Genomic landscape of rat strain and substrain variation

Background

Since the completion of the rat reference genome in 2003, whole-genome sequencing data from more than 40 rat strains have become available. These data represent the broad range of strains that are used in rat research including commonly used substrains. Currently, this wealth of information cannot be used to its full extent, because the variety of different variant calling algorithms employed by different groups impairs comparison between strains. In addition, all rat whole genome sequencing studies to date used an outdated reference genome for analysis (RGSC3.4 released in 2004).

Results

Here we present a comprehensive, multi-sample and uniformly called set of genetic variants in 40 rat strains, including 19 substrains. We reanalyzed all primary data using a recent version of the rat reference assembly (RGSC5.0 released in 2012) and identified over 12 million genomic variants (SNVs, indels and structural variants) among the 40 strains. 28,318 SNVs are specific to individual substrains, which may be explained by introgression from other unsequenced strains and ongoing evolution by genetic drift. Substrain SNVs may have a larger predicted functional impact compared to older shared SNVs.

Conclusions

In summary we present a comprehensive catalog of uniformly analyzed genetic variants among 40 widely used rat inbred strains based on the RGSC5.0 assembly. This represents a valuable resource, which will facilitate rat functional genomic research. In line with previous observations, our genome-wide analyses do not show evidence for contribution of multiple ancestral founder rat subspecies to the currently used rat inbred strains, as is the case for mouse. In addition, we find that the degree of substrain variation is highly variable between strains, which is of importance for the correct interpretation of experimental data from different labs.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1594-1) contains supplementary material, which is available to authorized users.     

Evaluation of variant identification methods for whole genome sequencing data in dairy cattle

Background

Advances in human genomics have allowed unprecedented productivity in terms of algorithms, software, and literature available for translating raw next-generation sequence data into high-quality information. The challenges of variant identification in organisms with lower quality reference genomes are less well documented. We explored the consequences of commonly recommended preparatory steps and the effects of single and multi sample variant identification methods using four publicly available software applications (Platypus, HaplotypeCaller, Samtools and UnifiedGenotyper) on whole genome sequence data of 65 key ancestors of Swiss dairy cattle populations. Accuracy of calling next-generation sequence variants was assessed by comparison to the same loci from medium and high-density single nucleotide variant (SNV) arrays.

Results

The total number of SNVs identified varied by software and method, with single (multi) sample results ranging from 17.7 to 22.0 (16.9 to 22.0) million variants. Computing time varied considerably between software. Preparatory realignment of insertions and deletions and subsequent base quality score recalibration had only minor effects on the number and quality of SNVs identified by different software, but increased computing time considerably. Average concordance for single (multi) sample results with high-density chip data was 58.3% (87.0%) and average genotype concordance in correctly identified SNVs was 99.2% (99.2%) across software. The average quality of SNVs identified, measured as the ratio of transitions to transversions, was higher using single sample methods than multi sample methods. A consensus approach using results of different software generally provided the highest variant quality in terms of transition/transversion ratio.

Conclusions

Our findings serve as a reference for variant identification pipeline development in non-human organisms and help assess the implication of preparatory steps in next-generation sequencing pipelines for organisms with incomplete reference genomes (pipeline code is included). Benchmarking this information should prove particularly useful in processing next-generation sequencing data for use in genome-wide association studies and genomic selection.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-948) contains supplementary material, which is available to authorized users.     

Are special read alignment strategies necessary and cost-effective when handling sequencing reads from patient-derived tumor xenografts?

Background

Patient-derived tumor xenografts in mice are widely used in cancer research and have become important in developing personalized therapies. When these xenografts are subject to DNA sequencing, the samples could contain various amounts of mouse DNA. It has been unclear how the mouse reads would affect data analyses. We conducted comprehensive simulations to compare three alignment strategies at different mutation rates, read lengths, sequencing error rates, human-mouse mixing ratios and sequenced regions. We also sequenced a nasopharyngeal carcinoma xenograft and a cell line to test how the strategies work on real data.

Results

We found the "filtering" and "combined reference" strategies performed better than aligning reads directly to human reference in terms of alignment and variant calling accuracies. The combined reference strategy was particularly good at reducing false negative variants calls without significantly increasing the false positive rate. In some scenarios the performance gain of these two special handling strategies was too small for special handling to be cost-effective, but it was found crucial when false non-synonymous SNVs should be minimized, especially in exome sequencing.

Conclusions

Our study systematically analyzes the effects of mouse contamination in the sequencing data of human-in-mouse xenografts. Our findings provide information for designing data analysis pipelines for these data.

Electronic supplementary material

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Characterization of a Natural Mutator Variant of Human DNA Polymerase λ which Promotes Chromosomal Instability by Compromising NHEJ

Background

DNA polymerase lambda (Polλ) is a DNA repair polymerase, which likely plays a role in base excision repair (BER) and in non-homologous end joining (NHEJ) of DNA double-strand breaks (DSB).

Principal Findings

Here, we described a novel natural allelic variant of human Polλ (hPolλ) characterized by a single nucleotide polymorphism (SNP), C/T variation in the first base of codon 438, resulting in the amino acid change Arg to Trp. In vitro enzyme activity assays of the purified W438 Polλ variant revealed that it retained both DNA polymerization and deoxyribose phosphate (dRP) lyase activities, but had reduced base substitution fidelity. Ectopic expression of the W438 hPolλ variant in mammalian cells increases mutation frequency, affects the DSB repair NHEJ pathway, and generates chromosome aberrations. All these phenotypes are dependent upon the catalytic activity of the W438 hPolλ.

Conclusions

The expression of a cancer-related natural variant of one specialized DNA polymerase can be associated to generic instability at the cromosomal level, probably due a defective NHEJ. These results establish that chromosomal aberrations can result from mutations in specialized DNA repair polymerases.     

Benchmarking mutation effect prediction algorithms using functionally validated cancer-related missense mutations

Background

Massively parallel sequencing studies have led to the identification of a large number of mutations present in a minority of cancers of a given site. Hence, methods to identify the likely pathogenic mutations that are worth exploring experimentally and clinically are required. We sought to compare the performance of 15 mutation effect prediction algorithms and their agreement. As a hypothesis-generating aim, we sought to define whether combinations of prediction algorithms would improve the functional effect predictions of specific mutations.

Results

Literature and database mining of single nucleotide variants (SNVs) affecting 15 cancer genes was performed to identify mutations supported by functional evidence or hereditary disease association to be classified either as non-neutral (n = 849) or neutral (n = 140) with respect to their impact on protein function. These SNVs were employed to test the performance of 15 mutation effect prediction algorithms. The accuracy of the prediction algorithms varies considerably. Although all algorithms perform consistently well in terms of positive predictive value, their negative predictive value varies substantially. Cancer-specific mutation effect predictors display no-to-almost perfect agreement in their predictions of these SNVs, whereas the non-cancer-specific predictors showed no-to-moderate agreement. Combinations of predictors modestly improve accuracy and significantly improve negative predictive values.

Conclusions

The information provided by mutation effect predictors is not equivalent. No algorithm is able to predict sufficiently accurately SNVs that should be taken forward for experimental or clinical testing. Combining algorithms aggregates orthogonal information and may result in improvements in the negative predictive value of mutation effect predictions.

Electronic supplementary material

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Amino Acid Usage Is Asymmetrically Biased in AT- and GC-Rich Microbial Genomes

Introduction

Genomic base composition ranges from less than 25% AT to more than 85% AT in prokaryotes. Since only a small fraction of prokaryotic genomes is not protein coding even a minor change in genomic base composition will induce profound protein changes. We examined how amino acid and codon frequencies were distributed in over 2000 microbial genomes and how these distributions were affected by base compositional changes. In addition, we wanted to know how genome-wide amino acid usage was biased in the different genomes and how changes to base composition and mutations affected this bias. To carry this out, we used a Generalized Additive Mixed-effects Model (GAMM) to explore non-linear associations and strong data dependences in closely related microbes; principal component analysis (PCA) was used to examine genomic amino acid- and codon frequencies, while the concept of relative entropy was used to analyze genomic mutation rates.

Results

We found that genomic amino acid frequencies carried a stronger phylogenetic signal than codon frequencies, but that this signal was weak compared to that of genomic %AT. Further, in contrast to codon usage bias (CUB), amino acid usage bias (AAUB) was differently distributed in AT- and GC-rich genomes in the sense that AT-rich genomes did not prefer specific amino acids over others to the same extent as GC-rich genomes. AAUB was also associated with relative entropy; genomes with low AAUB contained more random mutations as a consequence of relaxed purifying selection than genomes with higher AAUB.

Conclusion

Genomic base composition has a substantial effect on both amino acid- and codon frequencies in bacterial genomes. While phylogeny influenced amino acid usage more in GC-rich genomes, AT-content was driving amino acid usage in AT-rich genomes. We found the GAMM model to be an excellent tool to analyze the genomic data used in this study.     

Expression of human nPTB is limited by extreme suboptimal codon content

Background

The frequency of synonymous codon usage varies widely between organisms. Suboptimal codon content limits expression of viral, experimental or therapeutic heterologous proteins due to limiting cognate tRNAs. Codon content is therefore often adjusted to match codon bias of the host organism. Codon content also varies between genes within individual mammalian species. However, little attention has been paid to the consequences of codon content upon translation of host proteins.

Methodology/Principal Findings

In comparing the splicing repressor activities of transfected human PTB and its two tissue-restricted paralogs–nPTB and ROD1–we found that the three proteins were expressed at widely varying levels. nPTB was expressed at 1–3% the level of PTB despite similar levels of mRNA expression and 74% amino acid identity. The low nPTB expression was due to the high proportion of codons with A or U at the third codon position, which are suboptimal in human mRNAs. Optimization of the nPTB codon content, akin to the “humanization” of foreign ORFs, allowed efficient translation in vivo and in vitro to levels comparable with PTB. We were then able to demonstrate that all three proteins act as splicing repressors.

Conclusions/Significance

Our results provide a striking illustration of the importance of mRNA codon content in determining levels of protein expression, even within cells of the natural host species.     

Edge effects in calling variants from targeted amplicon sequencing

Background

Analysis of targeted amplicon sequencing data presents some unique challenges in comparison to the analysis of random fragment sequencing data. Whereas reads from randomly fragmented DNA have arbitrary start positions, the reads from amplicon sequencing have fixed start positions that coincide with the amplicon boundaries. As a result, any variants near the amplicon boundaries can cause misalignments of multiple reads that can ultimately lead to false-positive or false-negative variant calls.

Results

We show that amplicon boundaries are variant calling blind spots where the variant calls are highly inaccurate. We propose that an effective strategy to avoid these blind spots is to incorporate the primer bases in obtaining read alignments and post-processing of the alignments, thereby effectively moving these blind spots into the primer binding regions (which are not used for variant calling). Targeted sequencing data analysis pipelines can provide better variant calling accuracy when primer bases are retained and sequenced.

Conclusions

Read bases beyond the variant site are necessary for analysis of amplicon sequencing data. Enzymatic primer digestion, if used in the target enrichment process, should leave at least a few primer bases to ensure that these bases are available during data analysis. The primer bases should only be removed immediately before the variant calling step to ensure that the variants can be called irrespective of where they occur within the amplicon insert region.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-1073) contains supplementary material, which is available to authorized users.     

Versatile Dual Reporter Gene Systems for Investigating Stop Codon Readthrough in Plants

Background

Translation is most often terminated when a ribosome encounters the first in-frame stop codon (UAA, UAG or UGA) in an mRNA. However, many viruses (and some cellular mRNAs) contain “stop” codons that cause a proportion of ribosomes to terminate and others to incorporate an amino acid and continue to synthesize a “readthrough”, or C-terminally extended, protein. This dynamic redefinition of codon meaning is dependent on specific sequence context.

Methodology

We describe two versatile dual reporter systems which facilitate investigation of stop codon readthrough in vivo in intact plants, and identification of the amino acid incorporated at the decoded stop codon. The first is based on the reporter enzymes NAN and GUS for which sensitive fluorogenic and histochemical substrates are available; the second on GST and GFP.

Conclusions

We show that the NAN-GUS system can be used for direct in planta measurements of readthrough efficiency following transient expression of reporter constructs in leaves, and moreover, that the system is sufficiently sensitive to permit measurement of readthrough in stably transformed plants. We further show that the GST-GFP system can be used to affinity purify readthrough products for mass spectrometric analysis and provide the first definitive evidence that tyrosine alone is specified in vivo by a ‘leaky’ UAG codon, and tyrosine and tryptophan, respectively, at decoded UAA, and UGA codons in the Tobacco mosaic virus (TMV) readthrough context.     

Selective constraints on amino acids estimated by a mechanistic codon substitution model with multiple nucleotide changes

Background

Empirical substitution matrices represent the average tendencies of substitutions over various protein families by sacrificing gene-level resolution. We develop a codon-based model, in which mutational tendencies of codon, a genetic code, and the strength of selective constraints against amino acid replacements can be tailored to a given gene. First, selective constraints averaged over proteins are estimated by maximizing the likelihood of each 1-PAM matrix of empirical amino acid (JTT, WAG, and LG) and codon (KHG) substitution matrices. Then, selective constraints specific to given proteins are approximated as a linear function of those estimated from the empirical substitution matrices.

Results

Akaike information criterion (AIC) values indicate that a model allowing multiple nucleotide changes fits the empirical substitution matrices significantly better. Also, the ML estimates of transition-transversion bias obtained from these empirical matrices are not so large as previously estimated. The selective constraints are characteristic of proteins rather than species. However, their relative strengths among amino acid pairs can be approximated not to depend very much on protein families but amino acid pairs, because the present model, in which selective constraints are approximated to be a linear function of those estimated from the JTT/WAG/LG/KHG matrices, can provide a good fit to other empirical substitution matrices including cpREV for chloroplast proteins and mtREV for vertebrate mitochondrial proteins.

Conclusions/Significance

The present codon-based model with the ML estimates of selective constraints and with adjustable mutation rates of nucleotide would be useful as a simple substitution model in ML and Bayesian inferences of molecular phylogenetic trees, and enables us to obtain biologically meaningful information at both nucleotide and amino acid levels from codon and protein sequences.     

Whole genome profiling of spontaneous and chemically induced mutations in Toxoplasma gondii

Background

Next generation sequencing is helping to overcome limitations in organisms less accessible to classical or reverse genetic methods by facilitating whole genome mutational analysis studies. One traditionally intractable group, the Apicomplexa, contains several important pathogenic protozoan parasites, including the Plasmodium species that cause malaria.Here we apply whole genome analysis methods to the relatively accessible model apicomplexan, Toxoplasma gondii, to optimize forward genetic methods for chemical mutagenesis using N-ethyl-N-nitrosourea (ENU) and ethylmethane sulfonate (EMS) at varying dosages.

Results

By comparing three different lab-strains we show that spontaneously generated mutations reflect genome composition, without nucleotide bias. However, the single nucleotide variations (SNVs) are not distributed randomly over the genome; most of these mutations reside either in non-coding sequence or are silent with respect to protein coding. This is in contrast to the random genomic distribution of mutations induced by chemical mutagenesis. Additionally, we report a genome wide transition vs transversion ratio (ti/tv) of 0.91 for spontaneous mutations in Toxoplasma, with a slightly higher rate of 1.20 and 1.06 for variants induced by ENU and EMS respectively. We also show that in the Toxoplasma system, surprisingly, both ENU and EMS have a proclivity for inducing mutations at A/T base pairs (78.6% and 69.6%, respectively).

Conclusions

The number of SNVs between related laboratory strains is relatively low and managed by purifying selection away from changes to amino acid sequence. From an experimental mutagenesis point of view, both ENU (24.7%) and EMS (29.1%) are more likely to generate variation within exons than would naturally accumulate over time in culture (19.1%), demonstrating the utility of these approaches for yielding proportionally greater changes to the amino acid sequence. These results will not only direct the methods of future chemical mutagenesis in Toxoplasma, but also aid in designing forward genetic approaches in less accessible pathogenic protozoa as well.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-354) contains supplementary material, which is available to authorized users.     

Molecular Adaptation of rbcL in the Heterophyllous Aquatic Plant Potamogeton

Background

Heterophyllous aquatic plants show marked phenotypic plasticity. They adapt to environmental changes by producing different leaf types: submerged, floating and terrestrial leaves. By contrast, homophyllous plants produce only submerged leaves and grow entirely underwater. Heterophylly and submerged homophylly evolved under selective pressure modifying the species-specific optima for photosynthesis, but little is known about the evolutionary outcome of habit. Recent evolutionary analyses suggested that rbcL, a chloroplast gene that encodes a catalytic subunit of RuBisCO, evolves under positive selection in most land plant lineages. To examine the adaptive evolutionary process linked to heterophylly or homophylly, we analyzed positive selection in the rbcL sequences of ecologically diverse aquatic plants, Japanese Potamogeton.

Principal Findings

Phylogenetic and maximum likelihood analyses of codon substitution models indicated that Potamogeton rbcL has evolved under positive Darwinian selection. The positive selection has operated specifically in heterophyllous lineages but not in homophyllous ones in the branch-site models. This suggests that the selective pressure on this chloroplast gene was higher for heterophyllous lineages than for homophyllous lineages. The replacement of 12 amino acids occurred at structurally important sites in the quaternary structure of RbcL, two of which (residue 225 and 281) were identified as potentially under positive selection.

Conclusions/Significance

Our analysis did not show an exact relationship between the amino acid replacements and heterophylly or homophylly but revealed that lineage-specific positive selection acted on the Potamogeton rbcL. The contrasting ecological conditions between heterophyllous and homophyllous plants have imposed different selective pressures on the photosynthetic system. The increased amino acid replacement in RbcL may reflect the continuous fine-tuning of RuBisCO under varying ecological conditions.     

Regulating Factors of PrPres Glycosylation in Creutzfeldt-Jakob Disease - Implications for the Dissemination and the Diagnosis of Human Prion Strains

Objective

The glycoprofile of pathological prion protein (PrP^res) is widely used as a diagnosis marker in Creutzfeldt-Jakob disease (CJD) and is thought to vary in a strain-specific manner. However, that the same glycoprofile of PrP^res always accumulates in the whole brain of one individual has been questioned. We aimed to determine whether and how PrP^res glycosylation is regulated in the brain of patients with sporadic and variant Creutzfeldt-Jakob disease.

Methods

PrP^res glycoprofiles in four brain regions from 134 patients with sporadic or variant CJD were analyzed as a function of the genotype at codon 129 of PRNP and the Western blot type of PrP^res.

Results

The regional distribution of PrP^res glycoforms within one individual was heterogeneous in sporadic but not in variant CJD. PrP^res glycoforms ratio significantly correlated with the genotype at codon 129 of the prion protein gene and the Western blot type of PrP^res in a region-specific manner. In some cases of sCJD, the glycoprofile of thalamic PrP^res was undistinguishable from that observed in variant CJD.

Interpretation

Regulations leading to variations of PrP^res pattern between brain regions in sCJD patients, involving host genotype and Western blot type of PrP^res may contribute to the specific brain targeting of prion strains and have direct implications for the diagnosis of the different forms of CJD.     

Structural Models of Human eEF1A1 and eEF1A2 Reveal Two Distinct Surface Clusters of Sequence Variation and Potential Differences in Phosphorylation

Background

Despite sharing 92% sequence identity, paralogous human translation elongation factor 1 alpha-1 (eEF1A1) and elongation factor 1 alpha-2 (eEF1A2) have different but overlapping functional profiles. This may reflect the differential requirements of the cell-types in which they are expressed and is consistent with complex roles for these proteins that extend beyond delivery of tRNA to the ribosome.

Methodology/Principal Findings

To investigate the structural basis of these functional differences, we created and validated comparative three-dimensional (3-D) models of eEF1A1 and eEF1A2 on the basis of the crystal structure of homologous eEF1A from yeast. The spatial location of amino acid residues that vary between the two proteins was thereby pinpointed, and their surface electrostatic and lipophilic properties were compared. None of the variations amongst buried amino acid residues are judged likely to have a major structural effect on the protein fold, or to affect domain-domain interactions. Nearly all the variant surface-exposed amino acid residues lie on one face of the protein, in two proximal but distinct sub-clusters. The result of previously performed mutagenesis in yeast may be interpreted as confirming the importance of one of these clusters in actin-bundling and filament disorganization. Interestingly, some variant residues lie in close proximity to, and in a few cases show differences in interactions with, residues previously inferred to be directly involved in binding GTP/GDP, eEF1Bα and aminoacyl-tRNA. Additional sequence-based predictions, in conjunction with the 3-D models, reveal likely differences in phosphorylation sites that could reconcile some of the functional differences between the two proteins.

Conclusions

The revelation and putative functional assignment of two distinct sub-clusters on the surface of the protein models should enable rational site-directed mutagenesis, including homologous reverse-substitution experiments, to map surface binding patches onto these proteins. The predicted variant-specific phosphorylation sites also provide a basis for experimental verification by mutagenesis. The models provide a structural framework for interpretation of the resulting functional analysis.     

Genome diversification within a clonal population of pandemic Vibrio parahaemolyticus seems to depend on the life circumstances of each individual bacteria

Background

New strains of Vibrio parahaemolyticus that cause diarrhea in humans by seafood ingestion periodically emerge through continuous evolution in the ocean. Influx and expansion in the Southern Chilean ocean of a highly clonal V. parahaemolyticus (serotype O3:K6) population from South East Asia caused one of the largest seafood-related diarrhea outbreaks in the world. Here, genomics analyses of isolates from this rapidly expanding clonal population offered an opportunity to observe the molecular evolutionary changes often obscured in more diverse populations.

Results

Whole genome sequence comparison of eight independent isolates of this population from mussels or clinical cases (from different years) was performed. Differences of 1366 to 217,729 bp genome length and 13 to 164 bp single nucleotide variants (SNVs) were found. Most genomic differences corresponded to the presence of regions unique to only one or two isolates, and were probably acquired by horizontal gene transfer (HGT). Some DNA gain was chromosomal but most was in plasmids. One isolate had a large region (8,644 bp) missing, which was probably caused by excision of a prophage. Genome innovation by the presence of unique DNA, attributable to HGT from related bacteria, varied greatly among the isolates, with values of 1,366 (ten times the number of highest number of SNVs) to 217,729 (a thousand times more than the number of highest number of SNVs).

Conclusions

The evolutionary forces (SNVs, HGT) acting on each isolate of the same population were found to differ to an extent that probably depended on the ecological scenario and life circumstances of each bacterium.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1385-8) contains supplementary material, which is available to authorized users.     

Similar Prevalence of Low-Abundance Drug-Resistant Variants in Treatment-Naive Patients with Genotype 1a and 1b Hepatitis C Virus Infections as Determined by Ultradeep Pyrosequencing

Background and Objectives

Hepatitis C virus (HCV) variants that confer resistance to direct-acting-antiviral agents (DAA) have been detected by standard sequencing technology in genotype (G) 1 viruses from DAA-naive patients. It has recently been shown that virological response rates are higher and breakthrough rates are lower in G1b infected patients than in G1a infected patients treated with certain classes of HCV DAAs. It is not known whether this corresponds to a difference in the composition of G1a and G1b HCV quasispecies in regards to the proportion of naturally occurring DAA-resistant variants before treatment.

Methods

We used ultradeep pyrosequencing to determine the prevalence of low-abundance (<25% of the sequence reads) DAA-resistant variants in 191 NS3 and 116 NS5B isolates from 208 DAA-naive G1-infected patients.

Results

A total of 3.5 million high-quality reads of ≥200 nucleotides were generated. The median coverage depth was 4150x and 4470x per NS3 and NS5B amplicon, respectively. Both G1a and G1b populations showed Shannon entropy distributions, with no difference between G1a and G1b in NS3 or NS5B region at the nucleotide level. A higher number of substitutions that confer resistance to protease inhibitors were observed in G1a isolates (mainly at amino acid 80 of the NS3 region). The prevalence of amino acid substitutions that confer resistance to NS5B non-nucleoside inhibitors was similar in G1a and G1b isolates. The NS5B S282T variant, which confers resistance to the polymerase inhibitors mericitabine and sofosbuvir, was not detected in any sample.

Conclusion

The quasispecies genetic diversity and prevalence of DAA-resistant variants was similar in G1a and G1b isolates and in both NS3 and NS5B regions, suggesting that this is not a determinant for the higher level of DAA resistance observed across G1a HCV infected patients upon treatment.     

A Digital Network Approach to Infer Sex Behavior in Emerging HIV Epidemics

Purpose

Improve the ability to infer sex behaviors more accurately using network data.

Methods

A hybrid network analytic approach was utilized to integrate: (1) the plurality of reports from others tied to individual(s) of interest; and (2) structural features of the network generated from those ties. Network data was generated from digitally extracted cell-phone contact lists of a purposeful sample of 241 high-risk men in India. These data were integrated with interview responses to describe the corresponding individuals in the contact lists and the ties between them. HIV serostatus was collected for each respondent and served as an internal validation of the model’s predictions of sex behavior.

Results

We found that network-based model predictions of sex behavior and self-reported sex behavior had limited correlation (54% agreement). Additionally, when respondent sex behaviors were re-classified to network model predictions from self-reported data, there was a 30.7% decrease in HIV seroprevalence among groups of men with lower risk behavior, which is consistent with HIV transmission biology.

Conclusion

Combining the relative completeness and objectivity of digital network data with the substantive details of classical interview and HIV biomarker data permitted new analyses and insights into the accuracy of self-reported sex behavior.