where they leave a carefully hidden note that says they basically just copied the article verbatim from a university press release (e.g. see Science Daily and other related sites).
I don't know where that 34% figure comes from for the manual double checking. The test set contains about 60% vandalism and 40% real edits, so I'll assume this represents the rate of vandalism on wikipedia. Now, consider a set of 1000 edits. 600 would be vandalism while 400 would be real edits. The second filter would catch 570 instances of real vandalism along with 120 false positives. Even if you used the first filter to automatically remove the 120 instances of vandalism it finds, you would still be left with a set of 450 instances of vandalism + 120 false positives to check. This means that you would have to sort through about 57% of the original edits in order to identify the 120 false positives.
X-ray crystallography usually requires carefully prepared and concentrated proteins. By treating them with chemicals not normally found in their natural environment, it is possible to induce atypical behavior and structures. In fact, crystallography literally demands that the proteins become static, which is not their normal behavior. In comparison, cryo-EM literally freezes a protein sample instantly from whatever conformation it was in. Maybe it won't be possible to get good data out of it, but the structure you have frozen will probably be a more relevant one, closer to what it truly would be in nature.
These are all good points, especially the point that cryo-EM helps avoid artifacts induced by crystal packing. However, I'm not sure cryo-EM helps with the issue of conformational flexibility of these large complexes. Even though the cryo-EM samples will freeze the sample in whatever conformation it was in, the single particle reconstruction methods used to analyze the EM data will average over the conformational heterogeneity, so you would end up losing most of that information in your final structure anyway. The same averaging over conformational heterogeneity occurs in crystallography except in the data acquisition step instead of the data analysis step. While it is in principle possible to sort out the different conformers in your sample during image classification, this is very difficult to do (because the cryo-EM images have such poor resolution and low contrast) and would likely only catch very large structural rearrangements.
The Aug 27 issue of Science, in which the x-ray crystallography study from Scripps appears, actually pubished two papers that describe the structure of adenovirus. The two papers use different techniques to achieve the same ends: the study from the researchers at Scripps grew crystals of the virus and studdied the x-ray diffraction patterns to deduce the structure of the virus. The other paper, done in collaboration between researches at UCLA and Xiangtan University in China, used a technique called cryo-electron microscopy. In this technique, the researchers freeze samples of the virus and use an electron microscope to take tens of thousands of pictures of different viruses within their samples. Although the pictures only give 2D projections of the virus structure, the individual electron microscopy images show the virus from different perspectives. By computationally aligning the images, they can reconstruct the 3 dimensional structure of the virus from the many 2D images taken. While this technique avoids the inherent difficulties of producing crystals (a process that can take decades for some samples), until very recently it has been difficult to achieve high resolution structures using this method. The cryo-EM adenovirus structure is one of only a handful of atomic resolution cryo-EM structures that have been solved to date.
While both studies are very informative and represent scientific tours de force for their respective techniques, it is interesting that the Medical Daily focuses only on the x-ray crystallography study from Scripps. Indeed, in a commentary published by Science that accompanies the articles, Prof. Stephen Harrison of Harvard Medical School (the first person to describe the full structure of a virus) writes that, "Indeed, the cryo-EM density map of Liu et al. appears to be substantially clearer and more interpretable than the x-ray density map of Reddy et al." Perhaps Medical Daily needs to do a better job of doing their homework.
In the PNAS paper published by the scientists, they noted that the "healer" strains of mice deficient in the p21 protein showed increased signs of DNA damage. These observations make sense because p21 is a key component of biochemical stress response pathways that, for example, stop a cell from dividing after its DNA has been damaged.
In fact, p21 is one of the proteins that carries out instructions from the infamous p53 protein (the tumor-suppressor protein commonly referred to as the "Guardian of the Genome" that is mutated in over 50% of cancers). So, in terms of applications, disrupting p21 function in order to induce regenerative abilities would be like playing with fire: such a modification would shut down one pathway through which p53 protects cells against cancer. If one were to think of using this knowledge for regenerative medicine, applications where p21 is temporarily disabled (for example, through transient application of RNA interference) would be better than permanently shutting off the gene.
Overall, however, this paper produces some nice evidence pointing to DNA damage as an important mechanism in aging. This is of course known, but it's always nice to see these concepts pop up in fields related to aging.
I agree. At the risk of sounding a bit old fashioned, why do we expect extensive analysis of the text of a bill that came out just five hours prior to this post? Perhaps the lack of sources quoted is simply due to the fact that the article was published before any reporter could contact US government officials for a response? Indeed, at this point I would not expect any good journalism on this topic to be published because good journalists would contact government officials for responses to criticism or answers to questions. Maybe the poster's claim that few reporters are interested in the topic might be valid if there is not significant coverage of the issue by tonight or tomorrow. However, expecting reporters to publish information (let alone analysis) on this issue without giving the reporters time to think deeply about the bill's text and gather responses from officials is unreasonable. This is one of the problems facing our society today; while useful information and news does get disseminated much more quickly and widely than before (a plus), the time pressures of publishing makes this information be based much more on cursory reactions and less on thoughtful analysis.
A good example of how disastrous one error in data analysis code can be comes from the field of biochemistry, specifically analyzing the x-ray diffraction patterns from crystallized proteins to determine the three dimensional structure of the proteins. Geoff Chang, faculty at the prestigious Scripps Research Institute in San Diego, had published a series of landmark papers describing the structures of various important membrane proteins, whose structures had never been solved before. Although these results did not mesh other researchers' models for how these proteins worked, many researchers used Chang's structures as starting points to develop and test new models for how these proteins might work. However, in 2006, things came crashing down:
In September, Swiss researchers published a paper in Nature that cast serious doubt on a protein structure Chang's group had described in a 2001 Science paper. When he investigated, Chang was horrified to discover that a homemade data-analysis program had flipped two columns of data, inverting the electron-density map from which his team had derived the final protein structure. Unfortunately, his group had used the program to analyze data for other proteins. As a result, on page 1875, Chang and his colleagues retract three Science papers and report that two papers in other journals also contain erroneous structures.
(from a Science news article (subscription required to view full article):
Of course, there were other factors that caused this situation (because the proteins are notoriously difficult to work with, the data were fairly poor quality. Had the data quality been better, Chang would have likely realized the mistakes prior to publishing the papers). However, it is sobering to note the resources wasted on research following up on these incorrect structures produced by a simple coding error (I know a few people whose entire theses were invalidated by these retractions).
It is, however, unclear whether releasing the data analysis code would have fixed this situation. The software for analyzing x-ray diffraction data is fairly standard (I don't know why Chang was using his own homemade software) and various open-source software are available. Furthermore, in his field, it is common to release the raw diffraction data (I'm not sure if it was released in the case of these five structures), so it may have been possible for others to double check his work with their own analysis software. Perhaps the greater error here is in Chang, the peer reviewers of his publications, and the scientific community for believing Chang's conclusions (based on relatively poor quality diffraction data) over the conclusions of many other researches whose techniques may not have been as sophisticated, but who had generated data of much higher quality.
That would assume that these large RNAs are non-coding functional RNAs, something not clearly answered one way or the other by the paper. One possiblity is that these RNAs are remanants of viruses that have integrated into the bacteria (indeed the fact that the GOLLD RNA resides in an apparent prophage and is expressed under conditions that promote prophage expression supports this conclusion). Then it might be more appropriate to compare the size to viral genomes which can also be very large, highly structured RNAs. For example, the HIV genome is ~10,000 nucleotides long and is also highly structured.
However, the fact that these RNAs are expressed and conserved in a variety of organisms is a interesting result suggesting that they may have some function. I'm looking forward to seeing whether they can figure out exactly what these RNAs are doing in the bacteria.
You are correct that it is well known that limited diets (i.e. caloric restriction) increase lifespan and also decrease fertility. Many believe the mechanism involves just what you said: in conditions of limited resources, the body shifts resources away from reproduction.
The authors of the study set out to test the hypothesis that the decreased fertility from caloric restriction results from a lack of calories. The authors predicted that if this hypothesis is true, it should not be possible to find nutrient conditions that increase lifespan without decreasing fertility. However, the authors found that they could restore normal fertility levels while maintaining the increased lifespan in calorie restricted flies by adding methionine to the flies' diet. Thus, as the authors state in the paper's abstract: "reallocation of nutrients therefore does not explain the responses to dietary restriction."
Furthermore, they found that it is primarily the lifespan increases in caloric restriction come primarily from restricting amino acids. Adding carbohydrates or fats to the diets of calorie restricted flies did not reduce the increases in lifespan due to calorie restriction. So yes, the summary is completely wrong. Restricting the intake all amino acids except for methionine could increase lifespan (in flies) without harming fertility, not the other way around as the summary implies.
Of course, it's an open question whether any of this applies to humans or whether this fountain of youth works only for fruit flies.
Lee H, McKeon RJ, Bellamkonda RV. Sustained delivery of thermostabilized chABC enhances axonal sprouting and functional recovery after spina chord injury. Proc. Natl. Acad. Sci. USA 2009. doi: 10.1073/pnas.0905437106.
The summary is slightly incorrect in saying that this group discovered that the chondroitinase enzyme can aid in recovery after spinal cord injury (this has been known for a while, see Bradbury et al. (2002) Nature 416:636–640, whom the authors cite). The authors contribution is to engineer a version of the enzyme that is more stable and works better than the natural version of the enzyme. Because the enzyme is more stable than the natural enzyme, the authors can implant a hydrogel at the site of injury that slowly releases the enzyme over the course of two weeks. The authors show that this sustained delivery improves neuron regrowth and the locomotor function of the injured animals compared to just a single dose of the natural enzyme (which degrades relatively quickly after injection).
The research team that produced the paper in Science paper (link (subscription required to see more than the abstract)) described in the science daily writeup also published a paper in Nature (link) that more fully describes their method of creating three dimensional objects out of DNA (the newest paper expands these methods to construct more complicated objects with more precise curvature). Furthermore, they have published the open-source software that they used to design the DNA nanostructures (http://cadnano.org/). I was at a talk by the lead author of the Nature paper who said that, using their software, a high school student was able to design one of the structures they used in the paper as a summer project.
My understanding of the article was that they sequenced DNA -- both strands -- not the RNA. But for reasons I don't understand, Schweitzer said it might be the consequences of RNA editing, to the messenger RNA.
From the paper published in the journal Human Genetics (subscription required), the authors sequenced the mRNA from aortic tissue and genomic DNA from the blood of individuals. To sequence mRNA, researchers must first extract the mRNA from cells and convert the mRNA into a DNA sequence (called complementary DNA or cDNA) using the enzyme Reverse Transcriptase. The reason why we do this is because DNA is much more stable than RNA (our bodies contain many enzymes that rapidly degrade RNA. These enzymes are secreted from our skin, so if you literaly touch an RNA sample it begins to degrade. I know because I work with RNA and it is a pain). Furthermore, sequencing procedures are optimized for sequencing DNA strands, not RNA strands. So, when the article refers to sequencing cDNA, it really means sequencing mRNA (indirectly).
Because the authors of the study looked only at the mRNA from the aortic tissue, they cannot exclude the possibility that the mutations in the mRNA arose from RNA editing, and not somatic mutation. It seems like it would have been fairly simple to sequence the genomic DNA from the aortic tissue, and I'm curious as to why the authors did not perform these analyses (perhaps they knew that other groups had made similar findings and wanted to rush the paper out before others could publish?).
As other readers have noticed, the authors of this study have used existing DNA synthesis technology to incorporate non-natural bases into DNA. While it is impressive that the authors could design bases with the correct geometry to support a DNA-like double helix, the chemistry is not too novel. However, the ability to customize DNA-like polymers has a few interesting applications.
First, all of the sci-fi applications involving artificial life are not really feasible because one would have to design a huge number of new enzymes to recognize these artificial bases. As the field of enzyme design is still in its infancy, I do not see this happening anytime soon.
The real applications come from non-biological uses of DNA. As previous commenter have noted, biotechnologists are investigating the use of DNA as a tool for computation/data storage. Doi et al. have designed their DNA-like scaffold such that other researchers could relatively easily construct new nucleotide pairs in order to expand the number of nucleotides used in the helix. This ability to expand the number of nucleotides could aid researchers in performing calculations using DNA.
Another application involves DNA nanostructures (such as the "DNA origami" designed by Paul Rothemund). DNA is useful for creating nanostructures because it can be easily programmed for self-assembly into arbitrary structures (such as happy faces or long six-helical nanotubes). However, biology is full of enzymes that can degrade DNA, limiting its usefulness. As the authors of this study note, these artificial DNA molecules are resistant to degradation by natural enzymes. Furthermore, it may be possible to alter the mechanical properties of the artificial DNA by tailoring the strength of base-pairing and stacking of the non-natural bases. This could give researchers much greater control over the properties of their DNA nanostructures. One disadvantage of these artificial DNA molecules over natural DNA molecules would be the fact that it is much easier to produce long molecules of natural DNA (the non-enzymatic DNA synthesis technologies used to create the artificial DNA have difficulty creating long [>100bp] strands of DNA). Another caveat is that the authors of the study did not provide a crystal structure of the DNA so we don't yet know its true 3D structure (i.e. whether it forms a helix with the same geometry as regular DNA, although a different geometry could also be interesting).
A real significant advance for DNA nanostructures would be an artificial DNA-like polymer that incorporates a non-natural sugar-phosphate backbone. DNA nanostructures are not stable outside of water which limits their possible applications, in part because water molecules help to stabilize the structure of the sugar-phosphate backbone. Designing a DNA nanostructure that retains its properties outside of water would be a huge boon to the field.
Scientists have been able to design new proteins that can catalyze reactions. In two landmark papers just this year (De Novo Computational Design of Retro-Aldol Enzymes, Science2008319, 1387; Kemp elimination catalysts by computational enzyme design, Nature2008453, 190), David Baker's group at the University of Washington was able to computationally design two entirely new enzymes from scratch. Of course, there's still a lot of work to be done as these enzymes are not nearly as efficient as natural enzymes, but these breakthroughs open up many great possibilities.
Here's a summary describing the results of the Science paper.
My problem with the article is that it doesn't directly examine females' attraction. The study merely looks at how many sexual partners "bad boys" v. "good boys" have. Not surprisingly, the "bad boys," who desire more relationships of shorter duration, have more relationships than the "good boys," who do not desire such promiscuity. So yes, people who seek more sexual relationships have more sexual relationships. That's the duh factor of the article. It's up to future studies to determine whether these bad boys are actually more attractive or desirable to girls.
Slashdot Mirror
You are correct that the site did not correctly format the DOI link, but the research has been published. Here is the correct DOI link doi:10.1038/nature09518. Also, here is the link to the article on the Nature website: http://www.nature.com/nature/journal/vaop/ncurrent/abs/nature09518.html (link probably valid only for the next week or so)
where they leave a carefully hidden note that says they basically just copied the article verbatim from a university press release (e.g. see Science Daily and other related sites).
Thank you two for the clarification. I should really read the links more thoroughly before posting.
I don't know where that 34% figure comes from for the manual double checking. The test set contains about 60% vandalism and 40% real edits, so I'll assume this represents the rate of vandalism on wikipedia. Now, consider a set of 1000 edits. 600 would be vandalism while 400 would be real edits. The second filter would catch 570 instances of real vandalism along with 120 false positives. Even if you used the first filter to automatically remove the 120 instances of vandalism it finds, you would still be left with a set of 450 instances of vandalism + 120 false positives to check. This means that you would have to sort through about 57% of the original edits in order to identify the 120 false positives.
X-ray crystallography usually requires carefully prepared and concentrated proteins. By treating them with chemicals not normally found in their natural environment, it is possible to induce atypical behavior and structures. In fact, crystallography literally demands that the proteins become static, which is not their normal behavior. In comparison, cryo-EM literally freezes a protein sample instantly from whatever conformation it was in. Maybe it won't be possible to get good data out of it, but the structure you have frozen will probably be a more relevant one, closer to what it truly would be in nature.
These are all good points, especially the point that cryo-EM helps avoid artifacts induced by crystal packing. However, I'm not sure cryo-EM helps with the issue of conformational flexibility of these large complexes. Even though the cryo-EM samples will freeze the sample in whatever conformation it was in, the single particle reconstruction methods used to analyze the EM data will average over the conformational heterogeneity, so you would end up losing most of that information in your final structure anyway. The same averaging over conformational heterogeneity occurs in crystallography except in the data acquisition step instead of the data analysis step. While it is in principle possible to sort out the different conformers in your sample during image classification, this is very difficult to do (because the cryo-EM images have such poor resolution and low contrast) and would likely only catch very large structural rearrangements.
The Aug 27 issue of Science, in which the x-ray crystallography study from Scripps appears, actually pubished two papers that describe the structure of adenovirus. The two papers use different techniques to achieve the same ends: the study from the researchers at Scripps grew crystals of the virus and studdied the x-ray diffraction patterns to deduce the structure of the virus. The other paper, done in collaboration between researches at UCLA and Xiangtan University in China, used a technique called cryo-electron microscopy. In this technique, the researchers freeze samples of the virus and use an electron microscope to take tens of thousands of pictures of different viruses within their samples. Although the pictures only give 2D projections of the virus structure, the individual electron microscopy images show the virus from different perspectives. By computationally aligning the images, they can reconstruct the 3 dimensional structure of the virus from the many 2D images taken. While this technique avoids the inherent difficulties of producing crystals (a process that can take decades for some samples), until very recently it has been difficult to achieve high resolution structures using this method. The cryo-EM adenovirus structure is one of only a handful of atomic resolution cryo-EM structures that have been solved to date.
While both studies are very informative and represent scientific tours de force for their respective techniques, it is interesting that the Medical Daily focuses only on the x-ray crystallography study from Scripps. Indeed, in a commentary published by Science that accompanies the articles, Prof. Stephen Harrison of Harvard Medical School (the first person to describe the full structure of a virus) writes that, "Indeed, the cryo-EM density map of Liu et al. appears to be substantially clearer and more interpretable than the x-ray density map of Reddy et al." Perhaps Medical Daily needs to do a better job of doing their homework.
The cryo-EM study is available at the following link (subscription required): http://www.sciencemag.org/cgi/content/abstract/329/5995/1038
In the PNAS paper published by the scientists, they noted that the "healer" strains of mice deficient in the p21 protein showed increased signs of DNA damage. These observations make sense because p21 is a key component of biochemical stress response pathways that, for example, stop a cell from dividing after its DNA has been damaged.
In fact, p21 is one of the proteins that carries out instructions from the infamous p53 protein (the tumor-suppressor protein commonly referred to as the "Guardian of the Genome" that is mutated in over 50% of cancers). So, in terms of applications, disrupting p21 function in order to induce regenerative abilities would be like playing with fire: such a modification would shut down one pathway through which p53 protects cells against cancer. If one were to think of using this knowledge for regenerative medicine, applications where p21 is temporarily disabled (for example, through transient application of RNA interference) would be better than permanently shutting off the gene.
Overall, however, this paper produces some nice evidence pointing to DNA damage as an important mechanism in aging. This is of course known, but it's always nice to see these concepts pop up in fields related to aging.
I agree. At the risk of sounding a bit old fashioned, why do we expect extensive analysis of the text of a bill that came out just five hours prior to this post? Perhaps the lack of sources quoted is simply due to the fact that the article was published before any reporter could contact US government officials for a response? Indeed, at this point I would not expect any good journalism on this topic to be published because good journalists would contact government officials for responses to criticism or answers to questions. Maybe the poster's claim that few reporters are interested in the topic might be valid if there is not significant coverage of the issue by tonight or tomorrow. However, expecting reporters to publish information (let alone analysis) on this issue without giving the reporters time to think deeply about the bill's text and gather responses from officials is unreasonable. This is one of the problems facing our society today; while useful information and news does get disseminated much more quickly and widely than before (a plus), the time pressures of publishing makes this information be based much more on cursory reactions and less on thoughtful analysis.
A good example of how disastrous one error in data analysis code can be comes from the field of biochemistry, specifically analyzing the x-ray diffraction patterns from crystallized proteins to determine the three dimensional structure of the proteins. Geoff Chang, faculty at the prestigious Scripps Research Institute in San Diego, had published a series of landmark papers describing the structures of various important membrane proteins, whose structures had never been solved before. Although these results did not mesh other researchers' models for how these proteins worked, many researchers used Chang's structures as starting points to develop and test new models for how these proteins might work. However, in 2006, things came crashing down:
In September, Swiss researchers published a paper in Nature that cast serious doubt on a protein structure Chang's group had described in a 2001 Science paper. When he investigated, Chang was horrified to discover that a homemade data-analysis program had flipped two columns of data, inverting the electron-density map from which his team had derived the final protein structure. Unfortunately, his group had used the program to analyze data for other proteins. As a result, on page 1875, Chang and his colleagues retract three Science papers and report that two papers in other journals also contain erroneous structures.
(from a Science news article (subscription required to view full article):
Of course, there were other factors that caused this situation (because the proteins are notoriously difficult to work with, the data were fairly poor quality. Had the data quality been better, Chang would have likely realized the mistakes prior to publishing the papers). However, it is sobering to note the resources wasted on research following up on these incorrect structures produced by a simple coding error (I know a few people whose entire theses were invalidated by these retractions).
It is, however, unclear whether releasing the data analysis code would have fixed this situation. The software for analyzing x-ray diffraction data is fairly standard (I don't know why Chang was using his own homemade software) and various open-source software are available. Furthermore, in his field, it is common to release the raw diffraction data (I'm not sure if it was released in the case of these five structures), so it may have been possible for others to double check his work with their own analysis software. Perhaps the greater error here is in Chang, the peer reviewers of his publications, and the scientific community for believing Chang's conclusions (based on relatively poor quality diffraction data) over the conclusions of many other researches whose techniques may not have been as sophisticated, but who had generated data of much higher quality.
That would assume that these large RNAs are non-coding functional RNAs, something not clearly answered one way or the other by the paper. One possiblity is that these RNAs are remanants of viruses that have integrated into the bacteria (indeed the fact that the GOLLD RNA resides in an apparent prophage and is expressed under conditions that promote prophage expression supports this conclusion). Then it might be more appropriate to compare the size to viral genomes which can also be very large, highly structured RNAs. For example, the HIV genome is ~10,000 nucleotides long and is also highly structured.
However, the fact that these RNAs are expressed and conserved in a variety of organisms is a interesting result suggesting that they may have some function. I'm looking forward to seeing whether they can figure out exactly what these RNAs are doing in the bacteria.
You are correct that it is well known that limited diets (i.e. caloric restriction) increase lifespan and also decrease fertility. Many believe the mechanism involves just what you said: in conditions of limited resources, the body shifts resources away from reproduction.
The authors of the study set out to test the hypothesis that the decreased fertility from caloric restriction results from a lack of calories. The authors predicted that if this hypothesis is true, it should not be possible to find nutrient conditions that increase lifespan without decreasing fertility. However, the authors found that they could restore normal fertility levels while maintaining the increased lifespan in calorie restricted flies by adding methionine to the flies' diet. Thus, as the authors state in the paper's abstract: "reallocation of nutrients therefore does not explain the responses to dietary restriction."
Furthermore, they found that it is primarily the lifespan increases in caloric restriction come primarily from restricting amino acids. Adding carbohydrates or fats to the diets of calorie restricted flies did not reduce the increases in lifespan due to calorie restriction. So yes, the summary is completely wrong. Restricting the intake all amino acids except for methionine could increase lifespan (in flies) without harming fertility, not the other way around as the summary implies.
Of course, it's an open question whether any of this applies to humans or whether this fountain of youth works only for fruit flies.
Here's the actual research paper being cited:
Lee H, McKeon RJ, Bellamkonda RV. Sustained delivery of thermostabilized chABC enhances axonal sprouting and functional recovery after spina chord injury. Proc. Natl. Acad. Sci. USA 2009. doi: 10.1073/pnas.0905437106.
The summary is slightly incorrect in saying that this group discovered that the chondroitinase enzyme can aid in recovery after spinal cord injury (this has been known for a while, see Bradbury et al. (2002) Nature 416:636–640, whom the authors cite). The authors contribution is to engineer a version of the enzyme that is more stable and works better than the natural version of the enzyme. Because the enzyme is more stable than the natural enzyme, the authors can implant a hydrogel at the site of injury that slowly releases the enzyme over the course of two weeks. The authors show that this sustained delivery improves neuron regrowth and the locomotor function of the injured animals compared to just a single dose of the natural enzyme (which degrades relatively quickly after injection).
The research team that produced the paper in Science paper (link (subscription required to see more than the abstract)) described in the science daily writeup also published a paper in Nature (link) that more fully describes their method of creating three dimensional objects out of DNA (the newest paper expands these methods to construct more complicated objects with more precise curvature). Furthermore, they have published the open-source software that they used to design the DNA nanostructures (http://cadnano.org/). I was at a talk by the lead author of the Nature paper who said that, using their software, a high school student was able to design one of the structures they used in the paper as a summer project.
My understanding of the article was that they sequenced DNA -- both strands -- not the RNA. But for reasons I don't understand, Schweitzer said it might be the consequences of RNA editing, to the messenger RNA.
From the paper published in the journal Human Genetics (subscription required), the authors sequenced the mRNA from aortic tissue and genomic DNA from the blood of individuals. To sequence mRNA, researchers must first extract the mRNA from cells and convert the mRNA into a DNA sequence (called complementary DNA or cDNA) using the enzyme Reverse Transcriptase. The reason why we do this is because DNA is much more stable than RNA (our bodies contain many enzymes that rapidly degrade RNA. These enzymes are secreted from our skin, so if you literaly touch an RNA sample it begins to degrade. I know because I work with RNA and it is a pain). Furthermore, sequencing procedures are optimized for sequencing DNA strands, not RNA strands. So, when the article refers to sequencing cDNA, it really means sequencing mRNA (indirectly).
Because the authors of the study looked only at the mRNA from the aortic tissue, they cannot exclude the possibility that the mutations in the mRNA arose from RNA editing, and not somatic mutation. It seems like it would have been fairly simple to sequence the genomic DNA from the aortic tissue, and I'm curious as to why the authors did not perform these analyses (perhaps they knew that other groups had made similar findings and wanted to rush the paper out before others could publish?).
As other readers have noticed, the authors of this study have used existing DNA synthesis technology to incorporate non-natural bases into DNA. While it is impressive that the authors could design bases with the correct geometry to support a DNA-like double helix, the chemistry is not too novel. However, the ability to customize DNA-like polymers has a few interesting applications.
First, all of the sci-fi applications involving artificial life are not really feasible because one would have to design a huge number of new enzymes to recognize these artificial bases. As the field of enzyme design is still in its infancy, I do not see this happening anytime soon.
The real applications come from non-biological uses of DNA. As previous commenter have noted, biotechnologists are investigating the use of DNA as a tool for computation/data storage. Doi et al. have designed their DNA-like scaffold such that other researchers could relatively easily construct new nucleotide pairs in order to expand the number of nucleotides used in the helix. This ability to expand the number of nucleotides could aid researchers in performing calculations using DNA.
Another application involves DNA nanostructures (such as the "DNA origami" designed by Paul Rothemund). DNA is useful for creating nanostructures because it can be easily programmed for self-assembly into arbitrary structures (such as happy faces or long six-helical nanotubes). However, biology is full of enzymes that can degrade DNA, limiting its usefulness. As the authors of this study note, these artificial DNA molecules are resistant to degradation by natural enzymes. Furthermore, it may be possible to alter the mechanical properties of the artificial DNA by tailoring the strength of base-pairing and stacking of the non-natural bases. This could give researchers much greater control over the properties of their DNA nanostructures. One disadvantage of these artificial DNA molecules over natural DNA molecules would be the fact that it is much easier to produce long molecules of natural DNA (the non-enzymatic DNA synthesis technologies used to create the artificial DNA have difficulty creating long [>100bp] strands of DNA). Another caveat is that the authors of the study did not provide a crystal structure of the DNA so we don't yet know its true 3D structure (i.e. whether it forms a helix with the same geometry as regular DNA, although a different geometry could also be interesting).
A real significant advance for DNA nanostructures would be an artificial DNA-like polymer that incorporates a non-natural sugar-phosphate backbone. DNA nanostructures are not stable outside of water which limits their possible applications, in part because water molecules help to stabilize the structure of the sugar-phosphate backbone. Designing a DNA nanostructure that retains its properties outside of water would be a huge boon to the field.
Scientists have been able to design new proteins that can catalyze reactions. In two landmark papers just this year (De Novo Computational Design of Retro-Aldol Enzymes, Science 2008 319, 1387; Kemp elimination catalysts by computational enzyme design, Nature 2008 453, 190), David Baker's group at the University of Washington was able to computationally design two entirely new enzymes from scratch. Of course, there's still a lot of work to be done as these enzymes are not nearly as efficient as natural enzymes, but these breakthroughs open up many great possibilities. Here's a summary describing the results of the Science paper.
My problem with the article is that it doesn't directly examine females' attraction. The study merely looks at how many sexual partners "bad boys" v. "good boys" have. Not surprisingly, the "bad boys," who desire more relationships of shorter duration, have more relationships than the "good boys," who do not desire such promiscuity. So yes, people who seek more sexual relationships have more sexual relationships. That's the duh factor of the article. It's up to future studies to determine whether these bad boys are actually more attractive or desirable to girls.