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The 7.4 million plant accessions in gene banks are largely underutilized due to various resource constraints, but current genomic and analytic technologies are enabling us to mine this natural heritage. Here we report a proof-of-concept study to integrate genomic prediction into a broad germplasm evaluation process. First, a set of 962 biomass sorghum accessions were chosen as a reference set by germplasm curators. With high throughput genotyping-by-sequencing (GBS), we genetically characterized this reference set with 340,496 single nucleotide polymorphisms (SNPs). A set of 299 accessions was selected as the training set to represent the overall diversity of the reference set, and we phenotypically characterized the training set for biomass yield and other related traits. Cross-validation with multiple analytical methods using the data of this training set indicated high prediction accuracy for biomass yield. Empirical experiments with a 200-accession validation set chosen from the reference set confirmed high prediction accuracy. The potential to apply the prediction model to broader genetic contexts was also examined with an independent population. Detailed analyses on prediction reliability provided new insights into strategy optimization. The success of this project illustrates that a global, cost-effective strategy may be designed to assess the vast amount of valuable germplasm archived in 1,750 gene banks.

Purpose Determine the localized expression pattern and clinical significance of VISTA/PD-1H in human NSCLC. Experimental Design Using multiplex quantitative immunofluorescence (QIF), we performed localized measurements of VISTA, PD-1 and PD-L1 protein in 758 stage I-IV NSCLCs from 3 independent cohorts represented in tissue microarray format. The targets were selectively measured in cytokeratin+ tumor epithelial cells, CD3+ T-cells, CD4+ T-helper cells, CD8+ cytotoxic T-cells, CD20+ B-lymphocytes and CD68+ tumor-associated macrophages. We determined the association between the targets, clinico-pathological/molecular variables and survival. Genomic analyses of lung cancer cases from TCGA was also performed. Results VISTA protein was detected in 99% of NSCLCs with a predominant membranous/cytoplasmic staining pattern. Expression in tumor and stromal cells was seen in 21% and 98% of cases, respectively. The levels of VISTA were positively associated with PD-L1, PD-1, CD8+ T-cells and CD68+ macrophages. VISTA expression was higher in T-lymphocytes than in macrophages; and in cytotoxic T-cells than in T-helper cells. Elevated VISTA was associated with absence of EGFR mutations and lower mutational burden in lung adenocarcinomas. Presence of VISTA in tumor compartment predicted longer 5-year survival. Conclusions VISTA is frequently expressed in human NSCLC and shows association with increased TILs, PD-1 axis markers, specific genomic alterations and outcome. These results support the immuno-modulatory role of VISTA in human NSCLC and suggests its potential as therapeutic target.

The maize shoot apical meristem (SAM) comprises a small pool of stem cells that generate all above-ground organs. Although mutational studies have identified genetic networks regulating SAM function, little is known about SAM morphological variation in natural populations. Here we report the use of high-throughput image processing to capture rich SAM size variation within a diverse maize inbred panel. We demonstrate correlations between seedling SAM size and agronomically important adult traits such as flowering time, stem size and leaf node number. Combining SAM phenotypes with 1.2 million single nucleotide polymorphisms (SNPs) via genome-wide association study reveals unexpected SAM morphology candidate genes. Analyses of candidate genes implicated in hormone transport, cell division and cell size confirm correlations between SAM morphology and trait-associated SNP alleles. Our data illustrate that the microscopic seedling SAM is predictive of adult phenotypes and that SAM morphometric variation is associated with genes not previously predicted to regulate SAM size.

Immunotherapy offers new cancer treatment options, but efficacy varies across cancer types. Colorectal cancers (CRCs) are largely refractory to immune checkpoint blockade, suggesting the presence of yet-to-be characterized immune suppressive mechanisms. Here we report that APC-loss in intestinal tumor cells or PTEN-loss in melanoma cells upregulates the expression of dickkopf-2 (DKK2), which, together with its receptor LRP5, constitutes an unconventional mechanism for tumor immune evasion. DKK2 secreted by tumor cells acts on cytotoxic lymphocytes, inhibiting STAT5 signaling by impeding STAT5 nuclear localization via LRP5 but independently of LRP6 and the Wnt-β-catenin pathway. Genetic or antibody-mediated ablation of DKK2 activates natural killer (NK) and CD8+ cells in tumors, impedes tumor progression, and cooperates with PD-1 blockade. Thus, we have identified a previously unknown tumor immune suppressive mechanism and immunotherapeutic targets particularly relevant for CRCs and a subset of melanomas.

Dysregulation of several metabolite pathways, including branched-chain amino acids (BCAAs), are associated with Non-Alcoholic Fatty Liver Disease (NAFLD) and insulin resistance in adults, while studies in youth reported conflicting results. We explored whether, independently of obesity and insulin resistance, obese adolescents with NAFLD display a metabolomic signature consistent with disturbances in amino acid and lipid metabolism. A total of 180 plasma metabolites were measured by a targeted metabolomic approach in 78 obese adolescents with (n = 30) or without (n = 48) NAFLD assessed by magnetic resonance imaging (MRI). All subjects underwent an oral glucose tolerance test and subsets of patients underwent a two-step hyperinsulinemic-euglycemic clamp and/or a second MRI after a 2.2 ± 0.8-year follow-up. Adolescents with NAFLD had higher plasma levels of valine (p = 0.02), isoleucine (p = 0.03), tryptophan (p = 0.02), and lysine (p = 0.02) after adjustment for confounding factors. Circulating BCAAs were negatively correlated with peripheral and hepatic insulin sensitivity. Furthermore, higher baseline valine levels predicted an increase in hepatic fat content (HFF) at follow-up (p = 0.01). These results indicate that a dysregulation of BCAA metabolism characterizes obese adolescents with NAFLD independently of obesity and insulin resistance and predict an increase in hepatic fat content over time.

Brachypodium distachyon (Brachypodium) is a temperate wild grass species and is a powerful model system for studying grain, energy, forage and turf grasses. Exploring the natural variation in the drought response of Brachypodium provides an important basis for dissecting the genetic network of drought tolerance. Two experiments were conducted in a greenhouse to assess the drought tolerance of 57 natural populations of Brachypodium. Principle component analysis revealed that reductions in chlorophyll fluorescence (Fv/Fm) and leaf water content (LWC) under drought stress explained most of the phenotypic variation, which was used to classify the tolerant and susceptible accessions. Four groups of accessions differing in drought tolerance were identified, with 3 tolerant, 16 moderately tolerant, 32 susceptible and 6 most susceptible accessions. The tolerant group had little leaf wilting and fewer reductions in Fv/Fm and LWC, while the most susceptible groups showed severe leaf wilting and more reductions in Fv/Fm and LWC. Drought stress increased total water soluble sugar (WSS) concentration, but no differences in the increased WSS were found among different groups of accessions. The large phenotypic variation of Brachypodium in response to drought stress can be used to identify genes and alleles important for the complex trait of drought tolerance.

BackgroundMany Single Nucleotide Polymorphism (SNP) calling programs have been developed to identify Single Nucleotide Variations (SNVs) in next-generation sequencing (NGS) data. However, low sequencing coverage presents challenges to accurate SNV identification, especially in single-sample data. Moreover, commonly used SNP calling programs usually include several metrics in their output files for each potential SNP. These metrics are highly correlated in complex patterns, making it extremely difficult to select SNPs for further experimental validations.ResultsTo explore solutions to the above challenges, we compare the performance of four SNP calling algorithm, SOAPsnp, Atlas-SNP2, SAMtools, and GATK, in a low-coverage single-sample sequencing dataset. Without any post-output filtering, SOAPsnp calls more SNVs than the other programs since it has fewer internal filtering criteria. Atlas-SNP2 has stringent internal filtering criteria; thus it reports the least number of SNVs. The numbers of SNVs called by GATK and SAMtools fall between SOAPsnp and Atlas-SNP2. Moreover, we explore the values of key metrics related to SNVs’ quality in each algorithm and use them as post-output filtering criteria to filter out low quality SNVs. Under different coverage cutoff values, we compare four algorithms and calculate the empirical positive calling rate and sensitivity. Our results show that: 1) the overall agreement of the four calling algorithms is low, especially in non-dbSNPs; 2) the agreement of the four algorithms is similar when using different coverage cutoffs, except that the non-dbSNPs agreement level tends to increase slightly with increasing coverage; 3) SOAPsnp, SAMtools, and GATK have a higher empirical calling rate for dbSNPs compared to non-dbSNPs; and 4) overall, GATK and Atlas-SNP2 have a relatively higher positive calling rate and sensitivity, but GATK calls more SNVs.ConclusionsOur results show that the agreement between different calling algorithms is relatively low. Thus, more caution should be used in choosing algorithms, setting filtering parameters, and designing validation studies. For reliable SNV calling results, we recommend that users employ more than one algorithm and use metrics related to calling quality and coverage as filtering criteria.