NCSE tells us,
April 18-25, 2015, is the inaugural Climate Education Week, sponsored by Earth Day Network. To celebrate, the Climate Education Week website is providing K-12 educators with the Climate Education Toolkit – “a free, easy-to-use, ready-to-go resource with everything you need. The Toolkit includes a week’s worth of lesson plans, activities, and contests for K-12 students that meet Next Generation Science Standards and Common Core. Each day covers a different theme related to climate change with two highlighted activities handpicked by Earth Day Network for your use.” There are videos, contests, a downloadable Earth Day poster, and even an interactive on-line textbook for middle school students – all aimed at helping to promote climate education!
You may find NCSE’s resources on climate science and climate education on their Website.
What do Charles Darwin, wisdom teeth, and cancer have in common? They are all related to an emerging field called evolutionary medicine, the application of evolutionary principles to understanding why and how organisms get sick. Scientists in the field believe that an evolutionary perspective can help improve our diagnosis and treatment of disease.
In his keynote address at the inaugural meeting of the International Society for Evolution, Medicine, and Public Health (held March 19-21 in Tempe, AZ), Dr. Harvey Fineberg stated that an understanding of evolution is central to health. Fineberg, the former Dean of the Harvard School of Public Health, argued that an evolutionary viewpoint is necessary to explain structures and functions of the human body (like the fact that wisdom teeth were helpful in some way to our ancestors but serve no purpose now) and evolution can provide insight into diseases that develop and spread under evolutionary mechanisms, like infectious disease and cancer.
Antimicrobial resistance occurs when bacteria, viruses, and other infection-causing microorganisms evolve and develop mutations that enable them to resist drug therapies. Drug-resistant bacteria alone affect over two million Americans each year, according to the CDC. The process of microbial evolution follows the guiding principles of natural selection, so scientists can use their knowledge of evolution to understand how microbes attain resistance and perhaps even prevent it. For example, the current methods of treating bacterial infections target a mechanism of mutation called de novo mutation, but scientists have learned that antibiotic resistance mostly develops from a different method called horizontal gene transfer (Sterns, 2012), which suggests that we may need new therapies for bacterial infection.
Bacteria, like the mycobacteria above that cause tuberculosis, develop drug resistances by evolving and mutating under the influence of natural selection, just like all other organisms. Image source: CDC
Evolutionary medicine has also started to play a role in cancer research. Some scientists are using an evolutionary background to understand how cancers develop, spread, and metastasize as well as to find effective treatments. For instance, a group of scientists is trying to understand how large animals with long lifespans, like the blue whale, have evolved and developed cancer suppression techniques that are reportedly 1000 times better than those of humans. Many hypotheses attempting to explain this phenomenon exist: the lower metabolic rate of large animals might lead to a lower mutation rate, or perhaps tumors are so much bigger in large animals that they are actually less likely to become malignant than smaller tumors (Nagy et. al., 2007). Whatever the explanation, understanding why and how large animals evolved to gain such effective tumor suppressor mechanisms could provide new therapies for cancer in humans. (Caulin and Maley, 2012.)
Additionally, studying deviations from physiological homeostasis in an evolutionary light may suggest that we need to make changes in how we treat some conditions. As Dr. Joe Alcock of the University of New Mexico commented at the ISEMPH meeting, what is defined as “normal” for the human body may be different depending on the conditions. For instance, doctors typically test patients for normal levels of hemoglobin (the molecule that transports oxygen in the blood) and glucose. But evolution has led some populations to adapt to unique environments and develop abnormal levels of these molecules; those living at higher altitudes are found to have a higher base level of hemoglobin than normal, pregnant women exhibit lower concentrations of hemoglobin as an adaptation to pregnancy, and patients with sepsis, a severe complication of infection, have elevated glucose levels, which may be an adaptive survival response. When doctors detect these abnormal glucose and hemoglobin levels, they will often treat the patients to return them to normal; however, Alcock argues that trying to restore every patient to one standard level may in fact do more harm than good if deviation from normalcy has an adaptive purpose.
The growth in the field of evolutionary biology, along with the sharp decline in genome-sequencing costs, has led to a new discipline of treating and diagnosing diseases called phylomedicine (Kumar et. al., 2011). Studying the differences between genomic information of healthy and diseased people, scientists have discovered many genetic diseases and the DNA variations associated with them. For example, mutations in the ALDH1L1 gene are associated with an increased risk of stroke (Williams et. al., 2014). However, simply analyzing individual genomes to discover the variations linked with certain diseases is inefficient and produces an extremely high volume of data, not all of which are significant. Instead, scientists can combine this analysis with a multi-species evolutionary perspective to narrow down the list and determine which genetic markers are associated with disease. Once these markers, like the ALDH1L1 gene, are identified, we can use them for diagnosis and as potential therapeutic targets.
Evolutionary principles can give insight into a wide range of medical topics: besides cancer and infectious disease, evolutionary thinking has shed light on other diseases like jaundice, influenza, and mental disorders (Nesse and Stearns, 2008). Also, studying the timeline of animal evolution and trait development can tell us which animals are most accurate models of human physiology for drug and device preclinical testing.
Members of the discipline see evolutionary medicine as having the potential to revolutionize the way we think about medicine. Adopting a new, evolutionary viewpoint on some of our most complex diseases could greatly benefit patients.
In our next post, we’ll go into more detail about a specific clinical application of evolutionary medicine. Is there a topic you’d like to hear more about? Let us know in the comments section.
This series is supported by NSF Grant #DBI-1356548 to RA Cartwright.
Eudyptula Minor – little penguin, Kangaroo Island, Australia. These penguins are nocturnal, but are apparently blind to the red light. Unfortunately, according to Kangaroo Island Penguin Center, “Our nocturnal Penguin Tours ceased in November 2013 due to the very low numbers of Penguins in the Kingscote colony. Predation by the increasing numbers of New Zealand Fur Seals from 2010 onwards has decimated the Penguin Colony, because the seals kill the adult penguins as they swim ashore at night to feed their chicks and therefore the chicks also die. We apologise for this, but the situation has been beyond our control.”
This post is by Joe Felsenstein and Tom English
Back in October, one of us (JF) commented at Panda’s Thumb on William Dembski’s seminar presentation at the University of Chicago, Conservation of Information in Evolutionary Search. In his reply at the Discovery Institute’s Evolution News and Views blog, Dembski pointed out that he had referred to three of his own papers, and that Joe had mentioned only two. He generously characterized Joe’s post as an “argument by misdirection”, the sort of thing magicians do when they are deliberately trying to fool you. (Thanks, how kind).
Dembski is right that Joe did not cite his most recent paper, and that he should have. The paper, “A General Theory of Information Cost Incurred by Successful Search”, by Dembski, Winston Ewert, and Robert J. Marks II (henceforth DEM), defines search differently than do the other papers. However, it does not jibe with the “Seven Components of Search” slide of the presentation (details here). One of us (TE) asked Dembski for technical clarification. He responded only that he simplified for the talk, and stands by the approach of DEM.
Whatever our skills at prestidigitation, we will not try to untangle the differences between the talk and the DEM paper. Rather than guess how Dembski simplified, we will regard the DEM paper as his authoritative source. Studying that paper, we found that:
They address “search” in a space of points. To make this less abstract, and to have an example for discussing evolution, we assume a space of possible genotypes. For example, we may have a stretch of 1000 bases of DNA in a haploid organism, so that the points in the space are all 41000 possible sequences.
A “search” generates a sequence of genotypes, and then chooses one of them as the final result. The process is random to some degree, so each genotype has a probability of being the outcome. DEM ultimately describe the search in terms of its results, as a probability distribution on the space of genotypes.
A set of genotypes is designated the “target”. A “search” is said to succeed when its outcome is in the target. Because the outcome is random, the search has some probability of success.
DEM assume that there is a baseline “search” that does not favor any particular “target”. For our space of genotypes, the baseline search generates all outcomes with equal probability. DEM in fact note that on average over all possible searches, the probability of success is the same as if we simply drew randomly (uniformly) from the space of genotypes.
They calculate the “active information” of a “search” by taking the ratio of its probability of success to that of the baseline search, and then taking the logarithm of the ratio. The logarithm is not essential to their argument.
Contrary to what Joe said in his previous post, DEM do not explicitly consider all possible fitness surfaces. He was certainly wrong about that. But as we will show, the situation is even worse than he thought. There are “searches” that go downhill on the fitness surface, ones that go sideways, and ones that pay no attention at all to fitnesses.
If we make a simplified model of a “greedy” uphill-climbing algorithm that looks at the neighboring genotypes in the space, and which prefers to move to a nearby genotype if that genotype has higher fitness than the current one, its search will do a lot better than the baseline search, and thus a lot better than the average over all possible searches. Such processes will be in an extremely small fraction of all of DEM’s possible searches, the small fraction that does a lot better than picking a genotype at random.
So just by having genotypes that have different fitnesses, evolutionary processes will do considerably better than random choice, and will be considered by DEM to use substantial values of Active Information. That is simply a result of having fitnesses, and does not require that a Designer choose the fitness surface. This shows that even a search which is evolution on a white-noise fitness surface is very special by DEM’s standards.
Searches that are like real evolutionary processes do have fitness surfaces. Furthermore, these fitness surfaces are smoother than white-noise surfaces “because physics”. That too increases the probability of success, and by a large amount.
Arguing whether a Designer has acted by setting up the laws of physics themselves is an argument one should have with cosmologists, not with biologists. Evolutionary biologists are concerned with how an evolving system will behave in our present universe, with the laws of physics that we have now. These predispose to fitness surfaces substantially smoother than white-noise surfaces.
Although moving uphill on a fitness surface is helpful to the organism, evolution is not actually a search for a particular small set of target genotypes; it is not only successful when it finds the absolutely most-fit genotypes in the space. We almost certainly do not reach optimal genotypes or phenotypes, and that’s OK. Evolution may not have made us optimal, but it has at least made us fit enough to survive and flourish, and smart enough to be capable of evaluating DEM’s arguments, and seeing that they do not make a case that evolution is a search actively chosen by a Designer.
This is the essence of our argument. It is a lot to consider, so let’s explain this in more detail below:
As usual I will pa-troll the comments, and send off-topic stuff by our usual trolls and replies to their off-topic stuff to the Bathroom Wall
Tom Loftus reports in the Louisville Courier-Journal that Gov. Steve Beshear has asked a federal court to dismiss the Ark Park’s lawsuit on the grounds that “[p]roviding the public funding sought for religious purposes …would constitute an unlawful establishment of religion” and thereby violate both the state and federal constitutions. Governor Beshear and his co-plaintiff, state Treasurer Bob Stewart, told the Courier-Journal that “the state’s denial of public funds for the ark park [sic] ‘reflects no hostility toward Plaintiffs’ faith’ and does not prohibit Answers in Genesis and its affiliated organizations from following their religious beliefs.”
Update, March 31, 2015: Americans United for the Separation of Church and State has submitted a motion to intervene on behalf of four Kentucky taxpayers to “prevent taxpayer dollars from being used to unconstitutionally finance a religious ministry.” According to a press release, the taxpayers argue “that ‘[t]he tax rebates sought for Ark Encounter would effectively compel me, as a Kentucky taxpayer, to subsidize a religious ministry against my will.’” Two of the taxpayers are Christian ministers. AU has also submitted a proposed motion to dismiss, which I take it becomes active if the motion to intervene is granted.
A pair of recent articles on the Science website seems to think so. Staff writer Robert Service says Researchers may have solved origin-of-life conundrum and writes,
Chemists report today that a pair of simple compounds [HCN and H2S], which would have been abundant on early Earth, can give rise to a network of simple reactions that produce the three major classes of biomolecules—nucleic acids, amino acids, and lipids—needed for the earliest form of life to get its start. Although the new work does not prove that this is how life started, it may eventually help explain one of the deepest mysteries in modern science.
The title is certainly misleading, since the origin of life puzzle is still very far from “cracked.” Showing that biomolecules, even complex biomolecules, can be synthesized under plausible primordial conditions is very different from showing how those molecules could have assembled to produce the first cell. Only then can one claim to have cracked the puzzle.
That seems to me to be essentially correct, but then the author, Walter Steiner, adds, somewhat mysteriously, “Solving that puzzle will require the discovery of some currently unknown natural phenomenon.” Another commenter suggests some kind of broken symmetry.
The creationists, intelligent-design and otherwise, have moved in on the “conundrum” article, which is now about 1 week old and boasts almost 1000 comments, some of which actually make sense.
Today is Pi Day, and the time will be exactly pi at 3/14/15 9:26:53, or a little thereafter. We will not see another Pi Day till 2115, but I am sure that someone next year will point out that pi = 3.1416 within a thousandth of 1 percent or so. Won’t be the same, though!
Remember the two studies published at the end of last year that produced groundbreaking evolutionary trees of birds and insects? The researchers in these studies used data from whole sequenced genomes to construct these more reliable trees. This is a practice that is somewhat novel but gaining importance in phylogenomics. But we’ve talked about how large data sets, like genomes, can lead to incorrect conclusions if analyzed improperly. How did the researchers avoid this problem?
In the last post, we discussed the two major methods of improving genomic analysis. First, scientists can determine the informative subset of a genome and only obtain and analyze that set. Alternatively, they can develop algorithms to compare whole genomes to a well-established reference genome. But these methods have their drawbacks; subsets of genomes often are not reusable in other experiments and reference genomes, if unavailable, can take a lot of time and work to develop.
Genomes can consist of several billions of nucleotides, so we need different methods of analyzing such a large dataset.
Image source: Boise State University
That’s why our lab is developing SISRS (pronounced “scissors,” Site Identification from Short Read Sequences), a new software program that can analyze genomic data in a matter of days. This NSF- and ASU-funded software eliminates the need for a reference genome and does not require genetic markers, which can take months to determine. Thus, SISRS greatly reduces the time, effort, and cost required to construct a phylogenetic tree from genomic data.
So how does SISRS achieve all of this? From data sequenced via next-generation sequencing, SISRS randomly constructs a subset of data using reservoir sampling. The software then uses de novo assemblers (for example, a program called Velvet) to construct a composite genome from this subset to act as a reference. Because sequences shared among species occur frequently in the collected data, they are more likely to be chosen during the random sampling process than sequences unique to one species. Thus, the composite genome contains genetic information from each species and is a suitable reference genome.
Once the composite reference genome is assembled, SISRS aligns the raw data to the reference. Some species may be missing data in sites, which could be due to several reasons: a gene may not be present in all genomes, there could be variable regions of the genome to which the reference does not align well, or there could have been error in the genome sequencing process. SISRS removes these sites that are missing too much information and filters out other sites that may produce errors (like sites with paralogous, or duplicate, genes). Finally, SISRS outputs the phylogenetically informative sites for phylogeny construction.
To verify SISRS’ effectiveness, our team tested it with the genomic data of primates, whose phylogenetic tree is well-established. SISRS reconstructed the tree with 100% accuracy. Along with genomes, SISRS worked with transcriptomes (the complete set of RNA), estimated the mammal phylogeny very well, and showed promising preliminary results of estimating species divergence times.
SISRS is still under development, and future improvements will enable the program to analyze larger data sets more rapidly. SISRS makes it possible to analyze genomic data quickly, efficiently, and accurately with minimal work. As we continue to improve the software, we welcome feedback from anyone working in the field of phylogenetics; SISRS is available open-source here. We expect this software will have a major impact on phylogenetic analysis.
For more detail about SISRS, click here.
This series is supported by NSF Grant #DBI-1356548 to RA Cartwright.
That is one of the disquieting results of a new survey, Enablers of doubt, by Michael Berkman and Eric Plutzer. The two Penn State professors interviewed a total of 35 students on 4 Pennsylvania campuses in 2013. All the students were training to be biology teachers; many were not comfortable with the theory of evolution, and many were “concerned about their ability to navigate controversy initiated by a student, parent, administrator, or other members of the community.” Indeed, instead of relying on their knowledge of biology, they intended to fall back on classroom-management techniques to deal with creationist students. Notably, these were not education students, but rather biology students who “take a set of required courses in educational psychology, classroom management, and methods of instruction.” Their lack of expertise in science seems not to concern them; to the contrary, they thought they would use their skills at avoiding controversy to avoid any controversies.
PT readers may remember Professors Berkman and Plutzer for their book, Evolution, Creationism, and the Battle to Control America’s Classrooms, which we reviewed here a few years ago. The disquieting conclusion of that book was that only about 28 % of biology teachers actually teach evolution according to recognized standards. The present study may help explain why.
The students, who attended a large research university, an institution that granted degrees at the master’s level, a Catholic college, or a historically Black university (all unnamed), were interviewed in focus groups. The interviews lasted 50-65 min and were conducted by the authors. The focus groups do not provide a statistical sample, but the authors attempted to include several different kinds of educational institution, and they consider the findings “suggestive.” Below the fold, some representative comments.
James Downard is an activist with decades of experience tracking the creationists, stretching back to encounters with Stephen Meyer in Washington state in the early 1990s. In 2010, he did a guest post for PT, “An Ill Wind in Tortuca”, available at: http://pandasthumb.org/archives/201[…]wind-in.html
Troubles in Paradise is a massive review of the creationism/ID movement, its people, and its arguments, along with a similarly massive review of relevant scientific evidence and literature. TIP primarily covers the movement up to about 2004, which of course was just about the peak of the ID movement, leading up to the 2005 Kitzmiller v. Dover case.
I think it is extremely valuable to the pro-science community to have such a historical review available: the ID movement actively tries to conceal what it was saying pre-Kitzmiller, and of course the “intelligent design” label itself was an attempt to disguise connections to creation science. (And, “creation science,” particularly the whitewashed version put forward for the Edwards v. Aguillard case, was its own attempt at obscuring connections to religious fundamentalism.) (On this, see especially: Matzke, N. (2009), “But Isn’t It Creationism? The beginnings of ‘intelligent design’ and Of Pandas and People in the midst of the Arkansas and Louisiana litigation.” In: But Is It Science?: The Philosophical Question in the Creation/Evolution Controversy, Updated Edition, eds. Pennock & Ruse, Prometheus Books, 377-413; google Scholar)
Today in 2015, it is not uncommon for commentators new to the creationism/ID debate to start producing writings almost totally ignorant of the history of the issue. Hopefully Downard’s effort will help correct this problem, and will serve as a resource that science fans can link to and cite.
Troubles in Paradise is really several books’ worth of work, so if you’ve ever gone to the bookstore and bought a science book, please think about making a similar donation so that Downard can continue his efforts.
Below, I post Downard’s short description of the project, which includes a Q & A email interview I conducted with him, and links to his GoFundMe page, www.GoFundMe.com/dseego. Please reblog, retweet, and spread the word! PS: James Downard’s Twitter is: @RJDownard – Nick Matzke
Short description of Troubles in Paradise, by James Downard:
Welcome to TIP, a new open access resource for defenders of sound science who get really unsettled by the claims of antievolutionists (be they Young Earth Creationists or the newer brand of Intelligent Design) but may not have all the best science information ready to drop on their claims.
The TIP files (all in pdf format) cover all aspects of antievolutionism (from paleontology and biology to the social and political ramifications of antievolutionism as they play out in schoolrooms and school boards or in state legislatures, Congress, or even candidates for President.
The Old TIP files form the base of the project, drawing on over 5500 sources, and step by step I am updating that material with a much larger set of newer data (over 36,000 sources and counting, including over 14,000 technical science sources aimed at claims popping up in over 6000 antievolutionist works) to keep TIP constantly current. The new modules also have an index to help locating all specific topics and people covered.
There are more pdfs & offsite web links in Other Stuff, including the 3ME illustrated guide to the Cambrian Explosion, and the origin of birds and mammals, the perfect heavy brick to lob at antievolutionists who make the mistake of claiming “there’s no evidence for macroevolution.” 3ME not only shows how wrong that is, it also pulls back the curtain to see just how antievolutionists manage to evade all that evidence (not a pretty picture, but has to be done).
Check out all the material here on TIP, all open access to download and share freely with anyone you think needs evens stronger evidence to counter the claims of antievolutionists.
Q & A with James Downard:
Q: Why did you decide to call your project “Troubles in Paradise” (TIP)?
Or, perhaps more precisely, Did dark matter kill the dinosaurs?, which is the way that an article in ScienceNOW put it.
Readers of PT doubtless know that there have been a half-dozen or so mass extinctions in the history of the earth, and they appear with a periodicity on the order of 30 million years. You can see an early graph here. The vertical arrows are separated by approximately 30 million years. Not every vertical arrow points to a mass extinction, so it might be better to say that the first harmonic of the data set is 30 million years; that is, if the periodicity is real, it sometimes skips a beat.
What is interesting is that some of the extinctions appear to have been caused by collisions with an asteroid, whereas others may be the result of long periods of extreme volcanism – yet all the extinctions occur with the same period of 30 million years.
… And I will tell you the outcome. I cannot find the origin of that quotation, and I am pretty sure it is not original, but I thought of it when I read this article in Science. In a nutshell, Willie Soon, a part-time employee of the Smithsonian Institution, has published a number of articles linking changes in Arctic air temperature with changes in the sun’s output. His conclusion is at variance with the well established theory that anthropogenic carbon dioxide has caused those changes. The science historian Naomi Oreskes told the New York Times that “Willie Soon is playing a role in a certain kind of political theater” designed to give the impression that there is debate about global warming.
Dr. Soon (according to the Times) is neither an astrophysicist nor a climatologist. He has nevertheless received funding from a utility company with considerable holdings in coal and is alleged not to have disclosed that funding in a number of scientific publications that require such disclosure. Professor Oreskes opines that any papers that have failed to disclose corporate funding, when required, should be withdrawn (and, incidentally, warns that universities need to look closely at this problem).
Dr. Soon has further received funding from a group called Donor’s Trust, which according to Science funnels anonymous donations to groups “championed by political conservatives.” Further, Greenpeace has asked the IRS to investigate whether Dr. Soon has been supported by a foundation funded by Charles Koch, possibly in violation of rules that prohibit non-profits from trying to influence legislation.
The Times reports that Dr. Soon has received a “warm welcome” from such luminaries as Sen. James Inhofe, who believes or pretends to believe that climate change is a widespread hoax.
The Smithsonian Institution, for its part, has sicced its Inspector General on Dr. Soon; the IG will investigate whether Dr. Soon has violated the conflict-of-interest policies of the journals in which he published.
By Steven Mahone.
What would happen if a dyed-in-the-wool secularist was given the opportunity to speak with students from one of the most religiously conservative school districts in the country? Well, I had the privilege of finding out first hand.
The Classical Academy (TCA) is an affluent, public charter high school in north Colorado Springs, so imagine my surprise at receiving an invitation to represent the secular and scientific viewpoint for a week-long seminar titled “Worldviews: The Scientific, Religious, and Cultural Underpinnings of Our Society”. The school is situated two miles from Focus on the Family (an evangelical stronghold for 19th century Christian “values”) and New Life Church, a 10,000-member mega-church that was once pastored by Ted Haggard. (You might recall that Haggard had a parking lot “altercation” with Richard Dawkins when Dawkins attempted to interview him for a BBC special. You can’t help but appreciate the irony when six months after he admonished Dawkins for living a lie behind the veil of science, Haggard was caught with methamphetamines and a male prostitute.) Also sharing the same zip code with the school are the corporate headquarters for Compassion International, The Association of Christian Schools International, and Cook Ministries. I bring this up only to set the stage for my mindset before I ever arrived at the school’s parking lot.
Imagine that you want to analyze the 3.2 billion bases of the human genome. If you recruited every undergraduate student at ASU, all 70,000 of us, to type those data into a spreadsheet, it would still take about 13 hours. So you develop a computer program that analyzes the data for you. But then you find out that your huge data set amplified small errors in your algorithm and gave you the wrong answer. This is the issue facing evolutionary biologists using genomic data, a practice that is becoming standard to construct reliable phylogenies (see our previous posts about the new bird and insect phylogenies). Our lab, working under Dr. Reed Cartwright, has developed a novel method to quickly analyze genomic data and produce an accurate phylogeny that improves upon previous techniques.
The giant panda genome was assembled using de novo techniques in 2010, but better methods of phylogeny construction are in development. Image: Wikipedia
Historically, scientists have compensated for potential inaccuracies in genomic-size data in two ways: by using better statistical tools to analyze the data after they have been acquired or by acquiring fewer, more informative data.
In the first method, you start with sequenced genomes in the form of short fragments (about 100 base pairs) and develop computational algorithms to compare those sequences to a reference genome for reassembly, like Liu et al. did in their 2003 analysis of primate genomes. The reference genome is one that we know with a high level of confidence; for example, the human genome is reliably known and often used as a reference. If, however, a reference is unavailable or unreliable, you could use a computer program to assemble the sequences with a process known as de novo assembly, which Li et al. used to construct the giant panda genome in 2010. These programs, called assemblers, use graphical techniques (for example, De Brujin graphs) to remove errors in phylogenetic trees and resolve repeated data that are harder to determine in short sequences than longer ones. Algorithms like this can greatly improve the accuracy of conclusions made from genomic data, but de novo assembly without a reference genome requires high quality annotation of the sequences and, once the genome is reconstructed, time-consuming alignments of similar sequences to produce a phylogenetic tree.
Alternatively, you could acquire fewer data in the first place. You would need to determine which markers in a genome are informative and necessary to draw certain conclusions and then only obtain those data. By reducing the size of the data set and eliminating unnecessary information, we improve the accuracy without having to implement sophisticated analytical techniques. McCormack et al. used this principle in 2012 to determine the tree of placental mammals from certain markers. However, the major drawback of this method is that markers appropriate for a particular project or species most likely cannot be reused for other projects. The ability to recycle genomic data reduces the cost and time of phylogenomic studies.
Our lab is working on a program that constructs phylogenetic trees more quickly and easily than either of these methods. The program, called SISRS, combines genome assembly with identification of homologous genes to rapidly reconstruct phylogenies without the need of a reference genome or annotation. In the next post, we’ll go into detail about how SISRS works and what makes it a better way to analyze genomic data.
This series is supported by NSF Grant #DBI-1356548 to RA Cartwright.
Four pandas in a captive breeding population have died of canine distemper, one is “stable,” and four are “sick,” according to an article in today’s Science magazine. The pandas have been quarantined, and close contact with tourists, who may carry the disease, has been eliminated. The authorities have also repaired fences to keep dogs out. There is, fortunately, no indication that the disease has spread to a wild breeding population, which is apparently on the far side of a mountain range. The article notes that there is a vaccine to protect against canine distemper, but it is “unclear” whether the breeding center has used the vaccine.
The article goes on to describe the practice of introducing adults bred in captivity into the wild. The government maintains reserves for the pandas and has established corridors that, according to the article, cover 85 % of the pandas’ natural habitat. The article also describes a controversy over the breeding program, in particular, over the practice of taking cubs in the wild from their mothers prematurely, so that the mothers can breed more often, without regard to the needs of individual pandas.
Finally, researchers are awaiting the results of a survey which will ascertain the quality of the protected habitat and help scientists decide how many pandas they may introduce.