The genetic load argument is one of the oldest arguments for junk DNA and it's one of the most powerful arguments that most of our genome must be junk. The concept dates back to J.B.S. Haldane in the late 1930s but the modern argument traditionally begins with Hermann Muller's classic paper from 1950. It has been extended and refined by him and many others since then (Muller, 1950; Muller, 1966).
[According to Ensembl86] the human genome encodes 58,037 genes, of which approximately one-third are protein-coding (19,950), and yields 198,093 transcripts. By comparison, the mouse genome encodes 48,709 genes, of which half are protein-coding (22,018 genes), and yields 118,925 transcripts overall.The very latest Ensembl estimates (April 2017) for Homo sapiens and Mus musculus are similar. The difference in gene numbers between mouse and human is not significant according to the authors ...
The discrepancy in total number of annotated genes between the two species is unlikely to reflect differences in underlying biology, and can be attributed to the less advanced state of the mouse annotation.This is correct but it doesn't explain the other numbers. There's general agreement on the number of protein-coding genes in mammals. They all have about 20,000 genes. There is no agreement on the number of genes for functional noncoding RNAs. In its latest build, Ensemble says there are 14,727 lncRNA genes, 5,362 genes for small noncoding RNAs, and 2,222 other genes for nocoding RNAs. The total number of non-protein-coding genes is 22,311.
Breschi, A., Gingeras, T.R., and Guigó, R. (2017) Comparative transcriptomics in human and mouse. Nature Reviews Genetics [doi: 10.1038/nrg.2017.19]
I recently criticized a paper by Lu and Bourrat on the extended evolutionary synthesis [Debating philosophers: The Lu and Bourrat paper]. Pierrick Bourrat responds in this guest post.
This is my fifth post on the Lu and Bourrat paper [Debating philosophers: The Lu and Bourrat paper]. The authors are attempting to justify the inclusion of epigenetics into current evolutionary theory by re-defining the concept of "gene," specifically the evolutionary gene concept. So far, I've discussed their understanding of current evolutionary theory and why I think it is flawed [Debating philosophers: The Modern Synthesis]. I described their view of "genes" and pointed out the confusion between "genes" and "alleles" and why I think "alleles" is the better term [Debating philosophers: The difference between genes and alleles]. In my last post I discussed their definition of the evolutionary gene and why it is too adaptationist to serve a useful function [Debating philosophers: The evolutionary gene].
This is the forth post on the Lu and Bourrat paper [Debating philosophers: The Lu and Bourrat paper]. The philosophers are attempting to redefine the word "gene" in order to make epigenetics compatible with current evolutionary theory.
I define a gene in the following way: "A gene is a DNA sequence that is transcribed to produce a functional product" [What Is a Gene?]. This is a biochemical/molecular definition and it's not the same as the definition used in traditional evolution.
This is my third post on the Lu and Bourrat (2017) paper [Debating philosophers: The Lu and Bourrat paper]. Part of their argument is to establish that modern evolutionary theory is a gene-centric theory. They need to make this connection because they are about to re-define the word "gene" in order to accommodate epigenetics.
In my last post I referred to their defense of the Modern Synthesis and quoted them as saying that the major tenets of the Modern Synthesis (MS) are still the basis of modern evolutionary theory. They go on to say,
John Wilkins posted a link on Facebook to a recent paper by his colleagues in Australia. The authors are Qiaoying Lu of the Department of Philosophy at Macquarie University in Sidney Australia and Pierrick Bourat of the Department of Philosophy at The University of Sydney in Sidney Australia.
Lu, Q., and Bourrat, P. (2017) The evolutionary gene and the extended evolutionary synthesis. The British Journal for the Philosophy of Science, (advanced article) April 20, 2017. [doi: 10.1093/bjps/axw035] [PhilSci Archive]
Abstract: Advocates of an ‘extended evolutionary synthesis’ have claimed that standard evolutionary theory fails to accommodate epigenetic inheritance. The opponents of the extended synthesis argue that the evidence for epigenetic inheritance causing adaptive evolution in nature is insufficient. We suggest that the ambiguity surrounding the conception of the gene represents a background semantic issue in the debate. Starting from Haig’s gene-selectionist framework and Griffiths and Neumann-Held’s notion of the evolutionary gene, we define senses of ‘gene’, ‘environment’, and ‘phenotype’ in a way that makes them consistent with gene-centric evolutionary theory. We argue that the evolutionary gene, when being materialized, need not be restricted to nucleic acids but can encompass other heritable units such as epialleles. If the evolutionary gene is understood more broadly, and the notions of environment and phenotype are defined accordingly, current evolutionary theory does not require a major conceptual change in order to incorporate the mechanisms of epigenetic inheritance.
1 Introduction
2 The Gene-centric Evolutionary Theory and the ‘Evolutionary Gene’
2.1 The evolutionary gene
2.2 Genes, phenotypes, and environments
3 Epigenetic Inheritance and the Gene-Centred Framework
3.1 Treating the gene as the sole heritable material?
3.2 Epigenetics and phenotypic plasticity
4 Conclusion
A few years ago, Tomasetti and Vogelstein (2015) published a paper where they noted a correlation between rates of cancer and the number of cell divisions. They concluded that a lot of cancers could be attributed to bad luck. This conclusion didn't sit well with most people for two reasons. (1) There are many well-known environmental effects that increase cancer rates (e.g. smoking, radiation), and (2) there's a widespread belief that you can significantly reduce your chances of getting cancer by "healthy living" (whatever that is). The first objection is based on solid scientific evidence but the second one is not as scientific.
Some of the objections to the original Tomasetti and Vogelstein paper were based on the mathematical models they used to reach their conclusions. The authors have now followed up on their original study with more data. The paper appears in the March 24, 2017 issue of Science (Tomasetti and Vogelstein, 2017). If you're interested in the debate over "bad luck" you should read the accompanying review by Nowak and Waclaw (2017). They conclude that the math is sound and many cancer-causing mutations are, in fact, due to chance mutations in somatic cells. They point out something that should be obvious but bears repeating.
"Epigenetics" is the (relatively) new buzzword. Old-fashioned genetics is boring so if you want to convince people (and grant agencies) that you're on the frontlines of research you have to say you're working on epigenetics. Even better, you can tell them that you are on the verge of overthrowing Darwinism and bringing back Jean-Baptiste Lamarck.
But you need to be careful if you adopt this strategy. Don't let anyone pin you down by defining "epigenetics." It's best to leave it as ambiguous as possible so you can adopt the Humpty-Dumpty strategy.1 Sarah C.P. Williams made that mistake a few years ago and incurred the wrath of Mark Ptashne [Core Misconcept: Epigenetics].With a current population size of over 7 billion, the human population should contain a huge amount of genetic variation. Most of it resides in junk DNA so it's of little consequence. We would like to know more about the amount of variation in functional regions of the genome because it tells us something about population genetics and evolutionary theory.
A recent paper in Nature (Aug. 2016) looked at a large dataset of 60,706 individuals. They sequenced the protein-coding regions of all these people to see what kind of variation existed (Lek et al., 2016) (ExAC). The group included representatives from all parts of the world although it was heavily weighted toward Europeans. The authors used a procedure called "principal component analysis" (PCA) to cluster the individuals according to their genetic characteristics. The analysis led to the typical clustering by "population clusters." (That term is used to avoid the words "race" and/or "subspecies.")
De novo genes1 are quite rare but genome duplications are quite common. Sometimes the duplicated regions contain genes so the new genome contains two copies of a gene that was formerly present in only one copy. "Common" in this sense means on a scale of millions of years. Michael Lynch and his colleague have calculated that the rate of fixed gene duplication is about 0.01 per gene per million years (Lynch and Conery, 2003 a,b; Lynch 2007). Since a typical vertebrate has more than 20,000 genes, this means that 200 genes will be duplicated and fixed every million years.
The frequency of blood type O is very high in some populations of native Americans. In many North American tribes, for example, the frequency is over 90% and often approaches 100%. A majority of individuals in those populations have blood type O (homozygous for the O allele). [see Theme: ABO Blood Types]
Since there's no solid evidence that blood types are adaptive,1 the standard explanation is random genetic drift.One example of evolution by drift may be the unusual frequencies of blood types (as in the ABO system) in the Old Order Amish and Dunker religious communities in America. These are small, isolated, religious groups whose members intermarry—just the right circumstances for rapid evolution by genetic drift.
Accidents of sampling can also happen when a population is founded by just a few immigrants, as occurs when individuals colonize an island or a new area. The almost complete absence of genes producing the B blood type in Native American populations, for example, may reflect the loss of this gene in a small population of humans that colonized North America from Asia around twelve thousand years ago.
Triose phosphate isomerase (TIM) is one of the enzymes in the gluconeogenesis pathway leading to the synthesis of glucose from simple precursors. It also plays a role in the degradation of glucose (glycolysis). The enzyme catalyzes the following reaction ....
IT WAS a discovery that threatened to overturn everything we thought about what makes us human. At the dawn of the new millennium, two rival teams were vying to be the first to sequence the human genome. Their findings, published in February 2001, made headlines around the world. Back-of-the-envelope calculations had suggested that to account for the sheer complexity of human biology, our genome should contain roughly 100,000 genes. The estimate was wildly off. Both groups put the actual figure at around 30,000. We now think it is even fewer – just 20,000 or so.
"It was a massive shock," says geneticist John Mattick. "That number is tiny. It’s effectively the same as a microscopic worm that has just 1000 cells."
It's difficult to explain fundamental concepts of biology to the average person. That's why I'm so interested in Siddhartha Mukherjee's book "The Gene: an intimate history." It's a #1 bestseller so he must be doing something right. 
A gene is a DNA sequence that is transcribed to produce a functional product.This covers two types of genes: those that eventually produce proteins (polypeptides); and those that produce functional noncoding RNAs. This distinction is important when discussing what's in our genome.
If you knew the complete genome sequence of someone could you tell where they came from and their ethnic background (race)? The answer is confusing according to Siddhartha Mukherjee writing in his latest book "The Gene: an intimate history." The answer appears to be "yes" but then Mukherjee denies that knowing where someone came from tells us anything about their genome or their phenotype. He writes the following on page 342.
... the genetic diversity within any racial group dominates the diversity between racial groups. This degree of intraracial variability makes "race" a poor surrogate for nearly any feature: in a genetic sense, an African man from Nigeria is so "different" from another man from Namibia that it makes little sense the lump them into the same category.I find this view very strange. Imagine that you were an anthropologist who was an expert on humans and human evolution. Imagine you were told that there's a woman in the next room whose eight great-grandparents all came from Japan. According to Mukherjee, such a scientist could not predict anything about the features of that woman. Does that make any sense?
For race and genetics, then, the genome is strictly a one-way street. You can use the genome to predict where X or Y came from. But knowing where A or B came from, you can predict little about the person's genome. Or: every genome carries a signature of an individual's ancestry—but an individual's racial ancestry predicts little about the person's genome. You can sequence DNA from an African-American man and conclude that his ancestors came from Sierra Leone or Nigeria. But if you encounter a man whose great-grandparents came from Nigeria or Sierra Leone, you can say little about the features of this particular man. The geneticist goes home happy; the racist returns empty-handed.
Many ethnic groups carry distinct signatures. For example, from a genome sequence you can usually tell if an individual is African-American, Caucasian, Asian, Satnami, or Ashkenazi Jew, even if you've never laid eyes on the patient. A well-regarded research scientist whom I had never met made his genome sequence publically available as part of a research study. I remember scrolling through his genetic variant files and trying, more successfully than I had expected, to guess what he would look like before I peeked at his webpage photo. The personal genome is more than skin deep.This makes more sense to me. If you know what you look for—and Simon Monroe certainly does—then many of the features of a particular person can be deduced from their genome sequence. And if you know which variants are more common in certain ethnic groups then you can certainly predict what a person might look like just by knowing where their ancestors came from.
Sharma, E., Sterne-Weiler, T., O’Hanlon, D., and Blencowe, B.J. (2016) Global Mapping of Human RNA-RNA Interactions. Molecular Cell, [doi: 10.1016/j.molcel.2016.04.030]
ABSTRACT (Summary)
The majority of the human genome is transcribed into non-coding (nc)RNAs that lack known biological functions or else are only partially characterized. Numerous characterized ncRNAs function via base pairing with target RNA sequences to direct their biological activities, which include critical roles in RNA processing, modification, turnover, and translation. To define roles for ncRNAs, we have developed a method enabling the global-scale mapping of RNA-RNA duplexes crosslinked in vivo, ‘‘LIGation of interacting RNA followed by high-throughput sequencing’’ (LIGR-seq). Applying this method in human cells reveals a remarkable landscape of RNA-RNA interactions involving all major classes of ncRNA and mRNA. LIGR-seq data reveal unexpected interactions between small nucleolar (sno) RNAs and mRNAs, including those involving the orphan C/D box snoRNA, SNORD83B, that control steady-state levels of its target mRNAs. LIGR-seq thus represents a powerful approach for illuminating the functions of the myriad of uncharacterized RNAs that act via base-pairing interactions.
It is finally time to return to the problem with which we started, to the tension between individual organism and gene as rival candidates for the central role in natural selection...One way of sorting this whole matter out is to use the terms ‘replicator’ and ‘vehicle’. The fundamental units of natural selection, the basic things that survive or fail to survive, that form lineages of identical copies with occasional random mutations, are called replicators. DNA molecules are replicators. They generally, for reasons that we shall come to, gang together into large communal survival machines or ‘vehicles’.
Richard Dawkins
Blomen, V.A., Májek, P., Jae, L.T., Bigenzahn, J.W., Nieuwenhuis, J., Staring, J., Sacco, R., van Diemen, F.R., Olk, N., and Stukalov, A. (2015) Gene essentiality and synthetic lethality in haploid human cells. Science, 350:1092-1096. [doi: 10.1126/science.aac7557 ]Each group identified between 1500 and 2000 protein-coding genes that are essential in their chosen cell lines.
Wang, T., Birsoy, K., Hughes, N.W., Krupczak, K.M., Post, Y., Wei, J.J., Lander, E. S., and Sabatini, D.M. (2015) Identification and characterization of essential genes in the human genome. Science, 350:1096-1101. [doi: 10.1126/science.aac7041]
Hart, T., Chandrashekhar, M., Aregger, M., Steinhart, Z., Brown, K.R., MacLeod, G., Mis, M., Zimmermann, M., Fradet-Turcotte, A., and Sun, S. (2015) High-Resolution CRISPR Screens Reveal Fitness Genes and Genotype-Specific Cancer Liabilities. Cell 163:1515-1526. [doi: 10.1016/j.cell.2015.11.015]
