Privacy Risks from Genomic Data-Sharing Beacons

The human genetics community needs robust protocols that enable secure sharing of genomic data from participants in genetic research. Beacons are web servers that answer allele-presence queries—such as “Do you have a genome that has a specific nucleotide (e.g., A) at a specific genomic position (e.g., position 11,272 on chromosome 1)?”—with either “yes” or “no.” Here, we show that individuals in a beacon are susceptible to re-identification even if the only data shared include presence or absence information about alleles in a beacon. Specifically, we propose a likelihood-ratio test of whether a given individual is present in a given genetic beacon. Our test is not dependent on allele frequencies and is the most powerful test for a specified false-positive rate. Through simulations, we showed that in a beacon with 1,000 individuals, re-identification is possible with just 5,000 queries. Relatives can also be identified in the beacon. Re-identification is possible even in the presence of sequencing errors and variant-calling differences. In a beacon constructed with 65 European individuals from the 1000 Genomes Project, we demonstrated that it is possible to detect membership in the beacon with just 250 SNPs. With just 1,000 SNP queries, we were able to detect the presence of an individual genome from the Personal Genome Project in an existing beacon. Our results show that beacons can disclose membership and implied phenotypic information about participants and do not protect privacy a priori. We discuss risk mitigation through policies and standards such as not allowing anonymous pings of genetic beacons and requiring minimum beacon sizes.     

Benefits and limitations of a new genome‐based PCR‐RFLP genotyping assay (GB‐RFLP): A SNP‐based detection method for identification of species in extremely young adaptive radiations

High‐throughput DNA sequencing technologies make it possible now to sequence entire genomes relatively easily. Complete genomic information obtained by whole‐genome resequencing (WGS) can aid in identifying and delineating species even if they are extremely young, cryptic, or morphologically difficult to discern and closely related. Yet, for taxonomic or conservation biology purposes, WGS can remain cost‐prohibitive, too time‐consuming, and often constitute a “data overkill.” Rapid and reliable identification of species (and populations) that is also cost‐effective is made possible by species‐specific markers that can be discovered by WGS. Based on WGS data, we designed a PCR restriction fragment length polymorphism (PCR‐RFLP) assay for 19 Neotropical Midas cichlid populations (Amphilophus cf. citrinellus), that includes all 13 described species of this species complex. Our work illustrates that identification of species and populations (i.e., fish from different lakes) can be greatly improved by designing genetic markers using available “high resolution” genomic information. Yet, our work also shows that even in the best‐case scenario, when whole‐genome resequencing information is available, unequivocal assignments remain challenging when species or populations diverged very recently, or gene flow persists. In summary, we provide a comprehensive workflow on how to design RFPL markers based on genome resequencing data, how to test and evaluate their reliability, and discuss the benefits and pitfalls of our approach.     

Using High-Throughput Sequencing to Leverage Surveillance of Genetic Diversity and Oseltamivir Resistance: A Pilot Study during the 2009 Influenza A(H1N1) Pandemic

Background

Influenza viruses display a high mutation rate and complex evolutionary patterns. Next-generation sequencing (NGS) has been widely used for qualitative and semi-quantitative assessment of genetic diversity in complex biological samples. The “deep sequencing” approach, enabled by the enormous throughput of current NGS platforms, allows the identification of rare genetic viral variants in targeted genetic regions, but is usually limited to a small number of samples.

Methodology and Principal Findings

We designed a proof-of-principle study to test whether redistributing sequencing throughput from a high depth-small sample number towards a low depth-large sample number approach is feasible and contributes to influenza epidemiological surveillance. Using 454-Roche sequencing, we sequenced at a rather low depth, a 307 bp amplicon of the neuraminidase gene of the Influenza A(H1N1) pandemic (A(H1N1)pdm) virus from cDNA amplicons pooled in 48 barcoded libraries obtained from nasal swab samples of infected patients (n  =  299) taken from May to November, 2009 pandemic period in Mexico. This approach revealed that during the transition from the first (May-July) to second wave (September-November) of the pandemic, the initial genetic variants were replaced by the N248D mutation in the NA gene, and enabled the establishment of temporal and geographic associations with genetic diversity and the identification of mutations associated with oseltamivir resistance.

Conclusions

NGS sequencing of a short amplicon from the NA gene at low sequencing depth allowed genetic screening of a large number of samples, providing insights to viral genetic diversity dynamics and the identification of genetic variants associated with oseltamivir resistance. Further research is needed to explain the observed replacement of the genetic variants seen during the second wave. As sequencing throughput rises and library multiplexing and automation improves, we foresee that the approach presented here can be scaled up for global genetic surveillance of influenza and other infectious diseases.     

Coexistence and Within-Host Evolution of Diversified Lineages of Hypermutable Pseudomonas aeruginosa in Long-term Cystic Fibrosis Infections

The advent of high-throughput sequencing techniques has made it possible to follow the genomic evolution of pathogenic bacteria by comparing longitudinally collected bacteria sampled from human hosts. Such studies in the context of chronic airway infections by Pseudomonas aeruginosa in cystic fibrosis (CF) patients have indicated high bacterial population diversity. Such diversity may be driven by hypermutability resulting from DNA mismatch repair system (MRS) deficiency, a common trait evolved by P. aeruginosa strains in CF infections. No studies to date have utilized whole-genome sequencing to investigate within-host population diversity or long-term evolution of mutators in CF airways. We sequenced the genomes of 13 and 14 isolates of P. aeruginosa mutator populations from an Argentinian and a Danish CF patient, respectively. Our collection of isolates spanned 6 and 20 years of patient infection history, respectively. We sequenced 11 isolates from a single sample from each patient to allow in-depth analysis of population diversity. Each patient was infected by clonal populations of bacteria that were dominated by mutators. The in vivo mutation rate of the populations was ∼100 SNPs/year–∼40-fold higher than rates in normo-mutable populations. Comparison of the genomes of 11 isolates from the same sample showed extensive within-patient genomic diversification; the populations were composed of different sub-lineages that had coexisted for many years since the initial colonization of the patient. Analysis of the mutations identified genes that underwent convergent evolution across lineages and sub-lineages, suggesting that the genes were targeted by mutation to optimize pathogenic fitness. Parallel evolution was observed in reduction of overall catabolic capacity of the populations. These findings are useful for understanding the evolution of pathogen populations and identifying new targets for control of chronic infections.     

Oceanic Metagenomics: The Sorcerer II Global Ocean Sampling Expedition: Northwest Atlantic through Eastern Tropical Pacific

The world's oceans contain a complex mixture of micro-organisms that are for the most part, uncharacterized both genetically and biochemically. We report here a metagenomic study of the marine planktonic microbiota in which surface (mostly marine) water samples were analyzed as part of the Sorcerer II Global Ocean Sampling expedition. These samples, collected across a several-thousand km transect from the North Atlantic through the Panama Canal and ending in the South Pacific yielded an extensive dataset consisting of 7.7 million sequencing reads (6.3 billion bp). Though a few major microbial clades dominate the planktonic marine niche, the dataset contains great diversity with 85% of the assembled sequence and 57% of the unassembled data being unique at a 98% sequence identity cutoff. Using the metadata associated with each sample and sequencing library, we developed new comparative genomic and assembly methods. One comparative genomic method, termed “fragment recruitment,” addressed questions of genome structure, evolution, and taxonomic or phylogenetic diversity, as well as the biochemical diversity of genes and gene families. A second method, termed “extreme assembly,” made possible the assembly and reconstruction of large segments of abundant but clearly nonclonal organisms. Within all abundant populations analyzed, we found extensive intra-ribotype diversity in several forms: (1) extensive sequence variation within orthologous regions throughout a given genome; despite coverage of individual ribotypes approaching 500-fold, most individual sequencing reads are unique; (2) numerous changes in gene content some with direct adaptive implications; and (3) hypervariable genomic islands that are too variable to assemble. The intra-ribotype diversity is organized into genetically isolated populations that have overlapping but independent distributions, implying distinct environmental preference. We present novel methods for measuring the genomic similarity between metagenomic samples and show how they may be grouped into several community types. Specific functional adaptations can be identified both within individual ribotypes and across the entire community, including proteorhodopsin spectral tuning and the presence or absence of the phosphate-binding gene PstS.     

Comprehensive Characterization of Human Genome Variation by High Coverage Whole-Genome Sequencing of Forty Four Caucasians

Whole genome sequencing studies are essential to obtain a comprehensive understanding of the vast pattern of human genomic variations. Here we report the results of a high-coverage whole genome sequencing study for 44 unrelated healthy Caucasian adults, each sequenced to over 50-fold coverage (averaging 65.8×). We identified approximately 11 million single nucleotide polymorphisms (SNPs), 2.8 million short insertions and deletions, and over 500,000 block substitutions. We showed that, although previous studies, including the 1000 Genomes Project Phase 1 study, have catalogued the vast majority of common SNPs, many of the low-frequency and rare variants remain undiscovered. For instance, approximately 1.4 million SNPs and 1.3 million short indels that we found were novel to both the dbSNP and the 1000 Genomes Project Phase 1 data sets, and the majority of which (∼96%) have a minor allele frequency less than 5%. On average, each individual genome carried ∼3.3 million SNPs and ∼492,000 indels/block substitutions, including approximately 179 variants that were predicted to cause loss of function of the gene products. Moreover, each individual genome carried an average of 44 such loss-of-function variants in a homozygous state, which would completely “knock out” the corresponding genes. Across all the 44 genomes, a total of 182 genes were “knocked-out” in at least one individual genome, among which 46 genes were “knocked out” in over 30% of our samples, suggesting that a number of genes are commonly “knocked-out” in general populations. Gene ontology analysis suggested that these commonly “knocked-out” genes are enriched in biological process related to antigen processing and immune response. Our results contribute towards a comprehensive characterization of human genomic variation, especially for less-common and rare variants, and provide an invaluable resource for future genetic studies of human variation and diseases.     

Bacterial evolution during human infection: Adapt and live or adapt and die

Microbes are constantly evolving. Laboratory studies of bacterial evolution increase our understanding of evolutionary dynamics, identify adaptive changes, and answer important questions that impact human health. During bacterial infections in humans, however, the evolutionary parameters acting on infecting populations are likely to be much more complex than those that can be tested in the laboratory. Nonetheless, human infections can be thought of as naturally occurring in vivo bacterial evolution experiments, which can teach us about antibiotic resistance, pathogenesis, and transmission. Here, we review recent advances in the study of within-host bacterial evolution during human infection and discuss practical considerations for conducting such studies. We focus on 2 possible outcomes for de novo adaptive mutations, which we have termed “adapt-and-live” and “adapt-and-die.” In the adapt-and-live scenario, a mutation is long lived, enabling its transmission on to other individuals, or the establishment of chronic infection. In the adapt-and-die scenario, a mutation is rapidly extinguished, either because it carries a substantial fitness cost, it arises within tissues that block transmission to new hosts, it is outcompeted by more fit clones, or the infection resolves. Adapt-and-die mutations can provide rich information about selection pressures in vivo, yet they can easily elude detection because they are short lived, may be more difficult to sample, or could be maladaptive in the long term. Understanding how bacteria adapt under each of these scenarios can reveal new insights about the basic biology of pathogenic microbes and could aid in the design of new translational approaches to combat bacterial infections.     

Mitochondrial DNA D‐loop sequence analysis reveals high variation and multiple maternal origins of indigenous Tanzanian goat populations

The Small East African (SEA) goat are widely distributed in different agro‐ecological zones of Tanzania. We report the genetic diversity, maternal origin, and phylogenetic relationship among the 12 Tanzanian indigenous goat populations, namely Fipa, Songwe, Tanga, Pwani, Iringa, Newala, Lindi, Gogo, Pare, Maasai, Sukuma, and Ujiji, based on the mitochondrial DNA (mtDNA) D‐loop. High haplotype (H _d = 0.9619–0.9945) and nucleotide (π = 0.0120–0.0162) diversities were observed from a total of 389 haplotypes. The majority of the haplotypes (n = 334) belonged to Haplogroup A which was consistent with the global scenario on the genetic pattern of maternal origin of all goat breeds in the world. Haplogroup G comprised of 45 haplotypes drawn from all populations except the Ujiji goat population while Haplogroup B with 10 haplotypes was dominated by Ujiji goats (41%). Tanzanian goats shared four haplotypes with the Kenyan goats and two with goats from South Africa, Namibia, and Mozambique. There was no sharing of haplotypes observed between individuals from Tanzanian goat populations with individuals from North or West Africa. The indigenous goats in Tanzania have high genetic diversity defined by 389 haplotypes and multiple maternal origins of haplogroup A, B, and G. There is a lot of intermixing and high genetic variation within populations which represent an abundant resource for selective breeding in the different agro‐ecological regions of the country.     

LD-CNV: rapid and simple discovery of chromosomal translocations using linkage disequilibrium between copy number variable loci

Large-scale structural variations, such as chromosomal translocations, can have profound effects on fitness and phenotype, but are difficult to identify and characterize. Here, we describe a simple and effective method aimed at identifying translocations using only the dosage of sequence reads mapped on the reference genome. We binned reads on genomic segments sized according to sequencing coverage and identified instances when copy number segregated in populations. For each dosage-polymorphic 1 Mb bin, we tested independence, effectively an apparent linkage disequilibrium (LD), with other variable bins. In nine potato (Solanum tuberosum) dihaploid families translocations affecting pericentromeric regions were common and in two cases were due to genomic misassembly. In two populations, we found evidence for translocation affecting euchromatic arms. In cv. PI 310467, a nonreciprocal translocation between chromosomes (chr.) 7 and 8 resulted in a 5–3 copy number change affecting several Mb at the respective chromosome tips. In cv. “Alca Tarma,” the terminal arm of chr. 4 translocated to the tip of chr. 1. Using oligonucleotide-based fluorescent in situ hybridization painting probes (oligo-FISH), we tested and confirmed the predicted arrangement in PI 310467. In 192 natural accessions of Arabidopsis thaliana, dosage haplotypes tended to vary continuously and resulted in higher noise, while apparent LD between pericentromeric regions suggested the effect of repeats. This method, LD-CNV, should be useful in species where translocations are suspected because it tests linkage without the need for genotyping.     

Evolution of Haplotypes at the DRD2 Locus

We present here the first evolutionary perspective on haplotypes at DRD2, the locus for the dopamine D₂ receptor. The dopamine D₂ receptor plays a critical role in the functioning of many neural circuits in the human brain. If functionally relevant variation at the DRD2 locus exists, understanding the evolution of haplotypes on the basis of polymorphic sites encompassing the gene should provide a powerful framework for identifying that variation. Three DRD2 polymorphisms (TaqI “A” and “B” RFLPs and the (CA)_n short tandem repeat polymorphism) encompassing the coding sequences have been studied in 15 populations; these markers are polymorphic in all the populations studied, and they display strong and significant linkage disequilibria with each other. The common haplotypes for the two TaqI RFLPs are separately derived from the ancestral haplotype but predate the spread of modern humans around the world. The knowledge of how the various haplotypes have evolved, the allele frequencies of the haplotypes in human populations, and the physical relationships of the polymorphisms to each other and to the functional parts of the gene should now allow proper design and interpretation of association studies.     

The Phylogeographical Pattern and Conservation of the Chinese Cobra (Naja atra) across Its Range Based on Mitochondrial Control Region Sequences

The vulnerable Chinese cobra (Naja atra) ranges from southeastern China south of the Yangtze River to northern Vietnam and Laos. Large mountain ranges and water bodies may influence the pattern of genetic diversity of this species. We sequenced the mitochondrial DNA control region (1029 bp) using 285 individuals collected from 23 localities across the species'' range and obtained 18 sequences unique to Taiwan from GenBank for phylogenetic and population analysis. Two distinct clades were identified, one including haplotypes from the two westernmost localities (Hekou and Miyi) and the other including haplotypes from all sampling sites except Miyi. A strong population structure was found (Φst = 0.76, P<0.0001) with high haplotype diversity (h = 1.00) and low nucleotide diversity (π = 0.0049). The Luoxiao and Nanling Mountains act as historical geographical barriers limiting gene exchange. In the haplotype network there were two “star” clusters. Haplotypes from populations east of the Luoxiao Mountains were represented within one cluster and haplotypes from populations west of the mountain range within the other, with haplotypes from populations south of the Nanling Mountains in between. Lineage sorting between mainland and island populations is incomplete. It remains unknown as to how much adaptive differentiation there is between population groups or within each group. We caution against long-distance transfers within any group, especially when environmental differences are apparent.     

Population Genetic Structure of the Magnificent Frigatebird Fregata magnificens (Aves,Suliformes) Breeding Colonies in the Western Atlantic Ocean

The Magnificent Frigatebird Fregata magnificens has a pantropical distribution, nesting on islands along the Atlantic and Pacific coasts. In the Caribbean, there is little genetic structure among colonies; however, the genetic structure among the colonies off Brazil and its relationship with those in the Caribbean are unknown. In this study, we used mtDNA and microsatellite markers to infer population structure and evolutionary history in a sample of F. magnificens individuals collected in Brazil, Grand Connétable (French Guyana), and Barbuda. Virtually all Brazilian individuals had the same mtDNA haplotype. There was no haplotype sharing between Brazil and the Caribbean, though Grand Connétable shared haplotypes with both regions. A Bayesian clustering analysis using microsatellite data found two genetic clusters: one associated with Barbuda and the other with the Brazilian populations. Grand Connétable was more similar to Barbuda but had ancestry from both clusters, corroborating its “intermediate” position. The Caribbean and Grand Connétable populations showed higher genetic diversity and effective population size compared to the Brazilian population. Overall, our results are in good agreement with an effect of marine winds in isolating the Brazilian meta-population.     

Widespread Genomic Signatures of Natural Selection in Hominid Evolution

Selection acting on genomic functional elements can be detected by its indirect effects on population diversity at linked neutral sites. To illuminate the selective forces that shaped hominid evolution, we analyzed the genomic distributions of human polymorphisms and sequence differences among five primate species relative to the locations of conserved sequence features. Neutral sequence diversity in human and ancestral hominid populations is substantially reduced near such features, resulting in a surprisingly large genome average diversity reduction due to selection of 19–26% on the autosomes and 12–40% on the X chromosome. The overall trends are broadly consistent with “background selection” or hitchhiking in ancestral populations acting to remove deleterious variants. Average selection is much stronger on exonic (both protein-coding and untranslated) conserved features than non-exonic features. Long term selection, rather than complex speciation scenarios, explains the large intragenomic variation in human/chimpanzee divergence. Our analyses reveal a dominant role for selection in shaping genomic diversity and divergence patterns, clarify hominid evolution, and provide a baseline for investigating specific selective events.     

Exploring a Local Genetic Interaction Network Using Evolutionary Replay Experiments

Understanding how genes interact is a central challenge in biology. Experimental evolution provides a useful, but underutilized, tool for identifying genetic interactions, particularly those that involve non-loss-of-function mutations or mutations in essential genes. We previously identified a strong positive genetic interaction between specific mutations in KEL1 (P344T) and HSL7 (A695fs) that arose in an experimentally evolved Saccharomyces cerevisiae population. Because this genetic interaction is not phenocopied by gene deletion, it was previously unknown. Using “evolutionary replay” experiments, we identified additional mutations that have positive genetic interactions with the kel1-P344T mutation. We replayed the evolution of this population 672 times from six timepoints. We identified 30 populations where the kel1-P344T mutation reached high frequency. We performed whole-genome sequencing on these populations to identify genes in which mutations arose specifically in the kel1-P344T background. We reconstructed mutations in the ancestral and kel1-P344T backgrounds to validate positive genetic interactions. We identify several genetic interactors with KEL1, we validate these interactions by reconstruction experiments, and we show these interactions are not recapitulated by loss-of-function mutations. Our results demonstrate the power of experimental evolution to identify genetic interactions that are positive, allele specific, and not readily detected by other methods, shedding light on an underexplored region of the yeast genetic interaction network.     

Evolution of root nodule symbiosis: Focusing on the transcriptional regulation from the genomic point of view

Since molecular phylogenetics recognized root nodule symbiosis (RNS) of all lineages as potentially homologous, scientists have tried to understand the “when” and the “how” of RNS evolution. Initial progress was made on understanding the timing of RNS evolution, facilitating our progress on understanding the underlying genomic changes leading to RNS. Here, we will first cover the different hypotheses on the timings of gains/losses of RNS and show how this has helped us understand how RNS has evolved. Finally, we will discuss how our improved understanding of the genetic changes that led to RNS is now helping us refine our understanding on when RNS has evolved.     

Evolution of polygenic traits under global vs local adaptation

Observations about the number, frequency, effect size, and genomic distribution of alleles associated with complex traits must be interpreted in light of evolutionary process. These characteristics, which constitute a trait’s genetic architecture, can dramatically affect evolutionary outcomes in applications from agriculture to medicine, and can provide a window into how evolution works. Here, I review theoretical predictions about the evolution of genetic architecture under spatially homogeneous, global adaptation as compared with spatially heterogeneous, local adaptation. Due to the tension between divergent selection and migration, local adaptation can favor “concentrated” genetic architectures that are enriched for alleles of larger effect, clustered in a smaller number of genomic regions, relative to expectations under global adaptation. However, the evolution of such architectures may be limited by many factors, including the genotypic redundancy of the trait, mutation rate, and temporal variability of environment. I review the circumstances in which predictions differ for global vs local adaptation and discuss where progress can be made in testing hypotheses using data from natural populations and lab experiments. As the field of comparative population genomics expands in scope, differences in architecture among traits and species will provide insights into how evolution works, and such differences must be interpreted in light of which kind of selection has been operating.     

Evaluation of Group Genetic Ancestry of Populations from Philadelphia and Dakar in the Context of Sex-Biased Admixture in the Americas

Background

Population history can be reflected in group genetic ancestry, where genomic variation captured by the mitochondrial DNA (mtDNA) and non-recombining portion of the Y chromosome (NRY) can separate female- and male-specific admixture processes. Genetic ancestry may influence genetic association studies due to differences in individual admixture within recently admixed populations like African Americans.

Principal Findings

We evaluated the genetic ancestry of Senegalese as well as European Americans and African Americans from Philadelphia. Senegalese mtDNA consisted of ∼12% U haplotypes (U6 and U5b1b haplotypes, common in North Africa) while the NRY haplotypes belonged solely to haplogroup E. In Philadelphia, we observed varying degrees of admixture. While African Americans have 9–10% mtDNAs and ∼31% NRYs of European origin, these results are not mirrored in the mtDNA/NRY pools of European Americans: they have less than 7% mtDNAs and less than 2% NRYs from non-European sources. Additionally, there is <2% Native American contribution to Philadelphian African American ancestry and the admixture from combined mtDNA/NRY estimates is consistent with the admixture derived from autosomal genetic data. To further dissect these estimates, we have analyzed our samples in the context of different demographic groups in the Americas.

Conclusions

We found that sex-biased admixture in African-derived populations is present throughout the Americas, with continual influence of European males, while Native American females contribute mainly to populations of the Caribbean and South America. The high non-European female contribution to the pool of European-derived populations is consistently characteristic of Iberian colonization. These data suggest that genomic data correlate well with historical records of colonization in the Americas.     

Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER

As DNA sequencing technology has markedly advanced in recent years², it has become increasingly evident that the amount of genetic variation between any two individuals is greater than previously thought³. In contrast, array-based genotyping has failed to identify a significant contribution of common sequence variants to the phenotypic variability of common disease^4,5. Taken together, these observations have led to the evolution of the Common Disease / Rare Variant hypothesis suggesting that the majority of the "missing heritability" in common and complex phenotypes is instead due to an individual''s personal profile of rare or private DNA variants^6-8. However, characterizing how rare variation impacts complex phenotypes requires the analysis of many affected individuals at many genomic loci, and is ideally compared to a similar survey in an unaffected cohort. Despite the sequencing power offered by today''s platforms, a population-based survey of many genomic loci and the subsequent computational analysis required remains prohibitive for many investigators.To address this need, we have developed a pooled sequencing approach^1,9 and a novel software package¹ for highly accurate rare variant detection from the resulting data. The ability to pool genomes from entire populations of affected individuals and survey the degree of genetic variation at multiple targeted regions in a single sequencing library provides excellent cost and time savings to traditional single-sample sequencing methodology. With a mean sequencing coverage per allele of 25-fold, our custom algorithm, SPLINTER, uses an internal variant calling control strategy to call insertions, deletions and substitutions up to four base pairs in length with high sensitivity and specificity from pools of up to 1 mutant allele in 500 individuals. Here we describe the method for preparing the pooled sequencing library followed by step-by-step instructions on how to use the SPLINTER package for pooled sequencing analysis (http://www.ibridgenetwork.org/wustl/splinter). We show a comparison between pooled sequencing of 947 individuals, all of whom also underwent genome-wide array, at over 20kb of sequencing per person. Concordance between genotyping of tagged and novel variants called in the pooled sample were excellent. This method can be easily scaled up to any number of genomic loci and any number of individuals. By incorporating the internal positive and negative amplicon controls at ratios that mimic the population under study, the algorithm can be calibrated for optimal performance. This strategy can also be modified for use with hybridization capture or individual-specific barcodes and can be applied to the sequencing of naturally heterogeneous samples, such as tumor DNA.     

ClassTR: Classifying Within-Host Heterogeneity Based on Tandem Repeats with Application to Mycobacterium tuberculosis Infections

Genomic tools have revealed genetically diverse pathogens within some hosts. Within-host pathogen diversity, which we refer to as “complex infection”, is increasingly recognized as a determinant of treatment outcome for infections like tuberculosis. Complex infection arises through two mechanisms: within-host mutation (which results in clonal heterogeneity) and reinfection (which results in mixed infections). Estimates of the frequency of within-host mutation and reinfection in populations are critical for understanding the natural history of disease. These estimates influence projections of disease trends and effects of interventions. The genotyping technique MLVA (multiple loci variable-number tandem repeats analysis) can identify complex infections, but the current method to distinguish clonal heterogeneity from mixed infections is based on a rather simple rule. Here we describe ClassTR, a method which leverages MLVA information from isolates collected in a population to distinguish mixed infections from clonal heterogeneity. We formulate the resolution of complex infections into their constituent strains as an optimization problem, and show its NP-completeness. We solve it efficiently by using mixed integer linear programming and graph decomposition. Once the complex infections are resolved into their constituent strains, ClassTR probabilistically classifies isolates as clonally heterogeneous or mixed by using a model of tandem repeat evolution. We first compare ClassTR with the standard rule-based classification on 100 simulated datasets. ClassTR outperforms the standard method, improving classification accuracy from 48% to 80%. We then apply ClassTR to a sample of 436 strains collected from tuberculosis patients in a South African community, of which 92 had complex infections. We find that ClassTR assigns an alternate classification to 18 of the 92 complex infections, suggesting important differences in practice. By explicitly modeling tandem repeat evolution, ClassTR helps to improve our understanding of the mechanisms driving within-host diversity of pathogens like Mycobacterium tuberculosis.     

Horizontal DNA Transfer Mechanisms of Bacteria as Weapons of Intragenomic Conflict

Horizontal DNA transfer (HDT) is a pervasive mechanism of diversification in many microbial species, but its primary evolutionary role remains controversial. Much recent research has emphasised the adaptive benefit of acquiring novel DNA, but here we argue instead that intragenomic conflict provides a coherent framework for understanding the evolutionary origins of HDT. To test this hypothesis, we developed a mathematical model of a clonally descended bacterial population undergoing HDT through transmission of mobile genetic elements (MGEs) and genetic transformation. Including the known bias of transformation toward the acquisition of shorter alleles into the model suggested it could be an effective means of counteracting the spread of MGEs. Both constitutive and transient competence for transformation were found to provide an effective defence against parasitic MGEs; transient competence could also be effective at permitting the selective spread of MGEs conferring a benefit on their host bacterium. The coordination of transient competence with cell–cell killing, observed in multiple species, was found to result in synergistic blocking of MGE transmission through releasing genomic DNA for homologous recombination while simultaneously reducing horizontal MGE spread by lowering the local cell density. To evaluate the feasibility of the functions suggested by the modelling analysis, we analysed genomic data from longitudinal sampling of individuals carrying Streptococcus pneumoniae. This revealed the frequent within-host coexistence of clonally descended cells that differed in their MGE infection status, a necessary condition for the proposed mechanism to operate. Additionally, we found multiple examples of MGEs inhibiting transformation through integrative disruption of genes encoding the competence machinery across many species, providing evidence of an ongoing “arms race.” Reduced rates of transformation have also been observed in cells infected by MGEs that reduce the concentration of extracellular DNA through secretion of DNases. Simulations predicted that either mechanism of limiting transformation would benefit individual MGEs, but also that this tactic’s effectiveness was limited by competition with other MGEs coinfecting the same cell. A further observed behaviour we hypothesised to reduce elimination by transformation was MGE activation when cells become competent. Our model predicted that this response was effective at counteracting transformation independently of competing MGEs. Therefore, this framework is able to explain both common properties of MGEs, and the seemingly paradoxical bacterial behaviours of transformation and cell–cell killing within clonally related populations, as the consequences of intragenomic conflict between self-replicating chromosomes and parasitic MGEs. The antagonistic nature of the different mechanisms of HDT over short timescales means their contribution to bacterial evolution is likely to be substantially greater than previously appreciated.