Pages

Sunday, 9 June 2013

The White Tigers, the White Gorillas and the Green Turtle

We have been quite busy in the past weeks setting up our own NGS sequencing lab, but we haven't stop to look around for genomics news and new genomes!
Three articles have been published recently: the complete sequence of two species of turtle to get insight on the evolution of their peculiar body structure, the complete genome sequence of the only known exemplar of white gorilla; a large sequencing and genome wide association study to identify the cause of albinism in white tigers.

The first study appeared at the end of April on Nature Genetics (The draft genomes of soft-shell turtle and green sea turtle yield insights into the development and evolution of the turtle-specific body plan. Wang et al.) describe the complete genome assembly of two kind of turtles (P. sinensis and C. mydas) and also reports interesting results from embryo studies and comparative developmental studies against chicken embryos. Taken together these data give a comprehensive picture on turtle evolution and new insight on the crucial factor driving their peculiar body structure. From extensive analysis of embryo gene expression and comparison with chicken, authors found that turtle development initially follows the common vertebrate pattern but then it differentiate from the stage TK11 and they were also able to identify a set of 233 genes that should be crucial for the specific turtle body plan.

"Taken together, these results suggest that turtles indeed conform to the developmental hourglass model (Supplementary Fig. 15) by first establishing an ancient vertebrate body plan and by developing turtle-specific characteristics thereafter. The above results suggest that turtle-specific global repatterning of gene regulation begins after TK11 or the phylotypic period. Although turtle and chicken express many shared developmental genes in the embryo during the putative phylotypic period (Fig. 4a and Supplementary Tables 27and 28) and have the fewest expanded or contracted gene family members expressed (Supplementary Fig. 16) at this stage, later stages showed increasing differences in their molecular patterns. We found 233 genes that showed turtle-specific increasing expression patterns after the phylotype (Fig. 4b). Considering that the chicken orthologs did not show this type of increasing expression (Supplementary Figs. 17 and 18), these 233 genes represent attractive candidates for clarifying the genomic nature of turtle-specific morphological oddities"


This paper combines different techniques and imply a lot of NGS experiments. First of all, the genome sequencing of the two specimens was conducted by paired-end sequencing on Illumina HiSeq 2000 using both short and long insert libraries for a median of 105X and 82X (estimated genome size of about 2.2 Gb). The complete set of turtle transcripts were assessed by computational analysis, but also supported by RNA-Seq data of the soft-shell turtle conducted with three different approach: Titanium sequencig, Illumina strand-specific and non strand-specific RNA-seq, for a total of about 37 Gb of sequencing. Finally, authors investigated miRNAs as well by sequencing small RNAs on Illumina platform. They then used computational tools and comparison with other species known miRNA to infer potential binding sites and conserved miRNA species.



The other two paper deals with some more "exotic" species, trying to dissect the molecular origin of albinism in a white gorilla known as Snowflake and in a family of white tigers raised in captivity. Oculocutaneous albinism in humans is knwon to be related to mutations in the SLC45A2 gene and the authors found that this is the case also in the two considered species.
Complete sequence of the white gorilla was published at the end of May on BMC Genomics (The genome sequencing of an albino Western lowland gorilla reveals inbreeding in the wild. Prado-Martinez et al.). Authors reported the 19X whole genome sequencing of the only known white gorilla and compared these data with the human reference genome and other two already sequenced gorilla genome searching for SNVs in albinism related genes. Data analysis lead to the identification of a missense mutation in SLC45A2 gene resulting in the G518R aminoacid substitution, which should alter the function of the protein channel thus leading to albinism in the white gorilla. Interestingly, it resulted that the genome of snowflake presented large ROH regions, suggesting that it defect may result from high rate of inbreeding.

The study on white tigers was published at the beginning of June on Current Biology (The genetic basis of white tigers. Xu et al.). The authors performed an extensive genomic analysis on a family of 16 white tigers raised in captivity to track down the molecular defect responsible for the albinism in this species. Applying a combined approach based on genome-wide association mapping with restriction-site-associated DNA sequencing (RAD-seq), followed by whole-genome sequencing (WGS) of the three parents, they identified the aminoacid substitution A477V in the SLC45A2 gene as the causative mutation. This finding was confirmed by validation in 130 unrelated tigers identified and three-dimensional homology modeling, suggesting that the substitution may partially block the transporter channel cavity.

Tuesday, 4 June 2013

PubMed Highlights: Disease Gene Prioritization

The next generation sequencing field is reaching a solid robustness for what concern the techniques and now most of the weaknesses that characterized the first steps at the beginning of this new era have been mostly fixed or reduced. At the state of art, what still represent a "bottle neck" in finding the candidate disease gene, specially in exome sequencing and genome sequencing studies, is the gene prioritization step. Not always there is the availability of linkage or association data and the number of variants on which focusing remains high. The need to prioritize the genes inside a list could be crucial in a genetic study and many tools are now available. Here we suggest a chapter, taken from “Translational Bioinformatics" collection for PLOS Computational Biology, in which several tools are described with some of their successful applications.

This article is part of the “Translational Bioinformatics" collection for PLOS Computational Biology.


Abstract

Disease-causing aberrations in the normal function of a gene define that gene as a disease gene. Proving a causal link between a gene and a disease experimentally is expensive and time-consuming. Comprehensive prioritization of candidate genes prior to experimental testing drastically reduces the associated costs. Computational gene prioritization is based on various pieces of correlative evidence that associate each gene with the given disease and suggest possible causal links. A fair amount of this evidence comes from high-throughput experimentation. Thus, well-developed methods are necessary to reliably deal with the quantity of information at hand. Existing gene prioritization techniques already significantly improve the outcomes of targeted experimental studies. Faster and more reliable techniques that account for novel data types are necessary for the development of new diagnostics, treatments, and cure for many diseases.

Thursday, 30 May 2013

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! 




Monday, 27 May 2013

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.

Saturday, 25 May 2013

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!

Friday, 24 May 2013

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!



Friday, 17 May 2013

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.

Thursday, 2 May 2013

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.

Monday, 15 April 2013

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!

Wednesday, 10 April 2013

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!


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