Population Genetic Inference Research Articles

Commonly used Hardy-Weinberg equilibrium filtering schemes impact population structure inferences using RADseq data.

Reduced representation sequencing (RRS) is a widely used method to assay the diversity of genetic loci across the genome of an organism. The dominant class of RRS approaches assay loci associated with restriction sites within the genome (restriction site associated DNA sequencing, or RADseq). RADseq is frequently applied to non‐model organisms since it enables population genetic studies without relying on well‐characterized reference genomes. However, RADseq requires the use of many bioinformatic filters to ensure the quality of genotyping calls. These filters can have direct impacts on population genetic inference, and therefore require careful consideration. One widely used filtering approach is the removal of loci that do not conform to expectations of Hardy–Weinberg equilibrium (HWE). Despite being widely used, we show that this filtering approach is rarely described in sufficient detail to enable replication. Furthermore, through analyses of in silico and empirical data sets we show that some of the most widely used HWE filtering approaches dramatically impact inference of population structure. In particular, the removal of loci exhibiting departures from HWE after pooling across samples significantly reduces the degree of inferred population structure within a data set (despite this approach being widely used). Based on these results, we provide recommendations for best practice regarding the implementation of HWE filtering for RADseq data sets.

Branching structure of genealogies in spatially growing populations and its implications for population genetics inference

Spatial models where growth is limited to the population edge have been instrumental to understanding the population dynamics and the clone size distribution in growing cellular populations, such as microbial colonies and avascular tumours. A complete characterization of the coalescence process generated by spatial growth is still lacking, limiting our ability to apply classic population genetics inference to spatially growing populations. Here, we start filling this gap by investigating the statistical properties of the cell lineages generated by the two dimensional Eden model, leveraging their physical analogy with directed polymers. Our analysis provides quantitative estimates for population measurements that can easily be assessed via sequencing, such as the average number of segregating sites and the clone size distribution of a subsample of the population. Our results not only reveal remarkable features of the genealogies generated during growth, but also highlight new properties that can be misinterpreted as signs of selection if non-spatial models are inappropriately applied.

The East Asian wild apples, Malus baccata (L.) Borkh and Malus hupehensis (Pamp.) Rehder., are additional contributors to the genomes of cultivated European and Chinese varieties.

The domestication process in long-lived plant perennials differs dramatically from that of annuals, with a huge amount of genetic exchange between crop and wild populations. Though apple is a major fruit crop grown worldwide, the contribution of wild apple species to the genetic makeup of the cultivated apple genome remains a topic of intense study. We used population genomics approaches to investigate the contributions of several wild apple species to European and Chinese rootstock and dessert genomes, with a focus on the extent of wild-crop gene flow. Population genetic structure inferences revealed that the East Asian wild apples, Malus baccata (L.) Borkh and M. hupehensis (Pamp.), form a single panmictic group, and that the European dessert and rootstock apples form a specific gene pool whereas the Chinese dessert and rootstock apples were a mixture of three wild gene pools, suggesting different evolutionary histories of European and Chinese apple varieties. Coalescent-based inferences and gene flow estimates indicated that M. baccata - M. hupehensis contributed to the genome of both European and Chinese cultivated apples through wild-to-crop introgressions, and not as an initial contributor as previously supposed. We also confirmed the contribution through wild-to-crop introgressions of Malus sylvestris Mill. to the cultivated apple genome. Apple tree domestication is therefore one example in woody perennials that involved gene flow from several wild species from multiple geographical areas. This study provides an example of a complex protracted process of domestication in long-lived plant perennials, and is a starting point for apple breeding programmes.

Population genetics of polymorphism and divergence in rapidly evolving populations.

In rapidly evolving populations, numerous beneficial and deleterious mutations can arise and segregate within a population at the same time. In this regime, evolutionary dynamics cannot be analyzed using traditional population genetic approaches that assume that sites evolve independently. Instead, the dynamics of many loci must be analyzed simultaneously. Recent work has made progress by first analyzing the fitness variation within a population, and then studying how individual lineages interact with this traveling fitness wave. However, these "traveling wave" models have previously been restricted to extreme cases where selection on individual mutations is either much faster or much slower than the typical coalescent timescale Tc. In this work, we show how the traveling wave framework can be extended to intermediate regimes in which the scaled fitness effects of mutations (Tcs) are neither large nor small compared to one. This enables us to describe the dynamics of populations subject to a wide range of fitness effects, and in particular, in cases where it is not immediately clear which mutations are most important in shaping the dynamics and statistics of genetic diversity. We use this approach to derive new expressions for the fixation probabilities and site frequency spectra of mutations as a function of their scaled fitness effects, along with related results for the coalescent timescale Tc and the rate of adaptation or Muller's ratchet. We find that competition between linked mutations can have a dramatic impact on the proportions of neutral and selected polymorphisms, which is not simply summarized by the scaled selection coefficient Tcs. We conclude by discussing the implications of these results for population genetic inferences.

Linked selection shapes the landscape of genomic variation in three oak species.

Natural selection shapes genome-wide patterns of diversity within species and divergence between species. However, quantifying the efficacy of selection and elucidating the relative importance of different types of selection in shaping genomic variation remain challenging. We sequenced whole genomes of 101 individuals of three closely related oak species to track the divergence history, and to dissect the impacts of selective sweeps and background selection on patterns of genomic variation. We estimated that the three species diverged around the late Neogene and experienced a bottleneck during the Pleistocene. We detected genomic regions with elevated relative differentiation ('FST -islands'). Population genetic inferences from the site frequency spectrum and ancestral recombination graph indicated that FST -islands were formed by selective sweeps. We also found extensive positive selection; the fixation of adaptive mutations and reduction neutral diversity around substitutions generated a signature of selective sweeps. Prevalent negative selection and background selection have reduced genetic diversity in both genic and intergenic regions, and contributed substantially to the baseline variation in genetic diversity. Our results demonstrate the importance of linked selection in shaping genomic variation, and illustrate how the extent and strength of different selection models vary across the genome.

There Is No 'Rule of Thumb': Genomic Filter Settings for a Small Plant Population to Obtain Unbiased Gene Flow Estimates.

The application of high-density polymorphic single-nucleotide polymorphisms (SNP) markers derived from high-throughput sequencing methods has heralded plenty of biological questions about the linkages of processes operating at micro- and macroevolutionary scales. However, the effects of SNP filtering practices on population genetic inference have received much less attention. By performing sensitivity analyses, we empirically investigated how decisions about the percentage of missing data (MD) and the minor allele frequency (MAF) set in bioinformatic processing of genomic data affect direct (i.e., parentage analysis) and indirect (i.e., fine-scale spatial genetic structure – SGS) gene flow estimates. We focus specifically on these manifestations in small plant populations, and particularly, in the rare tropical plant species Dinizia jueirana-facao, where assumptions implicit to analytical procedures for accurate estimates of gene flow may not hold. Avoiding biases in dispersal estimates are essential given this species is facing extinction risks due to habitat loss, and so we also investigate the effects of forest fragmentation on the accuracy of dispersal estimates under different filtering criteria by testing for recent decrease in the scale of gene flow. Our sensitivity analyses demonstrate that gene flow estimates are robust to different setting of MAF (0.05–0.35) and MD (0–20%). Comparing the direct and indirect estimates of dispersal, we find that contemporary estimates of gene dispersal distance (σrt = 41.8 m) was ∼ fourfold smaller than the historical estimates, supporting the hypothesis of a temporal shift in the scale of gene flow in D. jueirana-facao, which is consistent with predictions based on recent, dramatic forest fragmentation process. While we identified settings for filtering genomic data to avoid biases in gene flow estimates, we stress that there is no ‘rule of thumb’ for bioinformatic filtering and that relying on default program settings is not advisable. Instead, we suggest that the approach implemented here be applied independently in each separate empirical study to confirm appropriate settings to obtain unbiased population genetics estimates.

Ancient Introgression Between Distantly Related White Oaks (Quercus sect. Quercus) Shows Evidence of Climate-Associated Asymmetric Gene Exchange.

Ancient introgression can be an important source of genetic variation that shapes the evolution and diversification of many taxa. Here, we estimate the timing, direction, and extent of gene flow between two distantly related oak species in the same section (Quercus sect. Quercus). We estimated these demographic events using genotyping by sequencing data, which generated 25 702 single nucleotide polymorphisms for 24 individuals of California scrub oak (Quercus berberidifolia) and 23 individuals of Engelmann oak (Quercus engelmannii). We tested several scenarios involving gene flow between these species using the diffusion approximation-based population genetic inference framework and model-testing approach of the Python package DaDi. We found that the most likely demographic scenario includes a bottleneck in Q. engelmannii that coincides with asymmetric gene flow from Q. berberidifolia into Q. engelmannii. Given that the timing of this gene flow coincides with the advent of a Mediterranean-type climate in the California Floristic Province, we propose that changing precipitation patterns and seasonality may have favored the introgression of climate-associated genes from the endemic into the non-endemic California oak.

The distribution of waiting distances in ancestral recombination graphs

The ancestral recombination graph (ARG) contains the full genealogical information of the sample, and many population genetic inference problems can be solved using inferred or sampled ARGs. In particular, the waiting distance between tree changes along the genome can be used to make inference about the distribution and evolution of recombination rates. To this end, we here derive an analytic expression for the distribution of waiting distances between tree changes under the sequentially Markovian coalescent model and obtain an accurate approximation to the distribution of waiting distances for topology changes. We use these results to show that some of the recently proposed methods for inferring sequences of trees along the genome provide strongly biased distributions of waiting distances. In addition, we provide a correction to an undercounting problem facing all available ARG inference methods, thereby facilitating the use of ARG inference methods to estimate temporal changes in the recombination rate.

Chromosome-scale inference of hybrid speciation and admixture with convolutional neural networks.

Inferring the frequency and mode of hybridization among closely related organisms is an important step for understanding the process of speciation and can help to uncover reticulated patterns of phylogeny more generally. Phylogenomic methods to test for the presence of hybridization come in many varieties and typically operate by leveraging expected patterns of genealogical discordance in the absence of hybridization. An important assumption made by these tests is that the data (genes or SNPs) are independent given the species tree. However, when the data are closely linked, it is especially important to consider their nonindependence. Recently, deep learning techniques such as convolutional neural networks (CNNs) have been used to perform population genetic inferences with linked SNPs coded as binary images. Here, we use CNNs for selecting among candidate hybridization scenarios using the tree topology (((P1 , P2 ), P3 ), Out) and a matrix of pairwise nucleotide divergence (dXY ) calculated in windows across the genome. Using coalescent simulations to train and independently test a neural network showed that our method, HyDe-CNN, was able to accurately perform model selection for hybridization scenarios across a wide breath of parameter space. We then used HyDe-CNN to test models of admixture in Heliconius butterflies, as well as comparing it to phylogeny-based introgression statistics. Given the flexibility of our approach, the dropping cost of long-read sequencing and the continued improvement of CNN architectures, we anticipate that inferences of hybridization using deep learning methods like ours will help researchers to better understand patterns of admixture in their study organisms.

Low impact of different SNP panels from two building-loci pipelines on RAD-Seq population genomic metrics: case study on five diverse aquatic species

BackgroundThe irruption of Next-generation sequencing (NGS) and restriction site-associated DNA sequencing (RAD-seq) in the last decade has led to the identification of thousands of molecular markers and their genotyping for refined genomic screening. This approach has been especially useful for non-model organisms with limited genomic resources. Many building-loci pipelines have been developed to obtain robust single nucleotide polymorphism (SNPs) genotyping datasets using a de novo RAD-seq approach, i.e. without reference genomes. Here, the performances of two building-loci pipelines, STACKS 2 and Meyer’s 2b-RAD v2.1 pipeline, were compared using a diverse set of aquatic species representing different genomic and/or population structure scenarios. Two bivalve species (Manila clam and common edible cockle) and three fish species (brown trout, silver catfish and small-spotted catshark) were studied. Four SNP panels were evaluated in each species to test both different building-loci pipelines and criteria for SNP selection. Furthermore, for Manila clam and brown trout, a reference genome approach was used as control.ResultsDespite different outcomes were observed between pipelines and species with the diverse SNP calling and filtering steps tested, no remarkable differences were found on genetic diversity and differentiation within species with the SNP panels obtained with a de novo approach. The main differences were found in brown trout between the de novo and reference genome approaches. Genotyped vs missing data mismatches were the main genotyping difference detected between the two building-loci pipelines or between the de novo and reference genome comparisons.ConclusionsTested building-loci pipelines for selection of SNP panels seem to have low influence on population genetics inference across the diverse case-study scenarios here studied. However, preliminary trials with different bioinformatic pipelines are suggested to evaluate their influence on population parameters according with the specific goals of each study.

Massively parallel sequencing of 165 ancestry-informative SNPs and forensic biogeographical ancestry inference in three southern Chinese Sinitic/Tai-Kadai populations

Ancestry informative markers (AIMs), which are distributed throughout the human genome, harbor significant allele frequency differences among diverse ethnic groups. The use of sets of AIMs to reconstruct population history and genetic relationships is attracting interest in the forensic community, because biogeographic ancestry information for a casework sample can potentially be predicted and used to guide the investigative process. However, subpopulation ancestry inference within East Asia remains in its infancy due to a lack of population reference data collection and incomplete validation work on newly developed or commercial AIM sets. In the present study, 316 Chinese persons, including 85 Sinitic-speaking Haikou Han, 120 Qiongzhong Hlai and 111 Daozhen Gelao individuals belonging to Tai-Kadai-speaking populations, were analyzed using the Precision ID Ancestry Panel (165 AISNPs). Combined with our previous 165-AISNP data (375 individuals from 6 populations), the 1000 Genomes Project and forensic literature, comprehensive population genetic comparisons and ancestry inference were further performed via ADMIXTURE, TreeMix, PCA, f-statistics and N-J tree. Although several nonpolymorphic loci were identified in the three southern Chinese populations, the forensic parameters of this ancestry inference panel were better than those for the 23 STR-based Huaxia Platinum System, which is suitable for use as a robust tool in forensic individual identification and parentage testing. The results based on the ancestry assignment and admixture proportion evaluation revealed that this panel could be used successfully to assign individuals at a continental scale but also possessed obvious limitations in discriminatory power in intercontinental individuals, especially for European-Asian admixed Uyghurs or in populations lacking reference databases. Population genetic analyses further revealed five continental population clusters and three East Asian-focused population subgroups, which is consistent with linguistic affiliations. Ancestry composition and multiple phylogenetic analysis further demonstrated that the geographically isolated Qiongzhong Hlai harbored a close phylogenetic relationship with Austronesian speakers and possessed a homogenous Tai-Kadai-dominant ancestry, which could be used as the ancestral source proxy in population history reconstruction of Tai-Kadai-speaking populations and as one of the representatives for forensic database establishment. In summary, more population-specific AIM sets focused on East Asian subpopulations, comprehensive algorithms and high-coverage population reference data should be developed and validated in the next step.

Effective double-digest RAD sequencing and genotyping despite large genome size.

Obtaining informative data is the ambition of any genomic project, but in nonmodel species with very large genomes, pursuing such a goal requires surmounting a series of analytical challenges. Double-digest RAD sequencing is routinely used in nonmodel organisms and offers some control over the volume of data obtained. However, the volume of data recovered is not always an indication of the reliability of data sets, and quality checks are necessary to ensure that true and artefactual information is set apart. In the present study, we aim to fill the gap existing between the known applicability of RAD sequencing methods in plants with large genomes and the use of the retrieved loci for population genetic inference. By analysing two populations of Cypripedium calceolus, a nonmodel orchid species with a large genome size (1C ~31.6Gbp), we provide a complete workflow from library preparation to bioinformatic filtering and inference of genetic diversity and differentiation. We show how filtering strategies to dismiss potentially misleading data need to be explored and adapted to data set-specific features. Moreover, we suggest that the occurrence of organellar sequences in libraries should not be neglected when planning the experiment and analysing the results. Finally, we explain how, in the absence of prior information about the genome of the species, seeking high standards of quality during library preparation and sequencing can provide an insurance against unpredicted technical or biological constraints.

Inference of population genetic parameters from an irregular time series of seasonal influenza virus sequences.

Basic summary statistics that quantify the population genetic structure of influenza virus are important for understanding and inferring the evolutionary and epidemiological processes. However, the sampling dates of global virus sequences in the last several decades are scattered nonuniformly throughout the calendar. Such temporal structure of samples and the small effective size of viral population hampers the use of conventional methods to calculate summary statistics. Here, we define statistics that overcome this problem by correcting for the sampling-time difference in quantifying a pairwise sequence difference. A simple linear regression method jointly estimates the mutation rate and the level of sequence polymorphism, thus providing an estimate of the effective population size. It also leads to the definition of Wright's FST for arbitrary time-series data. Furthermore, as an alternative to Tajima's D statistic or the site-frequency spectrum, a mismatch distribution corrected for sampling-time differences can be obtained and compared between actual and simulated data. Application of these methods to seasonal influenza A/H3N2 viruses sampled between 1980 and 2017 and sequences simulated under the model of recurrent positive selection with metapopulation dynamics allowed us to estimate the synonymous mutation rate and find parameter values for selection and demographic structure that fit the observation. We found that the mutation rates of HA and PB1 segments before 2007 were particularly high and that including recurrent positive selection in our model was essential for the genealogical structure of the HA segment. Methods developed here can be generally applied to population genetic inferences using serially sampled genetic data.

Mitochondrial DNA reveals genetically structured haplogroups of Bali sardinella (Sardinella lemuru) in Philippine waters

Population genetic structure of Sardinella lemuru in Philippine waters was examined using mitochondrial DNA markers, control region (CR) and cytochrome oxidase I (COI). The sampling effort was focused along the northern coast of Mindanao where the species was previously reported to have regionally structured stocks. Sequences from online databases were included to expand geographic coverage of the analyses. Phylogeographic and population genetic inferences revealed the presence of genetically structured sympatric haplogroups across the archipelago (CR: n = 493, K = 3, between-group genetic distance = 0.038 – 0.054, global ΦST=0.41 p < 0.001; COI: n = 159, K = 2, between-group genetic distance = 0.012, global ΦST=0.77, p < 0.001). In contrast, little to no genetic differentiation was inferred when samples were assigned based on geographic location (CR global ΦST=0.01, p < 0.05; COI global ΦST=0.001, p > 0.05). These results suggest that (1) gene flow occurs across space, but is limited among sympatric haplogroups, (2) these sympatric haplogroups do not correspond to cryptic species, and (3) differences in mutation rates between the two markers may have led to a different number of haplogroups being recovered. High haplotype diversity (HCR=0.99; HCOI=0.798), low nucleotide diversity (πCR=0.041; πCOI=0.005), and significantly negative Fu’s FS values implied demographic expansion for all haplogroups. The mismatch distribution and Bayesian Skyline plot indicated that expansion occurred during the late Pleistocene. Based on our results, we hypothesize that the Philippines is a secondary contact zone for S. lemuru, and testing this requires that samples be obtained from the entire habitat range of the species along the Indo-West Pacific Region.

Genome-scale target capture of mitochondrial and nuclear environmental DNA from water samples.

Environmental DNA (eDNA) provides a promising supplement to traditional sampling methods for population genetic inferences, but current studies have almost entirely focused on short mitochondrial markers. Here, we develop one mitochondrial and one nuclear set of target capture probes for the whale shark (Rhincodon typus) and test them on seawater samples collected in Qatar to investigate the potential of target capture for eDNA‐based population studies. The mitochondrial target capture successfully retrieved ~235× (90× − 352× per base position) coverage of the whale shark mitogenome. Using a minor allele frequency of 5%, we find 29 variable sites throughout the mitogenome, indicative of at least five contributing individuals. We also retrieved numerous mitochondrial reads from an abundant nontarget species, mackerel tuna (Euthynnus affinis), showing a clear relationship between sequence similarity to the capture probes and the number of captured reads. The nuclear target capture probes retrieved only a few reads and polymorphic variants from the whale shark, but we successfully obtained millions of reads and thousands of polymorphic variants with different allele frequencies from E. affinis. We demonstrate that target capture of complete mitochondrial genomes and thousands of nuclear loci is possible from aquatic eDNA samples. Our results highlight that careful probe design, taking into account the range of divergence between target and nontarget sequences as well as presence of nontarget species at the sampling site, is crucial to consider. eDNA sampling coupled with target capture approaches provide an efficient means with which to retrieve population genomic data from aggregating and spawning aquatic species.

Regional population genetics and global phylogeography of the endangered highly migratory shark Lamna nasus: Implications for fishery management and conservation

Abstract The porbeagle shark Lamna nasus is a large highly migratory shark distributed in cold and temperate marine waters of the North Atlantic and Southern Hemisphere (SH). According to the International Union for Conservation of Nature, the porbeagle is assessed globally as Vulnerable and regionally as Critically Endangered in the North Atlantic and the Mediterranean Sea. This study explored, for the first time, the population genetics of L. nasus at a regional (south‐east Pacific Ocean) and global scale. In this study, the null hypotheses of no genetic discontinuities among populations (i) within the SH, and (ii) between the SH and Northern Hemisphere (NH) were tested. Also, the demographic history of L. nasus in different ocean basins was assessed. Two mitochondrial markers (Control Region [CR] and cox1) well suited for population genetics inferences in sharks were used. Spatial–genetic analyses suggested two genetic clusters co‐occurring in the south‐eastern Pacific Ocean. A two‐way ANOVA using the cox1 but not the CR mtDNA fragment detected an effect of genetic identity on shark body size. Phylogeographic analyses, haplotype networks, and analyses of molecular variance demonstrated genetic differences between populations from the NH and SH but not among populations in the SH. Migration estimates indicated limited current maternal gene flow between the two hemispheres but high gene flow within hemispheres. Two well‐defined haplotype groups with star‐like shapes inhabited all ocean basins in the SH. These results could reflect a historical scenario of reproductive isolation and more recent mixture among previously isolated populations in the SH. A Bayesian skyline plot analysis indicated sudden population expansion in the SH occurring ~100–125 kya. This study highlights the need for additional studies focusing on the population genomics (using nuclear markers, i.e. single nucleotide polymorphisms) and the general biology of L. nasus to explore the existence of genetically dissimilar populations in the SH. Such studies will help implementing efficient genetic monitoring programmes.

Genetic variation and population genetic structure of the large yellow croaker (Larimichthys crocea) based on genome‐wide single nucleotide polymorphisms in farmed and wild populations

Populations of marine fishes are show relatively weak genetic differentiation due to the lack of geographical barriers and the potential for the strong diffusion ability favoring high levels of gene flow. The large yellow croaker (Larimichthys crocea) is a commercially important fish species with high gene flow, and its aquaculture production ranks first among all marine fishes cultured in China. To better understand the population structure of L. crocea, a total of 7161 quality-filtered SNP markers were identified in 120 individuals from five farmed and wild populations by using restriction site-associated DNA sequencing (RAD-seq). Our population genetic inferences suggest the existence of two genetic lineages of this croaker in the wild populations in the coastal waters of China. We suggested that an allopatric speciation mechanism is typically characterized by the formation of the Taiwan Strait between the South and East China Sea. The farmed and wild populations present in Ningde City exhibit similar genetic ancestry, which implies that the latter population may represent escaped farmed fish with a higher discharge frequency, rather than areal wild population.

Genome-wide discovery of microsatellite markers and, population genetic diversity inferences revealed high anthropogenic pressure on endemic populations of Trillium govanianum

Trillium govanianum ethnobotanical perspectives include the treatment of cancer, hypertension, neurasthenia, giddiness, arthritis, dysentery, and inflammation. As its industrial demand for steroidal content is increasing, the endemic species have been subjected to severe habitat degradation and fragmentation by the illicit trade in Indian Himalayan Region (IHR). Additionally, molecular genetics efforts in T. govanianum has also lagged, mainly because of the non-availability of genome-wide molecular marker resources. Apropos, using tissue-specific transcriptomic data derived from the rhizome, stem, leaf, and fruit, the present study identified 5337 novel functionally relevant genome-wide SSR markers. The tri repeats were most abundant (41%) with a higher occurrence of CCG/CGG repeat motif, mostly located in the CDS region. Based on functional annotations of SSR transcripts with multifarious public databases (NR, TAIR, KEGG, KOG, SwissProt & PTFdb), a set of 288 SSR markers encompassing important roles in steroidal saponins pathway, cellular and metabolic processes such as response to stress, binding, and catalytic activity were validated, successfully. Genetic diversity and population structure analysis of 290 genotypes of 14 geographically distinct populations representing eight different valleys (2086−3500 m amsl) of the IHR amplified an average of 4.33 alleles per locus. Overall, a low genetic diversity (He: 0.25), high genetic divergence (GST: 0.23), high within populations molecular variance (72 %), limited gene flow (0.792), and slight positive isolation by distance (Rxy = 0.260; p = 0.030) is recorded in T. govanianum populations. Further, neighbor-joining (NJ) based hierarchical clustering, PCoA, and Bayesian structure clustering identified two major groups in the tested populations. Novel microsatellite marker resources and population diversity inferences studied for the first time revealed that there is a need to recuperate diversity in situ and maintain effective population size, a much-required step to mitigate high anthropogenic pressure on T. govanianum in Indian Himalayan Region.

Modifying the Chi-square and the CMH test for population genetic inference: Adapting to overdispersion

Evolve and resequence studies provide a popular approach to simulate evolution in the lab and explore its genetic basis. In this context, Pearson’s chi-square test, Fisher’s exact test as well as the Cochran–Mantel–Haenszel test are commonly used to infer genomic positions affected by selection from temporal changes in allele frequency. However, the null model associated with these tests does not match the null hypothesis of actual interest. Indeed, due to genetic drift and possibly other additional noise components such as pool sequencing, the null variance in the data can be substantially larger than accounted for by these common test statistics. This leads to $p$-values that are systematically too small and, therefore, a huge number of false positive results. Even, if the ranking rather than the actual $p$-values is of interest, a naive application of the mentioned tests will give misleading results, as the amount of overdispersion varies from locus to locus. We therefore propose adjusted statistics that take the overdispersion into account while keeping the formulas simple. This is particularly useful in genome-wide applications, where millions of SNPs can be handled with little computational effort. We then apply the adapted test statistics to real data from Drosophila and investigate how information from intermediate generations can be included when available. We also discuss further applications such as genome-wide association studies based on pool sequencing data and tests for local adaptation.

Population Genomics on the Fly: Recent Advances in Drosophila.

Drosophila melanogaster, a small dipteran of African origin, represents one of the best-studied model organisms. Early work in this system has uniquely shed light on the basic principles of genetics and resulted in a versatile collection of genetic tools that allow to uncover mechanistic links between genotype and phenotype. Moreover, given its worldwide distribution in diverse habitats and its moderate genome-size, Drosophila has proven very powerful for population genetics inference and was one of the first eukaryotes whose genome was fully sequenced. In this book chapter, we provide a brief historical overview of research in Drosophila and then focus on recent advances during the genomic era. After describing different types and sources of genomic data, we discuss mechanisms of neutral evolution including the demographic history of Drosophila and the effects of recombination and biased gene conversion. Then, we review recent advances in detecting genome-wide signals of selection, such as soft and hard selective sweeps. We further provide a brief introduction to background selection, selection of noncoding DNA and codon usage and focus on the role of structural variants, such as transposable elements and chromosomal inversions, during the adaptive process. Finally, we discuss how genomic data helps to dissect neutral and adaptive evolutionary mechanisms that shape genetic and phenotypic variation in natural populations along environmental gradients. In summary, this book chapter serves as a starting point to Drosophila population genomics and provides an introduction to the system and an overview to data sources, important population genetic concepts and recent advances in the field.