Now ready to start real sequencing

As anticipated a couple of posts ago, Life Technologies technicians are installing our brand new ION Proton NGS sequencer in these days. All tests performed fine so we are excited to announce that we are now ready for sequence production!

We hope this will be the beginning of an exciting NGS quest! 

As enthusiastic as we are right now, we have put our lab on the world map of sequencing centers (High-Throughput Sequencing Map site) conceived by James Hadfield (Cancer Research UK, Cambridge) and built by Nick Loman (University of Birmingham).

Meanwhile take a look to our Now-Good-for-Sequencing lab! 

Personalized advertising based on your genomic data

Companies market products and services according to your online browsing behavior, shopping habits, age, and social-network activities. In a very future, they may be able to advertise to you on the basis of your genetic makeup.
Miinome, a Minneapolis-based startup called plans to develop the first “member-controlled human genetic marketplace.” Their innovative idea is to sell DNA information to marketers
The company, which has just three full-time employees and is still hunting for financing, is notable mostly for its bold idea: to sell DNA information to marketers.
A MIT Technology Review article hypothesizes: "Do you carry the genetic variants associated with lactose intolerance? Here, Lactaid has a coupon for you. The genes for male-pattern baldness? That’s accelerated by stress, so maybe you should come in for a discounted massage Jimmy’s Spa & Bath".
“Today, it’s such a niche market, but there’s tremendous growth opportunities there,” said geneticist Michael Schatz of the Cold Spring Harbor Laboratory. “In the endgame, it’s certain [genetics is] going to become one of the factors that big retailers would consider, but I think that’s pretty far off.” More info in this Wired article.

Evaluating variant detection methods: comparison of aligners and callers

Most of present NGS studies aim to the identification of genetic variants related to a condition of interest. To get to this final result you start with your bunch of sequencing reads and then you have to align them to a reference genome, refine the aligned data and finally call the variants, both SNPs or indels...Straighforward, isn't it? Actually there are several tools to perform each one of this steps and everyone of them produce different results and rely on different alghoritms, that make it more suitable for specific applications. So decide which one is better for your NGS data analysis is certainly not so easy...

Recently I've came into this good comparison on variant detection pipelines published on Blue Collar Bioinformatics blog. It considers the major aligner (bwa and novoaling), post-alignment analysis (using popular tools such as Picard and samtools rmdup) and variant callers (GATK UG and HC and freebayes).
For every steps the author report detailed metrics on the SNPs and indels called, their concordance and so on, giving a framework for the evaluation of the various solutions and assembly of your own analysis workflow.
For example in this picture from the original post on Blue Collar you can appreciate how even the choice of the aligner could impact your final variant dataset, mainly due to different strictness in dealing with indels that results in different depth of coverage in some regions.

As reported by the author: "This evaluation work is part of a larger community effort to better characterize variant calling methods. A key component of these evaluations is a well characterized set of reference variations for the NA12878 human HapMap genome, provided by NIST’s Genome in a Bottle consortium. The diagnostic component of this work supplements emerging tools like GCAT (Genome Comparison and Analytic Testing), which provides a community platform for comparing and discussing calling approaches."

Don't miss this!

Breaking News: the real stuff has arrived!

We are happy to announce that we are finally entering the NGS arena, and this time for real!

These not so mysterious boxes contain a just delivered ION Proton Sequencer with all the related instruments!

In the morning we finally received all the materials (besides the consumables) that will enables us to perform a whole experiment, from data production to data analysis! We are now waiting for the instrument installation to perform our first run! Stay tuned to follow the NGS Brescia evolution!

PubMed Highlight: CNV contribution to carrier states and disease-causing alleles

This paper published on Genome Research analyze a large cohort of patients by CGH array to asses the impact of CNVs on known disease-causing genes. Among others, interesting results are that complex phenotype could arise from structural variations affecting multiple disease-causing genes, and that dominant deleterious genes tend to be less affected (as expected by natural selection).

Deletions of recessive disease genes: CNV contribution to carrier states and disease-causing alleles
Philip M Boone, Ian M Campbell, Brett C Baggett, Zachry T Soens, Mitchell M Rao, Patricia M Hixson, Ankita Patel, Weimin Bi, Sau Wai Cheung, Seema R Lalani, Arthur L Beaudet, Pawel Stankiewicz, Chad A Shaw and James R Lupski1

Abstract
Over 1,200 recessive disease genes have been described in humans. The prevalence, allelic architecture, and per-genome load of pathogenic alleles in these genes remain to be fully elucidated, as does the contribution of DNA copy-number variants (CNVs) to carrier status and recessive disease. We mined CNV data from 21,470 individuals obtained by array comparative genomic hybridization in a clinical diagnostic setting to identify deletions encompassing or disrupting recessive disease genes. We identified 3,212 heterozygous potential carrier deletions affecting 419 unique recessive disease genes. Deletion frequency of these genes ranged from one occurrence to 1.5%. When compared with recessive disease genes never deleted in our cohort, the 419 recessive disease genes affected by at least one carrier deletion were longer and were located farther from known dominant disease genes, suggesting that the formation and/or prevalence of carrier CNVs may be affected by both local and adjacent genomic features and by selection. Some subjects had multiple carrier CNVs (307 subjects) and/or carrier deletions encompassing more than one recessive disease gene (206 deletions). Heterozygous deletions spanning multiple recessive disease genes may confer carrier status for multiple single-gene disorders, for complex syndromes resulting from the combination of two or more recessive conditions, or may potentially cause clinical phenotypes due to a multiply heterozygous state. In addition to carrier mutations, we identified homozygous and hemizygous deletions potentially causative for recessive disease. We provide further evidence that CNVs contribute to the allelic architecture of both carrier and recessive disease-causing mutations. Thus, a complete recessive carrier screening method or diagnostic test should detect CNV alleles.

PubMed Highlight: Zebrafish genome sequenced and the systematic genome-wide analysis of zebrafish protein-coding gene function

The new assembly of the Zebrafish (D. rerio) genome has been recently published in Nature describing also the complete set of proteins encoded in the teleost DNA and their relationship to human orthologs. In a second paper  the research group propose a complete genome-wide analysis on genotype-phenotype correlation for every single protein coding gene in the assembly.



The first paper describe the latest assembly of the D. rerio genome.
The first assembly of the Zebrafish genome was made available in 2002 (Zv1), and now the Zebrafish Genome Project has produced the latest detailed assembly based on NGS Illumina technology. The new version represents a great improvement: it provides a better coverage of the entire genome sequence, helped resolve tricky artifacts that are still sparse along the fish genome and allow better identification of the complete set of protein coding genes (about 26,000). Also the catalog of small RNA and repeated elements has been update and some mis-annotated genes has been removed (mostly genes from other species that was assigned to zebrafish in previous assemblies).
Having a complete and robust assembly of this teleost genome is a key factor for research community, giving its important role as animal model for studies on development and characterization of functional impact of mutations in disease genes.

The zebrafish reference genome sequence and its relationship to the human genome. Nature. 2013 Apr 25;496(7446):498-503.
Howe K, et al.
Wellcome Trust Sanger Institute

Abstract

Zebrafish have become a popular organism for the study of vertebrate gene function. The virtually transparent embryos of this species, and the ability to accelerate genetic studies by gene knockdown or overexpression, have led to the widespread use of zebrafish in the detailed investigation of vertebrate gene function and increasingly, the study of human genetic disease. However, for effective modelling of human genetic disease it is important to understand the extent to which zebrafish genes and gene structures are related to orthologous human genes. To examine this, we generated a high-quality sequence assembly of the zebrafish genome, made up of an overlapping set of completely sequenced large-insert clones that were ordered and oriented using a high-resolution high-density meiotic map. Detailed automatic and manual annotation provides evidence of more than 26,000 protein-coding genes, the largest gene set of any vertebrate so far sequenced. Comparison to the human reference genome shows that approximately 70% of human genes have at least one obvious zebrafish orthologue. In addition, the high quality of this genome assembly provides a clearer understanding of key genomic features such as a unique repeat content, a scarcity of pseudogenes, an enrichment of zebrafish-specific genes on chromosome 4 and chromosomal regions that influence sex determination.

The second paper describe a project for genome-wide characterization of mutations in every single protein coding genes in D. rerio.
In this perspective the research group working on D. rerio genome has published another interesting paper describing their active project to identify and phenotype the disruptive mutations in every zebrafish protein-coding gene, using high-throughput sequencing and efficient chemical mutagenesis. They have already identified pote
ntially disruptive mutations in more than 38% of all known zebrafish protein-coding genes and assessed the effects of each mutation during embryogenesis. Moreover they have analysed the phenotypic consequences of over 1,000 alleles, making all data available to the community for genotype-phenotype correlation studies.

A systematic genome-wide analysis of zebrafish protein-coding gene function.Nature. 2013 Apr 25;496(7446):494-7.
Kettleborough RN, Busch-Nentwich EM, Harvey SA, Dooley CM, de Bruijn E, van Eeden F, Sealy I, White RJ, Herd C, Nijman IJ, Fényes F, Mehroke S, Scahill C, Gibbons
R, Wali N, Carruthers S, Hall A, Yen J, Cuppen E, Stemple DL.
Wellcome Trust Sanger Institute 

Abstract 

Since the publication of the human reference genome, the identities of specific genes associated with human diseases are being discovered at a rapid rate. A central problem is that the biological activity of these genes is often unclear. Detailed investigations in model vertebrate organisms, typically mice, have been essential for understanding the activities of many orthologues of these disease-associated genes. Although gene-targeting approaches and phenotype analysis have led to a detailed understanding of nearly 6,000 protein-coding
genes, this number falls considerably short of the more than 22,000 mouse protein-coding genes. Similarly, in zebrafish genetics, one-by-one gene studies using positional cloning, insertional mutagenesis, antisense morpholino oligonucleotides, targeted re-sequencing, and zinc finger and TAL endonucleases have made substantial contributions to our understanding of the biological activity of vertebrate genes, but again the number of genes studied falls well short of the more than 26,000 zebrafish protein-coding genes. Importantly, for both mice and zebrafish, none of these strategies are particularly suited to the rapid generation of knockouts in thousands of genes and the assessment of their biological activity. Here we describe an active project that aims to identify and phenotype the disruptive mutations in every zebrafish protein-coding gene, using a well-annotated zebrafish reference genome sequence, high-throughput sequencing and efficient chemical mutagenesis. So far we have identified potentially disruptive mutations in more than 38% of all known zebrafish protein-coding genes. We have developed a multi-allelic phenotyping scheme to efficiently assess the effects of each allele during embryogenesis and have analysed the phenotypic consequences of over 1,000 alleles. All mutant alleles and data are available to the community and our phenotyping scheme is adaptable to phenotypic analysis beyond embryogenesis.

CLARITY and the new frontiers of brain-imaging: really a brilliant idea!

This is not actually a genomic news, but the new CLARITY brain imaging technique just appeared on Nature is so fascinating that I have to share the video!

This demonstrate how far we have gone in our ability to map the activity of single cells and open amazing possibilities for future studies, promising to provide knowledge on how the brain response to stimuli or coordinate body activities.
The construction of a complete and informative map of the neuron interactions seems feasible and it is a hot topic right now. The US BRAIN project (recently founded with 100 million $ by Obama administration) and the European Human Brain Project (HBP) (founded with 1 billion euros for ten years as one of the EU FET-flegship), are two huge international initiatives, just started to accomplish this ambitious goal.

Someone have already pointed to the brain map as the third revolutionizing achievement after the Human Genome Project and the ENCODE project.

See your brain, with plenty of colourful neuron cell...
This time you can literally say: this is a brilliant idea!
And THIS is amazing science!

PubMed Highlight: Updating benchtop sequencing performance comparison

The comparison of available NGS benchtop sequencers continue as every platform rapidly upgrade its performance...or at least claim to have done that!

Accurate evaluation of the present performance of the single technologies is really difficult in a such quickly developing field as NGS...However a snapshot of the NGS technology scenario is of great advantage to everyone to evaluate which one best fit its research needs!

Read the complete paper published on Nature Biotechnology!

What's new in this paper compared to the last benchmarks from BGI (published on Journal of Biomedicine and Biotechnology) and Wellcome Trust Institute (published on BMC Genomics)?

Two competitors emerge as the leaders in the field: Ion PGM and MiSeq. Data shows data some technological and analytic gaps have been closed, with both platforms performing about the same in term of substitution detection accuracy. MiSeq performance remains better than PGM in detecting small indels (about 100-fold lower error rate), with most of the errors due to troubles in sequencing homopolymers runs. MiSeq still have the lowest cost per Mb, while PGM still the fastest and more flexible.

A good recap of the findings can be found on this post from GenomeWeb, where you can read also the first official answers from both Illumina and Life Tech.

Table from Junemann et al., Nature Biotechnology 31(4): 294-296, April 2013

A walking-dead pidgeon and the return of the mummy...you can do NGS starting from any source!!!

Here we are again with some surprising data from NGS studies.

Besides provide some interesting (and, why not, funny) scientific stories, the following news clearly demonstrate how, relying on cut of the edge sample preparation, NGS technology allow sequencing from basically any input material. The ability to obtain a good sequence of an entire genome starting from few nanograms, but even picograms, of input DNA open the way to amazing application. From cancer genomics, to prenatal screening, the ability of sequence very little amount of cell-free DNA that is present in circulating blood as already provide really exciting results. This kind of techniques promise great improvements also in epidemic controls and contamination/pathogens detection in foods, water or any other samples.
The topic of sequencing from nanograms or picograms is extensively covered in this post on CoreGenomics, that provides also some examples of recently published papers and dicuss about the new library preparation kits that make NGS sequencing from low input DNA fast and easy!

Now the stories!
We have reported on September 2012 about Revive and Restore (see the our post here), a company founded with the ambitious and controversial aim of sequence and reconstruct the genome of extinct species with the ultimate goal of eventually bring them back to life.
We were not sure how far this initiative would have gone, but the last month they surprised us again with the announcement of an actual project to resurrect the extinct passenger pidgeon.

Ben Novak, a 26-year-old genetics, has received support from the company to achieve the goal of sequencing the entire DNA of this species from a tissue sample received from the Chicago's Field Museum in 2011. Working with evolutionary biologist Beth Shapiro at the University of California, Santa Cruz, they plan to complete the genome of passenger pidgeon and its closest living relative, the band-tailed pidgeon. The extinct DNA will then be aligned to the living one to identify all the differences and finally a massive mutagenesis will be performed on band-tailed pidgeon DNA to re-create the complete sequence of the passenger species.
However the idea not only require hard work, but it could really get dicey. Indeed, according to Shapiro, "because the last common ancestor of the two species flew about 30 million years ago, their genomes will likely differ at millions of locations." Fitting the pieces together will be grueling, if not impossible. GenomeWeb have a post on this and Wired also has covered the story in this article from Kelly Servick.

However one consider this real science or fantasy science, the general topic of de-extinction is getting increasing attention now that the DNA sequencing technology allow to effectively assemble genomes from ancient and degraded samples (remember for example the Neanderthal genome or the Mammoth genome). The collection of DNA from different species is a part of some huge projects intended to preserve and study biodiversity and experts are now discussing if and eventually how we have to deal with species that go extinct over time. If we as human race are responsible for the disappearing of a specific organism and we have the ability to bring it back to life, should we do this? What are the risks of re-introduce extinct species in our ecosystem?

Recently a TEDx event has been organized exploring the topic of de-extinction. and the recent advances in the field have received attention also from the National Geographic and The New York Times (this one dealing with bring an extinct frog back to life). Revive and Restore has a list of candidate organisms waiting for de-exctinction and is searching for collaborators! Looking at their list I may like to see a Dodo walking again in the garden...but want to raise my doubts about a tooth-saber cat!!

The second news is directly from scientific literature. In their paper recently published on Journal of Applied Genetics, Khairat et al. from the University of Tubingen, report the first metagenome analysis on ancient egyptian mummies. Their dataset comprise seven sequencing experiments performed on DNA obtained from five randomly selected Third Intermediate to Graeco-Roman Egyptian mummies (806 BC-124AD) and two unearthed pre-contact Bolivian lowland skeletons. Analyzing the data their were able to identify different genetic materials from bacteria, presumibly due to contamination from mummies conservation procedures, and also from plants, potentially associated with their use in embalming reagents. The paper demonstrates that also DNA from ancient mummies, could be a proper template for NGS sequencing, despite its age and the several treatment performed on the samples in the course of the conservation protocols.

All start from high quality reads in NGS!

If you are performing an NGS based experiment, first of all you want to be sure that your are starting from high quality raw data. Current technology have achieved outstanding robustness but the quality check on sequencing reads remain the first step in every analysis.

Several tools are available that return stats and graphs from analysis of your fastq files and, inspired by a new paper just appeared on PLoS ONE, I just report want to report a couple of solutions that I found useful.

First is FastQC. This is a relative simple tools which take your fastq or bam/sam file and report all the essential stats you need to be sure that nothing has gone wrong with your sequencing. It's based on Java and so it can easily run on almost every platform without the need for tricky installation steps.

You can find this from the official web page at Babraham Bioinformatic Institute. 

Second is NGS QC Toolkit. This is a set of tools for the quality control of next generation sequencing data. It accept data in the popular fastq format and provide with detailed results in the form of tables and graphs. Moreover it allows filtering of high-quality sequence data and includes few other tools, which are helpful in NGS data quality control and analysis (format conversion and trimming of the reads for example).

It is developed by the Indian National Institute of Plant Genome Research and you can find it at its official page here.

Also take a look at the official paper published on PLoS ONE in 2012 by Patel RK & Jain M

Third is this recent QC-chain tool that have cited above. The tool comprise a set of user-friendly tools for quality assessment and trimming of raw reads (Parallel-QC). Moreover it has an interesting feature that allows identification, quantification and filtration of unknown contamination to get high-quality clean reads. Authors stated that the tool was optimized based on parallel computation, promising that processing speed is significantly higher than other QC methods...This could be really useful if you routinely deal with a huge volume of data.

QC-chain is developed by the Computation Biology Team at Qingdao Institute of Bioenergy and Bioprocess Technology, and can be found here at the official web page.

This one also have an official paper published on PLoS ONE in 2013 by Zhou Q et al.