A Comprehensive Interaction Network Constructed Using miRNAs and mRNAs Provides New Insights into Potato Tuberization under High Temperatures.

High temperatures delay tuberization and decrease potato (Solanum tuberosum L.) yields. However, the molecular mechanisms and regulatory networks underlying tuberization under high temperatures remain largely unknown. Here, we performed the mRNA and miRNA sequencing of leaves and stems to identify genes and regulatory networks involved in tuberization under high temperatures. A total of 2804 and 5001 differentially expressed genes (DEGs) under high-temperature stress were identified in leaves and stems, respectively. These genes were significantly enriched in gene ontology terms regarding meristem development, the sucrose biosynthetic process, and response to heat. Meanwhile, 101 and 75 differentially expressed miRNAs (DEmiRNAs) were identified in leaves and stems, respectively. We constructed an interaction network between DEmiRNAs and DEGs, identifying 118 and 150 DEmiRNA-DEG pairs in leaves and stems, respectively. We found three miRNA-mRNA candidate modules involved in tuberization under high temperatures, including stu-miR8030-5p/StCPY714, stu-miR7981f-p5/StAGL8a, and stu-miR10532A/StAGL8b. Our study constructed an interaction network between miRNAs and target genes and proposes candidate miRNA-gene modules that regulate tuber formation under high temperatures. Our study provides new insights for revealing the regulatory mechanism of the high-temperature inhibition of tuberization and also provides gene resources for improving the heat tolerance in potatoes.

OcBSA: An NGS-based bulk segregant analysis tool for outcross populations.

Constructing inbred lines for self-incompatible species and species with long generation times is challenging, making the use of F1 outcross/segregating populations the main strategy for genetic studies of such species. However, there is a lack of dedicated algorithms/tools for rapid quantitative trait locus (QTL) mapping using the F1 populations. To this end, we have designed and developed an algorithm/tool called OcBSA specifically for QTL mapping of F1 populations. OcBSA transforms the four-haplotype inheritance problem from the two heterozygous diploid parents of the F1 population into the two-haplotype inheritance problem common in current genetic studies by removing the two haplotypes from the heterozygous parent that do not contribute to phenotype segregation in the F1 population. Testing of OcBSA on 1800 simulated F1 populations demonstrated its advantages over other currently available tools in terms of sensitivity and accuracy. In addition, the broad applicability of OcBSA was validated by QTL mapping using seven reported F1 populations of apple, pear, peach, citrus, grape, tea, and rice. We also used OcBSA to map the QTL for flower color in a newly constructed F1 population of potato generated in this study. The OcBSA mapping result was verified by the insertion or deletion markers to be consistent with a previously reported locus harboring the ANTHOCYANIN 2 gene, which regulates potato flower color. Taken together, these results highlight the power and broad utility of OcBSA for QTL mapping using F1 populations and thus a great potential for functional gene mining in outcrossing species. For ease of use, we have developed both Windows and Linux versions of OcBSA, which are freely available at: https://gitee.com/Bioinformaticslab/OcBSA.

Phylogenetic and Expression Analysis of the Sucrose Synthase and Sucrose Phosphate Synthase Gene Family in Potatoes.

Sucrose synthase (SUS) and sucrose phosphate synthase (SPS) are essential in plant sucrose metabolism. The potato is an important crop worldwide, but systematic analyses of the StSUS and StSPS gene families in potatoes are still lacking. Ten sucrose metabolism-related genes were identified in this study. The SUSs and SPSs could each be split into three subgroups through phylogenetic analysis. StSUSIc was the most highly expressed gene in different developmental tissues. Ka/Ks analysis showed that StSUSIb and StSUSIc were subjected to more-significant homozygous selection pressure. Our cis-acting element analysis of the StSUS and StSPS promoter sequences showed four elements: defense- and stress-responsive, hormone-responsive, light-responsive, and transcription factor elements. The expression of StSUS and StSPS genes was found to be regulated by circadian rhythm. In the treatments of 1% to 5% sucrose, glucose, and fructose, the expression of StSUS and StSPS family genes was enhanced by sucrose, but inhibited at high-glucose and fructose concentrations. This study identified six StSUS and four StSPS genes and analyzed their gene structure, conserved motifs, chromosome position, promoter elements, phylogenetic tree, and tissue-specific expression patterns. Our results will motivate more research into the biological process underlying the genes of sucrose metabolism in potatoes.

Machine learning improves mortality prediction in three-vessel disease.

BACKGROUND AND AIMS: Risk stratification for three-vessel coronary artery disease (3VD) remains an important clinical challenge. In this study, we utilized machine learning (ML), which can address the limitations of traditional regression-based models, to develop a novel model to assess mortality risk in patients with 3VD. METHODS: This study was based on a prospective cohort of 8943 participants with 3VD consecutively enrolled between 2004 and 2011. An ML-derived random forest model was trained and tested to predict 4-year mortality. The predictability of the model was compared with that of an established model, the Synergy Between Percutaneous Coronary Intervention With Taxus and Cardiac Surgery score II (SSII), among 3VD patients undergoing percutaneous coronary intervention (PCI), coronary artery bypass grafting (CABG), and medical therapy (MT) alone. RESULTS: The all-cause mortality was 7.5% (667 patients) over the 4-year follow-up period. The correlation-based feature selection algorithm selected 18 of the 94 features to develop the ML model. In the testing dataset, the ML-derived model achieved an area under the curve of 0.81 for 4-year mortality prediction. Its predictability was significantly better than that of the SSII among patients undergoing PCI (0.80 vs. 0.70, p < 0.001) or CABG (0.80 vs. 0.67, p < 0.001). The model also outperformed the SSII in patients receiving MT alone (ML: 0.75 vs. SSII for PCI: 0.70 or SSII for CABG: 0.66, p < 0.001). CONCLUSIONS: This ML-based approach exhibited better performance in risk stratification for 3VD compared with the conventional method. Further validation studies are needed to confirm these findings.

Using machine learning to aid treatment decision and risk assessment for severe three-vessel coronary artery disease.

BACKGROUND: Three-vessel disease (TVD) with a SYNergy between PCI with TAXus and cardiac surgery (SYNTAX) score of ≥ 23 is one of the most severe types of coronary artery disease. We aimed to take advantage of machine learning to help in decision-making and prognostic evaluation in such patients. METHODS: We analyzed 3786 patients who had TVD with a SYNTAX score of ≥ 23, had no history of previous revascularization, and underwent either coronary artery bypass grafting (CABG) or percutaneous coronary intervention (PCI) after enrollment. The patients were randomly assigned to a training group and testing group. The C4.5 decision tree algorithm was applied in the training group, and all-cause death after a median follow-up of 6.6 years was regarded as the class label. RESULTS: The decision tree algorithm selected age and left ventricular end-diastolic diameter (LVEDD) as splitting features and divided the patients into three subgroups: subgroup 1 (age of ≤ 67 years and LVEDD of ≤ 53 mm), subgroup 2 (age of ≤ 67 years and LVEDD of > 53 mm), and subgroup 3 (age of > 67 years). PCI conferred a patient survival benefit over CABG in subgroup 2. There was no significant difference in the risk of all-cause death between PCI and CABG in subgroup 1 and subgroup 3 in both the training data and testing data. Among the total study population, the multivariable analysis revealed significant differences in the risk of all-cause death among patients in three subgroups. CONCLUSIONS: The combination of age and LVEDD identified by machine learning can contribute to decision-making and risk assessment of death in patients with severe TVD. The present results suggest that PCI is a better choice for young patients with severe TVD characterized by left ventricular dilation.

Late Blight Resistance Evaluation and Genome-Wide Assessment of Genetic Diversity in Wild and Cultivated Potato Species.

Late blight, caused by the oomycete Phytophthora infestans, is the most devastating disease in potato-producing regions of the world. Cultivation of resistant varieties is the most effective and environmentally friendly way to control potato late blight disease, and identification of germplasms with late blight resistance and clarification their genetic relationship would promote the development of the resistant varieties. In this study, a diverse population of 189 genotypes with potential late blight resistance, consisting of 20 wild species and cultivated Solanum tuberosum Andigenum group and Chilotanum group, was screened for the presence of late blight resistance by performing challenge inoculation with four Phytophthora infestans isolates including one 13_A2 isolate, CN152. Ten elite resources with broad-spectrum resistance and 127 with isolate-specific resistance against P. infestans were identified. To improve the available gene pool for future potato breeding programs, the population was genotyped using 30 simple sequence repeat (SSR) markers covering the entire potato genome. A total of 173 alleles were detected with an average of 5.77 alleles per locus. Structure analysis discriminated the 189 potato genotypes into five populations based on taxonomic classification and genetic origin with some deviations. There was no obvious clustering by country of origin, ploidy level, EBN (endosperm balance number) value, or nuclear clade. Analysis of molecular variance showed 10.08% genetic variation existed among populations. The genetic differentiation (Fst) ranged from 0.0937 to 0.1764, and the nucleotide diversity (π) was 0.2269 across populations with the range from 0.1942 to 0.2489. Further genotyping of 20K SNP array confirmed the classification of SSRs and could uncover the genetic relationships of Solanum germplasms. Our results indicate that there exits abundant genetic variation in wild and cultivated potato germplasms, while the cultivated S. tuberosum Chilotanum group has lower genetic diversity. The phenotypic and genetic information obtained in this study provide a useful guide for hybrid combination and resistance introgression from wild gene pool into cultivated species for cultivar improvement, as well as for germplasm conservation efforts and resistance gene mining.

New Findings on the Resistance Mechanism of an Elite Diploid Wild Potato Species JAM1-4 in Response to a Super Race Strain of Phytophthora infestans.

Late blight is a devastating potato disease worldwide, caused by Phytophthora infestans. The P. infestans strain 2013-18-306 from Yunnan is a "supervirulent race" that overcomes all 11 known late blight resistance genes (R1 to R11) from Solanum demissum. In a previous study, we identified a diploid wild-type potato JAM1-4 (S. jamesii) with high resistance to 2013-18-306. dRenSeq analysis indicated the presence of novel R genes in JAM1-4. RNA-Seq was used to analyze the late blight resistance response genes and defense regulatory mechanisms of JAM1-4 against 2013-18-306. Gene ontology enrichment and KEGG pathway analysis showed that many disease-resistant pathways were significantly enriched. Analysis of differentially expressed genes (DEGs) revealed an active disease resistance mechanism of JAM1-4, and the essential role of multiple signal transduction pathways and secondary metabolic pathways comprised of SA-JA-ET in plant immunity. We also found that photosynthesis in JAM1-4 was inhibited to promote the immune response. Our study reveals the pattern of resistance-related gene expression in response to a super race strain of potato late blight and provides a theoretical basis for further exploration of potato disease resistance mechanisms, discovery of new late blight resistance genes, and disease resistance breeding.

Comparative Transcriptome Profiling Reveals Compatible and Incompatible Patterns of Potato Toward Phytophthora infestans.

Late blight, caused by Phytophthora infestans (P. infestans), is a devastating disease in potato worldwide. Our previous study revealed that the Solanum andigena genotype 03112-233 is resistant to P. infestans isolate 90128, but susceptible to the super race isolate, CN152. In this study, we confirmed by diagnostic resistance gene enrichment sequencing (dRenSeq) that the resistance of 03112-233 toward 90128 is most likely based on a distinct new R gene(s). To gain an insight into the mechanism that governs resistance or susceptibility in 03112-223, comparative transcriptomic profiling analysis based on RNAseq was initiated. Changes in transcription at two time points (24 h and 72 h) after inoculation with isolates 90128 or CN152 were analyzed. A total of 8,881 and 7,209 genes were differentially expressed in response to 90128 and CN152, respectively, and 1,083 differentially expressed genes (DEGs) were common to both time points and isolates. A substantial number of genes were differentially expressed in an isolate-specific manner with 3,837 genes showing induction or suppression following infection with 90128 and 2,165 genes induced or suppressed after colonization by CN152. Hierarchical clustering analysis suggested that isolates with different virulence profiles can induce different defense responses at different time points. Further analysis revealed that the compatible interaction caused higher induction of susceptibility genes such as SWEET compared with the incompatible interaction. The salicylic acid, jasmonic acid, and abscisic acid mediated signaling pathways were involved in the response against both isolates, while ethylene and brassinosteroids mediated defense pathways were suppressed. Our results provide a valuable resource for understanding the interactions between P. infestans and potato.

Atomistic Investigation of Anisotropic Nanoindentation Behavior of Nanotwinned Aluminum Containing Inclined Twin Boundaries.

Nanotwinned metals exhibit superior mechanical properties due to unique dislocation⁻twin boundary interactions. In the present work, we elucidate the microscopic deformation mechanisms and their correlations with the macroscopic mechanical response of nanotwinned Al containing inclined twin boundaries under nanoindentation by means of molecular dynamics simulations. The effect of twin boundary orientation with respect to the indented surface on the nanoindentation is evaluated. Simulation results reveal that dislocation slip, dislocation⁻twin boundary interaction, and twin boundary migration operate in parallel in the plastic deformation of nanotwinned Al. The inclination angle of twin boundaries with respect to indented surface has a strong influence on the interaction between individual deformation modes, which in turn leads to the anisotropic indentation behavior of nanotwinned Al.