Chromosome Chronicles Launches News Section

Inspired by one of my favorite sites, HackerNews, I’ve decided to launch my own version: The Chromosome Chronicles news section! Here, ANYONE can submit genetics news (I also have a few reputable news sites feeding to it). But I encourage anyone to submit, whether it is a new blog post, a funny genetics picture.The news allows all users and visitors to then vote up or vote down a submitted article. Also, I will be tweeting on my twitter account the most recent top stories @chromchron. Please submit!

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The 22nd Carnival of Evolution

The 22nd Blog Carnival of Evolution is now up at Beetles in the Bush! Check it out to see 26 great posts on evolution and perspectives on a diverse range of evolution-related fields. The Chromosome Chronicles article on In Silico Models of Evolution is featured in this edition. Stop over for some good old Darwinian reading.

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Divorcers and Polygamists: Evolutionary Superstars?

Brigham Young and 21 of his wives.

Evolutionary fitness is one of the most important concepts in Darwinian evolution. Essentially, fitness can be regarded as a measure of how much of an individual’s genes are passed on to the next generation. More specifically, the higher proportion of the next generation that is comprised of your genes, the more fit, evolutionarily, you are.

Fitness: A short example

For example, say I have one copy of a particular version of a gene: Gene X. No one else in my population of 100 individuals has it. Since we all have two copies of every gene, the frequency of Gene X can be regarded as 1 out of 200. Let’s assume that I pass on Gene X to four of my children in the next generation of 100 individuals for this population. Gene X has now increased from 1 out of 200 to 4 out of 200. Since the frequency of Gene X increased from the first to the second generation, Gene X can be regarded as a gene of higher evolutionary fitness.

Maximizing Your Fitness

Okay, now that we’ve reviewed fitness as the measure for evolutionary success, it begs the question: how can I maximize my evolutionary success? Answer: have as many children as possible (who will survive to one day themselves reproduce). This way, your genes will constitute a higher proportion of the future generations of gene pools.

An obvious limitation to the number of children a person can have is childbirth itself. Nine months, a painful delivery, and then years of caring for the child requires a huge investment in resources. Moreover, women might be viewed as a “limiting step” in this process (I hope I don’t get shot for that one). In particular, mating with only one women would surely slow a man down if his main goal was to produce as many offspring as possible.

Polygamy: Evolutionarily Advantageous

Joseph Smith Jr. was on to something when he founded the Church of the Latter Day Saints. Specifically, his many, many, many wives made him highly successful (from a Darwinian standpoint), although he publicly condemned the practice. By some accounts he may have had 20 children with his multiple wives. While the privilege of polygamy had previously only been reserved for the highest of alpha males (like the one and only Genghis Khan, to whom a large proportion of China can claim some relation), Smith had labored to include multiple wives in the doctrine of his faith. Simply join his church and you become an evolutionary celebrity. To this day, there are many living in Utah who can claim some relation to Joseph Smith Jr.

Divorce/Second Marriages: The Compromise in the name of Monogamy

Let’s assume (or believe) that all human actions are still driven by primal evolutionary urges. Having multiple wives surely fits this bill since it allows for greater evolutionary fitness. However, polygamy is outlawed in western culture, so outside of those who practice it underground, it is not a reliable option for men who wish to increase their fitness.

For men, the divorce/second marriage life route allows for more than one family, more than one wife, just not at the same time. By Darwinian standards, those who get divorced and remarry are actually more successful than those who are monogamous their whole lives (assuming that they have more children). Men who get divorced and remarry will be passing on a higher proportion of genetic material into the next generation.

Let’s take this argument a step further. What if the behavior: “Get divorced, remarry” has a genetic factor that predisposes a man to engaging in this behavior. If this behavior results in higher fitness (higher % of genes passed on by those who exhibit the behavior), then one might argue that a higher proportion of men in the next generation will have genes that predispose them to get divorced. By this logic, if divorce is an activity that makes men more fit (evolutionarily), then we can expect to see divorce rates rise in future generations!

Is Maximizing Our Darwinian Fitness our True Goal in Life?

This question gets to the heart of our discussion. Is maximizing the number of children we have our major goal in life? For some species, yes. For humans, no. Our sentience seems to have made us immune to many of the evolutionary pressures that drive other animals’ behaviors. For example, if having your own genes passed on in your children was so important, then why is adoption so popular? Also, why do many couples elect to not have children ever? These actions seem to be at odds with the idea of evolutionary fitness, yet many members of our species engage in them.

Finally, if maximizing evolutionary fitness was really the ultimate goal in life, then why wouldn’t all men (and women) go around the world donating sperm (and eggs) to all of the banks they can find. I can think of no quicker way to maximize the number of genetic offspring you have. Hopefully, no one does that because it would be kind of creepy.

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Analysis of 23andMe’s Genotyping: High Accuracy of Illumina Platform Confirmed by Comparing Siblings

Microarray genotyping platforms report high accuracy. Of course, this is given that you use their protocols, ideal conditions, etc. Depending on the genotyping facility, this accuracy may be even more tenuous. I recently set out to get some good estimates for the rate of genotyping errors from the Illumina assay employed by 23andMe.

First let me refer back to a previous post about determining haplotype when you have two parents and a child. By determining haplotypes for all of my siblings and I, I am able to compare regions where we share both parental haplotypes, or shared diplotypes. In my family, there are four siblings (including myself), and I have had us all tested at 23andMe. To analyze genotyping errors, I decided to compare informative SNPs from shared haplotypes between my three brothers and I.

Experimental Outline:

  1. Determine Transmitted Parental Haplotypes from all four siblings.
  2. Determine Where Both alleles are Shared for all four Siblings.
  3. Find out how many genotyping errors occurred in this region.

Determining the parental haplotypes is simple, and my method for doing this has already been described. Determining where the four siblings share alleles was accomplished using a program I wrote called NucleOlap. This program compares informative SNPs from paternal and maternal haplotypes between children and produces a nice output. It is designed to recognize candidate regions responsible for dominant or recessive genetic mutations given each child’s affected or unaffected status. However, if all children are affected, it is the same thing as analyzing haplotype sharing. Check out the documentation.

For every pair of siblings, it is expected that, on average, they will share both parental haplotypes for 25% of their genome. Add a 3rd sibling, and that 25% falls to 6.25%. For four siblings, it is expected that both haplotypes are shared for only 1.56% of their genome. According to release 36.1 of the Human Genome, the haploid length of the autosomes is 2,864,255,922 base pairs! I can expect that my three brothers and I share both parental haplotypes for 44,753,999 haploid base pairs.

The NucleOlap analysis found that my siblings and I all shared both haplotypes in six regions for a total of 47,656,130 haploid base pairs. Pretty good! The ideogram to the left shows the regions where my three brothers and I share the exact same genes from both parents. Shared regions occur on chromosomes 1, 2, 6, 13, 16, and 18. NucleOlap also provided me with the starting and ending positions (and SNPs) for each region. To determine where genotyping errors occured, I compared the raw data for these regions with each child (the program output is not affected by genotyping errors because it is able to recognize and ignore them).

The analysis occurred by gathering the SNPs in the identified shared regions and lining them up parallel to one another in Microsoft Excel. I then checked to see that all four siblings had the same genotype for each SNP (as they are expected to). A sample of how this worked is shown in the picture to the right.

My analysis revealed that 10,079 SNPs were contained within the regions where my brothers and I share diplotypes. Of these 10,079 SNPs, only 86 of them had any genotyping errors! This means that the genotyping calling was 99.15% accurate for these regions. Moreover, of the errors recorded, 79 of them occurred when there was a genotype call for some of the siblings and a null call (–) for others. Only 7 errors occurred where there was inconsistency in the genotype assigned to the siblings. The results are summarized in the table to the left.

My conclusion: the genotyping error rate is very low, less than 1% for the Illumina platform used by 23andMe. Even taking null calls into account, this number is still below 1%. My siblings and I shared 99.15% genotype identity in a region where we all share both parental haplotypes. I am very pleased with the accuracy.


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Modeling Evolution in vitro and in silico

When I think about models of evolution, I’m reminded of an episode of a cartoon show, “I am Weasel,” called I.M. Diety. Forgive me for taking us back to 1998, but the premise of this episode is that the super-genius main character, Weasel, and his nincompoop of a friend, Baboon, purchase these “instant life” packets which require the addition of DNA (spit) to grow your own society in a petri dish. It’s kind of like a chia pet, except you’re growing living beings.

To summarize, they watch life evolve on a petri dish from its earliest form all the way through advanced civilizations that worship them as “the gods in the sky.” The denizens of these science experiments are unaware of anything outside of the walls of their petri dish. Eventually, Weasel’s society develops sophisticated technology and flies to Baboons society. Intermixing of the species is cataclysmic and the experiment is over.

Evolution in a petri dish.

I am still amazed at how vivid my memory of this episode is. The really cool science aspect was that they simulated evolution in vitro. Directed evolution is a relatively common biological technique. For instance, when dealing with a normal strain of E. coli, if we wished to “create” a strain that is resistant to penicillin, we would simply plate some E. coli on penicillin infused culture media . While 99.99% of the E.coli would die from the penicillin, the remaining 0.01% will survive due to having received random mutations that conferred resistance to the compound. This can be viewed as evolution in vitro.

The dramatized, yet cool aspect of the “I am Weasel” episode is that highly complex life forms developed overnight. For organisms that we are familiar with to radically evolve in such a short period would be very unlikely (I have become accustomed to avoiding the word impossible). The main reason for such improbability is the long generational periods. A very large number of generations and different selection factors contributed to evolution on earth, and to replicate these results should take just as long!

While in vitro models of evolution might have us waiting forever, in silico models of evolution have already proven to be very worthy of consideration. Life forms on earth compete for resources in order to survive and reproduce. At the fundamental level, it is the perpetuation of a given sequence of DNA that drives animal instinct (even human beings): or so would argue those who believe in Dawkins’ Selfish Gene. With this in mind, we have identified some variables: resources, competitive ability, and reproductive ability. We have also identified DNA as giving the instructions on how to compete for these resources in order to reproduce. Adaptation occurs via mutation.

Moving from in vitro to in silico.

To create in silico models, these aspects of evolution had to be mapped to their computer counterparts. DNA can be substituted for by self replicating computer code that undergoes changes/rearrangement. Resources can be simulated by computer memory or RAM. The actions of competing and reproducing are executed by self-replicating code as they compete to take up more of the computer’s memory.

This is more or less what Thomas S. Ray created in Tierra, his model of artificial life developed in the early 1990s. In Tierra, strings of computer code compete for CPU time and computer memory by copying themselves with some rate of mutation. Ray’s program simulated a host-parasite battle where hosts were infected by parasites, and over time, it was seen that hosts developed immunity to the parasites in an evolutionary arms race occurring in silico.

Who is God of the Computer Realm?

In silico models of evolution are great because they allow for many generations to occur within a short period of time. The digital organisms being created by these investigators evolve and mutate just like biological organisms. While computer simulated evolutionary models have not created artificial sentient life, a real question that remains is, “Are these strings of computer codes real beings?” They compete for resources, they self replicate, and they perish just like biological beings. However, answering this question will likely require a bit more thought and ethical debate.

If it is concluded that these computer strings are real organisms, then it is simultaneously conceded that human beings have created life, an act though by many only possible by their god (throughout many religions in the world). Proper synthesis of silicon life through a model based on evolutionary principles also goes a long way to prove the theory of evolution (for those who were not convinced by fossil evidence, DNA evidence, and a plethora of other biological data). While this is truly exciting, I’m almost afraid of the emergence of a sentient silicon organism because its species would evolve at a much faster pace than us, mere biological organisms.

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