Modeling the association of space, time, and host species with variation of the HA, NA, and NS genes of H5N1 highly pathogenic avian influenza viruses isolated from birds in Romania in 2005-2007.

Molecular characterization studies of a diverse collection of avian influenza viruses (AIVs) have demonstrated that AIVs' greatest genetic variability lies in the HA, NA, and NS genes. The objective here was to quantify the association between geographical locations, periods of time, and host species and pairwise nucleotide variation in the HA, NA, and NS genes of 70 isolates of H5N1 highly pathogenic avian influenza virus (HPAIV) collected from October 2005 to December 2007 from birds in Romania. A mixed-binomial Bayesian regression model was used to quantify the probability of nucleotide variation between isolates and its association with space, time, and host species. As expected for the three target genes, a higher probability of nucleotide differences (odds ratios [ORs] > 1) was found between viruses sampled from places at greater geographical distances from each other, viruses sampled over greater periods of time, and viruses derived from different species. The modeling approach in the present study maybe useful in further understanding the molecular epidemiology of H5N1 HPAI virus in bird populations. The methodology presented here will be useful in predicting the most likely genetic distance for any of the three gene segments of viruses that have not yet been isolated or sequenced based on space, time, and host species during the course of an epidemic.

Analysis of high-depth sequence data for studying viral diversity: a comparison of next generation sequencing platforms using Segminator II.

BACKGROUND: Next generation sequencing provides detailed insight into the variation present within viral populations, introducing the possibility of treatment strategies that are both reactive and predictive. Current software tools, however, need to be scaled up to accommodate for high-depth viral data sets, which are often temporally or spatially linked. In addition, due to the development of novel sequencing platforms and chemistries, each with implicit strengths and weaknesses, it will be helpful for researchers to be able to routinely compare and combine data sets from different platforms/chemistries. In particular, error associated with a specific sequencing process must be quantified so that true biological variation may be identified. RESULTS: Segminator II was developed to allow for the efficient comparison of data sets derived from different sources. We demonstrate its usage by comparing large data sets from 12 influenza H1N1 samples sequenced on both the 454 Life Sciences and Illumina platforms, permitting quantification of platform error. For mismatches median error rates at 0.10 and 0.12%, respectively, suggested that both platforms performed similarly. For insertions and deletions median error rates within the 454 data (at 0.3 and 0.2%, respectively) were significantly higher than those within the Illumina data (0.004 and 0.006%, respectively). In agreement with previous observations these higher rates were strongly associated with homopolymeric stretches on the 454 platform. Outside of such regions both platforms had similar indel error profiles. Additionally, we apply our software to the identification of low frequency variants. CONCLUSION: We have demonstrated, using Segminator II, that it is possible to distinguish platform specific error from biological variation using data derived from two different platforms. We have used this approach to quantify the amount of error present within the 454 and Illumina platforms in relation to genomic location as well as location on the read. Given that next generation data is increasingly important in the analysis of drug-resistance and vaccine trials, this software will be useful to the pathogen research community. A zip file containing the source code and jar file is freely available for download from http://www.bioinf.manchester.ac.uk/segminator/.

Single-Cell Transcriptomic Analysis of Cardiac Differentiation from Human PSCs Reveals HOPX-Dependent Cardiomyocyte Maturation.

Cardiac differentiation of human pluripotent stem cells (hPSCs) requires orchestration of dynamic gene regulatory networks during stepwise fate transitions but often generates immature cell types that do not fully recapitulate properties of their adult counterparts, suggesting incomplete activation of key transcriptional networks. We performed extensive single-cell transcriptomic analyses to map fate choices and gene expression programs during cardiac differentiation of hPSCs and identified strategies to improve in vitro cardiomyocyte differentiation. Utilizing genetic gain- and loss-of-function approaches, we found that hypertrophic signaling is not effectively activated during monolayer-based cardiac differentiation, thereby preventing expression of HOPX and its activation of downstream genes that govern late stages of cardiomyocyte maturation. This study therefore provides a key transcriptional roadmap of in vitro cardiac differentiation at single-cell resolution, revealing fundamental mechanisms underlying heart development and differentiation of hPSC-derived cardiomyocytes.

Within-host variation of avian influenza viruses.

The emergence and spread of H5N1 avian influenza viruses from Asia through to Europe and Africa pose a significant animal disease problem and have raised concerns that the virus may pose a pandemic threat to humans. The epizootological factors that have influenced the wide distribution of the virus are complex, and the variety of viruses currently circulating reflects these factors. Sequence analysis of the virus genes sheds light on the H5N1 virus evolution during its emergence and spread, but the degree of virus variation at the level of an individual infected bird has been described in only a few studies. Here, we describe some results of a study in which turkeys, ducks and chickens were infected with either one of two H5N1 or one of three H7N1 viruses, and the degree of sequence variation within an individual infected avian host was examined. We developed 'deep amplicon' sequence analysis for this work, and the methods and results provide a background framework for application to disease outbreaks in the field.

Insertional polymorphisms of ETn retrotransposons include a disruption of the wiz gene in C57BL/6 mice.

ETn (early transposon) elements are moderate repetitive sequences present in hundreds of copies in the mouse genome. Their length ranges from 4.4 to 7.1 kb, and, like transposons, they contain long terminal repeats (LTRs) on both sides and are flanked by target site duplications (Kaghad et al. 1985). ETn-related elements can be grouped into three distinct families. Members of the ETn I and ETn II families mainly contain sequences of unknown origin in their core region. Only very short stretches of retrovirus-like sequences are present, and there are no ORFs. ETn I and ETn II elements differ primarily in the 3- half of both the 5- and 3- LTR, and in the 5- end of the core region (see Fig. 1). As a consequence, only ETn II elements contain a primer binding site for tRNALys. In contrast to ETn I and ETn II, members of the recently described MusD family (Mager and Freeman 2000) contain ORFs for (at least parts of) D-type virus Gag, Pro, and Pol proteins. However, in other regions they are structurally similar to ETn II elements and contain an intact primer binding site. It has been shown that MusD sequences are evolutionarily older than ETn II elements, suggesting that the latter might have arisen by recombinatory replacement of the MusD gene-coding sequences with sequences of unknown origin (Mager and Freeman 2000). ETn elements are still active as retrotransposons. In the past years, several germ line and somatic mutations caused by fresh ETn integrations have been found (Table 1). From 19 mutations, sufficient sequence is available in seven cases to show that the insertion was an ETn II element. In eight cases, the sequence data available indicate either an ETn II or a MusD element. ETn I has not been found to be the cause of any mutations, prompting the suggestion that ETn II is the "mobile" family, whereas ETn I elements have lost the capacity to retrotranspose.

Structure and expression of mobile ETnII retroelements and their coding-competent MusD relatives in the mouse.

ETnII elements are mobile members of the repetitive early transposon family of mouse long terminal repeat (LTR) retroelements and have caused a number of mutations by inserting into genes. ETnII sequences lack retroviral genes, but the recent discovery of related MusD retroviral elements with regions similar to gag, pro, and pol suggests that MusD provides the proteins necessary for ETnII transposition in trans. For this study, we analyzed all ETnII elements in the draft sequence of the C57BL/6J genome and classified them into three subtypes (alpha, beta, and gamma) based on structural differences. We then used database searches and quantitative real-time PCR to determine the copy number and expression of ETnII and MusD elements in various mouse strains. In 7.5-day-old embryos of a mouse strain in which two mutations due to ETnII-beta insertions have been identified (SELH/Bc), we detected a three- to sixfold higher level of ETnII-beta and MusD transcripts than in control strains (C57BL/6J and LM/Bc). The increased ETnII transcription level can in part be attributed to a higher number of ETnII-beta elements, but 70% of the MusD transcripts appear to have been derived from one or a few MusD elements that are not detectable in C57BL/6J mice. This element belongs to a young MusD subgroup with intact open reading frames and identical LTRs, suggesting that the overexpressed element(s) in SELH/Bc mice might provide the proteins for the retrotransposition of ETnII and MusD elements. We also show that ETnII is expressed up to 30-fold more than MusD, which could explain why only ETnII, but not MusD, elements have been positively identified as new insertions.