Even as the study of plant genomics rapidly develops through the use of high-throughput sequencing techniques, traditional plant phenotyping lags far behind. Here we develop a high-throughput rice phenotyping facility (HRPF) to monitor 13 traditional agronomic traits and 2 newly defined traits during the rice growth period. Using genome-wide association studies (GWAS) of the 15 traits, we identify 141 associated loci, 25 of which contain known genes such as the Green Revolution semi-dwarf gene, SD1. Based on a performance evaluation of the HRPF and GWAS results, we demonstrate that high-throughput phenotyping has the potential to replace traditional phenotyping techniques and can provide valuable gene identification information. The combination of the multifunctional phenotyping tools HRPF and GWAS provides deep insights into the genetic architecture of important traits.

With increasing demand for novel traits in crop breeding, the plant research community faces the challenge of quantitatively analyzing the structure and function of large numbers of plants. A clear goal of high-throughput phenotyping is to bridge the gap between genomics and phenomics. In this study, we quantified 106 traits from a maize (Zea mays) recombinant inbred line population (n = 167) across 16 developmental stages using the automatic phenotyping platform. Quantitative trait locus (QTL) mapping with a high-density genetic linkage map, including 2,496 recombinant bins, was used to uncover the genetic basis of these complex agronomic traits, and 988 QTLs have been identified for all investigated traits, including three QTL hotspots. Biomass accumulation and final yield were predicted using a combination of dissected traits in the early growth stage. These results reveal the dynamic genetic architecture of maize plant growth and enhance ideotype-based maize breeding and prediction.

Understanding how plants respond to drought can benefit drought resistance (DR) breeding. Using a non-destructive phenotyping facility, 51 image-based traits (i-traits) for 507 rice accessions were extracted. These i-traits can be used to monitor drought responses and evaluate DR. High heritability and large variation of these traits was observed under drought stress in the natural population. A genome-wide association study (GWAS) of i-traits and traditional DR traits identified 470 association loci, some containing known DR-related genes. Of these 470 loci, 443 loci (94%) were identified using i-traits, 437 loci (93%) co-localized with previously reported DR-related quantitative trait loci, and 313 loci (66.6%) were reproducibly identified by GWAS in different years. Association networks, established based on GWAS results, revealed hub i-traits and hub loci. This demonstrates the feasibility and necessity of dissecting the complex DR trait into heritable and simple i-traits. As proof of principle, we illustrated the power of this integrated approach to identify previously unreported DR-related genes. OsPP15 was associated with a hub i-trait, and its role in DR was confirmed by genetic transformation experiments. Furthermore, i-traits can be used for DR linkage analyses, and 69 i-trait locus associations were identified by both GWAS and linkage analysis of a recombinant inbred line population. Finally, we confirmed the relevance of i-traits to DR in the field. Our study provides a promising novel approach for the genetic dissection and discovery of causal genes for DR.

Loss of airway epithelial integrity contributes significantly to asthma pathogenesis. Thymic stromal lymphopoietin (TSLP) may have dual immunoregulatory roles. In inflammatory disorders of the bowel, the long isoform of TSLP (lfTSLP) promotes inflammation while the short isoform (sfTSLP) inhibits inflammation. We hypothesize that lfTSLP contributes to house dust mite (HDM)-induced airway epithelial barrier dysfunction and that synthetic sfTSLP can prevent these effects. In vitro, airway epithelial barrier function was assessed by monitoring transepithelial electrical resistance, fluorescent-dextran permeability, and distribution of E-cadherin and β-catenin. In vivo, BALB/c mice were exposed to HDM by nasal inhalation for 5 consecutive days per week to establish an asthma model. sfTSLP and 1α,25-Dihydroxyvitamin D3 (1,25D3) were administered 1 h before HDM exposure. After 8 weeks, animal lung function tests and pathological staining were performed to evaluate asthma progression. We found that HDM and lfTSLP impaired barrier function. Treatment with sfTSLP and 1,25D3 prevented HDM-induced airway epithelial barrier disruption. Moreover, sfTSLP and 1,25D3 treatment ameliorated HDM-induced asthma in mice. Our data emphasize the importance of the different expression patterns and biological properties of sfTSLP and lfTSLP. Moreover, our results indicate that sfTSLP and 1,25D3 may serve as novel therapeutic agents for individualized treatment of asthma.

HighlightA combination of high-throughput leaf phenotyping and genome-wide association analysis provides valuable insights into the genetic basis of rice leaf traits.

The evaluation of yield-related traits is an essential step in rice breeding, genetic research and functional genomics research. A new, automatic, and labor-free facility to automatically thresh rice panicles, evaluate rice yield traits, and subsequently pack filled spikelets is presented in this paper. Tests showed that the facility was capable of evaluating yield-related traits with a mean absolute percentage error of less than 5% and an efficiency of 1440 plants per continuous 24 h workday.

Depression involving neuroinflammation is one of the most common disabling and life-threatening psychiatric disorders. Phosphodiesterase 4 (PDE4) inhibitors produce potent antidepressant-like and cognition-enhancing effects. However, their clinical utility is limited by their major side effect of emesis. To obtain more selective PDE4 inhibitors with antidepressant and anti-neuroinflammation potential and less emesis, we designed and synthesized a series of N-alkyl catecholamides by modifying the 4-methoxybenzyl group of our hit compound, FCPE07, with an alkyl side chain. Among these compounds, 10 compounds displayed submicromolar IC values in the mid- to low-nanomolar range. Moreover, 4-difluoromethoxybenzamides 10g and 10j, bearing isopropyl groups, exhibited the highest PDE4 inhibitory activities, with IC values in the low-nanomolar range and with higher selectivities for PDE4 (approximately 5000-fold and 2100-fold over other PDEs, respectively). Furthermore, compound 10j displayed anti-neuroinflammation potential, promising antidepressant-like effects, and a zero incidence rate of emesis at 0.8 mg/kg within 180 min.

BackgroundClinical outcome of adrenocortical carcinoma (ACC) varies because of its heterogeneous nature and reliable prognostic prediction model for adult ACC patients is limited. The objective of this study was to develop and externally validate a nomogram for overall survival (OS) prediction in adult patients with ACC after surgery.MethodsBased on the data from the Surveillance Epidemiology, and End Results (SEER) database, adults patients diagnosed with ACC between January 1988 and December 2015 were identified and classified into a training set, comprised of 404 patients diagnosed between January 2007 and December 2015, and an internal validation set, comprised of 318 patients diagnosed between January 1988 and December 2006. The endpoint of this study was OS. The nomogram was developed using a multivariate Cox proportional hazards regression algorithm in the training set and its performance was evaluated in terms of its discriminative ability, calibration, and clinical usefulness. The nomogram was then validated using the internal SEER validation, also externally validated using the Cancer Genome Atlas set (TCGA, 82 patients diagnosed between 1998 and 2012) and a Chinese multicenter cohort dataset (82 patients diagnosed between December 2002 and May 2018), respectively.ResultsAge at diagnosis, T stage, N stage, and M stage were identified as independent predictors for OS. A nomogram incorporating these four predictors was constructed using the training set and demonstrated good calibration and discrimination (C-index 95% confidence interval [CI], 0.715 [0.679–0.751]), which was validated in the internal validation set (C-index [95% CI], 0.672 [0.637–0.707]), the TCGA set (C-index [95% CI], 0.810 [0.732–0.888]) and the Chinese multicenter set (C-index [95% CI], 0.726 [0.633–0.819]), respectively. Encouragingly, the nomogram was able to successfully distinguished patients with a high-risk of mortality in all enrolled patients and in the subgroup analyses. Decision curve analysis indicated that the nomogram was clinically useful and applicable.ConclusionsThe study presents a nomogram that incorporates clinicopathological predictors, which can accurately predict the OS of adult ACC patients after surgery. This model and the corresponding risk classification system have the potential to guide therapy decisions after surgery.