Can I just express my love/respect for C. Titus Brown? Not only is he into openness in science and metagenomics and such. But he practices what he preaches. For example see – Daily Life in an Ivory Basement : /mar-12/diginorm-paper-posted in which he describes his new submission to arXiv and some background. I know I am big on Open Access and all, but even we have been lame about submitting things to preprint servers like arXiv. Gonne do my best to fix that and try and copy Titus.
Tag: Misc.
Lenses in Biology collection from Nature Outlook: free (for now at least) & worth a look
Some nice long features in Nature Outlook on various topics plus interviews with the authors. Summed up in Lenses on Biology. All freely available though I think that is only for this collection and not in general for Nature Outlook.
- Ocean Science: The power of plankton by Paul Falkowski
- Climate Change: A planet in flux
- Synthetic Biology: Bits and pieces come to life
- Cancer: Solving an age-old problem
- Stem Cells: Flexible friends
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Notes (from me and mostly others) from the JGI User Meeting #JGIUM7
OK, so the DOE Joint Genome Institute User Meeting is underway. Day 2 just finished. And I have been there for much of it but alas, not in some of the talks since I can’t seem to get past the hallway/gathering area outside the talks. There are way way too many people there who I have not talked to or seen in a while … So … apologies to those who thought I might be live tweeting the whole meeting … it just hasn’t happened. But I did use the Storify web tool to make a “storification” of posts to twitter from the meeting – most of which were from other people. Here is the story in slideshow format.
http://storify.com/phylogenomics/jgi-user-meeting-day-1-2.js?template=slideshow[<a href=”http://storify.com/phylogenomics/jgi-user-meeting-day-1-2″ target=”_blank”>View the story “JGI User Meeting Day 1-2” on Storify</a>]
I will update the storification tomorrow. If you want to see the full details in a scrolling winder see below
http://storify.com/phylogenomics/jgi-user-meeting-day-1-2.js[<a href=”http://storify.com/phylogenomics/jgi-user-meeting-day-1-2″ target=”_blank”>View the story “JGI User Meeting Day 1-2” on Storify</a>]
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OMICS Driven Microbial Ecology …
Quick post here. Just discovered a nice review paper by Suenaga on targeted metagenomics: Targeted metagenomics: a high-resolution metagenomics approach for specific gene clusters in complex microbial communities – Suenaga – 2011 – Environmental Microbiology
This “Special Issue” on “OMICS Driven Microbial Ecology” has a series of papers, all of which seem to be freely available, of potential interest to readers of this blog including:
- Beyond the Venn diagram: the hunt for a core microbiome (pages 4–12)
- Omics for understanding microbial functional dynamics (pages 1–3)
- Microbial rhodopsins on leaf surfaces of terrestrial plants (pages 140–146)
- Photoautotrophic symbiont and geography are major factors affecting highly structured and diverse bacterial communities in the lichen microbiome (pages 147–161)
- Complete genome of Candidatus Chloracidobacterium thermophilum, a chlorophyll-based photoheterotroph belonging to the phylum Acidobacteria (pages 177–190)
- Metagenomic comparison of microbial communities inhabiting confined and unconfined aquifer ecosystems (pages 240–253)
and more
Oh, and a paper of mine (with Alex Worden and other members of her lab as well as multiple others)
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The Axis of Evol: Getting to the Root of DNA Repair with Philogeny
The Axis of Evol: Getting to the Root of DNA Repair with Philogeny
In 2005 I wrote an essay about my time in graduate school that was potentially going to be included in a special issue of Mutation Research in honor of my PhD advisor Phil Hanawalt. Alas, publishing my essay ran into complications in regard to the closed access policies of this journal. So in the end, my essay was not published. I had forgotten about it mostly until very recently. And so I decided to convert the essay to a blog post. The essay is sort of about what I did in grad. school and sort of about Phil …
Abstract:
Phylogenomics is a field in which genome analysis and evolutionary reconstructions are integrated. This integration is important because genome data is of great value in evolutionary reconstructions, because evolutionary analysis is critical for understanding and interpreting genomic data, and because there are feedback loops between evolutionary and genome analysis such that they need to be done in an integrated manner. In this paper I describe how I developed my particular phylogenomic approach under the guidance of my Ph.D advisor Philip C. Hanawalt. Since I was the first to use the term phylogenomics in a publication, I have decided to rename the field (at least temporarily) Philogenomics.
1. Doctor of Philosophy
When I went to Stanford for graduate school, I was interested in combining evolutionary analysis and molecular biology in a way that would allow me to study molecular mechanisms through an evolutionary perspective. Although I had gone to Stanford ostensibly to work on butterfly population genetics, within two days of starting a rotation in Phil’s lab, I knew that that was where I wanted to work. This decision was somewhat traumatic, since the work on butterflies included spending the summers at 10,000 feet in the Rocky Mountains and possibly chasing butterflies like a Nabakov wanna-be all over the mountain ranges of the world. As an avid outdoor person, this was quite appealing. Nevertheless, I chose to spend 99% of my graduate work in the dingy confines of Herrin Hall, studying DNA repair. The choice of joining Phil’s lab did have one very positive affect – and that was on my relationship with my grandfather on my mother’s side. Benjamin Post was in many ways like a father to me, especially after my father passed away. He was a physicist from the “old school” and thought that most of biology was completely useless. Needless to say, when I told him I was going to graduate school in California (which he considered already one strike against me) to study butterflies, he decided I was simply a lost cause. Despite all his talk of Einstein and computers and math when I was a child, I might as well have been a poet from his point of view. To make matters worse, my grandfather was a crystallographer, and my brother was getting his Ph.D in crystallography at Harvard. When I informed my grandfather that I was going to be working on DNA repair, he seemed somewhat interested. And then I told him, my advisor, Phil Hanawalt, is relatively well known, and actually used to be considered a biophysicist. Then my grandfather really perked up. He said, “Hanawalt – is he related to Don Hanawalt?” It turns out, that my grandfather worked in the same field as Phil’s father (they both did powder diffraction) and knew him. So my grandfather said “You may not be doing real science, but at least you are doing it with the relative of a real scientist.” Thankfully, I was no longer the black sheep in the family. So, with my grandfather’s approval, I embarked on a career in DNA repair.
I would like to add that I was very torn in writing this article. On the one hand, Phil was the greatest advisor I could ever imagine, allowing me to pursue studies on the evolution of DNA repair and comparative genomic analysis, even though nobody else in the lab worked on such things and at times, nobody seemed interested in them either. Phil’s support allowed me to explore my own interests and develop my concepts for the idea of “Phylogenomics” or the combining of evolutionary reconstructions and genome analysis. On the other hand, this special issue is being published in an Elsevier journal. As a supporter of the Open Access movement on scientific publications (see http://www.plos.org) and the brother of one of the founders of the Public Library of Science, publishing in an Elsevier journal is like cavorting with the devil. But the pull of Phil is very strong (some strange sort of force actually) and despite the effects that this may have on my relationship with my brother, I have agreed to publish in this special issue, and thus can now say that I sold my soul for Phil Hanawalt. [[OOPS – Spoke too soon on this when I wrote it — in the end I just could not sign on the dotted line]].
In this essay, I describe my development in Phil’s lab of the idea of “Phylogenomics” or the combination of evolutionary reconstructions and genome analysis. I would like to add that this is not an attempt to review the field of phylogenomics or all the studies that could be called phylogenomics of DNA repair. For that I recommend reading other papers by myself (some of which are discussed below) as well as those by Rick Wood [1-4]}, Janusz M Bujnicki [5], Eugene Koonin [6-14]}, Carlos Menck [15-18], Michael Lynch [19-21], Patrick Forterre [22-24], Nancy Moran [25-29], and others. This is just meant to review my angle on the phylogenomics of repair and Phil’s contribution to this.
2. RecAgnizing the value of evolutionary analysis in studies of DNA repair
A post-doc in Phil’s lab at the time I was there, Shi-Kau (now known as Scott) Liu was working on analysis of some studies of recA mutants he had done while working in Irwin Tessman’s lab. He asked me if I could help him with some comparative analyses of RecA protein sequences from different species, in the hopes that this might help interpret his experimental data. We then downloaded and aligned all available RecA protein sequences from different species of bacteria and compared the sequence variation to the recently solved crystal structure of a form of the E. coli RecA protein. Specifically we were looking for compensatory mutations in which there was a change in one amino-acid in the region there was a correlated change in another amino-acid in the same region (these were detected using an evolutionary method called character-state reconstruction). Interestingly, in some regions of the crystal structure (e.g., the monomer-monomer contact regions) extensive compensatory mutations could be detected, suggesting that this region of the crystal was conserved between species. In other regions of the crystal (e.g., the filament-filament contact regions), no compensatory mutations could be detected suggesting either that this region of the structure was not conserved between species or that the filament contact regions were some artifact of crystallization. This was important to show since the mutations Shi-Kau was looking at were suppressors of another recA mutant (recA1202) and the suppressors we found did not make complete sense if the filament-filament contact regions of the crystal reflected perfectly what was going on in-vivo (30).
In this way, evolutionary reconstructions helped inform experimental studies in E. coli. While this concept was not necessarily novel, it is important to point out that most molecular sequence comparisons used for structure-function studies both then and now focus on sequence conservation (that is, what is identical or similar between sequences). This does not take full advantage of the evolutionary history of sequences since it does not specifically examine how the sequence conservation came to be (that is, it does not look at the amino-acid changes that occurred, just what is conserved). This made me realize that comparative analysis (identifying what is similar or different between genes or species) was fundamentally different from evolutionary reconstructions (which can identify how and possibly even why the similarities and differences came into being). I should point out that to do the compensatory mutation analysis well requires lots of sequences and this was one of the hidden reasons behind why I have pushed for ten years for people studying the evolutionary relationships among microbes to use recA as a marker as they use rRNA (31).
3. Sniffing around at homologs of repair genes
Shortly after the recA analysis was complete, another problem being addressed in the Hanawalt lab presented an even more powerful test for evolutionary reconstructions. Kevin Sweder, another post-doc in the lab, was working on yeast strains with defects in homologs of human DNA repair genes. It was at this time that many of the human DNA repair genes were being cloned and shown to be members of the helicase superfamily of proteins. Many of these could further be assigned to one particular subfamily within the helicase superfamily – the subfamily that contained the yeast SNF2 protein. Proteins in the SNF2 family could be readily identified because their helicase-like domains were all much more similar to each other than any were to other helicase-domain containing proteins. Yet many scientists, including Kevin, were presented with a problem. As the yeast genome was being completed, blast searches could identify that yeast encoded many proteins in the SNF2 family. However, these same blast searches could not readily identify which yeast gene was the orthologs of which human gene. For those who do not know, homologous genes or proteins come in two primary forms – paralogs, which are genes related by gene duplications (e.g., alpha and beta globin) and orthologs, which are the same form of a gene in different species (e.g., human and mouse alpha-globin). Thus if one wanted to use yeast as a model to study a human disease due to a mutation in a SNF2 homolog, it would be helpful to know which yeast gene was the ortholog of the human gene of interest. Since paralogs are related to each other by duplication events and since duplication events are an evolutionary event, I figured that an evolutionary tree of the SNF2 family proteins might help divide the gene family into groups of orthologs.
Indeed, this is exactly what we found – the SNF2 family could be divided into many subfamilies, each of which contained a human and a yeast gene and thus these genes could be considered orthologs of each others. In our analysis we found something even more striking. For every subfamily in the SNF2 superfamily, if the function of more than one member of the subfamily was known (e.g., the human and yeast genes), the function was always conserved. Also, all different subfamilies appeared to have different functions (32). Thus one could predict the function of a gene by which subfamily in which it resided. As with the analysis of RecA, it should be pointed out that the phylogenetic tree-based assignment of genes to subfamilies was more useful than blast searches because blast is simply a way to identify similarity among genes/proteins. The tree allows one to group genes into correct subfamilies even if rates and patterns of evolution have changed over time and are different in different groups. Again, this is a distinction between comparative analysis and evolutionary analysis.
4. A gut feeling leads to the idea of “Phylogenomics”
With the SNF2 analysis as a backdrop, I proceeded to proselytize to anyone who would listes, that phylogenetic trees of genes were going to revolutionize genomic sequencing proteins by allowing one to predict the functions of many unknown genes. Genome sequencing projects of course product lots of sequence data and little functional information. Although most of the people in the Hanawalt lab (except maybe Phil) could not have cared less about my evolutionary rantings, fortunately for me, one person called my bluff. Rick Myers, a professor in the Stanford Medical School and one of the heads of the Stanford Human Genome Center was asked to write a News and Views for Nature Medicine about the recent publications of the genomes of E. coli O157:H7 and Helicobacter pylori. So Rick challenged me and said I should try and come up with a real example of how the people who worked on these genomes screwed something up by not doing an evolutionary analysis. Fortunately, it was easy to find an interesting case to study in one of the genomes. In the H. pylori paper, the authors had predicted that the species should have mismatch repair but then reported something quite unusual – the genome encoded a homolog of MutS but did not encode a homolog of MutL. I suppose this should have raised a red-flag to them since all species known to have mismatch repair required homologs of both of these proteins for the process. While some species had other bells and whistles (e.g., the use of MutH and Dam in gamma proteobacteria), the use of MutS and MutL was absolutely conserved. An evolutionary tree of the MutS homologs available at the time including the one in H. pylori also suggested a red-flag should have been raised before predicting that this species possessed mismatch repair.
The MutS family in prokaryotes could be divided into two separate subfamilies, which I called MutS1 and MutS2. All genes known to be involved in mismatch repair were in the MutS1 family. No gene in the MutS2 family had a known function. The H. pylori gene was in the MutS2 family. So this species had no MutL and a MutS homolog in a novel subfamily. To us, this suggested that it would be a bad idea to predict the presence of mismatch repair in this species (33). Later, I showed that there was a general trend – all prokaryotes with just a MutS2-like protein did not have a MutL-homolog, and all species with a MutS1-like protein did (34-36). Experimental work has now shown that the MutS2 of H. pylori is not involved in MMR and that this species apparently does not have any MMR (37). This is important because this apparently causes this species to have an exceptionally high mutation rate, which in turn can effect how one designs vaccines and drugs and diagnostics to target it. It should be pointed out that the role of the MutS2 homologs is not known although they have been knocked out in many species and as of yet none have a role in MMR. Thus predicting function by evolutionary analysis (or more specifically, not incorrectly predicting function) can be of great practical value.
It is from this analysis that I came up with the idea of “Phylogenomics” or the integration of evolutionary reconstructions and genome analysis (34-36). These approaches should be fully integrated because there is a feedback loop between them such that they cannot be done separately. For example, in the studies of MutS and MutL it is necessary to do a genome analysis to identify the presence or absence of homologs of these genes, then an evolutionary analysis to determine which forms of each of the genes are present, then a genome analysis again to determine the number and combination of different forms and then an evolutionary analysis to determine whether and when particular forms were gained and lost over evolutionary time, and so on.
5. Lions and TIGRs and bears
Since leaving Phil’s lab I have been a faculty member at The Institute for Genomic Research (TIGR) and in that time we have found dozens of new uses for a phylogenomic approach and designed many new methods to implement phylogenomics. Such an approach has led to many interesting findings relating to DNA repair. Phylogenetic analysis of eukaryotic genomes has allowed us to identify many nuclear encoded genes that are homologs of DNA repair genes but appear to evolutionary derived from the organellar genomes and thus are good candidates for still having a role in DNA repair in the organelles (38). These include both putatively plastid-derived genes (encoding RecA, Mfd, Fpg, RecG, MutS2, Phr, Lon) and mitochondrial-derived genes (encoding RecA, Tag). Interestingly the presence of Mfd but not UvrABCD is also found in many endosymbiotic bacteria, although the explanation for what this Mfd might be doing is unclear. Phylogenomic analysis has allowed us to identify the loss of important DNA repair genes in various species such as the apparent loss of all the genes for non-homologous end joining in the causative agent of malaria, Plasmodium falciparum (39). An important component of this analysis was the finding that this species did not have an orthologs of DNA ligase IV, even though the original annotation of the genome had suggested it did (Figure 1).
 |
| Figure 1. Phylogenetic tree of DNA ligase homologs showing the presence of an orthologs of DNA Ligase I in Plasmodium falciparum but no orthologs of DNA ligase IV, consistent with the absence of non homologous end joining. |
Among the other interesting repair-related features we have found are: the presence of two MutL homologs in an intracellular bacteria Wolbachia pipientis wMel (40), the presence of two UvrA homologs in Deinococcus radiodurans (41) and Chlorobium tepidum (42), the absence of MutS and MutL from Mycobacterium tuberculosis(43), and the presence of multiple ligases for each chromosome in Agrobacteriumtumefaciens (44). Continued surprises come from almost every genome.
However, all is not good in the world of phylogenomics. One of the biggest problems is that most of the experimental studies of DNA repair that have formed the basis of out knowledge in the field have been done in a narrow range of species. For example, there are estimated to be over 100 major divisions of bacteria (Phyla) and of these, most DNA repair studies have been restricted to three of these phyla (Proteobacteria, Firmicutes (also known as lowGC Gram-positives), and Actinobacteria (also known as highGC Gram positives). This means that if anything novel evolved in any of the other lineages, we would not know about it. This probably explains why, when we sequenced the genome of the radiation resistant bacteria D. radiodurans, analysis of the homologs of DNA repair genes in the genome did reveal many homologs of known repair genes but this list did not have many features that were unusual compared to non radiation resistant species (Table 1) and thus was not of much use in understanding what makes this species so resistant (41).
Table 1. Homologs of known DNA repair genes identified in the initial analysis of the D. radiodurans genome sequence
|
Process
|
Genes in D. radiodurans
|
Unusual features
|
|
Nucleotide Excision Repair
|
UvrABCD, UvrA2
|
UvrA2 not found in most species
|
|
Base Excision Repair
|
AlkA, Ung, Ung2, GT, MutM, MutY-Nths, MPG
|
More MutY-Nths than most species
|
|
AP Endonuclease
|
Xth
|
–
|
|
Mismatch Excision Repair
|
MutS, MutL
|
–
|
|
Recombination
Initiation
Recombinase
Migration and resolution
|
RecFJNRQ, SbcCD, RecD
RecA
RuvABC, RecG
|
–
|
|
Replication
|
PolA, PolC, PolX, phage Pol
|
PolX not in many bacteria
|
|
Ligation
|
DnlJ
|
–
|
|
dNTP pools, cleanup
|
MutTs, RRase
|
–
|
|
Other
|
LexA, RadA, HepA, UVDE, MutS2
|
UvDE not in many bacteria
|
This of course means that genome sequencing and analysis, even if done in a robust way, only works well if there is a core of experimental studies on which to base the analysis.
In the end, I would like to define a new word – philogenomics which is the combination of studies of evolution, genomics, DNA repair, thymine metabolism, and punning. The ultimate proof of a philogenomic approach, of course, will come when it figures out the mechanism underlying thymineless death. But that is another story.
6. Acknowledgements
I would like to thank Philip C. Hanawalt for his support during and after my Ph.D research in his lab. Everyone in the field knows he is a great scientist. What they may not all know is that he is an even better human being.
References
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[43] Fleischmann RD, Alland D, Eisen JA, Carpenter L, White O, Peterson J, DeBoy R, Dodson R, Gwinn M, Haft D, Hickey E, Kolonay JF, Nelson WC, Umayam LA, Ermolaeva M, Salzberg SL, Delcher A, Utterback T, Weidman J, Khouri H, Gill J, Mikula A, Bishai W, Jacobs WR Jr, Venter JC, Fraser CM. 2002. Whole-genome comparison of Mycobacterium tuberculosis clinical and laboratory strains. J. Bacteriol.184: 5479-5490.
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Evolution rap: 3.5* til infinity #music
Well, after a rough day I am in need of some lightness. And thanks to Eric Lowe, an undergrad. working in my lab, I got a giggle out of this:
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Elaine Mardis rocks: nice talk on "Next generation sequencing"
I wish I had seen this before I gave my first lecture on Next Gen Sequencing Methods on Monday. I will post mine later but here is a really really nice talk by Elaine Mardis from Washington University on the same topic:
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Diabetes & H.pylori – a correlation but no known causation despite authors claims
Am having a hard time right now with the comments from the authors of this new paper showing a correlation between H. pylori presence and both type II diabetes and blood glucose levels. As far as I can tell, the paper does not show any causal connection. That is, they do not determine if H. pylori infection is a cause of blood sugar issues or a consequence of blood sugar issues.
Yet the authors of the paper, one of whom (Martin Blaser) is a very respected H. pylori expert are saying things like
“This study provides further evidence of late-in-life cost to having H. pylori,”
And they suggest that antibiotic treatment for the elderly may help prevent diabetes.
This to be seems to be a bit over the top. Yes, it makes sense that H. pylori could cause these issues. And they have a model for how it might. But they really should be more careful with their words until a causal connection is established. After all, we have many well known negative effects of antibiotic overuse, including some shown by Blaser. The last thing we need is people going out and dosing up on antibiotics in the hope that it will prevent type II diabetes. But I can guarantee that is what will happen if this story gets overplayed.
At least a few sources report on the lack of anything showing a causal connection (e.g. see US News and World Report):
An expert not involved with the study said that while it did not show a cause-and-effect relationship between the bacterium and diabetes, the findings suggest certain possibilities
But I am worried that that is not enough skepticism to counteract the claims of the authors here. The study is certainly interesting. And their model for a causal connection is fine. But they probably need to do a little bit of toning down of their claims here.
UPDATE: 3/17/13
After some people asked me questions about this study at a few recent meetings I dug a little deeper. And I am a bit startled to find out what the basis is for Chen and Blaser to claim a causative association between H. pylori and type II diabetes/ glucose levels. Here is a summary of their logic:
Helicobacter pylori is acquired almost exclusively in childhood [8], and there is no clear mechanism for how glucose intolerance present only after the age of 18 would increase risk of H. pylori colonization. It also is unlikely that H. pylori positivity and high levels of HbA1c levels share a mutual antecedent cause because there is no diathesis to both acquire H. pylori and to cause glucose intolerance.
They go on to discuss other lines of indirect evidence for why they think their conclusion is correct. And some of this is very suggestive. But “likely” and “suggestive” is not proof. There are many possible issues with their conclusion. In particular I think it is easy to come up with a scenario whereby something about the host (either their genetics or their history of exposure or even their micro biome) could influence both whether or not they get colonized by H. pylori or even whether or not they get colonized by particular strains of HP. And the same factor could influence microbiome interactions later in life. I see no evidence to indicate that H. pylori is the causative agent here. And for them to then basically recommend prophylactic antibiotics for elderly with HP seems dangerous at best.
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California Breast Cancer Research Fund Tax Checkoff; wondering about Open Access policies
Just got this email below about what seems to be a worth cause:
March 8, 2012
Dear UC Colleagues, Throughout California and UC, researchers are developing new approaches to prevent, treat and cure cancer. I am writing you to share important information with those of you who will soon file your California state tax return. At the end of California Tax form 540, there is a section in which you can donate to two highly regarded cancer research programs that are administered by the UC Office of the President.
If you go to line 405, you can contribute to the California Breast Cancer Research Fund and if you go to line 413, you can contribute to the California Cancer Research Fund.
No contribution is too small, and 95 percent of contributions to these two programs via this tax check-off go directly to cancer research or community-based education.
Donations from line 405 go to our California Breast Cancer Research Program, which is renowned not only for its cutting-edge research, but also for working with community advocates and health care providers in targeting the issues and needs of patients and families, especially the underserved.
In recent years, donations from line 405 have supported critical research including: identifying environmental factors that potentially cause breast cancer; developing targeted therapies to block breast cancer from spreading to other organs; and improving support networks to empower patients as they maneuver the health care system. See this website for more information: http://cabreastcancer.org/taxcheckoff/
Donations to line 413 go to the California Cancer Research Fund, which is helping to provide prevention and awareness programs in communities disproportionately affected by cancer. One major ongoing project is increasing the understanding of the impact of tobacco use and cancer on vulnerable populations. This research could lead to reduced smoking, increased cancer awareness and strengthened prevention programs.
I wanted to be sure you were aware of this means of investing in research that can serve all Californians and our communities.
Sincerely,
Lawrence Pitts, M.D. Provost and Executive Vice President University of California, Office of the President
However, I wonder about the open access requirements of the fund. I sniffer around at their web site http://cbcrp.org/about/ and could not find anything about guaranteeing access to the results of the work supported by this fund. That is too bad – this seems to be a great case where openness could be both a good thing and a useful marketing tool (to get people to chip in money from their taxes).
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Not sure what to make of this new "Datasets.Com" effort from Hindawi
Just got this email and I thought I would share. Not sure what to make of this effort. I do support the sharing of data sets but I am think we probably do not need a whole new cadre of data journals to handle this data.
But there is a spread of what some have called “Predatory” open access publishers (see http://metadata.posterous.com/83235355 for example). Hindawi, who is behind this, seems to have a mix of good and predatory tendencies and this seems like it may fit into the more predatory categorization. And I just thought it would be good to bring this a bit more into the open to discuss it.
Dear Dr. Eisen,My name is Safa Tahoon and I am a Journal Developer for the Hindawi Publishing Corporation. We are in the process of launching a new peer-reviewed, open access journal titled Dataset Papers in Genetics, which will publish Dataset Papers in all areas of genetics research, and I am writing to invite you to join the Editorial Board of this new journal.
Dataset Papers in Genetics is part of a new journal platform that Hindawi is developing called Datasets International (http://www.datasets.com). The main objective of Datasets International is to help researchers in all academic disciplines archive, document, and distribute the datasets produced in their research to the entire academic community. In addition to publishing a series of journals devoted to the dissemination of Dataset Papers, Datasets International hosts the underlying data behind these Dataset Papers and makes it accessible to all researchers worldwide.
The journal will be run using a collaborative editorial model which is designed to provide a fast peer review process for all submitted manuscripts. The journal will be edited by a distributed Editorial Board, and it aims for an average review time of 4 weeks from submission until a final decision has been reached.
Manuscripts that are submitted to the journal will be sent to a number of Editorial Board Members (typically each manuscript will be sent to at least 5 Editors), who will have two weeks to provide either a recommendation for the publication of the manuscript, along with a written commentary detailing any improvements that the authors should make to their manuscript, or a written critique of why the manuscript should not be published.
After the two-week period has elapsed, if the majority of the editorial evaluations recommend the manuscript be rejected, the manuscript will be rejected. If all the editorial evaluations that are received recommend that the manuscript be accepted for publication, the manuscript will be accepted. Otherwise, the editorial evaluations will be anonymously communicated to all of the Editors who participated in the peer review process. Each Editor will be given an additional week to review the feedback of the other Editors and to either confirm or revise their earlier editorial recommendations. If the majority of the editorial evaluations that are received by the end of this second round of review recommend the manuscript be accepted for publication, the manuscript will be accepted. Otherwise, the manuscript will be rejected. If the manuscript is accepted for publication, the names of the Editors who recommended the publication of the manuscript will be published alongside the ma!
nuscript. More information on the journal is available on the following web pages:http://www.datasets.com/ (Datasets International Home Page)
http://www.datasets.com/journals/genetics/ (Journal Home Page)
http://www.datasets.com/journals/genetics/workflow/ (Editorial Workflow)
http://www.datasets.com/journals/genetics/editors/ (Editorial Board)The journal will be published using an open access model, which allows disseminating scholarly articles by removing the access barriers imposed by the subscription model, in order to make the full-text of all published articles freely available for any interested reader. In this model the publication costs of an article are covered in the form of Article Processing Charges, which are publication fees paid from the research budget of accepted authors. In this model authors retain the copyright of their work, and we make every possible effort to ensure that the full-text of every published article is both visible and accessible to all potential readers.
Manuscripts that are submitted by the members of the Editorial Board of Dataset Papers in Genetics to the journal will automatically receive a 50% reduction in their Article Processing Charges.
Please do visit the web pages above and let me know if you have any questions or comments. We hope you will accept to join the Editorial Board of the journal and I will be looking forward to hearing from you soon.
Best regards,
Safa Tahoon
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Safa Tahoon
Journal Developer
Hindawi Publishing Corporation
http://www.hindawi.com/
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Jonathan Eisen's Lab 