The recent development of a semiconductor-based, non-optical DNA sequencing technology promises scalable, low-cost and rapid sequence data production. The technology has previously been applied mainly to genomic sequencing and targeted re-sequencing. Here we demonstrate the utility of Ion Torrent semiconductor-based sequencing for sensitive, efficient and rapid chromatin immunoprecipitation followed by sequencing (ChIP-seq) through the application of sample preparation methods that are optimized for ChIP-seq on the Ion Torrent platform. We leverage this method for epigenetic profiling of tumour tissues.

This unit describes how to use BWA and the Genome Analysis Toolkit (GATK) to map genome sequencing data to a reference and produce high-quality variant calls that can be used in downstream analyses. The complete workflow includes the core NGS data-processing steps that are necessary to make the raw data suitable for analysis by the GATK, as well as the key methods involved in variant discovery using the GATK.

Pacific Biosciences' single molecule, real-time sequencing technology, SMRT, is one of several next-generation sequencing technologies that are currently in use. In the past, it has been somewhat overlooked because of its lower throughput compared with methods such as Illumina and Ion Torrent, and because of persistent rumors that it is inaccurate. Here, we seek to dispel these misconceptions and show that SMRT is indeed a highly accurate method with many advantages when used to sequence small genomes, including the possibility of facile closure of bacterial genomes without additional experimentation. We also highlight its value in being able to detect modified bases in DNA.

By characterizing the geographic and functional spectrum of human genetic variation, the 1000 Genomes Project aims to build a resource to help to understand the genetic contribution to disease. Here we describe the genomes of 1,092 individuals from 14 populations, constructed using a combination of low-coverage whole-genome and exome sequencing. By developing methods to integrate information across several algorithms and diverse data sources, we provide a validated haplotype map of 38 million single nucleotide polymorphisms, 1.4 million short insertions and deletions, and more than 14,000 larger deletions. We show that individuals from different populations carry different profiles of rare and common variants, and that low-frequency variants show substantial geographic differentiation, which is further increased by the action of purifying selection. We show that evolutionary conservation and coding consequence are key determinants of the strength of purifying selection, that rare-variant load varies substantially across biological pathways, and that each individual contains hundreds of rare non-coding variants at conserved sites, such as motif-disrupting changes in transcription-factor-binding sites. This resource, which captures up to 98% of accessible single nucleotide polymorphisms at a frequency of 1% in related populations, enables analysis of common and low-frequency variants in individuals from diverse, including admixed, populations.

Pacific Biosciences technology provides a fundamentally new data type that provides the potential to overcome some limitations of current next generation sequencing platforms by providing significantly longer reads, single molecule sequencing, low composition bias and an error profile that is orthogonal to other platforms. With these potential advantages in mind, we here evaluate the utility of the Pacific Biosciences RS platform for human medical amplicon resequencing projects. We evaluated the Pacific Biosciences technology for SNP discovery in medical resequencing projects using the Genome Analysis Toolkit, observing high sensitivity and specificity for calling differences in amplicons containing known true or false SNPs. We assessed data quality: most errors were indels (~14%) with few apparent miscalls (~1%). In this work, we define a custom data processing pipeline for Pacific Biosciences data for human data analysis. Critically, the error properties were largely free of the context-specific effects that affect other sequencing technologies. These data show excellent utility for follow-up validation and extension studies in human data and medical genetics projects, but can be extended to other organisms with a reference genome.

Medulloblastomas are the most common malignant brain tumours in children1. Identifying and understanding the genetic events that drive these tumours is critical for the development of more effective diagnostic, prognostic and therapeutic strategies. Recently, our group and others described distinct molecular subtypes of medulloblastoma on the basis of transcriptional and copy number profiles2, 3, 4, 5. Here we use whole-exome hybrid capture and deep sequencing to identify somatic mutations across the coding regions of 92 primary medulloblastoma/normal pairs. Overall, medulloblastomas have low mutation rates consistent with other paediatric tumours, with a median of 0.35 non-silent mutations per megabase. We identified twelve genes mutated at statistically significant frequencies, including previously known mutated genes in medulloblastoma such as CTNNB1, PTCH1, MLL2, SMARCA4 and TP53. Recurrent somatic mutations were newly identified in an RNA helicase gene, DDX3X, often concurrent with CTNNB1 mutations, and in the nuclear co-repressor (N-CoR) complex genes GPS2, BCOR and LDB1. We show that mutant DDX3X potentiates transactivation of a TCF promoter and enhances cell viability in combination with mutant, but not wild-type, β-catenin. Together,our study reveals the alteration of WNT, hedgehog, histone methyltransferase and now N-CoR pathways across medulloblastomas and within specific subtypes of this disease, and nominates the RNA helicase DDX3X as a component of pathogenic β-catenin signallin in medulloblastoma.

At a time when genomes are being sequenced by the hundreds, much attention has shifted from identifying genes and phenotypes to understanding the networks of interactions among genes.We developed a gene network developmental model expanding on previous models of transcription regulatory networks. In our model, each network is described by a matrix representing the interactions between transcription factors, and a vector of continuous values representing the transcription factor expression levels in an individual.In this work we used the gene network model to look at the impact of mating as well as insertions and deletions of genes in the evolution of complexity of these networks. We found that the natural process of diploid mating increases the likelihood of maintaining complexity, especially in higher order networks (more than 10 genes). We also show that gene insertion is a very efficient way to add more genes to a network as it provides a much higher chance of developmental stability.

The principles governing protein evolution under strong selection are important because of the recent history of evolved resistance to insecticides, antibiotics, and vaccines. One experimental approach focuses on studies of mutant proteins and all combinations of mutant sites that could possibly be intermediates in the evolutionary pathway to resistance. In organisms carrying each of the engineered proteins, a measure of protein function or a proxy for fitness is estimated. The correspondence between protein sequence and fitness is widely known as a fitness landscape or adaptive landscape. Here, we examine some empirical fitness landscapes and compare them with simulated landscapes in which the fitnesses are randomly assigned. We find that mutant sites in real proteins show significantly more additivity than those obtained from random simulations. The high degree of additivity is reflected in a summary statistic for adaptive landscapes known as the "roughness," which for the actual proteins so far examined lies in the smallest 0.5% tail of random landscapes.

Short-read sequencing techniques provide the opportunity to capture genome-wide sequence data in a single experiment. A current challenge is to identify questions that shallow-depth genomic data can address successfully and to develop corresponding analytical methods that are statistically sound. Here, we apply the Roche/454 platform to survey natural variation in strains of Drosophila melanogaster from an African (n = 3) and a North American (n = 6) population. Reads were aligned to the reference D. melanogaster genomic assembly, single nucleotide polymorphisms were identified, and nucleotide variation was quantified genome wide. Simulations and empirical results suggest that nucleotide diversity can be accurately estimated from sparse data with as little as 0.2× coverage per line. The unbiased genomic sampling provided by random short-read sequencing also allows insight into distributions of transposable elements and copy number polymorphisms found within populations and demonstrates that short-read sequencing methods provide an efficient means to quantify variation in genome organization and content. Continued development of methods for statistical inference of shallow-depth genome-wide sequencing data will allow such sparse, partial data sets to become the norm in the emerging field of population genomics.

While next generation sequencing is enabling genomic discoveries at an unprecedented pace, their large-scale validation remains a challenge, mostly due to the high costs of preparing large numbers of samples for sequencing. Here we present a cost-effective targeted sequencing framework and analytical methods for large-scale validation and replication, based on a reference sample guided error model and pooled variant calling.

The key concept of this invention is compression of unambiguous regions of the genome. By reducing the representation of these areas and intelligently keeping sufficient information around the ambiguous regions of the genome. The reduced representation enables high-throughput analysis of tens-of-thousands of samples to be performed at once. Despite the compression, it maintains similar or better accuracy (due to being able to process the samples the same time instead of by batches) as using the uncompressed dataset.

A first look at variant calling in two cenarios: variant discovery and genotyping using the upcoming sequencing technologies of Pacific Biosciences RS and Life Technologies ION Torrent. We evaluate the quality of the data generated by these instruments, and the potential for medical and population genetics use for variant calling.

The continuous model gives us a more complete view of the evolution of interacting genes. It allows the addition of more genes to the individuals and is more efficient in maintaining stability. The notion of a continuous output vector also creates a closer relationship with the reality of gene networks and gene products where it is not sufficient to determine whether or not a gene is on or off. Gene product concentrations play an important role in determining the viability of individuals and aids in the creation and maintenance of complexity. This model gives an insight on the mechanisms that regulate the evolution of complexity with a more general model that could be used to represent the concentration of the products of gene networks. The inclusion of gene product concentration brings the model closer to biology and perhaps gives us a better notion to the rarity of complex viable individuals in the real world.

Detailed knowledge about the rate of the genetic variation is vital for understanding how HIV induces disease and develops resistance, as well as for studies on the molecular epidemiology and origin of the virus. The molecular clock hypothesis in molecular evolutionary studies has been controversial since it was first proposed (Zuckerkandl and Pauling, 1965). A variety of methods have been developed to test the molecular clock and these have been applied to many studies, including the molecular evolution of viruses. The many studies and discussions about the existence of a molecular clock suitable to the different genes of the HIV-1 have been based on very small data sets what could likely create biased results. In this study, we tested 179 HIV-1 sequences extracted from the GeneBank, with the motifs most expressive in Brazil (Monica, 2004). The resulting Likelihood Ratio test (Felsenstein, 1981) rejected the molecular clock hypothesis for the env V3 region. This casts doubts on the validity of recent attempts to date the origin of the epidemic.