Although genomewide RNA expression analysis has become a routine tool in biomedical research, extracting biological insight from such information remains a major challenge. Here, we describe a powerful analytical method called Gene Set Enrichment Analysis (GSEA) for interpreting gene expression data. The method derives its power by focusing on gene sets, that is, groups of genes that share common biological function, chromosomal location, or regulation. We demonstrate how GSEA yields insights into several cancer-related data sets, including leukemia and lung cancer. Notably, where single-gene analysis finds little similarity between two independent studies of patient survival in lung cancer, GSEA reveals many biological pathways in common. The GSEA method is embodied in a freely available software package, together with an initial database of 1,325 biologically defined gene sets.

/pdf/gene-set-enrichment-analysis-a-knowledge-based-approach-for-mbpti6qljw.pdf

Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles

limma is an R/Bioconductor software package that provides an integrated solution for analysing data from gene expression experiments. It contains rich features for handling complex experimental designs and for information borrowing to overcome the problem of small sample sizes. Over the past decade, limma has been a popular choice for gene discovery through differential expression analyses of microarray and high-throughput PCR data. The package contains particularly strong facilities for reading, normalizing and exploring such data. Recently, the capabilities of limma have been significantly expanded in two important directions. First, the package can now perform both differential expression and differential splicing analyses of RNA sequencing (RNA-seq) data. All the downstream analysis tools previously restricted to microarray data are now available for RNA-seq as well. These capabilities allow users to analyse both RNA-seq and microarray data with very similar pipelines. Second, the package is now able to go past the traditional gene-wise expression analyses in a variety of ways, analysing expression profiles in terms of co-regulated sets of genes or in terms of higher-order expression signatures. This provides enhanced possibilities for biological interpretation of gene expression differences. This article reviews the philosophy and design of the limma package, summarizing both new and historical features, with an emphasis on recent enhancements and features that have not been previously described.

/pdf/limma-powers-differential-expression-analyses-for-rna-4yl7ae3arh.pdf

limma powers differential expression analyses for RNA-sequencing and microarray studies

抗原变异可使得多种致病微生物易于逃避宿主免疫应答。表达在感染红细胞表面的恶性疟原虫红细胞表面蛋白1（PfPMP1）与感染红细胞、内皮细胞、树突状细胞以及胎盘的单个或多个受体作用，在黏附及免疫逃避中起关键的作用。每个单倍体基因组var基因家族编码约60种成员，通过启动转录不同的var基因变异体为抗原变异提供了分子基础。

疟原虫var基因转换速率变化导致抗原变异[英]／Paul H, Robert P, Christodoulou Z, et al//Proc Natl Acad Sci U S A

http://www.klinikaikozpont.u-szeged.hu/pedia/images/pdf/CME_TEL/Full-Text/25.pdf

The Hallmarks of Aging

Obesity alters adipose tissue metabolic and endocrine function and leads to an increased release of fatty acids, hormones, and proinflammatory molecules that contribute to obesity associated complications. To further characterize the changes that occur in adipose tissue with increasing adiposity, we profiled transcript expression in perigonadal adipose tissue from groups of mice in which adiposity varied due to sex, diet, and the obesity-related mutations agouti (Ay) and obese (Lepob). We found that the expression of 1,304 transcripts correlated significantly with body mass. Of the 100 most significantly correlated genes, 30% encoded proteins that are characteristic of macrophages and are positively correlated with body mass. Immunohistochemical analysis of perigonadal, perirenal, mesenteric, and subcutaneous adipose tissue revealed that the percentage of cells expressing the macrophage marker F4/80 (F4/80+) was significantly and positively correlated with both adipocyte size and body mass. Similar relationships were found in human subcutaneous adipose tissue stained for the macrophage antigen CD68. Bone marrow transplant studies and quantitation of macrophage number in adipose tissue from macrophage-deficient (Csf1op/op) mice suggest that these F4/80+ cells are CSF-1 dependent, bone marrow-derived adipose tissue macrophages. Expression analysis of macrophage and nonmacrophage cell populations isolated from adipose tissue demonstrates that adipose tissue macrophages are responsible for almost all adipose tissue TNF-alpha expression and significant amounts of iNOS and IL-6 expression. Adipose tissue macrophage numbers increase in obesity and participate in inflammatory pathways that are activated in adipose tissues of obese individuals.

/pdf/obesity-is-associated-with-macrophage-accumulation-in-130af7ivca.pdf

Obesity is associated with macrophage accumulation in adipose tissue

Peroxisome proliferator activated receptor (PPAR) γ coactivator-1α (PGC-1α) is a potent transcriptional coactivator of oxidative metabolism and is induced in response to a variety of environmental cues. It regulates a broad array of target genes by coactivating a whole host of transcription factors. The estrogen-related receptor (ERR) family of nuclear receptors are key PGC-1α partners in the regulation of mitochondrial and tissue-specific oxidative metabolic pathways; these receptors also demonstrate strong physical and functional interactions with this coactivator. Here we perform comprehensive biochemical, biophysical, and structural analyses of the complex formed between PGC-1α and ERRγ. PGC-1α activation domain (PGC-1α2–220) is intrinsically disordered with limited secondary and no defined tertiary structure. Complex formation with ERRγ induces significant changes in the conformational mobility of both partners, highlighted by significant stabilization of the ligand binding domain (ERRγLBD) as determined by HDX (hydrogen/deuterium exchange) and an observed disorder-to-order transition in PGC-1α2–220. Small-angle X-ray scattering studies allow for modeling of the solution structure of the activation domain in the absence and presence of ERRγLBD, revealing a stable and compact binary complex. These data show that PGC-1α2–220 undergoes a large-scale conformational change when binding to the ERRγLBD, leading to substantial compaction of the activation domain. This change results in stable positioning of the N-terminal part of the activation domain of PGC-1α, favorable for assembly of an active transcriptional complex. These data also provide structural insight into the versatile coactivation profile of PGC-1α and can readily be extended to understand other transcriptional coregulators.

https://www.pnas.org/content/pnas/108/46/18678.full.pdf

Disorder-to-order transition underlies the structural basis for the assembly of a transcriptionally active PGC-1α/ERRγ complex

Cachexia, a progressive weight loss in cancer patients that results from tumor-induced energy wasting, is a serious problem that interferes with response to treatment and affects quality of life. Recent studies suggest that thermogenesis of adipose tissues is involved in energy wasting and also point to a link between the atrophy of fat and muscle. Tumor-derived PTHrP has emerged as a key molecule playing multiple roles in cachexia, from fat ‘browning' factor to potential therapeutic target.

Cachexia and Brown Fat: A Burning Issue in Cancer

Nucleotide sequence and hormonal regulation of mouse glycerophosphate dehydrogenase mRNA during adipocyte and muscle cell differentiation.

Insulin stimulates the acute release of adipsin from 3T3-L1 adipocytes.

Erratum: Genetic Depletion of Adipocyte Creatine Metabolism Inhibits Diet-Induced Thermogenesis and Drives Obesity (Cell Metabolism (2017) 26(4) (660–671.e3) (S1550413117304941)(10.1016/j.cmet.2017.08.009))

Bruce M. Spiegelman

Papers

Disorder-to-order transition underlies the structural basis for the assembly of a transcriptionally active PGC-1α/ERRγ complex

Cachexia and Brown Fat: A Burning Issue in Cancer

Nucleotide sequence and hormonal regulation of mouse glycerophosphate dehydrogenase mRNA during adipocyte and muscle cell differentiation.

Insulin stimulates the acute release of adipsin from 3T3-L1 adipocytes.

Erratum: Genetic Depletion of Adipocyte Creatine Metabolism Inhibits Diet-Induced Thermogenesis and Drives Obesity (Cell Metabolism (2017) 26(4) (660–671.e3) (S1550413117304941)(10.1016/j.cmet.2017.08.009))