Geometric Morphology and Population Genomics Provide Insights into the Adaptive Evolution of Apis Cerana in Changbai Mountain

Abstract Background: Exploration of adaptive evolution of organisms in response to environmental change will offer us a hint to the evolutionary history of species and the underlying mechanisms of adaptation to local environments, thus guiding future conservation programmes. Before the introduction of Apis mellifera in China, Apis cerana was the only species, which could be reared in captivity to obtain products. Moreover, A. cerana in Changbai Mountain is the only ecotype in such a flora. Result: We investigated the geometric morphological features of A. cerana in Changbai Mountain by analysing 300 wing specimens from 30 populations of A. cerana in 5 geographic regions. A total of 3,859,573 high-quality SNP loci were yielded via the whole-genome resequencing of 130 individuals from 130 A. cerana geographic populations.Conclusion: Corresponding geometric morphology and population genome confirmed the outstanding evolutionary role of the A. cerana population in Changbai Mountain. Genetic differentiation at the subspecies level exists between populations in Changbai Mountain and remaining geographic regions, and a significant reduction in the effective population size and an excessive degree of inbreeding may be responsible for a substantial loss of population genetic diversity. Candidate genes potentially associated with cold environmental adaptations in populations under natural selection were identified, which may represent local adaptations in populations. Our study provided insights into the evolutionary history and adaptive characteristics of A. cerana in Changbai Mountain, as well as the scientific conservation of this population.

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Population structure and introgression among recently differentiated Drosophila melanogaster populations

10.1101/2021.06.25.449842 ◽

2021 ◽

Author(s):

Jenn M Coughlan ◽

Andrius Dagilis ◽

Antonio Serrato-Capuchina ◽

Hope Elias ◽

David Peede ◽

...

Keyword(s):

Drosophila Melanogaster ◽

Phenotypic Variation ◽

Evolutionary Biology ◽

Evolutionary History ◽

Population Genomics ◽

Model Organism ◽

Genetic Incompatibility ◽

Behavioral Types ◽

Out Of Africa ◽

Geographic Regions

Understanding the factors that produce and maintain genetic variation is a central goal of evolutionary biology. Despite a century of genetic analysis, the evolutionary history underlying patterns of exceptional genetic and phenotypic variation in the model organism Drosophila melanogaster remains poorly understood. In particular, how genetic and phenotypic variation is partitioned across global D. melanogaster populations, and specifically in its putative ancestral range in Subtropical Africa, remains unresolved. Here, we integrate genomic and behavioral analyses to assess patterns of population genetic structure, admixture, mate preference, and genetic incompatibility throughout the range of this model organism. Our analysis includes 174 new accessions from novel and under-sampled regions within Subtropical Africa. We find that while almost all Out of Africa genomes correspond to a single genetic ancestry, different geographic regions within Africa contain multiple distinct ancestries, including the presence of substantial cryptic diversity within Subtropical Africa. We find evidence for significant admixture- and variation in admixture rates-between geographic regions within Africa, as well as between African and non-African lineages. By combining behavioral analysis with population genomics, we demonstrate that female mate choice is highly polymorphic, behavioral types are not monophyletic, and that genomic differences between behavioral types correspond to many regions across the genome. These include regions associated with neurological development, behavior, olfactory perception, and learning. Finally, we discovered that many individual pairs of putative incompatibility loci likely evolved during or after the expansion of D. melanogaster out of Africa. This work contributes to our understanding of the evolutionary history of a key model system, and provides insight into the distribution of reproductive barriers that are polymorphic within species.

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Accounting for Gene Flow from Unsampled ‘Ghost’ Populations while Estimating Evolutionay History under the Isolation with Migration Model

10.1101/733600 ◽

2019 ◽

Author(s):

Arun Sethuraman ◽

Melissa Lynch

Keyword(s):

Gene Flow ◽

Evolutionary History ◽

Population Genomics ◽

Divergence Times ◽

Effective Population ◽

Migration Rates ◽

Isolation With Migration ◽

Population Sizes ◽

And Migration ◽

Erroneous Inferences

AbstractUnsampled or extinct ‘ghost’ populations leave signatures on the genomes of individuals from extant, sampled populations, especially if they have exchanged genes with them over evolutionary time. This gene flow from ‘ghost’ populations can introduce biases when estimating evolutionary history from genomic data, often leading to data misinterpretation and ambiguous results. Here we assess these biases while accounting, or not accounting for gene flow from ‘ghost’ populations under the Isolation with Migration (IM) model. We perform extensive simulations under five scenarios with no gene flow (Scenario A), to extensive gene flow to- and from- an unsampled ‘ghost’ population (Scenarios B, C, D, and E). Estimates of evolutionary history across all scenarios A-E (effective population sizes, divergence times, and migration rates) indicate consistent a) under-estimation of divergence times between sampled populations, (b) over-estimation of effective population sizes of sampled populations, and (c) under-estimation of migration rates between sampled populations, with increased gene flow from the unsampled ‘ghost’ population. Without accounting for an unsampled ‘ghost’, summary statistics like FST are under-estimated, and π is over-estimated with increased gene flow from the‘ghost’. To show this persistent issue in empirical data, we use a 355 locus dataset from African Hunter-Gatherer populations and discuss similar biases in estimating evolutionary history while not accounting for unsampled ‘ghosts’. Considering the large effects of gene flow from these ‘ghosts’, we propose a multi-pronged approach to account for the presence of unsampled ‘ghost’ populations in population genomics studies to reduce erroneous inferences.

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Population genomics and morphological features underlying the adaptive evolution of the eastern honey bee (Apis cerana)

BMC Genomics ◽

10.1186/s12864-019-6246-4 ◽

2019 ◽

Vol 20 (1) ◽

Cited By ~ 2

Author(s):

Li Yancan ◽

Chao Tianle ◽

Fan Yunhan ◽

Lou Delong ◽

Wang Guizhi

Keyword(s):

Adaptive Evolution ◽

North China ◽

Environmental Changes ◽

Population Genomics ◽

Fundamental Problem ◽

Apis Cerana ◽

Morphological Characteristics ◽

Morphological Features ◽

Central China ◽

Data Set

Abstract Background The adaptation of organisms to changing environments is self-evident, with the adaptive evolution of organisms to environmental changes being a fundamental problem in evolutionary biology. Bees can pollinate in various environments and climates and play important roles in maintaining the ecological balance of the earth. Results We performed an analysis of 462 Apis cerana (A. cerana) specimens from 31 populations in 11 regions and obtained 39 representative morphological features. We selected 8 A. cerana samples from each population and performed 2b-RAD simplified genome sequencing. A total of 11,506 high-quality single nucleotide polymorphism (SNP) loci were obtained. For these SNPs, the minor allele frequency (MAF) was > 1%, the average number of unique labels for each sample was 49,055, and the average depth was 72.61x. The ratios of the unique labels of all samples were 64.27–86.33%. Conclusions Using 39 morphological characteristics as the data set, we proposed a method for the rapid classification of A. cerana. Using genomics to assess population structure and genetic diversity, we found that A. cerana has a large genetic difference at the ecotype level. A comparison of A. cerana in North China revealed that some physical obstacles, especially the overurbanization of the plains, have isolated the populations of this species. We identified several migration events in North China and Central China. By comparing the differences in the environmental changes in different regions, we found that A. cerana has strong potential for climate change and provides a theoretical basis for investigating and protecting A. cerana.

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A Phenotype–Genotype Codon Model for Detecting Adaptive Evolution

Systematic Biology ◽

10.1093/sysbio/syz075 ◽

2019 ◽

Vol 69 (4) ◽

pp. 722-738 ◽

Cited By ~ 2

Author(s):

Christopher T Jones ◽

Noor Youssef ◽

Edward Susko ◽

Joseph P Bielawski

Keyword(s):

Positive Selection ◽

Adaptive Evolution ◽

Evolutionary History ◽

Life History Trait ◽

Molecular Adaptation ◽

Simulation Studies ◽

Site Model ◽

Branch Site ◽

A Site ◽

Post Hoc

Abstract A central objective in biology is to link adaptive evolution in a gene to structural and/or functional phenotypic novelties. Yet most analytic methods make inferences mainly from either phenotypic data or genetic data alone. A small number of models have been developed to infer correlations between the rate of molecular evolution and changes in a discrete or continuous life history trait. But such correlations are not necessarily evidence of adaptation. Here, we present a novel approach called the phenotype–genotype branch-site model (PG-BSM) designed to detect evidence of adaptive codon evolution associated with discrete-state phenotype evolution. An episode of adaptation is inferred under standard codon substitution models when there is evidence of positive selection in the form of an elevation in the nonsynonymous-to-synonymous rate ratio $\omega$ to a value $\omega > 1$. As it is becoming increasingly clear that $\omega > 1$ can occur without adaptation, the PG-BSM was formulated to infer an instance of adaptive evolution without appealing to evidence of positive selection. The null model makes use of a covarion-like component to account for general heterotachy (i.e., random changes in the evolutionary rate at a site over time). The alternative model employs samples of the phenotypic evolutionary history to test for phenomenological patterns of heterotachy consistent with specific mechanisms of molecular adaptation. These include 1) a persistent increase/decrease in $\omega$ at a site following a change in phenotype (the pattern) consistent with an increase/decrease in the functional importance of the site (the mechanism); and 2) a transient increase in $\omega$ at a site along a branch over which the phenotype changed (the pattern) consistent with a change in the site’s optimal amino acid (the mechanism). Rejection of the null is followed by post hoc analyses to identify sites with strongest evidence for adaptation in association with changes in the phenotype as well as the most likely evolutionary history of the phenotype. Simulation studies based on a novel method for generating mechanistically realistic signatures of molecular adaptation show that the PG-BSM has good statistical properties. Analyses of real alignments show that site patterns identified post hoc are consistent with the specific mechanisms of adaptation included in the alternate model. Further simulation studies show that the covarion-like component of the PG-BSM plays a crucial role in mitigating recently discovered statistical pathologies associated with confounding by accounting for heterotachy-by-any-cause. [Adaptive evolution; branch-site model; confounding; mutation-selection; phenotype–genotype.]

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Population Genomics of American Mink Using Whole Genome Sequencing Data

Genes ◽

10.3390/genes12020258 ◽

2021 ◽

Vol 12 (2) ◽

pp. 258

Author(s):

Karim Karimi ◽

Duy Ngoc Do ◽

Mehdi Sargolzaei ◽

Younes Miar

Keyword(s):

Population Genomics ◽

Association Studies ◽

American Mink ◽

Population History ◽

Whole Genome Sequencing Data ◽

Whole Genome ◽

Nucleotide Polymorphisms ◽

Sequencing Data ◽

Effective Population ◽

Cross Validation Error

Characterizing the genetic structure and population history can facilitate the development of genomic breeding strategies for the American mink. In this study, we used the whole genome sequences of 100 mink from the Canadian Centre for Fur Animal Research (CCFAR) at the Dalhousie Faculty of Agriculture (Truro, NS, Canada) and Millbank Fur Farm (Rockwood, ON, Canada) to investigate their population structure, genetic diversity and linkage disequilibrium (LD) patterns. Analysis of molecular variance (AMOVA) indicated that the variation among color-types was significant (p < 0.001) and accounted for 18% of the total variation. The admixture analysis revealed that assuming three ancestral populations (K = 3) provided the lowest cross-validation error (0.49). The effective population size (Ne) at five generations ago was estimated to be 99 and 50 for CCFAR and Millbank Fur Farm, respectively. The LD patterns revealed that the average r2 reduced to <0.2 at genomic distances of >20 kb and >100 kb in CCFAR and Millbank Fur Farm suggesting that the density of 120,000 and 24,000 single nucleotide polymorphisms (SNP) would provide the adequate accuracy of genomic evaluation in these populations, respectively. These results indicated that accounting for admixture is critical for designing the SNP panels for genotype-phenotype association studies of American mink.

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dDocent: a RADseq, variant-calling pipeline designed for population genomics of non-model organisms

10.7287/peerj.preprints.314 ◽

2014 ◽

Author(s):

Jonathan Puritz ◽

Christopher M. Hollenbeck ◽

John R. Gold

Keyword(s):

Population Genomics ◽

De Novo ◽

Variant Calling ◽

Population Level ◽

Model Organisms ◽

Effective Population ◽

Reduction Techniques ◽

Indel Polymorphisms ◽

Indel Calling ◽

Population Sizes

Restriction-site associated DNA sequencing (RADseq) has become a powerful and useful approach for population genomics. Currently, no software exists that utilizes both paired-end reads from RADseq data to efficiently produce population-informative variant calls, especially for organisms with large effective population sizes and high levels of genetic polymorphism but for which no genomic resources exist. dDocent is an analysis pipeline with a user-friendly, command-line interface designed to process individually barcoded RADseq data (with double cut sites) into informative SNPs/Indels for population-level analyses. The pipeline, written in BASH, uses data reduction techniques and other stand-alone software packages to perform quality trimming and adapter removal, de novo assembly of RAD loci, read mapping, SNP and Indel calling, and baseline data filtering. Double-digest RAD data from population pairings of three different marine fishes were used to compare dDocent with Stacks, the first generally available, widely used pipeline for analysis of RADseq data. dDocent consistently identified more SNPs shared across greater numbers of individuals and with higher levels of coverage. This is most likely due to the fact that dDocent quality trims instead of filtering and incorporates both forward and reverse reads in assembly, mapping, and SNP calling, thus enabling use of reads with Indel polymorphisms. The pipeline and a comprehensive user guide can be found at (http://dDocent.wordpress.com).

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Runs of homozygosity for autozygosity estimation and genomic analysis in production animals

Pesquisa Agropecuária Brasileira ◽

10.1590/s0100-204x2018000900001 ◽

2018 ◽

Vol 53 (9) ◽

pp. 975-984 ◽

Cited By ~ 1

Author(s):

Arnaldo Basso Rebelato ◽

Alexandre Rodrigues Caetano

Keyword(s):

Evolutionary History ◽

Genomic Analysis ◽

Runs Of Homozygosity ◽

Demographic Information ◽

Genomic Information ◽

Selection Signatures ◽

Effective Population ◽

High Frequencies ◽

Production Animals ◽

Genealogical Information

Abstract: Runs of homozygosity (ROHs) are long stretches of homozygous genomic segments, identifiable by molecular markers, which can provide genomic information for accurate estimates to characterize populations, determine evolutionary history and demographic information, estimate levels of consanguinity, and identify selection signatures in production animals. This review paper aims to perform a survey of the works on the efficiency of ROHs for these purposes. Factors such as genetic drift, natural or artificial selection, founder effect, and effective population size directly influence the size and distribution of ROHs along the genome. Individually, genome estimates of consanguinity based on ROHs can be obtained using the FROH index, which is generally considered more accurate than indexes based on other types of genomic or genealogical information. High frequencies of specific ROHs in a population can be used to identify selection signatures. The results of recent studies with ROHs in domestic animals have shown the efficiency of their use to characterize herds in a reliable and accessible way, using genomic information.

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Fine-scale population structure and ecotypes of anadromous Hilsa shad (Tenualosa ilisha) across complex aquatic ecosystems revealed by NextRAD genotyping

Scientific Reports ◽

10.1038/s41598-019-52465-2 ◽

2019 ◽

Vol 9 (1) ◽

Cited By ~ 5

Author(s):

Md Asaduzzaman ◽

Md A. Wahab ◽

Md J. Rahman ◽

Md Nahiduzzzaman ◽

Malcom W. Dickson ◽

...

Keyword(s):

Aquatic Ecosystems ◽

Population Genomics ◽

Nucleotide Polymorphism ◽

Single Nucleotide ◽

Local Adaptations ◽

Life History Stages ◽

Marine Habitats ◽

Scale Population ◽

Tenualosa Ilisha ◽

Conservation And Management

Abstract The anadromous Hilsa shad (Tenualosa ilisha) live in the Bay of Bengal and migrate to the estuaries and freshwater rivers for spawning and nursing of the juveniles. This has led to two pertinent questions: (i) do all Hilsa shad that migrate from marine to freshwater rivers come from the same population? and (ii) is there any relationship between adults and juveniles of a particular habitat? To address these questions, NextRAD sequencing was applied to genotype 31,276 single nucleotide polymorphism (SNP) loci for 180 individuals collected from six strategic locations of riverine, estuarine and marine habitats. FST OutFLANK approach identified 14,815 SNP loci as putatively neutral and 79 SNP loci as putatively adaptive. We observed that divergent local adaptations in differing environmental habitats have divided Hilsa shad into three genetically structured ecotypes: turbid freshwater (Western Riverine), clear freshwater (Eastern Riverine) and brackish-saline (Southern Estuarine-Marine). Our results also revealed that genes involved in neuronal activity may have facilitated the juveniles’ Hilsa shad in returning to their respective natal rivers for spawning. This study emphasized the application of fundamental population genomics information in strategizing conservation and management of anadromous fish such as Hilsa shad that intersect diverse ecotypes during their life-history stages.

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