Using drone-retrieved multispectral data for phenomic selection in potato breeding.

Predictive breeding approaches, like phenomic or genomic selection, have the potential to increase the selection gain for potato breeding programs which are characterized by very large numbers of entries in early stages and the availability of very few tubers per entry in these stages. The objectives of this study were to (i) explore the capabilities of phenomic prediction based on drone-derived multispectral reflectance data in potato breeding by testing different prediction scenarios on a diverse panel of tetraploid potato material from all market segments and considering a broad range of traits, (ii) compare the performance of phenomic and genomic predictions, and (iii) assess the predictive power of mixed relationship matrices utilizing weighted SNP array and multispectral reflectance data. Predictive abilities of phenomic prediction scenarios varied greatly within a range of - 0.15 and 0.88 and were strongly dependent on the environment, predicted trait, and considered prediction scenario. We observed high predictive abilities with phenomic prediction for yield (0.45), maturity (0.88), foliage development (0.73), and emergence (0.73), while all other traits achieved higher predictive ability with genomic compared to phenomic prediction. When a mixed relationship matrix was used for prediction, higher predictive abilities were observed for 20 out of 22 traits, showcasing that phenomic and genomic data contained complementary information. We see the main application of phenomic selection in potato breeding programs to allow for the use of the principle of predictive breeding in the pot seedling or single hill stage where genotyping is not recommended due to high costs.

A phenome-wide association study (PheWAS) to identify the health impacts of 4-cresol sulfate in the Nagahama Study.

Gut-microbiota derived metabolites are important regulators of host biology and metabolism. To understand the impacts of the microbial metabolite 4-cresol sulfate (4-CS) on four chronic diseases [type 2 diabetes mellitus, metabolic syndrome (MetS), non-alcoholic fatty liver disease, and chronic kidney disease (CKD)], we conducted association analyses of plasma 4-CS quantified by liquid chromatography coupled to mass spectrometry (LC-MS) in 3641 participants of the Nagahama study. Our results validated the elevation of 4-CS in CKD and identified a reducing trend in MetS. To delineate the holistic effects of 4-CS, we performed a phenome-wide association analysis (PheWAS) with 937 intermediate biological and behavioral traits. We detected associations between 4-CS and 39 phenotypes related to blood pressure regulation, hepatic and renal functions, hematology, sleep quality, intraocular pressure, ion regulation, ketone and fatty acid metabolisms, disease history and dietary habits. Among them, 19 PheWAS significant traits, including fatty acids and 14 blood pressure indices, were correlated with MetS, suggesting that 4-CS is a potential biomarker for MetS. Consistent associations of this gut microbial-derived metabolite on multiple endophenotypes underlying distinct etiopathogenesis support its role in the overall host health, with prospects of probiotic-based therapeutic solutions in chronic diseases.

Phenome-wide association study and precision medicine of cardiovascular diseases in the post-COVID-19 era.

SARS-CoV-2 infection causes injuries of not only the lungs but also the heart and endothelial cells in vasculature of multiple organs, and induces systemic inflammation and immune over-reactions, which makes COVID-19 a disease phenome that simultaneously affects multiple systems. Cardiovascular diseases (CVD) are intrinsic risk and causative factors for severe COVID-19 comorbidities and death. The wide-spread infection and reinfection of SARS-CoV-2 variants and the long-COVID may become a new common threat to human health and propose unprecedented impact on the risk factors, pathophysiology, and pharmacology of many diseases including CVD for a long time. COVID-19 has highlighted the urgent demand for precision medicine which needs new knowledge network to innovate disease taxonomy for more precise diagnosis, therapy, and prevention of disease. A deeper understanding of CVD in the setting of COVID-19 phenome requires a paradigm shift from the current phenotypic study that focuses on the virus or individual symptoms to phenomics of COVID-19 that addresses the inter-connectedness of clinical phenotypes, i.e., clinical phenome. Here, we summarize the CVD manifestations in the full clinical spectrum of COVID-19, and the phenome-wide association study of CVD interrelated to COVID-19. We discuss the underlying biology for CVD in the COVID-19 phenome and the concept of precision medicine with new phenomic taxonomy that addresses the overall pathophysiological responses of the body to the SARS-CoV-2 infection. We also briefly discuss the unique taxonomy of disease as Zheng-hou patterns in traditional Chinese medicine, and their potential implications in precision medicine of CVD in the post-COVID-19 era.

A comparative analysis of genomic and phenomic predictions of growth-related traits in 3-way coffee hybrids.

Genomic prediction has revolutionized crop breeding despite remaining issues of transferability of models to unseen environmental conditions and environments. Usage of endophenotypes rather than genomic markers leads to the possibility of building phenomic prediction models that can account, in part, for this challenge. Here, we compare and contrast genomic prediction and phenomic prediction models for 3 growth-related traits, namely, leaf count, tree height, and trunk diameter, from 2 coffee 3-way hybrid populations exposed to a series of treatment-inducing environmental conditions. The models are based on 7 different statistical methods built with genomic markers and ChlF data used as predictors. This comparative analysis demonstrates that the best-performing phenomic prediction models show higher predictability than the best genomic prediction models for the considered traits and environments in the vast majority of comparisons within 3-way hybrid populations. In addition, we show that phenomic prediction models are transferrable between conditions but to a lower extent between populations and we conclude that chlorophyll a fluorescence data can serve as alternative predictors in statistical models of coffee hybrid performance. Future directions will explore their combination with other endophenotypes to further improve the prediction of growth-related traits for crops.

A phenomics approach for antiviral drug discovery.

BACKGROUND: The emergence and continued global spread of the current COVID-19 pandemic has highlighted the need for methods to identify novel or repurposed therapeutic drugs in a fast and effective way. Despite the availability of methods for the discovery of antiviral drugs, the majority tend to focus on the effects of such drugs on a given virus, its constituent proteins, or enzymatic activity, often neglecting the consequences on host cells. This may lead to partial assessment of the efficacy of the tested anti-viral compounds, as potential toxicity impacting the overall physiology of host cells may mask the effects of both viral infection and drug candidates. Here we present a method able to assess the general health of host cells based on morphological profiling, for untargeted phenotypic drug screening against viral infections. RESULTS: We combine Cell Painting with antibody-based detection of viral infection in a single assay. We designed an image analysis pipeline for segmentation and classification of virus-infected and non-infected cells, followed by extraction of morphological properties. We show that this methodology can successfully capture virus-induced phenotypic signatures of MRC-5 human lung fibroblasts infected with human coronavirus 229E (CoV-229E). Moreover, we demonstrate that our method can be used in phenotypic drug screening using a panel of nine host- and virus-targeting antivirals. Treatment with effective antiviral compounds reversed the morphological profile of the host cells towards a non-infected state. CONCLUSIONS: The phenomics approach presented here, which makes use of a modified Cell Painting protocol by incorporating an anti-virus antibody stain, can be used for the unbiased morphological profiling of virus infection on host cells. The method can identify antiviral reference compounds, as well as novel antivirals, demonstrating its suitability to be implemented as a strategy for antiviral drug repurposing and drug discovery.

Antidepressant Screening Demonstrated Non-Monotonic Responses to Amitriptyline, Amoxapine and Sertraline in Locomotor Activity Assay in Larval Zebrafish.

Antidepressants are well-known drugs to treat depression and major depressive disorder for humans. However, the misuse and abuse of antidepressants keep increasing with several side effects reported. The aim of this study was to assess the potential adverse effects of 18 antidepressants by monitoring zebrafish larval locomotor activity performance based on the total distance traveled, burst movement count, and total rotation count at four dark-light intercalated phases. In general, zebrafish larvae displayed sedative effects after antidepressant exposure by showing a significant reduction in all of the locomotor activity-related endpoints. However, three antidepressants i.e., amitriptyline, amoxapine, and sertraline were able to trigger a significantly high locomotor activity in zebrafish larvae during the light cycle. These differences might be due to the pharmacologic differences among the antidepressants. In addition, since each antidepressant possesses a different dosage range from the other, overdoses of these antidepressants might also be the causes of these differences. Furthermore, based on these results, a further study was conducted to observe the effect of these three antidepressants in lower concentrations. From the results, biphasic effects in terms of zebrafish larval locomotor activity were demonstrated by these drugs. Even though further studies are still required to validate the mechanism, these findings indicate that these antidepressants might share a common mechanism responsible for their effects on zebrafish larval locomotor activity although there were some differences in potency of these effects.

Single-cell infrared phenomics: phenotypic screening with infrared microspectroscopy.

We conceptually demonstrate single-cell infrared phenomics as a novel strategy of phenotypic screening with infrared microspectroscopy. Based on this development, the cancer cell HepG2 glycocalyx was first identified as a potential target of protopanaxadiol, an herbal medicine. These findings provide a powerful tool to accurately evaluate the cell stress response and to largely expand the phenotypic screening toolkit for drug discovery.

Association between habitual coffee consumption and multiple disease outcomes: A Mendelian randomisation phenome-wide association study in the UK Biobank.

BACKGROUND: Coffee is the most commonly consumed beverage in the world after water, however the debate as to whether coffee consumption is beneficial or detrimental to health continues. Current evidence of the link between coffee and health outcomes is predominately observational, thus subject to methodological issues such a confounding and reverse causation. METHODS: This Mendelian randomisation phenome-wide association study (MR-PheWAS) used information from up to 333,214 participants of White-British ancestry in the UK Biobank to examine the causal association between genetically instrumented habitual coffee consumption and the full range of disease outcomes. We constructed a genetic risk score for habitual coffee consumption and screened for associations with disease outcomes across 1117 case-control series. All signals under false discovery rate controlled threshold (5.8 × 10-4) were followed by Mendelian randomisation (MR) analyses, with replication in independent data sources where possible. RESULTS: The initial phenome-wide association analysis identified signals for 13 outcomes representing five distinct diseases. The strongest signal was seen for gout (P = 2.3 × 10-12), but there was notable pleiotropy (Pdistortion <0.001) and MR analyses did not support an association with habitual coffee consumption (inverse variance weighted MR OR 0.41, 95% CI 0.08 to 2.25, P = 0.31). Support for a possible causal relationship between habitual coffee consumption was only obtained for four distinct disease outcomes, including an increased odds of osteoarthrosis (OR 1.23, 95% CI 1.11 to 1.35), other arthropathies (OR 1.22, 95% CI 1.12 to 1.33) and overweight (OR 1.28, 95% CI 1.05 to 1.56), and a lower odds of postmenopausal bleeding (OR 0.72, 95% CI 0.63 to 0.82). Evidence for an association between habitual coffee consumption and these four diseases was also supported by phenotypic associations with self-reported coffee consumption. CONCLUSIONS: This large-scale MR-PheWAS provided little evidence for notable harm or benefit with respect to higher habitual coffee consumption. The only evidence for harm was seen with respect to osteoarthrosis, other arthropathies and obesity.

Phenomics reveals a novel putative chloroplast fatty acid transporter in the marine diatom Skeletonema marinoi involved in temperature acclimation.

Diatoms are the dominant phytoplankton in temperate oceans and coastal regions and yet little is known about the genetic basis underpinning their global success. Here, we address this challenge by developing the first phenomic approach for a diatom, screening a collection of randomly mutagenized but identifiably tagged transformants. Based upon their tolerance to temperature extremes, several compromised mutants were identified revealing genes either stress related or encoding hypothetical proteins of unknown function. We reveal one of these hypothetical proteins is a novel putative chloroplast fatty acid transporter whose loss affects several fatty acids including the two omega-3, long-chain polyunsaturated fatty acids - eicosapentaenoic and docosahexaenoic acid, both of which have medical importance as dietary supplements and industrial significance in aquaculture and biofuels. This mutant phenotype not only provides new insights into the fatty acid biosynthetic pathways in diatoms but also highlights the future value of phenomics for revealing specific gene functions in these ecologically important phytoplankton.

Health effects associated with serum calcium concentrations: evidence from MR-PheWAS analysis in UK Biobank.

We conducted a phenome-wide Mendelian randomization analysis (MR-PheWAS) to survey health effects associated with high normal serum calcium. We found causal evidence for conditions related to renal function, bone and joint health, and cardiovascular risk. These conditions collectively suggest that tissue calcification may be a key mechanism through which serum calcium influences health. INTRODUCTION: Calcium is essential for the normal functioning of the cardiovascular system, muscles, and nerves. In this MR-PheWAS study, we sought to capture the totality of health effects associated with high normal serum calcium. METHODS: We used data from up to 337,535 UK Biobank participants, and tested for associations between calcium genetic score (calcium-GS) and 925 disease outcomes, with follow-up analyses using complementary MR methods. RESULTS: Calcium-GS was robustly associated with serum calcium concentration (F statistics = 349). After multiple testing correction (P < 1.62E-4), we saw genetic evidence for an association between high serum calcium and urinary calculus (OR per 1 mg/dl 3.5, 95%CI 1.3-9.2), renal colic (9.1, 95%CI 2.5-33.5), and allergy/adverse effect of penicillin (2.2, 95%CI 1.5-3.3). Secondary analyses with independent replication from consortia meta-analyses suggested further effects on myocardial infarction and osteoarthrosis. CONCLUSION: We found causal evidence for effects of high normal serum calcium with conditions related to renal function, bone and joint health, and cardiovascular risk, which may collectively reflect influences on tissue calcification and immune function.