Haplotype assignment of longitudinal viral deep-sequencing data using co-variation of variant frequencies

Longitudinal deep sequencing of viruses can provide detailed information about intra-host evolutionary dynamics including how viruses interact with and transmit between hosts. Many analyses require haplotype reconstruction, identifying which variants are co-located on the same genomic element. Most current methods to perform this reconstruction are based on a high density of variants and cannot perform this reconstruction for slowly evolving viruses. We present a new approach, HaROLD (HAplotype Reconstruction Of Longitudinal Deep sequencing data), which performs this reconstruction based on identifying co-varying variant frequencies using a probabilistic framework. We illustrate HaROLD on both RNA and DNA viruses with synthetic Illumina paired read data created from mixed human cytomegalovirus and norovirus genomes, and clinical datasets of human cytomegalovirus and norovirus samples, demonstrating high accuracy, especially when longitudinal samples are available

Estimating the Distribution of Selection Coefficients from Phylogenetic Data Using Sitewise Mutation-Selection Models

Estimation of the distribution of selection coefficients of mutations is a long-standing issue in molecular evolution. In addition to population-based methods, the distribution can be estimated from DNA sequence data by phylogenetic-based models. Previous models have generally found unimodal distributions where the probability mass is concentrated between mildly deleterious and nearly neutral mutations. Here we use a sitewise mutation–selection phylogenetic model to estimate the distribution of selection coefficients among novel and fixed mutations (substitutions) in a data set of 244 mammalian mitochondrial genomes and a set of 401 PB2 proteins from influenza. We find a bimodal distribution of selection coefficients for novel mutations in both the mitochondrial data set and for the influenza protein evolving in its natural reservoir, birds. Most of the mutations are strongly deleterious with the rest of the probability mass concentrated around mildly deleterious to neutral mutations. The distribution of the coefficients among substitutions is unimodal and symmetrical around nearly neutral substitutions for both data sets at adaptive equilibrium. About 0.5% of the nonsynonymous mutations and 14% of the nonsynonymous substitutions in the mitochondrial proteins are advantageous, with 0.5% and 24% observed for the influenza protein. Following a host shift of influenza from birds to humans, however, we find among novel mutations in PB2 a trimodal distribution with a small mode of advantageous mutations

Charting the Host Adaptation of Influenza Viruses

Four influenza pandemics have struck the human population during the last 100 years causing substantial morbidity and mortality. The pandemics were caused by the introduction of a new virus into the human population from an avian or swine host or through the mixing of virus segments from an animal host with a human virus to create a new reassortant subtype virus. Understanding which changes have contributed to the adaptation of the virus to the human host is essential in assessing the pandemic potential of current and future animal viruses. Here, we develop a measure of the level of adaptation of a given virus strain to a particular host. We show that adaptation to the human host has been gradual with a timescale of decades and that none of the virus proteins have yet achieved full adaptation to the selective constraints. When the measure is applied to historical data, our results indicate that the 1918 influenza virus had undergone a period of preadaptation prior to the 1918 pandemic. Yet, ancestral reconstruction of the avian virus that founded the classical swine and 1918 human influenza lineages shows no evidence that this virus was exceptionally preadapted to humans. These results indicate that adaptation to humans occurred following the initial host shift from birds to mammals, including a significant amount prior to 1918. The 2009 pandemic virus seems to have undergone preadaptation to human-like selective constraints during its period of circulation in swine. Ancestral reconstruction along the human virus tree indicates that mutations that have increased the adaptation of the virus have occurred preferentially along the trunk of the tree. The method should be helpful in assessing the potential of current viruses to found future epidemics or pandemics

Identifying Changes in Selective Constraints: Host Shifts in Influenza

The natural reservoir of Influenza A is waterfowl. Normally, waterfowl viruses are not adapted to infect and spread in the human population. Sometimes, through reassortment or through whole host shift events, genetic material from waterfowl viruses is introduced into the human population causing worldwide pandemics. Identifying which mutations allow viruses from avian origin to spread successfully in the human population is of great importance in predicting and controlling influenza pandemics. Here we describe a novel approach to identify such mutations. We use a sitewise non-homogeneous phylogenetic model that explicitly takes into account differences in the equilibrium frequencies of amino acids in different hosts and locations. We identify 172 amino acid sites with strong support and 518 sites with moderate support of different selection constraints in human and avian viruses. The sites that we identify provide an invaluable resource to experimental virologists studying adaptation of avian flu viruses to the human host. Identification of the sequence changes necessary for host shifts would help us predict the pandemic potential of various strains. The method is of broad applicability to investigating changes in selective constraints when the timing of the changes is known

Transcriptional diversity during lineage commitment of human blood progenitors.

Blood cells derive from hematopoietic stem cells through stepwise fating events. To characterize gene expression programs driving lineage choice, we sequenced RNA from eight primary human hematopoietic progenitor populations representing the major myeloid commitment stages and the main lymphoid stage. We identified extensive cell type-specific expression changes: 6711 genes and 10,724 transcripts, enriched in non-protein-coding elements at early stages of differentiation. In addition, we found 7881 novel splice junctions and 2301 differentially used alternative splicing events, enriched in genes involved in regulatory processes. We demonstrated experimentally cell-specific isoform usage, identifying nuclear factor I/B (NFIB) as a regulator of megakaryocyte maturation-the platelet precursor. Our data highlight the complexity of fating events in closely related progenitor populations, the understanding of which is essential for the advancement of transplantation and regenerative medicine.The work described in this article was primarily supported by the European Commission Seventh Framework Program through the BLUEPRINT grant with code HEALTH-F5-2011-282510 (D.H., F.B., G.C., J.H.A.M., K.D., L.C., M.F., S.C., S.F., and S.P.G.). Research in the Ouwehand laboratory is further supported by program grants from the National Institute for Health Research (NIHR, www.nihr.ac.uk; to A.A., M.K., P.P., S.B.G.J., S.N., and W.H.O.) and the British Heart Foundation under nos. RP-PG-0310-1002 and RG/09/12/28096 (www.bhf.org.uk; to A.R. and W.J.A.). K.F. and M.K. were supported by Marie Curie funding from the NETSIM FP7 program funded by the European Commission. The laboratory receives funding from the NHS Blood and Transplant for facilities. The Cambridge BioResource (www.cambridgebioresource.org.uk), the Cell Phenotyping Hub, and the Cambridge Translational GenOmics laboratory (www.catgo.org.uk) are supported by an NIHR grant to the Cambridge NIHR Biomedical Research Centre (BRC). The BRIDGE-Bleeding and Platelet Disorders Consortium is supported by the NIHR BioResource—Rare Diseases (http://bioresource.nihr.ac.uk/; to E.T., N.F., and Whole Exome Sequencing effort). Research in the Soranzo laboratory (L.V., N.S., and S. Watt) is further supported by the Wellcome Trust (Grant Codes WT098051 and WT091310) and the EU FP7 EPIGENESYS initiative (Grant Code 257082). Research in the Cvejic laboratory (A. Cvejic and C.L.) is funded by the Cancer Research UK under grant no. C45041/A14953. S.J.S. is funded by NIHR. M.E.F. is supported by a British Heart Foundation Clinical Research Training Fellowship, no. FS/12/27/29405. E.B.-M. is supported by a Wellcome Trust grant, no. 084183/Z/07/Z. Research in the Laffan laboratory is supported by Imperial College BRC. F.A.C., C.L., and S. Westbury are supported by Medical Research Council Clinical Training Fellowships, and T.B. by a British Society of Haematology/NHS Blood and Transplant grant. R.J.R. is a Principal Research Fellow of the Wellcome Trust, grant no. 082961/Z/07/Z. Research in the Flicek laboratory is also supported by the Wellcome Trust (grant no. 095908) and EMBL. Research in the Bertone laboratory is supported by EMBL. K.F. and C.v.G. are supported by FWO-Vlaanderen through grant G.0B17.13N. P.F. is a compensated member of the Omicia Inc. Scientific Advisory Board. This study made use of data generated by the UK10K Consortium, derived from samples from the Cohorts arm of the project.This is the author’s version of the work. It is posted here by permission of the AAAS for personal use, not for redistribution. The definitive version was published in Science on 26/9/14 in volume 345, number 6204, DOI: 10.1126/science.1251033. This version will be under embargo until the 26th of March 2015

A phylogenetic approach for weighting genetic sequences.

BackgroundMany important applications in bioinformatics, including sequence alignment and protein family profiling, employ sequence weighting schemes to mitigate the effects of non-independence of homologous sequences and under- or over-representation of certain taxa in a dataset. These schemes aim to assign high weights to sequences that are 'novel' compared to the others in the same dataset, and low weights to sequences that are over-represented.ResultsWe formalise this principle by rigorously defining the evolutionary 'novelty' of a sequence within an alignment. This results in new sequence weights that we call 'phylogenetic novelty scores'. These scores have various desirable properties, and we showcase their use by considering, as an example application, the inference of character frequencies at an alignment column-important, for example, in protein family profiling. We give computationally efficient algorithms for calculating our scores and, using simulations, show that they are versatile and can improve the accuracy of character frequency estimation compared to existing sequence weighting schemes.ConclusionsOur phylogenetic novelty scores can be useful when an evolutionarily meaningful system for adjusting for uneven taxon sampling is desired. They have numerous possible applications, including estimation of evolutionary conservation scores and sequence logos, identification of targets in conservation biology, and improving and measuring sequence alignment accuracy

A phylogenetic approach for weighting genetic sequences.

BackgroundMany important applications in bioinformatics, including sequence alignment and protein family profiling, employ sequence weighting schemes to mitigate the effects of non-independence of homologous sequences and under- or over-representation of certain taxa in a dataset. These schemes aim to assign high weights to sequences that are 'novel' compared to the others in the same dataset, and low weights to sequences that are over-represented.ResultsWe formalise this principle by rigorously defining the evolutionary 'novelty' of a sequence within an alignment. This results in new sequence weights that we call 'phylogenetic novelty scores'. These scores have various desirable properties, and we showcase their use by considering, as an example application, the inference of character frequencies at an alignment column-important, for example, in protein family profiling. We give computationally efficient algorithms for calculating our scores and, using simulations, show that they are versatile and can improve the accuracy of character frequency estimation compared to existing sequence weighting schemes.ConclusionsOur phylogenetic novelty scores can be useful when an evolutionarily meaningful system for adjusting for uneven taxon sampling is desired. They have numerous possible applications, including estimation of evolutionary conservation scores and sequence logos, identification of targets in conservation biology, and improving and measuring sequence alignment accuracy

Human cytomegalovirus haplotype reconstruction reveals high diversity due to superinfection and evidence of within-host recombination.

Recent sequencing efforts have led to estimates of human cytomegalovirus (HCMV) genome-wide intrahost diversity that rival those of persistent RNA viruses [Renzette N, Bhattacharjee B, Jensen JD, Gibson L, Kowalik TF (2011) PLoS Pathog 7:e1001344]. Here, we deep sequence HCMV genomes recovered from single and longitudinally collected blood samples from immunocompromised children to show that the observations of high within-host HCMV nucleotide diversity are explained by the frequent occurrence of mixed infections caused by genetically distant strains. To confirm this finding, we reconstructed within-host viral haplotypes from short-read sequence data. We verify that within-host HCMV nucleotide diversity in unmixed infections is no greater than that of other DNA viruses analyzed by the same sequencing and bioinformatic methods and considerably less than that of human immunodeficiency and hepatitis C viruses. By resolving individual viral haplotypes within patients, we reconstruct the timing, likely origins, and natural history of superinfecting strains. We uncover evidence for within-host recombination between genetically distinct HCMV strains, observing the loss of the parental virus containing the nonrecombinant fragment. The data suggest selection for strains containing the recombinant fragment, generating testable hypotheses about HCMV evolution and pathogenesis. These results highlight that high HCMV diversity present in some samples is caused by coinfection with multiple distinct strains and provide reassurance that within the host diversity for single-strain HCMV infections is no greater than for other herpesviruses.D.P.D. was supported by a grant from the Medical Research Foundation. C.J.H. was supported by Action Medical Research Grant GN2424. The PATHSEEK consortium was funded by the European Union’s Seventh Programme for research, technological development, and demonstration under grant agreement 304875