A Catalog of Neutral and Deleterious Polymorphism in Yeast

The abundance and identity of functional variation segregating in natural populations is paramount to dissecting the molecular basis of quantitative traits as well as human genetic diseases. Genome sequencing of multiple organisms of the same species provides an efficient means of cataloging rearrangements, insertion, or deletion polymorphisms (InDels) and single-nucleotide polymorphisms (SNPs). While inbreeding depression and heterosis imply that a substantial amount of polymorphism is deleterious, distinguishing deleterious from neutral polymorphism remains a significant challenge. To identify deleterious and neutral DNA sequence variation within Saccharomyces cerevisiae, we sequenced the genome of a vineyard and oak tree strain and compared them to a reference genome. Among these three strains, 6% of the genome is variable, mostly attributable to variation in genome content that results from large InDels. Out of the 88,000 polymorphisms identified, 93% are SNPs and a small but significant fraction can be attributed to recent interspecific introgression and ectopic gene conversion. In comparison to the reference genome, there is substantial evidence for functional variation in gene content and structure that results from large InDels, frame-shifts, and polymorphic start and stop codons. Comparison of polymorphism to divergence reveals scant evidence for positive selection but an abundance of evidence for deleterious SNPs. We estimate that 12% of coding and 7% of noncoding SNPs are deleterious. Based on divergence among 11 yeast species, we identified 1,666 nonsynonymous SNPs that disrupt conserved amino acids and 1,863 noncoding SNPs that disrupt conserved noncoding motifs. The deleterious coding SNPs include those known to affect quantitative traits, and a subset of the deleterious noncoding SNPs occurs in the promoters of genes that show allele-specific expression, implying that some cis-regulatory SNPs are deleterious. Our results show that the genome sequences of both closely and distantly related species provide a means of identifying deleterious polymorphisms that disrupt functionally conserved coding and noncoding sequences

Wheat Domestication Accelerated Evolution and Triggered Positive Selection in the β-Xylosidase Enzyme of Mycosphaerella graminicola

Plant cell wall degrading enzymes (PCWDEs) of plant pathogens are receiving increasing interest for their potential to trigger plant defense reactions. In an antagonistic co-evolutionary arms race between host and pathogen, PCWDEs could be under strong selection. Here, we tested the hypothesis that PCWDEs in the fungal wheat pathogen Mycosphaerella graminicola have been positively selected by analyzing ratios of non-synonymous and synonymous nucleotide changes in the genes encoding these enzymes. Analyses of five PCWDEs demonstrated that one (β-xylosidase) has been under strong positive selection and experienced an accelerated rate of evolution. In contrast, PCWDEs in the closest relatives of M. graminicola collected from wild grasses did not show evidence for selection or deviation from a molecular clock. Since the genealogical divergence of M. graminicola from these latter species coincided with the onset of agriculture, we hypothesize that the recent domestication of the host plant and/or agricultural practices triggered positive selection in β-xylosidase and that this enzyme played a key role in the emergence of a host-specialized pathogen

Variable-temperature, variable-field magnetic circular dichroism spectroscopic study of NifEN-bound precursor and “FeMoco”

NifEN plays a key role in the biosynthesis of the iron–molybdenum cofactor (FeMoco) of nitrogenase. A scaffold protein that hosts the conversion of a FeMoco precursor to a mature cofactor, NifEN can assume three conformations during the process of FeMoco maturation. One, designated ΔnifB NifEN, contains only two permanent [Fe4S4]-like clusters. The second, designated NifENPrecursor, contains the permanent clusters and a precursor form of FeMoco. The third, designated NifEN“FeMoco”, contains the permanent [Fe4S4]-like clusters and a fully complemented, “FeMoco”-like structure. Here, we report a variable-temperature, variable-field magnetic circular dichroism spectroscopic investigation of the electronic structure of the metal clusters in the three forms of dithionite-reduced NifEN. Our data indicate that the permanent [Fe4S4]-like clusters are structurally and electronically conserved in all three NifEN species and exhibit spectral features of classic [Fe4S4]+ clusters; however, they are present in a mixed spin state with a small contribution from the S > ½ spin state. Our results also suggest that both the precursor and “FeMoco” have a conserved Fe/S electronic structure that is similar to the electronic structure of FeMoco in the MoFe protein, and that the “FeMoco” in NifEN“FeMoco” exists, predominantly, in an S = 3/2 spin state with spectral parameters identical to those of FeMoco in the MoFe protein. These observations provide strong support to the outcome of our previous EPR and X-ray absorption spectroscopy/extended X-ray absorption fine structure analysis of the three NifEN species while providing significant new insights into the unique electronic properties of the precursor and “FeMoco” in NifEN

The Impact of Different Types of Assistive Devices on Gait Measures and Safety in Huntington's Disease

BACKGROUND: Gait and balance impairments lead to frequent falls and injuries in individuals with Huntington's disease (HD). Assistive devices (ADs) such as canes and walkers are often prescribed to prevent falls, but their efficacy is unknown. We systematically examined the effects of different types of ADs on quantitative gait measures during walking in a straight path and around obstacles. METHODS: Spatial and temporal gait parameters were measured in 21 subjects with HD as they walked across a GAITRite walkway under 7 conditions (i.e., using no AD and 6 commonly prescribed ADs: a cane, a weighted cane, a standard walker, and a 2, 3 or 4 wheeled walker). Subjects also were timed and observed for number of stumbles and falls while walking around two obstacles in a figure-of-eight pattern. RESULTS: Gait measure variability (i.e., coefficient of variation), an indicator of fall risk, was consistently better when using the 4WW compared to other ADs. Subjects also walked the fastest and had the fewest number of stumbles and falls when using the 4WW in the figure-of-eight course. Subjects walked significantly slower using ADs compared to no AD both across the GAITRite and in the figure-of-eight. Measures reflecting gait stability and safety improved with the 4WW but were made worse by some other ADs

Benchmarking and Analysis of Protein Docking Performance in Rosetta v3.2

RosettaDock has been increasingly used in protein docking and design strategies in order to predict the structure of protein-protein interfaces. Here we test capabilities of RosettaDock 3.2, part of the newly developed Rosetta v3.2 modeling suite, against Docking Benchmark 3.0, and compare it with RosettaDock v2.3, the latest version of the previous Rosetta software package. The benchmark contains a diverse set of 116 docking targets including 22 antibody-antigen complexes, 33 enzyme-inhibitor complexes, and 60 ‘other’ complexes. These targets were further classified by expected docking difficulty into 84 rigid-body targets, 17 medium targets, and 14 difficult targets. We carried out local docking perturbations for each target, using the unbound structures when available, in both RosettaDock v2.3 and v3.2. Overall the performances of RosettaDock v2.3 and v3.2 were similar. RosettaDock v3.2 achieved 56 docking funnels, compared to 49 in v2.3. A breakdown of docking performance by protein complex type shows that RosettaDock v3.2 achieved docking funnels for 63% of antibody-antigen targets, 62% of enzyme-inhibitor targets, and 35% of ‘other’ targets. In terms of docking difficulty, RosettaDock v3.2 achieved funnels for 58% of rigid-body targets, 30% of medium targets, and 14% of difficult targets. For targets that failed, we carry out additional analyses to identify the cause of failure, which showed that binding-induced backbone conformation changes account for a majority of failures. We also present a bootstrap statistical analysis that quantifies the reliability of the stochastic docking results. Finally, we demonstrate the additional functionality available in RosettaDock v3.2 by incorporating small-molecules and non-protein co-factors in docking of a smaller target set. This study marks the most extensive benchmarking of the RosettaDock module to date and establishes a baseline for future research in protein interface modeling and structure prediction

Similarity of Traveling-Wave Delays in the Hearing Organs of Humans and Other Tetrapods

Transduction of sound in mammalian ears is mediated by basilar-membrane waves exhibiting delays that increase systematically with distance from the cochlear base. Most contemporary accounts of such “traveling-wave” delays in humans have ignored postmortem basilar-membrane measurements in favor of indirect in vivo estimates derived from brainstem-evoked responses, compound action potentials, and otoacoustic emissions. Here, we show that those indirect delay estimates are either flawed or inadequately calibrated. In particular, we argue against assertions based on indirect estimates that basilar-membrane delays are much longer in humans than in experimental animals. We also estimate in vivo basilar-membrane delays in humans by correcting postmortem measurements in humans according to the effects of death on basilar-membrane vibrations in other mammalian species. The estimated in vivo basilar-membrane delays in humans are similar to delays in the hearing organs of other tetrapods, including those in which basilar membranes do not sustain traveling waves or that lack basilar membranes altogether

Fused Traditional and Geometric Morphometrics Demonstrate Pinniped Whisker Diversity

Vibrissae (whiskers) are important components of the mammalian tactile sensory system, and primarily function as detectors of vibrotactile information from the environment. Pinnipeds possess the largest vibrissae among mammals and their vibrissal hair shafts demonstrate a diversity of shapes. The vibrissae of most phocid seals exhibit a beaded morphology with repeating sequences of crests and troughs along their length. However, there are few detailed analyses of pinniped vibrissal morphology, and these are limited to a few species. Therefore, we comparatively characterized differences in vibrissal hair shaft morphologies among phocid species with a beaded profile, phocid species with a smooth profile, and otariids with a smooth profile using traditional and geometric morphometric methods. Traditional morphometric measurements (peak-to-peak distance, crest width, trough width and total length) were collected using digital photographs. Elliptic Fourier analysis (geometric morphometrics) was used to quantify the outlines of whole vibrissae. The traditional and geometric morphometric datasets were subsequently combined by mathematically scaling each to true rank, followed by a single eigendecomposition. Quadratic discriminant function analysis demonstrated that 79.3, 97.8 and 100% of individuals could be correctly classified to their species based on vibrissal shape variables in the traditional, geometric and combined morphometric analyses, respectively. Phocids with beaded vibrissae, phocids with smooth vibrissae, and otariids each occupied distinct morphospace in the geometric morphometric and combined data analyses. Otariids split into two groups in the geometric morphometric analysis and gray seals appeared intermediate between beaded- and smooth-whiskered species in the traditional and combined analyses. Vibrissal hair shafts modulate the transduction of environmental stimuli to the mechanoreceptors in the follicle-sinus complex (F-SC), which results in vibrotactile reception, but it is currently unclear how the diversity of shapes affects environmental signal modulation

Predicting the impact of Lynch syndrome-causing missense mutations from structural calculations

Accurate methods to assess the pathogenicity of mutations are needed to fully leverage the possibilities of genome sequencing in diagnosis. Current data-driven and bioinformatics approaches are, however, limited by the large number of new variations found in each newly sequenced genome, and often do not provide direct mechanistic insight. Here we demonstrate, for the first time, that saturation mutagenesis, biophysical modeling and co-variation analysis, performed in silico, can predict the abundance, metabolic stability, and function of proteins inside living cells. As a model system, we selected the human mismatch repair protein, MSH2, where missense variants are known to cause the hereditary cancer predisposition disease, known as Lynch syndrome. We show that the majority of disease-causing MSH2 mutations give rise to folding defects and proteasome-dependent degradation rather than inherent loss of function, and accordingly our in silico modeling data accurately identifies disease-causing mutations and outperforms the traditionally used genetic disease predictors. Thus, in conclusion, in silico biophysical modeling should be considered for making genotype-phenotype predictions and for diagnosis of Lynch syndrome, and perhaps other hereditary diseases

Mapping genetic variations to three- dimensional protein structures to enhance variant interpretation: a proposed framework

The translation of personal genomics to precision medicine depends on the accurate interpretation of the multitude of genetic variants observed for each individual. However, even when genetic variants are predicted to modify a protein, their functional implications may be unclear. Many diseases are caused by genetic variants affecting important protein features, such as enzyme active sites or interaction interfaces. The scientific community has catalogued millions of genetic variants in genomic databases and thousands of protein structures in the Protein Data Bank. Mapping mutations onto three-dimensional (3D) structures enables atomic-level analyses of protein positions that may be important for the stability or formation of interactions; these may explain the effect of mutations and in some cases even open a path for targeted drug development. To accelerate progress in the integration of these data types, we held a two-day Gene Variation to 3D (GVto3D) workshop to report on the latest advances and to discuss unmet needs. The overarching goal of the workshop was to address the question: what can be done together as a community to advance the integration of genetic variants and 3D protein structures that could not be done by a single investigator or laboratory? Here we describe the workshop outcomes, review the state of the field, and propose the development of a framework with which to promote progress in this arena. The framework will include a set of standard formats, common ontologies, a common application programming interface to enable interoperation of the resources, and a Tool Registry to make it easy to find and apply the tools to specific analysis problems. Interoperability will enable integration of diverse data sources and tools and collaborative development of variant effect prediction methods