PSEA: A phenotypic similarity ensemble approach for prioritizes candidate genes to aid mendelian disease diagnosis

Motivation: Next-generation sequencing is increasingly applied to the molecular diagnosis of genetic disorders. However, challenges for the interpretation of NGS data remain given the massive number of variants produced by NGS. Careful assessment is required to identify the most likely disease-causing variants that best match the patients' clinical phenotypes, which is highly experience-dependent and of low cost-effectiveness. Results: The human phenotype ontology (HPO) together with the information content (IC) are widely used for phenotypic similarity evaluation. Here, we introduce PSEA, a new phenotypic similarity evaluation tool capable of quantifying groups of HPO terms unbiasedly. By comparing with other methods, PSEA show optimal performance and show a higher tolerance to phenotypic noise or incompleteness. We also developed a web server for disease-causing gene prioritization and HPO-gene weighted linkage visualization. Availability: Source code and Web service are free available at https://github.com/zhonghua-wang/psea and https://phoenix.bgi.com/psea, respectively.

The Effect of Animal Bipedal Posture on Perceived Cuteness, Fear, and Willingness to Protect Them

Human–animal relationships have long been the subject of controversy because they are shaped by several cultural, inter-individual, and evolutionary factors. Understanding these relationships, however, is important to optimize conservation efforts. There is agreement that perceived similarity between animals and humans is associated with more positive attitudes. The human–animal similarity could be caused by phylogenetic closeness. We hypothesized that the bipedal posture of an animal may be perceived as a cue of phenotypic similarity with humans. We examined this topic by comparing perceived cuteness, fear, and willingness to protect animals differing in body posture, body size, and phylogenetic closeness with humans on a sample of N = 349 Slovak participants. We found that the bipedal posture enhanced perceived cuteness, but this effect was most pronounced in small-bodied animals, particularly those with direct eye contact. Phylogenetically close and small-bodied species (e.g., small mammals) received greater conservation support than phylogenetically distant species (e.g., invertebrates). However, anthropomorphic-looking animals received greater conservation support, suggesting that pictures of animals that more closely resemble humans can be used in conservation campaigns.

Phenotypic homogeneity in childhood epilepsies evolves in gene-specific patterns across 3251 patient-years of clinical data

While genetic studies of epilepsies can be performed in thousands of individuals, phenotyping remains a manual, non-scalable task. A particular challenge is capturing the evolution of complex phenotypes with age. Here, we present a novel approach, applying phenotypic similarity analysis to a total of 3251 patient-years of longitudinal electronic medical record data from a previously reported cohort of 658 individuals with genetic epilepsies. After mapping clinical data to the Human Phenotype Ontology, we determined the phenotypic similarity of individuals sharing each genetic etiology within each 3-month age interval from birth up to a maximum age of 25 years. 140 of 600 (23%) of all 27 genes and 3-month age intervals with sufficient data for calculation of phenotypic similarity were significantly higher than expect by chance. 11 of 27 genetic etiologies had significant overall phenotypic similarity trajectories. These do not simply reflect strong statistical associations with single phenotypic features but appear to emerge from complex clinical constellations of features that may not be strongly associated individually. As an attempt to reconstruct the cognitive framework of syndrome recognition in clinical practice, longitudinal phenotypic similarity analysis extends the traditional phenotyping approach by utilizing data from electronic medical records at a scale that is far beyond the capabilities of manual phenotyping. Delineation of how the phenotypic homogeneity of genetic epilepsies varies with age could improve the phenotypic classification of these disorders, the accuracy of prognostic counseling, and by providing historical control data, the design and interpretation of precision clinical trials in rare diseases.

A Novel Algorithm for Rare Disease Gene Prediction Based on Phenotypic Similarity

Genetic studies have yielded only a limited number of genes clearly implicated in endocrine disorders, in large part due to two current knowledge gaps. First, genome wide association studies (GWAS) of common diseases have yielded many associations that are hard to translate to causal genes and pathways. Second, whole exome sequencing (WES) studies have transformed diagnosis of rare diseases but often yield many variants of unknown significance that cannot yet be reliably prioritized for disease causality. We hypothesized that phenotypically similar diseases are more likely to share causal genes and pathways. Thus, genes implicated in a (rare or common) disease should be strong candidates to also contribute to a phenotypically similar disease. To test this hypothesis, we aggregated genes (a) for 3,209 rare diseases from OMIM and (b) nearby GWAS signals for 2,316 common diseases from the NHGRI/EBI GWAS catalog. We measured phenotypic similarity based on proximity in the Experimental Factor Ontology (EFO). Across ~2.7M common disease pairs, the number of genes shared increased with phenotypic similarity (Spearman p < 0.1). Similarly, across ~7.4M common and rare disease pairs and ~5.1M rare disease pairs, phenotypic similarity was significantly higher for disease pairs with at least one shared gene compared to those with no shared genes (T-test p < 0.05). We next developed an algorithm to predict genes for a rare disease based on its phenotypic similarity to other diseases and their known genes. Given a rare disease, the algorithm (a) identifies nearby diseases in the EFO; (b) collates their known genes and groups them into gene ontology (GO) terms; and (c) predicts the genes that occur in the most frequently observed GO term as potentially novel disease genes. We evaluated algorithm performance via cross-validation on rare diseases in OMIM. Across 140 rare endocrine diseases, the algorithm predicted on average 4.84 candidate genes with the correct (known but hidden by cross-validation) disease gene within the candidates 23.6% of the time; performance (5.11 candidates, 13.1% success rate) was similar for the other 3,069 rare diseases in OMIM. Examples include Leprechaunism (known gene INSR), for which genes INSR and TWIST2 were predicted based on phenotypic similarity to diseases Barber-Say syndrome, Rabson-Mendenhall syndrome and Gingival fibromatosis-hypertrichosis syndrome. Lubinsky syndrome (no known genes), for which genes ABCD1, LMNA, CNBP were predicted based on phenotypic similarity to diseases Ricker syndrome, X-ALD, DM1, Malouf syndrome, and Noonan syndrome. These data suggest that known phenotypic relationships and disease-gene databases can increase our ability to predict novel genes for less well-studied diseases, potentially speeding the biological translation of GWAS associations for common diseases and increasing the diagnostic yield of WES for rare diseases.

The Taxa of the Hyponephele lycaon – H. lupina Species Complex (Lepidoptera, Nymphalidae, Satyrinae): Deep DNA Barcode Divergence despite Morphological Similarity

The genus Hyponephele includes about 40 species distributed throughout the southern part of the Palaearctic area. Within this genus, the taxa of the H. lycaon – H. lupina species complex are similar with respect to the wing pattern and genitalia structure. Here we revise this group using analysis of butterfly morphology, DNA barcodes, and study of the type material. We show that, with a few exceptions, the species in this group are allopatric in distribution. Allopatry in combination with phenotypic similarity may be theoretically interpreted as evidence for the conspecifity of these taxa. Here we falsify this hypothesis by using DNA barcode analysis. We show that the species of this complex are genetically very distant and cannot be combined together as a polytypic species. We also demonstrate that H. lupina consists of two deeply diverged allopatric clades, H. lupina s. s. and H. mauritanica comb. & stat. nov. The barcode p-distance between these taxa (3.4-4.9%) is significantly higher than the generally accepted 'standard' minimum interspecific divergence (2.0-3.0% ) threshold. These two clades can also be distinguished by the color of the upperside of the wing in males (brown with conspicuous golden reflection in H. lupina ; dark brown without golden reflection in H. mauritanica) and by details in male genitalia and male androconia structures. Syntypes of Hyponephele sifanica, H. cheena cheena, H. cheena iskander, and H. cheena kashmirica are studied and figured.

It’s all relative: population estimates enhance kin recognition in the guppy

Kin recognition plays a fundamental role in social evolution, enabling active inbreeding avoidance, nepotism, and promoting cooperative social organization. Many organisms recognize kin based on phenotypic similarity – a process called phenotype matching – by comparing information associated with their own phenotype against the phenotypes of conspecifics. However, recent theory demonstrates that to accurately judge phenotypic similarity (and hence, relatedness), individuals require estimates of the population’s distribution of phenotypes as a “frame of reference.” Here, I use the Trinidadian guppy (Poecilia reticulata) to provide the first empirical test of this population estimation theory. I varied the phenotypic distributions of the groups in which focal individuals developed and found that, as adults, their patterns of inbreeding avoidance and nepotistic intrasexual competition differed as predicted by population estimation theory. Individuals reared with conspecifics more similar to themselves treated novel conspecifics as less closely related, suggesting a shifted population estimate. Individuals reared with more phenotypically variable conspecifics exhibited less extreme kin discrimination, suggesting a broader population estimate. These results provide experimental evidence that population estimates inform phenotype matching, and are acquired plastically through social experience. By calibrating phenotype matching to the population distribution of phenotypes, population estimation enhances kin recognition, increasing opportunities for the evolution of inbreeding avoidance and nepotism.

Feeding intensity of insect herbivores is associated more closely with key metabolite profiles than phylogenetic relatedness of their potential hosts

Determinants of the host ranges of insect herbivores are important from an evolutionary perspective and also have implications for applications such as biological control. Although insect herbivore host ranges typically are phylogenetically constrained, herbivore preference and performance ultimately are determined by plant traits, including plant secondary metabolites. Where such traits are phylogenetically labile, insect hervivore host ranges are expected to be phylogenetically disjunct, reflecting phenotypic similarities rather than genetic relatedness among potential hosts. We tested this hypothesis in the laboratory with a Brassicaceae-specialized weevil, Ceutorhynchus cardariae Korotyaev (Coleoptera: Curculionidae), on 13 test plant species differing in their suitability as hosts for the weevil. We compared the associations between feeding by C. cardariae and either phenotypic similarity (secondary chemistry—glucosinolate profile) or genetic similarity (sequence of the chloroplast gene ndhF) using two methods—simple correlations or strengths of association between feeding by each species, and dendrograms based on either glucosinolates or ndhF sequence (i.e., a phylogram). For comparison, we performed a similar test with the oligophagous Plutella xylostella (L.) (Lepidoptera: Plutellidae) using the same plant species. We found using either method that phenotypic similarity was more strongly associated with feeding intensity by C. cardariae than genetic similarity. In contrast, neither genetic nor phenotypic similarity was significantly associated with feeding intensity on the test species by P. xylostella. The result indicates that phenotypic traits can be more reliable indicators of the feeding preference of a specialist than phylogenetic relatedness of its potential hosts. This has implications for the evolution and maintenance of host ranges and host specialization in phytophagous insects. It also has implications for identifying plant species at risk of nontarget attack by potential weed biological control agents and hence the approach to prerelease testing.