Precision medicine integrating whole-genome sequencing, comprehensive metabolomics, and advanced imaging.

Genome sequencing has established clinical utility for rare disease diagnosis. While increasing numbers of individuals have undergone elective genome sequencing, a comprehensive study surveying genome-wide disease-associated genes in adults with deep phenotyping has not been reported. Here we report the results of a 3-y precision medicine study with a goal to integrate whole-genome sequencing with deep phenotyping. A cohort of 1,190 adult participants (402 female [33.8%]; mean age, 54 y [range 20 to 89+]; 70.6% European) had whole-genome sequencing, and were deeply phenotyped using metabolomics, advanced imaging, and clinical laboratory tests in addition to family/medical history. Of 1,190 adults, 206 (17.3%) had at least 1 genetic variant with pathogenic (P) or likely pathogenic (LP) assessment that suggests a predisposition of genetic risk. A multidisciplinary clinical team reviewed all reportable findings for the assessment of genotype and phenotype associations, and 137 (11.5%) had genotype and phenotype associations. A high percentage of genotype and phenotype associations (>75%) was observed for dyslipidemia (n = 24), cardiomyopathy, arrhythmia, and other cardiac diseases (n = 42), and diabetes and endocrine diseases (n = 17). A lack of genotype and phenotype associations, a potential burden for patient care, was observed in 69 (5.8%) individuals with P/LP variants. Genomics and metabolomics associations identified 61 (5.1%) heterozygotes with phenotype manifestations affecting serum metabolite levels in amino acid, lipid and cofactor, and vitamin pathways. Our descriptive analysis provides results on the integration of whole-genome sequencing and deep phenotyping for clinical assessments in adults.

An unsupervised learning approach to identify novel signatures of health and disease from multimodal data.

BACKGROUND: Modern medicine is rapidly moving towards a data-driven paradigm based on comprehensive multimodal health assessments. Integrated analysis of data from different modalities has the potential of uncovering novel biomarkers and disease signatures. METHODS: We collected 1385 data features from diverse modalities, including metabolome, microbiome, genetics, and advanced imaging, from 1253 individuals and from a longitudinal validation cohort of 1083 individuals. We utilized a combination of unsupervised machine learning methods to identify multimodal biomarker signatures of health and disease risk. RESULTS: Our method identified a set of cardiometabolic biomarkers that goes beyond standard clinical biomarkers. Stratification of individuals based on the signatures of these biomarkers identified distinct subsets of individuals with similar health statuses. Subset membership was a better predictor for diabetes than established clinical biomarkers such as glucose, insulin resistance, and body mass index. The novel biomarkers in the diabetes signature included 1-stearoyl-2-dihomo-linolenoyl-GPC and 1-(1-enyl-palmitoyl)-2-oleoyl-GPC. Another metabolite, cinnamoylglycine, was identified as a potential biomarker for both gut microbiome health and lean mass percentage. We identified potential early signatures for hypertension and a poor metabolic health outcome. Additionally, we found novel associations between a uremic toxin, p-cresol sulfate, and the abundance of the microbiome genera Intestinimonas and an unclassified genus in the Erysipelotrichaceae family. CONCLUSIONS: Our methodology and results demonstrate the potential of multimodal data integration, from the identification of novel biomarker signatures to a data-driven stratification of individuals into disease subtypes and stages-an essential step towards personalized, preventative health risk assessment.

Target discovery using biobanks and human genetics.

Large-scale biobanks can yield unprecedented insights into our health and provide discoveries of new and potentially targetable biomarkers. Several protective loss-of-function alleles have been identified, including variants that protect against cardiovascular disease, obesity, type 2 diabetes, and asthma and allergic diseases. These alleles serve as indicators of efficacy, mimicking the effects of drugs and suggesting that inhibiting these genes could provide therapeutic benefit, as has been observed for PCSK9. We provide a context for these findings through a multifaceted review covering the use of genetics in drug discovery efforts through genome-wide and phenome-wide association studies, linking deep mutation scanning data to molecular function and highlighting some additional tools that might help in the interpretation of newly discovered variants.

A Molecular Signature in Blood Reveals a Role for p53 in Regulating Malaria-Induced Inflammation.

Immunity that controls parasitemia and inflammation during Plasmodium falciparum (Pf) malaria can be acquired with repeated infections. A limited understanding of this complex immune response impedes the development of vaccines and adjunctive therapies. We conducted a prospective systems biology study of children who differed in their ability to control parasitemia and fever following Pf infection. By integrating whole-blood transcriptomics, flow-cytometric analysis, and plasma cytokine and antibody profiles, we demonstrate that a pre-infection signature of B cell enrichment, upregulation of T helper type 1 (Th1) and Th2 cell-associated pathways, including interferon responses, and p53 activation associated with control of malarial fever and coordinated with Pf-specific immunoglobulin G (IgG) and Fc receptor activation to control parasitemia. Our hypothesis-generating approach identified host molecules that may contribute to differential clinical outcomes during Pf infection. As a proof of concept, we have shown that enhanced p53 expression in monocytes attenuated Plasmodium-induced inflammation and predicted protection from fever.

Profound Perturbation of the Metabolome in Obesity Is Associated with Health Risk.

Obesity is a heterogeneous phenotype that is crudely measured by body mass index (BMI). There is a need for a more precise yet portable method of phenotyping and categorizing risk in large numbers of people with obesity to advance clinical care and drug development. Here, we used non-targeted metabolomics and whole-genome sequencing to identify metabolic and genetic signatures of obesity. We find that obesity results in profound perturbation of the metabolome; nearly a third of the assayed metabolites associated with changes in BMI. A metabolome signature identifies the healthy obese and lean individuals with abnormal metabolomes-these groups differ in health outcomes and underlying genetic risk. Specifically, an abnormal metabolome associated with a 2- to 5-fold increase in cardiovascular events when comparing individuals who were matched for BMI but had opposing metabolome signatures. Because metabolome profiling identifies clinically meaningful heterogeneity in obesity, this approach could help select patients for clinical trials.

Novel insight into the genetic basis of high-altitude pulmonary hypertension in Kyrgyz highlanders.

The Central Asian Kyrgyz highland population provides a unique opportunity to address genetic diversity and understand the genetic mechanisms underlying high-altitude pulmonary hypertension (HAPH). Although a significant fraction of the population is unaffected, there are susceptible individuals who display HAPH in the absence of any lung, cardiac or hematologic disease. We report herein the analysis of the whole-genome sequencing of healthy individuals compared with HAPH patients and other controls (total n = 33). Genome scans reveal selection signals in various regions, encompassing multiple genes from the first whole-genome sequences focusing on HAPH. We show here evidence of three candidate genes MTMR4, TMOD3 and VCAM1 that are functionally associated with well-known molecular and pathophysiological processes and which likely lead to HAPH in this population. These processes are (a) dysfunctional BMP signaling, (b) disrupted tissue repair processes and (c) abnormal endothelial cell function. Whole-genome sequence of well-characterized patients and controls and using multiple statistical tools uncovered novel candidate genes that belong to pathways central to the pathogenesis of HAPH. These studies on high-altitude human populations are pertinent to the understanding of sea level diseases involving hypoxia as a main element of their pathophysiology.

Comparison of phasing strategies for whole human genomes.

Humans are a diploid species that inherit one set of chromosomes paternally and one homologous set of chromosomes maternally. Unfortunately, most human sequencing initiatives ignore this fact in that they do not directly delineate the nucleotide content of the maternal and paternal copies of the 23 chromosomes individuals possess (i.e., they do not 'phase' the genome) often because of the costs and complexities of doing so. We compared 11 different widely-used approaches to phasing human genomes using the publicly available 'Genome-In-A-Bottle' (GIAB) phased version of the NA12878 genome as a gold standard. The phasing strategies we compared included laboratory-based assays that prepare DNA in unique ways to facilitate phasing as well as purely computational approaches that seek to reconstruct phase information from general sequencing reads and constructs or population-level haplotype frequency information obtained through a reference panel of haplotypes. To assess the performance of the 11 approaches, we used metrics that included, among others, switch error rates, haplotype block lengths, the proportion of fully phase-resolved genes, phasing accuracy and yield between pairs of SNVs. Our comparisons suggest that a hybrid or combined approach that leverages: 1. population-based phasing using the SHAPEIT software suite, 2. either genome-wide sequencing read data or parental genotypes, and 3. a large reference panel of variant and haplotype frequencies, provides a fast and efficient way to produce highly accurate phase-resolved individual human genomes. We found that for population-based approaches, phasing performance is enhanced with the addition of genome-wide read data; e.g., whole genome shotgun and/or RNA sequencing reads. Further, we found that the inclusion of parental genotype data within a population-based phasing strategy can provide as much as a ten-fold reduction in phasing errors. We also considered a majority voting scheme for the construction of a consensus haplotype combining multiple predictions for enhanced performance and site coverage. Finally, we also identified DNA sequence signatures associated with the genomic regions harboring phasing switch errors, which included regions of low polymorphism or SNV density.

The human noncoding genome defined by genetic diversity.

Understanding the significance of genetic variants in the noncoding genome is emerging as the next challenge in human genomics. We used the power of 11,257 whole-genome sequences and 16,384 heptamers (7-nt motifs) to build a map of sequence constraint for the human species. This build differed substantially from traditional maps of interspecies conservation and identified regulatory elements among the most constrained regions of the genome. Using new Hi-C experimental data, we describe a strong pattern of coordination over 2 Mb where the most constrained regulatory elements associate with the most essential genes. Constrained regions of the noncoding genome are up to 52-fold enriched for known pathogenic variants as compared to unconstrained regions (21-fold when compared to the genome average). This map of sequence constraint across thousands of individuals is an asset to help interpret noncoding elements in the human genome, prioritize variants and reconsider gene units at a larger scale.

Profiling of Short-Tandem-Repeat Disease Alleles in 12,632 Human Whole Genomes.

Short tandem repeats (STRs) are hyper-mutable sequences in the human genome. They are often used in forensics and population genetics and are also the underlying cause of many genetic diseases. There are challenges associated with accurately determining the length polymorphism of STR loci in the genome by next-generation sequencing (NGS). In particular, accurate detection of pathological STR expansion is limited by the sequence read length during whole-genome analysis. We developed TREDPARSE, a software package that incorporates various cues from read alignment and paired-end distance distribution, as well as a sequence stutter model, in a probabilistic framework to infer repeat sizes for genetic loci, and we used this software to infer repeat sizes for 30 known disease loci. Using simulated data, we show that TREDPARSE outperforms other available software. We sampled the full genome sequences of 12,632 individuals to an average read depth of approximately 30× to 40× with Illumina HiSeq X. We identified 138 individuals with risk alleles at 15 STR disease loci. We validated a representative subset of the samples (n = 19) by Sanger and by Oxford Nanopore sequencing. Additionally, we validated the STR calls against known allele sizes in a set of GeT-RM reference cell-line materials (n = 6). Several STR loci that are entirely guanine or cytosines (G or C) have insufficient read evidence for inference and therefore could not be assayed precisely by TREDPARSE. TREDPARSE extends the limit of STR size detection beyond the physical sequence read length. This extension is critical because many of the disease risk cutoffs are close to or beyond the short sequence read length of 100 to 150 bases.

New Insights into the Genetic Basis of Monge's Disease and Adaptation to High-Altitude.

Human high-altitude (HA) adaptation or mal-adaptation is explored to understand the physiology, pathophysiology, and molecular mechanisms that underlie long-term exposure to hypoxia. Here, we report the results of an analysis of the largest whole-genome-sequencing of Chronic Mountain Sickness (CMS) and nonCMS individuals, identified candidate genes and functionally validated these candidates in a genetic model system (Drosophila). We used PreCIOSS algorithm that uses Haplotype Allele Frequency score to separate haplotypes carrying the favored allele from the noncarriers and accordingly, prioritize genes associated with the CMS or nonCMS phenotype. Haplotypes in eleven candidate regions, with SNPs mostly in nonexonic regions, were significantly different between CMS and nonCMS subjects. Closer examination of individual genes in these regions revealed the involvement of previously identified candidates (e.g., SENP1) and also unreported ones SGK3, COPS5, PRDM1, and IFT122 in CMS. Remarkably, in addition to genes like SENP1, SGK3, and COPS5 which are HIF-dependent, our study reveals for the first time HIF-independent gene PRDM1, indicating an involvement of wider, nonHIF pathways in HA adaptation. Finally, we observed that down-regulating orthologs of these genes in Drosophila significantly enhanced their hypoxia tolerance. Taken together, the PreCIOSS algorithm, applied on a large number of genomes, identifies the involvement of both new and previously reported genes in selection sweeps, highlighting the involvement of multiple hypoxia response systems. Since the overwhelming majority of SNPs are in nonexonic (and possibly regulatory) regions, we speculate that adaptation to HA necessitates greater genetic flexibility allowing for transcript variability in response to graded levels of hypoxia.

Fast and accurate HLA typing from short-read next-generation sequence data with xHLA.

The HLA gene complex on human chromosome 6 is one of the most polymorphic regions in the human genome and contributes in large part to the diversity of the immune system. Accurate typing of HLA genes with short-read sequencing data has historically been difficult due to the sequence similarity between the polymorphic alleles. Here, we introduce an algorithm, xHLA, that iteratively refines the mapping results at the amino acid level to achieve 99-100% four-digit typing accuracy for both class I and II HLA genes, taking only [Formula: see text]3 min to process a 30× whole-genome BAM file on a desktop computer.

The blood DNA virome in 8,000 humans.

The characterization of the blood virome is important for the safety of blood-derived transfusion products, and for the identification of emerging pathogens. We explored non-human sequence data from whole-genome sequencing of blood from 8,240 individuals, none of whom were ascertained for any infectious disease. Viral sequences were extracted from the pool of sequence reads that did not map to the human reference genome. Analyses sifted through close to 1 Petabyte of sequence data and performed 0.5 trillion similarity searches. With a lower bound for identification of 2 viral genomes/100,000 cells, we mapped sequences to 94 different viruses, including sequences from 19 human DNA viruses, proviruses and RNA viruses (herpesviruses, anelloviruses, papillomaviruses, three polyomaviruses, adenovirus, HIV, HTLV, hepatitis B, hepatitis C, parvovirus B19, and influenza virus) in 42% of the study participants. Of possible relevance to transfusion medicine, we identified Merkel cell polyomavirus in 49 individuals, papillomavirus in blood of 13 individuals, parvovirus B19 in 6 individuals, and the presence of herpesvirus 8 in 3 individuals. The presence of DNA sequences from two RNA viruses was unexpected: Hepatitis C virus is revealing of an integration event, while the influenza virus sequence resulted from immunization with a DNA vaccine. Age, sex and ancestry contributed significantly to the prevalence of infection. The remaining 75 viruses mostly reflect extensive contamination of commercial reagents and from the environment. These technical problems represent a major challenge for the identification of novel human pathogens. Increasing availability of human whole-genome sequences will contribute substantial amounts of data on the composition of the normal and pathogenic human blood virome. Distinguishing contaminants from real human viruses is challenging.

Whole-genome sequencing identifies common-to-rare variants associated with human blood metabolites.

Genetic factors modifying the blood metabolome have been investigated through genome-wide association studies (GWAS) of common genetic variants and through exome sequencing. We conducted a whole-genome sequencing study of common, low-frequency and rare variants to associate genetic variations with blood metabolite levels using comprehensive metabolite profiling in 1,960 adults. We focused the analysis on 644 metabolites with consistent levels across three longitudinal data collections. Genetic sequence variations at 101 loci were associated with the levels of 246 (38%) metabolites (P ≤ 1.9 × 10-11). We identified 113 (10.7%) among 1,054 unrelated individuals in the cohort who carried heterozygous rare variants likely influencing the function of 17 genes. Thirteen of the 17 genes are associated with inborn errors of metabolism or other pediatric genetic conditions. This study extends the map of loci influencing the metabolome and highlights the importance of heterozygous rare variants in determining abnormal blood metabolic phenotypes in adults.

Comparative analysis of the Rotarix™ vaccine strain and G1P[8] rotaviruses detected before and after vaccine introduction in Belgium.

G1P[8] rotaviruses are responsible for the majority of human rotavirus infections worldwide. The effect of universal mass vaccination with rotavirus vaccines on circulating G1P[8] rotaviruses is still poorly understood. Therefore we analyzed the complete genomes of the Rotarix™ vaccine strain, and 70 G1P[8] rotaviruses, detected between 1999 and 2010 in Belgium (36 before and 34 after vaccine introduction) to investigate the impact of rotavirus vaccine introduction on circulating G1P[8] strains. All rotaviruses possessed a complete Wa-like genotype constellation, but frequent intra-genogroup reassortments were observed as well as multiple different cluster constellations circulating in a single season. In addition, identical cluster constellations were found to circulate persistently over multiple seasons. The Rotarix™ vaccine strain possessed a unique cluster constellation that was not present in currently circulating G1P[8] strains. At the nucleotide level, the VP6, VP2 and NSP2 gene segments of Rotarix™ were relatively distantly related to any Belgian G1P[8] strain, but other gene segments of Rotarix™ were found in clusters also containing circulating Belgian strains. At the amino acid level, the genetic distance between Rotarix™ and circulating Belgian strains was considerably lower, except for NSP1. When we compared the Belgian G1P[8] strains collected before and after vaccine introduction a reduction in the proportion of strains that were found in the same cluster as the Rotarix™ vaccine strain was observed for most gene segments. The reduction in the proportion of strains belonging to the same cluster may be the result of the vaccine introduction, although natural fluctuations cannot be ruled out.

Deep sequencing of 10,000 human genomes.

We report on the sequencing of 10,545 human genomes at 30×-40× coverage with an emphasis on quality metrics and novel variant and sequence discovery. We find that 84% of an individual human genome can be sequenced confidently. This high-confidence region includes 91.5% of exon sequence and 95.2% of known pathogenic variant positions. We present the distribution of over 150 million single-nucleotide variants in the coding and noncoding genome. Each newly sequenced genome contributes an average of 8,579 novel variants. In addition, each genome carries on average 0.7 Mb of sequence that is not found in the main build of the hg38 reference genome. The density of this catalog of variation allowed us to construct high-resolution profiles that define genomic sites that are highly intolerant of genetic variation. These results indicate that the data generated by deep genome sequencing is of the quality necessary for clinical use.

Transcriptomic evidence for modulation of host inflammatory responses during febrile Plasmodium falciparum malaria.

Identifying molecular predictors and mechanisms of malaria disease is important for understanding how Plasmodium falciparum malaria is controlled. Transcriptomic studies in humans have so far been limited to retrospective analysis of blood samples from clinical cases. In this prospective, proof-of-principle study, we compared whole-blood RNA-seq profiles at pre-and post-infection time points from Malian adults who were either asymptomatic (n = 5) or febrile (n = 3) during their first seasonal PCR-positive P. falciparum infection with those from malaria-naïve Dutch adults after a single controlled human malaria infection (n = 5). Our data show a graded activation of pathways downstream of pro-inflammatory cytokines, with the highest activation in malaria-naïve Dutch individuals and significantly reduced activation in malaria-experienced Malians. Newly febrile and asymptomatic infections in Malians were statistically indistinguishable except for genes activated by pro-inflammatory cytokines. The combined data provide a molecular basis for the development of a pyrogenic threshold as individuals acquire immunity to clinical malaria.

Genome-Wide Evolutionary Analyses of G1P[8] Strains Isolated Before and After Rotavirus Vaccine Introduction.

Rotaviruses are the most important etiological agent of acute gastroenteritis in young children worldwide. Among the first countries to introduce rotavirus vaccines into their national immunization programs were Belgium (November 2006) and Australia (July 2007). Surveillance programs in Belgium (since 1999) and Australia (since 1989) offer the opportunity to perform a detailed comparison of rotavirus strains circulating pre- and postvaccine introduction. G1P[8] rotaviruses are the most prominent genotype in humans, and a total of 157 G1P[8] rotaviruses isolated between 1999 and 2011 were selected from Belgium and Australia and their complete genomes were sequenced. Phylogenetic analysis showed evidence of frequent reassortment among Belgian and Australian G1P[8] rotaviruses. Although many different phylogenetic subclusters were present before and after vaccine introduction, some unique clusters were only identified after vaccine introduction, which could be due to natural fluctuation or the first signs of vaccine-driven evolution. The times to the most recent common ancestors for the Belgian and Australian G1P[8] rotaviruses ranged from 1846 to 1955 depending on the gene segment, with VP7 and NSP4 resulting in the most recent estimates. We found no evidence that rotavirus population size was affected after vaccine introduction and only six amino acid sites in VP2, VP3, VP7, and NSP1 were identified to be under positive selective pressure. Continued surveillance of G1P[8] strains is needed to determine long-term effects of vaccine introductions, particularly now rotavirus vaccines are implemented in the national immunization programs of an increasing number of countries worldwide.

Stool microbiota composition is associated with the prospective risk of Plasmodium falciparum infection.

BACKGROUND: In humans it is unknown if the composition of the gut microbiota alters the risk of Plasmodium falciparum infection or the risk of developing febrile malaria once P. falciparum infection is established. Here we collected stool samples from a cohort composed of 195 Malian children and adults just prior to an intense P. falciparum transmission season. We assayed these samples using massively parallel sequencing of the 16S ribosomal RNA gene to identify the composition of the gut bacterial communities in these individuals. During the ensuing 6-month P. falciparum transmission season we examined the relationship between the stool microbiota composition of individuals in this cohort and their prospective risk of both P. falciparum infection and febrile malaria. RESULTS: Consistent with prior studies, stool microbial diversity in the present cohort increased with age, although the overall microbiota profile was distinct from cohorts in other regions of Africa, Asia and North America. Age-adjusted Cox regression analysis revealed a significant association between microbiota composition and the prospective risk of P. falciparum infection; however, no relationship was observed between microbiota composition and the risk of developing febrile malaria once P. falciparum infection was established. CONCLUSIONS: These findings underscore the diversity of gut microbiota across geographic regions, and suggest that strategic modulation of gut microbiota composition could decrease the risk of P. falciparum infection in malaria-endemic areas, potentially as an adjunct to partially effective malaria vaccines.

A model of a patient-derived IDH1 mutant anaplastic astrocytoma with alternative lengthening of telomeres.

Mutations in isocitrate dehydrogenase 1 (IDH1) have been found in the vast majority of low grade and progressive infiltrating gliomas and are characterized by the production of 2-hydroxyglutarate from α-ketoglutarate. Recent investigations of malignant gliomas have identified additional genetic and chromosomal abnormalities which cluster with IDH1 mutations into two distinct subgroups. The astrocytic subgroup was found to have frequent mutations in ATRX, TP53 and displays alternative lengthening of telomeres. The second subgroup with oligodendrocytic morphology has frequent mutations in CIC or FUBP1, and is linked to co-deletion of the 1p/19q arms. These mutations reflect the development of two distinct molecular pathways representing the majority of IDH1 mutant gliomas. Unfortunately, due to the scarcity of endogenously derived IDH1 mutant models, there is a lack of accurate models to study mechanism and develop new therapy. Here we report the generation of an endogenous IDH1 anaplastic astrocytoma in vivo model with concurrent mutations in TP53, CDKN2A and ATRX. The model has a similar phenotype and histopathology as the original patient tumor, expresses the IDH1 (R132H) mutant protein and exhibits an alternative lengthening of telomeres phenotype. The JHH-273 model is characteristic of anaplastic astrocytoma and represents a valuable tool for investigating the pathogenesis of this distinct molecular subset of gliomas and for preclinical testing of compounds targeting IDH1 mutations or alternative lengthening of telomeres.

Comparative genomic analysis of genogroup 1 (Wa-like) rotaviruses circulating in the USA, 2006-2009.

Group A rotaviruses (RVA) are double stranded RNA viruses that are a significant cause of acute pediatric gastroenteritis. Beginning in 2006 and 2008, respectively, two vaccines, Rotarix™ and RotaTeq®, have been approved for use in the USA for prevention of RVA disease. The effects of possible vaccine pressure on currently circulating strains in the USA and their genome constellations are still under investigation. In this study we report 33 complete RVA genomes (ORF regions) collected in multiple cities across USA during 2006-2009, including 8 collected from children with verified receipt of 3 doses of rotavirus vaccine. The strains included 16 G1P[8], 10 G3P[8], and 7 G9P[8]. All 33 strains had a Wa like backbone with the consensus genotype constellation of G(1/3/9)-P[8]-I1-R1-C1-M1-A1-N1-T1-E1-H1. From maximum likelihood based phylogenetic analyses, we identified 3-7 allelic constellations grouped mostly by respective G types, suggesting a possible allelic segregation based on the VP7 gene of RVA, primarily for the G3 and G9 strains. The vaccine failure strains showed similar grouping for all genes in G9 strains and most genes of G3 strains suggesting that these constellations were necessary to evade vaccine-derived immune protection. Substitutions in the antigenic region of VP7 and VP4 genes were also observed for the vaccine failure strains which could possibly explain how these strains escape vaccine induced immune response. This study helps elucidate how RVA strains are currently evolving in the population post vaccine introduction and supports the need for continued RVA surveillance.