Population dynamics, demographic stochasticity, and the evolution of cooperation

A basic evolutionary problem posed by the Iterated Prisoner’s Dilemma game is to understand when the paradigmatic cooperative strategy Tit-for-Tat can invade a population of pure defectors. Deterministically, this is impossible. We consider the role of demographic stochasticity by embedding the Iterated Prisoner’s Dilemma into a population dynamic framework. Tit-for-Tat can invade a population of defectors when their dynamics exhibit short episodes of high population densities with subsequent crashes and long low density periods with strong genetic drift. Such dynamics tend to have reddened power spectra and temporal distributions of population size that are asymmetric and skewed toward low densities. The results indicate that ecological dynamics are important for evolutionary shifts between adaptive peaks.

Modeling and optimization of populations subject to time-dependent mutation.

It has become clear that many organisms possess the ability to regulate their mutation rate in response to environmental conditions. So the question of finding an optimal mutation rate must be replaced by that of finding an optimal mutation schedule. We show that this task cannot be accomplished with standard population-dynamic models. We then develop a "hybrid" model for populations experiencing time-dependent mutation that treats population growth as deterministic but the time of first appearance of new variants as stochastic. We show that the hybrid model agrees well with a Monte Carlo simulation. From this model, we derive a deterministic approximation, a "threshold" model, that is similar to standard population dynamic models but differs in the initial rate of generation of new mutants. We use these techniques to model antibody affinity maturation by somatic hypermutation. We had previously shown that the optimal mutation schedule for the deterministic threshold model is phasic, with periods of mutation between intervals of mutation-free growth. To establish the validity of this schedule, we now show that the phasic schedule that optimizes the deterministic threshold model significantly improves upon the best constant-rate schedule for the hybrid and Monte Carlo models.

γ-Aminobutyric acid type B receptor-dependent burst-firing in thalamic neurons: A dynamic clamp study

Synchronized network responses in thalamus depend on phasic inhibition originating in the thalamic reticular nucleus (nRt) and are mediated by the neurotransmitter γ-aminobutyric acid (GABA). A suggested role for intra-nRt connectivity in inhibitory phasing remains controversial. Recently, functional GABA type B (GABAB) receptors were demonstrated on nRt cells, and the slow time course of the GABAB synaptic response seems ideally suited to deinactivate low-threshold calcium channels. This promotes burst firing, a characteristic feature of synchronized responses. Here we investigate GABAB-mediated rebound burst firing in thalamic cells. Whole-cell current-clamp recordings were obtained from nRt cells and somatosensory thalamocortical relay cells in rat brain slices. Synthetic GABAB inhibitory postsynaptic potentials, generated by a hybrid computer–neuron synapse (dynamic clamp), triggered rebound low-threshold calcium spikes in both cell types when peak inhibitory postsynaptic potential hyperpolarization was greater than −92 mV. The threshold inhibitory postsynaptic potential conductance for rebound burst generation was comparable in nRt (7 nS) and thalamocortical (5 nS) cells. However, burst onset in nRt (1 s) was considerably delayed compared with thalamocortical (0.6 s) cells. Thus, GABAB inhibitory postsynaptic potentials can elicit low-threshold calcium spikes in both relay and nRt neurons, but the resultant oscillation frequency would be faster for thalamocortical–nRt networks (3 Hz) than for nRt–nRt networks (1–2 Hz). We conclude, therefore, that fast (>2 Hz) GABAB-dependent thalamic oscillations are maintained primarily by reciprocal connections between excitatory and inhibitory cells. These findings further indicate that when oscillatory neural networks contain both recurrent and reciprocal inhibition, then distinct population frequencies may result when one or the other type of inhibition is favored.

Population genetics of Ice Age brown bears

The Pleistocene was a dynamic period for Holarctic mammal species, complicated by episodes of glaciation, local extinctions, and intercontinental migration. The genetic consequences of these events are difficult to resolve from the study of present-day populations. To provide a direct view of population genetics in the late Pleistocene, we measured mitochondrial DNA sequence variation in seven permafrost-preserved brown bear (Ursus arctos) specimens, dated from 14,000 to 42,000 years ago. Approximately 36,000 years ago, the Beringian brown bear population had a higher genetic diversity than any extant North American population, but by 15,000 years ago genetic diversity appears similar to the modern day. The older, genetically diverse, Beringian population contained sequences from three clades now restricted to local regions within North America, indicating that current phylogeographic patterns may provide misleading data for evolutionary studies and conservation management. The late Pleistocene phylogeographic data also indicate possible colonization routes to areas south of the Cordilleran ice sheet.

Dynamic expression of multiple scavenger receptor cysteine-rich genes in coelomocytes of the purple sea urchin

Coelomocytes, the heterogeneous population of sea urchin putative immune cells, were found to express a complex set of transcripts featuring scavenger receptor cysteine-rich (SRCR) repeats. SRCR domains define a metazoan superfamily of proteins, many of which are implicated in development and regulation of the immune system of vertebrates. Coelomocytes transcribe multiple SRCR genes from among a multigene family encoding an estimated number of 1,200 SRCR domains in specific patterns particular to each individual. Transcription levels for given SRCR genes may range from pronounced to undetectable, yet all tested animals harbor the genomic loci encoding these genes. Analysis of several SRCR genes revealed multiple loci corresponding to each type. In the case of one SRCR type, a cluster of at least three genes was detected within a 133-kb bacterial artificial chromosome insert, and conserved as well as unique regions were identified in sequences of three genomic clones derived from a single animal. Array hybridizations with repeated samples of coelomocyte messages revealed substantial alterations in levels of expression of many SRCR genes, with fluctuations of up to 10-fold in 1 week and up to 30-fold over a period of 3 months. This report is the first demonstration of genomic and transcriptional complexity in molecules expressed by invertebrate coelomocytes. The mechanisms controlling SRCR gene expression and the functional significance of this dynamic system await elucidation.

Digging for dead genes: an analysis of the characteristics of the pseudogene population in the Caenorhabditis elegans genome

Pseudogenes are non-functioning copies of genes in genomic DNA, which may either result from reverse transcription from an mRNA transcript (processed pseudogenes) or from gene duplication and subsequent disablement (non-processed pseudogenes). As pseudogenes are apparently ‘dead’, they usually have a variety of obvious disablements (e.g., insertions, deletions, frameshifts and truncations) relative to their functioning homologs. We have derived an initial estimate of the size, distribution and characteristics of the pseudogene population in the Caenorhabditis elegans genome, performing a survey in ‘molecular archaeology’. Corresponding to the 18 576 annotated proteins in the worm (i.e., in Wormpep18), we have found an estimated total of 2168 pseudogenes, about one for every eight genes. Few of these appear to be processed. Details of our pseudogene assignments are available from http://bioinfo.mbb.yale.edu/genome/worm/pseudogene. The population of pseudogenes differs significantly from that of genes in a number of respects: (i) pseudogenes are distributed unevenly across the genome relative to genes, with a disproportionate number on chromosome IV; (ii) the density of pseudogenes is higher on the arms of the chromosomes; (iii) the amino acid composition of pseudogenes is midway between that of genes and (translations of) random intergenic DNA, with enrichment of Phe, Ile, Leu and Lys, and depletion of Asp, Ala, Glu and Gly relative to the worm proteome; and (iv) the most common protein folds and families differ somewhat between genes and pseudogenes—whereas the most common fold found in the worm proteome is the immunoglobulin fold and the most common ‘pseudofold’ is the C-type lectin. In addition, the size of a gene family bears little overall relationship to the size of its corresponding pseudogene complement, indicating a highly dynamic genome. There are in fact a number of families associated with large populations of pseudogenes. For example, one family of seven-transmembrane receptors (represented by gene B0334.7) has one pseudogene for every four genes, and another uncharacterized family (represented by gene B0403.1) is approximately two-thirds pseudogenic. Furthermore, over a hundred apparent pseudogenic fragments do not have any obvious homologs in the worm.