Genomic prediction and allele mining of agronomic and morphological traits in pea (Pisum sativum) germplasm collections.

Well-performing genomic prediction (GP) models for polygenic traits and molecular marker sets for oligogenic traits could be useful for identifying promising genetic resources in germplasm collections, setting core collections, and establishing molecular variety distinction. This study aimed at (i) defining GP models and key marker sets for predicting 15 agronomic or morphological traits in germplasm collections, (ii) verifying the GP model usefulness also for selection in breeding programs, (iii) investigating the consistency between molecular and phenotypic diversity patterns, and (iv) identifying genomic regions associated with to the target traits. The study was based on phenotyping data and over 41,000 genotyping-by-sequencing-generated SNP markers of 220 landraces or old cultivars belonging to a world germplasm collection and 11 modern cultivars. Non-metric multi-dimensional scaling (NMDS) and an analysis of population genetic structure indicated a high level of genetic differentiation of material from Western Asia, a major West-East diversity gradient, and quite limited genetic diversity of the improved germplasm. Mantel's test revealed a low correlation (r = 0.12) between phenotypic and molecular diversity, which increased (r = 0.45) when considering only the molecular diversity relative to significant SNPs from genome-wide association analyses. These analyses identified, inter alia, several areas of chromosome 6 involved in a largely pleiotropic control of vegetative or reproductive organ pigmentation. We found various significant SNPs for grain and straw yield under severe drought and onset of flowering, and one SNP on chromosome 5 for grain protein content. GP models displayed moderately high predictive ability (0.43 to 0.61) for protein content, grain and straw yield, and onset of flowering, and high predictive ability (0.76) for individual seed weight, based on intra-population, intra-environment cross-validations. The inter-population, inter-environment assessment of the models trained on the germplasm collection for breeding material of three recombinant inbred line (RIL) populations, which was challenged by much narrower diversity of the material, over eight-fold less available markers and quite different test environments, led to an overall loss of predictive ability of about 40% for seed weight, 50% for protein content and straw yield, and 60% for onset of flowering, and no prediction for grain yield. Within-RIL population predictive ability differed among populations.

Pea Breeding for Intercropping With Cereals: Variation for Competitive Ability and Associated Traits, and Assessment of Phenotypic and Genomic Selection Strategies.

Mixed stand (MS) cropping of pea with small-grain cereals can produce more productive and environment-friendly grain crops relative to pure stand (PS) crops but may require selection to alleviate the pea competitive disadvantage. This study aimed to assess the pea variation for competitive ability and its associated traits and the efficiency of four phenotypic or genomic selection strategies. A set of 138 semi-leafless, semi-dwarf pea lines belonging to six recombinant inbred line populations and six parent lines were genotyped using genotyping-by-sequencing and grown in PS and in MS simultaneously with one barley and one bread wheat cultivar in two autumn-sown trials in Northern Italy. Cereal companions were selected in a preliminary study that highlighted the paucity of cultivars with sufficient earliness for association. Pea was severely outcompeted in both years albeit with variation for pea proportion ranging from nearly complete suppression (<3%) to values approaching a balanced mixture. Greater pea proportion in MS was associated with greater total yield of the mixture (r ≥ 0.46). The genetic correlation for pea yield across MS and PS conditions slightly exceeded 0.40 in both years. Later onset of flowering and taller plant height at flowering onset displayed a definite correlation with pea yield in MS (r ≥ 0.46) but not in PS, whereas tolerance to ascochyta blight exhibited the opposite pattern. Comparisons of phenotypic selection strategies within or across populations based on predicted or actual yield gains for independent years indicated an efficiency of 52-64% for indirect selection based on pea yield in PS relative to pea yield selection in MS. The efficiency of an indirect selection index including onset of flowering, plant height, and grain yield in PS was comparable to that of pea yield selection in MS. A genome-wide association study based on 5,909 SNP markers revealed the substantial diversity of genomic areas associated with pea yield in MS and PS. Genomic selection for pea yield in MS displayed an efficiency close to that of phenotypic selection for pea yield in MS, and nearly two-fold greater efficiency when also taking into account its shorter selection cycle and smaller evaluation cost.

Pea Grain Protein Content Across Italian Environments: Genetic Relationship With Grain Yield, and Opportunities for Genome-Enabled Selection for Protein Yield.

Wider pea (Pisum sativum L.) cultivation has great interest for European agriculture, owing to its favorable environmental impact and provision of high-protein feedstuff. This work aimed to investigate the extent of genotype × environment interaction (GEI), genetically based trade-offs and polygenic control for crude protein content and grain yield of pea targeted to Italian environments, and to assess the efficiency of genomic selection (GS) as an alternative to phenotypic selection (PS) to increase protein yield per unit area. Some 306 genotypes belonging to three connected recombinant inbred line (RIL) populations derived from paired crosses between elite cultivars were genotyped through genotyping-by-sequencing and phenotyped for grain yield and protein content on a dry matter basis in three autumn-sown environments of northern or central Italy. Line variation for mean protein content ranged from 21.7 to 26.6%. Purely genetic effects, compared with GEI effects, were over two-fold larger for protein content, and over 2-fold smaller for grain and protein yield per unit area. Grain yield and protein content exhibited no inverse genetic correlation. A genome-wide association study revealed a definite polygenic control not only for grain yield but also for protein content, with small amounts of trait variation accounted for by individual loci. On average, the GS predictive ability for individual RIL populations based on the rrBLUP model (which was selected out of four tested models) using by turns two environments for selection and one for validation was moderately high for protein content (0.53) and moderate for grain yield (0.40) and protein yield (0.41). These values were about halved for inter-environment, inter-population predictions using one RIL population for model construction to predict data of the other populations. The comparison between GS and PS for protein yield based on predicted gains per unit time and similar evaluation costs indicated an advantage of GS for model construction including the target RIL population and, in case of multi-year PS, even for model training based on data of a non-target population. In conclusion, protein content is less challenging than grain yield for phenotypic or genome-enabled improvement, and GS is promising for the simultaneous improvement of both traits.

Development and Proof-of-Concept Application of Genome-Enabled Selection for Pea Grain Yield under Severe Terminal Drought.

Terminal drought is the main stress limiting pea (Pisum sativum L.) grain yield in Mediterranean environments. This study aimed to investigate genotype × environment (GE) interaction patterns, define a genomic selection (GS) model for yield under severe drought based on single nucleotide polymorphism (SNP) markers from genotyping-by-sequencing, and compare GS with phenotypic selection (PS) and marker-assisted selection (MAS). Some 288 lines belonging to three connected RIL populations were evaluated in a managed-stress (MS) environment of Northern Italy, Marchouch (Morocco), and Alger (Algeria). Intra-environment, cross-environment, and cross-population predictive ability were assessed by Ridge Regression best linear unbiased prediction (rrBLUP) and Bayesian Lasso models. GE interaction was particularly large across moderate-stress and severe-stress environments. In proof-of-concept experiments performed in a MS environment, GS models constructed from MS environment and Marchouch data applied to independent material separated top-performing lines from mid- and bottom-performing ones, and produced actual yield gains similar to PS. The latter result would imply somewhat greater GS efficiency when considering same selection costs, in partial agreement with predicted efficiency results. GS, which exploited drought escape and intrinsic drought tolerance, exhibited 18% greater selection efficiency than MAS (albeit with non-significant difference between selections) and moderate to high cross-population predictive ability. GS can be cost-efficient to raise yields under severe drought.

Response to ipilimumab therapy in metastatic melanoma patients: potential relevance of CTLA-4+ tumor infiltrating lymphocytes and their in situ localization.

Immune checkpoint inhibitors, including ipilimumab (IPI), achieve a clinical benefit in a small proportion of melanoma patients highlighting the need to investigate predictive biomarkers. In this study, we characterized tumor infiltrating lymphocytes (TILs), focusing on the CTLA-4+ subset, and evaluated their possible predictive significance. We characterized TIL density, cell type, and localization in 40 melanoma lesions from 17 patients treated with IPI. Associations of TILs with IPI timing, tissue localization, and response to IPI were estimated using a linear mixed-effects modelling approach. We found that most of TIL subsets increased in situ upon IPI therapy, with particular reference to FoxP3+ cells. TILs and TIL subsets, such as CD3+, CD45RO+, CTLA-4+, CD4+, CD8+ T cells, CD20+ B cells, and NKp46+ NK cells, showed significantly different spatial distributions in the tumor microenvironment being higher at the invasive margin (IM) as compared to the tumor center (TC) (P value < 0.001 for TIL score and P value < 0.05 for all subsets). Remarkably, high TIL score and density of CD3+, CD8+ T cells, and CTLA-4+ immune cells were significantly associated with a better response to IPI (P values = 0.002, 0.023, 0.007, and 0.001, respectively, for responders vs non-responders). In conclusion, we provide a detailed analysis of CTLA-4+ TIL distribution in melanoma tissues taking into account localization, relationship with CD3+/CD8+ TILs, and changes in response to IPI treatment. We identified that CTLA-4+ TILs may represent a marker of IPI response, alone or with CD3+/CD8+ subsets, although this requires confirmation in larger studies.

Pea genomic selection for Italian environments.

BACKGROUND: A thorough verification of the ability of genomic selection (GS) to predict estimated breeding values for pea (Pisum sativum L.) grain yield is pending. Prediction for different environments (inter-environment prediction) has key importance when breeding for target environments featuring high genotype × environment interaction (GEI). The interest of GS would increase if it could display acceptable prediction accuracies in different environments also for germplasm that was not used in model training (inter-population prediction). RESULTS: Some 306 genotypes belonging to three connected RIL populations derived from paired crosses between elite cultivars were genotyped through genotyping-by-sequencing and phenotyped for grain yield, onset of flowering, lodging susceptibility, seed weight and winter plant survival in three autumn-sown environments of northern or central Italy. The large GEI for grain yield and its pattern (implying larger variation across years than sites mainly due to year-to-year variability for low winter temperatures) encouraged the breeding for wide adaptation. Wider within-population than between-population variation was observed for nearly all traits, supporting GS application to many lines of relatively few elite RIL populations. Bayesian Lasso without structure imputation and 1% maximum genotype missing rate (including 6058 polymorphic SNP markers) was selected for GS modelling after assessing different GS models and data configurations. On average, inter-environment predictive ability using intra-population predictions reached 0.30 for yield, 0.65 for onset of flowering, 0.64 for seed weight, and 0.28 for lodging susceptibility. Using inter-population instead of intra-population predictions reduced the inter-environment predictive ability to 0.19 for grain yield, 0.40 for onset of flowering, 0.28 for seed weight, and 0.22 for lodging susceptibility. A comparison of GS vs phenotypic selection (PS) based on predicted genetic gains per unit time for same selection costs suggested greater efficiency of GS for all traits under various selection scenarios. For yield, the advantage in predicted efficiency of GS over PS was at least 80% using intra-population predictions and 20% using inter-population predictions. A genome-wide association study confirmed the highly polygenic control of most traits. CONCLUSIONS: Genome-enabled predictions can increase the efficiency of pea line selection for wide adaptation to Italian environments relative to phenotypic selection.

Complement component C5a induces aberrant epigenetic modifications in renal tubular epithelial cells accelerating senescence by Wnt4/ßcatenin signaling after ischemia/reperfusion injury.

Epigenetic mechanisms, such as DNA methylation, affect tubular maladaptive response after Acute Kidney Injury (AKI) and accelerate renal aging. Upon ischemia/reperfusion (I/R) injury, Complement activation leads to C5a release that mediates damage; however, little is known about the effect of C5a-C5a Receptor (C5aR) interaction in Renal Tubular Epithelial Cells (RTEC).Through a whole-genome DNA methylation analysis in cultured RTEC, we found that C5a induced aberrant methylation, particularly in regions involved in cell cycle control, DNA damage and Wnt signaling. The most represented genes were BCL9, CYP1B1 and CDK6. C5a stimulation of RTEC led to up-regulation of SA-ß Gal and cell cycle arrest markers such as p53 and p21. C5a increased also IL-6, MCP-1 and CTGF gene expression, consistent with SASP development. In accordance, in a swine model of renal I/R injury, we found the increased expression of Wnt4 and ßcatenin correlating with SA-ß Gal, p21, p16 and IL-6 positivity. Administration of Complement Inhibitor (C1-Inh), antagonized SASP by reducing SA-ß Gal, p21, p16, IL-6 and abrogating Wnt4/ßcatenin activation.Thus, C5a affects the DNA methylation of genes involved in tubular senescence. Targeting epigenetic programs and Complement may offer novels strategies to protect tubular cells from accelerated aging and to counteract progression to Chronic Kidney Disease.

Targeting of Histone Demethylases KDM5A and KDM6B Inhibits the Proliferation of Temozolomide-Resistant Glioblastoma Cells.

Lysine histone demethylases (KDMs) are considered potential therapeutic targets in several tumors, including glioblastoma (GB). In particular, KDM5A is involved in the acquisition of temozolomide (TMZ) resistance in adult GB cells and UDX/KDM6B regulates H3K27 methylation, which is involved in the pediatric diffuse intrinsic pontine glioma (DIPG). Synthetic inhibitors of KDM5A (JIB 04 and CPI-455) efficiently block the proliferation of native and TMZ-resistant cells and the KDM6B inhibitor GSK J4 improves survival in a model of DIPG. The aim of our work was to determine if GSK J4 could be effective against GB cells that have acquired TMZ resistance and if it could synergize with TMZ or JIB 04 to increase the clinical utility of these molecules. Standard functional and pharmacological analytical procedures were utilized to determine the efficacy of the molecules under study when used alone or in combination against native GB cells and in a model of drug resistance. The results of this study indicated that although GSK J4 is active against native and TMZ-resistant cells, it does so at a lower efficacy than JIB 04. Drug combination studies revealed that GSK J4, differently from JIB 04, does not synergize with TMZ. Interestingly, GSK J4 and JIB 04 strongly synergize and are a potent combination against TMZ-resistant cells. Further studies in animal models will be necessary to determine if this combination of molecules might foster the development of novel therapeutic approaches for glioblastoma.

Soluble CTLA-4 as a favorable predictive biomarker in metastatic melanoma patients treated with ipilimumab: an Italian melanoma intergroup study.

CTLA-4 blockade by means of ipilimumab (IPI) potentiates the immune response and improves overall survival (OS) in a minority of metastatic melanoma (MM) patients. We investigated the role of soluble CTLA-4 (sCTLA-4) as a possible biomarker for identifying this subset of patients. sCTLA-4 levels were analyzed at baseline in sera from 113 IPI-treated MM patients by ELISA, and the median value (200 pg/ml) was used to create two equally sized subgroups. Associations of sCTLA-4 with best overall response (BOR) to IPI and immune-related adverse events (irAEs) were evaluated through logistic regression. Kaplan-Meier and Cox regression methods were used to analyze OS. A remarkable association between sCTLA-4 levels and BOR was found. Specifically, the proportion of patients with sCTLA-4 > 200 pg/ml in irSD or irPD (immune-related stable or progressive disease) was, respectively, 80% (OR = 0.23; 95%CL = 0.03-1.88) and 89% (OR = 0.11; 95%CL = 0.02-0.71) and was lower than that observed among patients in irCR/irPR (immune-related complete/partial response). sCTLA-4 levels increased during IPI treatment, since the proportion of patients showing sCTLA > 200 pg/ml after 3 cycles was 4 times higher (OR = 4.41, 95%CL = 1.02-19.1) than that after 1 cycle. Moreover, a significantly lower death rate was estimated for patients with sCTLA-4 > 200 pg/ml (HR = 0.61, 95%CL = 0.39-0.98). Higher baseline sCTLA-4 levels were also associated with the onset of any irAE (p value = 0.029), in particular irAEs of the digestive tract (p value = 0.041). In conclusion, our results suggest that high sCTLA-4 serum levels might predict favorable clinical outcome and higher risk of irAEs in IPI-treated MM patients.

Immune Checkpoints and Innovative Therapies in Glioblastoma.

Targeting the Immune Checkpoint molecules (ICs; CTLA-4, PD-1, PD-L1/2, and others) which provide inhibitory signals to T cells, dramatically improves survival in hard-to-treat tumors. The establishment of an immunosuppressive environment prevents endogenous immune response in glioblastoma; therefore, manipulating the host immune system seems a reasonable strategy also for this tumor. In glioma patients the accumulation of CD4+/CD8+ T cells and Treg expressing high levels of CTLA-4 and PD-1, or the high expression of PD-L1 in glioma cells correlates with WHO high grade and short survival. Few clinical studies with IC inhibitors (ICis) were completed so far. Notably, the first large-scale randomized trial (NCT 02017717) that compared PD-1 blockade and anti-VEGF, did not show an OS increase in the patients treated with anti-PD-1. Several factors could have contributed to the failure of this trial and must be considered to design further clinical studies. In particular the possibility of targeting at the same time different ICs was pre-clinically tested in an animal model were inhibitors against IDO, CTLA-4 and PD-L1 were combined and showed persistent and significant antitumor effects in glioma-bearing mice. It is reasonable to hypothesize that the immunological characterization of the tumor in terms of type and level of expressed IC molecules on the tumor and TIL may be useful to design the optimal ICi combination for a given subset of tumor to overcome the immunosuppressive milieu of glioblastoma and to efficiently target a tumor with such high cellular complexity.