Dissecting the genetic basis of comorbid epilepsy phenotypes in neurodevelopmental disorders.

BACKGROUND:Neurodevelopmental disorders (NDDs) such as autism spectrum disorder, intellectual disability, developmental disability, and epilepsy are characterized by abnormal brain development that may affect cognition, learning, behavior, and motor skills. High co-occurrence (comorbidity) of NDDs indicates a shared, underlying biological mechanism. The genetic heterogeneity and overlap observed in NDDs make it difficult to identify the genetic causes of specific clinical symptoms, such as seizures. METHODS:We present a computational method, MAGI-S, to discover modules or groups of highly connected genes that together potentially perform a similar biological function. MAGI-S integrates protein-protein interaction and co-expression networks to form modules centered around the selection of a single "seed" gene, yielding modules consisting of genes that are highly co-expressed with the seed gene. We aim to dissect the epilepsy phenotype from a general NDD phenotype by providing MAGI-S with high confidence NDD seed genes with varying degrees of association with epilepsy, and we assess the enrichment of de novo mutation, NDD-associated genes, and relevant biological function of constructed modules. RESULTS:The newly identified modules account for the increased rate of de novo non-synonymous mutations in autism, intellectual disability, developmental disability, and epilepsy, and enrichment of copy number variations (CNVs) in developmental disability. We also observed that modules seeded with genes strongly associated with epilepsy tend to have a higher association with epilepsy phenotypes than modules seeded at other neurodevelopmental disorder genes. Modules seeded with genes strongly associated with epilepsy (e.g., SCN1A, GABRA1, and KCNB1) are significantly associated with synaptic transmission, long-term potentiation, and calcium signaling pathways. On the other hand, modules found with seed genes that are not associated or weakly associated with epilepsy are mostly involved with RNA regulation and chromatin remodeling. CONCLUSIONS:In summary, our method identifies modules enriched with de novo non-synonymous mutations and can capture specific networks that underlie the epilepsy phenotype and display distinct enrichment in relevant biological processes. MAGI-S is available at https://github.com/jchow32/magi-s

Rodent phylogeny revised: analysis of six nuclear genes from all major rodent clades

<p>Abstract</p> <p>Background</p> <p>Rodentia is the most diverse order of placental mammals, with extant rodent species representing about half of all placental diversity. In spite of many morphological and molecular studies, the family-level relationships among rodents and the location of the rodent root are still debated. Although various datasets have already been analyzed to solve rodent phylogeny at the family level, these are difficult to combine because they involve different taxa and genes.</p> <p>Results</p> <p>We present here the largest protein-coding dataset used to study rodent relationships. It comprises six nuclear genes, 41 rodent species, and eight outgroups. Our phylogenetic reconstructions strongly support the division of Rodentia into three clades: (1) a "squirrel-related clade", (2) a "mouse-related clade", and (3) Ctenohystrica. Almost all evolutionary relationships within these clades are also highly supported. The primary remaining uncertainty is the position of the root. The application of various models and techniques aimed to remove non-phylogenetic signal was unable to solve the basal rodent trifurcation.</p> <p>Conclusion</p> <p>Sequencing and analyzing a large sequence dataset enabled us to resolve most of the evolutionary relationships among Rodentia. Our findings suggest that the uncertainty regarding the position of the rodent root reflects the rapid rodent radiation that occurred in the Paleocene rather than the presence of conflicting phylogenetic and non-phylogenetic signals in the dataset.</p

FastML: a web server for probabilistic reconstruction of ancestral sequences

Ancestral sequence reconstruction is essential to a variety of evolutionary studies. Here, we present the FastML web server, a user-friendly tool for the reconstruction of ancestral sequences. FastML implements various novel features that differentiate it from existing tools: (i) FastML uses an indel-coding method, in which each gap, possibly spanning multiples sites, is coded as binary data. FastML then reconstructs ancestral indel states assuming a continuous time Markov process. FastML provides the most likely ancestral sequences, integrating both indels and characters; (ii) FastML accounts for uncertainty in ancestral states: it provides not only the posterior probabilities for each character and indel at each sequence position, but also a sample of ancestral sequences from this posterior distribution, and a list of the k-most likely ancestral sequences; (iii) FastML implements a large array of evolutionary models, which makes it generic and applicable for nucleotide, protein and codon sequences; and (iv) a graphical representation of the results is provided, including, for example, a graphical logo of the inferred ancestral sequences. The utility of FastML is demonstrated by reconstructing ancestral sequences of the Env protein from various HIV-1 subtypes. FastML is freely available for all academic users and is available online at http://fastml.tau.ac.i

An Evolutionary Analysis of Lateral Gene Transfer in Thymidylate Synthase Enzymes

Thymidylate synthases (Thy) are key enzymes in the synthesis of deoxythymidylate, 1 of the 4 building blocks of DNA. As such, they are essential for all DNA-based forms of life and therefore implicated in the hypothesized transition from RNA genomes to DNA genomes. Two evolutionally unrelated Thy enzymes, ThyA and ThyX, are known to catalyze the same biochemical reaction. Both enzymes are sporadically distributed within each of the 3 domains of life in a pattern that suggests multiple nonhomologous lateral gene transfer (LGT) events. We present a phylogenetic analysis of the evolution of the 2 enzymes, aimed at unraveling their entangled evolutionary history and tracing their origin back to early life. A novel probabilistic evolutionary model was developed, which allowed us to compute the posterior probabilities and the posterior expectation of the number of LGT events. Simulation studies were performed to validate the model's ability to accurately detect LGT events, which have occurred throughout a large phylogeny. Applying the model to the Thy data revealed widespread nonhomologous LGT between and within all 3 domains of life. By reconstructing the ThyA and ThyX gene trees, the most likely donor of each LGT event was inferred. The role of viruses in LGT of Thy is finally discussed

The birth of a human-specific neural gene by incomplete duplication and gene fusion

Background: Gene innovation by duplication is a fundamental evolutionary process but is difficult to study in humans due to the large size, high sequence identity, and mosaic nature of segmental duplication blocks. The human-specific gene hydrocephalus-inducing 2, HYDIN2, was generated by a 364 kbp duplication of 79 internal exons of the large ciliary gene HYDIN from chromosome 16q22.2 to chromosome 1q21.1. Because the HYDIN2 locus lacks the ancestral promoter and seven terminal exons of the progenitor gene, we sought to characterize transcription at this locus by coupling reverse transcription polymerase chain reaction and long-read sequencing. Results: 5' RACE indicates a transcription start site for HYDIN2 outside of the duplication and we observe fusion transcripts spanning both the 5' and 3' breakpoints. We observe extensive splicing diversity leading to the formation of altered open reading frames (ORFs) that appear to be under relaxed selection. We show that HYDIN2 adopted a new promoter that drives an altered pattern of expression, with highest levels in neural tissues. We estimate that the HYDIN duplication occurred ~3.2 million years ago and find that it is nearly fixed (99.9%) for diploid copy number in contemporary humans. Examination of 73 chromosome 1q21 rearrangement patients reveals that HYDIN2 is deleted or duplicated in most cases. Conclusions: Together, these data support a model of rapid gene innovation by fusion of incomplete segmental duplications, altered tissue expression, and potential subfunctionalization or neofunctionalization of HYDIN2 early in the evolution of the Homo lineage

Evolutionary Modeling of Rate Shifts Reveals Specificity Determinants in HIV-1 Subtypes

A hallmark of the human immunodeficiency virus 1 (HIV-1) is its rapid rate of evolution within and among its various subtypes. Two complementary hypotheses are suggested to explain the sequence variability among HIV-1 subtypes. The first suggests that the functional constraints at each site remain the same across all subtypes, and the differences among subtypes are a direct reflection of random substitutions, which have occurred during the time elapsed since their divergence. The alternative hypothesis suggests that the functional constraints themselves have evolved, and thus sequence differences among subtypes in some sites reflect shifts in function. To determine the contribution of each of these two alternatives to HIV-1 subtype evolution, we have developed a novel Bayesian method for testing and detecting site-specific rate shifts. The RAte Shift EstimatoR (RASER) method determines whether or not site-specific functional shifts characterize the evolution of a protein and, if so, points to the specific sites and lineages in which these shifts have most likely occurred. Applying RASER to a dataset composed of large samples of HIV-1 sequences from different group M subtypes, we reveal rampant evolutionary shifts throughout the HIV-1 proteome. Most of these rate shifts have occurred during the divergence of the major subtypes, establishing that subtype divergence occurred together with functional diversification. We report further evidence for the emergence of a new sub-subtype, characterized by abundant rate-shifting sites. When focusing on the rate-shifting sites detected, we find that many are associated with known function relating to viral life cycle and drug resistance. Finally, we discuss mechanisms of covariation of rate-shifting sites

The discovery of integrated gene networks for autism and related disorders

Despite considerable genetic heterogeneity underlying neurodevelopmental diseases, there is compelling evidence that many disease genes will map to a much smaller number of biological subnetworks. We developed a computational method, termed MAGI (merging affected genes into integrated networks), that simultaneously integrates protein-protein interactions and RNA-seq expression profiles during brain development to discover "modules" enriched for de novo mutations in probands. We applied this method to recent exome sequencing of 1116 patients with autism and intellectual disability, discovering two distinct modules that differ in their properties and associated phenotypes. The first module consists of 80 genes associated with Wnt, Notch, SWI/SNF, and NCOR complexes and shows the highest expression early during embryonic development (8-16 post-conception weeks [pcw]). The second module consists of 24 genes associated with synaptic function, including long-term potentiation and calcium signaling with higher levels of postnatal expression. Patients with de novo mutations in these modules are more significantly intellectually impaired and carry more severe missense mutations when compared to probands with de novo mutations outside of these modules. We used our approach to define subsets of the network associated with higher functioning autism as well as greater severity with respect to IQ. Finally, we applied MAGI independently to epilepsy and schizophrenia exome sequencing cohorts and found significant overlap as well as expansion of these modules, suggesting a core set of integrated neurodevelopmental networks common to seemingly diverse human diseases

The discovery of integrated gene networks for autism and related disorders

Despite considerable genetic heterogeneity underlying neurodevelopmental diseases, there is compelling evidence that many disease genes will map to a much smaller number of biological subnetworks. We developed a computational method, termed MAGI (merging affected genes into integrated networks), that simultaneously integrates protein–protein interactions and RNA-seq expression profiles during brain development to discover “modules” enriched for de novo mutations in probands. We applied this method to recent exome sequencing of 1116 patients with autism and intellectual disability, discovering two distinct modules that differ in their properties and associated phenotypes. The first module consists of 80 genes associated with Wnt, Notch, SWI/SNF, and NCOR complexes and shows the highest expression early during embryonic development (8–16 post-conception weeks [pcw]). The second module consists of 24 genes associated with synaptic function, including long-term potentiation and calcium signaling with higher levels of postnatal expression. Patients with de novo mutations in these modules are more significantly intellectually impaired and carry more severe missense mutations when compared to probands with de novo mutations outside of these modules. We used our approach to define subsets of the network associated with higher functioning autism as well as greater severity with respect to IQ. Finally, we applied MAGI independently to epilepsy and schizophrenia exome sequencing cohorts and found significant overlap as well as expansion of these modules, suggesting a core set of integrated neurodevelopmental networks common to seemingly diverse human diseases