Recombination and lineage‐specific gene loss in the aflatoxin gene cluster of Aspergillus flavus

Aflatoxins produced by Aspergillus flavus are potent carcinogens that contaminate agricultural crops. Recent efforts to reduce aflatoxin concentrations in crops have focused on biological control using nonaflatoxigenic A. flavus strains AF36 (=NRRL 18543) and NRRL 21882 (the active component of afla‐guard^®). However, the evolutionary potential of these strains to remain nonaflatoxigenic in nature is unknown. To elucidate the underlying population processes that influence aflatoxigenicity, we examined patterns of linkage disequilibrium (LD) spanning 21 regions in the aflatoxin gene cluster of A. flavus. We show that recombination events are unevenly distributed across the cluster in A. flavus. Six distinct LD blocks separate late pathway genes aflE, aflM, aflN, aflG, aflL, aflI and aflO, and there is no discernable evidence of recombination among early pathway genes aflA, aflB, aflC, aflD, aflR and aflS. The discordance in phylogenies inferred for the aflW/aflX intergenic region and two noncluster regions, tryptophan synthase and acetamidase, is indicative of trans‐species evolution in the cluster. Additionally, polymorphisms in aflW/aflX divide A. flavus strains into two distinct clades, each harbouring only one of the two approved biocontrol strains. The clade with AF36 includes both aflatoxigenic and nonaflatoxigenic strains, whereas the clade with NRRL 21882 comprises only nonaflatoxigenic strains and includes all strains of A. flavus missing the entire gene cluster or with partial gene clusters. Our detection of LD blocks in partial clusters indicates that recombination may have played an important role in cluster disassembly, and multilocus coalescent analyses of cluster and noncluster regions indicate lineage‐specific gene loss in A. flavus. These results have important implications in assessing the stability of biocontrol strains in nature.     

Linkage disequilibrium for different scales and applications

Assessing the patterns of linkage disequilibrium (LD) has become an important issue in both evolutionary biology and medical genetics since the rapid accumulation of densely spaced DNA sequence variation data in several organisms. LD deals with the correlation of genetic variation at two or more loci or sites in the genome within a given population. There are a variety of LD measures which range from traditional pairwise LD measures such as D' or r2 to entropy-based multi-locus measures or haplotype-specific approaches. Understanding the evolutionary forces (in particular recombination) that generate the observed variation of LD patterns across genomic regions is addressed by model-based LD analysis. Marker type and its allelic composition also influence the observed LD pattern, microsatellites having a greater power to detect LD in population isolates than SNPs. This review aims to explain basic LD measures and their application properties.     

High-throughput single-nucleotide polymorphism discovery and the search for candidate genes for long-term SIVmac nonprogression in Chinese rhesus macaques (Macaca mulatta)

Background Genetic differences between Indian and Chinese rhesus macaques contribute to the phenotypic variance of clinical trials, including infection with SIVmac. The completion of the rhesus genome has facilitated the discovery of several thousand markers. Methods We developed a genome‐wide SNP map for rhesus macaques containing 3869 validated markers with an average distance of 0.88 Mb and used the program VarLD to identify genomic areas with significant differences in linkage disequilibrium (LD) between Indian‐derived and Chinese rhesus macaques. Results Forty‐one statistically significant differences in LD between Chinese and Indian‐origin rhesus were detected on chromosomes 1, 4, 5 and 11. The region of greatest LD difference was located on the proximal end of chromosome one, which also contained the genes ELAVL4, MAST2 and HIVEP3. Conclusion These genomic areas provide entry to more detailed studies of gene function. This method is also applicable to the study of differences in biomarkers between regional populations of other species.     

Recombination, balancing selection and adaptive evolution in the aflatoxin gene cluster of Aspergillus parasiticus

Aflatoxins are toxic and carcinogenic polyketides produced by several Aspergillus species that are known to contaminate agricultural commodities, posing a serious threat to animal and human health. Aflatoxin (AF) biosynthesis is almost fully characterized and involves the coordinated expression of approximately 25 genes clustered in a 70-kb DNA region. Aspergillus parasiticus is an economically important and common agent of AF contamination. Naturally occurring nonaflatoxigenic strains of A. parasiticus are rarely found and generally produce O-methylsterigmatocystin (OMST), the immediate precursor of AF. To elucidate the evolutionary forces acting to retain AF and OMST pathway extrolites (chemotypes), we sequenced 21 intergenic regions spanning the entire cluster in 24 A. parasiticus isolates chosen to represent the genetic diversity within a single Georgia field population. Linkage disequilibrium analyses revealed five distinct recombination blocks in the A. parasiticus cluster. Phylogenetic network analyses showed a history of recombination between chemotype-specific haplotypes, as well as evidence of contemporary recombination. We performed coalescent simulations of variation in recombination blocks and found an approximately twofold deeper coalescence for cluster genealogies compared to noncluster genealogies, our internal standard of neutral evolution. Significantly deeper cluster genealogies are indicative of balancing selection in the AF cluster of A. parasiticus and are further corroborated by the existence of trans-species polymorphisms and common haplotypes in the cluster for several closely related species. Estimates of Ka/Ks for representative cluster genes provide evidence of selection for OMST and AF chemotypes, and indicate a possible role of chemotypes in ecological adaptation and speciation.     

Genome-wide variation in the human and fruitfly: a comparison

Average levels of nucleotide diversity are ten-fold lower in humans than in the fruitfly, Drosophila melanogaster. Despite this difference, apparently as a result of a lower population size, patterns of genomic diversity are strikingly similar in being correlated with local rates of recombination, and influenced by similar interactions between positive natural selection and recombination. Both species also show lower levels of variation on average in non-African compared to African populations, reflecting a similar evolutionary history and perhaps both natural selection and founder effects in new environments.     

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.     

Genome-Wide Linkage-Disequilibrium Profiles from Single Individuals

Although the analysis of linkage disequilibrium (LD) plays a central role in many areas of population genetics, the sampling variance of LD is known to be very large with high sensitivity to numbers of nucleotide sites and individuals sampled. Here we show that a genome-wide analysis of the distribution of heterozygous sites within a single diploid genome can yield highly informative patterns of LD as a function of physical distance. The proposed statistic, the correlation of zygosity, is closely related to the conventional population-level measure of LD, but is agnostic with respect to allele frequencies and hence likely less prone to outlier artifacts. Application of the method to several vertebrate species leads to the conclusion that >80% of recombination events are typically resolved by gene-conversion-like processes unaccompanied by crossovers, with the average lengths of conversion patches being on the order of one to several kilobases in length. Thus, contrary to common assumptions, the recombination rate between sites does not scale linearly with distance, often even up to distances of 100 kb. In addition, the amount of LD between sites separated by <200 bp is uniformly much greater than can be explained by the conventional neutral model, possibly because of the nonindependent origin of mutations within this spatial scale. These results raise questions about the application of conventional population-genetic interpretations to LD on short spatial scales and also about the use of spatial patterns of LD to infer demographic histories.     

A sequential coalescent algorithm for chromosomal inversions

Chromosomal inversions are common in natural populations and are believed to be involved in many important evolutionary phenomena, including speciation, the evolution of sex chromosomes and local adaptation. While recent advances in sequencing and genotyping methods are leading to rapidly increasing amounts of genome-wide sequence data that reveal interesting patterns of genetic variation within inverted regions, efficient simulation methods to study these patterns are largely missing. In this work, we extend the sequential Markovian coalescent, an approximation to the coalescent with recombination, to include the effects of polymorphic inversions on patterns of recombination. Results show that our algorithm is fast, memory-efficient and accurate, making it feasible to simulate large inversions in large populations for the first time. The SMC algorithm enables studies of patterns of genetic variation (for example, linkage disequilibria) and tests of hypotheses (using simulation-based approaches) that were previously intractable.     

The origin of selection signatures on bovine chromosome 6

The extent and pattern of linkage disequilibrium (LD) between closely spaced markers contain information about population history, including past population size and selection history. Selection signatures can be identified by comparing the LD surrounding a putative selected allele at a locus to the putative non-selected allele. In livestock populations, locations of selection signatures identified in this way should be correlated with QTL affecting production traits, as the populations have been under strong artificial selection for these traits. We used a dense SNP map of bovine chromosome 6 to characterize the pattern of LD on this chromosome in Norwegian Red cattle, a breed which has been strongly selected for milk production. The pattern of LD was generally consistent with strong selection in regions containing QTL affecting milk production traits, including a strong selection signature in a region containing a mutation known to affect milk production. The results demonstrate that in livestock populations, the origin of selection signatures will often be QTL for livestock production traits, and illustrate the value of selection signatures in uncovering new mutations with potential effects on quantitative traits.     

Genomic haplotype blocks may not accurately reflect spatial variation in historic recombination intensity

Recently, genomic data have revealed a "block-like" structure of haplotype diversity on human chromosomes. This structure is anticipated to facilitate gene mapping studies, because strong associations among loci within a block may allow haplotype variation to be tagged with a limited number of markers. But its usefulness to mapping efforts depends on the consistency of the block structure within and among populations, which in turn depends on how the block structure arises. Recombination hot spots are generally thought to underlie the block structure, but haplotype blocks can also develop stochastically under random recombination, in which case the block structure will show limited consistency among populations. Using coalescent models, which we upscaled to simulate the evolution of haplotypes with many markers at fixed distances, we show that the relationship between block boundaries and historic recombination intensity may be surprisingly weak. The majority of historic recombinations do not leave a footprint in present-day linkage disequilibrium patterns, and the block structure is sensitive to factors that affect the timing of recombination relative to marker mutation events in the genealogy, such as marker frequency bias and historic population size changes. Our results give insight into the potential of stochastic events to affect haplotype block structure, which can limit the usefulness of the block structure to mapping studies.