Addendum: Standardizing global gene expression analysis between laboratories and across platforms

Bammler, Theodore; Beyer, Richard P.; Bhattacharya, Sanchita; Boorman, Gary A.; Boyles, Abee L.; Bradford, Blair U.; Bumgarner, R. E.; Bushel, Pierre R.; Chaturvedi, Kabir; Choi, Dong‐Hee; Cunningham, Michael L.; Deng, Shibing; Dressman, Holly K.; Fannin, Rick D.; Farin, Fredrico M.; Freedman, Jonathan H.; Fry, Rebecca C.; Harper, Angel; Humble, Michael C.; Hurban, Patrick; Kavanagh, Terrance J.; Kaufmann, William K.; Kerr, Kathleen F.; Li, Jing; Lapidus, Jodi; Lasarev, Michael; Li, Jianying; Li, Yi-Ju; Lobenhofer, Edward K.; Lu, Xinfang; Malek, Renae L.; Milton, Sean; Nagalla, Srinivasa R.; O’Malley, Jean P.; Palmer, Valerie S.; Pattee, Patrick; Paules, Richard S.; Perou, Charles M.; Phillips, Kenneth L.; Qin, Li‐Xuan; Yang, Qin; Quigley, Sean; Rodland, Matthew; Rusyn, Ivan; Samson, Leona D.; Schwartz, David A.; Shi, Yan; Shin, Jung-Lim; Sieber, Stella O.; Slifer, Susan H.; Speer, Marcy C.; Spencer, Peter S.; Sproles, Dean I.; Swenberg, James A.; Suk, William A.; Sullivan, Robert; Tian, Ruhui; Tennant, Raymond W.; Todd, Signe A.; Tucker, Charles J.; Houten, Bennett Van; Weis, Brenda K.; Xuan, Shirley; Zarbl, Helmut

doi:10.1038/nmeth0605-477a

Cited by 274 publications

(127 citation statements)

References 1 publication

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“…In insects, expression patterns of only a limited set of orthologs have been compared between the ant Camponotus festinantus and D. melanogaster (19). Guided by methodological conclusions of previous studies addressing the issue of gene expression comparisons between microarray platforms (20)(21)(22)(23)(24), we performed the first large-scale comparative analysis of insect development between A. gambiae and D. melanogaster. Our analysis shows a strong positive correlation of expression for 1,039 orthologous gene pairs and reveals that orthologs frequently share similar developmental expression patterns.…”

Section: Discussionmentioning

confidence: 99%

Life cycle transcriptome of the malaria mosquito Anopheles gambiae and comparison with the fruitfly Drosophila melanogaster

Koutsos

Blass

Meister

et al. 2007

Proc. Natl. Acad. Sci. U.S.A.

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The African mosquito Anopheles gambiae is the major vector of human malaria. We report a genome-wide survey of mosquito gene expression profiles clustered temporally into developmental programs and spatially into adult tissue-specific patterns. Global expression analysis shows that genes that belong to related functional categories or that encode the same or functionally linked protein domains are associated with characteristic developmental programs or tissue patterns. Comparative analysis of our data together with data published from Drosophila melanogaster reveal an overall strong and positive correlation of developmental expression between orthologous genes. The degree of correlation varies, depending on association of orthologs with certain developmental programs or functional groups. Interestingly, the similarity of gene expression is not correlated with the coding sequence similarity of orthologs, indicating that expression profiles and coding sequences evolve independently. In addition to providing a comprehensive view of temporal and spatial gene expression during the A. gambiae life cycle, this large-scale comparative transcriptomic analysis has detected important evolutionary features of insect transcriptomes.comparative transcriptomics ͉ insect development ͉ insect evolution ͉ microarrays A nopheles gambiae is the major vector of human malaria in subSaharan Africa, a secondary vector of filariasis, and the key vector of O'nyong-nyong viral fever outbreaks. Effective transmission of pathogens results from extreme anthropophilic behavior and repeated bloodfeeding of A. gambiae adult females. Indeed, female mosquitoes are found typically around human habitations and bloodfeed largely on humans rather than animals. Therefore, successful malaria control campaigns to date have coincided largely with local control of Anopheles populations.A substantial bloodmeal is required for A. gambiae egg development, the start of the next life cycle. Eggs are fertilized while traversing the genital chamber and begin embryonic development, which normally lasts 2-3 days and is similar to that of Drosophila melanogaster despite notable morphological (1) and molecular (2) differences. Four larval stages (instars) ensue, as compared with three in Drosophila, accompanied by continuous growth. In that period, larval organs are functional and adult organs incipient or slowly developing. During metamorphosis (from larva to pupa and adult) most larval organs are histolyzed, whereas others persist or grow.To date, molecular and cell biological research on A. gambiae has used D. melanogaster as the model system. These dipterans have diverged from a common ancestor Ϸ250 mya.

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Section: Discussionmentioning

confidence: 99%

Life cycle transcriptome of the malaria mosquito Anopheles gambiae and comparison with the fruitfly Drosophila melanogaster

Koutsos

Blass

Meister

et al. 2007

Proc. Natl. Acad. Sci. U.S.A.

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“…That is, firstly, PCCs between pairwise genes are obtained by normalized tumor expression. Acceptable correlations with PCC > 0.75 are often considered high correlated and selected [34]. Here, we choose 0.8 as threshold to ensure selected pairwise genes being higher correlated and increase reliability.…”

Section: Gene-gene Interaction Networkmentioning

confidence: 99%

DriverFinder: A Gene Length-Based Network Method to Identify Cancer Driver Genes

Wei

Zhang

et al. 2017

Complexity

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Integration of multi-omics data of cancer can help people to explore cancers comprehensively. However, with a large volume of different omics and functional data being generated, there is a major challenge to distinguish functional driver genes from a sea of inconsequential passenger genes that accrue stochastically but do not contribute to cancer development. In this paper, we present a gene length-based network method, named DriverFinder, to identify driver genes by integrating somatic mutations, copy number variations, gene-gene interaction network, tumor expression, and normal expression data. To illustrate the performance of DriverFinder, it is applied to four cancer types from The Cancer Genome Atlas including breast cancer, head and neck squamous cell carcinoma, thyroid carcinoma, and kidney renal clear cell carcinoma. Compared with some conventional methods, the results demonstrate that the proposed method is effective. Moreover, it can decrease the influence of gene length in identifying driver genes and identify some rare mutated driver genes.

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“…A recent study comparing data obtained from the latest, state-of-the-art platforms showed minimal technical variation and good correlation with qRT-PCR, the gold standard for mRNA measurement (178). Similarly, recent comparative cross-laboratory studies gave very promising data (179,180). Thus, because of patients' heterogeneity and of the high complexity of sepsis pathophysiology, much will be gained from the next multicenter studies monitoring the dynamic behavior of gene expression over time (181,182).…”

Section: Toward a Genomic Approachmentioning

confidence: 99%

Monitoring Immune Dysfunctions in the Septic Patient: A New Skin for the Old Ceremony

Monneret

Venet

Pachot

et al. 2008

Mol Med

306

323

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Addendum: Standardizing global gene expression analysis between laboratories and across platforms

Cited by 274 publications

References 1 publication

Life cycle transcriptome of the malaria mosquito Anopheles gambiae and comparison with the fruitfly Drosophila melanogaster

Life cycle transcriptome of the malaria mosquito Anopheles gambiae and comparison with the fruitfly Drosophila melanogaster

DriverFinder: A Gene Length-Based Network Method to Identify Cancer Driver Genes

Monitoring Immune Dysfunctions in the Septic Patient: A New Skin for the Old Ceremony

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