John S. Conery

Mutation Accumulation and the Extinction of Small Populations

Although extensive work has been done on the relationship between population size and the risk of extinction due to demographic and environmental stochasticity, the role of genetic deterioration in the extinction process is poorly understood. We develop a general theoretical approach for evaluating the risk of small populations to extinction via the accumulation of mildly deleterious mutations, and we support this with extensive computer simulations. Unlike previous attempts to model the genetic consequences of small population size, our approach is genetically explicit and fully accounts for the mutations inherited by a founder population as well as those introduced by subsequent mutation. Application of empirical estimates of the properties of spontaneous deleterious mutations leads to the conclusion that populations with effective sizes smaller than 100 (and actual sizes smaller than 1,000) are highly vulnerable to extinction via a mutational meltdown on timescales of approximately 100 generations. We point out a number of reasons why this is likely to be an overly optimistic view. Thus, from a purely genetic perspective, current management policies that provide formal protection to species only after they have dwindled to 100-1,000 individuals are inadequate. A doubling of the deleterious mutation rate, as can result from the release of mutagenic pollutants by human activity, is expected to reduce the longevity of a population by about 50%. As some investigators have previously suggested, the genetic load of a population can be readily purged by intentional inbreeding. However, this effect is at best transient, as intentional inbreeding can only enhance the probability of fixation of deleterious alleles, and those alleles that are purged are rapidly replaced with new mutations.

MUTATIONAL MELTDOWNS IN SEXUAL POPULATIONS

Although it is widely acknowledged that the gradual accumulation of mildly deleterious mutations is an important source of extinction for asexual populations, it is generally assumed that this process is of little relevance to sexual species. Here we present results, based on computer simulations and supported by analytical approximations, that indicate that mutation accumulation in small, random‐mating monoecious populations can lead to mean extinction times less than a few hundred to a few thousand generations. Unlike the situation in obligate asexuals in which the mean time to extinction (t̄e) increases more slowly than linearly with the population carrying capacity (K), t̄e increases approximately exponentially with K in outcrossing sexual populations. The mean time to extinction for obligately selfing populations is shown to be equivalent to that for asexual populations of the same size, but with half the mutation rate and twice the mutational effect; this suggests that obligate selfing, like obligate asexuality, is inviable as a long‐term reproductive strategy. Under all mating systems, the mean time to extinction increases relatively slowly with the logarithm of fecundity, and mutations with intermediate effects (similar to those observed empirically) cause the greatest risk of extinction. Because our analyses ignore sources of demographic and environmental stochasticity, which have synergistic effects that exacerbate the accumulation of deleterious mutations, our results should yield liberal upper bounds to the mean time to extinction caused by mutational degradation. Thus, deleterious mutation accumulation cannot be ruled out generally as a significant source of extinction vulnerability in small sexual populations or as a selective force influencing mating‐system evolution.

The evolutionary demography of duplicate genes

Although gene duplication has generally been viewed as a necessary source of material for the origin of evolutionary novelties, the rates of origin, loss, and preservation of gene duplicates are not well understood. Applying steady-state demographic techniques to the age distributions of duplicate genes censused in seven completely sequenced genomes, we estimate the average rate of duplication of a eukaryotic gene to be on the order of 0.01/gene/million years, which is of the same order of magnitude as the mutation rate per nucleotide site. However, the average half-life of duplicate genes is relatively small, on the order of 4.0 million years. Significant interspecific variation in these rates appears to be responsible for differences in species-specific genome sizes that arise as a consequence of a quasi-equilibrium birth-death process. Most duplicated genes experience a brief period of relaxed selection early in their history and a minority exhibit the signature of directional selection, but those that survive more than a few million years eventually experience strong purifying selection. Thus, although most theoretical work on the gene-duplication process has focused on issues related to adaptive evolution, the origin of a new function appears to be a very rare fate for a duplicate gene. A more significant role of the duplication process may be the generation of microchromosomal rearrangements through reciprocal silencing of alternative copies, which can lead to the passive origin of post-zygotic reproductive barriers in descendant lineages of incipient species.

Automated identification of conserved synteny after whole-genome duplication

An important objective for inferring the evolutionary history of gene families is the determination of orthologies and paralogies. Lineage-specific paralog loss following whole-genome duplication events can cause anciently related homologs to appear in some assays as orthologs. Conserved synteny-the tendency of neighboring genes to retain their relative positions and orders on chromosomes over evolutionary time-can help resolve such errors. Several previous studies examined genome-wide syntenic conservation to infer the contents of ancestral chromosomes and provided insights into the architecture of ancestral genomes, but did not provide methods or tools applicable to the study of the evolution of individual gene families. We developed an automated system to identify conserved syntenic regions in a primary genome using as outgroup a genome that diverged from the investigated lineage before a whole-genome duplication event. The product of this automated analysis, the Synteny Database, allows a user to examine fully or partially assembled genomes. The Synteny Database is optimized for the investigation of individual gene families in multiple lineages and can detect chromosomal inversions and translocations as well as ohnologs (paralogs derived by whole-genome duplication) gone missing. To demonstrate the utility of the system, we present a case study of gene family evolution, investigating the ARNTL gene family in the genomes of Ciona intestinalis, amphioxus, zebrafish, and human.

Parallel execution of logic programs

1 Introduction.- 2 Logic Programming.- 2.1 Syntax.- 2.2 Semantics.- 2.3 Control.- 2.4 Prolog.- 2.4.1 Evaluable Predicates and Arithmetic.- 2.4.2 Higher Order Functions.- 2.4.3 The Cut Symbol.- 2.5 Alternate Control Strategies.- 2.5.1 Selection by Number of Solutions.- 2.5.2 Selection by Number of Uninstantiated Variables.- 2.5.3 Intelligent Backtracking.- 2.5.4 Coroutines.- 2.6 Chapter Summary.- 3 Parallelism in Logic Programs.- 3.1 Models for OR Parallelism.- 3.1.1 Pure OR Parallelism.- 3.1.2 OR Processes.- 3.1.3 Distributed Search.- 3.1.4 Summary.- 3.2 Models for AND Parallelism.- 3.2.1 Stream Parallel Models.- 3.2.2 AND Processes.- 3.2.3 AND Parallelism in the Goal Tree.- 3.2.4 Summary.- 3.3 Low Level Parallelism.- 3.4 Chapter Summary.- 4 The AND/OR Process Model.- 4.1 Oracle.- 4.2 Messages.- 4.3 OR Processes.- 4.4 AND Processes.- 4.5 Interpreter.- 4.6 Programming Language.- 4.7 Chapter Summary.- 5 Parallel OR Processes.- 5.1 Operating Modes.- 5.2 Execution.- 5.3 Example.- 5.4 Chapter Summary.- 6 Parallel AND Processes.- 6.1 Ordering of Literals.- 6.1.1 Dataflow Graphs.- 6.1.2 The Ordering Algorithm.- 6.1.3 Examples.- 6.2 Forward Execution.- 6.2.1 Forward Execution Algorithm.- 6.2.2 Solution of a Deterministic Function.- 6.3 Backward Execution.- 6.3.1 Generating Tuples of Terms.- 6.3.2 Definitions for Backward Execution.- 6.3.3 The Backward Execution Algorithm.- 6.4 Detailed Example.- 6.4.1 Ordering.- 6.4.2 Forward Execution.- 6.4.3 Backward Execution.- 6.4.4 Additional Solutions.- 6.5 Discussion.- 6.5.1 Relative Order of Incoming Messages.- 6.5.2 Definition of Candidate Set.- 6.5.3 Result Cache.- 6.5.4 Infinite Domains.- 6.5.5 Multisets of Results.- 6.6 Chapter Summary.- 7 Implementation.- 7.1 Overview of the Interpreter.- 7.2 Parallel AND Processes.- 7.3 Process Allocation.- 7.4 Growth Control.- 7.4.1 Conditional Expressions.- 7.4.2 Process Priorities.- 7.4.3 Message Protocols.- 7.4.4 Secondary Memory.- 7.5 Summary.

Parallel interpretation of logic programs

Logic programs offer many opportunities for parallelism. We present an abstract model that exploits the parallelism due to nondeterministic choices in a logic program. A working interpreter based on this model is described, along with variants of the basic model that are capable of exploiting other sources of parallelism. We conclude with a discussion of our plans for experimenting with the various models, plans which we hope will lead eventually to a multi-processor machine.

AND parallelism and nondeterminism in logic programs

This paper defines an abstract interpreter for logic programs based on a system of asynchronous, independent processors which communicate only by passing messages. Each logic program is automatically partitioned and its pieces distributed to available processors. This approach permits two distinct forms of parallelism. OR parallelism arises from evaluating nondeterministic choices simultaneously. AND parallelism arises when a computation involves independent, but necessary, subcomputations. Algorithms like quicksort, which follow a divide and conquer approach, usually exhibit this form of parallelism. These two forms of parallelism are conjointly achieved by the parallel interpreter.

A Neural Network Model of Chemotaxis Predicts Functions of Synaptic Connections in the Nematode Caenorhabditis elegans

The anatomical connectivity of the nervous system of the nematode Caenorhabditis elegans has been almost completely described, but determination of the neurophysiological basis of behavior in this system is just beginning. Here we used an optimization algorithm to search for patterns of connectivity sufficient to compute the sensorimotor transformation underlying C. elegans chemotaxis, a simple form of spatial orientation behavior in which turning probability is modulated by the rate of change of chemical concentration. Optimization produced differentiator networks capable of simulating chemotaxis. A surprising feature of these networks was inhibitory feedback connections on all neurons. Further analysis showed that feedback regulates the latency between sensory input and behavior. Common patterns of connectivity between the model and biological networks suggest new functions for previously identified connections in the C. elegans nervous system.

Binding environments for parallel logic programs in non-shared memory multiprocessors

A method known asclosed environments can be used to represent variable bindings for OR-parellel logic programs without relying on a shared memory or common address space. The representation is based on a procedure that trans-forms stack frames after unification, taking into account problems with common unbound ancestors and shared instances of complex terms. Closed environments were developed for the AND/OR Process Model, but may be applicable to other OR-parallel models.

Nucleotide substitutions and the evolution of duplicate genes.

This paper describes software created to search for and analyze pairs of duplicate genes within a genome. The process is based on a program that uses aligned amino acid sequences to generate a corresponding alignment of the underlying nucleotide sequences and perform a codon by codon comparison of the nucleotides. Observed numbers of nucleotide substitutions can be used to make inferences about the ages of gene duplication events and the effects of natural selection acting on duplicate genes.