A beginners guide to SNP calling from high-throughput DNA-sequencing data

A primer for disease gene prioritization using next-generation sequencing data

High-throughput next-generation sequencing (NGS) technology produces a tremendous amount of raw sequence data. The challenges for researchers are to process the raw data, to map the sequences to genome, to discover variants that are different from the reference genome, and to prioritize/rank the variants for the question of interest. The recent development of many computational algorithms and programs has vastly improved the ability to translate sequence data into valuable information for disease gene identification. However, the NGS data analysis is complex and could be overwhelming for researchers who are not familiar with the process. Here, we outline the analysis pipeline and describe some of the most commonly used principles and tools for analyzing NGS data for disease gene identification.

Adult genetic risk screening

Recent advances in genetic analysis especially DNA sequencing technology open a new strategy for adult disease prevention by genetic screening. Physicians presently treat disease pathology with less emphasis on disease risk prevention/reduction. Genetic screening has reduced the incidence of untreatable childhood genetic diseases and improved the care of newborns. The opportunity exists to expand screening programs and reduce the incidence of adult onset diseases via genetic risk identification and disease intervention. This article outlines the approach, challenges, and benefits of such screening for adult genetic disease risks.

The future of genomics for developmentalists

The momentum of genomic science will carry it far into the future and into the heart of research on typical and atypical behavioral development. The purpose of this paper is to focus on a few implications and applications of these advances for understanding behavioral development. Quantitative genetics is genomic and will chart the course for molecular genomic research now that these two worlds of genetics are merging in the search for many genes of small effect. Although current attempts to identify specific genes have had limited success, known as the missing heritability problem, whole-genome sequencing will improve this situation by identifying all DNA sequence variations, including rare variants. Because the heritability of complex traits is caused by many DNA variants of small effect in the population, polygenic scores that are composites of hundreds or thousands of DNA variants will be used by developmentalists to predict children's genetic risk and resilience. The most far-reaching advance will be the widespread availability of whole-genome sequence for children, which means that developmentalists would no longer need to obtain DNA or to genotype children in order to use genomic information in research or in the clinic.

Signatures of rapid evolution in urban and rural transcriptomes of white-footed mice (Peromyscus leucopus) in the New York metropolitan area

Urbanization is a major cause of ecological degradation around the world, and human settlement in large cities is accelerating. New York City (NYC) is one of the oldest and most urbanized cities in North America, but still maintains 20% vegetation cover and substantial populations of some native wildlife. The white-footed mouse, Peromyscusleucopus, is a common resident of NYC's forest fragments and an emerging model system for examining the evolutionary consequences of urbanization. In this study, we developed transcriptomic resources for urban P. leucopus to examine evolutionary changes in protein-coding regions for an exemplar "urban adapter." We used Roche 454 GS FLX+ high throughput sequencing to derive transcriptomes from multiple tissues from individuals across both urban and rural populations. From these data, we identified 31,015 SNPs and several candidate genes potentially experiencing positive selection in urban populations of P. leucopus. These candidate genes are involved in xenobiotic metabolism, innate immune response, demethylation activity, and other important biological phenomena in novel urban environments. This study is one of the first to report candidate genes exhibiting signatures of directional selection in divergent urban ecosystems.

Integration of cancer genomics with treatment selection: from the genome to predictive biomarkers

The field of cancer genomics is rapidly advancing as new technology provides detailed genetic and epigenetic profiling of human cancers. The amount of new data available describing the genetic make-up of tumors is paralleled by rapid advances in drug discovery and molecular therapy currently under investigation to treat these diseases. This review summarizes the challenges and approaches associated with the integration of genomic data into the development of new biomarkers in the management of cancer.

Next-generation sequencing diagnostics for neurological diseases/disorders: from a clinical perspective

Neurological diseases encompass a broad, heterogeneous group of disorders ranging from pediatric neurodevelopmental diseases to late-onset neurodegenerative diseases, most of which are poorly understood and few of which are curable. Most of these diseases have a genetic basis and thus are expected to be amenable to genetic or genomic analysis by next-generation sequencing (NGS). While the advancement of contemporary technologies (such as NGS) is exciting, translating this tool into actual benefit for patients and clinicians can be challenging. In a clinical setting, a sequencing test that is fast, non-invasive, cheap and with perfect specificity would be ideal. However, in practice, there are several hurdles and caveats to consider even before a NGS diagnostic testing can be optimally applied. Proper definition of clinical phenotype, selection of the most appropriate subjects and the clinical setting, optimization of both sensitivity and specificity of the test, evaluation of the availability of the infrastructure and expertise, and consideration of economic, ethical and legal issues are vital in the final application of NGS diagnostic screening in the clinics.

Operating Cooperatively (OC) sensor for highly specific recognition of nucleic acids

Molecular Beacon (MB) probes have been extensively used for nucleic acid analysis because of their ability to produce fluorescent signal in solution instantly after hybridization. The indirect binding of MB probe to a target analyte offers several advantages, including: improved genotyping accuracy and the possibility to analyse folded nucleic acids. Here we report on a new design for MB-based sensor, called ‘Operating Cooperatively’ (OC), which takes advantage of indirect binding of MB probe to a target analyte. The sensor consists of two unmodified DNA strands, which hybridize to a universal MB probe and a nucleic acid analyte to form a fluorescent complex. OC sensors were designed to analyze two human SNPs and E.coli 16S rRNA. High specificity of the approach was demonstrated by the detection of true analyte in over 100 times excess amount of single base substituted analytes. Taking into account the flexibility in the design and the simplicity in optimization, we conclude that OC sensors may become versatile and efficient tools for instant DNA and RNA analysis in homogeneous solution.

Clinical genetic testing of periodic fever syndromes

Periodic fever syndromes (PFSs) are a wide group of autoinflammatory diseases. Due to some clinical overlap between different PFSs, differential diagnosis can be a difficult challenge. Nowadays, there are no universally agreed recommendations for most PFSs, and near half of patients may remain without a genetic diagnosis even after performing multiple-gene analyses. Molecular analysis of periodic fevers' causative genes can improve patient quality of life by providing early and accurate diagnosis and allowing the administration of appropriate treatment. In this paper we focus our discussion on effective usefulness of genetic diagnosis of PFSs. The aim of this paper is to establish how much can the diagnostic system improve, in order to increase the success of PFS diagnosis. The mayor expectation in the near future will be addressed to the so-called next generation sequencing approach. Although the application of bioinformatics to high-throughput genetic analysis could allow the identification of complex genotypes, the complexity of this definition will hardly result in a clear contribution for the physician. In our opinion, however, to obtain the best from this new development a rule should always be kept well in mind: use genetics only to answer specific clinical questions.

Detecting rare variants for psychiatric disorders using next generation sequencing: a methods primer

Recent advances in massively parallel sequencing (MPS) have had an extensive impact on research in medical genomics. In particular, the analysis of rare variants using MPS promises to lead to a better understanding of complex disorders. Nevertheless, for meaningful studies that address the genetic basis for neuropsychiatric disorders, at least hundreds of patient samples have to be analyzed. This undertaking is still not feasible for single research groups on a whole-genome scale and in individual samples. Thus, researchers increasingly employ strategies for reducing the amount of sequencing efforts, such as target enrichment and non-barcoded sample pooling. This review provides an overview of current technologies, discusses options for reduced experimental designs, and illustrates the successful application of the presented methodologies in a recent study of panic disorder patients. Thereby, it aims to introduce the emerging field of MPS into neuropsychiatric research and might serve as a guide for further studies.