We present primary results from the Sequencing Quality Control (SEQC) project, coordinated by the United States Food and Drug Administration. Examining Illumina HiSeq, Life Technologies SOLiD and Roche 454 platforms at multiple laboratory sites using reference RNA samples with built-in controls, we assess RNA sequencing (RNA-seq) performance for junction discovery and differential expression profiling and compare it to microarray and quantitative PCR (qPCR) data using complementary metrics. At all sequencing depths, we discover unannotated exon-exon junctions, with >80% validated by qPCR. We find that measurements of relative expression are accurate and reproducible across sites and platforms if specific filters are used. In contrast, RNA-seq and microarrays do not provide accurate absolute measurements, and gene-specific biases are observed, for these and qPCR. Measurement performance depends on the platform and data analysis pipeline, and variation is large for transcript-level profiling. The complete SEQC data sets, comprising >100 billion reads (10Tb), provide unique resources for evaluating RNA-seq analyses for clinical and regulatory settings.
Poorly organized tumour vasculature often results in areas of limited nutrient supply and hypoxia. Despite our understanding of solid tumour responses to hypoxia, how nutrient deprivation regionally affects tumour growth and therapeutic response is poorly understood. Here, we show the core region of solid tumours displayed glutamine deficiency compared to other amino acids. Low glutamine in tumour core regions led to dramatic histone hyper-methylation due to decreased α-ketoglutarate levels, a key cofactor for the Jumonji-domain containing (JmjC) histone demethylases (JHDMs). Using patient-derived V600EBRAF melanoma cells, we found that low glutamine-induced histone hyper-methylation resulted in cancer cell de-differentiation and resistance to BRAF inhibitor treatment, which was largely mediated by methylation on H3K27, as knockdown of the H3K27-specific demethylase KDM6B and methyltransferase EZH2 respectively reproduced and attenuated the low glutamine effects in vitro and in vivo. Thus, intra-tumoural regional variation in the nutritional microenvironment contributes to tumour heterogeneity and therapeutic response.
Partial person re-identification (re-id) is a challenging problem, where only several partial observations (images) of people are available for matching. However, few studies have provided flexible solutions to identifying a person in an image containing arbitrary part of the body. In this paper, we propose a fast and accurate matching method to address this problem. The proposed method leverages Fully Convolutional Network (FCN) to generate fix-sized spatial feature maps such that pixel-level features are consistent. To match a pair of person images of different sizes, a novel method called Deep Spatial feature Reconstruction (DSR) is further developed to avoid explicit alignment. Specifically, DSR exploits the reconstructing error from popular dictionary learning models to calculate the similarity between different spatial feature maps. In that way, we expect that the proposed FCN can decrease the similarity of coupled images from different persons and increase that from the same person. Experimental results on two partial person datasets demonstrate the efficiency and effectiveness of the proposed method in comparison with several state-ofthe-art partial person re-id approaches. Additionally, DSR achieves competitive results on a benchmark person dataset Market1501 with 83.58% Rank-1 accuracy. The website of DSR code can be found from https://github.com/ lingxiao-he/Partial-Person-ReID.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.