Exploiting selection at linked sites to infer the rate and strength of adaptation, bioRxiv, 2018-09-26
Genomic data encodes past evolutionary events and has the potential to reveal the strength, rate, and biological drivers of adaptation. However, robust estimation of adaptation rate (alpha) and adaptation strength remains a challenging problem because evolutionary processes such as demography, linkage, and non-neutral polymorphism can confound inference. Here, we exploit the influence of background selection to reduce the fixation rate of weakly-beneficial alleles to jointly infer the strength and rate of adaptation. We develop a novel MK-based method (ABC-MK) to infer adaptation rate and strength, and estimate alpha=0.135 in human protein-coding sequences, 72% of which is contributed by weakly adaptive variants. We show that in this adaptation regime alpha is reduced approx. 25% by linkage genome-wide. Moreover, we show that virus-interacting proteins (VIPs) undergo adaptation that is both stronger and nearly twice as frequent as the genome average (alpha=0.224, 56% due to strongly-beneficial alleles). Our results suggest that while most adaptation in human proteins is weakly-beneficial, adaptation to viruses is often strongly-beneficial. Our method provides a robust framework for estimating adaptation rate and strength across species.
biorxiv evolutionary-biology 0-100-users 2018Slow transcriptional elongation causes embryonic lethality and perturbs kinetic coupling of long neural genes, bioRxiv, 2018-09-26
The rate of RNA Polymerase II (RNAPII) elongation has an important role in the control of Alternative splicing (AS); however, the in vivo consequences of an altered elongation rate are unknown. Here, we generated mouse embryonic stem cells (ESCs) knocked-in for a slow elongating form of RNAPII. We show that a reduced transcriptional elongation rate results in early embryonic lethality in mice and impairs the differentiation of ESCs into the neural lineage. This is accompanied by changes in splicing and in gene expression in ESCs and along the pathway of neuronal differentiation. In particular, we found a crucial role for RNAPII elongation rate in transcription and splicing of long neuronal genes involved in synapse signaling. The impact of the kinetic coupling of RNAPII elongation rate with AS is more predominant in ESC-differentiated neurons than in pluripotent cells. Our results demonstrate the requirement for an appropriate transcriptional elongation rate to ensure proper gene expression and to regulate AS during development.
biorxiv molecular-biology 0-100-users 2018Stronger and higher proportion of beneficial amino acid changing mutations in humans compared to mice and flies, bioRxiv, 2018-09-26
ABSTRACTQuantifying and comparing the amount of adaptive evolution among different species is key to understanding evolutionary processes. Previous studies have shown differences in adaptive evolution across species, however their specific causes remain elusive. Here, we use improved modeling of weakly deleterious mutations and the demographic history of the outgroup species and estimate that 30–34% of nonsynonymous substitutions between humans and outgroup species have been fixed by positive selection. This estimate is much higher than previous estimates, which did not account for the population size of the outgroup species. Next, we directly estimate the proportion and selection coefficients of newly arising strongly beneficial nonsynonymous mutations in humans, mice, and D. melanogaster by examining patterns of polymorphism and divergence. We develop a novel composite likelihood framework to test whether these parameters differ across species. Overall, we reject a model with the same proportion and the same selection coefficients of beneficial mutations across species, and estimate that humans have a higher proportion of beneficial mutations compared to Drosophila and mice. We demonstrate that this result cannot be attributed to biased gene conversion. In summary, we find the proportion of beneficial mutations is higher in humans than in D. melanogaster or mice, suggesting that organismal complexity, which increases the number of steps required in adaptive walks, may be a key predictor of the amount of adaptive evolution within a species.
biorxiv evolutionary-biology 0-100-users 2018The ecological drivers of variation in global language diversity, bioRxiv, 2018-09-26
AbstractLanguage diversity is distributed unevenly over the globe. Why do some areas have so many different languages and other areas so few? Intriguingly, patterns of language diversity resemble biodiversity patterns, leading to suggestions that similar mechanisms may underlie both linguistic and biological diversification. Here we present the first global analysis of language diversity that identifies the relative importance of two key ecological mechanisms suggested to promote language diversification - isolation and ecological risk - after correcting for spatial autocorrelation and phylogenetic non-independence. We find significant effects of climate on language diversity consistent with the ecological risk hypothesis that areas of high year-round productivity lead to more languages by supporting human cultural groups with smaller distributions. Climate has a much stronger effect on language diversity than landscape features that might contribute to isolation of cultural groups, such as altitudinal variation, river density, or landscape roughness. The association between biodiversity and language diversity appears to be an incidental effect of their covariation with climate, rather than a causal link between the two. While climate and landscape provide strong explanatory signal for variation in language diversity, we identify a number of areas of high unexplained language diversity, with more languages than would be predicted from environmental features alone; notably New Guinea, the Himalayan foothills, West Africa, and Mesoamerica. Additional processes may be at play in generating higher than expected language diversity in these regions.
biorxiv ecology 0-100-users 2018Amygdala neuronal ensembles dynamically encode behavioral states, bioRxiv, 2018-09-25
AbstractInternal states, including affective or homeostatic states, are important behavioral motivators. The amygdala is a key brain region involved in the regulation of motivated behaviors, yet how distinct internal states are represented in amygdala circuits is unknown. Here, by imaging somatic neural calcium dynamics in freely moving mice, we identify changes in the relative activity levels of two major, non-overlapping populations of principal neurons in the basal nucleus of the amygdala (BA) that predict switches between exploratory and non-exploratory (defensive, anxiety-like) behavioral states across different environments. Moreover, the amygdala widely broadcasts internal state information via several output pathways to larger brain networks, and sensory responses in BA occur independently of behavioral state encoding. Thus, the brain processes external stimuli and internal states in an orthogonal manner, which may facilitate rapid and flexible selection of appropriate, state-dependent behavioral responses.
biorxiv neuroscience 0-100-users 2018Layer-dependent activity in human prefrontal cortex during working memory, bioRxiv, 2018-09-24
Working memory involves a series of functions encoding a stimulus, maintaining or manipulating its representation over a delay, and finally making a behavioral response. While working memory engages dorsolateral prefrontal cortex (dlPFC), few studies have investigated whether these subfunctions are localized to different cortical depths in this region, and none have done so in humans. Here, we use high-resolution functional MRI to interrogate the layer specificity of neural activity during different epochs of a working memory task in dlPFC. We detect activity timecourses that follow the hypothesized patterns superficial layers are preferentially active during the delay period, while deeper layers are preferentially active during the response. Results demonstrate that layer-specific fMRI can be used in higher-order brain regions to non-invasively map cognitive information processing along cortical circuitry in humans.
biorxiv neuroscience 0-100-users 2018