Differential gene expression and gene variants drive color and pattern development in divergent color morphs of a mimetic poison frog, bioRxiv, 2019-07-22

AbstractEvolutionary biologists have long investigated the ecological contexts, evolutionary forces, and proximate mechanisms that produce the diversity of animal coloration we see in the natural world. In aposematic species, color and pattern is directly tied to survival and thus understanding the origin of the phenotype has been a focus of both theoretical and empirical inquiry. In order to better understand this diversity, we examined gene expression in skin tissue during development in four different color morphs of the aposematic mimic poison frog, Ranitomeya imitator. We identified a suite of candidate color-related genes a priori and identified the pattern of expression in these genes over time, differences in expression of these genes between the mimetic morphs, and genetic variants that differ between color morphs. We identified several candidate color genes that are differentially expressed over time or across populations, as well as a number of color genes with fixed genetic variants between color morphs. Many of the color genes we discovered in our dataset are involved in the canonical Wnt signaling pathway, including several fixed SNPs between color morphs. Further, many genes in this pathway were differentially expressed at different points in development (e.g., lef1, tyr, tyrp1). Importantly, Wnt signaling pathway genes are overrepresented relative to expression in Xenopus tropicalis. Taken together, this provides evidence that the Wnt signaling pathway is contributing to color pattern production in R. imitator, and is an excellent candidate for producing some of the differences in color pattern between morphs. In addition, we found evidence that sepiapterin reductase is likely important in the production of yellow-green coloration in this adaptive radiation. Finally, two iridophore genes (arfap1, gart) draw a strong parallel to previous work in another dendrobatid, indicating that these genes are also strong candidates for differential color production. We have used high throughput sequencing throughout development to examine the evolution of coloration in a rapid mimetic adaptive radiation and found that these divergent color patterns are likely to be affected by a combination of developmental patterns of gene expression, color morph-specific gene expression, and color morph-specific gene variants.

biorxiv evolutionary-biology 0-100-users 2019

RootNav 2.0 Deep Learning for Automatic Navigation of Complex Plant Root Architectures, bioRxiv, 2019-07-20

AbstractWe present a new image analysis approach that provides fully-automatic extraction of complex root system architectures from a range of plant species in varied imaging setups. Driven by modern deep-learning approaches, RootNav 2.0 replaces previously manual and semi-automatic feature extraction with an extremely deep multi-task Convolutional Neural Network architecture. The network has been designed to explicitly combine local pixel information with global scene information in order to accurately segment small root features across high-resolution images. In addition, the network simultaneously locates seeds, and first and second order root tips to drive a search algorithm seeking optimal paths throughout the image, extracting accurate architectures without user interaction. The proposed method is evaluated on images of wheat (Triticum aestivum L.) from a seedling assay. The results are compared with semi-automatic analysis via the original RootNav tool, demonstrating comparable accuracy, with a 10-fold increase in speed. We then demonstrate the ability of the network to adapt to different plant species via transfer learning, offering similar accuracy when transferred to an Arabidopsis thaliana plate assay. We transfer for a final time to images of Brassica napus from a hydroponic assay, and still demonstrate good accuracy despite many fewer training images. The tool outputs root architectures in the widely accepted RSML standard, for which numerous analysis packages exist (<jatsext-link xmlnsxlink=httpwww.w3.org1999xlink ext-link-type=uri xlinkhref=httprootsystemml.github.io>httprootsystemml.github.io<jatsext-link>), as well as segmentation masks compatible with other automated measurement tools.

biorxiv bioinformatics 0-100-users 2019

Tree Lab Portable genomics for early detection of plant viruses and pests in Sub-Saharan Africa, bioRxiv, 2019-07-20

AbstractIn this case study we successfully teamed the PDQeX DNA purification technology developed by MicroGEM, New Zealand, with the MinION and MinIT mobile sequencing devices developed by Oxford Nanopore Technologies to produce an effective point-of-need field diagnostic system. The PDQeX extracts DNA using a cocktail of thermophilic proteinases and cell wall degrading enzymes, thermo-responsive extractor cartridges and a temperature control unit. This single-step closed system delivers purified DNA with no cross contamination. The MinIT is a newly released data processing unit that converts MinION raw signal output into base called data locally in real time, removing the need for high specification computers and large file transfers from the field. All three devices are battery powered with an exceptionally small footprint that facilitates transport and set up.To evaluate and validate capability of the system for unbiased pathogen identification by realtime sequencing in a farmer’s field setting, we analysed samples collected from cassava plants grown by subsistence farmers in three sub-Sahara African countries (Tanzania, Uganda and Kenya). A range of viral pathogens, all with similar symptoms, greatly reduce yield or completely destroy cassava crops. 800 million people worldwide depend on cassava for food and yearly income, and viral diseases are a significant constraint on its production (<jatsext-link xmlnsxlink=httpwww.w3.org1999xlink ext-link-type=uri xlinkhref=httpscassavavirusactionproject.com>httpscassavavirusactionproject.com<jatsext-link>). Early pathogen detection at a molecular level has great potential to rescue crops within a single growing season by providing results that inform decisions on disease management, use of appropriate virus resistant or replacement planting.This case study presented conditions of working in-field with limited or no access to mains power, laboratory infrastructure, internet connectivity and highly variable ambient temperature. An additional challenge is that, generally, plant material contains inhibitors of downstream molecular processes making effective DNA purification critical. We successfully undertook real-time on-farm genome sequencing of samples collected from cassava plants on three farms, one in each country. Cassava mosaic begomoviruses were detected by sequencing leaf, stem, tuber and insect samples. The entire process, from arrival on farm to diagnosis including sample collection, processing and provisional sequencing results was complete in under 4 hours. The need for accurate, rapid and on-site diagnosis grows as globalized human activity accelerates. This technical breakthrough has applications that are relevant to human and animal health, environmental management and conservation.

biorxiv genomics 100-200-users 2019

Comparison of adopted and non-adopted individuals reveals gene-environment interplay for education in the UK Biobank, bioRxiv, 2019-07-19

AbstractIndividual-level polygenic scores can now explain ∼10% of the variation in number of years of completed education. However, associations between polygenic scores and education capture not only genetic propensity but information about the environment that individuals are exposed to. This is because individuals passively inherit effects of parental genotypes, since their parents typically also provide the rearing environment. In other words, the strong correlation between offspring and parent genotypes results in an association between the offspring genotypes and the rearing environment. This is termed passive gene-environment correlation. We present an approach to test for the extent of passive gene-environment correlation for education without requiring intergenerational data. Specifically, we use information from 6311 individuals in the UK Biobank who were adopted in childhood to compare genetic influence on education between adoptees and non-adopted individuals. Adoptees’ rearing environments are less correlated with their genotypes, because they do not share genes with their adoptive parents. We find that polygenic scores are twice as predictive of years of education in non-adopted individuals compared to adoptees (R2= 0.074 vs 0.037, difference test p= 8.23 × 10−24). We provide another kind of evidence for the influence of parental behaviour on offspring education individuals in the lowest decile of education polygenic score attain significantly more education if they are adopted, possibly due to educationally supportive adoptive environments. Overall, these results suggest that genetic influences on education are mediated via the home environment. As such, polygenic prediction of educational attainment represents gene-environment correlations just as much as it represents direct genetic effects.

biorxiv genomics 100-200-users 2019

 

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