Human aneuploid cells depend on the RAF/MEK/ERK pathway for overcoming increased DNA damage.

Aneuploidy is a hallmark of human cancer, yet the molecular mechanisms to cope with aneuploidy-induced cellular stresses remain largely unknown. Here, we induce chromosome mis-segregation in non-transformed RPE1-hTERT cells and derive multiple stable clones with various degrees of aneuploidy. We perform a systematic genomic, transcriptomic and proteomic profiling of 6 isogenic clones, using whole-exome DNA, mRNA and miRNA sequencing, as well as proteomics.

Increased RNA and Protein Degradation Is Required for Counteracting Transcriptional Burden and Proteotoxic Stress in Human Aneuploid Cells.

Aneuploidy results in a stoichiometric imbalance of protein complexes that jeopardizes cellular fitness. Aneuploid cells thus need to compensate for the imbalanced DNA levels by regulating their RNA and protein levels, but the underlying molecular mechanisms remain unknown. In this study, we dissected multiple diploid versus aneuploid cell models.

Inferring Characteristics of the Tumor Immune Microenvironment of Patients with HNSCC from Single-Cell Transcriptomics of Peripheral Blood.

Unlabelled: In this study, we explore the possibility of inferring characteristics of the tumor immune microenvironment from the blood. Specifically, we investigate two datasets of patients with head and neck squamous cell carcinoma with matched single-cell RNA sequencing (scRNA-seq) from peripheral blood mononuclear cells (PBMCs) and tumor tissues. Our analysis shows that the immune cell fractions and gene expression profiles of various immune cells within the tumor microenvironment can be inferred from the matched PBMC scRNA-seq data.

Analysis of RNA translation with a deep learning architecture provides new insight into translation control.

Accurate annotation of coding regions in RNAs is essential for understanding gene translation. We developed a deep neural network to directly predict and analyze translation initiation and termination sites from RNA sequences. Trained with human transcripts, our model learned hidden rules of translation control and achieved a near perfect prediction of canonical translation sites across entire human transcriptome.

Microenvironment shapes small-cell lung cancer neuroendocrine states and presents therapeutic opportunities.

Small-cell lung cancer (SCLC) is the most fatal form of lung cancer. Intratumoral heterogeneity, marked by neuroendocrine (NE) and non-neuroendocrine (non-NE) cell states, defines SCLC, but the cell-extrinsic drivers of SCLC plasticity are poorly understood. To map the landscape of SCLC tumor microenvironment (TME), we apply spatially resolved transcriptomics and quantitative mass spectrometry-based proteomics to metastatic SCLC tumors obtained via rapid autopsy.

LORIS robustly predicts patient outcomes with immune checkpoint blockade therapy using common clinical, pathologic and genomic features.

Despite the revolutionary impact of immune checkpoint blockade (ICB) in cancer treatment, accurately predicting patient responses remains challenging. Here, we analyzed a large dataset of 2,881 ICB-treated and 841 non-ICB-treated patients across 18 solid tumor types, encompassing a wide range of clinical, pathologic and genomic features. We developed a clinical score called LORIS (logistic regression-based immunotherapy-response score) using a six-feature logistic regression model.

Pan-Cancer Analysis of Patient Tumor Single-Cell Transcriptomes Identifies Promising Selective and Safe Chimeric Antigen Receptor Targets in Head and Neck Cancer.

Chimeric antigen receptor (CAR) T cell therapies have yielded transformative clinical successes for patients with blood tumors, but their full potential remains to be unleashed against solid tumors. One challenge is finding targets, which we define intuitively to be cell surface proteins that are expressed widely by cancer cells but minimally by healthy cells in the tumor microenvironment and other normal tissues. Analyzing patient tumor single-cell transcriptomics data, we first defined and quantified selectivity and safety scores of existing CAR targets for indications in which they are in clinical trials or approved.

Optimizing cancer immunotherapy response prediction by tumor aneuploidy score and fraction of copy number alterations.

Identifying patients that are likely to respond to cancer immunotherapy is an important, yet highly challenging clinical need. Using 3139 patients across 17 different cancer types, we comprehensively studied the ability of two common copy-number alteration (CNA) scores-the tumor aneuploidy score (AS) and the fraction of genome single nucleotide polymorphism encompassed by copy-number alterations (FGA)-to predict survival following immunotherapy in both pan-cancer and individual cancer types. First, we show that choice of cutoff during CNA calling significantly influences the predictive power of AS and FGA for patient survival following immunotherapy.

Predicting tumor immune microenvironment and checkpoint therapy response of head & neck cancer patients from blood immune single-cell transcriptomics.

Unlabelled: The immune state of tumor microenvironment is crucial for determining immunotherapy response but is not readily accessible. Here we investigate if we can infer the tumor immune state from the blood and further predict immunotherapy response. First, we analyze a dataset of head and neck squamous cell carcinoma (HNSCC) patients with matched scRNA-Seq of peripheral blood mononuclear cells (PBMCs) and tumor tissues.

Common evolutionary trajectory of short life-cycle in Brassicaceae ruderal weeds.

Weed species are detrimental to crop yield. An understanding of how weeds originate and adapt to field environments is needed for successful crop management and reduction of herbicide use. Although early flowering is one of the weed trait syndromes that enable ruderal weeds to overcome frequent disturbances, the underlying genetic basis is poorly understood.

Defining the scope for altering rice leaf anatomy to improve photosynthesis: a modelling approach.

Leaf structure plays an important role in photosynthesis. However, the causal relationship and the quantitative importance of any single structural parameter to the overall photosynthetic performance of a leaf remains open to debate. In this paper, we report on a mechanistic model, eLeaf, which successfully captures rice leaf photosynthetic performance under varying environmental conditions of light and CO .

3dCAP-Wheat: An Open-Source Comprehensive Computational Framework Precisely Quantifies Wheat Foliar, Nonfoliar, and Canopy Photosynthesis.

Canopy photosynthesis is the sum of photosynthesis of all above-ground photosynthetic tissues. Quantitative roles of nonfoliar tissues in canopy photosynthesis remain elusive due to methodology limitations. Here, we develop the first canopy photosynthesis model incorporating all above-ground photosynthetic tissues and validate this model on wheat with state-of-the-art gas exchange measurement facilities.

Diurnal and Seasonal Variations of Photosynthetic Energy Conversion Efficiency of Field Grown Wheat.

Improving canopy photosynthetic light use efficiency and energy conversion efficiency (ε ) is a major option to increase crop yield potential. However, so far, the diurnal and seasonal variations of canopy light use efficiency (LUE) and ε are largely unknown due to the lack of an efficient method to estimate ε in a high temporal resolution. Here we quantified the dynamic changes of crop canopy LUE and ε during a day and a growing season with the canopy gas exchange method.

Potential metabolic mechanisms for inhibited chloroplast nitrogen assimilation under high CO2.

Improving photosynthesis is considered a major and feasible option to dramatically increase crop yield potential. Increased atmospheric CO2 concentration often stimulates both photosynthesis and crop yield, but decreases protein content in the main C3 cereal crops. This decreased protein content in crops constrains the benefits of elevated CO2 on crop yield and affects their nutritional value for humans.

Systems models, phenomics and genomics: three pillars for developing high-yielding photosynthetically efficient crops.

Recent years witnessed a stagnation in yield enhancement in major staple crops, which leads plant biologists and breeders to focus on an urgent challenge to dramatically increase crop yield to meet the growing food demand. Systems models have started to show their capacity in guiding crops improvement for greater biomass and grain yield production. Here we argue that systems models, phenomics and genomics combined are three pillars for the future breeding for high-yielding photosynthetically efficient crops (HYPEC).

Scheduling of nitrogen fertilizer topdressing during panicle differentiation to improve grain yield of rice with a long growth duration.

Topdressing at panicle differentiation (PF) according to soil fertility and regularity of rice nutrient absorption is an important agronomic practice used in cultivation of rice cultivars with a long growth duration. We studied the impacts of timing of nitrogen fertilizer application during PF on photosynthesis and yield-related agronomic traits in 'Y-Liang-You 900' and 'Y-Liang-You 6', which are representative rice cultivars with a long growth duration. Data for two years showed that timing of topdressing application during PF affected panicles per unit area, percentage grain set, spikelets per panicle, and leaf photosynthetic traits during the grain-filling period.

Morphological and physiological factors contributing to early vigor in the elite rice cultivar 9,311.

Huanghuazhan (HHZ) and 9,311 are two elite rice cultivars in China. They have achieved high yield through quite different mechanisms. One of the major features that gives high yield capacity to 9,311 is its strong early vigor, i.

Architectural and Physiological Features to Gain High Yield in an Elite Rice Line YLY1.

Identification of traits strongly associated with high yield can help future gene engineering towards improvements of productivity. Here we systematically determine the major architectural and physiological features associated with high yield in two elite historical hybrid rice cultivars, i.e.

Genome-Wide Association Study Unravels as a Dark Respiration Regulator in Rice ( L.).

Respiration is a major plant physiological process that generates adenosine triphosphate (ATP) to support the various pathways involved in the plant growth and development. After decades of focused research on basic mechanisms of respiration, the processes and major proteins involved in respiration are well elucidated. However, much less is known about the natural variation of respiration.

An in situ approach to characterizing photosynthetic gas exchange of rice panicle.

Background: Photosynthesis of reproductive organs in C cereals is generally regarded as important to crop yield. Whereas, photosynthetic characteristics of reproductive organs are much less understood as compared to leaf photosynthesis, mainly due to methodological limitations. To date, many indirect methods have been developed to study photosynthesis of reproductive organs and its contribution to grain yield, such as organ shading, application of herbicides and photosynthetic measurement of excised organs or tissues, which might be intrusive and cause biases.

Overexpression of maize transcription factor mEmBP-1 increases photosynthesis, biomass, and yield in rice.

Identifying new options to improve photosynthetic capacity is a major approach to improve crop yield potential. Here we report that overexpression of the gene encoding the transcription factor mEmBP-1 led to simultaneously increased expression of many genes in photosynthesis, including genes encoding Chl a,b-binding proteins (Lhca and Lhcb), PSII (PsbR3 and PsbW) and PSI reaction center subunits (PsaK and PsaN), chloroplast ATP synthase subunit, electron transport reaction components (Fd1 and PC), and also major genes in the Calvin-Benson-Bassham cycle, including those encoding Rubisco, glyceraldehyde phosphate dehydrogenase, fructose bisphosphate aldolase, transketolase, and phosphoribulokinase. These increased expression of photosynthesis genes resulted in increased leaf chlorophyll pigment, photosynthetic rate, biomass growth, and grain yield both in the greenhouse and in the field.

A three-dimensional canopy photosynthesis model in rice with a complete description of the canopy architecture, leaf physiology, and mechanical properties.

In current rice breeding programs, morphological parameters such as plant height, leaf length and width, leaf angle, panicle architecture, and tiller number during the grain filling stage are used as major selection targets. However, so far, there is no robust approach to quantitatively define the optimal combinations of parameters that can lead to increased canopy radiation use efficiency (RUE). Here we report the development of a three-dimensional canopy photosynthesis model (3dCAP), which effectively combines three-dimensional canopy architecture, canopy vertical nitrogen distribution, a ray-tracing algorithm, and a leaf photosynthesis model.

Systems model-guided rice yield improvements based on genes controlling source, sink, and flow.

A large number of genes related to source, sink, and flow have been identified after decades of research in plant genetics. Unfortunately, these genes have not been effectively utilized in modern crop breeding. This perspective paper aims to examine the reasons behind such a phenomenon and propose a strategy to resolve this situation.