Sponsored by the Office of the Vice-President for Research.
Speaker Information:
Dan Bauer is a lecturer in Pediatrics at Harvard Medical School. He is first author on the October 2013 Science paper “An erythroid enhancer of BCL11A subject to genetic variation determines fetal hemoglobin level”. He received his MD and PhD from the University of Pennsylvania and his BS from Brown University.
Patrick Hsu is a graduate student in Feng Zhang’s lab at the Broad Institute at MIT and Harvard and the McGovern Institute for brain research at MIT. In the past year he has contributed to 8 papers from the Zhang lab on CRISPR and genome engineering. He received his BS from Berkeley in Cellular and Molecular Biology.
Ophir Shalem is a postdoctoral research fellow in Feng Zhang’s lab at the Broad Institute of MIT and Harvard and the McGovern Institute for brain research at MIT. He is the first author on the January 2014 Science paper “Genome-scale CRISPR-Cas9 knockout screening in human cells” from the Zhang lab. He received his PhD from the Weizmann institute of Science in Biology and Computer Science and his BS from Ben Gurion University in Bioinformatics and Computer Science.
Jian-Kang Zhu is Distinguished Professor in the Departments of Biochemistry and Horticulture and Landscape Architecture at Purdue University. Recent work in his lab, which includes publications in Nature, PLOS Genetics and PNAS, has focused on RNA binding, genome engineering and DNA methylation. He received his BS from Beijing Agricultural University and his PhD from Purdue. He was a post-doctoral researcher at Rockefeller University.
Here's some recent CRIPSR coverage, focused on a method for measuring editing accuracy:
Recently a powerful new technology has emerged (called CRISPR) that allows researchers to make small, precise and permanent changes in the DNA of animal and human cells. It builds on the concept of genome editing that is key to generating cells, cell lines or even whole animals such as laboratory mice, containing specific genetic changes for study. With CRISPR, however, researchers can generate in days or weeks experimental models that usually take months or years. As a result, they can quickly assess the effect of a particular gene by deleting it entirely, or experiment with repeated, tiny changes to its DNA sequence.See also here:
According to a recent New York Times article, scientists roundly agree that CRISPR is revolutionary. At least three companies have been launched in the mere 18 months since the first results were reported by researchers at the University of California, Berkeley and Umea University in Sweden, and more than 100 research papers based on the technique have been published. But, although it’s highly specific, it’s (sadly) not perfect. According to the New York Times piece:
Quick is not always accurate, however. While Crispr is generally precise, it can have off-target effects, cutting DNA at places where the sequence is similar but not identical to that of the guide RNA.Obviously it’s important to know when (and how frequently) this happens. Unfortunately, that’s been difficult to assess.
Enter researchers in the laboratory of pediatric cancer biologist Matthew Porteus, MD, PhD. Porteus’s lab is interested in (among other things) learning how to a particular type of genome editing called homologous recombination to treat diseases like sickle cell anemia, thalassemia, hemophilia and HIV. They’ve devised a way to monitor the efficiency of genome editing by CRISPR (as well as other more-traditional genome editing technologies) that could be widely helpful to researchers worldwide. Their technique was published today in Cell Reports. As postdoctoral researcher Ayal Hendel, PhD, told me:
We have developed a novel method for quantifying individual genome editing outcomes at any site of interest using single-molecule real-time (also known as SMRT) DNA sequencing. This approach works regardless of the editing technique used, and in any type of cell from any species.
MIT scientists report the use of a CRISPR methodology to cure mice of a rare liver disorder caused by a single genetic mutation. They say their study (“Genome editing with Cas9 in adult mice corrects a disease mutation and phenotype”), published in Nature Biotechnology, offers the first evidence that this gene-editing technique can reverse disease symptoms in living animals. CRISPR, which provides a way to snip out mutated DNA and replace it with the correct sequence, holds potential for treating many genetic disorders, according to the research team.
I hope that some day every newborn will have the variants which protect some smokers against lung cancer. Then more people can smoke.
ReplyDeleteHow many of the boldest claims will be shown to be the products not even of error, but of fraud?
ReplyDeleteThis field is advancing very fast. Gene editing is rapidly becoming a standard tool in plant, animal and human biology. Most labs report being able to use the tools effectively right away. These are not especially delicate protocols.
ReplyDeleteThese polymorphisms of tiny effect, however, are so many ghosts and the search for them is the last gasp of a failed paradigm.
ReplyDeletehttp://www.independentsciencenews.org/wp-content/uploads/2013/09/Pulp-O-Mizer_heritability.jpg
http://www.independentsciencenews.org/health/still-chasing-ghosts-a-new-genetic-methodology-will-not-find-the-missing-heritability/
Consider a recent GCTA study by Plomin et al., who reported a SNP-based
heritability estimate of 35% for “general cognitive ability” among UK 12
year olds (as compared to a twin heritability estimate of 46%)
Which means the 95% confidence interval goes from 60 pts to a mere 56 pts. Let's make public policy with that!
There was also this by Dreary (a Scott so all he says one may ignore): http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3182557/
ReplyDeleteAccording to Dreary a heritability of .4 is HIGH. Why not higher my not so bonny lass? Why not as high as the twin studies?
It is also possible that causal variants are present in regions of the genome not well covered by the commercial SNP arrays. Nevertheless, our results suggest that common SNPs that are in LD with unknown causal variants account for more than half of all additive genetic variation for human intelligence.
Talk about a human capital shortage!