Concepts – Relationship Predictions | DNAeXplained – Genetic Genealogy
Recombination hotspots in wild castaneus show little overlap, however, with the .. were compared with centimorgans per megabase values obtained by Cox et al. Examining the correlation between recombination rate and properties of. In yeast and mammals, several studies have found a correlation between a high Finally, we provide evidence of meiotic recombination hot spots and show that both .. (Black line) CO rates in centiMorgans per megabase. Humans have about twice as much recombination per generation as the rodents, .. as the relationship between true hotspots and large-scale regional variation in . (in centimorgans, cM) by the distance between the markers in the sequence.
The Recombination Landscape in Wild House Mice Inferred Using Population Genomic Data
That chromosome size does not have a significant effect on recombination in mouse windows may be due to the fact that except for chromosome 19, there is not much variation in size among the mouse chromosomes, relative to human and rat. It is essential to understand the relationship between mutation and recombination, as these potentially interacting variables can confound interpretations in studies of the effects of recombination and in estimating costs involved in the evolution of sex and recombination.
For example, the positive correlation in humans between recombination rate and nucleotide diversity has been explained as the result of background selection or hitch-hiking Nachman ; Lercher and Hurstalthough subsequent studies with larger data sets show that this correlation may be entirely due to a correlation between the mutation and recombination rates Hellman et al.
Our results show that at face value the positive correlation between recombination and mutation is not a universal feature of mammals; in fact, in mouse the correlation is negative. Is it possible that recombination is mutagenic in rat and human, but antimutagenic in mouse?
Perhaps, but the complex relationships between these variables and other genomic factors such as GC content suggest that the difference may lie in the nature of interactions between multiple factors and may depend on which estimate of the neutral mutation rate is used Hardison et al. Although the nature of these relationships and causative explanations remain elusive for now, the strengths of a multiple-species comparative approach are obvious, especially with the observation that the closely related mouse and rat differ in these respects.
Conservation of Recombination Across Mammals When comparing syntenic homologous blocks across species, we found only a slight positive correlation between recombination rates of different species. On the other hand, multiple genomic rearrangements have occurred among rat, mouse, and human RGSPCplacing homologous regions into different chromosomal environments in each species.
Also, it has been predicted on theoretical grounds—and later with empirical support—that recombination hotspots will tend to drive themselves to extinction, resulting in a rapid turnover of hotspots Boulton et al.
The genomic scale and the time scale at which such a phenomenon occurs are unknown, as the relationship between true hotspots and large-scale regional variation in recombination is unknown.
Understanding the relationships between recombination rate and various genomic parameters such as nucleotide composition, mutation rate, efficiency of natural selection, rate of protein evolution, and molecular diversity within species from an evolutionary perspective requires information about the tempo of evolution in recombination rate. Theories addressing the origin and maintenance of sexual reproduction also identify the rate of divergence in recombination as a key parameter.
In the future, combining our data with those from several additional closely related species could provide the first estimates of this parameter, paving the way for studies of coevolution with other genomic variables and providing empirical benchmarks for theories about the evolution of recombination and sexual reproduction. Consequences for Mapping Traits If multiple genes each with a small to moderate effect in the same direction on a quantitative trait are clustered together in a region of low recombination, this region may show up with strong and significant linkage to the trait in a typical genome scan in an animal model.
This is because even though each gene contributes only a small effect to the phenotype, the lack of recombination will cause such a cluster of genes to act as a single large-effect gene Noor et al.
Conversely, if these multiple genes are tightly linked but alleles have opposite effects on a trait, it may be difficult to detect the effect of any single gene in a genome scan. Once a QTL is identified for a complex trait in rat, it is common to attempt to positionally clone the responsible gene through the construction of congenic and subcongenic rats where, for example, several substrains are developed that contain small portions of the QTL introgressed from the normal strain onto the background of a strain susceptible to a complex disease Markel et al.
This process relies entirely on identifying the rare recombinant occurring within the QTL. With the quantification of the amounts and patterns of recombination in the rat genome herein it should be possible to incorporate this information into the planning of future research projects, and to develop an optimized set of markers to maximize the information content from a genome scan.
Future Directions We anticipate that the accuracy and resolution of the estimates of recombination in the rat, mouse, and human will continue to improve along with the improvements in each new iteration of the genome assembly, and with the construction of higher-resolution genetic maps with larger numbers of progeny.
This will be important for the future of complex trait mapping in animal models if the strategies of using linkage disequilibrium being developed in human are to be eventually applied to the rat and mouse Arnheim et al. The high-resolution recombination rate maps will also be of tremendous value for investigating questions of genome evolution. Understanding the causes and consequences of recombination rate variation will also be enhanced with accurate estimates of sex-specific recombination in rat and mouse.
This is crucial, because there is obviously more to the regulation of recombination than sequence motifs and chromosome location; human females have 1.
Finally, as we have shown, data from multiple species provide new insights into the factors that covary with, and therefore may be affecting or affected by, recombination that are seen in only one species. Data from more mammals will likely reveal lineage-specific patterns in the evolution of recombination.
Genetic maps are available for a number of additional species Swinburne et al. The effect of recombination on long-term evolutionary patterns has received considerable attention in recent years.
For example, covariation with nucleotide diversity may reveal the effects of background selection Charlesworth et al.
The Recombination Landscape in Wild House Mice Inferred Using Population Genomic Data
Methods that include multiple species of greater or lesser amounts of divergence i. Therefore, our rat—mouse—human comparative approach provides a beginning toward what will be a much more complete understanding of the evolution of recombination and how it interacts with other features of mammalian genome evolution.
All maps were made using the Kosambi map function. The versions of the genome assemblies used were: Locations of individual markers for each of the rat, mouse, and human genomes were determined based on alignments of the full sequence of the marker when available using BLAT Kent and also using primer sequence information using e-PCR Schuler and BLAT.
Markers placed to different chromosomes in the genetic versus genome sequence were discarded. We filtered the complete set of markers placed on the genomic sequences to include the maximal set for each map such that the order of the markers in both the genetic and sequence maps agreed. From the maximally consistent set of markers derived for a particular genetic map, the recombination rate between all pairs of adjacent markers was calculated by simply dividing the distance between the markers in the genetic map in centimorgans, cM by the distance between the markers in the sequence map in megabases, Mb.
For simplicity, the location of a marker in the sequence map is set to the midpoint of the alignment of that marker. Each base pair in the interval between adjacent markers is then assigned the calculated rate. To approximate the recombination rate for any window of sequence of arbitrary size and location, we summed the rates corresponding to each base in the window and divided by the size of the window.
Finally, a few windows with large discrepancies between the genetic map and the sequence assembly were removed. Recombination rates for individual chromosomes were calculated by dividing the genetic length cM by the sequence length Mb between the first and last marker placed on each chromosome. Measuring Chromosomal and Sequence Features and Substitution Rates For each window in each species, we calculated the proportional distance from the center of the chromosome to the center of the window absolute distance divided by half the chromosome length and proportional distance from the centromere to the center of the window absolute distance divided by the length of the chromosomal arm.
For this, the position of the centromere in rat was estimated by comparing the positions of markers mapped by fluorescent in situ hybridization data from RatMap: The centromeres rat chromosomes 3, 11, and 12 were assigned to base pair position zero, because the p-arms of these chromosomes are NOR containing satellited DNA and therefore are presumed to not be in the current genome assembly RGSPC The centromeres of rat and mouse telocentrics are also placed at position zero.
Positions of human centromeres were estimated based on the cytogenetic band mapping to the genome Furey and Haussler Data for the repetitive elements were taken from the RepeatMasker A. The remaining sequence motifs were calculated with custom perl scripts. Ancestral repeat AR sites from retro- or DNA-transposons were inserted in the human—rodent ancestral genome before the human—rodent split and appear in syntenic positions in all species A.
The human—mouse—rat phylogenetic tree used for this model was constructed using maximum likelihood methods Siepel and Haussler Variance and CV Calculations Genomic levels of variation in recombination rate were estimated, separately on the 10 Mb and 5 Mb scales, by calculating variance and the coefficient of variation CV.
Ninety-five percent confidence limits were estimated as the 2. More recently, Begun et al. The association between recombination rate and diversity, but not divergence, in Drosophila is considered to be driven primarily by natural selection 3 — 5: Similar studies in other taxa have yielded conflicting results.
Although, in most cases, associations between recombination rate and nucleotide diversity are observed, they sometimes can be quite weak 89and in some species such as maize and humans, significant associations are observed between recombination rate and interspecies divergence 10 — Because regions of severely reduced recombination often exhibit typical levels of interspecific divergence but reduced diversity within species, it is unequivocal that selective forces have contributed to this pattern in some species.
Less clear is how much residual variation is explained by other forces, such as mutational heterogeneity associated with recombination rate. The relative role of these forces would be better understood if a more fine-grained and reliable recombinational map was available.
If there is fine-scale heterogeneity in recombination rate, a mutational relationship between recombination and nucleotide diversity or divergence would be easiest to detect by examining recombination over small, rather than large, spatial scales assuming some temporal stability of recombination hotspots.
Fine-scale heterogeneity in recombination rate has been shown in humans, yeast, and other taxa 13including regions of Drosophila pseudoobscura The reliability of known recombinational distances may also be problematic: Available genetic distance estimates such as those from D. Because the cross-over rate in different parts of the genome was studied in different crosses and varying conditions, perhaps only extreme differences in the cross-over rate between parts of the genome may have been accurately captured.
To address the discord among studies comparing recombination rate to diversity and divergence, we investigate the association of fine-scale cross-over rate with nucleotide diversity within species and divergence between species in the D.
We used illumina array microbeads to genotype a large F2 backcross between two D. We also generated and aligned, at low-coverage, genomic reads of a second strain of D. To validate patterns of nucleotide diversity and divergence with respect to recombination rate on a different part of the genome, we sequenced multiple loci by using standard technologies on chromosome XL in 10 isolates of D.
Results Cross-Over Rate Variation.