Selection on a Variant Associated with Improved Viral Clearance Drives Local, Adaptive Pseudogenization of Interferon Lambda 4 (<i>IFNL4</i>)

<div><p>Interferon lambda 4 gene (<i>IFNL4</i>) encodes IFN-λ4, a new member of the IFN-λ family with antiviral activity. In humans <i>IFNL4</i> open reading frame is truncated by a polymorphic frame-shift insertion that eliminates IFN-λ4 and turns <i>IFNL4</i> into a polymorphic pseudogene. Functional IFN-λ4 has antiviral activity but the elimination of IFN-λ4 through pseudogenization is strongly associated with improved clearance of hepatitis C virus (HCV) infection. We show that functional IFN-λ4 is conserved and evolutionarily constrained in mammals and thus functionally relevant. However, the pseudogene has reached moderately high frequency in Africa, America, and Europe, and near fixation in East Asia. In fact, the pseudogenizing variant is among the 0.8% most differentiated SNPs between Africa and East Asia genome-wide. Its raise in frequency is associated with additional evidence of positive selection, which is strongest in East Asia, where this variant falls in the 0.5% tail of SNPs with strongest signatures of recent positive selection genome-wide. Using a new Approximate Bayesian Computation (ABC) approach we infer that the pseudogenizing allele appeared just before the out-of-Africa migration and was immediately targeted by moderate positive selection; selection subsequently strengthened in European and Asian populations resulting in the high frequency observed today. This provides evidence for a changing adaptive process that, by favoring IFN-λ4 inactivation, has shaped present-day phenotypic diversity and susceptibility to disease.</p></div

Allele frequency of rs368234815 - ΔG allele (blue) and TT allele (green) for each population from the 1000 Genomes dataset.

<p>American populations of European and African origin (CEU, ASW) are placed near the geographic area of origin. For full population names see <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1004681#s4" target="_blank">Methods</a>.</p

(A) Graphical representation of the different models of selection tested in the ABC analysis (NTR - neutral, SDN - selection on a de novo mutation, and SSV - selection on standing variation).

<p>We simulated one ancestral population that splits at the out-of-Africa event (at 51,000 years ago) into the African (AFR) and the non-African (non-AFR) populations, which experience subsequent migration. The star indicates the appearance of the focal mutation. In the first case the neutral (black) mutation appeared and evolved under neutrality in both populations. In the SDN model the advantageous mutation (red) is immediately under positive selection with strength s_A, and time when selection started t_mut (the prior parameter space for t_mut is indicated by a green line); selection strength is allowed to change in the non-African population to s_NA. In the SSV model the neutral (black) mutation appeared and evolved under neutrality, becoming advantageous in the non-African population (red line) at time t_mut. Prior parameter spaces can be found in methods. (<b>B</b>) Posterior probabilities of the model choice for the different selection models under perfect additivity. (<b>C</b>) Posterior probabilities of the model choice for the different dominance models (and neutrality, NTR). For all models except NTR the posterior probability represent the sum for the SDN and SSV selection models. (<b>D</b>) Posterior probabilities of the model choice for the different selection models under the supra-additive model. In (<b>B</b>), (<b>C</b>), and (<b>D</b>), NTR has negligible posterior probability and is therefore not visible.</p

Derived allele frequency (DAF), LD to rs368234815, and signatures of selection (empirical P-values for F_ST and XP-EHH) for other relevant SNPs across the <i>IFNL</i>-locus.

<p>Derived allele frequency (DAF), LD to rs368234815, and signatures of selection (empirical P-values for F_ST and XP-EHH) for other relevant SNPs across the <i>IFNL</i>-locus.</p

Phylogenetic tree showing the dN/dS ratio of each lineage analyzed.

<p>Phylogenetic tree showing the dN/dS ratio of each lineage analyzed.</p

F_ST values and for F_ST, XP-EHH, iHS and Fay and Wu's H (FW) the empirical P-values are shown for rs368234815 in every population.

<p>F_ST values and for F_ST, XP-EHH, iHS and Fay and Wu's H (FW) the empirical P-values are shown for rs368234815 in every population.</p

Human local adaptation of the TRPM8 cold receptor along a latitudinal cline

<div><p>Ambient temperature is a critical environmental factor for all living organisms. It was likely an important selective force as modern humans recently colonized temperate and cold Eurasian environments. Nevertheless, as of yet we have limited evidence of local adaptation to ambient temperature in populations from those environments. To shed light on this question, we exploit the fact that humans are a cosmopolitan species that inhabit territories under a wide range of temperatures. Focusing on cold perception–which is central to thermoregulation and survival in cold environments–we show evidence of recent local adaptation on <i>TRPM8</i>. This gene encodes for a cation channel that is, to date, the only temperature receptor known to mediate an endogenous response to moderate cold. The upstream variant rs10166942 shows extreme population differentiation, with frequencies that range from 5% in Nigeria to 88% in Finland (placing this SNP in the 0.02% tail of the F_ST empirical distribution). When all populations are jointly analyzed, allele frequencies correlate with latitude and temperature beyond what can be explained by shared ancestry and population substructure. Using a Bayesian approach, we infer that the allele originated and evolved neutrally in Africa, while positive selection raised its frequency to different degrees in Eurasian populations, resulting in allele frequencies that follow a latitudinal cline. We infer strong positive selection, in agreement with ancient DNA showing high frequency of the allele in Europe 3,000 to 8,000 years ago. rs10166942 is important phenotypically because its ancestral allele is protective of migraine. This debilitating disorder varies in prevalence across human populations, with highest prevalence in individuals of European descent–precisely the population with the highest frequency of rs10166942 derived allele. We thus hypothesize that local adaptation on previously neutral standing variation may have contributed to the genetic differences that exist in the prevalence of migraine among human populations today.</p></div

ABC analysis.

<p><b>(A)</b> Graphical representation of the three models (SSV, SDN, NTR) and their associated parameters. Birth of the allele and start time of selection are shown by black and red lines, respectively. The range of the prior distribution for time of selection start is depicted by a star and a blue line. A double headed arrow indicates population migration. <b>(B)</b> Posterior probabilities for each model and population. <b>(C)</b> Prior distribution of each parameter as a histogram. Posterior distribution of the SSV model parameters as a line for each population.</p

Correlation between latitude and derived allele frequency.

<p>Correlation of the frequency of the rs10166942 T allele with latitude. The fitted function (dashed line) results for the 1KGP data from <b>(A)</b> the PGLS and <b>(B)</b> GLMM analysis. <b>(C)</b> Results of the best model in the GLMM analysis of the SGDP dataset. The fitted response is shown as gridded surface, and the dots represent the average frequency of the rs10166942 T allele per cell of the gridded surface. Points above the surface are filled, points below are open. The volume of the points corresponds to the number of populations per cell.</p

PGLS and GLMM analysis.

<p>All models considered, ordered by their fit (Model rank). Three measures of model support are shown: AIC, delta AIC, and Akaike weight. The cumulative probability are shown together with the resulting confidence set (models that together provide just over 0.95 cumulative probability; indicated by ‘yes’). Results are shown for the 1KGP in PGLS and GLMM analyses, the SGDP in a GLMM analysis, and the SGDP using only the Eurasian populations in a GLMM analysis.</p