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.

Haplotype complementarity under mutational pressure.

Natural populations do not correspond to Mendelian populations. Effective populations are much smaller, inbreeding higher, and organization of large number of genes into chromosomes connected with relatively low recombination rate invalidates the law of independent gene assortment. Under such conditions, a large number of genes is inherited as clusters and evolves as genetic units. Computer simulations have shown that mutations inside clusters are not eliminated independently by purifying selection but, instead, the whole clusters tend to complement each other. It means that whenever one haplotype carries one of two possible alleles, the other haplotype at that locus carries the other allele; thus inherited recessive deleterious diseases do not affect the health of the phenotype even if their fraction in the genome is high. This complementation seems to be a winning strategy in small or spatially distributed populations. We discuss possible consequences of this complementarity.

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

In the human genomes, recombination frequency between homologous chromosomes during meiosis is highly correlated with their physical length while it differs significantly when their coding density is considered. Furthermore, it has been observed that the recombination events are distributed unevenly along the chromosomes. We have found that many of such recombination properties can be predicted by computer simulations of population evolution based on the Monte Carlo methods. For example, these simulations have shown that the probability of acceptance of the recombination events by selection is higher at the ends of chromosomes and lower in their middle parts. The regions of high coding density are more prone to enter the strategy of haplotype complementation and to form clusters of genes, which are "recombination deserts". The phenomenon of switching in-between the purifying selection and haplotype complementation has a phase transition character, and many relations between the effective population size, coding density, chromosome size and recombination frequency are those of the power law type.

Why are diploid genomes widespread and dominant mutations rare?

We have used the sexual Penna ageing model to show that the relation between dominance and recessiveness could be a force which optimizes the genome size. While the possibility of complementation of the damaged allele by its functional counterparts (recessiveness) leads to the redundancy of genetic information, the dominant effect of defective genes tends to diminish the number of alleles fulfilling the same function. Playing with the fraction of dominant loci in the genome it is possible to obtain the condition where the diploid state of the genome is optimal. If the status of each bit position as dominant or recessive mutations is changed for each individual randomly and rarely, then after a long time a stationary equilibrium of many recessive and few dominant loci is established in the sexual Penna model. This effect vanishes if the same changing distribution of dominant loci applies to all individuals.

Sympatric speciation as intrinsic property of the expanding population.

Sympatric speciation is still debatable, though some well documented empirical data that support it already exist. Our computer modeling reveals that sympatric speciation is an intrinsic property of the expanding populations with differentiated inbreeding-higher at the edges and lower inside the territory. At the edges of expanding populations, the probability of forming deleterious phenotypes by placing two defective alleles in the corresponding loci is relatively high even with low genetic load. Thus, the winning strategy is to use rather the complementary haplotypes to form zygotes. This strategy leads to a very fast sympatric speciation and specific distribution of recombination activity along the chromosomes-higher at the subtelomeric regions (close to the ends of chromosomes) and lower in the middle of chromosomes, which is also observed in all human chromosomes (excluding Y).

The relationships between the isoelectric point and: length of proteins, taxonomy and ecology of organisms.

BACKGROUND: The distribution of isoelectric point (pI) of proteins in a proteome is universal for all organisms. It is bimodal dividing the proteome into two sets of acidic and basic proteins. Different species however have different abundance of acidic and basic proteins that may be correlated with taxonomy, subcellular localization, ecological niche of organisms and proteome size. RESULTS: We have analysed 1784 proteomes encoded by chromosomes of Archaea, Bacteria, Eukaryota, and also mitochondria, plastids, prokaryotic plasmids, phages and viruses. We have found significant correlation in more than 95% of proteomes between the protein length and pI in proteomes--positive for acidic proteins and negative for the basic ones. Plastids, viruses and plasmids encode more basic proteomes while chromosomes of Archaea, Bacteria, Eukaryota, mitochondria and phages more acidic ones. Mitochondrial proteomes of Viridiplantae, Protista and Fungi are more basic than Metazoa. It results from the presence of basic proteins in the former proteomes and their absence from the latter ones and is related with reduction of metazoan genomes. Significant correlation was found between the pI bias of proteomes encoded by prokaryotic chromosomes and proteomes encoded by plasmids but there is no correlation between eukaryotic nuclear-coded proteomes and proteomes encoded by organelles. Detailed analyses of prokaryotic proteomes showed significant relationships between pI distribution and habitat, relation to the host cell and salinity of the environment, but no significant correlation with oxygen and temperature requirements. The salinity is positively correlated with acidicity of proteomes. Host-associated organisms and especially intracellular species have more basic proteomes than free-living ones. The higher rate of mutations accumulation in the intracellular parasites and endosymbionts is responsible for the basicity of their tiny proteomes that explains the observed positive correlation between the decrease of genome size and the increase of basicity of proteomes. The results indicate that even conserved proteins subjected to strong selectional constraints follow the global trend in the pI distribution. CONCLUSION: The distribution of pI of proteins in proteomes shows clear relationships with length of proteins, subcellular localization, taxonomy and ecology of organisms. The distribution is also strongly affected by mutational pressure especially in intracellular organisms.

The role of intragenomic recombination rate in the evolution of population's genetic pool.

In a simple computer model of population evolution, we have shown that frequency of recombination between haplotypes during the gamete production influences the effectiveness of the reproduction strategy. High recombination rates keeps the fraction of defective alleles low while low recombination rate or uneven distributed recombination spots change the strategy of genomes' evolution and result in the accumulation of heterozygous loci in the genomes. Even short fragment of chromosome with restricted recombination influences the genetic structure of neighboring regions.

Monte Carlo simulations of the age structure of the human population.

In this mini review, we present assumptions and some results of Monte Carlo simulations based on the Penna model, which support the mutation accumulation theory of aging. This microscopic model has been exploited for the quantitative description of many biological phenomena connected with the population evolution. We show how the results of simulations could describe the changes of mortality trajectories of the human populations during the last 150 years, and how the method could be used for predicting the human age distribution in the future. The main assumption of the model is that genes are expressed chronologically one after another in the same order in all individuals during their life span. Different forces of selection pressure exerted on genes expressed at different periods of life generate characteristic gradient of defective genes accumulated in the germline cells. The genes expressed after the minimum reproduction age are under weaker selection pressure, and the fraction of defects among them is higher than among the genes expressed before the minimum reproduction age. This gradient of defects generates a gradient of mortality for the part of the population in the reproduction age following the exponential Gompertz law. The limitations of the model and some biological interpretations of its parameters are also discussed.

Higher mutation rate helps to rescue genes from the elimination by selection.

Directional mutation pressure associated with replication processes is the main cause of the asymmetry between the leading and lagging DNA strands in bacterial genomes. On the other hand, the asymmetry between sense and antisense strands of protein coding sequences is a result of both mutation and selection pressures. Thus, there are two different ways of superposition of the sense strand, on the leading or lagging strand. Besides many other implications of these two possible situations, one seems to be very important - because of the asymmetric replication-associated mutation pressure, the mutation rate of genes depends on their location. Using Monte Carlo methods, we have simulated, under experimentally determined directional mutation pressure, the divergence rate and the elimination rate of genes depending on their location in respect to the leading/lagging DNA strands in the asymmetric prokaryotic genome. We have found that the best survival strategy for the majority of genes is to sometimes switch between DNA strands. Paradoxically, this strategy results in higher substitution rates but remains in agreement with observations in bacterial genomes that such inversions are very frequent and divergence rate between homologs lying on different DNA strands is very high.

Altruism and antagonistic pleiotropy in Penna ageing model.

The Penna ageing model is based on mutation accumulation theory. We show that it also allows for self-organization of antagonistic pleiotropy which helps at young age at the expense of old age. This can be interpreted as emergence of altruism.

Where does bacterial replication start? Rules for predicting the oriC region.

Three methods, based on DNA asymmetry, the distribution of DnaA boxes and dnaA gene location, were applied to identify the putative replication origins in 120 chromosomes. The chromosomes were classified according to the agreement of these methods and the applicability of these methods was evaluated. DNA asymmetry is the most universal method of putative oriC identification in bacterial chromosomes, but it should be applied together with other methods to achieve better prediction. The three methods identify the same region as a putative origin in all Bacilli and Clostridia, many Actinobacteria and gamma Proteobacteria. The organization of clusters of DnaA boxes was analysed in detail. For 76 chromosomes, a DNA fragment containing multiple DnaA boxes was identified as a putative origin region. Most bacterial chromosomes exhibit an overrepresentation of DnaA boxes; many of them contain at least two clusters of DnaA boxes in the vicinity of the oriC region. The additional clusters of DnaA boxes are probably involved in controlling replication initiation. Surprisingly, the characteristic features of the initiation of replication, i.e. a cluster of DnaA boxes, a dnaA gene and a switch in asymmetry, were not found in some of the analysed chromosomes, particularly those of obligatory intracellular parasites or endosymbionts. This is presumably connected with many mechanisms disturbing DNA asymmetry, translocation or disappearance of the dnaA gene and decay of the Escherichia coli perfect DnaA box pattern.

Representation of mutation pressure and selection pressure by PAM matrices.

This paper analyses the relationship between the mutation data matrix 1PAM/PET91, representing the effect of both mutation and selection pressures exerted on 16130 homologous proteins of different organisms, and a mutation probability matrix (1PAM/MPM) representing the effect of pure mutation pressure on protein coding of the Borrelia burgdorferi genome. The 1PAM/PMP matrix was derived with the help of computer simulations, which used empirical nucleotide substitution rates found for the B. burgdorferi genome. Here, it is shown that the frequency of amino acid occurrence is strongly related to their effective survival time. We found that the shorter the turnover time of an amino acid under pure mutation pressure, the lower its fraction in the proteins coded by the genome and the more protected by selection pressure is its position in proteins. Results of analyses suggest that during evolution the mutational pressure has been optimised to some extent to the selection requirements.

High divergence rate of sequences located on different DNA strands in closely related bacterial genomes.

One of the common features of bacterial genomes is a strong compositional asymmetry between differently replicating DNA strands (leading and lagging). The main cause of the observed bias is the mutational pressure associated with replication. This suggests that genes translocated between differently replicating DNA strands are subjected to a higher mutational pressure, which may influence their composition and divergence rate. Analyses of groups of completely sequenced bacterial genomes have revealed that the highest divergence rate is observed for the DNA sequences that in closely related genomes are located on different DNA strands in respect to their role in replication. Paradoxically, for this group of sequences the absolute values of divergence rate are higher for closely related species than for more diverged ones. Since this effect concerns only the specific group of orthologs, there must be a specific mechanism introducing bias into the structure of chromosome by enriching the set of homologs in trans position in newly diverged species in relatively highly diverged sequences. These highly diverged sequences may be of varied nature: (1) paralogs or other fast-evolving genes under weak selection; or (2) pseudogenes that will probably be eliminated from the genome during further evolution; or (3) genes whose history after divergence is longer than the history of the genomes in which they are found. The use of these highly diverged sequences for phylogenetic analyses may influence the topology and branch length of phylogenetic trees. The changing mutational pressure may contribute to arising of genes with new functions as well.

Rearrangements between differently replicating DNA strands in asymmetric bacterial genomes.

Many bacterial genomes are under asymmetric mutational pressure which introduces compositional asymmetry into DNA molecule resulting in many biases in coding structure of chromosomes. One of the processes affected by the asymmetry is translocation changing the position of the coding sequence on chromosome in respect to the orientation on the leading and lagging DNA strand. When analysing sets of paralogs in 50 genomes, we found that the number of observed genes which switched their positions on DNA strand is lowest for genomes with the highest DNA asymmetry. However, the number of orthologs which changed DNA strand increases with the phylogenetic distance between the compared genomes. Nevertheless, there is a fraction of coding sequences that stay on the leading strand in all analysed genomes, whereas there are no sequences that stay always on the lagging strand. Since sequences diverge very fast after switching the DNA strand, this bias in mobility of sequences is responsible, in part, for higher divergence rates among some of coding sequences located on the lagging DNA strand.

Monte Carlo simulation of genome viability with paralog replacement.

Recent analyses of genome content have revealed that many single functions, even in haploid organisms, can be executed by more than one gene. As a result, experimental disruption of many individual genes does not exert lethal effects on the organism or even any visible change in the phenotype of the organism with a knockedout gene. Our analysis shows that such genetic redundancy allows for an appreciably higher mutation load in the genome simulations before the viability of the whole organism is destroyed.

How many protein-coding genes are there in the Saccharomyces cerevisiae genome?

We have compared the results of estimations of the total number of protein-coding genes in the Saccharomyces cerevisiae genome, which have been obtained by many laboratories since the yeast genome sequence was published in 1996. We propose that there are 5300-5400 genes in the genome. This makes the first estimation of the number of intronless ORFs longer than 100 codons, based on the features of the set of genes with phenotypes known in 1997 to be correct. This estimation assumed that the set of the first 2300 genes with known phenotypes was representative for the whole set of protein-coding genes in the genome. The same method used in this paper for the approximation of the total number of protein-coding sequences among more than 40 000 ORFs longer than 20 codons gives a result that is only slightly higher. This suggests that there are still some non-coding ORFs in the databases and a few dozen small ORFs, not yet annotated, which probably code for proteins.