Butterfly speciation and the distribution of gene effect sizes fixed during adaptation

Mimicry has had a significant historical influence as a tractable system for studying adaptation and is known to play a role in speciation. Here, we discuss recent theoretical treatment of adaptive walks to local adaptive peaks and contrast this with the adaptive landscape of mimicry. Evolution of novel Müllerian mimicry patterns almost certainly involves substitution of a major mutation to provide an initial similarity to the model, such that major gene effects are expected to an even greater degree than for other adaptive traits. The likelihood of large adaptive peak shifts in mimicry evolution may therefore promote speciation. In addition, mimicry adaptive peaks are determined by the local abundance of particular patterns and may be more fluid than the case for other traits. It will therefore be of considerable interest to test empirically the distribution of effect sizes fixed during mimicry evolution. Here, we show the feasibility of this by presenting a preliminary quantitative trait locus (QTL) analysis of Heliconius colour patterns. This shows that a number of modifier loci of different effect sizes influence forewing band morphology. We also show multiple pleiotropic effects of major Heliconius patterning loci and discuss the likelihood of multiple substitutions at the same loci in pattern evolution, which would inflate the importance of major loci in QTL analysis of the gene effect sizes. Analyses such as these have the potential to uncover the genetic architecture of both within and between species adaptive differences.     

Natural Genetic Variation in Selected Populations of Arabidopsis thaliana Is Associated with Ionomic Differences

Controlling elemental composition is critical for plant growth and development as well as the nutrition of humans who utilize plants for food. Uncovering the genetic architecture underlying mineral ion homeostasis in plants is a critical first step towards understanding the biochemical networks that regulate a plant''s elemental composition (ionome). Natural accessions of Arabidopsis thaliana provide a rich source of genetic diversity that leads to phenotypic differences. We analyzed the concentrations of 17 different elements in 12 A. thaliana accessions and three recombinant inbred line (RIL) populations grown in several different environments using high-throughput inductively coupled plasma- mass spectroscopy (ICP-MS). Significant differences were detected between the accessions for most elements and we identified over a hundred QTLs for elemental accumulation in the RIL populations. Altering the environment the plants were grown in had a strong effect on the correlations between different elements and the QTLs controlling elemental accumulation. All ionomic data presented is publicly available at www.ionomicshub.org.     

Indolocarbazoles: potent, selective inhibitors of human cytomegalovirus replication.

In our search for new, safer anti-HCMV agents, we discovered that the natural product Arcyriaflavin A (la) was a potent inhibitor of HCMV replication in cell culture. A series of analogues (symmetrical indolocarbazoles) was synthesised to investigate structure activity relationships in this series against a range of herpes viruses (HCMV, VZV, HSV1, and 2). This identified a number of novel, selective and potent inhibitors of HCMV, 12,13-dihydro-2,10-difluoro-5H-indolo[2,3-a]pyrrolo[3,4-c]carbazol e-5,7-(6H)-dione (1d) being the best example (IC50=40 nM, therapeutic index > 1450). Compounds described in this series were generally poor inhibitors of protein kinase C betaII, and no correlation was found between the ability to inhibit HCMV and the enzyme PKC.     

South African mouse shrews (<Emphasis Type="Italic">Myosorex</Emphasis>) feel the heat: using species distribution models (SDMs) and IUCN Red List criteria to flag extinction risks due to climate change

Five species of mouse or forest shrews (Myosorex) are endemic to South Africa, Lesotho and Swaziland, four of which (Myosorex varius, Myosorex cafer, Myosorex longicaudatus and Myosorex cf. tenuis) are associated with montane or temperate grassland, fynbos and/or forest habitats while a fifth (Myosorex sclateri) is associated with lowland subtropical forests. Due to their small size, specialised habitat, low dispersal capacity, high metabolism and sensitivity to temperature extremes, we predicted that, particularly for montane species, future climate change should have a negative impact on area of occupancy (AOO) and ultimately extinction risks. Species distribution models (SDMs) indicated general declines in AOO of three species by 2050 under the A1b and A2 climate change scenarios (M. cafer, M. varius, M. longicaudatus) while two species (M. sclateri and M. cf. tenuis) remained unchanged (assuming no dispersal) or increased their AOO (assuming dispersal). While temperate species such as M. varius appear to be limited by temperature maxima (preferring cooler temperatures), the subtropical species M. sclateri appears to be limited by temperature minima (preferring warmer temperatures). Evidence for declines in AOO informed the uplisting (to a higher category of threat) of the Red List status of four Myosorex species to either vulnerable or endangered as part of a separate regional International Union for Conservation of Nature (IUCN) Red List assessment.     

Development and validation of a computational method for assessment of missense variants in hypertrophic cardiomyopathy

Assessing the significance of novel genetic variants revealed by DNA sequencing is a major challenge to the integration of genomic techniques with medical practice. Many variants remain difficult to classify by traditional genetic methods. Computational methods have been developed that could contribute to classifying these variants, but they have not been properly validated and are generally not considered mature enough to be used effectively in a clinical setting. We developed a computational method for predicting the effects of missense variants detected in patients with hypertrophic cardiomyopathy (HCM). We used a curated clinical data set of 74 missense variants in six genes associated with HCM to train and validate an automated predictor. The predictor is based on support vector regression and uses phylogenetic and structural features specific to genes involved in HCM. Ten-fold cross validation estimated our predictor's sensitivity at 94% (95% confidence interval: 83%-98%) and specificity at 89% (95% confidence interval: 72%-100%). This corresponds to an odds ratio of 10 for a prediction of pathogenic (95% confidence interval: 4.0-infinity), or an odds ratio of 9.9 for a prediction of benign (95% confidence interval: 4.6-21). Coverage (proportion of variants for which a prediction was made) was 57% (95% confidence interval: 49%-64%). This performance exceeds that of existing methods that are not specifically designed for HCM. The accuracy of this predictor provides support for the clinical use of automated predictions alongside family segregation and population frequency data in the interpretation of new missense variants and suggests future development of similar tools for other diseases.