for the UK10K Consortium C ytochrome-c oxidase (COX) is the final enzyme (complex IV) of the mitochondrial respiratory chain, catalyzing electron transfer from ferrocytochrome c to oxygen. Three subunits (MTCO1-3) form the enzyme's catalytic core and are encoded by mitochondrial DNA (mtDNA); the remaining 11 subunits (including the subunit formerly considered a constituent of complex I 1,2 ) are nuclear encoded. Cytochrome-c oxidase deficiency has been linked to mutations in all 3 mtDNA-encoded subunits, 3 nuclear-encoded subunits (COX4I2, COX6B1, and COX7B), and 11 nuclear-encoded factors needed for assembly of the enzyme complex (SURF1,

Altered metabolism in tumor cells is required for rapid proliferation but also can influence other phenotypes that affect clinical outcomes such as metastasis and sensitivity to chemotherapy. Here, a genome-wide association study (GWAS)-guided integration of NCI-60 transcriptome and metabolome data identified ecto-5′-nucleotidase (NT5E or CD73) as a major determinant of metabolic phenotypes in cancer cells. NT5E expression and associated metabolome variations were also correlated with sensitivity to several chemotherapeutics including platinum-based treatment. NT5E mRNA levels were observed to be elevated in cells upon in vitro and in vivo acquisition of platinum resistance in ovarian cancer cells, and specific targeting of NT5E increased tumor cell sensitivity to platinum. We observed that tumor NT5E levels were prognostic for outcomes in ovarian cancer and were elevated after treatment with platinum, supporting the translational relevance of our findings. In this work, we integrated and analyzed a plethora of public data, demonstating the merit of such a systems oncology approach for the discovery of novel players in cancer biology and therapy. We experimentally validated the main findings of the NT5E gene being involved in both intrinsic and acquired resistance to platinum-based drugs. We propose that the efficacy of conventional chemotherapy could be improved by NT5E inhibition and that NT5E expression may be a useful prognostic and predictive clinical biomarker.

Background: In situ analysis of biomarkers such as DNA, RNA and proteins are important for research and diagnostic purposes. At the RNA level, plant gene expression studies rely on qPCR, RNAseq and probe-based in situ hybridization (ISH). However, for ISH experiments poor stability of RNA and RNA based probes commonly results in poor detection or poor reproducibility. Recently, the development and availability of the RNAscope RNA-ISH method addressed these problems by novel signal amplification and background suppression. This method is capable of simultaneous detection of multiple target RNAs down to the single molecule level in individual cells, allowing researchers to study spatiotemporal patterning of gene expression. However, this method has not been optimized thus poorly utilized for plant specific gene expression studies which would allow for fluorescent multiplex detection. Here we provide a step-bystep method for sample collection and pretreatment optimization to perform the RNAscope assay in the leaf tissues of model monocot plant barley. We have shown the spatial distribution pattern of HvGAPDH and the low expressed disease resistance gene Rpg1 in leaf tissue sections of barley and discuss precautions that should be followed during image analysis. Results: We have shown the ubiquitous HvGAPH and predominantly stomatal guard cell associated subsidiary cell expressed Rpg1 expression pattern in barley leaf sections and described the improve RNAscope methodology suitable for plant tissues using confocal laser microscope. By addressing the problems in the sample collection and incorporating additional sample backing steps we have significantly reduced the section detachment and experiment failure problems. Further, by reducing the time of protease treatment, we minimized the sample disintegration due to over digestion of barley tissues. Conclusions: RNAscope multiplex fluorescent RNA-ISH detection is well described and adapted for animal tissue samples, however due to morphological and structural differences in the plant tissues the standard protocol is deficient and required optimization. Utilizing barley specific HvGAPDH and Rpg1 RNA probes we report an optimized method which can be used for RNAscope detection to determine the spatial expression and semi-quantification of target RNAs. This optimized method will be immensely useful in other plant species such as the widely utilized Arabidopsis.

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Changes in the relative genetic performance of genotypes across environments are referred to as 20 genotype × environment interactions (GEIs). GEIs can affect barley breeding improvement for 21 salt-tolerance because it often complicates the evaluation and selection of superior genotypes 22 properly. The present study was seeking to evaluate the GEIs over 60 barley genotypes that were 23 evaluated for yield components and grain-yield in six-salinity environments in North Delta, 24 Egypt. Data were analyzed using the additive main effects and multiplicative interaction 25 (AMMI) and Tai's stability parameters. GEIs effects on yield explained 20.3, 20.1, 14.6 and 26 33.0% of the total variation besides, the first two principal components account for 67.3, 56.3, 27 64.3 and 83.7% of the explained variance in the four sets, respectively. The ideal genotype-28 model are G-4, G-7, G-20, G-34, G-36, and G-39 which, were most stable and high-yield29genotypes across environments (GY > 2.00 t ha -1 ), and located almost zero and/or close to zero 30 projection onto the AEC ordinate. Tai's stability parameters demonstrated that they were more 1 responsive to the environmental changes. The genotypes G-50 and G-53 showed perfect/static 2 stability (α = -0.95, -0.91, respectively). In contrast, the genotype; G-36 had α = 0 and λ = 1.10, 3 indicating parallel with the environmental effects followed by G-44. Overall, we found that GEIs 4 for grain yield is a highly significant in all sets, suggesting that responded differently across environments. This interaction may be a result of changes in genotypes' relative performance 6 across environments, due to their differential responses to various abiotic factors.

Asexual urediniospore infection of primary cereal hosts by Puccinia graminis f. sp. tritici ( Pgt ), the wheat stem rust pathogen, was considered biphasic. The first phase, spore germination and appressoria formation, requires a dark period and moisture. The second phase, host entry by the penetration peg originating from the appressoria formed over the guard cells, was thought to require light to induce natural stomata opening. Previous studies concluded that inhibition of colonization by the dark was due to lack of penetration through closed stomata. A sensitive WGA-Alexa Fluor 488 fungal staining, surface creation and biovolume analysis method was developed enabling visualization and quantification of fungal growth in planta at early infection stages surpassing visualization barriers using previous methods. The improved method was used to investigate infection processes of Pgt during stomata penetration and colonization in barley and wheat showing that penetration is light independent. Based on the visual growth and fungal biovolume analysis it was concluded that the differences in pathogen growth dynamics in both resistant and susceptible genotypes was due to light induced pathogen growth after penetration into the substomatal space. Thus, light induced plant or pathogen cues triggers pathogen growth in-planta post penetration.

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27Plant biotrophic pathogen disease resistances rely on immunity receptor-mediated programmed 28 cell death (PCD) responses, but specialized necrotrophic/hemi-biotrophic pathogens hijack these 29 mechanisms to colonize the resulting dead tissue in their necrotrophic phase. Thus, immunity receptors 30 can become necrotrophic pathogen dominant susceptibility targets but resistance mechanisms that resist 31 necrotroph manipulation are recessive resistance genes. The barley rcs5 QTL imparts recessive resistance 32 against the disease spot blotch caused by the hemi-biotrophic fungal pathogen Bipolaris sorokiniana. The 33 rcs5 genetic interval was delimited to ~0.23 cM, representing an ~234 kb genomic region containing four 34 wall-associated kinase (WAK) genes, designated HvWak2, Sbs1, Sbs2 (susceptibility to Bipolaris 35 sorokiniana 1&2), and HvWak5. Post-transcriptional gene silencing of Sbs1&2 in susceptible barley 36 cultivars resulted in resistance showing dominant susceptibility function. Allele analysis of Sbs1&2 from 37 resistant and susceptible barley cultivars identified sequence polymorphisms associated with phenotypes 38in their primary coding sequence and promoter regions, suggesting differential transcriptional regulation 39 may contribute to susceptibility. Transcript analysis of Sbs1&2 showed nearly undetectable expression in 40 resistant and susceptible cultivars prior to pathogen challenge; however, upregulation of both genes 41 occurred specifically in susceptible cultivars post-inoculation with a virulent isolate. Apoplastic wash 42 fluids collected from barley infected with a virulent isolate induced Sbs1, suggesting regulation by an 43 apoplastic-secreted effector. Thus, Sbs1&2 function as B. sorokiniana susceptibility targets and non-44 functional alleles or alleles that resist induction by the pathogen mediate rcs5-recessive resistance. The 45 sbs1&2 alleles underlying the rcs5 QTL that the pathogen is unable to manipulate are the first resistance 46 genes identified against spot blotch. 47Bipolaris sorokiniana 1 and 2) as wall-associated kinases. These genes are hijacked by the 53 hemibiotrophic pathogen in its necrotrophic phase to induce programmed cell death, facilitating disease 54 development. We report the first spot blotch resistance/susceptibility genes cloned that function via alleles 55 that cannot be specifically induced and hijacked by virulent isolates of the pathogen. 56 study on a large breeding panel provided a comprehensive assessment of the genetic architecture of this 79 durable spot blotch resistance, identifying three quantitative trait loci (QTL): Rcs-qtl-1H-11_10764, Rcs-80 qtl-3H-11_10565 and Rcs-qtl-7H-11_20162. Of these QTL, Rcs-qtl-7H-11_20162 conferred the largest 81 allelic effect across different populations (10) with several genetic studies positioning rcs5 within the 82 interval of this chromosome 7H QTL (9-11). Thus, the gene/s underlying the rcs5 QTL is an important 83 target for cloning and functional characterization, which was the objective of this study. 8...