scholarly journals Stabilizing the dynamics of laboratory populations ofDrosophila melanogasterthrough upper and lower limiter controls

2015 ◽  
Author(s):  
Sudipta Tung ◽  
Abhishek Mishra ◽  
Sutirth Dey
Keyword(s):  
Population Size ◽  
Effective Population Size ◽  
Real Life ◽  
Extinction Probability ◽  
Population Fluctuations ◽  
Control Methods ◽  
Effective Population ◽  
Population Dynamics Model ◽  
Wide Range ◽  
Laboratory Populations

Although a large number of methods exist to control the dynamics of populations to a desired state, few of them have been empirically validated. This limits the scope of using these methods in real-life scenarios. To address this issue, we tested the efficacy of two well-known control methods in enhancing different kinds of stability in highly fluctuating, extinction-prone populations ofDrosophila melanogaster. The Upper Limiter Control (ULC) method was able to reduce the fluctuations in population sizes as well as the extinction probability of the populations. On the negative side, it had no effect on the effective population size and required a large amount of effort. On the other hand, Lower Limiter Control (LLC) enhanced effective population size and reduced extinction probability at a relatively low amount of effort. However, its effects on population fluctuations were equivocal. We examined the population size distributions with and without the control methods, to derive biologically intuitive explanations for how these control methods work. We also show that biologically-realistic simulations, using a very general population dynamics model, are able to capture most of the trends of our data. This suggests that our results are likely to be generalizable to a wide range of scenarios.

scholarly journals Inferring population size history from large samples of genome wide molecular data - an approximate Bayesian computation approach

2016 ◽  
Author(s):  
Simon Boitard ◽  
Willy Rodriguez ◽  
Flora Jay ◽  
Stefano Mona ◽  
Frederic Austeritz
Keyword(s):  
Population Genetics ◽  
Population Size ◽  
Effective Population Size ◽  
Approximate Bayesian Computation ◽  
Recent Common Ancestor ◽  
Bayesian Computation ◽  
Effective Population ◽  
Wide Range ◽  
Complete Genomes ◽  
Approximate Bayesian

Inferring the ancestral dynamics of effective population size is a long-standing question in population genetics, which can now be tackled much more accurately thanks to the massive genomic data available in many species. Several promising methods that take advantage of whole-genome sequences have been recently developed in this context. However, they can only be applied to rather small samples, which limits their ability to estimate recent population size history. Besides, they can be very sensitive to sequencing or phasing errors. Here we introduce a new approximate Bayesian computation approach named PopSizeABC that allows estimating the evolution of the effective population size through time, using a large sample of complete genomes. This sample is summarized using the folded allele frequency spectrum and the average zygotic linkage disequilibrium at different bins of physical distance, two classes of statistics that are widely used in population genetics and can be easily computed from unphased and unpolarized SNP data. Our approach provides accurate estimations of past population sizes, from the very first generations before present back to the expected time to the most recent common ancestor of the sample, as shown by simulations under a wide range of demographic scenarios. When applied to samples of 15 or 25 complete genomes in four cattle breeds (Angus, Fleckvieh, Holstein and Jersey), PopSizeABC revealed a series of population declines, related to historical events such as domestication or modern breed creation. We further highlight that our approach is robust to sequencing errors, provided summary statistics are computed from SNPs with common alleles.

scholarly journals Comparison of genetic variation between rare and common congeners of Dipodomys with estimates of contemporary and historical effective population size

2021 ◽  
Author(s):  
Michaela Halsey ◽  
John Stuhler ◽  
Natalia J Bayona-Vasquez ◽  
Roy N Platt ◽  
Jim R Goetze ◽  
...  
Keyword(s):  
Genetic Diversity ◽  
Genetic Variation ◽  
Population Size ◽  
Effective Population Size ◽  
Population Fluctuations ◽  
Nucleotide Polymorphisms ◽  
Effective Population ◽  
Single Nucleotide ◽  
Demographic Dynamics ◽  
Population Sizes

Organisms with low effective population sizes are at greater risk of extinction because of reduced genetic diversity.   Dipodomys elator  is a kangaroo rat that is classified as threatened in Texas and field surveys from the past 50 years indicate that the distribution of this species has decreased. This suggests geographic range reductions that could have caused population fluctuations, potentially impacting effective population size. Conversely, the more common and widespread  D. ordii  is thought to exhibit relative geographic and demographic stability. Genetic variation between  D. elator  and  D. ordii  samples was assessed using 3RAD, a modified restriction site associated sequencing approach. It was hypothesized that  D. elator  would show lower levels of nucleotide diversity, observed heterozygosity, and effective population size when compared to  D. ordii . Also of interest was identifying population structure within contemporary samples of  D. elator  and detecting genetic variation between temporal samples that could indicate demographic dynamics. Up to 61,000 single nucleotide polymorphisms were analyzed. It was determined that genetic variability and effective population size in contemporary  D. elator  populations were lower than that of  D. ordii, that there is only slight, if any, structure within contemporary  D. elator  populations, and there is little genetic differentiation between spatial or temporal historical samples suggesting little change in nuclear genetic diversity over 30 years. Results suggest that genetic diversity of  D. elator  has remained stable despite claims of reduced population size and/or abundance, which may indicate a metapopulation-like system, whose fluctuations might counteract any immediate decrease in fitness.

scholarly journals A pseudo-likelihood method for estimating effective population size from temporally spaced samples

2001 ◽  
Vol 78 (3) ◽  
pp. 243-257 ◽  
Author(s):  
JINLIANG WANG
Keyword(s):  
Population Size ◽  
Effective Population Size ◽  
Growth Parameters ◽  
Computing Time ◽  
Likelihood Method ◽  
Effective Population ◽  
Data Set ◽  
Statistic Method ◽  
Pseudo Likelihood ◽  
Wide Range

A pseudo maximum likelihood method is proposed to estimate effective population size (Ne) using temporal changes in allele frequencies at multi-allelic loci. The computation is simplified dramatically by (1) approximating the multi-dimensional joint probabilities of all the data by the product of marginal probabilities (hence the name pseudo-likelihood), (2) exploiting the special properties of transition matrix and (3) using a hidden Markov chain algorithm. Simulations show that the pseudo-likelihood method has a similar performance but needs much less computing time and storage compared with the full likelihood method in the case of 3 alleles per locus. Due to computational developments, I was able to assess the performance of the pseudo-likelihood method against the F-statistic method over a wide range of parameters by extensive simulations. It is shown that the pseudo-likelihood method gives more accurate and precise estimates of Ne than the F-statistic method, and the performance difference is mainly due to the presence of rare alleles in the samples. The pseudo-likelihood method is also flexible and can use three or more temporal samples simultaneously to estimate satisfactorily the Nes of each period, or the growth parameters of the population. The accuracy and precision of both methods depend on the ratio of the product of sample size and the number of generations involved to Ne, and the number of independent alleles used. In an application of the pseudo-likelihood method to a large data set of an olive fly population, more precise estimates of Ne are obtained than those from the F-statistic method.

Simultaneous enhancement of multiple stability properties using two-parameter control methods inDrosophila melanogaster

2015 ◽  
Author(s):  
Sudipta Tung ◽  
Abhishek Mishra ◽  
Sutirth Dey
Keyword(s):  
Parameter Control ◽  
Population Fluctuations ◽  
Control Methods ◽  
Effective Population ◽  
Linear Dynamics ◽  
Wide Range ◽  
Population Sizes ◽  
Almost All ◽  
Two Parameter ◽  
Multiple Stability

Although a large number of methods have been proposed to control the non-linear dynamics of unstable populations, very few have been actually adopted for application. One reason for this gap is the fact that few control methods have been empirically verified using biological populations. To address this issue, we investigated the effects of two well-studied control methods (Both Limiter Control and Target-Oriented Control) on the dynamics of unstable populations ofDrosophila melanogaster. We show that both methods can significantly reduce population fluctuations, decrease extinction probability and increase effective population size simultaneously. This is in contrast with single parameter control methods that are not able to achieve multiple aspects of stability at the same time. We use the distribution of population sizes to derive biologically intuitive explanations for the mechanisms of how these two control methods attain stability. Finally, we show that non-Drosophila specific biologically realistic simulations are able to capture almost all the trends of our data. This shows that our results are likely generalizable over a wide range of taxa. The primary insight of our study is that control methods that incorporate both culling and restocking have better all-round performance in terms of stabilizing populations.

The Nonadaptive Forces of Evolution

2018 ◽  
Author(s):  
Bruce Walsh ◽  
Michael Lynch
Keyword(s):  
Population Size ◽  
Effective Population Size ◽  
Mutation Rate ◽  
Recombination Rate ◽  
Effective Population ◽  
Evolutionary Forces ◽  
Wide Range ◽  
Population Sizes ◽  
Genomic Results

This chapter examines the relative strengths of the nonadaptive evolutionary forces (drift, mutation, recombination) acting on genomes. It reviews estimators for effective population size, mutation rate, and recombination rate, and summarizes the known genomic results over a wide range of taxa. The mutation rate tends to be lower in organisms with larger effective population sizes, consistent with the drift-barrier hypothesis wherein selection is ineffective when it is less than the reciprocal of the effective population size.

scholarly journals Codon usage bias in animals: disentangling the effects of natural selection, effective population size and GC-biased gene conversion

2017 ◽  
Author(s):  
N. Galtier ◽  
C. Roux ◽  
M. Rousselle ◽  
J. Romiguier ◽  
E. Figuet ◽  
...  
Keyword(s):  
Natural Selection ◽  
Codon Usage ◽  
Population Size ◽  
Gene Conversion ◽  
Effective Population Size ◽  
Codon Usage Bias ◽  
Effective Population ◽  
Translational Selection ◽  
Wide Range ◽  
Biased Gene Conversion

AbstractSelection on codon usage bias is well documented in a number of microorganisms. Whether codon usage is also generally shaped by natural selection in large organisms, despite their relatively small effective population size (Ne), is unclear. Codon usage bias in animals has only been studied in a handful of model organisms so far, and can be affected by confounding, non-adaptive processes such as GC-biased gene conversion and experimental artefacts. Using population transcriptomics data we analysed the relationship between codon usage, gene expression, allele frequency distribution and recombination rate in 31 non-model species of animals, each from a different family, covering a wide range of effective population sizes. We disentangled the effects of translational selection and GC-biased gene conversion on codon usage by separately analysing GC-conservative and GC-changing mutations. We report evidence for effective translational selection on codon usage in large-Ne species of animals, but not in small-Ne ones, in agreement with the nearly neutral theory of molecular evolution. C- and T-ending codons are generally preferred over synonymous G- and A-ending ones, for reasons that remain to be determined. In contrast, we uncovered a conspicuous effect of GC-biased gene conversion, which is widespread in animals and the main force determining the fate of AT↔GC mutations. Intriguingly, the strength of its effect was uncorrelated with Ne.

scholarly journals Effective population size and evolutionary dynamics in outbred laboratory populations of Drosophila

2013 ◽  
Vol 92 (3) ◽  
pp. 349-361 ◽  
Author(s):  
LAURENCE D. MUELLER ◽  
AMITABH JOSHI ◽  
MARTA SANTOS ◽  
MICHAEL R. ROSE
Keyword(s):  
Population Size ◽  
Effective Population Size ◽  
Evolutionary Dynamics ◽  
Effective Population ◽  
Laboratory Populations

scholarly journals An examination of genetic diversity and effective population size in Atlantic salmon populations

2009 ◽  
Vol 91 (6) ◽  
pp. 395-412 ◽  
Author(s):  
NATACHA NIKOLIC ◽  
JAMES R. A. BUTLER ◽  
JEAN-LUC BAGLINIÈRE ◽  
ROBERT LAUGHTON ◽  
IAIN A. G. McMYN ◽  
...  
Keyword(s):  
Genetic Diversity ◽  
Atlantic Salmon ◽  
Population Size ◽  
Effective Population Size ◽  
Demographic History ◽  
Effective Population ◽  
High Genetic Diversity ◽  
Historical Processes ◽  
Wide Range ◽  
Microsatellite Dna Markers

SummaryEffective population size (Ne) is an important parameter in the conservation of genetic diversity. Comparative studies of empirical data that gauge the relative accuracy of Ne methods are limited, and a better understanding of the limitations and potential of Ne estimators is needed. This paper investigates genetic diversity and Ne in four populations of wild anadromous Atlantic salmon (Salmo salar L.) in Europe, from the Rivers Oir and Scorff (France) and Spey and Shin (Scotland). We aimed to understand present diversity and historical processes influencing current population structure. Our results showed high genetic diversity for all populations studied, despite their wide range of current effective sizes. To improve understanding of high genetic diversity observed in the populations with low effective size, we developed a model predicting present diversity as a function of past demographic history. This suggested that high genetic diversity could be explained by a bottleneck occurring within recent centuries rather than by gene flow. Previous studies have demonstrated the efficiency of coalescence models to estimate Ne. Using nine subsets from 37 microsatellite DNA markers from the four salmon populations, we compared three coalescence estimators based on single and dual samples. Comparing Ne estimates confirmed the efficiency of increasing the number and variability of microsatellite markers. This efficiency was more accentuated for the smaller populations. Analysis with low numbers of neutral markers revealed uneven distributions of allelic frequencies and overestimated short-term Ne. In addition, we found evidence of artificial stock enhancement using native and non-native origin. We propose estimates of Ne for the four populations, and their applications for salmon conservation and management are discussed.

scholarly journals Close-kin methods to estimate census size and effective population size

2021 ◽  
Author(s):  
Robin S. Waples ◽  
Pierre Feutry
Keyword(s):  
Population Size ◽  
Effective Population Size ◽  
Estimation Methods ◽  
Vital Rates ◽  
Effective Population ◽  
Census Size ◽  
Wide Range ◽  
Close Relatives ◽  
Evolutionary Consequences ◽  
Joint Evaluation

AbstractThe last two decades have witnessed rapid developments and increasing interest in use of (1) genetic methods to estimate effective population size (Ne) and (2) close-kin mark-recapture (CKMR) methods to estimate abundance based on the incidence of close relatives. Whereas Ne-estimation methods have been applied to a wide range of taxa, all CKMR applications to date have been for aquatic species. These two fields of inquiry have developed largely independently, and this is unfortunate because deepest insights can be gained by joint evaluation of eco-evolutionary processes. In this synthesis, we outline factors (life-history traits; experimental design; stochasticity; ancillary information) that should be considered in identifying good candidate species and determining sampling/analytical regimes that can produce meaningful estimates. We show that the Ne/N ratio and the probability of a close-kin match both depend on a vector of parental weights that specify relative probabilities that different individuals will produce offspring. Although age-specific vital rates are central to both methodologies, for CKMR they are nuisance parameters that can bias abundance estimates unless properly accounted for, whereas they represent the signals of genetic drift that Ne estimation methods depend on. The most robust implementations of CKMR incorporate information from both parent-offspring pairs and siblings into a single, overarching framework, within which all demographic parameters can be jointly estimated in a way that allows coherent statements about uncertainty. Coordinating Ne and CKMR estimation methods using the same or overlapping datasets would facilitate joint evaluation of both the ecological and evolutionary consequences of abundance.

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