Sugarcane in Brazil is increasingly grown for bioethanol. What's often overlooked is that it doesn't just have the potential to cool the planet through reduced carbon emissions,but through its direct effect on the climate too.... Read more »
Loarie, S., Lobell, D., Asner, G., Mu, Q., & Field, C. (2011) Direct impacts on local climate of sugar-cane expansion in Brazil. Nature Climate Change. DOI: 10.1038/NCLIMATE1067
The ENCODE project is one of the “big data” projects that is generating genome-wide data on a variety of different aspects of genome biology. It’s been around for a while, and some people have heard about it but really haven’t begun to dive into the data yet. And they really should.
We’ve had our hands on the ENCODE data since the earliest days of the new scale-up or production phase. We’ve been doing outreach for the UCSC Genome Browser’s DCC portion of the ENCODE work, meaning workshops, online materials, etc. So as a “user” of the data, I can tell you that there is some amazing stuff coming out of this project now. And a lot of it is brand new information to you–I assure you.
I talked about some great stuff recently that was published about chromatin state: ENCODE Chromatin state data offers nice insights. Take this and run with it. That paper is a closer look at one of the data types that’s coming in, and provides some nice guidance on how to explore your own regions of interest for the signals they detect. But the ENCODE team as a whole had just published a paper that looks across the whole project, gives you more background on how the data is generated and what the individual project pieces are supposed to be generating, and some tips on how to use the data. They’ve published a “User’s Guide”.
Figure 1 provides a nice summary of many of the types of data that are coming out of the project, and the techniques used to analyze the features: many types of long-range regulatory elements such as enhancers, silencers, etc; short-range regulatory elements such as promoters and transcription factor binding sites; many types of RNAs being made in the cells, and so on. I also love the copy number variation data the cell lines and other structural info coming out. The other part of the figure talks to the structure of the project data and flow, which is helpful to understand as well.
But most importantly, here’s where you come in–when you start to use this and make discoveries, you can feed back into the project with your insights:
Examples applying ENCODE data at individual loci to specific biological or medical issues are a good starting point for exploration and use of the data. Thus, we also provide a collection of examples at the “session gallery” at the ENCODE portal. Users are encouraged to submit additional examples; we anticipate that this community-based sharing of insights will accelerate the use and impact of the ENCODE data.
I know people have made discoveries in the ENCODE data. When we did a workshop at the NIH there was a woman sitting in the front row giggling about some TFBS data we showed her how to obtain. I have seen chromatin signals that identify a tissue-specific splice site that I know about, but which is not annotated in human. My 23andMe SNPs sometimes have been in really sparse regions–and the only data I have seen in that region is some intriguing ENCODE regulation data: I think I’ve found an un-annotated gene. I’ve seen CNV data that led me to curious correlations in the International Cancer Genome Consortium (IGCG) data. It’s just sitting there waiting for you.
There’s good and novel stuff in there. You need to look at your regions of interest and add this context to it.
The paper also does talk about the limitations of the ENCODE data as well. One is that cells are not synchronized, so it has to provide a population look at the cells, which means their cell cycle states are mixed. A couple of the cell lines are known to have some genome instability (and yeah, that’s what I saw in the CNV data). And cell lines are not human tissues. There are also some limitations of the sequence reads that are generated. But still–the data that is coming along should keep you busy nonetheless.
You can read the user’s guide for more details, and it will be really helpful as a reference as you get into the data. You can also explore the tutorial that we developed with the UCSC team for an overview.
Special note for software junkies: be sure to see the Supplemental Data. Table S1 has a nice summary of the software tools that are being used to generate the data (Warning–it’s a word doc). Some of it isn’t published yet, but is worth keeping an eye out for. One point we keep making in the workshops is that even if you don’t care much about these specific data types, the ENCODE project is offering nice strategies and tools for you to use for analyzing and displaying your own NGS data with genome context.
The ENCODE Project Consortium. (2011). A User’s Guide to the Encyclopedia of DNA Elements (ENCODE) PLoS Biology, 9 (4) DOI: 10.1371/journal.pbio.1001046
ENCODE tutorial at OpenHelix, freely available because it is sponsored by UCSC: http://openhelix.com/ENCODE
Other reading about this:
RT @sangerinstitute: Genomes are deep stores of nuanced messages: ENCODE project hunts meaning http://bit.ly/dFoaqH
NHGRI Press Release: New user’s guide and tutorial helps disease researchers interpret human genome
Nature (2011). Genomics: A guided tour of the genome Nature, 473 (7345), 8-9 DOI: 10.1038/473008d
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The ENCODE Project Consortium. (2011) A User's Guide to the Encyclopedia of DNA Elements (ENCODE). PLoS Biology, 9(4). DOI: 10.1371/journal.pbio.1001046
Ok, really today's post isn't about that. But it's definitely the one major thing I took away from this paper. This post is actually about the effects of cell phones on semen. But refer to your semen as "neat" once, and well, it sticks with you. (These scientists like their semen the way they like [...]... Read more »
Agarwal, A., Desai, N., Makker, K., Varghese, A., Mouradi, R., Sabanegh, E., & Sharma, R. (2009) Effects of radiofrequency electromagnetic waves (RF-EMW) from cellular phones on human ejaculated semen: an in vitro pilot study. Fertility and Sterility, 92(4), 1318-1325. DOI: 10.1016/j.fertnstert.2008.08.022
Some months ago, Bosco Ho, Molecular Dynamics (MD) boy wonder and HTML5 wiz, contacted a group of scientists, myself included, to start a world wide Journal Club (JC). The subject: Molecular Dynamics, the venue? Annotatr - a mashup of CiteULike and Disqus. The motivation behind Annotatr was to get scientists to comment on articles (lower the energy barrier if you prefer).
Since then the MD JC had several prolific sessions, discussing some great MD papers on which I'll discuss briefly below.
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Shaw DE, Maragakis P, Lindorff-Larsen K, Piana S, Dror RO, Eastwood MP, Bank JA, Jumper JM, Salmon JK, Shan Y.... (2010) Atomic-level characterization of the structural dynamics of proteins. Science (New York, N.Y.), 330(6002), 341-6. PMID: 20947758
Meyer T, D'Abramo M, Hospital A, Rueda M, Ferrer-Costa C, Pérez A, Carrillo O, Camps J, Fenollosa C, Repchevsky D.... (2010) MoDEL (Molecular Dynamics Extended Library): a database of atomistic molecular dynamics trajectories. Structure (London, England : 1993), 18(11), 1399-409. PMID: 21070939
The Third BHD Symposium has been discussed a lot in the blog and it is now only 5 days away! Final preparations are underway for the meeting, which will be held in Maastricht, the Netherlands on 11th and 12th May. … Continue reading →... Read more »
Lee & Hasagawa (2011) use phylogenetic methods to trace the origins of Japonic languages and dialects.... Read more »
Lee S, & Hasegawa T. (2011) Bayesian phylogenetic analysis supports an agricultural origin of Japonic languages. Proceedings. Biological sciences / The Royal Society. PMID: 21543358
Gray, R., Drummond, A., & Greenhill, S. (2009) Language Phylogenies Reveal Expansion Pulses and Pauses in Pacific Settlement. Science, 323(5913), 479-483. DOI: 10.1126/science.1166858
When we talk about plant traits here we are usually referring to things like characterization and evaluation descriptors, and how they vary within crops. But there’s an ambitious initiative underway to document “the morphological, anatomical, physiological, biochemical, and phenological characteristics of plants and their organs” — some 1500 of them — across the world’s entire [...]... Read more »
Moles, A., Wallis, I., Foley, W., Warton, D., Stegen, J., Bisigato, A., Cella-Pizarro, L., Clark, C., Cohen, P., Cornwell, W.... (2011) Putting plant resistance traits on the map: a test of the idea that plants are better defended at lower latitudes. New Phytologist. DOI: 10.1111/j.1469-8137.2011.03732.x
Guest Post: Introducing Lassa virus, the forgotten Ebola brother.... Read more »
Neural crest cells are transitory, making them difficult to study. Dr. Alexey Terskikh and colleagues show how the SOX2 gene controls their differentiation into neurons.... Read more »
Cimadamore F, Fishwick K, Giusto E, Gnedeva K, Cattarossi G, Miller A, Pluchino S, Brill LM, Bronner-Fraser M, & Terskikh AV. (2011) Human ESC-Derived Neural Crest Model Reveals a Key Role for SOX2 in Sensory Neurogenesis . Cell Stem Cell, 8(5), 538-551. info:/doi:10.1016/j.stem.2011.03.011
Regenerative medicine and stem cell research go hand-in-hand when it comes to dreaming up future strategies for treating disease and injury in humans. Today’s image is from a recent Development paper discussing how damaged heart tissue regenerates in zebrafish, and serves as a great model for devising strategies to help human heart attack patients. When [...]... Read more »
Gonzalez-Rosa, J., Martin, V., Peralta, M., Torres, M., & Mercader, N. (2011) Extensive scar formation and regression during heart regeneration after cryoinjury in zebrafish. Development, 138(9), 1663-1674. DOI: 10.1242/dev.060897
For baboons, running away from home is something a boy is expected to do. Most baboon species rely on young males leaving the social group they’re born into and starting or joining another group to disperse genes and ensure diversity. In one species, though, the hamadryas baboon (Papio hamadryas) of northeast Africa, genetic evidence suggests [...]... Read more »
Pines M, & Swedell L. (2011) Not without a fair fight: failed abductions of females in wild hamadryas baboons. Primates; journal of primatology. PMID: 21359653
by Moselio Schaechter in Small Things Considered
by Merry Youle
Given the streamlined genomes and the frugal nature of the Bacteria and Archaea, one might expect their proteins to be short and to the point. However, a survey of the 580 prokaryotic sequenced genomes available in 2008 found many genes apparently encoding large proteins. Specifically, 0.2% of the ORFs (3732 genes) were longer than 5 kb. Of those, 80 were truly giants—more than 20 kb! These mammoths were found scattered about in 47 taxa in 8 different phyla. The longest two, both from the green sulfur bacterium Chlorobium chlorochromatii CaD3, encode proteins containing 36,806 and 20,647 amino acids, respectively.... Read more »
A new paper has just been published on the mechanisms associated with BRAF resistance by Corcoran et al., (2011). One of the things I liked about this paper, other than it’s clarity and simplicity, is that you can find it … Continue reading →
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Corcoran RB, Settleman J, & Engelman JA. (2011) Potential Therapeutic Strategies to Overcome Acquired Resistance to BRAF or MEK Inhibitors in BRAF Mutant Cancers. Oncotarget. PMID: 21505228
In January 2011, Junchang Lü, David Unwin, Charles Deeming and colleagues published their Science paper on the amazing discovery of an egg-adult association in the Jurassic pterosaur Darwinopterus (Lü et al. 2011) [the specimen is shown here: image courtesy of Junchang Lü, Institute of Geology, Beijing, used with permission]. Darwinopterus is the incredible 'transitional pterosaur', first unveiled to the world in October 2009 and rapidly becoming one of the most important pterosaurs of all in terms of what we're learning from it.
As I discussed in a Tet Zoo article published in February, Lü et al.'s egg-adult discovery not only adds another confirmed pterosaur egg to the rather paltry global record, it also provides new data on pterosaur sexual dimorphism and, by inference, behaviour and biology. However, that wasn't the whole story, and here I complete what I started a few months ago. Why the delay? All will be explained below... Read the rest of this post... | Read the comments on this post...... Read more »
Lü J, Unwin DM, Deeming DC, Jin X, Liu Y, & Ji Q. (2011) An egg-adult association, gender, and reproduction in pterosaurs. Science (New York, N.Y.), 331(6015), 321-4. PMID: 21252343
So much depends on healthy cell division, so it is no wonder how magnificent the spindle checkpoint is. This checkpoint keeps our cells healthy and our biologists busy as they try to figure it all out. The spindle checkpoint ensures that a dividing cell undergoes anaphase only when all chromosomes are properly attached the mitotic spindle. Without this checkpoint, cells may end up with an incorrect number of chromosomes. Recently, a group teased apart some of the specifics of the checkpoint by using a construct engineered in the lab. This construct fused the kinetochore protein Mis12 to the checkpoint protein Mad1, which blocks progression to anaphase when it localizes to kinetochores not attached to the spindle. This Mad1-Mis12 construct targeted Mad1 to kinetochores despite their orientation state on the mitotic spindle, meaning that this construct allowed researchers to distinguish between Mad1 checkpoint signaling and the initial orientation error signal. The images above show metaphase spindles in control cells (top) or cells with the Mad1-Mis12 construct (bottom). The construct (mCherry, red in merged image) localizes to kinetochores (CREST, blue in merged) attached to the spindle (tubulin, green).Maldonado, M., & Kapoor, T. (2011). Constitutive Mad1 targeting to kinetochores uncouples checkpoint signalling from chromosome biorientation Nature Cell Biology, 13 (4), 475-482 DOI: 10.1038/ncb2223Adapted by permission from Macmillan Publishers Ltd, copyright 2011... Read more »
Maldonado, M., & Kapoor, T. (2011) Constitutive Mad1 targeting to kinetochores uncouples checkpoint signalling from chromosome biorientation. Nature Cell Biology, 13(4), 475-482. DOI: 10.1038/ncb2223
The question of how a genotype (the arrangement of letters in DNA) maps to a phenotype (the shape and behavior of an organism) can be examined at many levels. On the one hand, we’d like to know how small differences in DNA sequence determine differences between individual humans, such as susceptibility to disease, height, IQ, [...]... Read more »
Yanai I, Peshkin L, Jorgensen P, & Kirschner MW. (2011) Mapping gene expression in two Xenopus species: evolutionary constraints and developmental flexibility. Developmental cell, 20(4), 483-96. PMID: 21497761
Last year, the world of psychiatric genetics was rocked by the news that a highly-studied gene, believed to be associated with depression, wasn't in fact linked to depression at all.The genetic variant was 5-HTTLPR. It's a length variant in the gene coding for the serotonin transporter protein (5HTT) which the target of antidepressants like Prozac. There are two flavors of this variant, short and long.Many studies have shown that the short ("s") variant is associated with a high risk of getting depression in response to stress - but then last year a large meta-analysis of all the evidence concluded that there was in reality no link. Bummer.Now another team of researchers have done a new analysis of the 5-HTTLPR & stress & depression data and they claim that there is a link after all: hooray! So who's right? I'm not sure, but the new paper raises many questions.The new paper puts together the results of all 54 studies which have looked at this gene in the context of depression, caused by any kind of stress. The authors were intentionally liberal in their inclusion criteria: studies in any population were OK, for example they included people with Parkinson's disease or heart disease.They say that this is the main difference between the present work and earlier meta-analyses that found no link. The famous 2010 paper, for example, only included 14 studies because they only considered certain kinds of stress.Anyway, the short variant is associated with depression after all, across all of the studies. They extracted the p values from the results of all previous studies, and took the average of those, weighted by the sample size. They found a very significant association: P=.00002.Here's all the results. Each square is a study, the further to the left, the more strongly they found an association. Bigger squares mean larger studies. As you can see, most studies found a link but the three largest studies - which were much larger than the others - found none. Hmm.In terms of specific kinds of stress, they found strong evidence that "specific stressors" (like medical illness), and childhood trauma, were associated with more depression in s-allele carriers. However, in the studies on "Stressful Life Events", which is a broad category meaning pretty much anything bad that happens, the evidence was weaker. The previous meta-analyses only considered these studies.Ultimately, I think this analysis should remind us that the issue of 5HTTLPR is still "open", but I have concerns about the dataset. The fact that larger studies seem less likely to be positive is a classic warning sign of publication bias.The authors do consider this and say that they calculate that there would have to be over 700 unpublished, negative studies out there, in order to make the overall data negative. They also find that you could ignore the smallest 45 studies and still find a result. But still. Something doesn't feel right. Maybe I just have the wrong 5HTTLPR variant.Karg K, Burmeister M, Shedden K, & Sen S (2011). The Serotonin Transporter Promoter Variant (5-HTTLPR), Stress, and Depression Meta-analysis Revisited: Evidence of Genetic Moderation. Archives of general psychiatry, 68 (5), 444-54 PMID: 21199959... Read more »
Karg K, Burmeister M, Shedden K, & Sen S. (2011) The Serotonin Transporter Promoter Variant (5-HTTLPR), Stress, and Depression Meta-analysis Revisited: Evidence of Genetic Moderation. Archives of general psychiatry, 68(5), 444-54. PMID: 21199959
If you’ve ever been rejected by a loved one, you knows that it hurts. Think of the language that we use to describe the feeling – hurt, pain, broken hearts, heartache, and so on. Across cultures, many of the same words are used to describe social rejection and bodily pain. Is this all just metaphor, or are people who have been dumped genuinely feeling physical pain? A recent study by Ethan Kross and colleagues set out to address this question by putting volunteers who had recently experienced such intense rejection into brain imaging machines.... Read more »
Kross E, Berman MG, Mischel W, Smith EE, & Wager TD. (2011) Social rejection shares somatosensory representations with physical pain. Proceedings of the National Academy of Sciences of the United States of America, 108(15), 6270-5. PMID: 21444827
Every thirteen years they come. After over a decade underground, they build burrows to the earth’s surface and emerge in synchrony, clawing and crawling up through the soil, rip their skins down the back and are reborn as adults. And after a month, they will be dead, whether consumed by the animals awaiting their arrival [...]... Read more »
Wheeler, G., Williams, K., & Smith, K. (1992) Role of periodical cicadas (Homoptera: Cicadidae: Magicicada) in forest nutrient cycles. Forest Ecology and Management, 51(4), 339-346. DOI: 10.1016/0378-1127(92)90333-5
Pray, C., Nowlin, W., & Vanni, M. (2009) Deposition and decomposition of periodical cicadas (Homoptera: Cicadidae: ) in woodland aquatic ecosystems . Journal of the North American Benthological Society, 28(1), 181-195. DOI: 10.1899/08-038.1
Yang, L. (2004) Periodical Cicadas as Resource Pulses in North American Forests. Science, 306(5701), 1565-1567. DOI: 10.1126/science.1103114
Yang, L. (2005) Interactions between a detrital resource pulse and a detritivore community. Oecologia, 147(3), 522-532. DOI: 10.1007/s00442-005-0276-0
Speer, J., Clay, K., Bishop, G., & Creech, M. (2010) The Effect of Periodical Cicadas on Growth of Five Tree Species in Midwestern Deciduous Forests. The American Midland Naturalist, 164(2), 173-186. DOI: 10.1674/0003-0031-164.2.173
Koenig, W., & Liebhold, A. (2003) Regional impacts of periodical cicadas on oak radial increment. Canadian Journal of Forest Research, 33(6), 1084-1089. DOI: 10.1139/X03-037
Yang, L. (2008) PULSES OF DEAD PERIODICAL CICADAS INCREASE HERBIVORY OF AMERICAN BELLFLOWERS. Ecology, 89(6), 1497-1502. DOI: 10.1890/07-1853.1
Krohne, D., Couillard, T., & Riddle, J. (1991) Population Responses of Peromyscus leucopus and Blarina brevicauda to Emergence of Periodical Cicadas. American Midland Naturalist, 126(2), 317. DOI: 10.2307/2426107
Koenig, W., & Liebhold, A. (2005) EFFECTS OF PERIODICAL CICADA EMERGENCES ON ABUNDANCE AND SYNCHRONY OF AVIAN POPULATIONS. Ecology, 86(7), 1873-1882. DOI: 10.1890/04-1175
Koenig, W., Ries, L., Olsen, V., & Liebhold, A. (2011) Avian predators are less abundant during periodical cicada emergences, but why?. Ecology, 92(3), 784-790. DOI: 10.1890/10-1583.1
by Vincent Racaniello in virology blog
Since the first association of the retrovirus XMRV with chronic fatigue syndrome in 2009 in the US, subsequent studies have failed to detect evidence of infection in patients from the US, Europe, and China. These studies were potentially compromised by a number of factors, such as differences in patient characterization, geographic locations, clinical samples used, [...]... Read more »
Clifford H. Shin, Lucinda Bateman, Robert Schlaberg, Ashley M. Bunker, Christopher J. Leonard, Ronald W. Hughen, Alan R. Light, Kathleen C. Light, & Ila R. Singh1*. (2011) Absence of XMRV and other MLV-related viruses in patients with Chronic Fatigue Syndrome. Journal of Virology. info:/10.1128/JVI.00693-11
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