More than meets the eye: syntopic and morphologically similar mangrove killifish species show different mating systems and patterns of genetic structure along the Brazilian coast

AbstractDifferent mating systems can strongly affect the extent of genetic diversity and population structure among species. Given the increased effects of genetic drift on reduced population size, theory predicts that species undergoing self-fertilization should have greater population structure than outcrossed species, however demographic dynamics may affect this scenario. The mangrove killifish clade is composed of the two only known examples of self-fertilising species among vertebrates (Kryptolebias marmoratus and K. hermaphroditus). A third species in this clade, K. ocellatus, inhabits mangrove forests in southeast Brazil, however its mating system and patterns of genetic structure have been rarely explored. Here, we examined the genetic structure and phylogeographic patterns of K. ocellatus along its distribution, using mitochondrial DNA and microsatellites to compare its patterns of genetic structure with the predominantly selfing and often syntopic, K. hermaphroditus. Our results indicate that K. ocellatus reproduces mainly by outcrossing across much of its known range, with no current evidence of selfing, despite being an androdioecious species. Our results also reveal a stronger population subdivision in K. ocellatus compared to K. hermaphroditus, contrary to the theoretical predictions based on reproductive biology of the two species Our findings indicate that, although morphologically similar, K. ocellatus and K. hermaphroditus had remarkably different evolutionary histories when colonising the same mangrove areas in south-eastern Brazil, with other factors (e. g. time of colonisation, dispersal/establishment capacity) having more profound effects on the current population structuring of those species than differences in mating systems.

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More than meets the eye: syntopic and morphologically similar mangrove killifish species show different mating systems and patterns of genetic structure along the Brazilian coast

Heredity ◽

10.1038/s41437-020-00356-y ◽

2020 ◽

Vol 125 (5) ◽

pp. 340-352

Author(s):

Waldir M. Berbel-Filho ◽

Andrey Tatarenkov ◽

Helder M. V. Espírito-Santo ◽

Mateus G. Lira ◽

Carlos Garcia de Leaniz ◽

...

Keyword(s):

Genetic Structure ◽

Mating Systems ◽

Brazilian Coast ◽

Mangrove Killifish

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Genome-Wide Single Nucleotide Polymorphisms are Robust in Resolving Fine-Scale Population Genetic Structure of the Small Brown Planthopper, Laodelphax striatellus (Fallén) (Hemiptera: Delphacidae)

Journal of Economic Entomology ◽

10.1093/jee/toz145 ◽

2019 ◽

Vol 112 (5) ◽

pp. 2362-2368

Author(s):

Yan Liu ◽

Lei Chen ◽

Xing-Zhi Duan ◽

Dian-Shu Zhao ◽

Jing-Tao Sun ◽

...

Keyword(s):

Population Structure ◽

Discriminant Analysis ◽

Genetic Structure ◽

Population Genetic ◽

Brown Planthopper ◽

Fine Scale ◽

Nucleotide Polymorphisms ◽

Single Nucleotide ◽

Small Brown Planthopper ◽

Scale Population

Abstract Deciphering genetic structure and inferring migration routes of insects with high migratory ability have been challenging, due to weak genetic differentiation and limited resolution offered by traditional genotyping methods. Here, we tested the ability of double digest restriction-site associated DNA sequencing (ddRADseq)-based single nucleotide polymorphisms (SNPs) in revealing the population structure relative to 13 microsatellite markers by using four small brown planthopper populations as subjects. Using ddRADseq, we identified 230,000 RAD loci and 5,535 SNP sites, which were present in at least 80% of individuals across the four populations with a minimum sequencing depth of 10. Our results show that this large SNP panel is more powerful than traditional microsatellite markers in revealing fine-scale population structure among the small brown planthopper populations. In contrast to the mixed population structure suggested by microsatellites, discriminant analysis of principal components (DAPC) of the SNP dataset clearly separated the individuals into four geographic populations. Our results also suggest the DAPC analysis is more powerful than the principal component analysis (PCA) in resolving population genetic structure of high migratory taxa, probably due to the advantages of DAPC in using more genetic variation and the discriminant analysis function. Together, these results point to ddRADseq being a promising approach for population genetic and migration studies of small brown planthopper.

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Average Number of Nucleotide Differences in a Sample From a Single Subpopulation: A Test for Population Subdivision

Genetics ◽

10.1093/genetics/117.1.149 ◽

1987 ◽

Vol 117 (1) ◽

pp. 149-153

Author(s):

Curtis Strobeck

Keyword(s):

Monte Carlo Simulation ◽

Population Structure ◽

Random Mating ◽

Population Subdivision ◽

Expected Number ◽

Migration Rates ◽

Mating Population ◽

Unbiased Estimates ◽

Increasing Function ◽

Stepping Stone Model

ABSTRACT Unbiased estimates of θ = 4Nµ in a random mating population can be based on either the number of alleles or the average number of nucleotide differences in a sample. However, if there is population structure and the sample is drawn from a single subpopulation, these two estimates of θ behave differently. The expected number of alleles in a sample is an increasing function of the migration rates, whereas the expected average number of nucleotide differences is shown to be independent of the migration rates and equal to 4N Tµ for a general model of population structure which includes both the island model and the circular stepping-stone model. This contrast in the behavior of these two estimates of θ is used as the basis of a test for population subdivision. Using a Monte-Carlo simulation developed so that independent samples from a single subpopulation could be obtained quickly, this test is shown to be a useful method to determine if there is population subdivision.

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Selection, Load and Inbreeding Depression in a Large Metapopulation

Genetics ◽

10.1093/genetics/160.3.1191 ◽

2002 ◽

Vol 160 (3) ◽

pp. 1191-1202 ◽

Cited By ~ 1

Author(s):

Michael C Whitlock

Keyword(s):

Population Structure ◽

Inbreeding Depression ◽

Population Subdivision ◽

Response To Selection ◽

Mutation Load ◽

Deleterious Alleles ◽

Subdivided Population ◽

Soft Selection ◽

Mean Fitness ◽

The Mean

Abstract The subdivision of a species into local populations causes its response to selection to change, even if selection is uniform across space. Population structure increases the frequency of homozygotes and therefore makes selection on homozygous effects more effective. However, population subdivision can increase the probability of competition among relatives, which may reduce the efficacy of selection. As a result, the response to selection can be either increased or decreased in a subdivided population relative to an undivided one, depending on the dominance coefficient FST and whether selection is hard or soft. Realistic levels of population structure tend to reduce the mean frequency of deleterious alleles. The mutation load tends to be decreased in a subdivided population for recessive alleles, as does the expected inbreeding depression. The magnitude of the effects of population subdivision tends to be greatest in species with hard selection rather than soft selection. Population structure can play an important role in determining the mean fitness of populations at equilibrium between mutation and selection.

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Equilibrium Values of Measures of Population Subdivision for Stepwise Mutation Processes

Genetics ◽

10.1093/genetics/142.4.1357 ◽

1996 ◽

Vol 142 (4) ◽

pp. 1357-1362

Author(s):

François Rousset

Keyword(s):

Population Structure ◽

Population Subdivision ◽

Identity By Descent ◽

Infinite Allele Model ◽

Coalescence Time ◽

Stepwise Mutation ◽

Expected Values ◽

The Relationship ◽

Allele Model ◽

Coalescence Times

Abstract Expected values of Wright'sF-statistics are functions of probabilities of identity in state. These values may be quite different under an infinite allele model and under stepwise mutation processes such as those occurring at microsatellite loci. However, a relationship between the probability of identity in state in stepwise mutation models and the distribution of coalescence times can be deduced from the relationship between probabilities of identity by descent and the distribution of coalescence times. The values of FIS and FST can be computed using this property. Examination of the conditional probability of identity in state given some coalescence time and of the distribution of coalescence times are also useful for explaining the properties of FIS and FST at high mutation rate loci, as shown here in an island model of population structure.

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CHANGING POPULATION STRUCTURE THROUGH THE USE OF COMPOUND CHROMOSOMES

Genetics ◽

10.1093/genetics/72.1.183 ◽

1972 ◽

Vol 72 (1) ◽

pp. 183-186

Author(s):

D Childress

Keyword(s):

Population Structure ◽

Genetic Structure ◽

Theoretical Calculations ◽

Population Cage ◽

Insect Populations

ABSTRACT Theoretical calculations and population cage data are presented to illustrate the use of compound chromosomes to change the genetic structure of insect populations.

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A spectral theory for Wright’s inbreeding coefficients and related quantities

PLoS Genetics ◽

10.1371/journal.pgen.1009665 ◽

2021 ◽

Vol 17 (7) ◽

pp. e1009665

Author(s):

Olivier François ◽

Clément Gain

Keyword(s):

Population Structure ◽

Genetic Variation ◽

Population Genetic ◽

Principal Component ◽

Large Data ◽

Population Subdivision ◽

Adaptive Genetic Variation ◽

Genomic Locus ◽

Inbreeding Coefficients ◽

Definition Of

Wright’s inbreeding coefficient, FST, is a fundamental measure in population genetics. Assuming a predefined population subdivision, this statistic is classically used to evaluate population structure at a given genomic locus. With large numbers of loci, unsupervised approaches such as principal component analysis (PCA) have, however, become prominent in recent analyses of population structure. In this study, we describe the relationships between Wright’s inbreeding coefficients and PCA for a model of K discrete populations. Our theory provides an equivalent definition of FST based on the decomposition of the genotype matrix into between and within-population matrices. The average value of Wright’s FST over all loci included in the genotype matrix can be obtained from the PCA of the between-population matrix. Assuming that a separation condition is fulfilled and for reasonably large data sets, this value of FST approximates the proportion of genetic variation explained by the first (K − 1) principal components accurately. The new definition of FST is useful for computing inbreeding coefficients from surrogate genotypes, for example, obtained after correction of experimental artifacts or after removing adaptive genetic variation associated with environmental variables. The relationships between inbreeding coefficients and the spectrum of the genotype matrix not only allow interpretations of PCA results in terms of population genetic concepts but extend those concepts to population genetic analyses accounting for temporal, geographical and environmental contexts.

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Genetic diversity and population structure among goat genotypes in Kenya

10.1101/2020.07.06.189290 ◽

2020 ◽

Author(s):

Ruth W. Waineina ◽

Kiplangat Ngeno ◽

Tobias O. Otieno ◽

Evans D. Ilatsia

Keyword(s):

Population Structure ◽

Principal Component ◽

Genetic Distances ◽

Snp Markers ◽

Founder Population ◽

Good Opportunity ◽

Model Based Clustering ◽

Population Structuring ◽

Improvement Programs ◽

Genotype Clustering

AbstractPopulation structure and relationship information among goats is critical for genetic improvement, utilization and conservation. This study explored population structure and level of gene intermixing among four goat genotypes in Kenya: Alpine (n = 30), Toggenburg (n = 28), Saanen (n = 24) and Galla (n = 12). The population structuring and relatedness were estimated using principal component analysis utilizing allele frequencies of the SNP markers. Genotype relationships were evaluated based on the calculated Reynolds genetic distances. A phylogenetic tree was constructed to represent genotype clustering using iTOL software. Population structure was investigated using model-based clustering (ADMIXTURE) Genotypes relationships revealed four distinctive clusters: Alpine, Galla, Saanen and Toggenburg. The ADMIXTURE results revealed some level of gene intermixing among Alpine, Toggenburg and Saanen with Galla. Saanen goats were the most admixed genotype with 84%, 7% and 4% of its genome derived from Galla, Alpine and Toggenburg respectively. Alpine and Toggenburg goats shared some associations with the Galla goat; 10% and 1% respectively. The association of Galla with other genotypes was anticipated since Galla goat was used as the founder population for crossbreeding with Saanen, Alpine and Toggenburg breed. The genetic variations among the goat genotypes observed, will provide a good opportunity for sustainable utilization, conservation and future genetic resource improvement programs in goat genotypes in Kenya.

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Whole-genome SNP analysis elucidates the genetic population structure and diversity of Acrocomia species

10.1101/2020.10.08.331140 ◽

2020 ◽

Author(s):

Brenda G. Díaz ◽

Maria I. Zucchi ◽

Alessandro. Alves-Pereira ◽

Caléo P. de Almeida ◽

Aline C. L. Moraes ◽

...

Keyword(s):

Genetic Diversity ◽

Population Structure ◽

Genetic Structure ◽

Genetic Relationships ◽

Geographical Area ◽

Taxonomic Classification ◽

Genomic Diversity ◽

Productive Capacity ◽

Snp Analysis ◽

Genetic Population

AbstractAcrocomia (Arecaceae) is a genus widely distributed in tropical and subtropical America that has been achieving economic interest due to the great potential of oil production of some of its species. In particular A. aculeata, due to its vocation to supply oil with the same productive capacity as the oil palm even in areas with water deficit. Although eight species are recognized in the genus, the taxonomic classification based on morphology and geographic distribution is still controversial. Knowledge about the genetic diversity and population structure of the species is limited, which has limited the understanding of the genetic relationships and the orientation of management, conservation, and genetic improvement activities of species of the genus. In the present study, we analyzed the genomic diversity and population structure of seven species of Acrocomia including 117 samples of A. aculeata covering a wide geographical area of occurrence, using single nucleotide Polymorphism (SNP) markers originated from Genotyping By Sequencing (GBS). The genetic structure of the Acrocomia species were partially congruent with the current taxonomic classification based on morphological characters, recovering the separation of the species A. aculeata, A. totai, A. crispa and A. intumescens as distinct taxonomic groups. However, the species A. media was attributed to the cluster of A. aculeata while A. hassleri and A. glauscescens were grouped together with A. totai. The species that showed the highest and lowest genetic diversity were A. totai and A. media, respectively. When analyzed separately, the species A. aculeata showed a strong genetic structure, forming two genetic groups, the first represented mainly by genotypes from Brazil and the second by accessions from Central and North American countries. Greater genetic diversity was found in Brazil when compared to the other countries. Our results on the genetic diversity of the genus are unprecedented, as is also establishes new insights on the genomic relationships between Acrocomia species. It is also the first study to provide a more global view of the genomic diversity of A. aculeata. We also highlight the applicability of genomic data as a reference for future studies on genetic diversity, taxonomy, evolution and phylogeny of the Acrocomia genus, as well as to support strategies for the conservation, exploration and breeding of Acrocomia species and in particular A. aculeata.

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A differential expression of pyrethroid resistance genes in the malaria vector Anopheles funestus across Uganda is associated with patterns of gene flow

PLoS ONE ◽

10.1371/journal.pone.0240743 ◽

2020 ◽

Vol 15 (11) ◽

pp. e0240743

Author(s):

Maurice Marcel Sandeu ◽

Charles Mulamba ◽

Gareth D. Weedall ◽

Charles S. Wondji

Keyword(s):

Population Structure ◽

Gene Flow ◽

Genetic Structure ◽

Genetic Differentiation ◽

Insecticide Resistance ◽

Pyrethroid Resistance ◽

Anopheles Funestus ◽

Metabolic Resistance ◽

Transcription Analysis ◽

Genome Wide

Background Insecticide resistance is challenging the effectiveness of insecticide-based control interventions to reduce malaria burden in Africa. Understanding the molecular basis of insecticides resistance and patterns of gene flow in major malaria vectors such as Anopheles funestus are important steps for designing effective resistance management strategies. Here, we investigated the association between patterns of genetic structure and expression profiles of genes involved in the pyrethroid resistance in An. funestus across Uganda and neighboring Kenya. Methods Blood-fed mosquitoes An. funestus were collected across the four localities in Uganda and neighboring Kenya. A Microarray-based genome-wide transcription analysis was performed to identify the set of genes associated with permethrin resistance. 17 microsatellites markers were genotyped and used to establish patterns of genetic differentiation. Results Microarray-based genome-wide transcription profiling of pyrethroid resistance in four locations across Uganda (Arua, Bulambuli, Lira, and Tororo) and Kenya (Kisumu) revealed that resistance was mainly driven by metabolic resistance. The most commonly up-regulated genes in pyrethroid resistance mosquitoes include cytochrome P450s (CYP9K1, CYP6M7, CYP4H18, CYP4H17, CYP4C36). However, expression levels of key genes vary geographically such as the P450 CYP6M7 [Fold-change (FC) = 115.8 (Arua) vs 24.05 (Tororo) and 16.9 (Kisumu)]. In addition, several genes from other families were also over-expressed including Glutathione S-transferases (GSTs), carboxylesterases, trypsin, glycogenin, and nucleotide binding protein which probably contribute to insecticide resistance across Uganda and Kenya. Genotyping of 17 microsatellite loci in the five locations provided evidence that a geographical shift in the resistance mechanisms could be associated with patterns of population structure throughout East Africa. Genetic and population structure analyses indicated significant genetic differentiation between Arua and other localities (FST>0.03) and revealed a barrier to gene flow between Arua and other areas, possibly associated with Rift Valley. Conclusion The correlation between patterns of genetic structure and variation in gene expression could be used to inform future interventions especially as new insecticides are gradually introduced.

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