scholarly journals Reducing bias in population and landscape genetic inferences: the effects of sampling related individuals and multiple life stages

PeerJ ◽  
2016 ◽  
Vol 4 ◽  
pp. e1813 ◽  
Author(s):  
William Peterman ◽  
Emily R. Brocato ◽  
Raymond D. Semlitsch ◽  
Lori S. Eggert
Keyword(s):  
Best Practice ◽  
Isolation By Distance ◽  
Life Stage ◽  
Population Sample ◽  
Life Stages ◽  
Effective Population ◽  
Data Set ◽  
Sibling Pairs ◽  
Population Sizes ◽  
Landscape Genetic

In population or landscape genetics studies, an unbiased sampling scheme is essential for generating accurate results, but logistics may lead to deviations from the sample design. Such deviations may come in the form of sampling multiple life stages. Presently, it is largely unknown what effect sampling different life stages can have on population or landscape genetic inference, or how mixing life stages can affect the parameters being measured. Additionally, the removal of siblings from a data set is considered best-practice, but direct comparisons of inferences made with and without siblings are limited. In this study, we sampled embryos, larvae, and adultAmbystoma maculatumfrom five ponds in Missouri, and analyzed them at 15 microsatellite loci. We calculated allelic richness, heterozygosity and effective population sizes for each life stage at each pond and tested for genetic differentiation (FSTandDC) and isolation-by-distance (IBD) among ponds. We tested for differences in each of these measures between life stages, and in a pooled population of all life stages. All calculations were done with and without sibling pairs to assess the effect of sibling removal. We also assessed the effect of reducing the number of microsatellites used to make inference. No statistically significant differences were found among ponds or life stages for any of the population genetic measures, but patterns of IBD differed among life stages. There was significant IBD when using adult samples, but tests using embryos, larvae, or a combination of the three life stages were not significant. We found that increasing the ratio of larval or embryo samples in the analysis of genetic distance weakened the IBD relationship, and when usingDC, the IBD was no longer significant when larvae and embryos exceeded 60% of the population sample. Further, power to detect an IBD relationship was reduced when fewer microsatellites were used in the analysis.

scholarly journals Reducing bias in population and landscape genetic inferences: The effects of sampling related individuals and multiple life stages

2015 ◽  
Author(s):  
William Peterman ◽  
Emily R Brocato ◽  
Raymond D Semlitsch ◽  
Lori S Eggert
Keyword(s):  
Isolation By Distance ◽  
Life Stage ◽  
Population Sample ◽  
Life Stages ◽  
Effective Population ◽  
Sibling Pairs ◽  
Target Sample Size ◽  
Population Sizes ◽  
Landscape Genetic ◽  
Genetic Inference

In population or landscape genetics studies, an unbiased sampling scheme is essential for generating accurate results, but logistics may lead to deviations from the sample design. Such deviations may come in the form of sampling multiple life stages. Presently, it is largely unknown what effect sampling different life stages can have on population or landscape genetic inference, or how mixing life stages can affect the parameters being measured. In this study, we sampled embryos, larvae, and adult Ambystoma maculatum from five ponds in Missouri, and analyzed them at 15 microsatellite loci. We calculated allelic richness, heterozygosity and effective population sizes for each life stage at each pond and tested for genetic differentiation (FST and DC) and isolation-by-distance (IBD) among ponds. We tested for differences in each of these measures between life stages, and in a pooled population of all life stages. All calculations were done with and without sibling pairs to assess the effect of sibling removal. No statistically significant differences were found among ponds or life stages for any of the population genetic measures, but patterns of IBD differed among life stages. There was significant IBD when using adult samples, but tests using embryos, larvae, or a combination of the three life stages were not significant. Further, we found that increasing the ratio of larval or embryo samples in the analysis of genetic distance weakened the IBD relationship, and when using DC, the IBD was no longer significant when larvae and embryos exceeded 60% of the population sample. Our findings suggest that it may be possible to mix life stages to reach target sample size quotas, but researchers should nonetheless proceed with caution depending upon the goals and objectives of the study.

scholarly journals Reducing bias in population and landscape genetic inferences: The effects of sampling related individuals and multiple life stages

2015 ◽  
Author(s):  
William Peterman ◽  
Emily R Brocato ◽  
Raymond D Semlitsch ◽  
Lori S Eggert
Keyword(s):  
Isolation By Distance ◽  
Life Stage ◽  
Population Sample ◽  
Life Stages ◽  
Effective Population ◽  
Sibling Pairs ◽  
Target Sample Size ◽  
Population Sizes ◽  
Landscape Genetic ◽  
Genetic Inference

In population or landscape genetics studies, an unbiased sampling scheme is essential for generating accurate results, but logistics may lead to deviations from the sample design. Such deviations may come in the form of sampling multiple life stages. Presently, it is largely unknown what effect sampling different life stages can have on population or landscape genetic inference, or how mixing life stages can affect the parameters being measured. In this study, we sampled embryos, larvae, and adult Ambystoma maculatum from five ponds in Missouri, and analyzed them at 15 microsatellite loci. We calculated allelic richness, heterozygosity and effective population sizes for each life stage at each pond and tested for genetic differentiation (FST and DC) and isolation-by-distance (IBD) among ponds. We tested for differences in each of these measures between life stages, and in a pooled population of all life stages. All calculations were done with and without sibling pairs to assess the effect of sibling removal. No statistically significant differences were found among ponds or life stages for any of the population genetic measures, but patterns of IBD differed among life stages. There was significant IBD when using adult samples, but tests using embryos, larvae, or a combination of the three life stages were not significant. Further, we found that increasing the ratio of larval or embryo samples in the analysis of genetic distance weakened the IBD relationship, and when using DC, the IBD was no longer significant when larvae and embryos exceeded 60% of the population sample. Our findings suggest that it may be possible to mix life stages to reach target sample size quotas, but researchers should nonetheless proceed with caution depending upon the goals and objectives of the study.

scholarly journals Distribution of gene tree histories under the coalescent model with gene flow

2015 ◽  
Author(s):  
Yuan Tian ◽  
Laura Kubatko
Keyword(s):  
Gene Flow ◽  
Maximum Likelihood ◽  
Gene Tree ◽  
Species Tree ◽  
Tree Topology ◽  
Effective Population ◽  
Sequence Alignments ◽  
Data Set ◽  
Coalescent Model ◽  
Population Sizes

We propose a coalescent model for three species that allows gene flow between both pairs of sister populations. The model is designed to analyze multilocus genomic sequence alignments, with one sequence sampled from each of the three species. The model is formulated using a Markov chain representation, which allows use of matrix exponentiation to compute analytical expressions for the probability density of gene tree genealogies. The gene tree history distribution as well as the gene tree topology distribution under this coalescent model with gene flow are then calculated via numerical integration. We analyze the model to compare the distributions of gene tree topologies and gene tree histories for species trees with differing effective population sizes and gene flow rates. Our results suggest conditions under which the species tree and associated parameters are not identifiable from the gene tree topology distribution when gene flow is present, but indicate that the gene tree history distribution may identify the species tree and associated parameters. Thus, the gene tree history distribution can be used to infer parameters such as the ancestral effective population sizes and the rates of gene flow in a maximum likelihood (ML) framework. We conduct computer simulations to evaluate the performance of our method in estimating these parameters, and we apply our method to an Afrotropical mosquito data set (Fontaine et al., 2015) to demonstrate the usefulness of our method for the analysis of empirical data. Key words: coalescent, gene flow, migration, hybridization, gene tree, topology, history, maximum likelihood, speciation.

scholarly journals Detection and stage classification of Plasmodium falciparum from images of Giemsa stained thin blood films using random forest classifiers

2020 ◽  
Vol 15 (1) ◽  
Author(s):  
Syed Saiden Abbas ◽  
Tjeerd M. H. Dijkstra
Keyword(s):  
Random Forest ◽  
Life Stage ◽  
Average Intensity ◽  
Life Stages ◽  
Dice Coefficient ◽  
Malaria Parasites ◽  
Data Set ◽  
Otsu Method ◽  
Stage Classification

Abstract Background The conventional method for the diagnosis of malaria parasites is the microscopic examination of stained blood films, which is time consuming and requires expertise. We introduce computer-based image segmentation and life stage classification with a random forest classifier. Segmentation and stage classification are performed on a large dataset of malaria parasites with ground truth labels provided by experts. Methods We made use of Giemsa stained images obtained from the blood of 16 patients infected with Plasmodium falciparum. Experts labeled the parasite types from each of the images. We applied a two-step approach: image segmentation followed by life stage classification. In segmentation, we classified each pixel as a parasite or non-parasite pixel using a random forest classifier. Performance was evaluated with classification accuracy, Dice coefficient and free-response receiver operating characteristic (FROC) analysis. In life stage classification, we classified each of the segmented objects into one of 8 classes: 6 parasite life stages, early ring, late ring or early trophozoite, mid trophozoite, early schizont, late schizont or segmented, and two other classes, white blood cell or debris. Results Our segmentation method gives an average cross-validated Dice coefficient of 0.82 which is a 13% improvement compared to the Otsu method. The Otsu method achieved a True Positive Fraction (TPF) of 0.925 at the expense of a False Positive Rate (FPR) of 2.45. At the same TPF of 0.925, our method achieved an FPR of 0.92, an improvement by more than a factor two. We find that inclusion of average intensity of the whole image as feature for the random forest considerably improves segmentation performance. We obtain an overall accuracy of 58.8% when classifying all life stages. Stages are mostly confused with their neighboring stages. When we reduce the life stages to ring, trophozoite and schizont only, we obtain an accuracy of 82.7%. Conclusion Pixel classification gives better segmentation performance than the conventional Otsu method. Effects of staining and background variations can be reduced with the inclusion of average intensity features. The proposed method and data set can be used in the development of automatic tools for the detection and stage classification of malaria parasites. The data set is publicly available as a benchmark for future studies.

scholarly journals Whole-genome sequences suggest long term declines of spotted owl (Strix occidentalis) (Aves: Strigiformes: Strigidae) populations in California

2018 ◽  
Author(s):  
Zachary R. Hanna ◽  
John P. Dumbacher ◽  
Rauri C.K. Bowie ◽  
Jeffrey D. Wall
Keyword(s):  
Isolation By Distance ◽  
Whole Genome ◽  
Population Declines ◽  
Effective Population ◽  
Spotted Owl ◽  
Strix Occidentalis ◽  
Genome Data ◽  
Population Sizes ◽  
California Spotted Owl

AbstractWe analyzed whole-genome data of four spotted owls (Strix occidentalis) to provide a broad-scale assessment of the genome-wide nucleotide diversity across S. occidentalis populations in California. We assumed that each of the four samples was representative of its population and we estimated effective population sizes through time for each corresponding population. Our estimates provided evidence of long-term population declines in all California S. occidentalis populations. We found no evidence of genetic differentiation between northern spotted owl (S. o. caurina) populations in the counties of Marin and Humboldt in California. We estimated greater differentiation between populations at the northern and southern extremes of the range of the California spotted owl (S. o. occidentalis) than between populations of S. o. occidentalis and S. o. caurina in northern California. The San Diego County S. o. occidentalis population was substantially diverged from the other three S. occidentalis populations. These whole-genome data support a pattern of isolation-by-distance across spotted owl populations in California, rather than elevated differentiation between currently recognized subspecies.

Testing theoretical metapopulation conditions with genotypic data from Boreal Chorus Frogs (Pseudacris maculata)

2019 ◽  
Vol 97 (11) ◽  
pp. 1042-1053
Author(s):  
Shawn M. Billerman ◽  
Brett R. Jesmer ◽  
Alexander G. Watts ◽  
Peter E. Schlichting ◽  
Marie-Josée Fortin ◽  
...  
Keyword(s):  
Demographic Data ◽  
Methodological Framework ◽  
Effective Population ◽  
Pseudacris Maculata ◽  
Breeding Populations ◽  
Chorus Frogs ◽  
Population Sizes ◽  
Feasible Alternative ◽  
Landscape Genetic

The metapopulation concept has far-reaching implications in ecology and conservation biology. Hanski’s criteria operationally define metapopulations, yet testing them is hindered by logistical and financial constraints inherent to the collection of long-term demographic data. Hence, ecologists and conservationists often assume metapopulation existence for dispersal-limited species that occupy patchy habitats. To advance understanding of metapopulation theory and improve conservation of metapopulations, we used population and landscape genetic tools to develop a methodological framework for evaluating Hanski’s criteria. We used genotypic data (11 microsatellite loci) from a purported metapopulation of Boreal Chorus Frogs (Pseudacris maculata (Agassiz, 1850)) in Colorado, U.S.A., to test Hanski’s four criteria. We found support for each criterion: (1) significant genetic differentiation between wetlands, suggesting distinct breeding populations; (2) wetlands had small effective population sizes and recent bottlenecks, suggesting populations do not experience long-term persistence; (3) population graphs provided evidence of gene flow between patches, indicating potential for recolonization; and (4) multiscale bottleneck analyses suggest asynchrony, indicating that simultaneous extinction of all populations was unlikely. Our methodological framework provides a logistically and financially feasible alternative to long-term demographic data for identifying amphibian metapopulations.

scholarly journals Contribution of spatial heterogeneity in effective population sizes to the variance in pairwise measures of genetic differentiation

2015 ◽  
Author(s):  
Jérôme G. Prunier ◽  
Vincent Dubut ◽  
Lounès Chikhi ◽  
Simon Blanchet
Keyword(s):  
Genetic Variation ◽  
Genetic Differentiation ◽  
Spatial Heterogeneity ◽  
Landscape Genetics ◽  
Isolation By Distance ◽  
List Type ◽  
Unique Contribution ◽  
Landscape Resistance ◽  
Effective Population ◽  
Population Sizes

SummaryPairwise measures of neutral genetic differentiation are supposed to contain information about past and on-going dispersal events and are thus often used as dependent variables in correlative analyses to elucidate how neutral genetic variation is affected by landscape connectivity. However, spatial heterogeneity in the intensity of genetic drift, stemming from variations in population sizes, may inflate variance in measures of genetic differentiation and lead to erroneous or incomplete interpretations in terms of connectivity. Here, we tested the efficiency of two distance-based metrics designed to capture the unique influence of spatial heterogeneity in local drift on genetic differentiation. These metrics are easily computed from estimates of effective population sizes or from environmental proxies for local carrying capacities, and allow us to introduce the hypothesis of Spatial-Heterogeneity-in-Effective-Population-Sizes (SHNe). SHNe can be tested in a way similar to isolation-by-distance or isolation-by-resistance within the classical landscape genetics hypothesis-testing framework.We used simulations under various models of population structure to investigate the reliability of these metrics to quantify the unique contribution of SHNe in explaining patterns of genetic differentiation. We then applied these metrics to an empirical genetic dataset obtained for a freshwater fish (Gobio occitaniae).Simulations showed that SHNe explained up to 60% of variance in genetic differentiation (measured as Fst) in the absence of gene flow, and up to 20% when migration rates were as high as 0.10. Furthermore, one of the two metrics was particularly robust to uncertainty in the estimation of effective population sizes (or proxies for carrying capacity). In the empirical dataset, the effect of SHNe on spatial patterns of Fst was five times higher than that of isolation-by-distance, uniquely contributing to 41% of variance in pairwise Fst. Taking the influence of SHNe into account also allowed decreasing the signal-to-noise ratio, and improving the upper estimate of effective dispersal distance.We conclude that the use of SHNe metrics in landscape genetics will substantially improve the understanding of evolutionary drivers of genetic variation, providing substantial information as to the actual drivers of patterns of genetic differentiation in addition to traditional measures of Euclidean distance or landscape resistance.

‘And all my children?’

2018 ◽  
Author(s):  
Charlotte Scott
Keyword(s):  
Early Modern ◽  
Life Stage ◽  
Early Modern Period ◽  
Life Stages ◽  
Cultural Imagination ◽  
Modern Period

Beginning with an exploration of the role of the child in the cultural imagination, Chapter 1 establishes the formative and revealing ways in which societies identify themselves in relation to how they treat their children. Focusing on Shakespeare and the early modern period, Chapter 1 sets out to determine the emotional, symbolic, and political registers through which children are depicted and discussed. Attending to the different life stages and representations of the child on stage, this chapter sets out the terms of the book’s enquiry: what role do children play in Shakespeare’s plays; how do we recognize them as such—age, status, parental dynamic—and what are the effects of their presence? This chapter focuses on how the early moderns understood the child, as a symbolic figure, a life stage, a form of obligation, a profound bond, and an image of servitude.

scholarly journals EFFECTS OF POPULATION SIZE AND SELECTION INTENSITY ON SHORT-TERM RESPONSE TO SELECTION FOR POSTWEANING GAIN IN MICE

Genetics ◽  
1973 ◽  
Vol 73 (3) ◽  
pp. 513-530
Author(s):  
J P Hanrahan ◽  
E J Eisen ◽  
J E Legates
Keyword(s):  
Population Size ◽  
Selection Response ◽  
Selection Intensity ◽  
Realized Heritability ◽  
Family Selection ◽  
Effective Population ◽  
Population Sizes ◽  
Selection For ◽  
Selection Intensities ◽  
Term Response

ABSTRACT The effects of population size and selection intensity on the mean response was examined after 14 generations of within full-sib family selection for postweaning gain in mice. Population sizes of 1, 2, 4, 8 and 16 pair matings were each evaluated at selection intensities of 100% (control), 50% and 25% in a replicated experiment. Selection response per generation increased as selection intensity increased. Selection response and realized heritability tended to increase with increasing population size. Replicate variability in realized heritability was large at population sizes of 1, 2 and 4 pairs. Genetic drift was implicated as the primary factor causing the reduced response and lowered repeatability at the smaller population sizes. Lines with intended effective population sizes of 62 yielded larger selection responses per unit selection differential than lines with effective population sizes of 30 or less.

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