentiation between all three study sites. Even on a small spatial scale as within the BV reserve genetic distance was increasing with geographic distance. Together with the observation of low dispersal rates between the study sites, our findings suggest that effective dispersal and gene flow rates are extremely low given the small geographic scale considered. Interestingly, dispersal rates as well as population structure inferred from individual genotypes revealed similar genetic sub-structuring between the two study sites within the Buenaventura reserve (~3 km distance) as between the northern area of Buenaventura and Cerro Azul (~13 km distance) indicating that geographic barriers may influence fine-scale genetic structure in the El Oro parakeet.Myrmeciza exsul) [Orthonyx temminckii) [The genetic divergence and the existence of IBD between our subpopulations indicate that even small geographic distances limit dispersal and induce genetic differentiation between El Oro parakeet populations. This is surprising since parrots are usually thought to be highly mobile birds with often high levels of gene flow between distant populations ,65. Altha exsul)  and the minckii) . Thus thIn general, elevated levels of natal philopatry and low dispersal distances can be expected to induce fine-scale genetic sub-structuring in cooperatively breeding species –68. It iThe genetic population structure found between the study sites may be explained by drift effects caused by a recent bottleneck event ,69,70. GPopulation structure inferred from individual genotypes as well as the indices of genetic differentiation revealed similar genetic sub-structuring between the two study sites within the Buenaventura reserve (~3 km distance) as between the northern area of Buenaventura and Cerro Azul (~13 km distance). Accordingly, we found low migration rates within the Buenaventura reserve. This finding is even more surprising since the valley separating the northern and southern parts of Buenaventura reserve is covered by forest seemingly providing good conditions for dispersal, whereas the region between the northern area of Buenaventura and Cerro Azul is covered by forest patches only. Despite this and although only three kilometre distance separates the northern and southern mountain ranges, our observational and genetic data indicate that El Oro parakeets rarely cross the valley. The genetic divergence found between individuals inhabiting opposite sides of the valley may be explicable by the biogeographic history of the Andean region. Dispersal barriers as river valleys and mountain ridges are considered to have played a central role in the allopatric speciation events during the Andean uplift and thereby have contributed to the high species diversity observed nowadays in this region . Even naOngoing population decline over the past decades, as shown by our bottleneck analyses, could have led to the withdrawal of El Oro parakeets from marginal habitat in the lower parts of the valley. The reduction of population size can lead to a re-assortment of the breeding population followed by the abandonment of marginal habitat . The BueAlthough climatic data are scarce for this region, altered conditions due to climate change are known to shift cloud cover, and hence humidity, to higher elevations in tropical montane cloud forests –76 leadiHigh deforestation rates are thought to pose an imminent threat especially to the survival of endemic species like the El Oro parakeet. Consensus estimates suggested a population decline of El Oro parakeets from approximately 8000–10000 individuals to approximately 1000 individuals during the last three decades ,55. AlthPopulation decline is often accompanied by adverse genetic effects like reduced genetic connectivity between habitat fragments and reduced genetic diversity . In the Pionus chalcopterus) or the red-masked parakeet (Aratinga erythrogenys)) in that they are usually flying through the canopy, which probably makes them highly susceptible to habitat loss and fragmentation. The population structure analysis combined with spatial information revealed that individuals from CA and BVNorth, where forest cover is widely missing, build two separate genetic clusters. In contrast, the dispersal rates inferred from genetic data suggest that dispersal between Buenaventura and Cerro Azul is not completely disrupted. In accordance, the Structure analyses showed that individuals from Cerro Azul do not form a completely separated genetic cluster. Instead, a few individuals from the northern area of Buenaventura were assigned to the genetic cluster of Cerro Azul. These findings indicate that, even though forest cover is largely reduced in this area, dispersal is still ongoing. This may be explained by the observation that El Oro parakeets regularly cross pastures, usually by flying close to the ground and often by using single tree groups as stopover. Moreover, El Oro parakeets presumably residing in forest fragments between Cerro Azul and Buenaventura may facilitate the maintenance of gene flow between these areas.El Oro parakeets strongly differ in their dispersal behaviour from other sympatric parrot species Click here for additional data file.S2 Fig(DOCX)Click here for additional data file.S1 Table(DOCX)Click here for additional data file.S2 Table(DOCX)Click here for additional data file.S3 TableGiven are genotypes of each individual and sample location.(XLSX)Click here for additional data file.


DNA data from a systematic literature review to produce estimates of diversity for both markers across 42 cetacean species. Factors relating to demography, distribution, classification, biology, and behavior were then tested using phylogenetic methods and linear models to assess their relative influence on the genetic diversity of both marker types. The results show that while relative nuclear diversity is correlated with population size, mitochondrial diversity is not. This is particularly relevant given the widespread use of mitochondrial DNA to infer historical demography. Instead, mitochondrial diversity was mostly influenced by the range and social structure of the species. In addition to population size, habitat type (neritic vs. oceanic) had a significant correlation with relative nuclear diversity. Combined, these results show that many often‐unconsidered factors are likely influencing patterns of genetic diversity in cetaceans, with implications regarding how to interpret, and what can be inferred from, existing patterns of diversity.Understanding what factors drive patterns of genetic diversity is a central aspect of many biological questions, ranging from the inference of historical demography to assessing the evolutionary potential of a species. However, as a larger number of datasets have become available, it is becoming clear that the relationship between the characteristics of a species and its genetic diversity is more complex than previously assumed. This may be particularly true for cetaceans, due to their relatively long lifespans, long generation times, complex social structures, and extensive ranges. In this study, we used microsatellite and mitochondrial  Prior to the first studies quantifying allozyme variation in wild populations, there was debate about the magnitude of genetic diversity expected  based on existing patterns of diversity , for example, lives for over 200 years  of just 1,000 individuals, it would take ~148,000 years to reach equilibrium. Given that major environmental changes, such as ice ages, occur in cycles much shorter than this, it is unlikely that the genetic characteristics in any bowhead whale population are ever representative of equilibrium conditions. Although the bowhead whale is an extreme example, the same is true for many cetaceans. Most species examined by Taylor et al.  events in the past.Cetaceans  represent a group of mammals for which the association between genetic diversity and population size may be particularly weak. For example, their long lifespans and generation times mean that populations may never reach mutation–drift equilibrium in between major changes in distribution, population structure, and abundance. The bowhead whale  and sperm whales —have matrilineal social systems and reduced levels of mitochondrial diversity  population size; (2) IUCN status and trend; (3) exploitation history; (4) phylogeny; (5) latitudinal range; (6) habitat type (neritic and oceanic); (7) body size (maximum length); (8) generation time and lifespan; (9) brain size; and (10) social structure. The rationale behind the choice of these classes of factor is explained below:Population size. Species with larger population size are expected to have higher genetic diversity due to reduced genetic drift and inbreeding depression  as Mysticetes  have disproportionate body enlargement, making EQ (our measure of brain size) inappropriate  AND TS=([common name] OR [Latin name])”). Microsatellite data were obtained from the Supplementary Material of Bourret, Mace, Bonhomme, and Crouau‐Roy (™ using the terms “TS=(microsatellite*) AND TS=” that covered the years 2008–2015. For each published use of each microsatellite on each cetacean species, we tabulated the microsatellite name, the species name, the number of individuals tested, the number of alleles found, and whether the microsatellite was ascertained on that specific species. For both the mitochondrial and microsatellite data, the datasets were also further divided into Rangewide (“O”) and Regional (“R”) samples. Data were considered as Rangewide if the samples covered 25% or more of the species range or an entire ocean basin, and Regional otherwise. The rationale for calculating diversity in these two different ways is to account for population structure. Briefly, if population structure is having a large impact on genetic diversity within a species, then the best‐fit model for the regional dataset should differ from that for the rangewide dataset. Moreover, comparing the models and estimated effects between the regional and rangewide datasets provides useful information on factors influencing diversity at smaller versus larger scales.Nucleotide diversities in the control region of the mtDNA (π in %) were obtained from Table ouau‐Roy  for papeRangewide and Regional estimates of mtDNA diversity for each species were calculated as the means of all published estimates of π with sample size greater than or equal to 100  data and μ = 0.2447 for the Rangewide (micO) data . We only included microsatellite loci that had been used on at least five different species, and species with analyses using at least four microsatellites, each with at least two alleles and a sample size greater than five individuals. The species effect in the linear mixed‐effects model, our estimate of relative nuclear genetic diversity, corresponds to the log of the actual divided by expected allelic diversity for each species relative to other cetaceans, controlling for sample size, the diversities of the different microsatellites, and ascertainment bias. Thus, a value below zero indicates lower than expected relative nuclear genetic diversity compared to other cetaceans and above zero greater than expected.These procedures resulted in relative genetic diversity estimates for: 30 cetacean species for the Regional microsatellite dataset (micR), 22 species for the Rangewide microsatellite dataset (micO), 23 species for the Regional mitochondrial dataset (πR) and 27 species for the Rangewide mitochondrial dataset (πO). In total, 42 different cetacean species were considered in the analysis: 31 odontocetes  and 11 mysticetes . The genetic diversity data are tabulated in Table 2.2Twenty‐one different predictive factors were considered in this study Table . Procedu2.3d was calculated for factors with two levels . PICS removes the phylogenetic bias by correlating the independent contrasts  instead of only correlating the values presented at the “end” of the phylogenetic tree  was used to obtain the respective F‐values and p‐values of the factors included in our GLMs as it accounts for the nonindependence of both continuous and categorical phylogenetic values in linear models  for each Regional and Rangewide genetic diversity marker . Backwards/and forwards stepwise regression using Akaike Information Criterion (AIC) was used to discriminate between the different models. AIC is a measure of the Kullback–Leibler Information, which is the distance between two models: in this case, the model being tested and reality. Therefore, when comparing between models, the most efficient model at predicting reality is the one with the lowest AIC Akaike, . EQ and  Grafen, .  and did not show strong effect sizes Tables . MoreovePopulation size was only correlated with nuclear DNA genetic diversity. The correlation was positive for both Regional and Rangewide nuclear data. As expected, more abundant populations tend to have greater relative nuclear genetic diversity  and 0.0835 to 0.268 (πO)  was only significant for πO  and strong effect on one or more measures of cetacean genetic diversity Table : IUCN stts Table . In bothts Table .3.2Social structure and Latitudinal range  model for both Regional and Rangewide mitochondrial genetic diversity data included the two factors e Tables  and 5. De Tables  and 7.Ocean2 and Population size . The potential reasons for these relationships are discussed below, as well as other factors that showed weaker associations.Of the 21 factors considered, mitochondrial diversity had the strongest association with 4.1Ne), but it is clear that the relationships between mitochondrial Ne and N are complex and that it may be erroneous to assume a clear relationship between the two, and therefore to make direct inferences of N based on estimates of Ne.In the recent past, one common perspective in population genetics was that mitochondrial diversity should be closely correlated with population size and therefore that mitochondrial diversity could be used to make inferences on population size in situations where information on the latter was lacking. Analyses based on this assumption have flourished, with implications across a wide range of fields. However, our results are in agreement with an increasing number of studies indicating that, contrary to this common view, there is not a close relationship between population size and mitochondrial diversity , and Hensen and Oberprieler  and, therefore, species with larger populations are less likely to be considered endangered or declining than species with smaller ones. The positive correlation between relative nuclear diversity and Population trend was significant for both Regional and Rangewide datasets, lending further support for a positive relationship between relative nuclear diversity and population size. The relatively low correlation between relative nuclear diversity and the two metrics of IUCN status may be due to a small sample size: 53% of cetacean species are listed as “Data Deficient.”Consistent with these patterns, we also found stronger correlations between relative nuclear diversity than mitochondrial diversity with several other metrics related to population size, including 4.2Social structure to be the most important factor in determining mitochondrial genetic diversity in cetaceans (relative to the other factors tested). The importance of social structure in both the Rangewide and Regional mitochondrial genetic diversity models was driven by significantly lower levels in the five cetacean species with known or presumed matrilineal social systems, in the sense that females typically stay grouped with their mothers while both are alive . This pattern has also been found in several other studies  and Population size not showing a significant relationship with mitochondrial genetic diversity when tested on its own. Instead, this correlation likely results from the segregation of species with large ranges into discrete populations sharing little or no gene flow. Species with wider latitudinal distributions are likely to face a broader range of environmental conditions and contain genetically distinct subpopulations, because of varying selection pressures and genetic drift, leading to higher diversity than species with smaller latitudinal ranges  belonging to the coastal ecotype had lower levels of genetic diversity than those belonging to the offshore ecotype. Their data suggest that this is likely due to the offshore populations acting as the source of founding individuals for the coastal populations.Our analyses found sequentially higher levels of microsatellite diversity in habitat categories “Neritic,” “Oceanic,” and “Both” Figure . SimilarSeveral other hypotheses, which are not mutually exclusive, may also explain this result. We think that the most likely explanation is that oceanic species have had larger historical population sizes due to more continuous, less fragmented environments and more stable historical conditions  showed a stronger correlation with mitochondrial diversity than relative nuclear diversity. EQ describes the relationship between brain size and body size and is often used as a measure of cognitive ability (Marino, In contrast to  Marino, . Previou Marino, . EQ valuEQ, and potential links between cognition and genetic diversity have not been much discussed in previous literature. A possible explanation could be that of Wilson (It is not clear why there seems to be a relationship between Odontocete mitochondrial diversity and f Wilson  who suggf Wilson  and thatf Wilson . Althougf Wilson , which w5There are major differences between the factors influencing mitochondrial and nuclear genetic diversity in cetaceans. While relative nuclear genetic diversity relates strongly to habitat type and seems to follow standard population genetic theory with respect to population size, mtDNA is mostly influenced by social structure and species range. These results indicate that nuclear data should be preferred over mtDNA for making inferences on population size. Moreover, we found that several factors seem to be influencing patterns of diversity in cetaceans, and therefore the interpretation of such data is more complex than is typically appreciated.None declared.FV conducted most of the literature review and data collation, conducted the analyses, and helped writing the manuscript. HW helped with the literature review, data collation, and analyses and also helped write the manuscript. TRF provided guidance with the data analysis and interpretation and helped write the manuscript. Click here for additional data file. Click here for additional data file.


Oryza sativa and O. glaberrima) to produce higher yields, cope with the effects of climate change, and resist attacks of pests and diseases, among others. However, the genetic resources of these species remain dramatically understudied, putting at risk their future availability from in situ and ex situ sources. Here we assess the distribution of genetic diversity of the four rice CWRs known to occur in Colombia . Furthermore, we estimated the degree of overlap between areas with suitable habitat for cultivated and wild rice, both under current and predicted future climate conditions to assess the potential spatiotemporal scale of potential gene flow from GM rice to its CWRs.Crop wild relatives (CWRs) of rice hold important traits that can contribute to enhancing the ability of cultivated rice  the sparse presence of CWR populations in protected areas (ii) the strong suitability overlap between cultivated rice and its four CWRs; and (iii) the complexity of managing and regulating areas to prevent alien gene flow, the first priority should be to establish representative The online version of this article (doi:10.1186/s12284-017-0150-9) contains supplementary material, which is available to authorized users. There is increasing global interest in crop wild relatives (CWRs) for the important contribution they can make to current endeavors to sustain and increase global food production  and 22 wild species  making gene transfer from wild relatives in the same complex relatively easy. However, many beneficial genes have also been successfully transferred to cultivated rice from the more distantly related species , included in the O. sativa complex, and the three allotetraploid species O. alta Swallen, O. grandiglumis (Doell) Prod., and O. latifolia Desv. included in the O. officinalis complex   were observed in the tetraploid species. Average HE across all loci was 0.57 for O. latifolia, 0.43 for O. grandiglumis, and 0.40 for O. alta. The lowest HE value was found for O. glumaepatula (0.21).For the tetraploid species, highest allelic richness was observed in A scatter plot of the first two axes of a PCoA undertaken for all species samples Fig. , shows aO. grandiglumis (two clusters) and provided more detail on the small-scale genetic structure of O. alta, O. glumaepatula and O. latifolia. ΔK values are shown in Additional file O. alta (K = 3) two subclusters were identified in cluster 2, corresponding with the two isolated groups of points in the upper and lower parts in the PCoA diagram, respectively. However, these two subgroups were not geographically coherent. Results of ΔK computation for O. glumaepatula showed support for K = 2 and 4. For K = 2 (results not shown) part of the individuals from Casanare department .A comparison of habitat suitability under current and future climate conditions suggests that all CWRs except ure Fig. , implyinOur modelling exercise has identified extensive suitable areas for rice cultivation  we found for O. glumaepatula could be considered relatively high and the inbreeding coefficient relatively low (0.37), when taking into account the small number of samples studied (n = 25). Karasawa et al. , indicating a predominantly autogamous reproduction in their study populations. Similarly, isoenzyme marker studies –known to result in lower HE scores than with SSRs  and high FIS values (>0.9) in a large number of individuals (333 and 1090)  suggest the Colombian populations hold high genetic diversity. For example, Sun et al. . These observations are in line with the findings of . Also the subgroups detected by Bayesian cluster analysis for clusters 3 and 4 of O. latifolia , and its four CWRs. Although niche suitability is not necessarily followed by cultivation practice, this outcome is indicative of the potential scale of gene flow between GM rice and its CWRs. Measures of gene flow frequencies are lower than 1% between cultivated rice and below 3% between cultivated and wild rice  Oka , therebyApis mellifera, carry pollen at least 500 m from the pollen source. Furthermore, they showed that A. mellifera-mediated transgene flow from genetically modified to conventional varieties of cultivated rice was much higher than when the bees did not participate in gene flow.Effective gene flow between GM rice and wild species is scarcely documented, possibly owing to the fact that GM rice is not yet commercially cultivated worldwide. The introgression of alien alleles in the sink population genome will ultimately depend on the manifestation, or not, of adaptive advantages. Alleles that grant some evolutionary advantage  may overcome almost any reproductive barrier, and may eventually become fixed in all exposed gene pools , requires exhaustive field testing to allow developing adequate in situ conservation strategies. In the absence of detailed knowledge on the actual probabilities of gene flow between GM rice and its wild relatives, including the tetraploid ones, a precautionary approach may be appropriate.Future research on gene transfer between GM rice and rice CWR in Colombia and beyond should therefore focus on identifying potential insect pollinators, and understanding CWRs’ phenology, gene flow distances, seeds and pollen longevity, and the adaptive advantage of any transgenic traits introduced. For example, our hypothesis that the O. glumaepatula); resistance to brown plant hopper and bacterial blight (O. latifolia); resistance to striped stem-borer ; and high biomass production  , which may in turn have potential for introgression in cultivated rice, for which less optimistic results were obtained  Jena . Our finnge Fig. , may indin situ conditions, or through the establishment and maintenance of ex situ collections. The fact that nearly all of the areas where the rice CWRs are known to occur in Colombia are located outside of protected areas and are also suitable for (GM) rice cultivation, complicates the possibility of in situ conservation in areas exempt from risks of alien gene flow. The current ex situ conservation status of Colombian rice CWR is similarly problematic. In spite of their high breeding potential and distinctive genetic makeup, Colombian rice CWRs are very poorly conserved in international and national gene banks. At the time of this research, the International Rice Research Institute (IRRI), held only two O. latifolia and one O. glumaepatula accessions from Colombia, while the International Center for Tropical Agriculture (CIAT) whose international gene bank is located in Cali, Colombia, conserved none. To our knowledge, national gene bank collections for any of the four CWRs do not exist in Colombia.The use of CWR genes for rice improvement is contingent on the effective conservation and availability of their genetic resources, either through the conservation of viable populations under ex situ collections for all wild species. Priority populations of rice CWRs for the collection of accessions for ex situ conservation and the development of in situ conservation strategies are a combination of populations that hold the highest levels of genetic diversity  and are complementary in terms of adaptive traits and their degree of genetic differentiation (beta diversity). In practical terms this would mean in situ conservation strategies should focus on those areas holding the highest genetic diversity for each of the genetic clusters. Additionally, the feasibility of establishing valuable populations, through assisted migration or assisted colonization, in areas holding favorable habitat conditions under current and/or future habitat for CWR, but not cultivated rice could be explored. According to our models such areas are likely to exist for all species.In light of the strong overlap between present and future suitable areas of cultivated rice and its four CWRs, the poor coverage of populations in protected areas, and the complexity of managing and regulating areas which are exempted from the possibility of alien gene flow (e.g. through a ban on cultivation of GM rice), a first priority should be to establish representative O. latifolia, for all species there are multiple areas that correspond to these characteristics and hence should be targeted for future collection and characterization missions. Logically, the development and implementation of in situ conservation plans should be preceded by genetic (and phenotypic) characterization and the collection of representative germplasm samples for ex situ conservation. This will allow establishing a baseline of the genetic diversity and structure of the CWR populations under consideration to which observations from future monitoring efforts can be compared.However, it is clear that our genetic characterization data are not complete and other highly diverse and genetically differentiated populations may exist that were not included in our sample but nonetheless deserve attention for conservation. Based on the results obtained here, identification of areas where CWRs are either known or likely to occur  and that overlap with, or are spatially close to, areas that may have held suitable habitat conditions during the LGM, could, in the absence of genetic characterization data, be a useful first step to prioritize areas deserving further attention. Areas that have acted as glacial refugia are likely to contain higher levels of unique genetic diversity compared to expansion areas within species’ ranges . Taxonomic identification of the different species was carried out based on a combination of morphological and molecular methods. The ploidy of the species was identified through RFLP (Restriction Fragment Length Polymorphism) analysis and comparison with reference samples of known taxonomic classification, grown from seeds obtained from the International Rice Research Institute (IRRI). Identification based on morphological traits was based on Vaughan . Total DNA quality was verified through visualization by horizontal electrophoresis in 0.8% w/v agarose gels stained with SYBR Safe (Invitrogen). DNA concentration was determined through quantification using the BioPhotometer spectrophotometer (Eppendorf).http://www.gramene.org/markers/microsat)   markers . Suitability mapping was carried out separately for both rainfed and irrigated rice , and posteriorly merged to obtain overall suitability maps of cultivated rice in Colombia. Presence data of the four CWRs collected during field sampling were complemented with records extracted from numerous sources . Given the low number of presence points available for Colombia, we carried out model calibrations based on all species records available for Latin America, from Mexico to Argentina  were carried out at 2.5 arc minute resolution using only WorldClim climate layers  for LGM model calibrations were randomly selected from the area enclosed by a convex hull polygon constructed around all presence points and extended with a buffer corresponding to 10% of the polygon’s largest axis. For future model calibrations we additionally limited the selection of background points to areas of the extended convex hull intersected by the vegetation units from Olson et al. , boosted regression trees , random forests (RF), generalized linear models , generalized additive models , multivariate adaptive regression splines (MARS), regression trees (RT), artificial neural networks (ANN), flexible discriminant analysis (FDA), support vector machines (SVM), and the BIOCLIM algorithm. As spatial autocorrelation among species presence points is known to bias model evaluations based on cross-validation, presence data permitting, we evaluated the ability of all individual modeling algorithms to cope with spatial autocorrelation by calculating calibrated Area Under Curve (cAUC) values and comparing these with a geographical null model Hijmans . We comphttp://www.worldclim.org/CMIP5v1). The RCP4.5 scenario assumes that greenhouse gas emissions will peak around 2040 and will then decline. It is expected that under scenario global surface temperature change for the end of the 21st century is more likely than not to exceed 2 °C  or through human intervention (cultivated rice), potential overestimations are justified. In fact, the use of the highest possible threshold that includes all presence locations in the area identified as suitable might still be too conservative as there is no certainty that our presence data include representative samples at the extremes of each species’ fundamental niche. To obtain summarizing maps for the two LGM climate models we averaged the threshold-limited suitability maps constructed for both individual climate scenarios.Future suitability maps (period 2040–2069) were limited to areas that were identified as suitable by at least half of all 30 possible threshold-limited climate projections. To identify areas where suitable habitat of cultivated rice (irrigated and rainfed) can realistically spatially overlap with that of its four wild relatives in Colombia, we overlaid maps of the combined current and future habitat suitability for cultivated rice and each of the wild relatives.E (expected heterozygosity) and GST (proportion of genetic diversity attributed to the differentiation among the populations) were estimated with ATetra v1.2  and the estimators of HE, observed heterozygosity (HO), overall fixation index (FIT), fixation index or genetic differentiation of subpopulations (FST), and inbreeding coefficient (FIS), were calculated with FSTAT v2.9.3  or the Bruvo distance. We identified different genetic groups for each of the species by submitting the Bruvo distance matrices to hierarchical cluster analysis with bootstrap resampling  to provide indications of branch support, implemented in the R package pvclust  tested varied from 1 to 6, and for O. latifolia from 1 to 13. We used burnin periods of one million steps followed by ten million additional MCMC repetitions. For each value of K, we carried out 10 independent iterations. We used the method of Evanno et al.  for visualizing genetic differentiation between and within species samples, using the R package o et al.  for deteo et al.  as implePolysat package and custom-made code for R . To obtain sufficient and more evenly distributed data points for constructing high resolution maps, we constructed circular neighborhoods of 5 arc minutes diameter (~10 km at the equator), following Genetic diversity estimators for the tetraploid species Additional file 2: Table S2.O. glumaepatlula. (DOCX 14 kb)Genetic diversity estimators for the diploid species Additional file 3: Figure S1.O. glumaepatula only) genetic distances and the Unweighted Pair Group Method with Arithmetic Mean. To types of p-values are provided to quantify branch support: the AU (Approximately Unbiased) p-value and BP (Bootstrap Probability) value. According to Suzuki and Shimodaira Hierarchical cluster dendrograms based on the Bruvo and Nei , compared with the distribution of genetic clusters and Shannon diversity index of sampled populations. (TIF 1687 kb)Habitat suitability of Additional file 6: Figure S4.O. glumaepatula during the Last Glacial Maximum , compared with the distribution of genetic clusters and Shannon diversity index of sampled populations. (TIF 1751 kb)Habitat suitability of Additional file 7: Figure S5.O. grandiglumis during the Last Glacial Maximum , compared with the distribution of genetic clusters and Shannon diversity index of sampled populations. (TIF 1731 kb)Habitat suitability of Additional file 8: Table S3.Results of Mantel tests for all rice CWR between genetic and geographical distances for all individuals sampled and individuals per genetic cluster. (DOCX 14 kb)Additional file 9: Figure S6.Oryza sativa, considering both rainfed and irrigated rice. (TIF 4570 kb)Predicted changes in habitat suitability from present to the 2050s of cultivated rice Additional file 10: Table S4.O. glumaepatula in Latin America. (DOCX 12 kb)Metrics obtained from genetic diversity studies of Additional file 11: Figure S7.Oryza latifolia with flower size smaller than 7 mm; (B) Oryza grandiglumis with approximately equal-sized sterile and fertile lemmas; and (C) Oryza alta with flower size larger than 7 mm (photo credits: Oscar Andrés Estrada). (DOCX 180 kb)Details of panicles (top), ligules and auricles (bottom) of (A) Additional file 12: Table S5.Oryza spp. samples with genetic characterization data. (CSV 74 kb)List of analyzed Additional file 13: Table S6.PCR primer sequences, allele size ranges and chromosome position on the Nipponbare genome of the SSR loci used in this study. (XLSX 12 kb)Additional file 14: Figure S8.Distribution of species records used in suitability model calibrations. (TIF 1695 kb)Additional file 15: Table S7.Suitability model statistics and metrics. (DOCX 17 kb)