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/

Comparative Analysis of Pyrosequencing and a Phylogenetic Microarray for Exploring Microbial Community Structures in the Human Distal Intestine

Background Variations in the composition of the human intestinal microbiota are linked to diverse health conditions. High-throughput molecular technologies have recently elucidated microbial community structure at much higher resolution than was previously possible. Here we compare two such methods, pyrosequencing and a phylogenetic array, and evaluate classifications based on two variable 16S rRNA gene regions. Methods and Findings Over 1.75 million amplicon sequences were generated from the V4 and V6 regions of 16S rRNA genes in bacterial DNA extracted from four fecal samples of elderly individuals. The phylotype richness, for individual samples, was 1,400–1,800 for V4 reads and 12,500 for V6 reads, and 5,200 unique phylotypes when combining V4 reads from all samples. The RDP-classifier was more efficient for the V4 than for the far less conserved and shorter V6 region, but differences in community structure also affected efficiency. Even when analyzing only 20% of the reads, the majority of the microbial diversity was captured in two samples tested. DNA from the four samples was hybridized against the Human Intestinal Tract (HIT) Chip, a phylogenetic microarray for community profiling. Comparison of clustering of genus counts from pyrosequencing and HITChip data revealed highly similar profiles. Furthermore, correlations of sequence abundance and hybridization signal intensities were very high for lower-order ranks, but lower at family-level, which was probably due to ambiguous taxonomic groupings. Conclusions The RDP-classifier consistently assigned most V4 sequences from human intestinal samples down to genus-level with good accuracy and speed. This is the deepest sequencing of single gastrointestinal samples reported to date, but microbial richness levels have still not leveled out. A majority of these diversities can also be captured with five times lower sampling-depth. HITChip hybridizations and resulting community profiles correlate well with pyrosequencing-based compositions, especially for lower-order ranks, indicating high robustness of both approaches. However, incompatible grouping schemes make exact comparison difficult

School Effects on the Wellbeing of Children and Adolescents

Well-being is a multidimensional construct, with psychological, physical and social components. As theoretical basis to help understand this concept and how it relates to school, we propose the Self-Determination Theory, which contends that self-determined motivation and personality integration, growth and well-being are dependent on a healthy balance of three innate psychological needs of autonomy, relatedness and competence. Thus, current indicators involve school effects on children’s well-being, in many diverse modalities which have been explored. Some are described in this chapter, mainly: the importance of peer relationships; the benefits of friendship; the effects of schools in conjunction with some forms of family influence; the school climate in terms of safety and physical ecology; the relevance of the teacher input; the school goal structure and the implementation of cooperative learning. All these parameters have an influence in promoting optimal functioning among children and increasing their well-being by meeting the above mentioned needs. The empirical support for the importance of schools indicates significant small effects, which often translate into important real-life effects as it is admitted at present. The conclusion is that schools do make a difference in children’s peer relationships and well-being

Next-generation genotyping of hypervariable loci in many individuals of a non-model species: technical and theoretical implications

BACKGROUND: Across species, diversity at the Major Histocompatibility Complex (MHC) is critical to disease resistance and population health; however, use of MHC diversity to quantify the genetic health of populations has been hampered by the extreme variation found in MHC genes. Next generation sequencing (NGS) technology generates sufficient data to genotype even the most diverse species, but workflows for distinguishing artifacts from alleles are still under development. We used NGS to evaluate the MHC diversity of over 300 captive and wild ring-tailed lemurs (Lemur catta: Primates: Mammalia). We modified a published workflow to address errors that arise from deep sequencing individuals and tested for evidence of selection at the most diverse MHC genes. RESULTS: In addition to evaluating the accuracy of 454 Titanium and Ion Torrent PGM for genotyping large populations at hypervariable genes, we suggested modifications to improve current methods of allele calling. Using these modifications, we genotyped 302 out of 319 individuals, obtaining an average sequencing depth of over 1000 reads per amplicon. We identified 55 MHC-DRB alleles, 51 of which were previously undescribed, and provide the first sequences of five additional MHC genes: DOA, DOB, DPA, DQA, and DRA. The additional five MHC genes had one or two alleles each with little sequence variation; however, the 55 MHC-DRB alleles showed a high dN/dS ratio and trans-species polymorphism, indicating a history of positive selection. Because each individual possessed 1–7 MHC-DRB alleles, we suggest that ring-tailed lemurs have four, putatively functional, MHC-DRB copies. CONCLUSIONS: In the future, accurate genotyping methods for NGS data will be critical to assessing genetic variation in non-model species. We recommend that future NGS studies increase the proportion of replicated samples, both within and across platforms, particularly for hypervariable genes like the MHC. Quantifying MHC diversity within non-model species is the first step to assessing the relationship of genetic diversity at functional loci to individual fitness and population viability. Owing to MHC-DRB diversity and copy number, ring-tailed lemurs may serve as an ideal model for estimating the interaction between genetic diversity, fitness, and environment, especially regarding endangered species. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12864-016-2503-y) contains supplementary material, which is available to authorized users