Bayesian inference of fine-scale recombination rates using population genomic data

Recently, several statistical methods for estimating fine-scale recombination rates using population samples have been developed. However, currently available methods that can be applied to large-scale data are limited to approximated likelihoods. Here, we developed a full-likelihood Markov chain Monte Carlo method for estimating recombination rate under a Bayesian framework. Genealogies underlying a sampling of chromosomes are effectively modelled by using marginal individual single nucleotide polymorphism genealogies related through an ancestral recombination graph. The method is compared with two existing composite-likelihood methods using simulated data.Simulation studies show that our method performs well for different simulation scenarios. The method is applied to two human population genetic variation datasets that have been studied by sperm typing. Our results are consistent with the estimates from sperm crossover analysis.     

Single molecule studies of homologous recombination

Single molecule methods offer an unprecedented opportunity to examine complex macromolecular reactions that are obfuscated by ensemble averaging. The application of single molecule techniques to study DNA processing enzymes has revealed new mechanistic details that are unobtainable from bulk biochemical studies. Homologous DNA recombination is a multi-step pathway that is facilitated by numerous enzymes that must precisely and rapidly manipulate diverse DNA substrates to repair potentially lethal breaks in the DNA duplex. In this review, we present an overview of single molecule assays that have been developed to study key aspects of homologous recombination and discuss the unique information gleaned from these experiments.     

Inferring processes underlying B-cell repertoire diversity

We quantify the VDJ recombination and somatic hypermutation processes in human B cells using probabilistic inference methods on high-throughput DNA sequence repertoires of human B-cell receptor heavy chains. Our analysis captures the statistical properties of the naive repertoire, first after its initial generation via VDJ recombination and then after selection for functionality. We also infer statistical properties of the somatic hypermutation machinery (exclusive of subsequent effects of selection). Our main results are the following: the B-cell repertoire is substantially more diverse than T-cell repertoires, owing to longer junctional insertions; sequences that pass initial selection are distinguished by having a higher probability of being generated in a VDJ recombination event; somatic hypermutations have a non-uniform distribution along the V gene that is well explained by an independent site model for the sequence context around the hypermutation site.     

Insights into recombination from population genetic variation

Patterns of genetic variation in natural populations are shaped by, and hence carry valuable information about, the underlying recombination process. In the past five years, the increasing availability of large-scale population genetic data on dense sets of markers, coupled with advances in statistical methods for extracting information from these data, have led to several important advances in our understanding of the recombination process in humans. These advances include the identification of large numbers of 'hotspots', where recombination appears to take place considerably more frequently than in the surrounding sequence, and the identification of DNA sequence motifs that are associated with the locations of these hotspots.     

An exploratory algorithm to identify intra-host recombinant viral sequences

Since recombination leads to the generation of mosaic genomes that violate the assumption of traditional phylogenetic methods that sequence evolution can be accurately described by a single tree, results and conclusions based on phylogenetic analysis of data sets including recombinant sequences can be severely misleading. Many methods are able to adequately detect recombination between diverse sequences, for example between different HIV-1 subtypes. More problematic is the identification of recombinants among closely related sequences such as a viral population within a host. We describe a simple algorithmic procedure that enables detection of intra-host recombinants based on split-decomposition networks and a robust statistical test for recombination. By applying this algorithm to several published HIV-1 data sets we conclude that intra-host recombination was significantly underestimated in previous studies and that up to one-third of the env sequences longitudinally sampled from a given subject can be of recombinant origin. The results show that our procedure can be a valuable exploratory tool for detection of recombinant sequences before phylogenetic analysis, and also suggest that HIV-1 recombination in vivo is far more frequent and significant than previously thought.     

Variability of allelic recombination frequencies

Summary Estimates of allelic recombination frequencies are shown to have coefficients of variation of between 20 and 40%. In Coprinus this is true of both high and low recombination frequencies and is also true when the alleles involved show marker effect. This variability is not confined to Coprinus but is a general feature of both meiotic and mitotic allelic recombination. Experimental errors do not make a major contribution to the observed variation althought it has the nature of a sampling variation. It is suggested that the variation arises from the diversity of ways in which the initial errors introduced by hybrid DNA formation can be resolved during the excision-repair stages of recombination. If the enzymes responsible for these processes are present in low concentrations then much latitude can be anticipated in the way the same errors are dealt with by separate, though isogenic, diploid or dikaryotic organisms. Each separate cross is thus interpreted as providing an estimate of the recombination frequency which is but a sample from a varied population of possible estimates of the same recombination frequency. Each pair of alleles exhibits a recombination frequency which, within the statistical boundaries of the general variation, is sufficiently reproducible to be described as a characteristic of them. Combinations of allelic recombination frequencies derived from pair-wise crosses fall into patterns that are sufficiently consistent for allele maps to be drawn; and, providing a sufficient number of replicate crosses have been analysed, the allele map can be shown to be statistically soundly based. Two marker effect situations are examined. One causes reduction of recombination frequency and is probably intrinsic to the mutant site itself, the other causes enhancement of recombination frequency and is due to a factor or factors distinct from the allelic mutant site in the strain in which it was first identified. When intercrossed the two effects counteract one another.     

Modeling linkage disequilibrium and identifying recombination hotspots using single-nucleotide polymorphism data

We introduce a new statistical model for patterns of linkage disequilibrium (LD) among multiple SNPs in a population sample. The model overcomes limitations of existing approaches to understanding, summarizing, and interpreting LD by (i) relating patterns of LD directly to the underlying recombination process; (ii) considering all loci simultaneously, rather than pairwise; (iii) avoiding the assumption that LD necessarily has a "block-like" structure; and (iv) being computationally tractable for huge genomic regions (up to complete chromosomes). We examine in detail one natural application of the model: estimation of underlying recombination rates from population data. Using simulation, we show that in the case where recombination is assumed constant across the region of interest, recombination rate estimates based on our model are competitive with the very best of current available methods. More importantly, we demonstrate, on real and simulated data, the potential of the model to help identify and quantify fine-scale variation in recombination rate from population data. We also outline how the model could be useful in other contexts, such as in the development of more efficient haplotype-based methods for LD mapping.     

First dating of a recombination event in mammalian tick-borne flaviviruses

The mammalian tick-borne flavivirus group (MTBFG) contains viruses associated with important human and animal diseases such as encephalitis and hemorrhagic fever. In contrast to mosquito-borne flaviviruses where recombination events are frequent, the evolutionary dynamic within the MTBFG was believed to be essentially clonal. This assumption was challenged with the recent report of several homologous recombinations within the Tick-borne encephalitis virus (TBEV). We performed a thorough analysis of publicly available genomes in this group and found no compelling evidence for the previously identified recombinations. However, our results show for the first time that demonstrable recombination (i.e., with large statistical support and strong phylogenetic evidences) has occurred in the MTBFG, more specifically within the Louping ill virus lineage. Putative parents, recombinant strains and breakpoints were further tested for statistical significance using phylogenetic methods. We investigated the time of divergence between the recombinant and parental strains in a Bayesian framework. The recombination was estimated to have occurred during a window of 282 to 76 years before the present. By unravelling the temporal setting of the event, we adduce hypotheses about the ecological conditions that could account for the observed recombination.     

Detection of recombination events in bacterial genomes from large population samples

Analysis of important human pathogen populations is currently under transition toward whole-genome sequencing of growing numbers of samples collected on a global scale. Since recombination in bacteria is often an important factor shaping their evolution by enabling resistance elements and virulence traits to rapidly transfer from one evolutionary lineage to another, it is highly beneficial to have access to tools that can detect recombination events. Multiple advanced statistical methods exist for such purposes; however, they are typically limited either to only a few samples or to data from relatively short regions of a total genome. By harnessing the power of recent advances in Bayesian modeling techniques, we introduce here a method for detecting homologous recombination events from whole-genome sequence data for bacterial population samples on a large scale. Our statistical approach can efficiently handle hundreds of whole genome sequenced population samples and identify separate origins of the recombinant sequence, offering an enhanced insight into the diversification of bacterial clones at the level of the whole genome. A data set of 241 whole genome sequences from an important pandemic lineage of Streptococcus pneumoniae is used together with multiple simulated data sets to demonstrate the potential of our approach.     

Directed evolution: selecting today's biocatalysts

Directed evolution has become a full-grown tool in molecular biology nowadays. The methods that are involved in creating a mutant library are extensive and can be divided into several categories according to their basic ideas. Furthermore, both screening and selection can be used to target the enzyme towards the desired direction. Nowadays, this technique is broadly used in two major applications: (industrial) biocatalysis and research. In the first field enzymes are engineered in order to produce suitable biocatalysts with high catalytic activity and stability in an industrial environment. In the latter area methods are established to quickly engineer new enzymes for every possible catalytic step, thereby creating a universal biotechnological toolbox. Furthermore, directed evolution can be used to try to understand the natural evolutionary processes. This review deals with new mutagenesis and recombination strategies published recently. A full overview of new methods for creating more specialised mutant libraries is given. The importance of selection in directed evolution strategies is being exemplified by some current successes including the beta-lactam acylases.     

Products and implied mechanism of H chain switch recombination

The Ig H chain switch is a DNA recombination event. The recombination occurs between two or more switch regions, areas of tandem sequence duplication that lie upstream of the corresponding H chain C region genes. We have determined the DNA sequence at four recombination sites in three molecularly cloned, rearranged switch regions. All eight donor and recipient recombination sites are at the common pentamers GGGGT, GAGCT, and GGTGG. One of the switch recombination events is an inversion of S gamma 3 sequences. Another of the recombinational events is an internal S gamma 1 deletion, which may be switch enzyme mediated. These results, together with other switch recombination site sequences, suggest that switch recombination is mediated by cutting enzymes with modest specificity and religation enzymes with no specificity.     

Tackling the population genetics of clonal and partially clonal organisms

Many clonal organisms experience occasional events of sexual recombination, with profound consequences for their population dynamics and evolutionary trajectories. With the recent development of polymorphic genetic markers and new statistical methods, we now have an unprecedented ability to detect recombination in organisms that are thought to reproduce strictly, or essentially asexually. However, it is not always obvious which methodology to apply. Consequently, biologists might decide how to analyse their data without clear guidelines. Here, we discuss the available methods, focusing on those best suited when working with limited genetic information, such as a few genetic markers or DNA sequences. We conclude by commenting on the prospects offered by some recent conceptual advances and the access to high throughput technologies in an increasing number of model organisms.     

细菌重组系统及其应用研究进展

利用重组酶和辅助蛋白共同作用于DNA片段上,使不同基因重新组合以完成基因重组的现象在细菌中广泛存在,基因重组对于细菌的遗传多样性、进化等具有重要意义。目前,细菌基因重组主要分为同源重组、位点特异性重组和转座重组3种类型。本文主要对细菌重组系统重组酶的种类、作用机制及其在细菌遗传操作中的应用策略进行阐述。     

Protein design in metabolic engineering and synthetic biology

Starting from experimental data on sequence, structure or biochemical properties of enzymes, protein design seeks to construct enzymes with desired activity, stability, specificity and selectivity. Two strategies are widely used to investigate sequence-structure-function relationships: statistical methods to analyse protein families or mutant libraries, and molecular modelling methods to study proteins and their interaction with ligands or substrates. On the basis of these methods, protein design has been successfully applied to fine-tune bottleneck enzymes in metabolic engineering and to design enzymes with new substrate spectra and new functions. However, constructing efficient metabolic pathways by integrating individual enzymes into a complex system is challenging. The field of synthetic biology is still in its infancy, but promising results have demonstrated the feasibility and usefulness of the concept.     

多结构域酶的结构域进化关系

近年来随着生命科学新技术、新方法的涌现,酶蛋白结构和功能研究逐渐深入。具有多结构域的酶蛋白中各个结构域常具有独立的催化或结合底物的功能,在重组酶和组合生物合成研究中具有极大的研究和应用价值。这些结构域功能和组织方式的多样性,是研究分子进化的基础。对结构域进行进化分析对于研究多结构域酶的进化过程、功能相近酶之间的关系,以及对酶的分类鉴定等有重要意义。本文从结构域的重复性、结构域的水平基因转移和结构域的重组等方面出发,对多结构域酶中结构域之间进化关系的研究成果进行综述。     

Accurately Measuring Recombination between Closely Related HIV-1 Genomes

Retroviral recombination is thought to play an important role in the generation of immune escape and multiple drug resistance by shuffling pre-existing mutations in the viral population. Current estimates of HIV-1 recombination rates are derived from measurements within reporter gene sequences or genetically divergent HIV sequences. These measurements do not mimic the recombination occurring in vivo, between closely related genomes. Additionally, the methods used to measure recombination make a variety of assumptions about the underlying process, and often fail to account adequately for issues such as co-infection of cells or the possibility of multiple template switches between recombination sites. We have developed a HIV-1 marker system by making a small number of codon modifications in gag which allow recombination to be measured over various lengths between closely related viral genomes. We have developed statistical tools to measure recombination rates that can compensate for the possibility of multiple template switches. Our results show that when multiple template switches are ignored the error is substantial, particularly when recombination rates are high, or the genomic distance is large. We demonstrate that this system is applicable to other studies to accurately measure the recombination rate and show that recombination does not occur randomly within the HIV genome.     

Saccharomyces cerevisiae in directed evolution: An efficient tool to improve enzymes

Over the past 20 years, directed evolution has been seen to be the most reliable approach to protein engineering. Emulating the natural selection algorithm, ad hoc enzymes with novel features can be tailor-made for practical purposes through iterative rounds of random mutagenesis, DNA recombination and screening. Of the heterologous hosts used in laboratory evolution experiments, the budding yeast Saccharomyces cerevisiae has become the best choice to express eukaryotic proteins with improved properties. S. cerevisiae not only allows mutant enzymes to be secreted but also, it permits a wide range of genetic manipulations to be employed, ranging from in vivo cloning to the creation of greater molecular diversity, thanks to its efficient DNA recombination apparatus. Here, we summarize some successful examples of the use of the S. cerevisiae machinery to accelerate artificial evolution, complementing the traditional in vitro methods to generate tailor-made enzymes.     

Frequent Intra-Subtype Recombination among HIV-1 Circulating in Tanzania

The study estimated the prevalence of HIV-1 intra-subtype recombinant variants among female bar and hotel workers in Tanzania. While intra-subtype recombination occurs in HIV-1, it is generally underestimated. HIV-1 env gp120 V1-C5 quasispecies from 45 subjects were generated by single-genome amplification and sequencing (median (IQR) of 38 (28–50) sequences per subject). Recombination analysis was performed using seven methods implemented within the recombination detection program version 3, RDP3. HIV-1 sequences were considered recombinant if recombination signals were detected by at least three methods with p-values of ≤0.05 after Bonferroni correction for multiple comparisons. HIV-1 in 38 (84%) subjects showed evidence for intra-subtype recombination including 22 with HIV-1 subtype A1, 13 with HIV-1 subtype C, and 3 with HIV-1 subtype D. The distribution of intra-patient recombination breakpoints suggested ongoing recombination and showed selective enrichment of recombinant variants in 23 (60%) subjects. The number of subjects with evidence of intra-subtype recombination increased from 29 (69%) to 36 (82%) over one year of follow-up, although the increase did not reach statistical significance. Adjustment for intra-subtype recombination is important for the analysis of multiplicity of HIV infection. This is the first report of high prevalence of intra-subtype recombination in the HIV/AIDS epidemic in Tanzania, a region where multiple HIV-1 subtypes co-circulate. HIV-1 intra-subtype recombination increases viral diversity and presents additional challenges for HIV-1 vaccine design.     

Recombination and Replication

The links between recombination and replication have been appreciated for decades and it is now generally accepted that these two fundamental aspects of DNA metabolism are inseparable: Homologous recombination is essential for completion of DNA replication and vice versa. This review focuses on the roles that recombination enzymes play in underpinning genome duplication, aiding replication fork movement in the face of the many replisome barriers that challenge genome stability. These links have many conserved features across all domains of life, reflecting the conserved nature of the substrate for these reactions, DNA.The interplay between replication and recombination is complex in terms of both mechanism and integration within DNA metabolism. At the heart of this interplay is the requirement for single-stranded DNA (ssDNA), the substrate for DNA-strand-exchange proteins, to initiate recombination (Cox 2007b; San Filippo et al. 2008). Whether, when, and where this ssDNA is generated determines the functional relationship between replication and recombination, a relationship that can operate in both directions. Homologous recombination enzymes are critical for successful completion of genome duplication (Kogoma 1997; Cox et al. 2000) but DNA replication also underpins homologous recombination, as discussed elsewhere in this collection. The links between recombination and replication are therefore intimate and one cannot be considered in isolation from the other. However, involvement of DNA-strand-exchange proteins, regardless of the metabolic context, comes with the unavoidable risk of genome rearrangements. This genome instability can occasionally increase evolutionary fitness but more frequently is deleterious to the viability of the individual.This review will focus on fundamental aspects of the links between replication and recombination enzymes rather than simply providing a list of known enzymes and reactions. The substrate, DNA, is identical in all of these reactions and this is reflected in the high mechanistic conservation of replication and recombination.     

Modeling DNA mutation and recombination for directed evolution experiments

Directed evolution experiments rely on the cyclical application of mutagenesis, screening and amplification in a test tube. They have led to the creation of novel proteins for a wide range of applications. However, directed evolution currently requires an uncertain, typically large, number of labor intensive and expensive experimental cycles before proteins with improved function are identified. This paper introduces predictive models for quantifying the outcome of the experiments aiding in the setup of directed evolution for maximizing the chances of obtaining DNA sequences encoding enzymes with improved activities. Two methods of DNA manipulation are analysed: error-prone PCR and DNA recombination. Error-prone PCR is a DNA replication process that intentionally introduces copying errors by imposing mutagenic reaction conditions. The proposed model calculates the probability of producing a specific nucleotide sequence after a number of PCR cycles. DNA recombination methods rely on the mixing and concatenation of genetic material from a number of parent sequences. This paper focuses on modeling a specific DNA recombination protocol, DNA shuffling. Three aspects of the DNA shuffling procedure are modeled: the fragment size distribution after random fragmentation by DNase I, the assembly of DNA fragments, and the probability of assembling specific sequences or combinations of mutations. Results obtained with the proposed models compare favorably with experimental data.