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Inference about genetic demographic and population management of albacore tuna (Thunnus alalunga)
Abstract
Albacore tuna (Thunnus alalunga) is an important portion for tuna fishing in all oceans. Over the past decade, commercial catches of albacore tuna have accounted for approximately 6% of world tuna catches. Assessing and managing this heavily exploited resource requires good knowledge of the species' biology and patterns of connectivity between marine regions. However, despite all the research, population boundaries remain contested. We analyzed the genetics of albacore (n=2315) with 32 polymorphic microsatellite loci in 18 sample sites from 4 sites (Mediterranean Sea, Atlantic Ocean, Pacific Ocean, Indian Ocean) to study connectivity and population structure. In addition, we examined the effective size (Ne) of each population. Pairwise Fst, DAPC and STRUCTURE analyses showed
significant differentiation between the six stocks currently managed by RFMOs. Heterogeneity was observed between samples from the Mediterranean Sea indicating the potential presence of two distinct populations in the Mediterranean Sea. Furthermore, migration flows between the South Atlantic and the Indian Ocean, as well as between the South Atlantic and the Pacific Ocean have been found, certainly due to the presence of currents.
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Albacore (Thunnus alalunga) support an economically valuable global fishery, but surprisingly little is known about the population structure of this highly migratory species. Physical tagging data suggest that Albacore from the North and South Pacific Ocean are separate stocks, but results from previous genetic studies did not support this two stock hypothesis. In addition, observed biological differences among juveniles suggest that there may be population substructure in the North Pacific. We used double digest restriction site‐associated DNA sequencing to assess population structure among 308 Albacore caught in 12 sample areas across the Pacific Ocean (10 North, 2 South). Since Albacore are highly migratory and spawning areas are unknown, sample groups were not assumed to be equivalent to populations and the genetic data were analyzed iteratively. We tested for putatively adaptive differences among groups and for genetic variation associated with sex. Results indicated that Albacore in the North and South Pacific can be distinguished using 84 putatively adaptive loci, but not using the remaining 12,788 presumed neutral sites. However, 2 individuals likely represent F1 hybrids between the North and South Pacific populations, and 43 Albacore potentially exhibit lower degrees of mixed ancestry. In addition, 4 or 5 cross‐hemisphere migrants were potentially identified. No genetic evidence was found for population substructure within the North Pacific, and no loci appeared to distinguish males and females. Potential functions for the putatively adaptive loci were identified, but an annotated Albacore genome is required for further exploration. Future research should try to locate spawning areas so that life history, demography and genetic population structure can be linked and spatiotemporal patterns can be investigated.
Albacore tuna (Thunnus alalunga) is an important target of tuna fisheries in the Atlantic and Indian Oceans. The commercial catch of albacore is the highest globally among all temperate tuna species, contributing around 6% in weight to global tuna catches over the last decade. The accurate assessment and management of this heavily exploited resource requires a robust understanding of the species' biology and of the pattern of connectivity among oceanic regions, yet Indian Ocean albacore population dynamics remain poorly understood and its level of connectivity with the Atlantic Ocean population is uncertain. We analysed morphometrics and genetics of albacore (n = 1,874) in the southwest Indian (SWIO) and southeast Atlantic (SEAO) Oceans to investigate the connectivity and population structure. Furthermore, we examined the species' dispersal potential by modelling particle drift through major oceanographic features. Males appear larger than females, except in South African waters, yet the length-weight relationship only showed significant male-female difference in one region (east of Madagascar and Reunion waters). The present study produced a genetic differentiation between the southeast Atlantic and southwest Indian Oceans, supporting their demographic independence. The particle drift models suggested dispersal potential of early life stages from SWIO to SEAO and adult or sub-adult migration from SEAO to SWIO.
Background:
Use of genomic tools to characterize wildlife populations has increased in recent years. In the past, genetic characterization has been accomplished with more traditional genetic tools (e.g., microsatellites). The explosion of genomic methods and the subsequent creation of large SNP datasets has led to the promise of increased precision in population genetic parameter estimates and identification of demographically and evolutionarily independent groups, as well as questions about the future usefulness of the more traditional genetic tools. At present, few empirical comparisons of population genetic parameters and clustering analyses performed with microsatellites and SNPs have been conducted.
Results:
Here we used microsatellite and SNP data generated from Gunnison sage-grouse (Centrocercus minimus) samples to evaluate concordance of the results obtained from each dataset for common metrics of genetic diversity (HO, HE, FIS, AR) and differentiation (FST, GST, DJost). Additionally, we evaluated clustering of individuals using putatively neutral (SNPs and microsatellites), putatively adaptive, and a combined dataset of putatively neutral and adaptive loci. We took particular interest in the conservation implications of any differences. Generally, we found high concordance between microsatellites and SNPs for HE, FIS, AR, and all differentiation estimates. Although there was strong correlation between metrics from SNPs and microsatellites, the magnitude of the diversity and differentiation metrics were quite different in some cases. Clustering analyses also showed similar patterns, though SNP data was able to cluster individuals into more distinct groups. Importantly, clustering analyses with SNP data suggest strong demographic independence among the six distinct populations of Gunnison sage-grouse with some indication of evolutionary independence in two or three populations; a finding that was not revealed by microsatellite data.
Conclusion:
We demonstrate that SNPs have three main advantages over microsatellites: more precise estimates of population-level diversity, higher power to identify groups in clustering methods, and the ability to consider local adaptation. This study adds to a growing body of work comparing the use of SNPs and microsatellites to evaluate genetic diversity and differentiation for a species of conservation concern with relatively high population structure and using the most common method of obtaining SNP genotypes for non-model organisms.
Understanding and predicting population abundance is a major challenge confronting scientists. Several genetic models have been developed using microsatellite markers to estimate the present and ancestral effective population sizes. However, to get an overview on the evolution of population requires that past fluctuation of population size be traceable. To address the question, we developed a new model estimating the past changes of effective population size from microsatellite by resolving coalescence theory and using approximate likelihoods in a Monte Carlo Markov Chain approach. The efficiency of the model and its sensitivity to gene flow and to assumptions on the mutational process were checked using simulated data and analysis. The model was found especially useful to provide evidence of transient changes of population size in the past. The times at which some past demographic events cannot be detected because they are too ancient and the risk that gene flow may suggest the false detection of a bottleneck are discussed considering the distribution of coalescence times. The method was applied on real data sets from several Atlantic salmon populations. The method called VarEff (Variation of Effective size) was implemented in the R package VarEff and is made available at https://qgsp.jouy.inra.fr and at http://cran.r-project.org/web/packages/VarEff.
This paper presents two novel statistical analyses of multiblock data using the R language. It is designed for data organized in (K +1) blocks (i.e., tables) consisting of a block of response variables to be explained by a large number of explanatory variables which are divided into K meaningful blocks. All the variables – explanatory and dependent – are measured on the same individuals. Two multiblock methods both useful in practice are included, namely multiblock partial least squares regression and multiblock principal component analysis with instrumental variables. The proposed new methods are included within the ade4 package widely used thanks to its great variety of multivariate methods. These methods are available on the one hand for statisticians and on the other hand for users from various fields in the sense that all the values derived from the multiblock processing are available. Some relevant interpretation tools are also developed. Finally the main results are summarized using overall graphical displays. This paper is organized following the different steps of a standard multiblock process, each corresponding to specific R functions. All these steps are illustrated by the analysis of real epidemiological datasets.
An empirical Bayes (EB) pairwise FST estimator was previously introduced and evaluated for its performance by numerical simulation. In this study, we conducted coalescent simulations and generated genetic population structure mechanistically, and compared the performance of the EBFST with Nei's GST , Nei & Chesser's bias-corrected GST (GST _NC ), Weir & Cockerham's ϴ (ϴWC ),( and ϴ with finite sample correction (ϴWC _F ). We also introduced EB estimators for Hedrick' G'ST and Jost' D. We applied these estimators to publicly available SNP genotypes of Atlantic herring. We also examined the power to detect the environmental factors causing the population structure. Our coalescent simulations revealed that the finite sample correction of ϴWC is necessary to assess population structure using pairwise FST values. For microsatellite markers, EBFST performed the best among the present estimators regarding both bias and precision under high gene flow scenarios (FST >0.032). For 300 SNPs, EBFST had the highest precision in all cases, but the bias was negative and greater than those for GST_NC and (ϴWC_F ) in all cases. GST_NC and (ϴWC_F ) performed very similarly at all levels of FST . As the number of loci increased up to 10 000, the precision of GST_NC and ϴWC_F became slightly better than for EBFST for cases with FST >0.004, even though the size of the bias remained constant. The EB estimators described the fine-scale population structure of the herring, and revealed that ~56% of the genetic differentiation was caused by sea surface temperature and salinity. The R package FINEPOP for implementing all estimators used here is available on CRAN. This article is protected by copyright. All rights reserved.
The GERMON project had several aims i) to understand the populations’ structure between albacore tuna southwest of the Indian Ocean and southeast Atlantic, ii) to determine the origin of juveniles observed in South Africa iii) to improve the understanding of the biology field (Size/Size and Size/Weight; reproduction and feeding area; trophic linkages) and iv) to initiate work on chemical analyzes and adaptation of the albacore species to its environment. These aims have been held and the results allow a better understanding of the management albacore. A general summary of results is presented in Part 9.
We use population genetics theory and computer simulations to demonstrate that population bottlenecks cause a characteristic mode-shift distortion in the distribution of allele frequencies at selectively neutral loci. Bottlenecks cause alleles at low frequency (< 0.1) to become less abundant than alleles in one or more intermediate allele frequency class (e.g., 0.1-0.2). This distortion is transient and likely to be detectable for only a few dozen generations. Consequently only recent bottlenecks are likely to be detected by tests for distortions in distributions of allele frequencies. We illustrate and evaluate a qualitative graphical method for detecting a bottleneck-induced distortion of allele frequency distributions. The simple novel method requires no information on historical population sizes or levels of genetic variation; it requires only samples of 5 to 20 polymorphic loci and approximately 30 individuals. The graphical method often differentiates between empirical datasets from bottlenecked and nonbottlenecked natural populations. Computer simulations show that the graphical method is likely (P > .80) to detect an allele frequency distortion after a bottleneck of < or = 20 breeding individuals when 8 to 10 polymorphic microsatellite loci are analyzed.
We introduce the R package strataG as a user-friendly population genetics toolkit. strataG provides easy access to a suite of standard genetic summaries as well as the ability to rapidly manipulate stratified genetic data for custom analyses. Tests of population subdivision with most common measures of population subdivision (e.g., FST , GST , ϕST, χ(2) ) can be conducted within a single function. The package also provides wrapper functions that allow users to configure and run popular external programs such as Genepop, STRUCTURE, and fastsimcoal from within R, and smoothly interface with popular R packages adegenet, and pegas. strataG is intended to be an open-source dynamic package that will grow with future needs and user input. This article is protected by copyright. All rights reserved.
Background
Depiction of the genetic diversity, linkage disequilibrium (LD) and population structure is essential for the efficient organization and exploitation of genetic resources. The objectives of this study were to (i) to evaluate the genetic diversity and to detect the patterns of LD, (ii) to estimate the levels of population structure and (iii) to identify a ‘core collection’ suitable for association genetic studies in sweet cherry.
Results
A total of 210 genotypes including modern cultivars and landraces from 16 countries were genotyped using the RosBREED cherry 6 K SNP array v1. Two groups, mainly bred cultivars and landraces, respectively, were first detected using STRUCTURE software and confirmed by Principal Coordinate Analysis (PCoA). Further analyses identified nine subgroups using STRUCTURE and Discriminant Analysis of Principal Components (DAPC). Several sub-groups correspond to different eco-geographic regions of landraces distribution. Linkage disequilibrium was evaluated showing lower values than in peach, the reference Prunus species. A ‘core collection’ containing 156 accessions was selected using the maximum length sub tree method.
Conclusion
The present study constitutes the first population genetics analysis in cultivated sweet cherry using a medium-density SNP (single nucleotide polymorphism) marker array. We provided estimations of linkage disequilibrium, genetic structure and the definition of a first INRA’s Sweet Cherry core collection useful for breeding programs, germplasm management and association genetics studies.
Electronic supplementary material
The online version of this article (doi:10.1186/s12870-016-0712-9) contains supplementary material, which is available to authorized users.
Recent developments in sequencing technologies and bioinformatics analysis provide a greater amount of DNA sequencing reads at a low cost. Microsatellites are the markers of choice for a variety of population genetic studies, and high quality markers can be discovered in non-model organisms, such as tuna, with these recent developments. Here, we use a high-throughput method to isolate microsatellite markers in albacore tuna, Thunnus alalunga, based on coupling multiplex enrichment and next-generation sequencing on 454 GS-FLX Titanium pyrosequencing. The crucial minimum number of polymorphic markers to infer evolutionary and ecological processes for this species has been described for the first time. We provide 1670 microsatellite design primer pairs, and technical and molecular genetics selection resulting in 43 polymorphic microsatellite markers. On this panel, we characterized 34 random and selectively neutral markers («neutral») and 9 «non-neutral» markers. The variability of «neutral» markers was screened with 136 individuals of albacore tuna from southwest Indian Ocean (42), northwest Indian Ocean (31), South Africa (31), and southeast Atlantic Ocean (32). Power analysis demonstrated that the panel of genetic markers can be applied in diversity and population genetics studies. Global genetic diversity for albacore was high with a mean number of alleles at 16.94; observed heterozygosity 66% and expected heterozygosity 77%. The number of individuals was insufficient to provide accurate results on differentiation. Of the 9 «non-neutral» markers, 3 were linked to a sequence of known function. The one is located to a sequence having an immunity function (ThuAla-Tcell-01) and the other to a sequence having energy allocation function (ThuAla-Hki-01). These two markers were genotyped on the 136 individuals and presented different diversity levels. ThuAla-Tcell-01 has a high number of alleles (20), heterozygosity (87-90%), and assignment index. ThuAla-Hki-01 has a lower number of alleles (9), low heterozygosity (24-27%), low assignment index and significant inbreeding. Finally, the 34 «neutral» and 3 «non-neutral» microsatellites markers were tested on four economically important Scombridae species-Thunnus albacares, Thunnus thynnus, Thunnus obesus, and Acanthocybium solandri.
In the present study we have investigated the population genetic structure of albacore (Thunnus alalunga, Bonnaterre 1788) and assessed the loss of genetic diversity, likely due to overfishing, of albacore population in the North Atlantic Ocean. For this purpose, 1,331 individuals from 26 worldwide locations were analyzed by genotyping 75 novel nuclear SNPs. Our results indicated the existence of four genetically homogeneous populations delimited within the Mediterranean Sea, the Atlantic Ocean, the Indian Ocean and the Pacific Ocean. Current definition of stocks allows the sustainable management of albacore since no stock includes more than one genetic entity. In addition, short-and long-term effective population sizes were estimated for the North Atlantic Ocean albacore population, and results showed no historical decline for this population. Therefore, the genetic diversity and, consequently, the adaptive potential of this population have not been significantly affected by overfishing.
Samples of albacore Thunnus alalunga from 6 locations worldwide were used for blood group analysis according to the binding patterns of 8 different lectins. Conventional tag recapture data was reviewed and a spatially structured tag attrition model was fitted to data from the North Atlantic and the Mediterranean. Blood group analyses suggest that: (1) the Pacific population is the most distant from the others, (2) the Indian and the South Atlantic populations are proximate, (3) the North Atlantic and the Gulf of Guinea populations are proximate, (4) the Gulf of Guinea and the North Atlantic are distant from South Atlantic, and (5) the Mediterranean and the North Atlantic populations are distant. Migration rates between the North Atlantic and the Mediterranean obtained from the tag attrition model were low and thus, consistent with genetic results.
Albacore (Thunnus alalunga) is a highly migratory pelagic species distributed in all tropical and temperate oceans. Recent analyses using both mitochondrial DNA (mtDNA) and nuclear DNA markers have demonstrated genetic subdivision within and between Atlantic and Pacific populations. However, although numerous biological differences have been reported for Atlantic and Mediterranean albacore, the genetic differentiation for these basins has not been demonstrated. We characterized 373 base pairs of nucleotide sequence from the mitochondrial DNA control region of 134 individuals collected in the Pacific (n=30), the northeast (NE) Atlantic (n=54) and the Mediterranean (n=50). Analysis of molecular variance (AMOVA) revealed a small, but highly significant, proportion of genetic variation separating these three regions (Φ
st =0.041; P=0.009), a pattern also supported by pairwise comparisons. These results demonstrate for the first time the genetic distinctiveness of the Mediterranean albacore from the NE Atlantic population giving support to the current management practices based on separate units. This outcome is concordant with reported migratory movements related to reproductive behavior between the NE Atlantic and the Mediterranean Sea. Additionally, the phylogenetic analyses of DNA sequences revealed the presence of a shallow genetic discontinuity with no geographic association. These two phylogroups are more likely the result of the demographic history of this species (i.e. long demographic stable history) as opposed to historical vicariance as has been proposed for other highly migratory fishes.
Restriction endonuclease analysis of mitochondrial DNA purified from 11 south Atlantic (Capetown, South Africa) and 12 north Pacific (San Diego, USA) albacore tuna (Thunnus alalunga) revealed no restriction sites which could distinguish an Atlantic from a Pacific albacore. Although restriction site variation was found within the pooled sample, variants were found only in single fish. These results suggest either recent isolation of Atlantic and Pacific albacore or, more likely, at least a small amount of migration between the two ocean basins.
We present a new R package, diveRsity , for the calculation of various diversity statistics, including common diversity partitioning statistics (θ, G ST ) and population differentiation statistics ( D Jost , , χ ² test for population heterogeneity), among others. The package calculates these estimators along with their respective bootstrapped confidence intervals for loci, sample population pairwise and global levels. Various plotting tools are also provided for a visual evaluation of estimated values, allowing users to critically assess the validity and significance of statistical tests from a biological perspective.
diveRsity has a set of unique features, which facilitate the use of an informed framework for assessing the validity of the use of traditional F ‐statistics for the inference of demography, with reference to specific marker types, particularly focusing on highly polymorphic microsatellite loci. However, the package can be readily used for other co‐dominant marker types (e.g. allozymes, SNP s).
Detailed examples of usage and descriptions of package capabilities are provided. The examples demonstrate useful strategies for the exploration of data and interpretation of results generated by diveRsity . Additional online resources for the package are also described, including a GUI web app version intended for those with more limited experience using R for statistical analysis.
Stock heterogeneity was investigated in albacore tuna (Thunnus alalunga, Bonnaterre 1788), a commercially important species in the North Atlantic Ocean and Mediterranean Sea. Twelve polymorphic microsatellite loci were examined in 581 albacore tuna from nine locations, four in the north-east Atlantic Ocean (NEA), three in the Mediterranean Sea (MED) and two in the south-western Pacific Ocean (SWP). Maximum numbers of alleles per locus ranged from 9 to 38 (sample mean, 5.2–22.6 per locus; overall mean, 14.2 ± 0.47 SE), and observed heterozygosities per locus ranged from 0.44 to 1.00 (overall mean: 0.79 ± 0.19 SE). Significant deficits of heterozygotes were observed in 20% of tests. Multilocus F
ST values were observed ranging from 0.00 to Θ = 0.036 and Θ′ = 0.253, with a mean of Θ = 0.013 and Θ′ = 0.079. Pairwise F
ST values showed that the SWP, NEA and MED stocks were significantly distinct from one another, thus corroborating findings in previous studies based on mitochondrial DNA, nuclear DNA (other than microsatellites) and allozyme analyses. Heterogeneity was observed for the first time between samples within the Mediterranean Sea. GENELAND indicated the potential presence of three populations across the NEA and two separate populations in the Mediterranean Sea. Observed genetic structure may be related to migration patterns and timing of movements of subpopulations to the feeding grounds in either summer or autumn. We suggest that a more intensive survey be conducted throughout the entire fishing season to ratify or refute the currently accepted genetic homogeneity within the NEA albacore stock.
One of the most common problems in fisheries is the definition of management units.
Albacore Thunnus alalunga is an important species for commercial fisheries. Its population structure
is still partially unknown; however, on the basis of fisheries data, tagging experiments, and
morpho-ecological studies, 6 management units are currently accepted for this species. The main
objective of this study was to define genetic entities within T. alalunga and to discuss the appropriateness
of current management units. For this purpose, 13 microsatellite loci were applied to
551 albacore samples collected worldwide, and the population genetic structure was assessed.
The most relevant differences between management and genetic units were that (1) Atlantic and
Indian Ocean samples are genetically indistinguishable, and (2) possible differentiation exists
within the Pacific Ocean and also within the Mediterranean Sea. Thus, this study provides genetic
information to clarify albacore population delimitation, which is a key factor to reach the
demanded sustainable management of this resource.
A sharp genetic break separates Atlantic from Indo-Pacific bigeye tuna (Thunnus obesus) populations, as the frequencies of two major mitochondrial (mt) DNA types ( \ifmmode\expandafter\hat\else\expandafter\^\fi{\theta } \ifmmode\expandafter\hat\else\expandafter\^\fi{\theta }
=0.025 to 0.042) was much lower than in mtDNA (
\ifmmode\expandafter\hat\else\expandafter\^\fi{\theta } \ifmmode\expandafter\hat\else\expandafter\^\fi{\theta }
=0.664 to 0.807). Probabilistic Bayesian assignment of individuals to a population confirmed that southern African bigeye tuna samples represent a simple mixture of individuals from Atlantic and Indian stocks that do not interbreed, with a higher contribution from Indian Ocean individuals (about 2/3 vs. 1/3).
Genetic analyses have much to offer fisheries managers, especially in the provision of tools enabling unequivocal specimen identification and assessment of stock structure. The three commonly-used genetic tools – allozymes, mitochondrial DNA and microsatellites – differ in their properties. These differences must be born in mind, especially when interpreting gene frequency data collected for stock structure research. Examples where genetic approaches have been used to identify specimens are given, with special attention being given to compliance and labelling issues. Treatment of stock structure focuses on Atlantic cod and on yellowfin, bigeye and albacore tunas. The different resolving powers of the various techniques are discussed. Marine fish typically show low levels of population genetic differentiation, and in such species the use of large sample sizes and, preferably, multiple types of markers are desirable to resolve stock structure issues.
The Atlantic bluefin tuna (Thunnus thynnus) is an extraordinary fish that has amazed humanity since ancient times. However, the continuous overexploitation of this
fishery, particularly in the Mediterranean Sea, could result in a total collapse of this resource. Currently, this species
is managed as two stocks: Western Atlantic and Mediterranean-Eastern Atlantic, with a recognized genetic differentiation between
them. On the other hand, the population structure within the Mediterranean Sea is still unclear. The biological data supports
the idea of two separate populations in the eastern and western Mediterranean basins. However, nuclear microsatellite and
mitochondrial DNA (mtDNA) analyses of two samples representative of these two basins result in a lack of heterogeneity. A
comparison of these results with previously published studies reveals some discrepancies. We have compared 59 genetic differentiation
tests that include samples within the Mediterranean. Of these, about 60% gave significant differentiation while the remaining
40% were non-significant. But, when only nuclear-based loci were considered, genetic differentiation was detected in up to
73% of the cases with an average significant F
ST
of only 0.018, whereas the average significant F
ST
of the mtDNA-based studies was significantly higher (0.029). However, in some cases, it is difficult to reconcile the biology
of the species with the results suggesting genetic differentiation. In conclusion, although it is not yet possible to reach
a definitive conclusion about the population structure, but considering all biological and genetic data, we suggest an independent
management approach for each basin to avoid the impact of a type II error that could lead to the possible loss of the regional
subpopulations.
KeywordsAtlantic bluefin tuna–Genetic population structure–Mediterranean Sea–Fishery management–
Thunnus thynnus
Until recently, large apex consumers were ubiquitous across the globe and had been for millions of years. The loss of these
animals may be humankind’s most pervasive influence on nature. Although such losses are widely viewed as an ethical and aesthetic
problem, recent research reveals extensive cascading effects of their disappearance in marine, terrestrial, and freshwater
ecosystems worldwide. This empirical work supports long-standing theory about the role of top-down forcing in ecosystems but
also highlights the unanticipated impacts of trophic cascades on processes as diverse as the dynamics of disease, wildfire,
carbon sequestration, invasive species, and biogeochemical cycles. These findings emphasize the urgent need for interdisciplinary
research to forecast the effects of trophic downgrading on process, function, and resilience in global ecosystems.
The field of molecular ecology has expanded enormously in the past two decades, largely because of the growing ease with which neutral molecular genetic data can be obtained from virtually any taxonomic group. However, there is also a growing awareness that neutral molecular data can provide only partial insight into parameters such as genetic diversity, local adaptation, evolutionary potential, effective population size, and taxonomic designations. Here we review some of the applications of neutral versus adaptive markers in molecular ecology, discuss some of the advantages that can be obtained by supplementing studies of molecular ecology with data from non-neutral molecular markers, and summarize new methods that are enabling researchers to generate data from genes that are under selection.
Multivariate analyses are well known and widely used to identify and understand structures of ecological communities. The ade4 package for the R statistical environment proposes a great number of multivariate methods. Its implementation follows the tradition of the French school of "Analyse des Donnees" and is based on the use of the duality diagram. We present the theory of the duality diagram and discuss its implementation in ade4. Classes and main functions are presented. An example is given to illustrate the ade4 philosophy.
We present here a framework for the study of molecular variation within a single species. Information on DNA haplotype divergence is incorporated into an analysis of variance format, derived from a matrix of squared-distances among all pairs of haplotypes. This analysis of molecular variance (AMOVA) produces estimates of variance components and F-statistic analogs, designated here as phi-statistics, reflecting the correlation of haplotypic diversity at different levels of hierarchical subdivision. The method is flexible enough to accommodate several alternative input matrices, corresponding to different types of molecular data, as well as different types of evolutionary assumptions, without modifying the basic structure of the analysis. The significance of the variance components and phi-statistics is tested using a permutational approach, eliminating the normality assumption that is conventional for analysis of variance but inappropriate for molecular data. Application of AMOVA to human mitochondrial DNA haplotype data shows that population subdivisions are better resolved when some measure of molecular differences among haplotypes is introduced into the analysis. At the intraspecific level, however, the additional information provided by knowing the exact phylogenetic relations among haplotypes or by a nonlinear translation of restriction-site change into nucleotide diversity does not significantly modify the inferred population genetic structure. Monte Carlo studies show that site sampling does not fundamentally affect the significance of the molecular variance components. The AMOVA treatment is easily extended in several different directions and it constitutes a coherent and flexible framework for the statistical analysis of molecular data.
In order to infer phylogenetic relationships between tuna species of the genus Thunnus, partial sequences of the mitochondrial cytochrome b and ATPase genes were determined in all eight species. Supplemental restriction analysis on the nuclear rRNA gene was also carried out. Pacific northern bluefin tuna (Thunnus thynnus orientalis) was found to have mtDNA distinct from that of the Atlantic subspecies (T. t. thynnus) but very similar to that from the species albacore (T. alaluga). In contrast, no differentiation in nuclear genome was observed between the Atlantic and Pacific northern bluefin tunas. The Atlantic northern bluefin and southern bluefin tunas possessed mtDNA sequences very similar to species of yellowfin tuna group and not so similar to albacore and bigeye tunas which were morphologically assigned to the bluefin tuna group. The molecular data indicate that (1) mtDNA from albacore has been incorporated into the Pacific population of northern bluefin tuna and has extensively displaced the original mtDNA, and (2) albacore is the earliest offshoot, followed by bigeye tuna in this genus, which is inconsistent with the phylogenetic relationships between these tuna species inferred from morphology.
Albacore tuna (Thunnus alalunga) is a highly economically important species in the western Indian Ocean. However, knowledge of its ecological and nutritional characteristics, essential for proper management of the species, is lacking in the region. The trophodynamics of the Indian Ocean albacore was thus examined using known fatty acid trophic markers (FATMs) of primary producers, nutritional condition indices (NCIs) (omega-3/omega-6 ratio and total fatty acid content (TFA)), and baseline and lipid corrected stable isotope of carbon (δ13Ccorr) and nitrogen (δ15Ncorr), measured in the muscle tissue. We applied generalized additive mixed models to understand the spatiotemporal patterns and drivers of these tracers, taking into consideration several intrinsic and extrinsic variables: fish size, fishing position, month, chlorophyll-a and sea surface temperature (SST). Both chlorophyll-a and SST were significant as single explanatory variables for all tracers with SST being the best predictor for docosahexaenoic acid/eicosapentaenoic acid ratio, the omega-6 protists FATM, omega-3/omega-6 ratio, δ13Ccorr and δ15Ncorr. TFA was best predicted by fish size only. Higher primary productivity, as inferred by high δ13Ccorr values and diatom contribution, nutritional condition and trophic position, as inferred by high δ15Ncorr values, were observed in albacore from the temperate southern waters than in the northern tropical regions. Relationships between environmental variables and corrected stable isotopes, FATMs confirm that ocean warming and changes in primary productivity will impact nutrient flow and energy transfer in the marine food web which may have negative nutritional outcomes for albacore. This knowledge is particularly crucial in areas where oceanographic conditions and seawater temperatures are changing at a fast rate and should also be taken into consideration by fisheries managers.
Microsatellite loci were isolated from a size-selected genomic library of Pacific northern tuna Thunnus thynnus orientalis, and PCR primer sets to amplify four loci were designed. Investigation on genetic polymorphism at these loci in the Pacific northern bluefin tuna sample (n=35-40) revealed high degree of length polymorphisms in all loci, in which number of alleles per locus ranged from 8 to 23 and observed heterozygosity from 0.533 to 1. These primer sets were applied to Atlantic northern bluefin tuna T t. thynnus, albacore T. alalunga, bigeye tuna T. obesus and yellowfin tuna T. albacares, detecting polymorphism in all loci comparable with those of Pacific northern bluefin tuna. Significant differences in the allele frequency were observed between Pacific and Atlantic northern bluefin tuna samples. These primer sets developed for Pacific northern bluefin tuna appeared to be useful for amplifying homologous microsatellite loci in the other Thunnus tuna species, and may have great potential as indicators for genetic variability within and between samples of tuna species of the genus Thunnus.
Inferences of population structure and more precisely the identification of genetically homogeneous groups of individuals are essential to the fields of ecology, evolutionary biology, and conservation biology. Such population structure inferences are routinely investigated via the program STRUCTURE implementing a Bayesian algorithm to identify groups of individuals at Hardy-Weinberg and linkage equilibrium. While the method is performing relatively well under various population models with even sampling between subpopulations, the robustness of the method to uneven sample size between subpopulations and/or hierarchical levels of population structure has not yet been tested despite being commonly encountered in empirical datasets. In this study, I used simulated and empirical microsatellite datasets to investigate the impact of uneven sample size between subpopulations and/or hierarchical levels of population structure on the detected population structure. The results demonstrated that uneven sampling often leads to wrong inferences on hierarchical structure and downward biased estimates of the true number of subpopulations. Distinct subpopulations with reduced sampling tended to be merged together, whilst at the same time, individuals from extensively sampled subpopulations were generally split, despite belonging to the same panmictic population. Four new supervised methods to detect the number of clusters were developed and tested as part of this study and were found to outperform the existing methods using both evenly and unevenly sampled datasets. Additionally, a sub-sampling strategy aiming to reduce sampling unevenness between subpopulations is presented and tested. These results altogether demonstrate that when sampling evenness is accounted for, the detection of the correct population structure is greatly improved. This article is protected by copyright. All rights reserved.
Both morphometric and DNA sequence analyses were applied in this study for throwing light on the stock structure of the albacore (Thunnus alalunga) resource in the Indian Ocean. A total of 144 albacore individuals, sampled from vessels fishing in six different localities of the Indian Ocean, were used for morphometric comparison. Two fisheries research surveys were carried out in 1990-1991 by the R/V Haikung, which belongs to the Taiwan Fisheries Research Institute, for collecting albacore specimens. Seven well-preserved (at -75°C) muscle tissue specimens, removed from seven albacores caught by the R/V Haikung from three different localities of the Indian Ocean, were used for DNA sequence comparison. The results show that (1) the first two eigenvalues absorb about 99% of the total within-character variability, it is thus advisable to use the first two canonical variables for comparison of morphometric samples; (2) the resultant mutual relationships drawn from morphometric analysis agree surprisingly well with those from the DNA sequence comparison; (3) albacore samples from the Indian Ocean can be categorised into two major groups: those collected from the area west of 90°E and those from the area east of that longitude; (4) within-group heterogeneity is much less than between-group heterogeneity, no matter which method is applied. Based on the results so far obtained, the authors believe that it is possible to have two albacore stocks delimited by the 90°E longitude in the Indian Ocean.
In spite of its pivotal role in future implementations of the Ecosystem Approach to Fisheries Management, current knowledge about tuna habitat preferences remains fragmented and heterogeneous, because it relies mainly on regional or local studies that have used a variety of approaches making them difficult to combine. Therefore in this study we analyse data from six tuna species in the Pacific, Atlantic and Indian Oceans in order to provide a global, comparative perspective of habitat preferences. These data are longline catch per unit effort from 1958 to2007 for albacore, Atlantic bluefin, southern bluefin, bigeye, yellowfin and skipjack tunas. Both quotient analysis and Generalized Additive Models were used to determine habitat preference with respect to eight biotic and abiotic variables. Results confirmed that, compared to temperate tunas, tropical tunas prefer warm, anoxic, stratified waters. Atlantic and southern bluefin tuna prefer higher concentrations of chlorophyll than the rest. The two species also tolerate most extreme sea surface height anomalies and highest mixed layer depths. In general, Atlantic bluefin tuna tolerates the widest range of environmental conditions. An assessment of the most important variables determining fish habitat is also provided.
This paper is a short summary of the main classes defined in the ade4 package for one table analysis methods (e. g., principal component analysis). Other papers will detail the classes defined in ade4 for two-tables coupling methods (such as canonical corre-spondence analysis, redundancy analysis, and co-inertia analysis), for methods dealing with K-tables analysis (i. e., three-ways tables), and for graphical methods. This package is a complete rewrite of the ADE4 software (Thioulouse et al. (1997), http://pbil. univ-lyon1.fr/ADE-4/) for the R environment. It contains
Genetic population structure of Atlantic and Mediterranean albacore Thunnus alalunga was investigated using nucleotide sequence variations of the glucose-6-phosphate dehydrogenase gene intron (G6PD) and the mitochondrial DNA (mtDNA) D-loop region (Dloop). Restriction analysis using Ase I digestion detected two major restriction types (A and B) at the Dloop locus with strong frequency differences between Atlantic and Mediterranean samples. Thirty-six individuals of 100 Mediterranean albacore were of the B type whereas no B type individuals were found in the Atlantic samples (n ¼ 102). Phylogenetic analysis using nucleotide sequence data of the Dloop locus indicated that the B type lineage recently arose from the ancestral A lineage in the Mediterranean Sea and has not dispersed into the Atlantic Ocean. The frequen-cies of two alleles (L and S) at the G6PD locus were significantly different between the samples from the Atlantic (L ¼ 0Á495) and the Mediterranean (L ¼ 0Á725), but no significant hetero-geneity was observed between mtDNA-A and -B types of the Mediterranean sample. These molecular data indicate that gene flow between the Atlantic and Mediterranean albacore populations have been considerably restricted and strongly suggest these populations should continue to be treated as two distinct management units. # 2005 The Fisheries Society of the British Isles
Microsatellite-enriched genomic libraries were obtained from the Atlantic northern bluefin tuna, Thunnus thynnus thynnus and seven tetranucleotide markers were successfully isolated and characterized from this library. These markers were found to have between 1 and 17 alleles in Atlantic northern bluefin tuna and heterozygosity ranged from 0 to 0.85. No deviations from the expectation of Hardy-Weinburg equilibrium were found for any marker. Several of these markers amplify reliably in other tuna species.
When the spring seasonal warming starts, North Atlantic albacore (Thunnus alalunga) juveniles and pre-adults perform a trophic migration to the northeastern Atlantic, to the Bay of Biscay and to the southeast of Ireland. During this migration, they are exploited by Spanish trolling and baitboat fleets. The present study analyzes the relationship between the albacore spatio-temporal distribution and the thermal environment. For this approach, several analyses have been performed on a database including fishing logbooks and sea surface temperature (SST) images, covering the period between 1987 and 2003. SST values and the SST gradients at the catch locations have been statistically compared to broader surrounding areas to test whether the thermal environment determines the spatial distribution of albacore. General additive models (GAM) have been used also to evaluate the relative importance of environmental variables and fleet behaviour. The results obtained show that, although juvenile albacore catch locations are affected by fleet dynamics, there is a close spatial and temporal relationship with the seasonal evolution of a statistically significant preferential SST window (16–18°C). However, differences have been identified between the relationship of albacore with SST within the Bay of Biscay in July and August (higher temperature). Such differences are found also in the spatial distribution of the catch locations; these reflect clearly the presence of two groups, differentiated after the third week of the fishing campaign at the end of June. The analysis undertaken relating the distribution of North Atlantic albacore juveniles with thermal gradients did not provide any evidence of a relationship between these catch locations and the nearby occurrence of thermal gradients.
Twenty-five microsatellites from Atlantic bluefin tuna (Thunnus thynnus thynnus) were characterized. All 25 microsatellites were polymorphic; the number of alleles among up to 56 individuals surveyed ranged from two to 23. Atlantic bluefin tuna are highly exploited and major questions remain as to stock structure and abundance in the eastern and western North Atlantic. The microsatellites will be useful in testing stock-structure hypotheses and in generating estimates of effective population size. The polymerase chain reaction primer sets developed also amplified identifiable alleles in three other species of genus Thunnus: T. albacares (yellowfin tuna), T. alalunga (albacore tuna) and T. obesus (bigeye tuna).
By providing new approaches to the investigation of demographic and evolutionary dynamics of wild populations, molecular genetics has led to fundamental changes in our understanding of marine ecology. In particular, genetic approaches have revolutionized our understanding in three areas: (i) most importantly, they have contributed to the discovery of extensive genetic population structure in many marine species, overturning the notion of large, essentially homogenous marine populations limiting local adaptation and speciation. (ii) Concomitant differences in ecologically important traits now indicate extensive adaptive differentiation and biocomplexity, potentially increasing the resilience to exploitation and disturbance. Evidence for rapid adaptive change in many populations underlies recent concerns about fisheries-induced evolution affecting life-history traits. (iii) A compilation of recent published research shows estimated effective population sizes that are 2–6 orders of magnitude smaller than census sizes, suggesting more complex recruitment dynamics in marine species than previously assumed. Studies on Atlantic cod are used to illustrate these paradigm shifts. In our synthesis, we emphasize the implications of these discoveries for marine ecology and evolution as well as the management and conservation of exploited marine fish populations. An important implication of genetic structuring and the potential for adaptive divergence is that locally adapted populations are unlikely to be replaced through immigration, with potentially detrimental consequences for the resilience to environmental change – a key consideration for sustainable fisheries management.
The genetic population structure of the highly migratory albacore (Thunnus alalunga) was investigated using restriction fragment length polymorphism (RFLP) analysis of the mitochondrial ATPase gene amplified by the polymerase chain reaction (PCR). 620 individuals comprising 13 geographically distant samples (ten Pacific, two Atlantic and the Cape of Good Hope) were surveyed between 1991 and 1994 with two restriction endonucleases (Mse I and Rsa I), resulting in seven haplotypes. No heterogeneity was observed in the distribution of haplotypes among the ten samples from the North and South Pacific, nor among the samples from North and South Atlantic and Cape of Good Hope. However, highly significant heterogeneity was evident among Atlantic and Pacific samples. Higher haplotypic diversity (h) was observed in the Pacific samples (0.59 to 0.69) than in the Atlantic and Cape samples (0.22 to 0.43). These results suggest greater gene flow between albacore of the northern and southern hemispheres (within oceans) than between the Atlantic and Pacific Oceans.
The fat content of 2945 juvenile albacore and 618 juvenile bluefin tunas caught in the Bay of Biscay was measured. Individuals were caught in 2004, 2005, 2006 and 2007 from June to early November by pelagic trawling, trolling and baitboat gears. The results for the two species show different seasonal trends. The fat content of albacore tuna increased linearly throughout the fishing season, which reflects their feeding migration. The seasonal trend of bluefin tuna showed a minimum in early August, which may be related to a different behaviour, physiology or feeding strategy. An interannual increase of fat content was observed in albacore tuna and in age-2 to age-5+ bluefin tuna, which is possibly related to a density-dependence phenomenon. The seasonal increase of fat content was strongest and appeared in the four years studied for age-3 and age-4 albacore tuna, which can be related to a different vertical habitat or a more efficient use of their ecological niche by the individuals of these age-groups, relatively to the younger age-groups. Condition factor and girth/length ratio do not appear to be relevant indicators of fat content.
Given human population growth and accelerated global trade, the rate of emergence of exotic plant pathogens is bound to increase. Understanding the processes that lead to the emergence of new pathogens can help manage emerging epidemics. Novel tools for analyzing population genetic variation can be used to infer the evolutionary history of populations or species, allowing for the unprecedented reconstruction of the demographic history of pathogens. Specifically, recent advances in the application of coalescent, maximum likelihood (ML), and Bayesian methods to population genetic data combined with increasing availability of affordable sequencing and parallel computing have created the opportunity to apply these methods to a broad range of questions regarding the evolution of emerging pathogens. These approaches are particularly powerful when used to test multiple competing hypotheses. We provide several examples illustrating how coalescent analysis provides critical insights into understanding migration pathways as well as processes of divergence, speciation, and recombination.
We investigate the effects of past changes of the effective population size on the present allelic diversity at a microsatellite marker locus. We first derive the analytical expression of the generating function of the joint probabilities of the time to the Most Recent Common Ancestor for a pair of alleles and of their distance (the difference in allele size). We give analytical solutions in the case of constant population size and the geometrical mutation model. Otherwise, numerical inversion allows the distributions to be calculated in general cases. The effects of population expansion or decrease and the possibility to detect an ancient bottleneck are discussed. The method is extended to samples of three and four alleles, which allows investigating the covariance structure of the frequencies f(k) of pairs of alleles with a size difference of k motifs, and suggesting some approaches to the estimation of past demography.
pegas (Population and Evolutionary Genetics Analysis System) is a new package for the analysis of population genetic data.
It is written in R and is integrated with two other existing R packages (ape and adegenet). pegas provides functions for standard
population genetic methods, as well as low-level functions for developing new methods. The flexible and efficient graphical
capabilities of R are used for plotting haplotype networks as well as for other functionalities. pegas emphasizes the need to further develop an integrated–modular approach for software dedicated to the analysis of population
genetic data.
Availability: pegas is distributed through the Comprehensive R Archive Network (CRAN): http://cran.r-project.org/web/packages/pegas/index.html Further information may be found at: http://ape.mpl.ird.fr/pegas/
Contact: emmanuel.paradis{at}ird.fr
Job number added acc. to DOCREP assignment
Dominant markers such as amplified fragment length polymorphisms (AFLPs) provide an economical way of surveying variation at many loci. However, the uncertainty about the underlying genotypes presents a problem for statistical analysis. Similarly, the presence of null alleles and the limitations of genotype calling in polyploids mean that many conventional analysis methods are invalid for many organisms. Here we present a simple approach for accounting for genotypic ambiguity in studies of population structure and apply it to AFLP data from whitefish. The approach is implemented in the program structure version 2.2, which is available from http://pritch.bsd.uchicago.edu/structure.html.
Intracellular signalling following mitogenic stimulation of quiescent cells involves the initiation of a phosphorylation cascade that leads to the rapid and reversible activation of the mitogen-activated protein (MAP) kinases ERK1 and ERK2. MAP kinase activation is mediated by dual phosphorylation within the motif Thr-Glu-Tyr by MAP kinase kinase (MEK). Following activation, the MAP kinases translocate into the nucleus where they phosphorylate several transduction targets, including transcription factors. We have previously identified PAC1 as an immediate-early mitogen-inducible tyrosine phosphatase in nuclei of T cells. Here we present several lines of evidence indicating that PAC1 is a physiologically relevant MAP kinase phosphatase. Recombinant PAC1 in vitro is a dual-specific Thr/Tyr phosphatase with stringent substrate specificity for MAP kinase. Constitutive expression of PAC1 in vivo leads to inhibition of MAP kinase activity normally stimulated by epidermal growth factor, phorbol myristyl acetate, or T-cell receptor crosslinking. The inactivation of MAP kinase by PAC1 results in inhibition of MAP kinase-regulated reporter gene expression.
We describe a model-based clustering method for using multilocus genotype data to infer population structure and assign individuals to populations. We assume a model in which there are K populations (where K may be unknown), each of which is characterized by a set of allele frequencies at each locus. Individuals in the sample are assigned (probabilistically) to populations, or jointly to two or more populations if their genotypes indicate that they are admixed. Our model does not assume a particular mutation process, and it can be applied to most of the commonly used genetic markers, provided that they are not closely linked. Applications of our method include demonstrating the presence of population structure, assigning individuals to populations, studying hybrid zones, and identifying migrants and admixed individuals. We show that the method can produce highly accurate assignments using modest numbers of loci-e.g. , seven microsatellite loci in an example using genotype data from an endangered bird species. The software used for this article is available from http://www.stats.ox.ac.uk/ approximately pritch/home. html.
Single-sample methods of bottleneck detection are now routine analyses in studies of wild populations and conservation genetics. Three common approaches to bottleneck detection are the heterozygosity excess, mode-shift, and M-ratio tests. Empirical groundtruthing of these methods is difficult, but their performances are critical for the accurate reconstruction of population demography. We use two banner-tailed kangaroo rat (Dipodomys spectabilis) populations from southeastern Arizona (USA) that are known to have experienced recent demographic reductions to search for genetic bottleneck signals with eight microsatellite loci. Over eight total sample-years, neither population showed a genetic bottleneck signature. M-ratios in both populations were large, stable, and never fell below a critical significance value (Mc). The mode shift test did not detect any distortion of allele frequencies, and tests of heterozygosity excess were not significant in postbottleneck samples when we used standard microsatellite mutation models. The genetic effects of bottlenecks like those experienced by our study populations should be strongly influenced by rates of mutation and migration. We used genetic parentage data to estimate a relatively high mutation rate in D. spectabilis (0.0081 mutants/generation/locus), but mutation alone is unlikely to explain the temporal distribution of rare alleles that we observed. Migration (gene flow) is a more likely explanation, despite prior mark-recapture analysis that estimated very low rates of interpopulation dispersal. We interpret our kangaroo rat data in light of the broader literature and conclude that in natural populations connected by dispersal, demographic bottlenecks may prove difficult to detect using molecular genetic data.
Single nucleotide polymorphism discovery in albacore and Atlantic bluefin tuna provides insights into worldwide population structure
- A Albaina
- M Iriondo
- I Velado
- U Laconcha
- I Zarraonaindia
- H Arrizabalaga
- M A Pardo
- M Lutcavage
- W S Grant
- A Estonba
Albaina, A., Iriondo, M., Velado, I., Laconcha, U., Zarraonaindia, I., Arrizabalaga, H., Pardo, M. A.,
Lutcavage, M., Grant, W. S., & Estonba, A. (2013). Single nucleotide polymorphism discovery in
albacore and Atlantic bluefin tuna provides insights into worldwide population structure. Animal
Genetics, 44(6), 678-692. https://doi.org/https://doi.org/10.1111/age.12051
Deecting the number of clusers of individuals using the software structure: a simulation study
- G Evanno
- S Renaugnaut
- J Goudet
Evanno G, Renaugnaut S, Goudet J (2005) Deecting the number of clusers of individuals using the
software structure: a simulation study. Molecular Ecology, 14:2611-2620.