scholarly journals Stochastic Demography and the Neutral Substitution Rate in Class-Structured Populations

Genetics ◽  
2014 ◽  
Vol 197 (1) ◽  
pp. 351-360 ◽  
Author(s):  
Laurent Lehmann
2017 ◽  
Vol 114 (44) ◽  
pp. 11582-11590 ◽  
Author(s):  
Russell Lande ◽  
Steinar Engen ◽  
Bernt-Erik Sæther

We analyze the stochastic demography and evolution of a density-dependent age- (or stage-) structured population in a fluctuating environment. A positive linear combination of age classes (e.g., weighted by body mass) is assumed to act as the single variable of population size, N, exerting density dependence on age-specific vital rates through an increasing function of population size. The environment fluctuates in a stationary distribution with no autocorrelation. We show by analysis and simulation of age structure, under assumptions often met by vertebrate populations, that the stochastic dynamics of population size can be accurately approximated by a univariate model governed by three key demographic parameters: the intrinsic rate of increase and carrying capacity in the average environment, r0 and K, and the environmental variance in population growth rate, σe2. Allowing these parameters to be genetically variable and to evolve, but assuming that a fourth parameter, θ, measuring the nonlinearity of density dependence, remains constant, the expected evolution maximizes E[Nθ]=[1−σe2/(2r0)]Kθ. This shows that the magnitude of environmental stochasticity governs the classical trade-off between selection for higher r0 versus higher K. However, selection also acts to decrease σe2, so the simple life-history trade-off between r- and K-selection may be obscured by additional trade-offs between them and σe2. Under the classical logistic model of population growth with linear density dependence (θ=1), life-history evolution in a fluctuating environment tends to maximize the average population size.


2009 ◽  
Vol 174 (6) ◽  
pp. 795-804 ◽  
Author(s):  
Steinar Engen ◽  
Russell Lande ◽  
Bernt‐Erik Sæther ◽  
F. Stephen Dobson

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Teame Gereziher MEHARI ◽  
Yanchao XU ◽  
Richard Odongo MAGWANGA ◽  
Muhammad Jawad UMER ◽  
Joy Nyangasi KIRUNGU ◽  
...  

Abstract Background Cotton is an important commercial crop for being a valuable source of natural fiber. Its production has undergone a sharp decline because of abiotic stresses, etc. Drought is one of the major abiotic stress causing significant yield losses in cotton. However, plants have evolved self-defense mechanisms to cope abiotic factors like drought, salt, cold, etc. The evolution of stress responsive transcription factors such as the trihelix, a nodule-inception-like protein (NLP), and the late embryogenesis abundant proteins have shown positive response in the resistance improvement to several abiotic stresses. Results Genome wide identification and characterization of the effects of Light-Harvesting Chloro a/b binding (LHC) genes were carried out in cotton under drought stress conditions. A hundred and nine proteins encoded by the LHC genes were found in the cotton genome, with 55, 27, and 27 genes found to be distributed in Gossypium hirsutum, G. arboreum, and G. raimondii, respectively. The proteins encoded by the genes were unevenly distributed on various chromosomes. The Ka/Ks (Non-synonymous substitution rate/Synonymous substitution rate) values were less than one, an indication of negative selection of the gene family. Differential expressions of genes showed that majority of the genes are being highly upregulated in the roots as compared with leaves and stem tissues. Most genes were found to be highly expressed in MR-85, a relative drought tolerant germplasm. Conclusion The results provide proofs of the possible role of the LHC genes in improving drought stress tolerance, and can be explored by cotton breeders in releasing a more drought tolerant cotton varieties.


2010 ◽  
Vol 78 (4) ◽  
pp. 239-249 ◽  
Author(s):  
Lee Worden ◽  
Louis W. Botsford ◽  
Alan Hastings ◽  
Matthew D. Holland

Genetics ◽  
1996 ◽  
Vol 142 (2) ◽  
pp. 629-639 ◽  
Author(s):  
Kent E Holsinger ◽  
Roberta J Mason-Gamer

Abstract Existing methods for analyzing nucleotide diversity require investigators to identify relevant hierarchical levels before beginning the analysis. We describe a method that partitions diversity into hierarchical components while allowing any structure present in the data to emerge naturally. We present an unbiased version of Nei's nucleotide diversity statistics and show that our modification has the same properties as Wright's  F  ST. We compare its statistical properties with several other F  ST estimators, and we describe how to use these statistics to produce a rooted tree of relationships among the sampled populations in which the mean time to coalescence of haplotypes drawn from populations belonging to the same node is smaller than the mean time to coalescence of haplotypes drawn from populations belonging to different nodes. We illustrate the method by applying it to data from a recent survey of restriction site variation in the chloroplast genome of Coreopsis grandiflora.


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