Estimating allele frequency from next-generation sequencing of pooled mitochondrial DNA samples

A web-oriented software for the optimization of pooled experiments in NGS for detection of rare mutations

Background

The cost per patient of next generation sequencing for detection of rare mutations may be significantly reduced using pooled experiments. Recently, some techniques have been proposed for the planning of pooled experiments and for the optimal allocation of patients into pools. However, the lack of a user friendly resource for planning the design of pooled experiments forces the scientists to do frequent, complex and long computations.

Results

OPENDoRM is a powerful collection of novel mathematical algorithms usable via an intuitive graphical user interface. It enables researchers to speed up the planning of their routine experiments, as well as, to support scientists without specific bioinformatics expertises. Users can automatically carry out analysis in terms of costs associated with the optimal allocation of patients in pools. They are also able to choose between three distinct pooling mathematical methods, each of which also suggests the optimal configuration for the submitted experiment. Importantly, in order to keep track of the performed experiments, users can save and export the results of their experiments in standard tabular and charts contents.

Conclusion

OPENDoRM is a freely available web-oriented application for the planning of pooled NGS experiments, available at: http://www-labgtp.na.icar.cnr.it/OPENDoRM. Its easy and intuitive graphical user interface enables researchers to plan theirs experiments using novel algorithms, and to interactively visualize the results.

Electronic supplementary material

The online version of this article (doi:10.1186/s13104-016-1889-6) contains supplementary material, which is available to authorized users.

Application of multi-objective optimization to pooled experiments of next generation sequencing for detection of rare mutations

In this paper we propose some mathematical models to plan a Next Generation Sequencing experiment to detect rare mutations in pools of patients. A mathematical optimization problem is formulated for optimal pooling, with respect to minimization of the experiment cost. Then, two different strategies to replicate patients in pools are proposed, which have the advantage to decrease the overall costs. Finally, a multi-objective optimization formulation is proposed, where the trade-off between the probability to detect a mutation and overall costs is taken into account. The proposed solutions are devised in pursuance of the following advantages: (i) the solution guarantees mutations are detectable in the experimental setting, and (ii) the cost of the NGS experiment and its biological validation using Sanger sequencing is minimized. Simulations show replicating pools can decrease overall experimental cost, thus making pooling an interesting option.

Genetic counselling in post-genomic era-to be or not to be

With the surge of genetic tests and technologies, genetic counsellors are faced with the challenge of translating emerging scientific knowledge into practical information for patients, clinicians and public health policy makers. The new tests and technologies also are associated with new psychosocial and ethical considerations. New guidelines are needed for each new discovery of the genomic impact on phenotype, pathology and disease while “old” syndromes and “old” pathology, continue to require attention. In the new post-Human Genome Project era, genetic counsellors will be an integral part of translating genomic discoveries into beneficial impact on human disease, health care, and medical benefits. The needs for genetic counselling should be designed into genomic research at the onset. Genetic counsellors need to handle old while rapidly assimilating new information and the principal challenge is to be up to date and updated.

Extensive variation at MHC DRB in the New Zealand sea lion (Phocarctos hookeri) provides evidence for balancing selection

Marine mammals are often reported to possess reduced variation of major histocompatibility complex (MHC) genes compared with their terrestrial counterparts. We evaluated diversity at two MHC class II B genes, DQB and DRB, in the New Zealand sea lion (Phocarctos hookeri, NZSL) a species that has suffered high mortality owing to bacterial epizootics, using Sanger sequencing and haplotype reconstruction, together with next-generation sequencing. Despite this species' prolonged history of small population size and highly restricted distribution, we demonstrate extensive diversity at MHC DRB with 26 alleles, whereas MHC DQB is dimorphic. We identify four DRB codons, predicted to be involved in antigen binding, that are evolving under adaptive evolution. Our data suggest diversity at DRB may be maintained by balancing selection, consistent with the role of this locus as an antigen-binding region and the species' recent history of mass mortality during a series of bacterial epizootics. Phylogenetic analyses of DQB and DRB sequences from pinnipeds and other carnivores revealed significant allelic diversity, but little phylogenetic depth or structure among pinniped alleles; thus, we could neither confirm nor refute the possibility of trans-species polymorphism in this group. The phylogenetic pattern observed however, suggests some significant evolutionary constraint on these loci in the recent past, with the pattern consistent with that expected following an epizootic event. These data may help further elucidate some of the genetic factors underlying the unusually high susceptibility to bacterial infection of the threatened NZSL, and help us to better understand the extent and pattern of MHC diversity in pinnipeds.

Parallel tagged next-generation sequencing on pooled samples - a new approach for population genetics in ecology and conservation

Next-generation sequencing (NGS) on pooled samples has already been broadly applied in human medical diagnostics and plant and animal breeding. However, thus far it has been only sparingly employed in ecology and conservation, where it may serve as a useful diagnostic tool for rapid assessment of species genetic diversity and structure at the population level. Here we undertake a comprehensive evaluation of the accuracy, practicality and limitations of parallel tagged amplicon NGS on pooled population samples for estimating species population diversity and structure. We obtained 16S and Cyt b data from 20 populations of Leiopelma hochstetteri, a frog species of conservation concern in New Zealand, using two approaches - parallel tagged NGS on pooled population samples and individual Sanger sequenced samples. Data from each approach were then used to estimate two standard population genetic parameters, nucleotide diversity (π) and population differentiation (FST), that enable population genetic inference in a species conservation context. We found a positive correlation between our two approaches for population genetic estimates, showing that the pooled population NGS approach is a reliable, rapid and appropriate method for population genetic inference in an ecological and conservation context. Our experimental design also allowed us to identify both the strengths and weaknesses of the pooled population NGS approach and outline some guidelines and suggestions that might be considered when planning future projects.

Analysis and optimal design for association studies using next-generation sequencing with case-control pools

With its potential to discover a much greater amount of genetic variation, next-generation sequencing is fast becoming an emergent tool for genetic association studies. However, the cost of sequencing all individuals in a large-scale population study is still high in comparison to most alternative genotyping options. While the ability to identify individual-level data is lost (without bar-coding), sequencing pooled samples can substantially lower costs without compromising the power to detect significant associations. We propose a hierarchical Bayesian model that estimates the association of each variant using pools of cases and controls, accounting for the variation in read depth across pools and sequencing error. To investigate the performance of our method across a range of number of pools, number of individuals within each pool, and average coverage, we undertook extensive simulations varying effect sizes, minor allele frequencies, and sequencing error rates. In general, the number of pools and pool size have dramatic effects on power while the total depth of coverage per pool has only a moderate impact. This information can guide the selection of a study design that maximizes power subject to cost, sample size, or other laboratory constraints. We provide an R package (hiPOD: hierarchical Pooled Optimal Design) to find the optimal design, allowing the user to specify a cost function, cost, and sample size limitations, and distributions of effect size, minor allele frequency, and sequencing error rate.