Although sequencing mRNA molecules by RNA-seq technology has almost replaced microarray technology in small/medium scale gene expression studies, the large-scale genetics of gene expression studies have been a bit slow to embrace Next-gen sequencing. Till recently almost all of the eQTL studies have primarily relied on measuring expression profiles by using microarray technologies.

Only two studies have been published that looked at at genetics of human gene expression by RNA-seq. Pritchard’s group at U. Chicago characterized the genetics of gene expression in 69 african samples from HapMap using RNA-seq and a group from Europe analyzed RNA-seq from 60 European HapMap samples. The results from these studies were published back-to-back in the Nature 2010 issue celebrating “The human genome at ten“.

After those two publications, there are no studies using RNA-seq for understanding genetics of gene expression. Actually, except for the ENCODE/MODENCODE project there is no large scale RNA-seq data published yet. ENCODE published over 410 RNA-seq studies, they were mainly from a few cell lines, not a population level data.

It is bit surprising to see that genetics of gene expression has been a bit slow to embrace sequencing. For sure there are many valid reasons, including funding, scale of such projects and challenges associated with collecting genotype, expression and possibly other phenotypes from the same population and challenges associated with analyzing RNA-seq data.

Genetics of Gene Expression Goes Next-Gen Sequencing

It is all going to change pretty soon. The recently concluded Biology of the Genomes conference highlighted at least two major studies on the genetics of human gene expression using RNA-seq data.

One study, Geuvadis project from Europe uses part of samples from the 1000 Genome project with the aim of setting up standards for biological/medical interpretation of sequence data in relation to clinical phenotypes. The Geuvadis project has sequenced both mRNA and microRNA molecules on 465 lymphoblastoid cell line (LCL) samples from 5 populations of the 1000 Genomes Project: one african (Yoruba, YRI) and four european (CEPH (CEU), Finns (FIN), British (GBR), and Toscani (TSI)).

Of these samples, 423 were part of the 1000 Genomes Phase 1 dataset with genome/exome sequencing data. Although the project results are not published yet, the underlying RNA-seq and microRNA-seq data are available from Geuvadis, under Fort Lauderdale Agreement. The Geuvadis website also says that one can expect the publication describing the results of the project pretty soon. Till then here are the tweets on talk at #BOG13 from the leading author of Geuvadis project.

Genetics of Gene Expression of samples from 1000 Genome #bog13

The lead author of Geuvadis project @tuuliel’s talk at #BOG13 storified.

Storified by NextGenSeek· Mon, May 13 2013 04:06:13

The second study from Stanford group led by Alexis Battle has sequenced transcriptomes for 922 individuals from the same population and genotyped them for 737,187 common SNPs. With over 900 individuals, it is the largest transcriptome sequencing effort ever. The mRNA from whole blood was sequenced to really high depth of over 60 million reads in each individual. This work does not have a project page yet and one can learn a bit. Here is the tweets from #BOG13 talk of Alexis Battle storified.

Large-scale RNA-seq study to understand the genetics of gene expression in human #bog13

Alexis Battle’s on the largest RNA-seq project at #bog13 storified

Storified by NextGenSeek· Mon, May 13 2013 04:12:08

NIH’s Genotype-Tissue Expression (GTEx) Project

These two large scale population level RNA-seq effort are only a beginning. NIH’s Genotype-Tissue Expression (GTEx) project is underway to create a largest resource of genotype and gene expression by RNA-seq on 30 to 50 tissues in the human body, including the brain, lung, heart and muscle. Just on the scale alone, the GTEx project could be called as “popENCODE” (Over 4000 experiments in ENCODE: 2142: ChIP-seq, 418:RNA-seq,318-DNase-seq). And the GTEx pilot project’s final data on 190 individuals with genotype information and RNA-seq on over 1800 tissues is available now. GTEx project plans to scale up the sample size in the future.

Follow Twitter to Get Live Update

Interested in following the high quality genomic science from the “tweetable” Biology of Genomes 2013 live? Unlike other conferences, CSHL does not even publish the complete schedule of the conference. Tune in to tweets with the hashtag #bog13 and more specifically look out for tweets from

• Ewan Birney
• Nathan Pearson
• Mike Schatz
  
• Yaniv erlich
• Joe Pickrell
• Daniel MacArthur
• JK. Conrad
• David Mittelman
• Chris Gunter
• Ori Bahcall
• Nicholas Robine

True to the name of the conference, The Biology of the Genome conference has the latest genome science on a variety of genomes. Although human genome is the most dominant topic at this year (see the wordle based on poster and talk titles), the conference also features the most recent work on Drosophila, Mouse, Neandertal, African and Caribbean vervet monkeys, and many more

Here is the wordle images from the talks and posters.

BOG13-talks

BOG13-posters

Qiagen Acquires Ingenuity

Qiagen announced that it has acquired the Ingenuity Systems for $105 Million. The California based Ingenuity Systems the early Bioinformatics software company was co-founded by Ramon Felciano in 1998 when he was a PhD student at Stanford.

Ingenuity has a variety of web based bioinformatics products based on its  manually curated Knowledge Base of biological interactions and functional annotations for proteins, genes, drugs, and diseases that distill knowledge from large-scale omics data.  Ingenuity’s Pathway analysis product (IPA) is widely used and it recently started offering web based products for Next-Gen sequencing data to identify causal variants and analyzing results from RNA-seq data.

Qiagen is predominantly a molecular diagnostics company with over 4000 employees across the world, has recently showed a lots of interest in Next-Gen sequencing market. First, Qiagen bought Intelligent Bio-Systems (IBS) in 2012, with interest in building a sequencer.  IBS has developed max-Seq using the sequencing-by-hybridization technology like Illumina, but based on the work from Columbia University professor Jingyue Ju.  Before being acquired by Qiagen, IBS was developing a desktop Next-Gen sequencer, mini-Seq for diagnostic market. It looks like IBS/Qiagen is close in developing the desktop sequencer. During the AGBT this year, Qiagen announced that it will be selling a new Desktop Next-gen sequencer, GeneReader, which sounded very similar to IBS’ mini-Seq. However, it did not offer much information about the sequencer.

Qiagen has been hinting a product that goes from sample to results for diagnostic market and the acquisition of Ingenuity Systems is a big step towards the integrated product that goes from sequencing to discovery. Announcing the acquisition, Qiagen said in the press release that many of the top people at Ingenuity will stay with Ingenuity. Here are some blurbs on the acquisitions by the CEOs Qiagen and Ingenuity.

Peer M. Schatz , Chief Executive Officer of QIAGEN N.V said

The interpretation of biological information is becoming a cornerstone of QIAGEN’s ecosystem of Sample & Assay Technologies for molecular testing – both in life sciences research and in diagnostics. We are establishing a leading role in this field and intend to further expand the value proposition and scope of our offering.

Ingenuity has created unparalleled leadership with its Knowledge Base and interpretation solutions to unlock the value of complex genomic and other biological information. Combining the highest-quality knowledge content with powerful search capabilities and easy-to-use interfaces, the Ingenuity suite provides customers with scientifically and clinically relevant insights into diseases. We are looking forward to expanding the seamless integration of leading biomedical information solutions into our full range of molecular testing solutions, thereby providing our customers a unique experience from sample to interpreted result and recommendations for next steps. Integration of Ingenuity’s solutions into a powerful, full-range ecosystem of QIAGEN’s molecular testing solutions, such as PCR and next-generation sequencing, promises to offer significant value to QIAGEN customers and shareholders.

Jake Leschly , President and CEO of Ingenuity Systems, said

Today we can sequence an entire human genome in just a couple of days for less than a few thousand dollars, but the data analysis can take from months to years. The Ingenuity suite of products enables this rapid and accurate interpretation in a matter of minutes, and this is fundamentally impacting scientific research and the ability to diagnose and manage patient care. The Ingenuity mission from day one has been to accelerate scientific discovery and enhance clinical decision-making through a rich understanding of biological systems. As part of QIAGEN, we will offer our biological knowledge content and software in the context of a best-in-class ecosystem of molecular testing solutions and to a greatly expanded range of customers around the world.

Thermo Fisher Announces the Acquisition of Life Technologies for $13.6 Billion

Thermo Fisher announced today that it is acquiring the Life Technologies for $13.6 billion. Life Technologies had been looking to be acquired since the beginning of the year. And the acquisition news initially came out yesterday from a WSJ report. Confirming the report, Thermo Fisher announced the acquisition news early this morning.

In a press release announcing the acquisition of Life Technologies, Marc N. Casper, president and chief executive officer of Thermo Fisher Scientific said

We are extremely excited about this transaction because it creates the ultimate partner for our customers and significant value for our shareholders. The acquisition of Life Technologies enhances all three elements of our growth strategy: technological innovation, a unique customer value proposition and expansion in emerging markets.

“Our customers in research and applied markets will now be able to achieve even higher levels of innovation and productivity by working with the combined company. We’re especially excited about the new opportunities we will have to leverage our complementary offerings, fueled by a shared commitment to continuous innovation. For our shareholders, we expect the transaction to generate attractive financial returns, as well as significant and immediate accretion to our adjusted EPS.

We look forward to welcoming our new colleagues from Life Technologies to the Thermo Fisher team. Together, we will be in an even stronger position to fulfill our company’s mission, which is to enable our customers to make the world healthier, cleaner and safer.

Gregory T. Lucier, chairman and chief executive officer of Life Technologies, said

This transaction brings together two companies intent on accelerating innovation for our customers and achieving greater success in a highly competitive global industry. Further, this combination delivers immediate and significant cash value to our stockholders and represents a successful conclusion to the board’s strategic review to enhance stockholder value and develop an even stronger future for Life Technologies. We look forward to joining forces with the outstanding team at Thermo Fisher, which shares our commitment to customers, employees and the communities we serve.

Life Technologies to acquired by Thermos Fisher: WSJ Reports

It looks like the California based Life Technologies is about to be acquired by the Massachussets based Thermo Fisher. According to the report on Wall Street Journal tonight, Life Technologies and Thermo Fisher are in advanced stages of the acquisition talk and it is expected that the companies can announce the acquisition as early as tomorrow for about $13 billion (and there is also a chance that the deal might fall apart).

According to the report, in addition to Thermo Fisher, the chemical giant Sigma-Aldrich and a private consortium were also bidded to acquire Life Technologies.

Life Technologies founded in 2008 has about 10,000 employees and has $3.8 billion in revenues as of 2012. It also boasts of having over 5000 patents.  Thermo Fisher has its origin in the company Thermo Electron founded in 1956 by George Hatsopoulos, a PhD student at MIT.  Later in 2006, Thermo Fisher was founded by the merger of Thermo Electron Corporation and Fisher Scientific International Inc for a value of about $12.8 billion.  Now, Thermo Fisher has about 39,000 employees and gets $13 billion in revenue.

PacBio Launches PacBio RS II Sequencer

Pacific Biosciences (PacBio) announced that it is launching its next version of PacBio sequencer, PacBio RS II.  The new PacBio RS II can produce 5,000 bp read lengths on an average and the longest reads are above 20,000 bp in length.  In addition, in the new PacBio RS II,  PacBio has doubled the number of simultaneously observable sequencing reactions  and thus doubling the throughput of the sequencer.

PacBio says that all the improvements made to the existing version of the sequencer are also available in the new PacBio RS; including  

PacBio’s C2 and XL chemistries, new analysis software with automated de novo assembly,  increased consensus accuracy to greater than 99.999% (Q50), a quadrupling of average read lengths, and a 10-fold reduction in input DNA required.

PacBio RS II will be available in the second quarter of 2013 and the users of existing PacBio RS will be able to upgrade to the new sequencer (for a yet to be announced price). Announcing the new PacBio RS II, Kevin Corcoran, Senior Vice President of Market Development, said

In addition to providing more, high-quality data in a highly robust system, the PacBio RS II includes all of the performance improvements we have made since we launched the commercial PacBio RS System in 2011.  The combined improvements in accuracy, reliability, and throughput, as well as increased cost efficiencies, are what many researchers have been waiting for in order to adopt SMRT Sequencing in their laboratories.

Richard Gibbs, Ph.D.,from Baylor College of Medicine, one of the early access users of PacBio RS II said

I have been very impressed with the progress Pacific Biosciences has made with this unique technology. With each performance upgrade, our ability to handle more complex projects increases. We are now using the system to improve the sequence of mammalian genomes.

A team led by Gholson Lyon from CSHL systematically evaluate the commonly used bioinformatics pipelines for calling variants from exome and whole genome sequence data and ask really simple question “How well do the results from multiple pipelines agree?” And they published their results in a paper titled Low concordance of multiple variant-calling pipelines: practical implications for exome and genome sequencing. Here is a quick summary of the paper.

The team sequenced 15 exomes from four families using Illumina HiSeq 200 with about ~120 X coverage and tested five commonly used alignment and variant calling pipelines;

• SOAP
• BWA-GATK
• BWA-SNVer
• GNUMAP
• BWA-Samtools. 

Among these five pipelines three (GATK, SOAP, and Samtools) can also call indels. In addition to the 15 exomes, the team had also sequenced the whole genome of an individual using Complete Genomics.  They also validated a set SNPs and indels by amplicon sequencing in MiSeq.

The gist of the findings is that there is very poor concordance of variants called from these five pipelines.  Across all the samples there was only about 57% of the SNPs called were concordant in the five pipelines used. Each pipeline came up with its own unique SNPs with varying degree; 0.5% to 5.1%.   As one expects, SNP calling fares better than indel calling. Only about 26% of the indels called agreed with each other in the three indel pipelines.

In addition, a comparison of variants from a Illumina exome sequence sample to exomic regions from whole genome sequencing from Complete Genomics (CG) show that a large number SNPs inferred from CG data is missing in the Illumina data and the SNPs that are present in the Illumina sample have low sequence coverage.

So which is the best “variant calling pipeline”? This a loaded question, under the “default” conditions for Illumina sequencing, 97% of GATK-only SNPs  and 54% of GATK-only indels could be validated using MiSeq sequencing. In comparison,  only about 60% of SOAP-only SNPs and 44% of SOAP-only indels could be validated. This suggests that GATK is superior.

This paper nicely highlights the problems with the current state of “calling variants”, which are both at the technology and pipelines that are available to call variants.  Stressing the need for change, the authors came with multiple recommendations to improve variant calling. They include

1. discussion on variant quality and the case for multiple methods for analyzing personal genomes
2. standardization of indel callings
3. need for studying large families for discovering variations
4. need for multiple platforms to comprehensively look at exomes

They are all valid recommendations that can improve the current state of variant discovery.

Here are a few thoughts on this paper and reproducibility of variant calling methods in general.

The authors have presented “pooled” results from comparing 15 across the five different pipelines. This basically gives an average picture of “pipeline-specific” and “pipeline-shared” variants.  Although it helped to see how discordant the results from multiple pipelines are, it will be interesting to see how each exome data fared under the five pipelines (May be it is in the Supp. Section and we missed it).  The detailed supplementary section provides data on exome capture  for each sample and it shows that there is lot variation between samples. For example, total number of reads mapped varies from 61M to 94M; mean depth of the target region varies from 100 to 150.

Comparing samples independently across multiple pipelines might give hint on how these pipeline specific and shared variants vary from sample to sample. And looking at the outliers might help understanding the strength and weakness of a pipeline.

On a more general note, the trouble with the “default” in a pipeline is that, it is tuned for one kind of analysis. And often, there is no way one can tune all the parameters to infer the best parameters.  In addition to the suggestions in this paper, another work around is that variant calling methods (and the way we use) need to get more quantitative/statistical. This will not solve all the problems, but will definitely help.

Reproducibility is a common problem in next-gen sequencing analysis. For example, just like multiple variant calling algorithms, there are multiple peak-calling algorithms for ChIP-Seq analysis. And ChIP-Seq also faces poor reproducibility across multiple pipelines for the same sample. Recently, Peter Bickel’s group at Berkeley developed Irreproducibility Discovery Rate (IDR) for measuring reproducibility of high-throughput experiments (manuscript at arXiv).  IDR is similar to FDR, but gives us a handle on reproducibility. ENCODE project successfully adapted IDR for its ChIP-Seq analysis.

It may not be trivial, but should be possible to extend or develop “IDR-like” approaches for assessing reproducibility in variant calling. It is possibly more challenging in the variant calling setting as the SNP calling and Indel calling are often inter-related. Such quantitative masure of reproducibility will readily allow us to compare multiple variant discovery procedures/platforms and a handle on the reliability of the results.

will address DNA sequence variation and its role in molecular evolution, population genetics and complex diseases, comparative genomics, large-scale studies of gene and protein expression, and genomic approaches to ecological systems. Both technologies and applications will be emphasized. In addition there will be a special session on the ethical, legal and social implications of genome research.

The Biology of Genomes, one of the most awaited genomics conference boasts of great line of talks and posters. The full schedule of the event is not finalized yet. Here is the list of 48 accepted talks at the 2013 Biology of Genomes.

1. Andersson, R. Systematic in vivo characterization of active enhancers across the human body
2. Arnold, C. STARR-seq identifies genome-wide quantitative enhancer activity maps
3. Auton, A.J. Genetic recombination is targeted towards gene promoter regions in dogs
4. Ayroles, J.F. Genetic incompatibilities within species are widespread
5. Bachtrog, D. Transposable element mediated rewiring of a regulatory network—Dosage compensation in Drosophila miranda
6. Battle, A. Characterizing the genetic basis of transcriptome diversity through RNA-sequencing of 922 individuals
7. Blekhman, R. Using deep whole-genome sequencing to understand the role of non-coding genetic variation in complex developmental disease
8. Brown, A. Genetic epistasis in gene expression regulation via variance expression quantitative trait loci in the TwinsUK cohort
9. Brown, J.B. The dynamic and eco-responsive transcriptome of Drosophila melanogaster
10. Bulyk, M. Highly parallel assays of tissue-specific enhancers in whole Drosophila embryos
11. Carpenter, M.L. Pulling out the 1%—Whole-genome capture for the targeted enrichment of ancient DNA sequencing libraries
12. Castellano, S. Patterns of coding variation in the complete exomes of three Neandertals
13. De Jong, P.J. The sequencing, assembly, and characterization of a 24Gb conifer genome (P. taeda)
14. Elvers, I. Mapping canine cancers—Overlapping and divergent pathways
15. Engreitz, J. Large noncoding RNAs can localize to regulatory DNA targets by exploiting the three-dimensional architecture of the genome
16. Esko, T. Polygenic variation of human height identifies new loci and biological pathways in a large-scale meta analysis of 250,000 individuals
17. Garfield, D. Contrasts between adaptive coding and noncoding changes reveals repeated evolutionary patterns across phyla
18. Garrison, E. Simultaneous assembly of thousands of human genomes
19. Gifford, D.K. Directional and non-directional pioneer transcription factors make way for settler factors
20. Gravel, S. Reconstructing Native American migrations using genome-wide sequence data
21. Jaffe, D.B. Highly accurate determination of indels (and SNPs) from human resequencing data with an assembly-based approach
22. Khurana, E. Interpretation of genomic variants using a unified biological network approach
23. Korbel, J.O. Origin, complexity and impact of DNA structural rearrangements in cancer
24. Kruglyak, L. Genomic approaches to the missing heritability problem in yeast
25. Kundaje, A.B. Comparative analysis of chromatin state dynamics across organisms, cell types and individuals
26. Kyriazopoulou Panagiotopoulou, S. Genome diversity within a human medulloblastoma
27. Lappalainen, T. Transcriptome and genome sequencing uncovers functional variation in human populations
28. MacArthur, D.G. Integrated analysis of protein-coding variation in over 25,000 individuals
29. Marioni, J. A general approach to account for technical noise in single-cell RNA-seq experiments
30. Mortazavi, A. Genomic analysis of Steinernema—Insights into insect parasitism, intragenus and intergenus evolution
31. Nordborg, M. The genotype-phenotype map in Arabidopsis thaliana
32. Pääbo, S. A high-coverage Neandertal genome
33. Parker, S.C. Integrative genomic analysis of RNA and ChIP-seq data across multiple cell types identifies “stretch enhancers” associated with type 2 diabetes
34. Parts, L. Quantitative genomics of single cell protein traits
35. Pennacchio, L.A. High throughput enhancer assessment in vivo
36. Pickrell, J.K. Unraveling waves of population mixture in sub-Saharan Africa using patterns of linkage disequilibrium
37. Pipes, L. Changes in RNA-seq profiles of silver foxes (Vulpes vulpes) after 50 generations of selection on tame/aggressive behaviors
38. Ren, B. A comparative and integrated map of functional sequences in the mouse genome
39. salzman, j. Developmentally regulated features of widespread circular RNA expression
40. Shapiro, B. Genomic signatures of intrahost evolution and selection in viral hemorrhagic fevers
41. Siepel, A.C. Genome-scale sampling of ancestral recombination graphs
42. Snyder, M. Adventures in personal medicine—Integrative personal omics profiling for monitoring healthy and disease states
43. Song, Y.S. Distortion of genealogical properties for very large samples
44. Soranzo, N. Whole-genome sequence based association studies of complex traits—The UK10K project
45. Sudmant, P. Evolution and diversity of copy number variation in the great ape lineage
46. Tischler, V. Primate genome architecture linked with formation mechanisms and functional consequences of structural variation
47. Williams, A. A genome-wide estimate of meiotic gene conversion rate in humans
48. Wilson, R.K. Comprehensive analysis of relapsed acute lymphoblastic leukemia reveals intronic mutations that drive FLT3 over-expression

In addition to the govt funding agencies, BRAIN initiative is keen to involve other players and roped in ofoundations to fund the project. The Allen Institute for Brain Science will be supporting $60 million annually, the Kavli Foundation plans to support $4 million per year for ten years. And the Howard Hughes Medical Institute and the Salk Institute for Biological Studies will also contribute funding towards the initiative.

Learn more about the BRAIN Initiative from

1. Brain Research through Advancing Innovative Neurotechnologies (BRAIN) Initiative
2. Fact Sheet: BRAIN Initiative
3. BRAIN Initiative Challenges Researchers to Unlock Mysteries of Human Mind
4. Remarks by the President on the BRAIN Initiative and American Innovation

Watch the YouTube video of Dr. Francis Collins, the Director of the National Institutes of Health highlighting the BRAIN Initiative project.

Watch the YouTube Video “Open for Questions”, where Tom Kalil, Deputy Director for Technology and Innovation in the Office of Science and Technology Policy; Dr. Francis Collins, Director of National Institutes of Health; and Dr. Arati Prabhakar, Director of the Defense Advanced Research Projects Agency answer questions about the BRAIN Initiative.

BRAIN Initiative Infographic