Parents influence the development of their offspring in many ways beyond the transmission of DNA. This includes transfer of epigenetic states, nutrients, antibodies and hormones, and behavioural interactions after birth. While the evolutionary consequences of such non-genetic inheritance are increasingly well understood, less is known about how inheritance mechanisms evolve. Here, we present a simple but versatile model to explore the adaptive evolution of non-genetic inheritance. Our model is based on a switch mechanism that produces alternative phenotypes in response to different inputs, including genes and non-genetic factors transmitted from parents and the environment experienced during development. This framework shows how genetic and non-genetic inheritance mechanisms and environmental conditions can act as cues by carrying correlational information about future selective conditions. Differential use of these cues is manifested as different degrees of genetic, parental or environmental morph determination. We use this framework to evaluate the conditions favouring non-genetic inheritance, as opposed to genetic determination of phenotype or within-generation plasticity, by applying it to two putative examples of adaptive non-genetic inheritance: maternal effects on seed germination in plants and transgenerational phase shift in desert locusts. Our simulation models show how the adaptive value of non-genetic inheritance depends on its mechanism, the pace of environmental change, and life history characteristics. Parents contribute to offspring development in many ways, including transmission of DNA and its associated epigenetic marks, allocation of resources to the egg and growing embryo, and behavioural interactions following birth or hatching. The mechanisms by which parents affect offspring development in addition to DNA transfer are known as parental effects or non-genetic inheritance , 2. The It is the adaptive value of non-genetic inheritance that we address in this paper. We do so by presenting a framework based on the assumption that, from the perspective of a developing organism, both genetic and non-genetic inputs can be potential sources of information about the selective regime facing an individual , 36. EvoOur framework builds on the work of Leimar and colleagues , 40. TheThe general framework for addressing when these different forms of non-genetic inheritance will be favoured by selection is outlined in ED) correlates with the environment at the time of natural selection on the morph (ES), then ED carries correlational information about ES. Similarly, the parental phenotype can carry correlational information about ES, for example, if the parental phenotype responds to its own environment and the parental environment correlates with offspring environment. Finally, because natural selection will tend to build up gene frequency differences between environments, genotype can also correlate with ES if different genotypes have different fitness across environments and there is incomplete admixture in between rounds of selection . We refer to these phenotypes as morphs. Evolution of morph determination thus occurs when the developmental switch changes its responsiveness to different sources of input, for example, a transition from responding primarily to allelic variation at one or several genetic loci to responding primarily to environmental variation. Evolution may also favour responsiveness to several types of cues. We have shown previously that such transitions can be captured in informational terms . This isonments, ).Under this information framework, there are several reasons why individuals might rely on certain types of information or not. Signals can be noisy, for example if the cues provided by the parental phenotype are obscured by other individuals or the external environment. Individuals may also incur costs in sensing or processing the signal. Finally, even when a reliable signal is available, there may be costs and benefits of using it, including costs of detection, or of false positive or false negative responses.Although all three sources of input can carry correlational information about the environment at the time of selection, the information carried by the genotype differs from that of the external environment and the parental phenotype in one important respect: the build-up of information in genotype is the result of natural selection on stably transmitted (or replicated) variants , 36, 40 . This meThis model approach presents a powerful way to evaluate the life-history and environmental conditions that favour non-genetic inheritance as opposed to genetic determination of phenotype or within-generation phenotypic plasticity. To exemplify the use of this approach for understanding the evolution of non-genetic inheritance we build individual-based simulation models. Specifically, we model two frequently discussed examples of adaptive non-genetic inheritance: maternal effects on the timing of germination in plants  and tranIn our first simulation model, we consider a plant-like system with limited dispersal of seed and pollen between patches, and where the trait under consideration is seed germination . In this system, we consider the evolution of a particular type of non-genetic inheritance: that of offspring responses to variation in parental phenotype. We investigate the effects of spatial environmental heterogeneity and sex-specific gamete dispersal on the evolution of this non-genetic inheritance. There are several routes by which parents can influence their young, however, with potentially contrasting consequences for adaptive evolution (review in ). Our seP1 and P2, in an environment that can take on one of two different states, E1 and E2. Phenotype P1 has higher fitness than phenotype P2 in E1, and vice versa for E2. Mortality of mismatched phenotypes is equal to s and relative fitness is thus defined as 1-s. For simplicity we consider non-overlapping generations in both of our models. The developmental regulation of morph expression is determined by the action of a developmental switch that can respond to three types of input: allelic variants on one or more genetic loci, stably transmitted from parents to offspring (genetic inheritance), the parental phenotype in some form that can causally affect offspring development (non-genetic inheritance), and the offspring’s external environment at the time of morph determination  is a function describing how the parental cue is affected by parental environment and phenotype ; EO describes the offspring’s assessment of its own environment; and is ε an error term . In general, the weighting terms bM and bO are continuous variables that can take on both positive and negative values and parameters describing parent and offspring phenotype or environment  can be discrete variables or continuous variables depending on the system.The three inputs combine into a single liability, From this general model we can subsequently specify the different functions, number of genetic loci, type and extent of environmental heterogeneity, and life history of the organism . This enables specific models that test the conditions that favour evolution of non-genetic inheritance of morphs, relative to genetic inheritance and within-generation plasticity, which we here exemplify with two case studies. In both case studies, we verified that the variables reached a stationary state in our simulations and present results from ten replication simulations for each setting.Campanulastrum americanum, seeds from mothers in light conditions tend to germinate in the autumn and those in shade conditions in the spring [In many plant species, the parental environment has a strong effect on traits expressed early in life in the next generation , 50. Onee spring , althouge spring  used a fe spring , wherebye spring , adaptive spring , and dete spring ).Claytonia perfolata polyploid complex demonstrated that the impact of adaptive transgenerational effects on leaf morphology in response to shade environment was small relative to within-generation plasticity and local adaptation [In these plant systems, with limited dispersal between patches, it seems plausible that parents should play a role in adaptive morph determination of their offspring. There are several open questions as to the relative importance of non-genetic inheritance compared to genetic inheritance and within-generation plasticity. A recent study on the aptation . As discaptation  and lateaptation . Anotheraptation .C. americanum, as outlined in yG is the effect ascribed to inherited genes; bM, bF and bO are the relative weights given to maternal, paternal and offspring inputs respectively; these inputs being maternal and paternal phenotype (PM and PF respectively) and offspring assessment of its own environment (EO); and ε is a developmental-noise error term.Here, we formalize verbal suggestions regarding the adaptive significance of maternal effects on seed germination using a life history characterized by that of We use this model to test the conditions under which adaptive maternal effects evolve, relative to genetic, paternal and direct environmental inputs. We vary the parameters of environment type frequency, extent of seed and pollen dispersal, environment-specific parental trait distribution and offspring assessment of the environment . We find that, when patches are found in equal numbers, genetic determination does not evolve whereas maternal effects evolve , with greater values when the parental phenotype is narrowly distributed between environments . We find that genetic determination only evolves when one patch is rare, when offspring cue is uninformative and  when parent traits overlap across environments , bottom.Schistocerca gregaria) exhibit remarkable phenotypic plasticity in response to crowding conditions, with solitary and gregarious morphs (termed ‘phases’) differing in a suite of morphological and behavioural traits [Desert locusts , hj is the transmission stability of the previous maternal input , depending on maternal phenotype (j = solitary or gregarious), bo is weighting on offspring environment input (EO) and ε is a developmental-noise error term.Here, we use simulations to explore the conditions under which maternal effects on morph determination and a hysteresis effect evolve. The model is similar to the basic model described above, although the population is spatially homogenous, with no dispersal, and the environment fluctuates between crowded and uncrowded states. The offspring phenotype is solitary or gregarious, which have relatively higher fitness in the uncrowded and crowded environments respectively. The life cycle is explained in We use this model to investigate, first, how variation in maternal and offspring error in assessing the environment affects the evolution of different mechanisms of non-genetic inheritance . We then consider the conditions under which hysteresis evolves, by allowing asymmetry between environments in selection on mismatched phenotypes, the number of generations at which the environment remains in a certain state, and in the probability mothers or offspring receive an incorrect signal about their environment . Finally, we compare the conditions under which maternal effects evolve when offspring are also allowed to assess their own environment. We provide an overview of our key findings below, with full details in Locust phase shift model: summary of results. We first examine how environmental stability and maternal error affect the evolution of direct maternal environmental effects and transmission stability of the maternal input received in the previous generation, assuming no genetic or offspring input. We find that maternal environmental effects evolve under all conditions and transmission stability evolves when maternal error is high and environments are relatively stable  and how different mechanisms of non-genetic inheritance can contribute to different transgenerational transition rates from one morph to the other (locust model). Below, we discuss these findings in more detail and suggest some additional uses of the framework for studying more complex scenarios.per se, but only in the process by which different mechanisms come to carry informational content [Both genetic and non-genetic inheritance are commonly conceptualized as transmission of information from one generation to the next –71. Here content , 36. ManOur first example concerns the evolution of maternal effects on germination strategies in spatially heterogeneous environments. While our model is parameterized to a spatially varying environment, the conclusions also apply to a situation of temporally varying environmental change with stochastic switching . In suppGenetic divergence between patches in meta-populations is often limited because of pollen or sperm dispersal. As expected, this also prevents strong genetic effects on the timing of seed germination in our plant example. Pollen dispersal also prevents the evolution of paternal effects because it reduces the autocorrelation between the paternal and offspring environment. It is important to note that with the life history modelled here, the paternal phenotype only carries information about the offspring environment when seed dispersal also is low. This reduces the overall importance of information transmitted through the male germ line, although the added information value may be sufficiently high to select for paternal effects under some circumstances . There are empirical examples of putative adaptive paternal effects , 76, andNon-genetic transmission of information between generations also readily evolves in a temporally variable environment. The same general criteria, for example, the extent to which parental phenotypes correlate with the selective agent in the following generation, apply here. Transmission of epigenetic variants down generations has received much attention and we show that increased stability is favoured when environmental change is infrequent relative to generation time and the information content of the parental phenotype is low . Other cIn the locust example, we also consider an alternative mechanism of non-genetic inheritance, that of phenotype-dependent transmission stability of epigenetic states. Research on DNA methylation and other epigenetic mechanisms suggests that transmission stability could depend on the phenotype of the parents. For example, in mice, the extent to which offspring inherit methylation status of the agouti locus  depends on the phenotype of their mother . In the Although we demonstrate that non-genetic inheritance can be adaptive across a range of conditions, most of these rely on limited availability of direct environmental cues . Thus, when both parental and environmental cues are available, the contribution of non-genetic inheritance to morph determination is likely to be quite minor. The most likely candidates for parental determination of offspring phenotype are therefore those where direct cues are unavailable or costly to assess, environments at the time of phenotype determination are not a good predictor of the environment of selection, when phenotypes are expressed at a stage in development where the necessary sensory systems for processing environmental information are lacking, or when a substantial time is required from assessing the cue to develop the phenotype . OffspriBoth examples in this paper are relatively simple and there are a number of interesting additional details that apply to many biological systems. For example, the maternal phenotype does not only affect offspring development directly by providing resources or information, but may also contribute indirectly by modifying offspring environment . Such efIn summary, we have expanded on a previous model of within-generation plasticity  to generS1 FileSimplified analytical version of the framework presented in the paper which predicts when genetic, parental and offspring inputs to development will evolve depending on how mutual information is maximized.(DOCX)Click here for additional data file.S2 FileComplete details on the parameters used in the simulation models, including description and figures of the results for all parameter combinations tested and example trajectories indicating stability of evolved locus values.(DOCX)Click here for additional data file.


Panulirus ornatus  in the South-East Asian archipelago from Vietnam to Australia. Partial mitochondrial DNA control region and 10 polymorphic microsatellites did not detect genetic structure of 216 wild P. ornatus samples from Australia, Indonesia and Vietnam. Analyses show no evidence for genetic differentiation among populations . A lack of evidence for regional or localized mtDNA haplotype clusters, or geographic clusters of microsatellite genotypes, reveals a pattern of high gene flow in P. ornatus throughout the South-East Asian Archipelago. This lack of genetic structure may be due to the oceanography-driven connectivity of the pelagic lobster larvae between spawning grounds in Papua New Guinea, the Philippines and, possibly, Indonesia. The connectivity cycle necessitates three generations. The lack of genetic structure of P. ornatus population in the South-East Asian archipelago has important implications for the sustainable management of this lobster in that the species within the region needs to be managed as one genetic stock.Here we utilize a combination of genetic data, oceanographic data, and local ecological knowledge to assess connectivity patterns of the ornate spiny lobster  Panulirus ornatus, lives in tropical waters of the Indo-West Pacific from the Red Sea and south-east Africa in the west to Japan and Fiji in the east.The species is of significant commercial importance supporting local capture fisheries and developing aquaculture operations. P.ornatus pueruli  are heavily exploited as seed-stock for aquaculture in South-East Asia, particularly in Vietnam and Indonesia, where wild pueruli are collected from the ocean in large numbers [P. ornatus pueruli wild harvest in Vietnam was only ~50% of that caught in other years [P. ornatus and it is not known where the source of pueruli being harvested is situated. An investigation into the connectivity among spiny lobster populations is therefore needed to provide data on the resilience and sustainability of heavy exploitation, as well as to provide information on larvae sources and sinks.The ornate spiny lobster,  numbers . Even th numbers –4, there numbers , 6. Thiser years , 7. ThisP. ornatus [P. ornatus in restricted areas of the species distribution. Previous studies in eastern Australian waters [P. ornatus (i.e. from spawning ground to puerulus settlement site over a few months). According to these models most larvae released from spawning grounds in the Coral Sea, such as the Gulf of Papua, would be carried back to the coastline of northeast Queensland, while a part of them could advect northward to the Vitiaz Strait of eastern PNG within three months [P. ornatus across the broader South-East Asian archipelago , geochemical markers , and/or the utilization of high-resolution biophysical models; however none of these approaches are likely to be conclusive in isolation and have not yet been applied to adequately address population connectivity in  ornatus –10. To dn waters  and in tn waters  focused e months . From die months . These shipelago .P. ornatus genetic structure, or in fact connectivity of other marine species. The existing oceanographic models include a number of fine-scale models focusing on restricted areas within the archipelago , and mego (e.g. ) that hago  and Binh Thuan  provinces, while Indonesian samples were collected from North Sumatra , Lombok  and West Timor . Australian samples were collected from wild-caught Torres Strait juveniles . All samples  were preserved immediately in a DMSO-salt preservative solution [2 pleopod clips or from the abdominal muscle tissue of juveniles using a modified CTAB protocol [A total of 216 ustralia . Specimeprotocol .Panulirus ornatus, P. gracilis, P. stimpsoni, P. japonicus, and P. inflatus from the NCBI database were aligned using SEQUENCHER version 4.5 (GeneCode) and primers to amplify 809 base pairs of the mtDNA control region designed based on conserved sites using PRIMER3WEB version 3.0.0 (http://primer3.wi.mit.edu/). These primers were; PO_F2 5’—ATAAAGGTAATAGCAAGAATC and PO_R1 5’—CAAACCTTTTGTCAGGCATC.Whole and partial genome sequences including mtDNA control regions of 2, 0.2 μM of dNTPs, 0.1 μM of Tag Red (Qiagen) and 0.3 μM of forward and reverse primers. PCR was performed on a BioRadC1000 Thermal Cycler . PCR products were then run on a 1.5% agarose gel for quantity and quality verification, and subsequently cleaned-up to remove excess primers by precipitation with isopropanol [Extracted DNA from samples was diluted to 10–40 ng/μl for use in a polymerase chain reaction (PCR). The control region was amplified in 20 μl reaction volumes containing ~5 ng DNA, 1× TM buffer (Qiagen), 1.5 μM of MgClpropanol . A repeaD [ΦST (using genetic distance) as well as pairwise ΦST were calculated using ARLEQUIN 3.5 [ΦST and pairwise ΦST comparisons between populations were estimated using the T92 model (Tamura 1992), with a gamma correction (α = 1.258) as determined by Model Selection in MEGA6 [ΦST values obtained, a significance test with 10,000 permutations was undertaken with ARLEQUIN 3.5 [http:\\www.fluxus-engineering.com) with default settings.Sequence data were aligned using Geneious ver. 6.0.5 with default alignment parameters and were checked manually for misalignments. Poorly-aligned regions were removed using GBlocks with the default setting . The nucD ) and parQUIN 3.5 . ΦST anon α = 1.8 as deteQUIN 3.5 . The medQUIN 3.5  for the Ten highly polymorphic microsatellite markers  were usehttp://genepop.curtin.edu.au/) was used to test for linkage disequilibrium among microsatellite loci. Corrections for multiple comparisons (HWE and linkage disequilibrium) were adjusted using the False Discovery Rate (FDR) method [Summary statistics such as the number of alleles, as well as observed and expected heterozygosities, were calculated for microsatellites in GENALEX 6.1 , which w) method . Polymor) method . Null al) method  while th) method .P. ornatus based on microsatellite markers was analysed using an Analysis of Molecular Variance (AMOVA) with 10,000 permutations, as well as calculating pairwise FST comparisons between populations, both of which were carried out with ARLEQUIN 3.5 [http://taylor0.biology.ucla.edu/structureHarvester/) was used to determine optimum number of clusters in this analysis. CLUMPP (http://www.stanford.edu/group/rosenberglab/clumpp.html) also was used to average across the replicate run and outputs were entered into DISTRUCT (http://www.stanford.edu/group/rosenberglab/distruct.html) to graph average q values.The level of genetic structure of QUIN 3.5 . FurtherQUIN 3.5  was usedΦST = -0.0039; FST = 0.0037; P >0.05) and accordingly we only report results from analyses for the Indonesian samples where we have treated them as a single population.The Indonesian samples were a mix of two different age groups . To test if there may have been temporally-induced genetic differences among these two collections we first undertook analyses treating each temporal sample as a separate collection. No evidence of genetic differentiation was evident among the temporally separated samples (o N) and November to January in the South , where Torres Strait lobsters spawn during the summer months from November to March , 37, 38.P. ornatus larvae are found mainly within this layer [http://www.aoml.noaa.gov/phod/argo/introduction_argo.php), but this had limited coverage for the South China, Philippines and Indonesian Seas. For those seas, the results of other field studies (listed in L) between two sites was measured by Distance Calculator using Google Maps (http://www.mapdevelopers.com/distance_finder.php), not as a straight line, but as the length of the streamline of the flow field joining these two sites; and u is the average speed of surface ocean current along that streamline during that period. Thus, the estimated time (t) for the larvae to reach different locations was calculated by Fischer [This biological data was then merged with oceanographic data to construct a map of the mean surface water circulation in the South-East Asian Archipelago, focusing on different months for different areas based on the known age of lobster larvae found during those months in those areas. We studied only the currents in the surface well-mixed layer, i.e. the layer above the thermocline, which in the tropics is typically about 100 m deep . The P. is layer  and it iis layer .The main Fischer ,P. ornatus individuals (Genbank accession no. KJ956062-KJ956250). A small number of samples for which DNA was extracted failed initial quality control checks and were not successfully sequenced. From the 189 individuals sequenced successfully a total of 182 haplotypes were detected, with 601 sites without gaps and missing data and 231 were polymorphic . All of the genetic variation measured with mtDNA occurred within populations, with no detectable among-population variance    . SimilarP >0.05) . As furtP >0.05) . TherefoP. ornatus were genotyped for subsequent population genetics analyses. A total of 143 alleles were observed, ranging from five (Orn_01) to 29 (Orn_11) alleles per locus. Significant departures from HWE were observed for two loci in the Lombok and Binh Thuan populations (Orn_01 in Lombok and Orn_17 in Binh Thuan) and the dataset was reanalyzed with and without these markers in these two populations to test if they were significantly influencing results obtained. No differences were found in genetic structure indices when these markers were included so the complete dataset of markers were analyzed and is presented here. No linkage disequilibrium was detected among the 10 loci genotyped. Null allele frequencies were above 10% at locus Orn_02 in Lombok (13%), at locus Orn_17 in West Timor (17%) and in Binh Thuan (15%) (FST estimates (Ten polymorphic microsatellite markers were successfully amplified  and PCR an (15%) . Null alstimates  Table. TFST estimates of population structure were again negligible and non-significant  , but were all non-significant after FDR correction (P > 0.05). Due to the small sample size collected from North Sumatra the higher sample FST values involving this population are likely a result of random sampling effects and small sample size.As for the mtDNA control region, no significant population genetic structure was evident between the six sites when genotyped with the 10 microsatellite loci. = 0.195) . The micFST estimates. Although Structure Harvester suggests K = 2 from multiple simulations runs at values of K from 1 to 10, visual examination of individual bar plots for K = 2 indicates an inability of the STRUCTURE algorithm to reliably assign any of the individuals to a distinct cluster, with assignment probabilities for each of the two populations of ~50% for all individuals sampled in each of the 10 replicate runs  or phylogeographic network analyses indicated any evidence for restrictions on gene flow across the region and integration of biological and oceanographic data show that genes can potentially circulate unimpeded throughout the entire region in only a few generations.A combination of mitochondrial DNA control region and microsatellite DNA data suggest a single, genetically homogeneous stock of tropical ornate spiny lobster across a broad region of the South-East Asian archipelago. Genetic differences were not detected between samples of Williams  of low gPanulirus species and may be a consequence of the long larval dispersal and adult migration life-history within this genus of lobsters. For instance, genetic studies on Japanese spiny lobster, P. japonicus, failed to reveal any stock heterogeneity within the Japan Sea [P. gilchristi in South Africa [P. cygnus in Western Australia [Panulirus lobsters does not always lead to low population divergence. In P. argus, for example, genetic differentiation is present between Bermuda and Florida populations within the Caribbean Sea, as well as those from Venezuela and Brazil [P. delagoae and P. elephas populations in the Atlantic Ocean and Mediterranean Sea exhibit shallow, but significant, levels of genetic structuring [P. penicillatus within localities in Western Pacific, but genetic structure was detected between Western and Eastern Pacific populations [Similar occurrences of high population inter-connectivity have been observed in other apan Sea . Low heth Africa  and P. custralia . Howeverd Brazil . Likewisucturing , 57. Reculations , 59. In Regarding the mtDNA data presented in our study, previous papers have illustrated the point that inadequate sampling can lead to the wrong conclusions and for studies based on the mtDNA control region alone, in the situation where such high haplotypic diversity is evident within a species very large sample sizes can be required to detect common haplotypes and associate them with particular geographic areas , 61. As P. ornatus populations within the South-East Asian archipelago within three generations of breeding. Starting arbitrarily as the first generation from the spawning ground in the Gulf of Papua, with spawning known to occur from November to March . Instead, larvae are carried through to the southern Philippines where they are dispersed widely by complex, swift currents through straits between islands from August to September (days 106 to 159 after spawning). This dispersal is facilitated by the directional swimming towards the shore of the pueruli during the last 25 days of development. After metamorphosis to the puerulus stage, lobsters settle to a benthic existence, where they progressively grow to maturity. It is unlikely they will move any great distance during this period, however, upon maturation adult lobsters may migrate up to a few hundred kilometres to the identified spawning grounds in the northern or western Philippines where they will spawn the second generation of larvae [Our oceanographic informed dispersal modelling suggests the potential for complete connectivity of to March , modellif larvae , [19, 61P. ornatus larvae then would rapidly travel with the Mindanao Current southward to Lombok which they would reach in about 73–113 days. At that time the larvae are old enough to metamorphose into pueurli and settle and mature to become the third generation of adults. Spawning P. ornatus adults in Indonesia appear to produce two larval plumes. One plume originates in the south of Lombok and would travel with the Indonesian Throughflow to arrive in the Indian Ocean and ultimately to reach the Indian Ocean coast of northern Sumatra in November—December. These larvae are advected back towards Lombok during the northern winter monsoon (from November to February) before settling. The second larvae plume originates from the north of Lombok and is advected by currents to the Banda Sea and the northern Arafura Sea during the northern winter monsoon to reach Torres Strait waters by February. Evidence for these small juveniles (<40 mm carapace length) have been observed in Western Torres Strait [The second generation of larvae are produced from these adults on the east and west coasts of the Philippines from May to August. These larvae then potentially disperse in three plumes. The first plume is advected northward towards Taiwan . The secs Strait . We suggIn our study area the mean sea level was 100 m lower at the end of the last Ice Age about 20,000 years ago. At that time the Torres Strait was land and there was no connection between the Arafura Sea and the Coral Sea; in fact it is only about 8000 years ago that Torres Strait was flooded . Thus thP. ornatus characterised by drift connectivity [P. ornatus larvae are known, the knowledge of larval sources is still rudimentary, with to date only a few spawning sites confirmed. The present study suggests that an additional spawning ground may also be present in Indonesia, and its location needs to be identified and protected. More detailed studies on population connectivity are necessary to ensure the sustainability of lobsters in the South-East Asia archipelago. Genetic connectivity should be conserved as a priority.The existence of a single genetic population of ectivity  might haectivity .ConsequeP. ornatus populations throughout the South-East Asian archipelago. The study is novel in terms of population dynamics because it suggests that this connectivity requires three generations for the cycle to complete and is reliant on timing of spawning events, time to settlement and prevailing ocean currents. These results have implications for fisheries management in the region, because there appears to be single stock of P. ornatus, which requires the engagement of governments and agencies to provide effective management policies for the benefit of all countries. A modelling study of larval transport processes over at least three generations is necessary to better locate the larval dispersal pathways and quantify the population dynamics including the relative influence of self-seeding versus broadcast connectivity between spawning populations.This study based on population genetic analyses at both mtDNA and nuclear DNA markers indicates high levels of connectivity among S1 Tablehttp://dx.doi.org/10.5061/dryad.sp418/2.(DOCX)Click here for additional data file.S2 Tablehttp://dx.doi.org/10.5061/dryad.sp418/3.Values above 10% are in bold. (DOCX)Click here for additional data file.S3 Tablehttp://dx.doi.org/10.5061/dryad.sp418/4.(DOCX)Click here for additional data file.S4 Tablehttp://dx.doi.org/10.5061/dryad.sp418/5.No significant value was found after correction using FDR. (DOCX)Click here for additional data file.


C. aegagrusor bezoar) suggest a pre-domestication management of wild populations in southern Zagros and central Iranian Plateau. In this study genetic diversity was assessed in seven Iranian native goat breeds, namely Markhoz, Najdi, Taleshi, Khalkhali, Naini, native Abadeh and Turki-Ghashghaei. A total of 317 animals were characterized using 14 microsatellite loci. Two Pakistani goat populations, Pahari and Teddy, were genotyped for comparison.Iran is an area of particular interest for investigating goat diversity. Archaeological remains indicate early goat domestication (about 10 000 years ago) in the Iranian Zagros Mountains as well as in the high Euphrates valley and southeastern Anatolia. In addition, mitochondrial DNA data of domestic goats and wild ancestors (GST = 5.9%). Positive and highly significant FIS values in the Naini, Turki-Ghashghaei, Abadeh and Markhoz breeds indicate some level of inbreeding in these populations. Multivariate analyses cluster Iranian goats into northern, central and western groups, with the western breeds relatively distinct from the others. Pakistani breeds show some relationship with Iranian populations, even if their position is not consistent across analyses. Gene flow was higher within regions  compared to between regions but particularly low between the western and the other two regions, probably due to the isolating topography of the Zagros mountain range. The Turki-Ghashghaei, Najdi and Abadeh breeds are reared in geographic areas where mtDNA provided evidence of early domestication. These breeds are highly variable, located on basal short branches in the neighbor-joining tree, close to the origin of the principal component analysis plot and, although highly admixed, they are quite distinct from those reared on the western side of the Zagros mountain range.Iranian goats possess a remarkable genetic diversity  mainly accounted for by the within-breed component  of an almost exclusive contribution of the eastern Anatolian bezoar to the domestic goat gene pool. Iranian goats are mainly reared in traditional systems by small holders. Since nomadic tribes are almost completely economically dependent on animal rearing, these stakeholders play an important role in the conservation of animal genetic resources, especially of small ruminants.Goats are multi-purpose animals that produce milk, meat and fiber and also serve other beneficial roles. In particular, they contribute to the economy of farmers living in arid and semi-arid regions, including southern Iran . AlthougGenetic diversity is an essential component for population survival, evolution, genetic improvement and adaptation to changing environmental conditions . Informahttp://www-naweb.iaea.org/nafa/about-nafa/index.html).This study was undertaken to examine the pattern of microsatellite variation within and among seven Iranian goat breeds. The resulting information may be used in national plans for sustainable improvement and conservation of goat genetic resources. This research was carried out as part of the IAEA-FAO joint program “Characterization of genetic resources in small ruminants in Asia” (D3.10.25), which aimed at developing methodologies, generating information and formulating decision support systems to analyze phenotypic and molecular genetic diversity, develop microsatellite and related technologies, and enable the development and implementation of national and regional strategies for optimum use and conservation of small ruminants in Asia , observed heterozygosity (HO) and mean number of alleles (MNA) were calculated using the Microsatellite Toolkit [P values from multiple comparisons were corrected using a Bonferroni correction [FIS) for each population and a pairwise FST distance matrix. The rarefaction technique of El Mousadik and Petit (1996) [FST)/(4FST) as applied in Genetix 4.05 [GST) [ST) do not conform to the prediction of a simple island model obtained by coalescent simulations [FST/HE values for all loci indicates a shared demographic history. Loci showing unusually large amounts of differentiation may mark regions of the genome that have been subject to directional selection, while loci showing unusually small amounts of differentiation may mark regions of the genome that have been subject to balancing selection [FST was calculated again. A final run included all loci. The infinite allele model and 95 000 simulations were used in this calculation. Hierarchical analysis of molecular variance (AMOVA) was conducted with geographical location as grouping factor, using Arlequin 3.11. Goat breeds were spatially partitioned into five groups including (A) TAL and KHL, (B) NAI, TUR and ABD, (C)MKZ, (D)NAJ and (E) TED and PAH (Pakistani populations). AMOVA was used to measure the extent of hierarchical genetic differentiation among the locations, among populations within a location, and among individual within a population [Unbiased estimates of genetic diversity   was usedt (1996) . The numt (1996)  was calct (1996) . The avetix 4.05 . This so96  was u05 [GST) , impleme05 [GST)  was usedulations . Similarelection . All locpulation .DA) [K) varied between 2 and 11. For each K, 10 independent runs were performed with a burn-in of 105 and Markov chain Monte Carlo length of 2 × 105 iterations under an admixture model with correlated allele frequencies and no prior information on the population of origin (popinfo = 0). The assignment probabilities were compiled for multiple runs in the program CLUMPP, which addresses multimodality and/or label-switching in run comparisons [K. The results of STRUCTURE analyses were depicted using the software Distruct [K was calculated as described by Evanno et al. [Three approaches were used to analyze the genetic relationships among individuals and populations: (i) genetic distances and dendrograms, (ii) model-based cluster analysis, and (iii) principal components analysis (PCA). A dendrogram was constructed using the Neighbor-Joining (NJ) algorithm  in DISPADA) . Trees wDA) . The BayDA)  was usedparisons . We usedDistruct . The esto et al.  using Sto et al. . PCA wasP < 0.05). Five populations, NAI, TUR, ABD, MKZ and TED, showed deviation from HWE for at least one locus (P < 0.05). Nine of the 126 locus × population combinations revealed significant departures from HWE. Several estimates of the frequency of null alleles (r) were greater than 0.11, i.e. for BMS1494, ILSTS029 and MAF035 [see Additional file Ar), which was also greatest in TUR (5.99) but smallest in NAJ (4.25). The mean of the effective number of alleles per locus and population ranged from 2.65 (NAJ) to 4.00 (KHL)  and MKZ (P < 0.01), which indicated inbreeding in these breeds  to 18 ILSTS029) per locus and the average number was equal to 10.7. Most loci displayed a high degree of polymorphism, as revealed by the PIC values that ranged between 0.435 (INRA0132) and 0.851 (MAF70), with a mean of 0.67. Relevant information per locus, such as the range of allele sizes, location on chromosomes, sequence and label of the primers, number of alleles (observed and effective), PIC and deviation from HWE, are presented in Additional file 9 per loc5 to 18 IFST obtained by the jack-knife method over loci was equal to 0.062 ± 0.016 and significantly different from zero (P < 0.001). Wright’s F-statistics were calculated for each of the 13 microsatellite loci across the nine breeds [see Additional file P < 0.01 and P < 0.001, respectively). Very similar results were obtained by clustering breeds according to the groups identified in the STRUCTURE analyses.The global FST values between breed pairs ranged from 0.0041 for the TAL-KHL pair to 0.1622 between PAH and MKZ breeds. Pairwise estimates of FST for north (TAL and KHL) and center  of Iran were not significant. For all remaining breed pairs, FST values were highly significant (P ≤ 0.001) (Table DA) ranged from 0.0521 between TAL and KHL to 0.2760 between NAJ and PAH. The two Pakistani breeds (TED and PAH) showed the lowest DA distance with TUR. Nei’s standard genetic distance (DS) ranged from 0.0108 (TAL-KHL) to 0.4269 (PAH-MKZ). TED and PAH showed the lowest DS distances with the Iranian KHL and TUR goat breeds [see Additional file DA genetic distances  cluster with the northern Iranian breeds (TAL and KHL), even if the branch lengths indicate that they remain rather distant from the Iranian pool and from each other. PCA grouped Iranian breeds in accordance with the NJ trees , center  and west (MKZ and NAJ) of Iran. The two Pakistani breeds were assigned to two other distinct clusters  Table .The numb1) Table . A gene C. aegagrusor bezoar) revealed signals of population expansions in wild populations in southern Zagros (Fars Province) and in the central Iranian Plateau (Yazd and Kerman Provinces), likely indicating a pre-domestication management of wild populations [Iran is close to, and in the case of goats, within, the main south west Asian livestock domestication center. In fact, archaeological remains indicate an early goat domestication (about 10 000 years ago) in the Iranian Zagros Mountains , as wellulations . These rThe analysis of 13 microsatellites resulted in a mean genetic diversity of 0.671  [see Additional file In the present study, expected heterozygosity and allelic richness had the highest values for ABD and TUR (two Iranian goats) with means of 0.72 and 5.99, respectively. We can thus conclude that Iranian goats possess a remarkably high genetic diversity, as expected, for native populations in the vicinity of a domestication center. With the exception of NAJ, the surveyed populations had higher expected than observed heterozygosities. This resulted in positive KZ Table , indicatGST = 5.9% (based on 13 markers) indicated that within-breed diversity accounts for a large part of the total genetic diversity of the breeds investigated. This observation is confirmed by AMOVA and by the low average pairwise FST value  and Swi; Table .). The te; Table .. However; Table . and BM18; Table ..K ranging from 2 to the most probable value (K = 5). At this value of K, Iranian breeds from the north (TAL and KHL), center  and west and south-west (MKZ and NAJ) form three clusters. The level of admixture is high in breeds from central Iran. It is lower in northern breeds that appear to contain almost identical proportions of ancestral genomes, confirming their high similarity as indicated by genetic parameters in the NJ tree and PCA. The two Pakistani populations constitute two distinct separate gene pools, although they originate from the same area (Punjab province) in Pakistan. Gene flow between these two breeds (Nm = 3.62) confirms STRUCTURE, NJ and PCA analyses and indicates that PAH and TED are distinct, even if some animals from TED seem to have a large portion of their genome in common with PAH. Overall, NAJ and MKZ, although they share a common ancestry at K = 5  of Iran Figure . It is aFST = 0.02, unpublished data). This may be due to the massive amount of gene flow occurring in sheep by translocation of superior breeds over a large geographical distance, because of the higher economic importance of sheep compared to goats. Overall, the degree of differentiation at the few microsatellite marker loci used in this study might appear inadequate to represent the degree of differentiation among breeds that is perceived based on physical appearance and other phenotypic traits. However, “neutral” markers such as microsatellites are designed to reconstruct the evolutionary and demographic history of populations and are theoretically “blind” to the effect of natural and anthropogenic selection that is sometimes very effective and rapid in changing morphological and production traits [QST) typically exceeds that observed in neutral marker genes (FST) [The level of population differentiation and genetic structure observed in Iranian goat breeds are clearly different from that observed in Iranian sheep populations (n traits . It has es (FST) , suggestTaken together, all the approaches used to analyze genetic relationship among individuals and populations in this study suggested a high molecular diversity in Iranian goats, with varying levels of genetic distinctiveness among breeds and considerable gene flow between breeds from the same geographic region. Between-breed diversity has a strong geographic component. Iranian goat breeds fall into three clusters, northern, central and western, with the western and southwestern breeds relatively distinct from others. Pakistani breeds show some relationships with Iranian populations, even if their position is not consistent across analyses. Pakistan and Iran are neighbors, connected by the Baluchistan region that is shared by the two countries. There is a long history of contact and mutual influence between the two countries. Agribusiness and livestock exchange have been ongoing for ages, so it is not surprising to find some similarity in the genetic background of Iranian and Pakistani goat breeds.per se. One suggested first step is to organize breeders into formal or informal associations, to facilitate development and implementation of genetic resource management strategies. Inbreeding seems to affect some breeds and an organization of breeders may allow for wider exchange of males within breeds, which would address this problem. Conversely, if the breeders express an interest in maintaining genetic purity, gene flow among breeds and regions should be monitored and avoided. Development of more complex strategies would benefit from the analysis of native breeds with high-density marker panels that can distinguish between neutral and selected genomic regions. This additional information would contribute to the decision making process, in particular by identifying patterns of diversity along genomes of neutral (present day) and selected (very near future) genomic regions. Three out of the seven investigated breeds are reared in geographic areas in which mtDNA provided evidence of early domestication. TUR and ABD  and NAI  fall exactly in the area in which the C haplogroup is observed at high frequency [In conclusion, to maintain the present genetic diversity and structure of these breeds, proper strategies of marker-assisted management need to be designed and implemented. Although a decreasing number of MKZ individuals has been noted, none of these breeds seem to be endangered according to the FAO risk classification system . Thereforequency . InteresThe authors declare that they have no competing interests.All authors contributed in designing the experiment, developing methods and drafting the manuscript. All authors read and approved the final manuscript.Characteristics of 14 microsatellite markers used to study nine Iranian and Pakistani goat breeds. The data provided represent the characteristics of the microsatellite markers used to study seven Iranian and two Pakistani goat breeds. Na indicates the number of alleles at each locus, Ne is the number of effective alleles, PIC is the Polymorphic Information Content calculated by Cervus 3.0.3 software, HE the genetic diversity per locus per population, *P < 0.05, *P < 0.01, ***P < 0.001, NS=not significant.Click here for fileEstimated null allele frequencies using the EM algorithm (r). The data provided represent the estimation of null allele frequencies using the Expectation Maximization (EM) algorithm for each locus and breed. r ≥ 0.2 is bolded.Click here for fileWright’s F-statistics for each of the 13 microsatellite loci across nine breeds. The file contains the estimated F-statistics per locus and overall values, across nine goat breeds. ***P < 0.001, the values in parentheses are the standard errors.Click here for fileDS and DA genetic distances between nine goat breeds based on 13 microsatellite markers. The data provided represent the DS and DA genetic distances between the breeds analyzed, based on 13 loci. Standard genetic distances (DS)  and Nei’s genetic distances (DA) .Click here for fileThe calculated measurements using Evanno method to find the best K based on Structure output. The Evanno table output was based on 13 microsatellite loci used in the evaluation of the nine goat breeds.Click here for fileRepresentation of the number of ideal clusters identified by Structure software. The delta K method  was exaClick here for fileThe actual and effective number of alleles of 14 microsatellite loci in nine goat breeds. The file contains the calculated actual and effective number of alleles per locus for each breed. N = actual number of alleles; Ne = effective number of alleles.Click here for fileHE, FST and confidence intervals obtained by LOSITAN. The file contains the fixation index and expected heterozygosity estimated for each locus to identify loci under selection using LOSITAN software.Click here for file


Pinctada margaritifera, where comprehensive fishery management is lacking, and the sustainability of exploitation uncertain. Weak fine-scale patterns of population structure were detected, indicative of broad-scale panmixia among wild oysters, while a hatchery-sourced farmed population exhibited a higher degree of genetic divergence (Fst = 0.0850–0.102). This hatchery-produced population had also experienced a bottleneck ; compared to infinite NeLD estimates for all wild oysters. Simulation of larval transport pathways confirmed the existence of broad-scale mixture by surface ocean currents, correlating well with fine-scale patterns of population structuring. Fst outlier tests failed to detect large numbers of loci supportive of selection, with 2–5 directional outlier SNPs identified (average Fst = 0.116). The lack of biologically significant population genetic structure, absence of evidence for local adaptation and larval dispersal simulation, all indicate the existence of a single genetic stock of P. margaritifera in the Fiji Islands. This approach using independent genomic and oceanographic tools has allowed fundamental insights into stock structure in this species, with transferability to other highly-dispersive marine taxa for their conservation and management.Fishery management and conservation of marine species increasingly relies on genetic data to delineate biologically relevant stock boundaries. Unfortunately for high gene flow species which may display low, but statistically significant population structure, there is no clear consensus on the level of differentiation required to resolve distinct stocks. The use of fine-scale neutral and adaptive variation, considered together with environmental data can offer additional insights to this problem. Genome-wide genetic data , together with an independent hydrodynamic particle dispersal model were used to inform farm and fishery management in the Fijian black-lip pearl oyster  Sustainable management and conservation of marine species is faced with a number of challenges, among which is the wide distribution of taxa across diverse habitats and geopolitical jurisdictions, that make species-specific management plans difficult to design and implement. Many taxa also face high rates of exploitation, that in some cases has led to the collapse or abnormally slow recovery of wild fisheries, bringing into question whether current management strategies are effective or appropriate –3. The nFor assessment of a particular stock, it is important to determine the number and extent of populations being examined. However, the biological concept of a population has either ecological , or evolutionary (genetic structuring) aspects ,5. ReissA major problem posed for application of the stock concept in the marine environment is the relative absence of barriers to dispersal and migration compared to terrestrial systems, and the highly-dispersive larval stages of many species . For speFor a large number of species that exhibit high levels of gene flow, low levels of genetic structure may be present, but difficult to detect ,3. The iA potential solution in recent years has been the use of genome-wide SNPs, which can reveal fine-scale patterns of population structure to highlight differences between populations, and also detect signatures of selection –17; withBivalve molluscs present a number of unique challenges for stock assessment, which include highly variable patterns of larval dispersal and recruitment. Additionally, traditional bivalve stock assessment surveys typically require extensive sampling to determine distribution and abundance, which in most situations can be costly and impractical. Because the adults of many taxa are sedentary and recruitment rates highly variable, a stock may occupy a discrete geographic region as large as an entire reef system, or as small as a single bivalve bed . When coPinctada margaritifera (Pteriidae) displays substantial genetic fragmentation, despite being a broadcast-spawner with an extended PLD of 26–30 days Particle seed location colour codes are identical to those described in (GIF)Click here for additional data file.S1 Table(DOCX)Click here for additional data file.S2 TableP. margaritifera, with 4,123 SNP loci using ML-RELATE [Values are provided for relationships between individuals within eleven Fijian populations of L-RELATE (DOCX)Click here for additional data file.S3 TableP. margaritifera with 4,123 SNP loci using ML-RELATE [Estimates are provided between geographic regions sampled from eleven Fijian populations of L-RELATE . All oth(DOCX)Click here for additional data file.S4 TableP. margaritifera from 11 Fijian populations. Significantly different values at p<0.000001 following 10,000 permutations are indicated with an asterisk.Estimates were computed using Arlequin  (Weir an(DOCX)Click here for additional data file.


B. attenuata may tolerate further changes in rainfall and temperature through evolutionary adaptations based on their adaptive genetic variation. However, the capacity to survive future climate change may be compromised by changes in the fire regime.Substantial climate changes are evident across Australia, with declining rainfall and rising temperature in conjunction with frequent fires. Considerable species loss and range contractions have been predicted; however, our understanding of how genetic variation may promote adaptation in response to climate change remains uncertain. Here we characterized candidate genes associated with rainfall gradients, temperatures, and fire intervals through environmental association analysis. We found that overall population adaptive genetic variation was significantly affected by shortened fire intervals, whereas declining rainfall and rising temperature did not have a detectable influence. Candidate SNPs associated with rainfall and high temperature were diverse, whereas SNPs associated with specific fire intervals were mainly fixed in one allele. Gene annotation further revealed four genes with functions in stress tolerance, the regulation of stomatal opening and closure, energy use, and morphogenesis with adaptation to climate and fire intervals.  Mediterranean type ecosystems (MTE’s) are among the most biologically diverse terrestrial ecosystems globally and are thought to be highly vulnerable to species loss under global change12et al. identify South-Western Australia (SWA) and the Cape Region of South Africa as two of the most vulnerable MTE regions globally, potentially losing more than 2000 plant species each over the next 100 years in the face of climate changeet al. estimated that up to 25% of Banksia species (Proteaceae) were projected to become extinct by 2080et al. simulated the impacts of climate-change scenarios on Banksia species distributions and reported an increased risk of decline for all speciesMalcolm in situ to new climatic conditions based on genetic variation within populations and plasticity, e.g., most species can persist outside their natural range1215. We therefore need to know the level of adaptive genetic variation in extant populations and the variation associated with adaptation to components of climate and other environmental conditions.However, the validity of these sobering extinction predictions is uncertain as critical gaps remain in our knowledge of the intrinsic capacity of species to respond to climate and other environmental changes. For instance, species may be able to adapt SWA is also one of the most fire-prone regions in the world20in situ through tolerating and/or adapting to the changes, or by migrating to suitable habitats if possible. Recent research has shown that many Australian plant species have the capacity to disperse their seeds over long distances, especially after fire25262731Plants may respond to climate and environmental changes either by persisting Investigating adaptive genetic variation may reveal the role of genetic diversity in buffering species and communities against the effects of changing climate3435123940The rapidly falling costs of next-generation sequencing are now enabling the genome-wide characterization of adaptive genetic variation, which offers unprecedented power to identify the loci that mediate local adaptation40Banksia attenuata (Proteaceae) is one of the most prominent and widespread woody plants in SWA. It occurs in semi-arid shrubland to mesic forest and is highly resilient to fire, recovering by resprouting from its trunk or base. Here, we utilize RAD-seq to screen large numbers of SNPs and characterize adaptive genetic diversity in B. attenuata populations spanning a broad range of precipitation, temperature, and fire regimes  in SWA. Our approach detects SNPs that show concordant differences in allele frequencies across populations with respect to specific local climates and fire regimes. We screened those genetic variations that are putatively associated with genes under directional selection and then used environmental association analysis to identify putative genes associated with adaptation to specific precipitation levels, temperatures, and fire intervals. Finally, we annotated those genes for their potential biological function. Our study attempts to answer the critical question of whether those alleles that confer adaptation to local climate factors and fire regime occur globally with varying frequencies or whether they are highly localized in specific populations. Our research quantifies genetic variations associated with adaptation to climate and fire regimes, identifies geographic regions that are predicted to be most sensitive to the disruption of current patterns of local adaptation under climate change, and provides critical insight into the evolutionary potential of further climate change for an iconic species in SWA.B. attenuata sampled across the nine locations. One sample with 2.1 million reads was discarded due to its low coverage. The average quality score (Q20) was 99.4%, with the lowest being 99.1%, suggesting very high quality for the obtained sequences. The final RAD reference genomes generated from the RAD sequences of twenty individuals using de novo assembly contained 241,259 contigs, with N50 = 264 and a total length of 63.6 million base pairs. The RAD reference genome had GC contents of 38.0%.RAD-seq sequencing coverage averaged 16.0 million reads and 1.53 GB of data per individual for each of the 80 individuals of P = 0.01, the Fst-outlier approach using a hierarchical population model and coalescent simulations identified 560 SNPs (9.8%) putatively under directional selection  in each population was largely determined by the change in fire interval  and not by change in local climate   have much more frequent contemporary fires compared with historical fires, whereas fire intervals in the other four populations have not changed significantly.Adaptive genetic diversity, as measured by the 560 SNPs putatively under directional selection, showed considerable differences among populations. PPL varied from 28% in the population at FR to 81% at GM, with an average of 59%, and expected heterozygosity ged 0.21 . Populat0.21 (He . Multiplerature) . The fivst values ranged from 0.003 to 0.342 and averaged 0.113. Populations are significantly differentiated, with all pairwise Fst values statistically greater than zero. SNPs putatively under directional selection revealed much greater genetic differentiation among populations, with pairwise Fst values ranging from 0.086 to 0.809 and averaging 0.438. For both measures, the geographic distance between populations has contributed to genetic differentiation, with differentiation increasing with increasing geographic distance between populations  as measured by 560 SNPs putatively under directional selection than those of populations from the northern part of the species’ geographic range. Principal components analysis suggests that the change in fire interval was the main driver of decline of adaptive genetic variation in B. attenuata populations. Recurrent fire has been a major evolutionary force in the evolution of terrestrial plants for at least 100 million years1747per se but, rather, to specific fire regimes that include fire frequency, fire intensity, and patterns of fuel consumptionBanksia attenuata populations in SWA, where fire occurrence has increased as a result of human influence, but not in others where historical fire regimes remain largely intact.Our results suggest that altered fire regime, and particularly shortened fire intervals in some parts of SWA, has had a significant impact on the level of adaptive genetic variation in populations of the widespread and abundant et al. reported a mean fire interval of approximately 80 years for tree-scarring fires in jarrah  forests of SWA in the pre-European periodMultiple lines of evidence support the idea of dramatic changes in fire interval in the southern forests of SWA. Burrows Acacia, Banksia, Casuarina, Eucalyptus, Grevillea, Melaleuca and Xylomelum angustifolium) has changed little since 2.9 Ma in Yallalie, SWA, a location close to the populations at Eneabba (Beekeepers Nature Reserve and South Eneabba Nature Reserve) used in our study. The mid-Pliocene fire interval at Yallalie was proposed to be slightly longer than 10 yearsPalynological evidence suggests that the Proteaceae-Myrtaceae “Kwongan” scrub vegetation . This contemporary evolutionary response to frequent fire has reduced variability at the selected loci. Such selective sweeps may reduce the population’s ability to respond genetically to future fluctuations in fire regime, leading to unpredictable effects on the species’ presence and abundance at the level of the plant community. Given the current very low level of adaptive genetic variation in populations in southern SWA, the capacity to survive more frequent fires is highly uncertain.Genome-wide analysis of adaptive genetic variation in Banksia attenuata across its range. Most of the candidate genes (~80%) associated with rainfall and high temperature have multiple alleles, and the results of our principal components analysis suggest that recent changes in rainfall and temperature have had little impact so far on within-population adaptive genetic variation. These results are perhaps not surprising because inter-annual fluctuations in rainfall and temperature are normal occurrences and different genotypes of a species may be favored in different years. Inter-annual environmental fluctuations may be one driver by which functional genetic variation is maintained in natural populationsB. attenuata range from semi-arid with an annual rainfall of 360 mm to the high rainfall zone with over 1000 mm annually, supporting the interpretation that species spanning wide climate range may have greater intrinsic adaptability due to high adaptive genetic variation. In Arabidopsis thaliana, Lee & Mitchell-Olds similarly demonstrated that environmental adaptation contributes to gene polymorphism across the genomeB. attenuata, its capacity to adapt to changes in climate  may be large.Rapid environmental changes have long been recognized as powerful driving forces for positive directional selectionB. attenuata. Although there is considerable overlap of the SNPs associated with the mean temperature of the hottest month, with 14 SNPs (out of 45) associated with at least two of these climate factors, of the 25 SNPs associated with annual rainfall, only one was associated with temperature. Such weak genetic correlations may allow traits to respond to selection independentlyThe impacts of declining rainfall on plant species may be greater in combination with increasing temperatures, prompting the hypothesis that genes that confer fitness under drought stress may overlap with those associated with tolerance to high temperatures. However, our results show that the opposite is true for Banksia species in woodlands near Perth, SWA. Extensive deaths of mature individuals, including B. attenuata, have been recorded since the 1970sBanksia species have become locally extinct during the more than 40 years of continuous decline in the water table. Furthermore, new individuals that became established under the changed ecohydrological state of lower groundwater availability have been less stressed by drought compared with their parent populationsEucalyptus, experimental trials indicate that climatic tolerances of the species may be greater than suggested by their natural distributionset al. showed that Eucalyptus regnans was able to grow well at trial sites where the annual mean temperature was 5 °C warmer than the hottest location in its natural distributionB. attenuata to tolerate further changes in rainfall and temperature.Over the last four decades, an unplanned experiment has shown the impact that increasing temperatures, declining rainfall and retreating groundwater levels may have had on B. attenuata, four candidate genes have clear implications for molecular functions in the adaptation to stress as revealed by experimental studies in many other plants. The malate dehydrogenase (MDH) gene was identified as closely related to rainfall variation and high temperature in our study. Previous studies have shown that MDH is sensitive to abiotic stresses and that the expression of MDH is positively correlated with the growth vigor of plants and cells under stress61B. attenuata populations confers a substantial capacity for the species to adapt to a broad spectrum of rainfall and high temperatures, including adaptation to dry and hot environments such as in the northern sandplain of SWA. The sphingosine 1-phosphate phosphatase (S1P) gene has been identified as specifically linked to adaptation to rainfall variation in B. attenuata. The S1P gene has important functions in controlling stomatal opening and closure632 uptake, photosynthesis, and transpirational cooling as well as on water and nutrient uptake. The ability to close the stomata during unfavorable conditions  represents an important intrinsic adaptation to repeated drought in B. attenuata.Among the candidate genes that have been identified with close associations to both climate  and fire intervals in B. attenuata. High temperatures promote stomatal closure, which leads to decreased CO2 uptake and subsequently lowers net photosynthesis. AMPK is a sensor of energy status and switches on catabolic pathways that generate ATP, which maintains cell survival during energy starvationB. attenuata.High temperature causes a negative carbon balance, which increases the risk of carbon starvationet al. investigated the genetic basis of climatic adaptation in loblolly pine (Pinus taeda) by evaluating the associations between environmental clines and allelic variation using genome-wide markers; they revealed five loci that were significantly associated with aridity gradientsArabidopsis  genes that confer stress tolerance. Our genome-wide scans identified candidate genes that are related to stress tolerance, the regulation of stomatal closure, energy use, and morphogenesis in the adaptation to climate and fire regime in B. attenuata. Further research points to experimentally investigating and validating the functional and physiological pathways of these candidate genes.Eckert de novo from RAD sequences was only 65 MB, equivalent to approximately one-tenth of the whole genome (assuming a genome size of 650–850 MB for Banksia). The resulting 5701 SNPs scattered across the genome may be sufficient for providing an overall evaluation of the level of adaptive genetic variation within populations of B. attenuata but may not be sufficient to cover all the genes that confer adaptive fitness to climate and fire regime. Furthermore, to facilitate the comparison of the genetic variation among populations and across the range of B. attenuata, only those SNPs that were present in all sampled individuals and populations were investigated, which may omit population- or individual-specific genetic variations. Indeed, over 61,000 SNPs  were discovered in individual samples, as estimated from the raw RAD sequences. Future advances in analytic methodology may make full use of all the data generated from high-throughput sequencing. Finally, many of the candidate genes in this study are still not well characterized at the functional or transcriptional level. Indeed, among the 18 candidate genes identified by aligning to the Banksia hookeriana leaf transcriptome, only the function for four genes can be connected to adaptation to local climate and fire regime. Future research on a fully annotated Banksia genome is anticipated to provide a critical platform for the ecology, evolution and adaptation of this iconic genus.The present effort of searching candidate genes involved in the adaptation to climate and fire regimes in SWA must be considered as preliminary, and the list of candidate genes is far from complete. Although our RAD-seq approach has generated data equivalent to a 2–3× coverage of the genome, the reference genome obtained B. attenuata, and most likely other species with a similar life history and distribution, may be able to tolerate further changes in rainfall and temperature based on adaptive genetic variation within populations. This is corroborated with the results from studies of the impacts of declining water availability on banksias58in situ for almost 3 million yearsGenetic variability has the capacity to buffer species against specific environmental changes. Our study was to detect a high level of adaptive genetic variation and candidate genes with a clear ecological function associated with adaptation to local climate and fire regimes in natural plant populations. Our results suggest that B. attenuata populations in southern SWA. Frequent fires have been driving changes in gene frequency within natural plant populations and have led to selective sweep. Given the current very low level of adaptive genetic variation in those populations of southern SWA, the capacity to survive more frequent fires and further environmental fluctuations in their habitat is substantially reduced. Even if adaptive genetic variations exist in B. attenuata populations and an evolutionary response to further climatic changes can occur, this may not be sufficient to ensure the survival of the population. The projected decline in rainfall in SWA, in conjunction with the continuing rise of summer temperature, may result in longer fire seasons and increased fire likelihood, thus further shortening fire intervalsOur results reveal that shortened fire intervals, predominantly a consequence of recent human activities, imposed the strongest selection pressure on B. attenuata was not representative of adaptive genetic variation, particularly in those populations experiencing shortened fire intervals in the southern part of SWA. Our results highlight the long-held concerns regarding the use of neutral genetic variation as a surrogate for adaptive genetic variation.Finally, despite the presence of positive correlations in heterozygosity as measured by neutral SNPs and by SNPs putatively under directional selection, the pattern of neutral genetic variation in populations of Banksia attenuata (Proteaceae) is a member of the iconic Australian genus Banksia, an important element of the flora, with over 180 species in SWA. This species forms an important component of open Eucalyptus and Banksia woodlands and shrublands as a dominant or understory tree or tall shrub. The distribution of B. attenuata spans a wide climate and environmental range, and it is the most widely distributed of all western banksias. B. attenuata is found across much of SWA west of the 400 mm isohyet, with a few populations penetrating slightly east into areas with less than 400 mm annual rainfall, through to the west coast of WA, north to Kalbarri National Park , south to Cape Leeuwin  and across to the Fitzgerald River region (BanksiaB. attenuata are estimated to live for 300 years or morer region . This spBanksia attenuata were randomly sampled from each of nine locations across its range in SWA (www.bom.gov.au). Long-term weather observations (since the 1930s) show a marked decline (15–30% reduction) in annual rainfall since 1975 in seven of the nine locations . EcoRI is a frequent cutter, resulting in the detection of more markers in RAD sequencing. For library construction, two 100 bp single-end sequencing libraries were constructed using the eight-nucleotide multiplex identifiers. Each library contained five individual samples. Each sample was assigned to a unique MID barcode. The RAD products from the 80 plants were processed on an Illumina HiSeq2000 platform  at Beijing Genomics Institute . Sequencing data were segregated by individual specific MID. Reads from each plant were clustered into tag reads by sequence similarity . To ensure quality, the raw data were modified by the following two steps: first, the adapter pollutions and index sequence in the reads were deleted, and then the reads which contained more than 50% low-quality bases  were discarded.Genomic DNA from each individual was extracted and then fragmented by the corresponding enzyme  shared 100% sequence identity across the Illumina reads. The RAD sequence cluster was set at a range of 50–750× to maximize the efficient assembly of sequences. The paired-end sequences corresponding to the selected SE were extracted for further assembly. The selected pair-end reads were input into the Velvet sequence assembler, and k-mer 40 was used for B. attenuata contig assemblyBecause there is no reference genome available for banksias or closely related taxa, a The final filtered RAD reference genome assemblies should thus represent single-copy genomic sequences. Reads for each individual were then aligned to the RAD reference using BOWTIE74B. attenuata. A locus under balancing selection should show uniform allele frequencies across populations, whereas loci under local directional selection should show large differences among populations. We used the Fst-outlier approach to detect SNP loci that are putatively under selection, and these markers were expected to reveal a signal of adaptive variation related to local climate and environment77st-outlier identification followed the approach of hierarchy modeling and coalescent simulation79st values could be considered as Fst outliers conditioned on the globally observed Fst value. The populations in our samples were separated by large geographic distances and could be considered as independent units, which minimizes false positives in hierarchy modeling and coalescent simulationP = 0.01, we categorized SNPs into three groups: SNPs under directional selection, those under balanced selection, and neutral SNPs. For each subset of SNPs, population genetic variation  and pairwise population differentiation (Fst) were estimated in Arlequin v3.5st, as estimated from SNPs that were detected under directional selection, Fst estimated from those SNPs other than under directional selection, and geographical distance (transformed using the logarithm function).To assess the presence and extent of adaptive genetic variation in populations, we began by asking how many SNP loci have diverged under selection in To investigate whether climate change  since ~1970 and changes in fire interval have impacted the level of adaptive genetic diversity in each population, we used multiple linear regression with adaptive genetic diversity  as dependent variable, and change in climate  and fire interval as independent variables.. Climate change was quantified as [Mean (post-1975) − Mean (pre-1975)]/[Mean (post-1975) + Mean (pre-1975)]. Change in fire interval was based on the historical versus contemporary intervals  and usedB. attenuata is a long-lived plant with a long generation time . We employed a Bayesian method that estimates the empirical pattern of covariance in allele frequencies between populations from a set of markers and then uses this as a null model for a test of individual SNPsBayenv (http://gcbias.org/bayenv/). Only one SNP locus from the same contig was used for environmental association.The subset of SNPs putatively under directional selection was further used to detect specific candidate genes associated with adaptation to annual precipitation, temperature , solar exposure, and historical fire intervals using environmental associations82de novo assembled contigs of B. attenuata were used for BLASTN searches and annotation against an annotated B. hookeriana transcriptome assembly (obtained from http://www.ncbi.nlm.nih.gov) using an E-value cut-off of 10−10 B. hookeriana-annotated transcripts’ information  was applied to B. attenuata contigs if they were matched against each other.We further investigated the current functional annotation and classification of the candidate genes for local adaptation as revealed in the above environmental associations. The How to cite this article: He, T. et al. Evolutionary potential and adaptation of Banksia attenuata (Proteaceae) to climate and fire regime in southwestern Australia, a global biodiversity hotspot. Sci. Rep.6, 26315; doi: 10.1038/srep26315 (2016).


C. capsularis L) and dark jute (C. olitorius L), is second to cotton in its commercial significance in the world. Here, we assessed the genetic structure and relationship in a panel of 159 jute accessions from 11 countries and regions using 63 SSRs. The structure analysis divided the 159 jute accessions from white and dark jute into Co and Cc group, further into Co1, Co2, Cc1 and Cc2 subgroups. Out of Cc1 subgroup, 81 accessions were from China and the remaining 10 accessions were from India (2), Japan (5), Thailand, Vietnam (2) and Pakistan (1). Out of Cc2 subgroup, 35 accessions were from China, and the remaining 3 accessions were from India, Pakistan and Thailand respectively. It can be inferred that the genetic background of these jute accessions was not always correlative with their geographical regions. Similar results were found in Co1 and Co2 subgroups. Analysis of molecular variance revealed 81% molecular variation between groups but it was low (19%) within subgroups, which further confirmed the genetic differentiation between the two groups. The genetic relationship analysis showed that the most diverse genotypes were Maliyeshengchangguo and Changguozhongyueyin in dark jute, BZ-2-2, Aidianyehuangma, Yangjuchiyuanguo, Zijinhuangma and Jute 179 in white jute, which could be used as the potential parents in breeding programs for jute improvement. These results would be very useful for association studies and breeding in jute.Population structure and relationship analysis is of great importance in the germplasm utilization and association mapping. Jute, comprised of white jute ( Corchorus genus in the Tiliaceae family and is second to cotton in its commercial importance in the world. It is mainly distributed in China, India, Bangladesh and east-central Africa, where it has been grown for several thousand years for natural fiber production ..Corchoru2n = 14) . For exaCurrently, some studies on genetic diversity in jute have been carried out with morphological traits . But thihttp://www.jute.org/statistics_07.htm). And South China is said to be one of the origin centers of white jute [Although there were some genetic diversity studies carried out with SSR markers to assess the genetic variation in jute –9, 11–12In the present study, we genotyped a panel of 159 jute accessions from 11 countries and regions, out of which originated from Chinese locations account for 81%, using 63 highly polymorphic SSR primers. The objectives of this research were to investigate the population structure and assess the genetic relationship among these jute germplasms.C. capsularis) and 30 accessions were dark jute (C. olitorius). These accessions, which included 129 accessions from China, 26 accessions from Bangladesh, India, Japan, Thailand, Vietnam and Pakistan, 3 accessions from Africa, and 1 accession from America, were selected on the basis of diverse geographical location for population structure analysis  and the number of alleles were estimated by PowerMarker 3.51 . AnalysiGenetic similarity coefficient (GSC) comparing all pairs of the 159 jute accessions was calculated using unweighted pair group method of arithmetic means (UPGMA) by NTsys .Dk appeared at k = 2  was conducted for partitioning the molecular variation at the group and subgroup levels . The anaTo uncover the genetic difference of diverse genotypes, the GSC analysis among all pairs of the 159 jute accessions was conducted on the basis of structure analysis . On the Out of Co group, the GSC ranged from 0.523 to 0.901, with the average of 0.750 . The paiOut of Cc group, the GSC ranged from 0.511 to 0.932, with the average of 0.711 . Among tSince SSRs can be easily detected by PCR, SSRs have been widely used in the analysis of population structure and genetic diversity in jute , 8, 9. IThe genetic diversity parameters for each group suggested that there is relatively much genetic differentiation between the two groups (Cc and Co). This was confirmed by AMOVA, where low level of estimated variation 21%) observed within subgroups compared to four fold 79%) higher variation within groups . It also% higher % observeAs is known, parental accessions of obvious genetic background difference usually generates an elite variety in the cross-breeding program. Thus, understanding of genetic relationship is critically important for crop improvement , 21. TheS1 Figa) the total panel; b) the Co group; c) the Cc group.(TIF)Click here for additional data file.S1 Table(XLS)Click here for additional data file.S2 Table(XLS)Click here for additional data file.S3 Table(XLS)Click here for additional data file.S4 Table(XLS)Click here for additional data file.


Avicennia germinans, Avicenniaceae) and the red  mangroves have similar geographic ranges but are very distantly related and show striking differences on their life-history traits. We sampled 18 Atlantic and 26 Pacific locations for A. germinans (N = 292) and R. mangle (N = 422). We performed coalescence simulations using microsatellite diversity to test for evidence of population change associated with quaternary climate fluctuations. In addition, we examined whether patterns of genetic variation were consistent with the directions of major marine  currents in the region. Our demographic analysis was grounded within a phylogeographic framework provided by the sequence analysis of two chloroplasts and one flanking microsatellite region in a subsample of individuals. The two mangrove species shared similar biogeographic histories including: (1) strong genetic breaks between Atlantic and Pacific ocean basins associated with the final closure of the Central American Isthmus (CAI), (2) evidence for simultaneous population declines between the mid-Pleistocene and early Holocene, (3) asymmetric historical migration with higher gene flow from the Atlantic to the Pacific oceans following the direction of the palaeomarine current, and (4) contemporary gene flow between West Africa and South America following the major Atlantic Ocean currents. Despite the remarkable differences in life-history traits of mangrove species, which should have had a strong influence on seed dispersal capability and, thus, population connectivity, we found that vicariant events, climate fluctuations and marine currents have shaped the distribution of genetic diversity in strikingly similar ways.Comparative phylogeography offers a unique opportunity to understand the interplay between past environmental events and life-history traits on diversification of unrelated but co-distributed species. Here, we examined the effects of the quaternary climate fluctuations and palaeomarine currents and present-day marine currents on the extant patterns of genetic diversity in the two most conspicuous mangrove species of the Neotropics. The black ( Mangrove forests are communities of trees and woody shrubs localized in intertidal zones of tropical and subtropical river deltas, lagoons, and estuarine coastal systems worldwide. These forests are composed of phylogenetically unrelated species, each of which has adapted to live at transition zones between land and sea. The main adaptations include tolerance to anoxic, saline and unstable soils, and aquatic seed dispersal  (Tomlinson Avicennia germinans (Avicenniaceae), and the red mangrove, Rhizophora mangle (Rhizophoraceae). Although their ranges are largely overlapping, the two species differ markedly in major life-history characteristics including seed viability in salt water (3 months vs. 1 year), pollination syndrome (ambophilous vs. entomophilous), and seed shape (round vs. oblong), which may have an important effect on population connectivity . If correct, then these historical contractions should leave a strong imprint on the distribution of genetic variation among populations of the two species that we can test with molecular data.The comparison of phylogeographic patterns across nonrelated species that occupy similar ecological niches offers an exceptional opportunity to explore this interplay between historical and contemporary forces in shaping ecological communities  Is there genetic evidence of simultaneous population declines associated with quaternary climate changes? (2) Does the distribution of genetic variation follow the direction of palaeomarine currents or reflect contemporary marine currents? and (3) Does the current population genetic structure at large spatial scales reflect differences in the amount of time seeds remain viable in salt water?A. germinans from 12 sites in the Atlantic Ocean (N = 208) and five in the Pacific Ocean (N = 84), and 422 individuals of R. mangle from 17 sites in the Atlantic Ocean (N = 269) and nine in the Pacific Ocean (N = 153)  see . Genomic153) see , have noA. germinans  and six microsatellite loci in R. mangle  followed previously described protocols , expected heterozygosity (He), and the fixation index (FIS) for each species using GenAlEx 6.0  replicates after a burn-in of 50,000 replicates using a model of correlated allele frequencies and without information of sampling locations. Analyses were performed over all sampling locations  and within each ocean basin . The best K and the ΔK  and historical migration rates (M). To obtain an unscaled Ne, we used mutation rates ranging from 10−2 to 10−3, as assumed for microsatellite loci in plants  obtained, we tested different models of gene flow within and between the Atlantic and Pacific oceans, using a Bayes factor approach  and ancestral (N1) effective population size, μ (mutation rate), and Xa , where Xa = g  × Ta (number of generations since expansion/decline). A hierarchical model , a strict stepwise mutation model, and an exponential change in size of populations were used for the analyses  and haplotype diversity using DnaSP v4.10.3 .For a subset of individuals, we also analyzed DNA sequence variation at two chloroplast (cpDNA) noncoding loci, Ho = 0.40 ± 0.02 SE and HE 0.42 ± 0.02 SE for A. germinans and Ho = 0.36 ± 0.02 SE and HE = 0.38 ± 0.03 SE for R. mangle. There was no compelling evidence of genotyping errors. However, certain loci in some locations showed strong evidence of null alleles with frequencies that ranged from 0.11 to 0.79 in A. germinans and from 0.07 to 0.71 in R. mangle , was associated with the CAI barrier  (RST = ρRST), with some exceptions  . GeneticStructure analyses showed a highest posterior likelihood of K = 2 for both species. The two inferred clusters clearly corresponded with the Atlantic and the Pacific ocean basins, highlighting the importance of the CAI as a barrier to gene flow for the mangrove species  .Most individuals were assigned to their respective clusters with a high average proportion of membership (Q), ranging from 88% to 90% for 6%) Fig. A. Both sA. germinans and 3.98 to 7.08 for R. mangle   in Θ and Ne among the two mangrove species. However, two A. germinans clusters localized on the Atlantic coast of Central America and northern South America (HO-PG-CC) and in the Antilles islands (PR-GU) showed higher Θ and Ne values compared with all four R. mangle clusters  ranged from 4.18 to 17.05 for BayesAss within each ocean were in general low . However, in the sites surrounding the Antilles Islands within Caribbean, we found asymmetrical patterns of migration with values of M > 0.1 in both species that were congruent with the direction of marine currents  was favored over the rest of the models tested Table . The currents FigB and 3B. Kessler   are on average two hundred times smaller than ancestral effective population sizes (N1)  were placed from 5000 to 30,200 years (at g = 10), from 17,300 to 120,200 years (at g = 40), and from 38,000 to 297,000 years (at g = 100) across all clusters of both species. Although some A. germinans clusters in the Caribbean Sea  showed older Xa values, all 95% HPD estimates within and between the two species indicated that population declines of A. germinans and R. mangle occurred during the mid-Pleistocene to early Holocene  Fig. B. The mes at g = 0, and frA. germinans, the two distinctive haplogroups were separated by two and six substitutions in the cpDNA and FMR genomes, respectively. In addition, within the Atlantic Ocean, the nuclear FMR shared haplotypes  between West Africa and Central and South America suggesting trans-Atlantic gene flow   and South America (French Guiana) were found   Fig. C. SimilaH6) Fig. D. Both gMR) Fig. C,D. HaplA. germinans and R. mangle, their extant genetic diversity has been similarly shaped by a combination of major geological events, quaternary climate fluctuations, and the contemporary and palaeomarine currents. Our data reaffirm the strong effect of the Central American Isthmus (CAI) closure on the diversification history of neotropical mangroves  and 40 Ma (Eocene) respectively, the current genetic diversity within both species is a legacy of the quaternary fluctuations in population size and range   and R. mangle (c.a. 360 days)   rates from Guadeloupe toward Puerto Rico in both species following the direction of the Antilles current  was evident in neighboring localities within Panama and between Panama and Costa Rica of both species. This pattern is consistent with short-distance currents, seasonal changes, and permanent eddies that characterize ocean circulation patterns in the east tropical Pacific. In October–December, main currents between northern Colombia, Panama, and Costa Rica follow a highly dynamic northwesterly direction. In comparison, in January–March, the dynamic of these currents decreases and although the main northwesterly direction is maintained, there are also opposing currents moving in the eastward direction  and pollination syndrome (ambophilous for R. mangle and entomophilous for A. germinans) that characterize the two species  was higher than all four R. mangle clusters  in neotropical regions will experience (1) a pole-ward shift under future climate scenarios, especially on North America a Alongi . This al