# Student Genetics Book Reading Recomendations

Towards the end of the semester I asked my students for their recommendation on extra credit reading assignments next year.  Here is a plot of their response with books that were suggested by two or more students (single entries, which were slightly more than a quarter of the total response, are grouped together).

The large number of students that recommended The Selfish Gene by Dawkins surprised me.  Actually it makes me a bit suspicious that they are already reading this for another class...  The four next most popular books are ones that were options this year, so I suspect they are a bit inflated, but are still good books that are relevant to genetics.  Controlling Human Heredity by Paul is also one that was among the options this year but it was not recommended as highly--it was dry and less enjoyable to read, but I still think it is an important book for them to be exposed to (the history of eugenics programs in the United States).  Still, the students have helped me identify several books that I can take a closer look at for reading options in class next year.

Here are some of the single entry student recommendations that caught my attention (this is not an endorsement for or against):

Lords Of The Harvest: Biotech, Big Money, And The Future Of Food by Daniel Charles

Genetically Modified Athletes: Biomedical Ethics, Gene Doping and Sport : by Andy Miah

Genetic Witness: Science, Law, and Controversy in the Making of DNA Profiling  by Jay Aronson

Evolution: Making Sense of Life by Carl Zimmer and Douglas Emlen

Everyone Here Spoke Sign Language: Hereditary Deafness on Martha's Vineyard by Nora Ellen Groce

Deep Ancestry: Inside the Genographic Project by T. Spencer Wells

Deep Ancestry: Inside the Genographic Project by Spencer Wells

Banana: The Fate of the Fruit That Changed the World by Dan Koeppel

The Red Queen: Sex and the Evolution of Human Nature by Matt Ridley

Power, Sex, Suicide: Mitochondria and the Meaning of Life by Nick Lane

Why We Get Sick: The New Science of Darwinian Medicine by Randolph M. Nesse and George C. Williams

Incognito: The Secret Lives of the Brain by David Eagleman

The Demon-Haunted World: Science as a Candle in the Dark by Carl Sagan and Ann Druyan

Mapping Human History: Genes, Race, and Our Common Origins by Steve Olson

Mutants: On Genetic Variety and the Human Body by Armand Marie Leroi

Crying Hands: Eugenics and Deaf People in Nazi Germany by Horst Biesold and Henry Friedlander

Survival of the Sickest: The Surprising Connections Between Disease and Longevity by Sharon Moalem and Jonathan Prince

Invasion of the Genes: Genetic Heritage of India by B. S. Ahloowalia

The Violinist's Thumb: And Other Lost Tales of Love, War, and Genius, as Written by Our Genetic Code by Sam Kean

Endless Forms Most Beautiful: The New Science of Evo Devo by Sean B. Carroll

War Against the Weak: Eugenics and America's Campaign to Create a Master Race by Edwin Black

The Family that Couldn't Sleep: D.T. Max

The Making of the Fittest: DNA and the Ultimate Forensic Record of Evolution by Sean B. Carroll

The Genetics Revolution: History, Fears, and Future of a Life-Altering Science by Rose Morgan

The Philadelphia Chromosome: A Mutant Gene and the Quest to Cure Cancer at the Genetic Level by Jessica Wapner and Robert A. Weinberg

The Emperor of All Maladies: A Biography of Cancer by Siddhartha Mukherjee

Denialism: How Irrational Thinking Hinders Scientific Progress, Harms the Planet, and Threatens Our Lives by Michael Specter

The Ethics of Genetic Engineering by Roberta M. Berry

Is It in Your Genes?: The Influence of Genes on Common Disorders and Diseases that Affect You and Your Family... by Philip R. Reilly

The Mismeasure of Man by Stephen Jay Gould

Abraham Lincoln's DNA and Other Adventures in Genetics by Philip R. Reilly

# A Few Common Tide Pool Fish Species

Final grades for the semester were due on Christmas Eve the 24th, and I had students calling me on my office phone and emailing me to ask about their grades up until the last minute on the afternoon of the 24th.  Then I was looking forward to a much needed break and went fishing with a video camera.  I'll try adding one of the videos here. It is down-sampled a bit to reduce the file size online.  This is a video of a Mokuleia tidepool on O'ahu.

You can clearly see three (?) fish species.  I am not a marine biologist (this is also part of a personal project on my part to learn more about marine natural history here in Hawai'i), so be suspicious of my attempts at identification.  I am fairly certain that two of the species are sharnosed mullets (Neomyxus leuciscus, uouoa in Hawaiian)--the larger long ones--and (juvenile)

blackspot sergeants (Abudefduf sordidus, Kūpīpī)--the ones with false "eye spots".

I suspect that flagtails are also present (Kuhlia spp., ʻāholehole) and the most common in this video, but I am less confident about their identification (see the update below, these are actually reticulated flagtails, Kuhlia sandvicensis).  There are also two brief glimpses of a third species that I suspect is a "rockskipper" zebra blenny.

If this works well then I will try uploading some more videos.

-----

I sent a picture of the flagtail from the video to some of my coworkers to ask about its identification.

Dr. Kathleen Cole wrote this in reply:

Hi Floyd.
This looks more like the reticulated flagtail, Kuhlia sandvicensis (also referred to as aholehole). It has a broader distribution than K. xenura, the latter of which is an endemic. Distinguishing features include a pale gray rather than dark grey tail, sometimes with a pale margin (which shows up in your picture), and a flattish, rather than slightly concave, head profile. The eye tends to be smaller in sandvicensis, but that doesn't help much unless you have the two species side by side.
Juveniles of both species are found in shallow coastal waters and tide pools so are easy to encounter.
Kassi

I also came across an article about the flagtails in Hawai'i that discusses some of the difficulties and confusion in distinguishing between them.

# Keeping up with email

This is something that I have struggled with for a long time and that has puzzled me.  How do people keep up with email?  I have tried all sorts of strategies.  I have over 200 students in my class this semester so I ask them to put the class code in the subject line to filter those to one folder.  I use completely different email addresses for work and family and typically do not use my work email when at home and vice versa.  I have a filter for people within the department that goes to another folder.  However, I am still way behind even just sifting through all the messages and keep missing important ones.  Here is a cropped screenshot of the times emails have come in between 10:00am and 10:30am this morning, and this is only for filtered emails within the department.

In this example, I am getting an important email every five minutes; these are from different people about different things.  Also, I did not cherry pick this; I'm sure if I searched I could find a denser set of messages.  It feels like as soon as I reply to one another one comes in.  And, this is not including the several phone calls and several people that stopped by my office this morning as well.  If replying to people was my only job I could keep up with it but it is not.  I have to prepare for class, grade exams, apply for grants, not to mention work in the lab, etc.

I know I am just complaining but I honestly don't see how people can keep up and still get everything else done.

-----

Update: A busy morning (Dec. 3).  I couldn't resist a screenshot of my inbox times.  (I can't wait for the semester to be done.)  ... I was interrupted by six people coming by my office before I finished posting this.

# A former student publishes on climate change in Nature!

A year or two ago I wrote a letter of recommendation for grad school for a former student of my genetics class.  Last week they wrote me back and told me about their climate change manuscript (link) that was accepted for publication in Nature.  The publication was also picked up by the media.

Here is the message:

"Aloha Dr. Reed,

How are things? I just wanted to say thanks again for everything that you did to help me get into grad school (you wrote me a letter of recommendation your first semester teaching genetics at UH fall of 2011). I wanted to thank you by sending you a copy of a paper that I was co-author on that just got published in Nature "The projected timing of climate departure". You may or may not have heard about this yet, but so far it is causing quite a media frenzy. I am sure that you will find this paper interesting as it has a heavy biodiversity focus and assesses the impacts of climate change in a new light, not just focusing on absolute changes. Anyways, I hope things are going well, and I just wanted to say thank you for everything and that you helped make a part of this.

Cheers,"

It feels wonderful to get this kind of positive feedback from students from time to time.  In everyday teaching of a class it often feels like everyone is unhappy because you tend to only hear from the small fraction of students that complain.

Last Friday the lead author, Dr. Camilo Mora, gave a presentation on the work in our joint department seminar series.  Most climate change predictions focus on the dramatic increase in temperature in the polar regions--and indeed this is where the largest temperature changes are expected to occur.  But this is not the full picture.  One question is how long until we will experience unprecedented change that is outside the range of previous temperatures.  It turns out that this is predicted to happen first in the tropics, because the tropics have such stable temperatures, a smaller change can push the climate outside of the normal historical boundaries.  The problem is that tropical species and environments can not handle temperature changes as well as temperate and polar species, because they have not had to adapt to wide swings of temperature in the past.  Another problem is that tropical countries tend to have less economic resources to deal with these changes.  The predictions for "climate departure" for some of the tropics are surprisingly near with some dates as soon as 2020.

Dr. Mora was able to do this as a student class project and with very little resources available, using a lot of free tools and data available online.

http://www.latimes.com/nation/la-sci-climate-change-tropics-20131010,0,482935.story

http://www.popsci.com/article/science/no-year-after-2047-will-be-cool-now

http://www.nytimes.com/2013/10/10/science/earth/by-2047-coldest-years-will-be-warmer-than-hottest-in-past.html?_r=0

http://articles.washingtonpost.com/2013-10-09/national/42849788_1_climate-change-intergovernmental-panel-global-ecology

http://www.weather.com/news/climate/2047-coldest-years-may-be-warmer-hottest-past-20131009

http://www.sciencedaily.com/releases/2013/10/131009133216.htm

# Government Shutdown

We had an exam yesterday in my genetics class.  During the exams I project the official time for Hawai'i on the screen so that my students can easily see how much time they have left.  However, because of the budget negotiation failure and partial government shutdown, the website I usually use was not available.  I projected it on the screen anyway.

And in the lower corner I opened the computer's clock settings so they could see that instead.  I announced that the government may be shutdown but we are not, so we are still having the exam today.  I also added that they may want to contact their representatives.

# The coalescent, part I, and average heterozygosity

The idea that ancestral lineages come together (coalesce) at some point in the past is a powerful and useful concept in population genetics.  We inherit our copies of our genes from a finite number of ancestors.  If we randomly picked two copies of a gene in the population there is a chance each generation back that they are inherited from the same ancestral copy.

The number of copies of a gene in the population is twice the population size, or $2N$ .  For example I have two "non-taster" alleles of the gene TAS2R38 and can not taste PTC.  These alleles are found all over the world.  If we look at the allele I inherited from my father, there is a chance that another random copy picked from the present human population is also inherited from the same copy from my father (by my brother or sister).  Moving further back in time my lineage intersects with my close cousins so that we inherited the same copy from our grandparents or great grandparents.  Even further are distant cousins with connections via more ancient common ancestors, and ultimately all modern humans and common ancestors hundreds of thousands of years ago.  Even the "taster" and "non-taster" allele branches are united in a common ancestor with some mutations along one lineage that converted a "taster" ancestor into a "non-taster" allele for people around the world to inherit.

On the simplest level, this probability of inheriting the same copy one generation ago is $\frac{1}{2N}$ , or one out of the total number of possible gene copies to pick from (assuming the population size is a constant $N$ each generation).  Once ancestral lineages come together to the same copy they cannot "uncoalesce" and split back apart; so eventually all lines of inheritance will trace back to one common ancestor in the distant past.

This describes an exponential "waiting-time" process, like radioactive decay or the example I talked about earlier with non-reversible mutations; however, this looks back in time to when an event happened instead of the time until it will occur in the future.  In my class I often use flipping coins or rolling dice as examples to illustrate this.  The chance of rolling a "three" on a die is $\frac{1}{6}$ so on average you need six rolls to get a three.  The chance of "tails" from flipping a penny is $1/2$ .  You could get this on the first try, or it might take a few tries, on average it takes two coin flips.  This is a shared property of all exponential distributions (technically it is actually a geometric distribution because we are thinking of discrete generations, but with a large population we can assume a continuous time approximation and use the exponential).  The rate of coalescence of two lineages each generation is $\frac{1}{2N}$ .  So, on average we wait a total of $2N$ generations until the copies came from a common ancestor.  (The mean of an exponential distribution is the inverse of the rate parameter.)

In the figure above copies of a gene are indicated by circles.  They are in pairs in each individual (rectangles).  I randomly pick two copies to compare in the current generation (red circles in the $g_0$ row).  The first copy on the left has a line of inheritance traced back to earlier generations by the thick black arrows.  There is a chance ( $\frac{1}{2N}$ ) that the second copy coalesces with the first in the previous generation (suggested by the green dashed arrow) but there is a much higher likelihood that it does not coalesce ( $1-\frac{1}{2N}$ , suggested by the gray dashed arrows).  In fact we expect coalescence to happen, on average, $2N$ generations in the past.

The total distance between two copies in the current generation is, starting from one, $2N$ generations back to the common ancestor and $2N$ down to the other copy.  This is a total distance of $4N$ generations.

If we include a per generation mutation rate of $\mu$ to trace along this lineage with an average length of $4N$ , we expect an average difference (or an average heterozygosity) in the population between two copies of a gene of $4N\mu$ (if each mutation affects a different nucleotide in the gene sequence so we see all of the events, which is generally expected for short time periods).  This measure of genetic diversity is a function of both the population size $N$ and the mutation rate $\mu$ .  Larger populations can accumulate more diversity before it is lost due to genetic drift and higher mutation rates introduce diversity at a greater rate.  This value of $4N\mu$ comes up frequently in population genetics and has its own symbol, $\theta=4N\mu$ .

For example, looking at the same thing in a different way.  The number of new mutations at a gene in a population each generation is $\theta/2$ .  There are $2N$ copies of the gene in the diploid population and the fraction $\mu$ of them are expected to mutate each generation: $2N\mu = \theta/2$ .

# A living Punnett Square

In my genetics class we start off with Punnett squares as a tool to generate the relative numbers of expected offspring from a cross.  In the simplest form we have two alleles at a single gene.  If there is a simple dominant/recessive phenotype pattern it can illustrate why we expect a three to one ratio of offspring phenotypes from a cross between two heterozgytoes (individuals that have two different types of alleles).

One of the nice things about working with yeast in the lab is that you can grow it as a haploid (only one copy of each gene) or as a diploid (two copies of each gene); the cells grow and divide in either form.  There are two mating types of cells, like male and female types in animals.  In yeast the mating types are MATa and MATα, or a and α (alpha) for short.  If cells of the two different mating types are growing near each other they will attempt to cross and create a diploid cell.

I used this as one of the introductory lab exercises in my genetics class.  We grew haploid wildtype (white colonies) and haploid mutant cells on a plate of media.  The mutants cannot produce adenine and are dark red because of oxidation of a precursor compound (in the adenine biosynthesis pathway) that accumulates in their cells.

I tried this out first and plated the mutant and wildtype haploid cells for each mating type a and α.  Then after these had grown overnight I spread the cells over each other in four spots corresponding to each cross.  Three of these diploid offspring cells turned (mostly) white, the dominant phenotype, and one was red because it had two mutant copies of the gene; illustrating the 3:1 phenotype ratio.