Archive for the 'Guest Posts' Category

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Identification of genomic regions shared between distant relatives

This is a guest post by Graham Coop and Peter Ralph, cross-posted from the Coop Lab website.

We’ve been addressing some of the FAQs on topics arising from our paper on the geography of recent genetic genealogy in Europe (PLOS Biology). We wanted to write one on shared genetic material in personal genomics data but it got a little long, and so we are posting it as its own blog post.

Personal genomics companies that type SNPs genome-wide can identify blocks of shared genetic material between people in their databases, offering the chance to identify distant relatives. Finding a connection to someone else who is an unknown relative is exciting, whether you do this through your family tree or through personal genomics (we’ve both pored over our 23&me results a bunch). However, given the fact that nearly everyone in Europe is related to nearly everyone else over the past 1000 years (see our recent paper and FAQs), and likely everyone in the world is related over the past ~3000 years, how should you interpret that genetic connection?

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Learning more from your 23andMe results with Imputation

PeterAndEliana This is a guest post by Peter Cheng and Eliana Hechter from the University of California, Berkeley.

Suppose that you’ve had your DNA genotyped by 23andMe or some other DTC genetic testing company. Then an article shows up in your morning newspaper or journal (like this one) and suddenly there’s an additional variant you want to know about. You check your raw genotypes file to see if the variant is present on the chip, but it isn’t! So what next? [Note: the most recent 23andMe chip does include this variant, although older versions of their chip do not.]

Genotype imputation is a process used for predicting, or “imputing”, genotypes that are not assayed by a genotyping chip. The process compares the genotyped data from a chip (e.g. your 23andMe results) with a reference panel of genomes (supplied by big genome projects like the 1000 Genomes or HapMap projects) in order to make predictions about variants that aren’t on the chip. If you want a technical review of imputation (and the program IMPUTE in particular), we recommend Marchini & Howie’s 2010 Nature Reviews Genetics article. However, the following figure provides an intuitive understanding of the process.

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Response to “Exaggerations and errors in the promotion of genetic ancestry testing”

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Following the Genomes Unzipped post entitled “Exaggerations and errors in the promotion of genetic ancestry testing”, we received a request to reply from Jim Wilson. Jim Wilson is the chief scientist of BritainsDNA. He is not the one who gave the BBC interview that prompted the Genomes Unzipped post but he is a key contributor to the science behind BritainsDNA. We are keen to tell both sides of this story and this post is an opportunity for BritainsDNA to state their arguments and motivation. -VP

I saw Vincent Plagnol’s post here on Genomes Unzipped about the promotion of genetic ancestry testing and felt compelled to respond. While I did not give the interview that was the subject of the post, I am the chief scientist at BritainsDNA and I feel that the post was biased in presenting only one side of the story and thus misrepresenting the situation. Perhaps I can offer another perspective for readers.

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Guest Post: Jimmy Lin on community-funded rare disease genomics

Jimmy Cheng-Ho Lin, MD, PhD, MHS is the Founder/President of Rare Genomics Institute, helping patients with rare diseases design, source, and fund personalized genomics projects. He is also on the faculty in the Pathology and Genetics Departments at the Washington University in St. Louis, as part of the Genomics and Pathology Services. Prior to this, he completed his training with Bert Vogelstein and Victor Veculescu at Johns Hopkins and Mark Gerstein at Yale, and led the computational analysis of some of the first exome sequencing projects in any disease, including breastcolorectal, glioblastoma, and pancreatic cancers.

At Rare Genomics Institute (RGI), we have a dream: that one day any parent or community can help access and fund the latest technology for their child with any disease. While nonprofits and foundations exist for many diseases, the vast majority of the 7,000 rare diseases do not have the scientific and philanthropic infrastructure to help. Many parents fight heroically on behalf of their children, and some of them have even become the driving force for research. At RGI, we are inspired by such parents and feel that if we can help provide the right tools and partnerships, extraordinary things can be achieved.

We start by helping parents connect with the right researchers and clinicians. Then, we provide mechanisms for them to fundraise. Finally, we try to guide them through the science that hopefully result in a better life for their child or for future children. Throughout the whole process, we try to educate, support, and walk alongside families undergoing this long journey.
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Guest post: Time to bring human genome sequencing into the clinic

Gholson Lyon is a physician-scientist currently working at the Utah Foundation for Biomedical Research and the Center for Applied Genomics at Children’s Hospital of Philadelphia. He will be starting as an assistant professor in human genetics at Cold Spring Harbor Laboratory next month. I asked him to write this guest post to provide some personal context to his thought-provoking commentary in Nature (subscription required) on returning genetic findings to research subjects. [DM]

Max

Photo of Max, who died aged four months from Ogden syndrome. Posted with permission from his family.

I have just published in Nature a commentary discussing the need to bring exome and genome sequencing into the clinical arena, so that these data are generated with the same rigorous clinical standards as for any other clinical test. This way, we can then easily return at least medically actionable results to research participants. In this day and age of consumer and patient empowerment, I can also see eventually returning all data, including the raw data, to any interested participants, as this can then promote crowd-sourcing for data analysis, with research participants controlling and promoting the relative privacy of and analysis of their own data.

As I described in my commentary, my thinking on this matter was prompted mainly by Max  (see picture) and his family. The obituary for Max can be found here, and that of his cousin, Sutter, here. We described their condition here, and we named this new disease Ogden Syndrome in honor of where the first family lives. I am now trying to think about and discuss the human aspects of and lessons from this story. My thinking has also been influenced somewhat by the late James Neel, who wrote a very thought-provoking book called Physician to the Gene Pool.

To me, it was deeply disconcerting that I could not officially return any results to this family (or to another family in a different project discussed here) even when the papers describing the genetic basis of their disease were published, as this was considered “research” and was not performed in a clinically appropriate (CLIA-certified) manner. This was all the more painful when one of the sisters in the Ogden family became pregnant and asked me what I knew. I cannot predict whether it would have helped or hurt this woman to learn during her pregnancy that she was indeed a carrier of the mutation, with the associated 50% risk of her baby boy having the disease. I also do not know if she would have undergone any genetic testing via amniocentesis of the fetus prior to birth (with the associated ~1% risk of miscarriage from the procedure), nor do I know what decisions she might have made prior to the birth even if she had undergone such testing. All in all, it was certainly an ethical and moral dilemma for me not to be able to return the research result to her, given that the results were not obtained in a CLIA-certified manner. It is still an issue, as there are even now financial and systematic barriers for getting all women in the family tested with a CLIA-certified gene test for NAA10 (which was developed over a six month period by ARUP Laboratories). It would have been so much better if we had just done the entire sequencing up front in a CLIA-certified manner.
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Ethics and Genomic Research: ‘Genomethics’

Dr Anna Middleton is an Ethics Researcher and Registered Genetic Counsellor, based at the Wellcome Trust Sanger Institute. She leads the ethics component of the Deciphering Developmental Disorders study, a collaborative project involving WTSI and the 23 National Health Service Regional Clinical Genetics Services in the UK. This project involves searching for the genetic cause of developmental disorders, using array-CGH, SNP genotyping and exome sequencing, in ~12,000 children in the UK who currently have no genetic diagnosis.

One of the issues raised by this, and many other research projects, is what should happen to ‘incidental’ findings, i.e. potentially interesting results from genomic analyses that are not directly related to the condition under study.  Here Anna discusses the research she is conducting on this topic as part of the DDD study, and provides a link to the DDD Genomethics survey where you can share your own views (I should also disclose here that both Caroline and I also work on the DDD study).[KIM]

Whole genome studies have the ability to produce enormous volumes of valuable data for individuals who take part in research. However, as a consequence of analysing all 20,000+ genes, whole genome studies unavoidably involve the discovery of health related information that may have actual clinical significance for the research participant.  Some of this will be considered a ‘pertinent finding’, i.e. directly related to the phenotype under study (e.g. the child’s developmental disorder); some of this will be considered an ‘incidental or secondary finding’ in that it is not directly linked to the phenotype under study or the research question that the genomic researchers are trying to answer.

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Going green: lessons from plant genomics for human sequencing studies

This is a guest post by Jeffrey Rosenfeld. Jeff is a next-generation sequencing advisor in the High Performance and Research Computing group at the University of Medicine and Dentistry of New Jersey, working on a variety of human and microbial genetics projects. He is also a Visiting Scientist at the American Museum of Natural History where he focuses on whole-genome phylogenetics. He was trained at the University of Pennsylvania, New York University and Cold Spring Harbor Laboratory.

As human geneticists, it is all too easy to ignore papers published about non-human organisms – especially when those organisms are plants. After all, how much can the analysis of (say) Arabidopsis genome diversity possibly assist in my quest to better understand the human genome and determine which genes cause disease? Quite a bit, as it happens: a fascinating recent paper in Nature demonstrates a number of lessons that we can learn from our distant green relatives.

By exploiting the small genome size of Arabidopsis (~120 million bases, compared to the relatively gargantuan 3 billion bases of Homo sapiens), researchers were able to perform complete genome sequencing and transcriptome profiling in 18 different ecotypes of the plant (similar to what we would call strains of an animal).

In a normal genome re-sequencing experiment, the procedure is to obtain DNA from an individual, sequence the DNA, align it to a reference sequence and then to call variants (i.e. differences from the reference). This approach is used by the 1000 Genomes Project and basically all of the hundreds of disease-focused human sequencing projects currently underway around the world. This approach allows researchers to relatively easily identify single-base substitution (SNP) and small insertion/deletion (indel) differences between genomes. However, the amount of variability that can be identified is restricted by the use of a reference: regions where there is extreme divergence between the reference and sample genomes are often badly called, and more complex variants (e.g. large, recurrent rearrangements of DNA) can be missed. Additionally, and crucially, sequences that are not present in the reference genome will be completely missed by this approach.
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Direct-to-consumer genetic test results in a clinical setting: a case report

Dr Neeta Tailor is an anaesthetist working at the Royal Gwent Hospital in Wales. Dr Tailor recently treated a friend of Genomes Unzipped members (referred to here as Patient X) who required emergency surgery following some unusual and fairly horrible complications (believe me, I’ve seen the photos!) from wisdom tooth removal. The remarkable thing about this case: prior to surgery the patient volunteered information about her potential drug responses based on her 23andMe profile, including variation in one gene that could have had a profound effect on her response to a standard muscle relaxant. Dr Tailor kindly agreed to write up her experience in this guest post.

For those interested in the genetic details: Patient X’s 23andMe results suggest she is heterozygous for the rs1799807 SNP, which induces an aspartate to glycine change in the BCHE gene and is associated with a substantially prolonged apnea (loss of breathing) following administration of succinylcholine. This is one of three separate mutations in the BCHE gene tested by 23andMe. Although in this case the clinicians had already decided independently to avoid the use of succinylcholine, it’s intriguing to think about how rapidly this type of information could become useful to clinicians – and what steps will need to be taken to ensure DTC genetic testing results are trustworthy enough to justify their consideration in this kind of emergency setting. [DM]


Anaesthesia is classically described as the pharmacologically induced triad of amnesia (memory loss), analgesia (pain reduction) and the loss of muscle reflexes. Patients usually come across anaesthetists during their pre-operative anaesthetic assessment; we are the ones telling you that our job is to pop you off to sleep, although it is usually more complicated than that!

The patient described below works in the world of genetics and invited me to describe her case in order to illustrate how pharmacogenomics and person specific genetic characteristics may affect the choice of general anaesthesia.

A 37 year old woman (Patient X) was booked onto the emergency theatre list on a Sunday morning. The planned operation was incision and drainage of an infected haematoma in the cheek, an unusual complication which had developed quickly over 48 hours following the extraction of a wisdom tooth by her own dentist. By the time she was admitted to hospital, she had extensive facial swelling, not just of her gum, but also the whole of the left side of her face from her forehead to her neck. In addition, she had reduced jaw movement, as well as limited mouth opening of less than one finger breadth. She was also feeling quite unwell having vomited during the night and her blood tests showed raised markers of infection. She was in pain requiring several different types of analgesia.

This presentation in itself poses some difficulty. One of our jobs as anaesthetists involves administering drugs to cause unconsciousness which subsequently requires maintenance of a patent airway using either a mask, an airway device that sits above the vocal cords, or by a tube in the trachea. We usually then maintain unconsciousness using an inhaled volatile anaesthetic via the chosen device.

During this operation we knew we were going to need to share the airway with our maxillo-facial surgery colleagues performing the procedure. To ensure the optimal outcome for all (an anaesthetised patient for us and access to the mouth for the maxfax team), a tube in the trachea was the most ideal option. However, to get to the trachea, we have to get in the mouth and get a good view of the vocal cords and this is where the potential problem could arise.
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Guest post by Adam Rutherford: Unknown unknowns and the human genome

This is the second of three guest posts from panellists in the Race to the $1000 Genome session tomorrow at the Cheltenham Science Festival. Yesterday we heard from Oxford Nanopore‘s Clive Brown about the disruptive effects of genomic technology; today’s instalment is from science broadcaster Adam Rutherford, presenter of the recent BBC series about the genome, The Gene Code. Tomorrow we’ll hear from Genomes Unzipped’s own Caroline Wright.

There are known knowns; there are things we know we know. We also know there are known unknowns; that is to say we know there are some things we do not know. But there are also unknown unknowns – the ones we don’t know we don’t know. —Donald Rumsfeld.

The expectations of the Human Genome Project were Rumsfeldian. This much-mocked statement that the then US Secretary of Defense Donald Rumsfeld made in response to the continued absence of evidence for weapons of mass destruction was made almost exactly a year after the publication of the first results of the Human Genome Project (HGP). His oddly profound cod-philosophy resonates with that grand endeavour. The announcement, initially in June 2000, and the publication, were met with triumphalism in the media, fanned by our and its glorious leaders. President Clinton stood on a platform, flanked by Craig Venter and Francis Collins at the White House, and declared that:

Without a doubt this is the most important most wondrous map produced by human kind…

Today we are learning the language in which God created life.

Whatever your religious disposition, that is a bold statement. He and others went on to speculate that soon we would understand and be on the path to curing many, if not all, diseases. Geneticists bristled at this hubris. The fundamental problem was unknown unknowns. It turned out that humans have far fewer genes than we expected. The vast majority of the genome does not contain genes. So what is it doing?
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Guest post by Clive Brown: the disruptive power of cheap DNA sequencing

In advance of the Cheltenham Science Festival session on the race for the $1,000 genome this Wednesday, panel participant Clive Brown agreed to write a guest post on the importance of advances in genomic technology. Clive is Chief Technology Officer at Oxford Nanopore Technologies, where he leads the specification and design of the Company’s nanopore based sensing platform, including strand DNA/RNA sequencing and protein sensing applications, which we’ve written about previously here at Genomes Unzipped.

Incidentally, the other panel members will be Adam Rutherford, presenter of the excellent recent genetics documentary series The Gene Code, and Genomes Unzipped’s very own Caroline Wright, and the session will be chaired by Times Science Editor Mark Henderson – so if you’re anywhere near Cheltenham, you should definitely check it out.

When the final Human Genome Project publication was published in 2004, hundreds of scientists from 18 different institutions from the UK to the US, China and Japan authored the paper. The cost of this phenomenal collaborative project has been estimated at more than $3 billion from its initiation, a ‘moon-shot’ that was necessary to step onto the path of improving the process of obtaining and understanding genetic information. In 2004 the cost of sequencing a whole (haploid) human genome was still in the region of tens of millions of dollars. In 2008 this dropped through $1 million, in 2009 through $100k and in 2011 the cost is approaching $10k.

Many people have criticised the fact that the Human Genome Project did not in itself deliver a new era of personalised medicine, without realising that the project was just the first hurdle which facilitated major steps forward in the basic scientific understanding of genomics – for example, understanding the basic structure of the genome or mapping the variation between different peoples’ genomes. Importantly, the foundations were laid for understanding the very complex mechanisms behind how the genetic code relates to the expression of a protein and therefore the ‘phenotype’ – how those genetic differences are manifested whether it is a trait or disease-causing malfunction.
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