Genome analyses and modelling the relationships between coding density, recombination rate and chromosome length

Re-evaluation of NCGR Davis Ficus carica and palmata SSR profiles

To date all public records of F. carica SSR profiles are from NCGR Davis. Prior studies of this data have not been received well because several of the stated relationships do not match what is observed in the field. Upon examination of the prior authors methods it is found that the 1979 Nei similarity measures are not valid distance metrics for the profiles thus invalidating their analysis of genetic distance. Further, the data are tensor in nature and it is shown here that "flattening the data" for use in a vector method will change the problem under study. Consequently the present analysis focuses on geometric, statistical, and biostatistical tensor-based methods–finding that only the latter produces results matching what is manually observed among the profiles. Combining this with historical breeding records and morphologic observations reveals that a modest portion of the profiled accessions are mislabeled–and also reveals the existence of previously undocumented close relations. Another area of concern in the prior studies is the statistical partitioning of the complete graph of distances to define clades. In the present analysis it is shown that genetic clades cannot be defined in this profile collection due to lack of cohesion in nearest neighbor components. It is also shown that it is presently intractable to significantly rectify gaps in the sample population by profile enrichment because the number of individuals in an entire population within the estimated profile distribution exceeds 10¹⁴. The profiles themselves are found to have very few occurrences of common values between the 15 loci and thus according to Fisher’s theory of epistatic variance no correlation to phenotype attributes is expected–a result verified by the original investigators. Therefore further discovery of appropriate markers is needed to fully capture geno- and pheno-type characteristics in F. carica and F. palmata SSR profiles.

Genetic differentiation and intrinsic genomic features explain variation in recombination hotspots among cocoa tree populations

Background

Recombination plays an important evolutionary role by breaking up haplotypes and shuffling genetic variation. This process impacts the ability of selection to eliminate deleterious mutations or increase the frequency of beneficial mutations in a population. To understand the role of recombination generating and maintaining haplotypic variation in a population, we can construct fine-scale recombination maps. Such maps have been used to study a variety of model organisms and proven to be informative of how selection and demographics shape species-wide variation. Here we present a fine-scale recombination map for ten populations of Theobroma cacao – a non-model, long-lived, woody crop. We use this map to elucidate the dynamics of recombination rates in distinct populations of the same species, one of which is domesticated.

Results

Mean recombination rates in range between 2.5 and 8.6 cM/Mb for most populations of T. cacao with the exception of the domesticated Criollo (525 cM/Mb) and Guianna, a more recently established population (46.5 cM/Mb). We found little overlap in the location of hotspots of recombination across populations. We also found that hotspot regions contained fewer known retroelement sequences than expected and were overrepresented near transcription start and termination sites. We find mutations in FIGL-1, a protein shown to downregulate cross-over frequency in Arabidopsis, statistically associated to higher recombination rates in domesticated Criollo.

Conclusions

We generated fine-scale recombination maps for ten populations of Theobroma cacao and used them to understand what processes are associated with population-level variation in this species. Our results provide support to the hypothesis of increased recombination rates in domesticated plants (Criollo population). We propose a testable mechanistic hypothesis for the change in recombination rate in domesticated populations in the form of mutations to a previously identified recombination-suppressing protein. Finally, we establish a number of possible correlates of recombination hotspots that help explain general patterns of recombination in this species.

Role of recombination and faithfulness to partner in sex chromosome degeneration

Sex determination in mammals is strongly linked to sex chromosomes. In most cases, females possess two copies of X chromosome while males have one X and one Y chromosome. It is assumed that these chromosomes originated from a pair of homologous autosomes, which diverged when recombination between them was suppressed. However, it is still debated why the sex chromosomes stopped recombining and how this process spread out over most part of the chromosomes. To study this problem, we developed a simulation model, in which the recombination rate between the sex chromosomes can freely evolve. We found that the suppression of recombination between the X and Y is spontaneous and proceeds very quickly during the evolution of population, which leads to the degeneration of the Y in males. Interestingly, the degeneration happens only when mating pairs are unfaithful. This evolutionary strategy purifies the X chromosome from defective alleles and leads to the larger number of females than males in the population. In consequence, the reproductive potential of the whole population increases. Our results imply that both the suppression of recombination and the degeneration of Y chromosome may be associated with reproductive strategy and favoured in polygamous populations with faithless mating partners.

What drives the evolution of condition-dependent recombination in diploids? Some insights from simulation modelling

While the evolutionary advantages of non-zero recombination rates have prompted diverse theoretical explanations, the evolution of essential recombination features remains underexplored. We focused on one such feature, the condition dependence of recombination, viewed as the variation in within-generation sensitivity of recombination to external (environment) and/or internal (genotype) conditions. Limited empirical evidence for its existence comes mainly from diploids, whereas theoretical models show that it only easily evolves in haploids. The evolution of condition-dependent recombination can be explained by its advantage for the selected system (indirect effect), or by benefits to modifier alleles, ensuring this strategy regardless of effects on the selected system (direct effect). We considered infinite panmictic populations of diploids exposed to a cyclical two-state environment. Each organism had three selected loci. Examining allele dynamics at a fourth, selectively neutral recombination modifier locus, we frequently observed that a modifier allele conferring condition-dependent recombination between the selected loci displaced the allele conferring the optimal constant recombination rate. Our simulations also confirm the results of theoretical studies showing that condition-dependent recombination cannot evolve in diploids on the basis of direct fitness-dependent effects alone. Therefore, the evolution of condition-dependent recombination in diploids can be driven by indirect effects alone, i.e. by modifier effects on the selected system.This article is part of the themed issue 'Evolutionary causes and consequences of recombination rate variation in sexual organisms'.

Coding sequence density estimation via topological pressure

We give a new approach to coding sequence (CDS) density estimation in genomic analysis based on the topological pressure, which we develop from a well known concept in ergodic theory. Topological pressure measures the 'weighted information content' of a finite word, and incorporates 64 parameters which can be interpreted as a choice of weight for each nucleotide triplet. We train the parameters so that the topological pressure fits the observed coding sequence density on the human genome, and use this to give ab initio predictions of CDS density over windows of size around 66,000 bp on the genomes of Mus Musculus, Rhesus Macaque and Drososphilia Melanogaster. While the differences between these genomes are too great to expect that training on the human genome could predict, for example, the exact locations of genes, we demonstrate that our method gives reasonable estimates for the 'coarse scale' problem of predicting CDS density. Inspired again by ergodic theory, the weightings of the nucleotide triplets obtained from our training procedure are used to define a probability distribution on finite sequences, which can be used to distinguish between intron and exon sequences from the human genome of lengths between 750 and 5,000 bp. At the end of the paper, we explain the theoretical underpinning for our approach, which is the theory of Thermodynamic Formalism from the dynamical systems literature. Mathematica and MATLAB implementations of our method are available at http://sourceforge.net/projects/topologicalpres/ .

Distribution of recombination hotspots in the human genome--a comparison of computer simulations with real data

Recombination is the main cause of genetic diversity. Thus, errors in this process can lead to chromosomal abnormalities. Recombination events are confined to narrow chromosome regions called hotspots in which characteristic DNA motifs are found. Genomic analyses have shown that both recombination hotspots and DNA motifs are distributed unevenly along human chromosomes and are much more frequent in the subtelomeric regions of chromosomes than in their central parts. Clusters of motifs roughly follow the distribution of recombination hotspots whereas single motifs show a negative correlation with the hotspot distribution. To model the phenomena related to recombination, we carried out computer Monte Carlo simulations of genome evolution. Computer simulations generated uneven distribution of hotspots with their domination in the subtelomeric regions of chromosomes. They also revealed that purifying selection eliminating defective alleles is strong enough to cause such hotspot distribution. After sufficiently long time of simulations, the structure of chromosomes reached a dynamic equilibrium, in which number and global distribution of both hotspots and defective alleles remained statistically unchanged, while their precise positions were shifted. This resembles the dynamic structure of human and chimpanzee genomes, where hotspots change their exact locations but the global distributions of recombination events are very similar.

Modelling survival and allele complementation in the evolution of genomes with polymorphic loci

We have simulated the evolution of sexually reproducing populations composed of individuals represented by diploid genomes. A series of eight bits formed an allele occupying one of 128 loci of one haploid genome (chromosome). The environment required a specific activity of each locus, this being the sum of the activities of both alleles located at the corresponding loci on two chromosomes. This activity is represented by the number of bits set to zero. In a constant environment the best fitted individuals were homozygous with alleles’ activities corresponding to half of the environment requirement for a locus (in diploid genome two alleles at corresponding loci produced a proper activity). Changing the environment under a relatively low recombination rate promotes generation of more polymorphic alleles. In the heterozygous loci, alleles of different activities complement each other fulfilling the environment requirements. Nevertheless, the genetic pool of populations evolves in the direction of a very restricted number of complementing haplotypes and a fast changing environment kills the population. If simulations start with all loci heterozygous, they stay heterozygous for a long time.