Allele-specific gene expression in a wild nonhuman primate population

Implementation of multi-omics in diagnosis of pediatric rare diseases

The rapid and accurate diagnosis of rare diseases is paramount in directing clinical management. In recent years, the integration of multi-omics approaches has emerged as a potential strategy to overcome diagnostic hurdles. This review examines the application of multi-omics technologies, including genomics, epigenomics, transcriptomics, proteomics, and metabolomics, in relation to the diagnostic journey of rare diseases. We explore how these combined approaches enhance the detection of pathogenic genetic variants and decipher molecular mechanisms. This review highlights the groundbreaking potential of multi-omics in advancing the precision medicine paradigm for rare diseases, offering insights into future directions and clinical applications. IMPACT: This review discusses using current tests and emerging technologies to diagnose pediatric rare diseases. We describe the next steps after inconclusive molecular testing and a structure for using multi-omics in further investigations. The use of multi-omics is expanding, and it is essential to incorporate it into clinical practice to enhance individualized patient care.

The ortholog of human ssDNA-binding protein SSBP3 influences neurodevelopment and autism-like behaviors in Drosophila melanogaster

1p32.3 microdeletion/duplication is implicated in many neurodevelopmental disorders-like phenotypes such as developmental delay, intellectual disability, autism, macro/microcephaly, and dysmorphic features. The 1p32.3 chromosomal region harbors several genes critical for development; however, their validation and characterization remain inadequate. One such gene is the single-stranded DNA-binding protein 3 (SSBP3) and its Drosophila melanogaster ortholog is called sequence-specific single-stranded DNA-binding protein (Ssdp). Here, we investigated consequences of Ssdp manipulations on neurodevelopment, gene expression, physiological function, and autism-associated behaviors using Drosophila models. We found that SSBP3 and Ssdp are expressed in excitatory neurons in the brain. Ssdp overexpression caused morphological alterations in Drosophila wing, mechanosensory bristles, and head. Ssdp manipulations also affected the neuropil brain volume and glial cell number in larvae and adult flies. Moreover, Ssdp overexpression led to differential changes in synaptic density in specific brain regions. We observed decreased levels of armadillo in the heads of Ssdp overexpressing flies, as well as a decrease in armadillo and wingless expression in the larval wing discs, implicating the involvement of the canonical Wnt signaling pathway in Ssdp functionality. RNA sequencing revealed perturbation of oxidative stress-related pathways in heads of Ssdp overexpressing flies. Furthermore, Ssdp overexpressing brains showed enhanced reactive oxygen species (ROS), altered neuronal mitochondrial morphology, and up-regulated fission and fusion genes. Flies with elevated levels of Ssdp exhibited heightened anxiety-like behavior, altered decisiveness, defective sensory perception and habituation, abnormal social interaction, and feeding defects, which were phenocopied in the pan-neuronal Ssdp knockdown flies, suggesting that Ssdp is dosage sensitive. Partial rescue of behavioral defects was observed upon normalization of Ssdp levels. Notably, Ssdp knockdown exclusively in adult flies did not produce behavioral and functional defects. Finally, we show that optogenetic manipulation of Ssdp-expressing neurons altered autism-associated behaviors. Collectively, our findings provide evidence that Ssdp, a dosage-sensitive gene in the 1p32.3 chromosomal region, is associated with various anatomical, physiological, and behavioral defects, which may be relevant to neurodevelopmental disorders like autism. Our study proposes SSBP3 as a critical gene in the 1p32.3 microdeletion/duplication genomic region and sheds light on the functional role of Ssdp in neurodevelopmental processes in Drosophila.

Selection against admixture and gene regulatory divergence in a long-term primate field study

Genetic admixture is central to primate evolution. We combined 50 years of field observations of immigration and group demography with genomic data from ~9 generations of hybrid baboons to investigate the consequences of admixture in the wild. Despite no obvious fitness costs to hybrids, we found signatures of selection against admixture similar to those described for archaic hominins. These patterns were concentrated near genes where ancestry is strongly associated with gene expression. Our analyses also show that introgression is partially predictable across the genome. This study demonstrates the value of integrating genomic and field data for revealing how "genomic signatures of selection" (e.g., reduced introgression in low-recombination regions) manifest in nature; moreover, it underscores the importance of other primates as living models for human evolution.

A guide for the diagnosis of rare and undiagnosed disease: beyond the exome

Rare diseases affect 30 million people in the USA and more than 300-400 million worldwide, often causing chronic illness, disability, and premature death. Traditional diagnostic techniques rely heavily on heuristic approaches, coupling clinical experience from prior rare disease presentations with the medical literature. A large number of rare disease patients remain undiagnosed for years and many even die without an accurate diagnosis. In recent years, gene panels, microarrays, and exome sequencing have helped to identify the molecular cause of such rare and undiagnosed diseases. These technologies have allowed diagnoses for a sizable proportion (25-35%) of undiagnosed patients, often with actionable findings. However, a large proportion of these patients remain undiagnosed. In this review, we focus on technologies that can be adopted if exome sequencing is unrevealing. We discuss the benefits of sequencing the whole genome and the additional benefit that may be offered by long-read technology, pan-genome reference, transcriptomics, metabolomics, proteomics, and methyl profiling. We highlight computational methods to help identify regionally distant patients with similar phenotypes or similar genetic mutations. Finally, we describe approaches to automate and accelerate genomic analysis. The strategies discussed here are intended to serve as a guide for clinicians and researchers in the next steps when encountering patients with non-diagnostic exomes.

Genetic ancestry predicts male-female affiliation in a natural baboon hybrid zone

Opposite-sex social relationships are important predictors of fitness in many animals, including several group-living mammals. Consequently, understanding sources of variance in the tendency to form opposite-sex relationships is important for understanding social evolution. Genetic contributions are of particular interest due to their importance in long-term evolutionary change, but little is known about genetic effects on male-female relationships in social mammals, especially outside of the mating context. Here, we investigate the effects of genetic ancestry on male-female affiliative behaviour in a hybrid zone between the yellow baboon, Papio cynocephalus, and the anubis baboon, Papio anubis, in a population in which male-female social bonds are known predictors of life span. We place our analysis within the context of other social and demographic predictors of affiliative behaviour in baboons. Genetic ancestry was the most consistent predictor of opposite-sex affiliative behaviour we observed, with the exception of strong effects of dominance rank. Our results show that increased anubis genetic ancestry is associated with a subtle, but significantly higher, probability of opposite-sex affiliative behaviour, in both males and females. Additionally, pairs of anubis-like males and anubis-like females were the most likely to socially affiliate, resulting in moderate assortativity in grooming and proximity behaviour as a function of genetic ancestry. Our findings indicate that opposite-sex affiliative behaviour partially diverged during baboon evolution to differentiate yellow and anubis baboons, despite overall similarities in their social structures and mating systems. Furthermore, they suggest that affiliative behaviour may simultaneously promote and constrain baboon admixture, through additive and assortative effects of ancestry, respectively.

Regulatory regions in natural transposable element insertions drive interindividual differences in response to immune challenges in Drosophila

Background

Variation in gene expression underlies interindividual variability in relevant traits including immune response. However, the genetic variation responsible for these gene expression changes remains largely unknown. Among the non-coding variants that could be relevant, transposable element insertions are promising candidates as they have been shown to be a rich and diverse source of cis-regulatory elements.

Results

In this work, we use a population genetics approach to identify transposable element insertions likely to increase the tolerance of Drosophila melanogaster to bacterial infection by affecting the expression of immune-related genes. We identify 12 insertions associated with allele-specific expression changes in immune-related genes. We experimentally validate three of these insertions including one likely to be acting as a silencer, one as an enhancer, and one with a dual role as enhancer and promoter. The direction in the change of gene expression associated with the presence of several of these insertions is consistent with an increased survival to infection. Indeed, for one of the insertions, we show that this is the case by analyzing both natural populations and CRISPR/Cas9 mutants in which the insertion is deleted from its native genomic context.

Conclusions

We show that transposable elements contribute to gene expression variation in response to infection in D. melanogaster and that this variation is likely to affect their survival capacity. Because the role of transposable elements as regulatory elements is not restricted to Drosophila, transposable elements are likely to play a role in immune response in other organisms as well.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13059-021-02471-3.

Testcrosses are an efficient strategy for identifying cis-regulatory variation: Bayesian analysis of allele-specific expression (BayesASE)

Allelic imbalance (AI) occurs when alleles in a diploid individual are differentially expressed and indicates cis acting regulatory variation. What is the distribution of allelic effects in a natural population? Are all alleles the same? Are all alleles distinct? The approach described applies to any technology generating allele-specific sequence counts, for example for chromatin accessibility and can be applied generally including to comparisons between tissues or environments for the same genotype. Tests of allelic effect are generally performed by crossing individuals and comparing expression between alleles directly in the F1. However, a crossing scheme that compares alleles pairwise is a prohibitive cost for more than a handful of alleles as the number of crosses is at least (n2-n)/2 where n is the number of alleles. We show here that a testcross design followed by a hypothesis test of AI between testcrosses can be used to infer differences between nontester alleles, allowing n alleles to be compared with n crosses. Using a mouse data set where both testcrosses and direct comparisons have been performed, we show that the predicted differences between nontester alleles are validated at levels of over 90% when a parent-of-origin effect is present and of 60%-80% overall. Power considerations for a testcross, are similar to those in a reciprocal cross. In all applications, the testing for AI involves several complex bioinformatics steps. BayesASE is a complete bioinformatics pipeline that incorporates state-of-the-art error reduction techniques and a flexible Bayesian approach to estimating AI and formally comparing levels of AI between conditions. The modular structure of BayesASE has been packaged in Galaxy, made available in Nextflow and as a collection of scripts for the SLURM workload manager on github (https://github.com/McIntyre-Lab/BayesASE).

A Genome-Wide Study of Allele-Specific Expression in Colorectal Cancer

Accumulating evidence from small-scale studies has suggested that allele-specific expression (ASE) plays an important role in tumor initiation and progression. However, little is known about genome-wide ASE in tumors. In this study, we conducted a comprehensive analysis of ASE in individuals with colorectal cancer (CRC) on a genome-wide scale. We identified 5.4 thousand genome-wide ASEs of single nucleotide variations (SNVs) from tumor and normal tissues of 59 individuals with CRC. We observed an increased ASE level in tumor samples and the ASEs enriched as hotspots on the genome. Around 63% of the genes located there were previously reported to contain complex regulatory elements, e.g., human leukocyte antigen (HLA), or were implicated in tumor progression. Focussing on the allelic expression of somatic mutations, we found that 37.5% of them exhibited ASE, and genes harboring such somatic mutations, were enriched in important pathways implicated in cancers. In addition, by comparing the expected and observed ASE events in tumor samples, we identified 50 tumor specific ASEs which possibly contributed to the somatic events in the regulatory regions of the genes and significantly enriched known cancer driver genes. By analyzing CRC ASEs from several perspectives, we provided a systematic understanding of how ASE is implicated in both tumor and normal tissues and will be of critical value in guiding ASE studies in cancer.

Direct Testing for Allele-Specific Expression Differences Between Conditions

Allelic imbalance (AI) indicates the presence of functional variation in cis regulatory regions. Detecting cis regulatory differences using AI is widespread, yet there is no formal statistical methodology that tests whether AI differs between conditions. Here, we present a novel model and formally test differences in AI across conditions using Bayesian credible intervals. The approach tests AI by environment (G×E) interactions, and can be used to test AI between environments, genotypes, sex, and any other condition. We incorporate bias into the modeling process. Bias is allowed to vary between conditions, making the formulation of the model general. As gene expression affects power for detection of AI, and, as expression may vary between conditions, the model explicitly takes coverage into account. The proposed model has low type I and II error under several scenarios, and is robust to large differences in coverage between conditions. We reanalyze RNA-seq data from a Drosophila melanogaster population panel, with F1 genotypes, to compare levels of AI between mated and virgin female flies, and we show that AI × genotype interactions can also be tested. To demonstrate the use of the model to test genetic differences and interactions, a formal test between two F1s was performed, showing the expected 20% difference in AI. The proposed model allows a formal test of G×E and G×G, and reaffirms a previous finding that cis regulation is robust between environments.

Bayesian Inference of Allele-Specific Gene Expression Indicates Abundant Cis-Regulatory Variation in Natural Flycatcher Populations

Polymorphism in cis-regulatory sequences can lead to different levels of expression for the two alleles of a gene, providing a starting point for the evolution of gene expression. Little is known about the genome-wide abundance of genetic variation in gene regulation in natural populations but analysis of allele-specific expression (ASE) provides a means for investigating such variation. We performed RNA-seq of multiple tissues from population samples of two closely related flycatcher species and developed a Bayesian algorithm that maximizes data usage by borrowing information from the whole data set and combines several SNPs per transcript to detect ASE. Of 2,576 transcripts analyzed in collared flycatcher, ASE was detected in 185 (7.2%) and a similar frequency was seen in the pied flycatcher. Transcripts with statistically significant ASE commonly showed the major allele in >90% of the reads, reflecting that power was highest when expression was heavily biased toward one of the alleles. This would suggest that the observed frequencies of ASE likely are underestimates. The proportion of ASE transcripts varied among tissues, being lowest in testis and highest in muscle. Individuals often showed ASE of particular transcripts in more than one tissue (73.4%), consistent with a genetic basis for regulation of gene expression. The results suggest that genetic variation in regulatory sequences commonly affects gene expression in natural populations and that it provides a seedbed for phenotypic evolution via divergence in gene expression.

Ovarian cycling and reproductive state shape the vaginal microbiota in wild baboons

BACKGROUND

The vaginal microbiome is an important site of bacterial-mammalian symbiosis. This symbiosis is currently best characterized for humans, where lactobacilli dominate the microbial community and may help defend women against infectious disease. However, lactobacilli do not dominate the vaginal microbiota of any other mammal studied to date, raising key questions about the forces that shape the vaginal microbiome in non-human mammals.

RESULTS

We used Illumina sequencing of the bacterial 16S rRNA gene to investigate variation in the taxonomic composition of the vaginal microbiota in 48 baboons (Papio cynocephalus), members of a well-studied wild population in Kenya. Similar to prior studies, we found that the baboon vaginal microbiota was not dominated by lactobacilli. Despite this difference, and similar to humans, reproductive state was the dominant predictor of baboon vaginal microbiota, with pregnancy, postpartum amenorrhea, and ovarian cycling explaining 18% of the variance in community composition. Furthermore, among cycling females, a striking 39% of variance in community composition was explained by ovarian cycle phase, with an especially distinctive microbial community around ovulation. Periovulatory females exhibited the highest relative abundance of lactic acid-producing bacteria compared to any other phase, with a mean relative abundance of 44%. To a lesser extent, sexual behavior, especially a history of shared sexual partners, also predicted vaginal microbial similarity between baboons.

CONCLUSIONS

Despite striking differences in their dominant microbes, both human and baboon vaginal microbiota exhibit profound changes in composition in response to reproductive state, ovarian cycle phase, and sexual behavior. We found major shifts in composition during ovulation, which may have implications for disease risk and conception success. These findings highlight the need for future studies to account for fine-scale differences in reproductive state, particularly differences between the various phases of the ovarian cycle. Overall, our work contributes to an emerging understanding of the forces that explain intra- and inter-individual variation in the mammalian vaginal microbiome, with particular emphasis on its role in host health and disease risk.

Resource base influences genome-wide DNA methylation levels in wild baboons (Papio cynocephalus)

Variation in resource availability commonly exerts strong effects on fitness-related traits in wild animals. However, we know little about the molecular mechanisms that mediate these effects, or about their persistence over time. To address these questions, we profiled genome-wide whole-blood DNA methylation levels in two sets of wild baboons: (i) 'wild-feeding' baboons that foraged naturally in a savanna environment and (ii) 'Lodge' baboons that had ready access to spatially concentrated human food scraps, resulting in high feeding efficiency and low daily travel distances. We identified 1014 sites (0.20% of sites tested) that were differentially methylated between wild-feeding and Lodge baboons, providing the first evidence that resource availability shapes the epigenome in a wild mammal. Differentially methylated sites tended to occur in contiguous stretches (i.e., in differentially methylated regions or DMRs), in promoters and enhancers, and near metabolism-related genes, supporting their functional importance in gene regulation. In agreement, reporter assay experiments confirmed that methylation at the largest identified DMR, located in the promoter of a key glycolysis-related gene, was sufficient to causally drive changes in gene expression. Intriguingly, all dispersing males carried a consistent epigenetic signature of their membership in a wild-feeding group, regardless of whether males dispersed into or out of this group as adults. Together, our findings support a role for DNA methylation in mediating ecological effects on phenotypic traits in the wild and emphasize the dynamic environmental sensitivity of DNA methylation levels across the life course.

A Flexible, Efficient Binomial Mixed Model for Identifying Differential DNA Methylation in Bisulfite Sequencing Data

Identifying sources of variation in DNA methylation levels is important for understanding gene regulation. Recently, bisulfite sequencing has become a popular tool for investigating DNA methylation levels. However, modeling bisulfite sequencing data is complicated by dramatic variation in coverage across sites and individual samples, and because of the computational challenges of controlling for genetic covariance in count data. To address these challenges, we present a binomial mixed model and an efficient, sampling-based algorithm (MACAU: Mixed model association for count data via data augmentation) for approximate parameter estimation and p-value computation. This framework allows us to simultaneously account for both the over-dispersed, count-based nature of bisulfite sequencing data, as well as genetic relatedness among individuals. Using simulations and two real data sets (whole genome bisulfite sequencing (WGBS) data from Arabidopsis thaliana and reduced representation bisulfite sequencing (RRBS) data from baboons), we show that our method provides well-calibrated test statistics in the presence of population structure. Further, it improves power to detect differentially methylated sites: in the RRBS data set, MACAU detected 1.6-fold more age-associated CpG sites than a beta-binomial model (the next best approach). Changes in these sites are consistent with known age-related shifts in DNA methylation levels, and are enriched near genes that are differentially expressed with age in the same population. Taken together, our results indicate that MACAU is an efficient, effective tool for analyzing bisulfite sequencing data, with particular salience to analyses of structured populations. MACAU is freely available at www.xzlab.org/software.html.

Behavior genetics: past, present, future

The disciplines of developmental psychopathology and behavior genetics are concerned with many of the same questions about the etiology and course of normal and abnormal behavior and about the factors that promote typical development despite the presence of risk. The goal of this paper is to summarize how research in behavior genetics has shed light on questions that are central to developmental psychopathology. We briefly review the origins of behavior genetics, summarize the findings that have been gleaned from several decades of quantitative and molecular genetics research, and describe future directions for research that will delineate gene function as well as pathways from genes to brain to behavior. The importance of environmental contributions, at both genetic and epigenetic levels, will be discussed. We conclude that behavior genetics has made significant contributions to developmental psychopathology by documenting the interplay among risk and protective factors at multiple levels of the organism, by clarifying the causal status of risk exposures, and by identifying factors that account for change and stability in psychopathology. As the tools to identify gene function become increasingly sophisticated, and as behavioral geneticists become increasingly interdisciplinary in their scope, the field is poised to make ever greater contributions to our understanding of typical and atypical development.

Social environmental effects on gene regulation

Social environmental conditions, particularly the experience of social adversity, have long been connected with health and mortality in humans and other social mammals. Efforts to identify the physiological basis for these effects have historically focused on their neurological, endocrinological, and immunological consequences. Recently, this search has been extended to understanding the role of gene regulation in sensing, mediating, and determining susceptibility to social environmental variation. Studies in laboratory rodents, captive primates, and human populations have revealed correlations between social conditions and the regulation of a large number of genes, some of which are likely causal. Gene expression responses to the social environment are, in turn, mediated by a set of underlying regulatory mechanisms, of which epigenetic marks are the best studied to date. Importantly, a number of genes involved in the response to the social environment are also associated with susceptibility to other external stressors, as well as certain diseases. Hence, gene regulatory studies are a promising avenue for understanding, and potentially developing strategies to address, the effects of social adversity on health.

The Influence of Social Systems on Patterns of Mitochondrial DNA Variation in Baboons

Behavior is influenced by genes but can also shape the genetic structure of natural populations. Investigating this link is of great importance because behavioral processes can alter the genetic diversity on which selection acts. Gene flow is one of the main determinants of the genetic structure of a population and dispersal is the behavior that mediates gene flow. Baboons (genus Papio) are among the most intensely studied primate species and serve as a model system to investigate the evolution of social systems using a comparative approach. The general mammalian pattern of male dispersal and female philopatry has thus far been found in baboons, with the exception of hamadryas baboons (Papio hamadryas). As yet, the lack of data on Guinea baboons (Papio papio) creates a taxonomic gap in genus-wide comparative analyses. In our study we investigated the sex-biased dispersal pattern of Guinea baboons in comparison to hamadryas, olive, yellow, and chacma baboons using sequences of the maternally transmitted mitochondrial hypervariable region I. Analyzing whole-range georeferenced samples (N = 777), we found strong evidence for female-biased gene flow in Guinea baboons and confirmed this pattern for hamadryas baboons, as shown by a lack of genetic-geographic structuring. In addition, most genetic variation was found within and not among demes, in sharp contrast to the pattern observed in matrilocal primates including the other baboon taxa. Our results corroborate the notion that the Guinea baboons’ social system shares some important features with that of hamadryas baboons, suggesting similar evolutionary forces have acted to distinguish them from all other baboons.

Puberty and dispersal in a wild primate population

This article is part of a Special Issue "Puberty and Adolescence". The onset of reproduction is preceded by a host of organismal adjustments and transformations, involving morphological, physiological, and behavioral changes. In highly social mammals, including humans and most nonhuman primates, the timing and nature of maturational processes are affected by the animal's social milieu as well as its ecology. Here, we review a diverse set of findings on how maturation unfolds in wild baboons in the Amboseli basin of southern Kenya, and we place these findings in the context of other reports of maturational processes in primates and other mammals. First, we describe the series of events and processes that signal maturation in female and male baboons. Sex differences in age at both sexual maturity and first reproduction documented for this species are consistent with expectations of life history theory; males mature later than females and exhibit an adolescent growth spurt that is absent or minimal in females. Second, we summarize what we know about sources of variance in the timing of maturational processes including natal dispersal. In Amboseli, individuals in a food-enhanced group mature earlier than their wild-feeding counterparts, and offspring of high-ranking females mature earlier than offspring of low-ranking females. We also report on how genetic admixture, which occurs in Amboseli between two closely related baboon taxa, affects individual maturation schedules.

Research progress in allele-specific expression and its regulatory mechanisms

Although the majority of genes are expressed equally from both alleles, some genes are differentially expressed. Organisms possess characteristics to preferentially express a particular allele under regulatory factors, which is termed allele-specific expression (ASE). It is one of the important genetic factors that lead to phenotypic variation and can be used to identify the variance of gene regulation factors. ASE indicates mechanisms such as DNA methylation, histone modifications, and non-coding RNAs function. Here, we review a broad survey of progress in ASE studies, and what this simple yet very effective approach can offer in functional genomics, and possible implications toward our better understanding of the underlying mechanisms of complex traits.

Social environment influences the relationship between genotype and gene expression in wild baboons

Variation in the social environment can have profound effects on survival and reproduction in wild social mammals. However, we know little about the degree to which these effects are influenced by genetic differences among individuals, and conversely, the degree to which social environmental variation mediates genetic reaction norms. To better understand these relationships, we investigated the potential for dominance rank, social connectedness and group size to modify the effects of genetic variation on gene expression in the wild baboons of the Amboseli basin. We found evidence for a number of gene-environment interactions (GEIs) associated with variation in the social environment, encompassing social environments experienced in adulthood as well as persistent effects of early life social environment. Social connectedness, maternal dominance rank and group size all interacted with genotype to influence gene expression in at least one sex, and either in early life or in adulthood. These results suggest that social and behavioural variation, akin to other factors such as age and sex, can impact the genotype-phenotype relationship. We conclude that GEIs mediated by the social environment are important in the evolution and maintenance of individual differences in wild social mammals, including individual differences in responses to social stressors.

Role of Grooming in Reducing Tick Load in Wild Baboons (Papio cynocephalus)

Nonhuman primate species spend a conspicuous amount of time grooming during social interactions, a behavior that probably serves both social and health-related functions. While the social implications of grooming have been relatively well studied, less attention has been paid to the health benefits, especially the removal of ectoparasites, which may act as vectors in disease transmission. In this study, we examined the relationship between grooming behavior, tick load (number of ticks), and haemoprotozoan infection status in a population of wild free-ranging baboons (Papio cynocephalus). We found that the amount of grooming received was influenced by an individual's age, sex and dominance rank. The amount of grooming received, in turn, affected the tick load of an individual. Baboons with higher tick loads had lower packed red cell volume (PCV or haematocrit), one general measure of health status. We detected a tick-borne haemoprotozoan, Babesia microti, but its low prevalence in the population precluded identifying sources of variance in infection.