New Paper: Constrained Evolution

Directional selection should erode genetic variance, but covariance among traits and antagonistic selection in different contexts could maintain it. In a recent project, led by Clarissa House and linked back to my MSc work, we used a quantitative genetic approach to look at the evolution of sex comb morphology in fruit flies, studying selection in pre- and post-copulatory contexts. While we show genetic variance within the traits and genetic correlations among the traits, it appeared that a lack of directional selection on the multivariate phenotype is in fact placing limits on adaptive evolution, allowing genetic variation in sex comb morphology to persist. The paper is now available via the Journal of Evolutionary Biology.




ESEB 2017 Symposium

The ESEB 2017 Scientific Committee have confirmed that Fiona Ingleby and I will be hosting a symposium at the next meeting in Groningen. The symposium, Modern quantitative genetics and the study of adaptation, will give a broad perspective on recent advances in quantitative genetic approaches (for example: the use of omics, hemiclone and chromosome substitution lines, methods to estimate large G-matrices), and how these can be used to study a number of evolutionary processes with adaptation at their core (for example: the evolution of sex differences, host-parasite/predator-prey co-evolutionary dynamics, evolutionary medicine, conservation strategy and adaptation to climate change).


We are very excited that Mark Blows and Anne Charmantier will be joining us as our plenary speakers and offering their considerable expertise on multivariate evolution, quantitative genetics in natural populations, and adaptation. We aim to welcome abstracts from researchers using modern quantitative genetic methods to tackle a variety of problems at the fore of modern evolutionary biology, with a strong emphasis on encouraging a cross-disciplinary exchange of knowledge and ideas.

Looking forward to ESEB2017!

New Paper: X-linkage of Sex-Specific Genetic Variance

The third paper from my PhD has been published in G3: Genes, Genomes, Genetics. In this paper we developed a new method to separately estimate sex-specific genetic variance and cross-sex genetic covariance of the X chromosomes and major autosomes in Drosophila melanogaster, and assayed lifespan and ageing.


The population genetics of the X chromosome differ to those of the autosomes because they occur as a single copy in males, just like in humans. This means that sexually antagonistic and, consequently, sex-specific mutations may more readily accumulate on the X, a prediction supported by our findings. We show that the cross-sex genetic correlation is lower for lifespan on the X chromosome, suggesting a potential for the X to play a special role in the evolution of sex differences.


Genetic Drift Simulator For R

Here is a program to simulate genetic drift in R (code pasted below), specifically one capable of handling unequal sex ratio. Sex ratio directly affects the effective population size, and this simulation can be used to show that it is the effective population size (NE), rather than the census population size (NA), that determines the population genetic behaviour of a population.

Here are some demonstration results, where 10 replicate populations are simulated with NE = 360, but very different actual population sizes, and an initial allele frequency of 0.5. The left hand simulations have unequal sex ratios, while the sex ratio is equal in the right hand simulations. Both sets of simulations behave similarly, showing that effective population size, rather than actual population size, is the determinant of population genetic behaviour.


#####~ Genetic Drift Simulator ~#####
#######~  Robert M. Griffin  ~#######
#####~ Updated March 22nd 2016 ~#####
# Pop   = Replicate populations
# Gen   = Generations
# NM    = Male population size
# NF    = Female population size
# P     = Frequency of focal allele
# histo = Optional histogram
GenDriftSim = function(Pop = Pop, Gen = Gen, NM, NF, P, histo = "yes"){
 P = (2*(NM+NF))*P
 NE = round((4*NM*NF)/(NM+NF),0)
 SR = round(NM/NF,2)
 Na = NM+NF
 plot(c(0,0),type = "n", main = bquote('N'[M]~'/ N'[F]~'='~.(SR)*', N'[A]~'='~.(Na)*', N'[E]~'='~.(NE)), cex.main = 1, 
 xlim = c(1,Gen), ylim=c(0,1), xlab = "Generations", ylab = "Fequency of focal allele")
 for (i in 1:Pop){
 N = NM+NF
 startA = as.vector(c(rep(1, times = P),rep(0, times = (2*N)-P)))
 Population = matrix(c(
 c(sample(startA, size = 2*N, replace = FALSE)),
 c(rep("M", times = NM), rep("F", times = NF))),
 ncol = 3)
 SimResults[(Gen*i)+1-Gen, 3] <<- sum(as.numeric(Population[,1:2]))/(N*2)
 for(j in 1:(Gen-1)){
 Population = matrix(c(
 c(sample(sample(Population[(1:NM),1:2], replace = TRUE),N, replace = TRUE)),
 c(sample(sample(Population[(1+NM):N,1:2], replace = TRUE),N, replace = TRUE)),
 c(rep("M", times = NM), rep("F", times = NF))), ncol = 3)
 SimResults[(Gen*i)+1+j-Gen, 3] <<- sum(as.numeric(Population[,1:2]))/(N*2)
 s = (i*Gen)-Gen+1; e = i*Gen
 r = as.vector(SimResults[s:e, 3])
 points(r~c(1:Gen), type = "l")
 if(histo == "yes"){SimResults[,1] = rep(1:Pop, each = Gen)
 SimResults[,2] = rep(1:Gen, times = Pop)
 hist(SimResults[,3][SimResults[,2]==Gen], xlim = c(0,1), cex.main = 1, main = bquote('N'[M]~'/ N'[F]~'='~.(SR)*', N'[A]~'='~.(Na)*', N'[E]~'='~.(NE)), xlab = paste0("Frequency of focal allele after ",Gen," Generations"))

Pop = 10
Gen = 25
P = 0.5
histo = "no"

SimResults = matrix(data = NA, ncol = 3, nrow = Gen*Pop)
GenDriftSim(Pop = Pop, Gen = Gen, NM = 100, NF = 900, P = P, histo = histo)
GenDriftSim(Pop = Pop, Gen = Gen, NM = 180, NF = 180, P = P, histo = "histo")

Postdoctoral Position

I am now a postdoctoral researcher on natural selection in contemporary human populations at Turku University in Virpi Lummaa’s research group! Virpi’s group studies life history evolution in Humans and Elephants using demographic data. I am really excited to be joining the group as they move from Sheffield to Turku, and look forward to trying my hand at quantitative genetics with pedigree data! News on projects will come soon.


Göteborg University Talk

I gave a presentation at Göteborg University Department of Zoology today, titled The Evolution of Sexual Dimorphism: Quantitative Genetic Explorations of the Drosophila Genome, which was based on my PhD work at Uppsala University. It was really good to present the complex elements of my work to a diverse research department, explaining the concept of adaptation and constraint in multivariate space over just 45 minutes is quite a challenge!


Thanks to Lotta Kvarnemo and the Department of Zoology for inviting me to speak today and the good discussion that followed.

PhD Defence

On September 18th 2015 I successfully defended my PhD thesis, The Genetic Architecture of Sexual Dimorphism, at Uppsala University. This brings an end to just over 4 years of work, in which I have shown that the shared genome constrains the evolution of sexual dimorphism and that the sex chromosomes appear to play a special role in resolving intralocus sexual conflict, by being enriched for sex-specific genetic variance. Thanks to my opponent, Russell Bonduriansky (University of New South Wales), and my committee, Jenny Hagenblad (Linköping University), Bengt Hansson (Lund University), and Dirk Jan De Koning (SLU Uppsala), for their excellent contributions to the defence. The thesis resulted in two publications, while two further manuscripts are in preparation. Urban, Holger, and I hope to publish these soon.