Unravelling cell type-specific responses to Parkinson's Disease at single cell resolution.

Parkinson's Disease (PD) is the second most common neurodegenerative disorder. The pathological hallmark of PD is loss of dopaminergic neurons and the presence of aggregated α-synuclein, primarily in the substantia nigra pars compacta (SNpc) of the midbrain. However, the molecular mechanisms that underlie the pathology in different cell types is not currently understood. Here, we present a single nucleus transcriptome analysis of human post-mortem SNpc obtained from 15 sporadic Parkinson's Disease (PD) cases and 14 Controls. Our dataset comprises ∼84K nuclei, representing all major cell types of the brain, allowing us to obtain a transcriptome-level characterization of these cell types. Importantly, we identify multiple subpopulations for each cell type and describe specific gene sets that provide insights into the differing roles of these subpopulations. Our findings reveal a significant decrease in neuronal cells in PD samples, accompanied by an increase in glial cells and T cells. Subpopulation analyses demonstrate a significant depletion of tyrosine hydroxylase (TH) enriched astrocyte, microglia and oligodendrocyte populations in PD samples, as well as TH enriched neurons, which are also depleted. Moreover, marker gene analysis of the depleted subpopulations identified 28 overlapping genes, including those associated with dopamine metabolism (e.g., ALDH1A1, SLC6A3 & SLC18A2). Overall, our study provides a valuable resource for understanding the molecular mechanisms involved in dopaminergic neuron degeneration and glial responses in PD, highlighting the existence of novel subpopulations and cell type-specific gene sets.

Systematic comparative analysis of strand-specific RNA-seq library preparation methods for low input samples.

Despite the recent precipitous decline in the cost of genome sequencing, library preparation for RNA-seq is still laborious and expensive for applications such as high throughput screening. Limited availability of RNA generated by some experimental workflows poses an additional challenge and increases the cost of RNA library preparation. In a search for low cost, automation-compatible RNA library preparation kits that maintain strand specificity and are amenable to low input RNA quantities, we systematically tested two recent commercial technologies-Swift RNA and Swift Rapid RNA, presently offered by Integrated DNA Technologies (IDT) -alongside the Illumina TruSeq stranded mRNA, the de facto standard workflow for bulk transcriptomics. We used the Universal Human Reference RNA (UHRR) (composed of equal quantities of total RNA from 10 human cancer cell lines) to benchmark gene expression in these kits, at input quantities ranging between 10 to 500 ng. We found normalized read counts between all treatment groups to be in high agreement. Compared to the Illumina TruSeq stranded mRNA kit, both Swift RNA library kits offer shorter workflow times enabled by their patented Adaptase technology. We also found the Swift RNA kit to produce the fewest number of differentially expressed genes and pathways directly attributable to input mRNA amount.

Reconstructed evolutionary history of the yeast septins Cdc11 and Shs1.

Septins are GTP-binding proteins conserved across metazoans. They can polymerize into extended filaments and, hence, are considered a component of the cytoskeleton. The number of individual septins varies across the tree of life-yeast (Saccharomyces cerevisiae) has seven distinct subunits, a nematode (Caenorhabditis elegans) has two, and humans have 13. However, the overall geometric unit (an apolar hetero-octameric protomer and filaments assembled there from) has been conserved. To understand septin evolutionary variation, we focused on a related pair of yeast subunits (Cdc11 and Shs1) that appear to have arisen from gene duplication within the fungal clade. Either Cdc11 or Shs1 occupies the terminal position within a hetero-octamer, yet Cdc11 is essential for septin function and cell viability, whereas Shs1 is not. To discern the molecular basis of this divergence, we utilized ancestral gene reconstruction to predict, synthesize, and experimentally examine the most recent common ancestor ("Anc.11-S") of Cdc11 and Shs1. Anc.11-S was able to occupy the terminal position within an octamer, just like the modern subunits. Although Anc.11-S supplied many of the known functions of Cdc11, it was unable to replace the distinct function(s) of Shs1. To further evaluate the history of Shs1, additional intermediates along a proposed trajectory from Anc.11-S to yeast Shs1 were generated and tested. We demonstrate that multiple events contributed to the current properties of Shs1: (1) loss of Shs1-Shs1 self-association early after duplication, (2) co-evolution of heterotypic Cdc11-Shs1 interaction between neighboring hetero-octamers, and (3) eventual repurposing and acquisition of novel function(s) for its C-terminal extension domain. Thus, a pair of duplicated proteins, despite constraints imposed by assembly into a highly conserved multi-subunit structure, could evolve new functionality via a complex evolutionary pathway.

A framework for integrating directed and undirected annotations to build explanatory models of cis-eQTL data.

A longstanding goal of regulatory genetics is to understand how variants in genome sequences lead to changes in gene expression. Here we present a method named Bayesian Annotation Guided eQTL Analysis (BAGEA), a variational Bayes framework to model cis-eQTLs using directed and undirected genomic annotations. We used BAGEA to integrate directed genomic annotations with eQTL summary statistics from tissues of various origins. This analysis revealed epigenetic marks that are relevant for gene expression in different tissues and cell types. We estimated the predictive power of the models that were fitted based on directed genomic annotations. This analysis showed that, depending on the underlying eQTL data used, the directed genomic annotations could predict up to 1.5% of the variance observed in the expression of genes with top nominal eQTL association p-values < 10-7. For genes with estimated effect sizes in the top 25% quantile, up to 5% of the expression variance could be predicted. Based on our results, we recommend the use of BAGEA for the analysis of cis-eQTL data to reveal annotations relevant to expression biology.

Haploinsufficiency leads to neurodegeneration in C9ORF72 ALS/FTD human induced motor neurons.

An intronic GGGGCC repeat expansion in C9ORF72 is the most common cause of amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD), but the pathogenic mechanism of this repeat remains unclear. Using human induced motor neurons (iMNs), we found that repeat-expanded C9ORF72 was haploinsufficient in ALS. We found that C9ORF72 interacted with endosomes and was required for normal vesicle trafficking and lysosomal biogenesis in motor neurons. Repeat expansion reduced C9ORF72 expression, triggering neurodegeneration through two mechanisms: accumulation of glutamate receptors, leading to excitotoxicity, and impaired clearance of neurotoxic dipeptide repeat proteins derived from the repeat expansion. Thus, cooperativity between gain- and loss-of-function mechanisms led to neurodegeneration. Restoring C9ORF72 levels or augmenting its function with constitutively active RAB5 or chemical modulators of RAB5 effectors rescued patient neuron survival and ameliorated neurodegenerative processes in both gain- and loss-of-function C9ORF72 mouse models. Thus, modulating vesicle trafficking was able to rescue neurodegeneration caused by the C9ORF72 repeat expansion. Coupled with rare mutations in ALS2, FIG4, CHMP2B, OPTN and SQSTM1, our results reveal mechanistic convergence on vesicle trafficking in ALS and FTD.

PhyloBot: A Web Portal for Automated Phylogenetics, Ancestral Sequence Reconstruction, and Exploration of Mutational Trajectories.

The method of phylogenetic ancestral sequence reconstruction is a powerful approach for studying evolutionary relationships among protein sequence, structure, and function. In particular, this approach allows investigators to (1) reconstruct and "resurrect" (that is, synthesize in vivo or in vitro) extinct proteins to study how they differ from modern proteins, (2) identify key amino acid changes that, over evolutionary timescales, have altered the function of the protein, and (3) order historical events in the evolution of protein function. Widespread use of this approach has been slow among molecular biologists, in part because the methods require significant computational expertise. Here we present PhyloBot, a web-based software tool that makes ancestral sequence reconstruction easy. Designed for non-experts, it integrates all the necessary software into a single user interface. Additionally, PhyloBot provides interactive tools to explore evolutionary trajectories between ancestors, enabling the rapid generation of hypotheses that can be tested using genetic or biochemical approaches. Early versions of this software were used in previous studies to discover genetic mechanisms underlying the functions of diverse protein families, including V-ATPase ion pumps, DNA-binding transcription regulators, and serine/threonine protein kinases. PhyloBot runs in a web browser, and is available at the following URL: http://www.phylobot.com. The software is implemented in Python using the Django web framework, and runs on elastic cloud computing resources from Amazon Web Services. Users can create and submit jobs on our free server (at the URL listed above), or use our open-source code to launch their own PhyloBot server.

Evolution of an ancient protein function involved in organized multicellularity in animals.

To form and maintain organized tissues, multicellular organisms orient their mitotic spindles relative to neighboring cells. A molecular complex scaffolded by the GK protein-interaction domain (GKPID) mediates spindle orientation in diverse animal taxa by linking microtubule motor proteins to a marker protein on the cell cortex localized by external cues. Here we illuminate how this complex evolved and commandeered control of spindle orientation from a more ancient mechanism. The complex was assembled through a series of molecular exploitation events, one of which - the evolution of GKPID's capacity to bind the cortical marker protein - can be recapitulated by reintroducing a single historical substitution into the reconstructed ancestral GKPID. This change revealed and repurposed an ancient molecular surface that previously had a radically different function. We show how the physical simplicity of this binding interface enabled the evolution of a new protein function now essential to the biological complexity of many animals.

Ancestral resurrection reveals evolutionary mechanisms of kinase plasticity.

Protein kinases have evolved diverse specificities to enable cellular information processing. To gain insight into the mechanisms underlying kinase diversification, we studied the CMGC protein kinases using ancestral reconstruction. Within this group, the cyclin dependent kinases (CDKs) and mitogen activated protein kinases (MAPKs) require proline at the +1 position of their substrates, while Ime2 prefers arginine. The resurrected common ancestor of CDKs, MAPKs, and Ime2 could phosphorylate substrates with +1 proline or arginine, with preference for proline. This specificity changed to a strong preference for +1 arginine in the lineage leading to Ime2 via an intermediate with equal specificity for proline and arginine. Mutant analysis revealed that a variable residue within the kinase catalytic cleft, DFGx, modulates +1 specificity. Expansion of Ime2 kinase specificity by mutation of this residue did not cause dominant deleterious effects in vivo. Tolerance of cells to new specificities likely enabled the evolutionary divergence of kinases.

How duplicated transcription regulators can diversify to govern the expression of nonoverlapping sets of genes.

The duplication of transcription regulators can elicit major regulatory network rearrangements over evolutionary timescales. However, few examples of duplications resulting in gene network expansions are understood in molecular detail. Here we show that four Candida albicans transcription regulators that arose by successive duplications have differentiated from one another by acquiring different intrinsic DNA-binding specificities, different preferences for half-site spacing, and different associations with cofactors. The combination of these three mechanisms resulted in each of the four regulators controlling a distinct set of target genes, which likely contributed to the adaption of this fungus to its human host. Our results illustrate how successive duplications and diversification of an ancestral transcription regulator can underlie major changes in an organism's regulatory circuitry.

tRNA genes rapidly change in evolution to meet novel translational demands.

Changes in expression patterns may occur when organisms are presented with new environmental challenges, for example following migration or genetic changes. To elucidate the mechanisms by which the translational machinery adapts to such changes, we perturbed the tRNA pool of Saccharomyces cerevisiae by tRNA gene deletion. We then evolved the deletion strain and observed that the genetic adaptation was recurrently based on a strategic mutation that changed the anticodon of other tRNA genes to match that of the deleted one. Strikingly, a systematic search in hundreds of genomes revealed that anticodon mutations occur throughout the tree of life. We further show that the evolution of the tRNA pool also depends on the need to properly couple translation to protein folding. Together, our observations shed light on the evolution of the tRNA pool, demonstrating that mutation in the anticodons of tRNA genes is a common adaptive mechanism when meeting new translational demands. DOI: http://dx.doi.org/10.7554/eLife.01339.001.

Following gene duplication, paralog interference constrains transcriptional circuit evolution.

Most models of gene duplication assume that the ancestral functions of the preduplication gene are independent and can therefore be neatly partitioned between descendant paralogs. However, many gene products, such as transcriptional regulators, are components within cooperative assemblies; here, we show that a natural consequence of duplication and divergence of such proteins can be competitive interference between the paralogs. Our example is based on the duplication of the essential MADS-box transcriptional regulator Mcm1, which is found in all fungi and regulates a large set of genes. We show that a set of historical amino acid sequence substitutions minimized paralog interference in contemporary species and, in doing so, increased the molecular complexity of this gene regulatory network. We propose that paralog interference is a common constraint on gene duplicate evolution, and its resolution, which can generate additional regulatory complexity, is needed to stabilize duplicated genes in the genome.

Replicate phylogenies and post-glacial range expansion of the pitcher-plant mosquito, Wyeomyia smithii, in North America.

Herein we tested the repeatability of phylogenetic inference based on high throughput sequencing by increased taxon sampling using our previously published techniques in the pitcher-plant mosquito, Wyeomyia smithii in North America. We sampled 25 natural populations drawn from different localities nearby 21 previous collection localities and used these new data to construct a second, independent phylogeny, expressly to test the reproducibility of phylogenetic patterns. Comparison of trees between the two data sets based on both maximum parsimony and maximum likelihood with Bayesian posterior probabilities showed close correspondence in the grouping of the most southern populations into clear clades. However, discrepancies emerged, particularly in the middle of W. smithii's current range near the previous maximum extent of the Laurentide Ice Sheet, especially concerning the most recent common ancestor to mountain and northern populations. Combining all 46 populations from both studies into a single maximum parsimony tree and taking into account the post-glacial historical biogeography of associated flora provided an improved picture of W. smithii's range expansion in North America. In a more general sense, we propose that extensive taxon sampling, especially in areas of known geological disruption is key to a comprehensive approach to phylogenetics that leads to biologically meaningful phylogenetic inference.

Identification and characterization of a previously undescribed family of sequence-specific DNA-binding domains.

Sequence-specific DNA-binding proteins are among the most important classes of gene regulatory proteins, controlling changes in transcription that underlie many aspects of biology. In this work, we identify a transcriptional regulator from the human fungal pathogen Candida albicans that binds DNA specifically but has no detectable homology with any previously described DNA- or RNA-binding protein. This protein, named White-Opaque Regulator 3 (Wor3), regulates white-opaque switching, the ability of C. albicans to switch between two heritable cell types. We demonstrate that ectopic overexpression of WOR3 results in mass conversion of white cells to opaque cells and that deletion of WOR3 affects the stability of opaque cells at physiological temperatures. Genome-wide chromatin immunoprecipitation of Wor3 and gene expression profiling of a wor3 deletion mutant strain indicate that Wor3 is highly integrated into the previously described circuit regulating white-opaque switching and that it controls a subset of the opaque transcriptional program. We show by biochemical, genetic, and microfluidic experiments that Wor3 binds directly to DNA in a sequence-specific manner, and we identify the set of cis-regulatory sequences recognized by Wor3. Bioinformatic analyses indicate that the Wor3 family arose more recently in evolutionary time than most previously described DNA-binding domains; it is restricted to a small number of fungi that include the major fungal pathogens of humans. These observations show that new families of sequence-specific DNA-binding proteins may be restricted to small clades and suggest that current annotations--which rely on deep conservation--underestimate the fraction of genes coding for transcriptional regulators.

Evolution of increased complexity in a molecular machine.

Many cellular processes are carried out by molecular 'machines'-assemblies of multiple differentiated proteins that physically interact to execute biological functions. Despite much speculation, strong evidence of the mechanisms by which these assemblies evolved is lacking. Here we use ancestral gene resurrection and manipulative genetic experiments to determine how the complexity of an essential molecular machine--the hexameric transmembrane ring of the eukaryotic V-ATPase proton pump--increased hundreds of millions of years ago. We show that the ring of Fungi, which is composed of three paralogous proteins, evolved from a more ancient two-paralogue complex because of a gene duplication that was followed by loss in each daughter copy of specific interfaces by which it interacts with other ring proteins. These losses were complementary, so both copies became obligate components with restricted spatial roles in the complex. Reintroducing a single historical mutation from each paralogue lineage into the resurrected ancestral proteins is sufficient to recapitulate their asymmetric degeneration and trigger the requirement for the more elaborate three-component ring. Our experiments show that increased complexity in an essential molecular machine evolved because of simple, high-probability evolutionary processes, without the apparent evolution of novel functions. They point to a plausible mechanism for the evolution of complexity in other multi-paralogue protein complexes.

The reconstructed ancestral subunit a functions as both V-ATPase isoforms Vph1p and Stv1p in Saccharomyces cerevisiae.

The vacuolar-type, proton-translocating ATPase (V-ATPase) is a multisubunit enzyme responsible for organelle acidification in eukaryotic cells. Many organisms have evolved V-ATPase subunit isoforms that allow for increased specialization of this critical enzyme. Differential targeting of the V-ATPase to specific subcellular organelles occurs in eukaryotes from humans to budding yeast. In Saccharomyces cerevisiae, the two subunit a isoforms are the only difference between the two V-ATPase populations. Incorporation of Vph1p or Stv1p into the V-ATPase dictates the localization of the V-ATPase to the vacuole or late Golgi/endosome, respectively. A duplication event within fungi gave rise to two subunit a genes. We used ancestral gene reconstruction to generate the most recent common ancestor of Vph1p and Stv1p (Anc.a) and tested its function in yeast. Anc.a localized to both the Golgi/endosomal network and vacuolar membrane and acidified these compartments as part of a hybrid V-ATPase complex. Trafficking of Anc.a did not require retrograde transport from the late endosome to the Golgi that has evolved for retrieval of the Stv1p isoform. Rather, Anc.a localized to both structures through slowed anterograde transport en route to the vacuole. Our results suggest an evolutionary model that describes the differential localization of the two yeast V-ATPase isoforms.

Robustness of ancestral sequence reconstruction to phylogenetic uncertainty.

Ancestral sequence reconstruction (ASR) is widely used to formulate and test hypotheses about the sequences, functions, and structures of ancient genes. Ancestral sequences are usually inferred from an alignment of extant sequences using a maximum likelihood (ML) phylogenetic algorithm, which calculates the most likely ancestral sequence assuming a probabilistic model of sequence evolution and a specific phylogeny--typically the tree with the ML. The true phylogeny is seldom known with certainty, however. ML methods ignore this uncertainty, whereas Bayesian methods incorporate it by integrating the likelihood of each ancestral state over a distribution of possible trees. It is not known whether Bayesian approaches to phylogenetic uncertainty improve the accuracy of inferred ancestral sequences. Here, we use simulation-based experiments under both simplified and empirically derived conditions to compare the accuracy of ASR carried out using ML and Bayesian approaches. We show that incorporating phylogenetic uncertainty by integrating over topologies very rarely changes the inferred ancestral state and does not improve the accuracy of the reconstructed ancestral sequence. Ancestral state reconstructions are robust to uncertainty about the underlying tree because the conditions that produce phylogenetic uncertainty also make the ancestral state identical across plausible trees; conversely, the conditions under which different phylogenies yield different inferred ancestral states produce little or no ambiguity about the true phylogeny. Our results suggest that ML can produce accurate ASRs, even in the face of phylogenetic uncertainty. Using Bayesian integration to incorporate this uncertainty is neither necessary nor beneficial.