Huntington’s disease (HD) is a monogenic disorder that is caused by a CAG repeat expansion in the HTT gene. However, beyond the CAG repeat size other genes also contribute to variations in neurodegeneration of the cortex and striatum as well as the timing of disease onset1,2. The standard method to find genetic modifiers of HD has been the use of genome-wide association studies (GWAS) of large numbers of unrelated patients1,3-5. Previous efforts in this vein have identified single nucleotide variants (SNVs) significantly associated with pathways involved in DNA damage and handling that modify HD age of onset (AO)1,3-8. However, many of these associations have small effect sizes, and typically it is not known whether the SNVs identified with GWAS are the basis for the modifying effect. Here, to augment modifier GWAS, we set out to identify variants that may modify AO in HD by performing family-based studies. We performed whole genome sequencing in families with HD in which individuals with similar CAG expansions showed variation in AO (ranging from a 3- to 20-year difference). We examined the segregation of every variant in the genome and associated the occurrence of those variants with AO. Focusing on rare and uncommon variants, we used a priori knowledge to examine the proximity of our top variants to previously reported GWAS loci. Further, we developed an HD impact scoring system to rank each variant and highlight those most likely to be impactful in the context of influencing the pathology associated with the CAG repeat expansion mutation. Pathway enrichment analysis of these genes revealed numerous pathways previously implicated in HD, as well as novel pathways that may be important in disease onset. Finally, we showed that a putative AO modifier in the ovarian-tumor-domain-containing deubiquitinase 3 (OTUD3) gene correlated with an altered rate of degeneration in patient-derived neurons, and that knockdown of OTUD3 accelerated degeneration in a human cell model of HD, validating our approach. This family-based strategy creates a novel resource for the HD community and establishes a framework that could be applied to study genetic modifiers of many other rare familial diseases.
Monitor lizards are unique among ectothermic reptiles in that they have high aerobic capacity and distinctive cardiovascular physiology resembling that of endothermic mammals. Here, we sequence the genome of the Komodo dragon Varanus komodoensis, the largest extant monitor lizard, and generate a high-resolution de novo chromosome-assigned genome assembly for V. komodoensis using a hybrid approach of long-range sequencing and single-molecule optical mapping. Comparing the genome of V. komodoensis with those of related species, we find evidence of positive selection in pathways related to energy metabolism, cardiovascular homoeostasis, and haemostasis. We also show species-specific expansions of a chemoreceptor gene family related to pheromone and kairomone sensing in V. komodoensis and other lizard lineages. Together, these evolutionary signatures of adaptation reveal the genetic underpinnings of the unique Komodo dragon sensory and cardiovascular systems, and suggest that selective pressure altered haemostasis genes to help Komodo dragons evade the anticoagulant effects of their own saliva. The Komodo dragon genome is an important resource for understanding the biology of monitor lizards and reptiles worldwide.
Detailed studies of individual genes have shown that gene expression divergence often results from adaptive evolution of regulatory sequence. Genome-wide analyses, however, have yet to unite patterns of gene expression with polymorphism and divergence to infer population genetic mechanisms underlying expression evolution. Here, we combined genomic expression data--analyzed in a phylogenetic context--with whole genome light-shotgun sequence data from six Drosophila simulans lines and reference sequences from D. melanogaster and D. yakuba. These data allowed us to use molecular population genetics to test for neutral versus adaptive gene expression divergence on a genomic scale. We identified recent and recurrent adaptive evolution along the D. simulans lineage by contrasting sequence polymorphism within D. simulans to divergence from D. melanogaster and D. yakuba. Genes that evolved higher levels of expression in D. simulans have experienced adaptive evolution of the associated 3' flanking and amino acid sequence. Concomitantly, these genes are also decelerating in their rates of protein evolution, which is in agreement with the finding that highly expressed genes evolve slowly. Interestingly, adaptive evolution in 5' cis-regulatory regions did not correspond strongly with expression evolution. Our results provide a genomic view of the intimate link between selection acting on a phenotype and associated genic evolution.
Next-generation sequencing technology enables the identification of thousands of gene regulatory sequences in many cell types and organisms. We consider the problem of testing if two such sequences differ in their number of binding site motifs for a given transcription factor (TF) protein. Binding site motifs impart regulatory function by providing TFs the opportunity to bind to genomic elements and thereby affect the expression of nearby genes. Evolutionary changes to such functional DNA are hypothesized to be major contributors to phenotypic diversity within and between species; but despite the importance of TF motifs for gene expression, no method exists to test for motif loss or gain. Assuming that motif counts are Binomially distributed, and allowing for dependencies between motif instances in evolutionarily related sequences, we derive the probability mass function of the difference in motif counts between two nucleotide sequences. We provide a method to numerically estimate this distribution from genomic data and show through simulations that our estimator is accurate. Finally, we introduce the R package {\tt motifDiverge} that implements our methodology and illustrate its application to gene regulatory enhancers identified by a mouse developmental time course experiment. While this study was motivated by analysis of regulatory motifs, our results can be applied to any problem involving two correlated Bernoulli trials.
We describe the genome of the western painted turtle, Chrysemys picta bellii, one of the most widespread, abundant, and well-studied turtles. We place the genome into a comparative evolutionary context, and focus on genomic features associated with tooth loss, immune function, longevity, sex differentiation and determination, and the species' physiological capacities to withstand extreme anoxia and tissue freezing.Our phylogenetic analyses confirm that turtles are the sister group to living archosaurs, and demonstrate an extraordinarily slow rate of sequence evolution in the painted turtle. The ability of the painted turtle to withstand complete anoxia and partial freezing appears to be associated with common vertebrate gene networks, and we identify candidate genes for future functional analyses. Tooth loss shares a common pattern of pseudogenization and degradation of tooth-specific genes with birds, although the rate of accumulation of mutations is much slower in the painted turtle. Genes associated with sex differentiation generally reflect phylogeny rather than convergence in sex determination functionality. Among gene families that demonstrate exceptional expansions or show signatures of strong natural selection, immune function and musculoskeletal patterning genes are consistently over-represented.Our comparative genomic analyses indicate that common vertebrate regulatory networks, some of which have analogs in human diseases, are often involved in the western painted turtle's extraordinary physiological capacities. As these regulatory pathways are analyzed at the functional level, the painted turtle may offer important insights into the management of a number of human health disorders.
