scholarly journals Comparison of Non-Human Primate and Human Whole Blood Tissue Gene Expression Profiles

2005 ◽  
Author(s):  
James F. Dillman III ◽  
Christopher S. Phillips
Keyword(s):  
Gene Expression ◽  
Whole Blood ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Human Whole Blood ◽  
Human Primate ◽  
Tissue Gene Expression

Blood-based multi-tissue gene expression inference with Bayesian ridge regression

2020 ◽  
Vol 36 (12) ◽  
pp. 3788-3794
Author(s):  
Wenjian Xu ◽  
Xuanshi Liu ◽  
Fei Leng ◽  
Wei Li
Keyword(s):  
Gene Expression ◽  
Gene Expression Profile ◽  
Expression Profile ◽  
Ridge Regression ◽  
Whole Blood ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Blood Gene Expression ◽  
Tissue Specific ◽  
Tissue Gene Expression

Abstract Motivation Gene expression profiling is widely used in basic and cancer research but still not feasible in many clinical applications because tissues, such as brain samples, are difficult and not ethnical to collect. Gene expression in uncollected tissues can be computationally inferred using genotype and expression quantitative trait loci. No methods can infer unmeasured gene expression of multiple tissues with single tissue gene expression profile as input. Results Here, we present a Bayesian ridge regression-based method (B-GEX) to infer gene expression profiles of multiple tissues from blood gene expression profile. For each gene in a tissue, a low-dimensional feature vector was extracted from whole blood gene expression profile by feature selection. We used GTEx RNAseq data of 16 tissues to train inference models to capture the cross-tissue expression correlations between each target gene in a tissue and its preselected feature genes in peripheral blood. We compared B-GEX with least square regression, LASSO regression and ridge regression. B-GEX outperforms the other three models in most tissues in terms of mean absolute error, Pearson correlation coefficient and root-mean-squared error. Moreover, B-GEX infers expression level of tissue-specific genes as well as those of non-tissue-specific genes in all tissues. Unlike previous methods, which require genomic features or gene expression profiles of multiple tissues, our model only requires whole blood expression profile as input. B-GEX helps gain insights into gene expressions of uncollected tissues from more accessible data of blood. Availability and implementation B-GEX is available at https://github.com/xuwenjian85/B-GEX. Supplementary information Supplementary data are available at Bioinformatics online.

Gene expression profiles in whole blood and associations with metabolic dysregulation in obesity

2018 ◽  
Vol 12 (2) ◽  
pp. 204-213
Author(s):  
Amanda J. Cox ◽  
Ping Zhang ◽  
Tiffany J. Evans ◽  
Rodney J. Scott ◽  
Allan W. Cripps ◽  
...  
Keyword(s):  
Gene Expression ◽  
Whole Blood ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Metabolic Dysregulation

Whole blood genome-wide gene expression profile in males after prolonged wakefulness and sleep recovery

2012 ◽  
Vol 44 (21) ◽  
pp. 1003-1012 ◽  
Author(s):  
R. Pellegrino ◽  
D. Y. Sunaga ◽  
C. Guindalini ◽  
R. C. S. Martins ◽  
D. R. Mazzotti ◽  
...  
Keyword(s):  
Gene Expression ◽  
Whole Blood ◽  
Inflammatory Responses ◽  
Expression Profiles ◽  
Killer Cell ◽  
Gene Expression Profiles ◽  
Sleep Loss ◽  
The Body ◽  
Dna Damage And Repair ◽  
Peripheral Tissues

Although the specific functions of sleep have not been completely elucidated, the literature has suggested that sleep is essential for proper homeostasis. Sleep loss is associated with changes in behavioral, neurochemical, cellular, and metabolic function as well as impaired immune response. Using high-resolution microarrays we evaluated the gene expression profiles of healthy male volunteers who underwent 60 h of prolonged wakefulness (PW) followed by 12 h of sleep recovery (SR). Peripheral whole blood was collected at 8 am in the morning before the initiation of PW (Baseline), after the second night of PW, and one night after SR. We identified over 500 genes that were differentially expressed. Notably, these genes were related to DNA damage and repair and stress response, as well as diverse immune system responses, such as natural killer pathways including killer cell lectin-like receptors family, as well as granzymes and T-cell receptors, which play important roles in host defense. These results support the idea that sleep loss can lead to alterations in molecular processes that result in perturbation of cellular immunity, induction of inflammatory responses, and homeostatic imbalance. Moreover, expression of multiple genes was downregulated following PW and upregulated after SR compared with PW, suggesting an attempt of the body to re-establish internal homeostasis. In silico validation of alterations in the expression of CETN3, DNAJC, and CEACAM genes confirmed previous findings related to the molecular effects of sleep deprivation. Thus, the present findings confirm that the effects of sleep loss are not restricted to the brain and can occur intensely in peripheral tissues.

Selenium Supplementation Alters Gene Expression Profiles Associated with Innate Immunity in Whole-Blood Neutrophils of Sheep

2013 ◽  
Vol 154 (1) ◽  
pp. 28-44 ◽  
Author(s):  
Hugejiletu Hugejiletu ◽  
Gerd Bobe ◽  
William R. Vorachek ◽  
M. Elena Gorman ◽  
Wayne D. Mosher ◽  
...  
Keyword(s):  
Gene Expression ◽  
Innate Immunity ◽  
Whole Blood ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Selenium Supplementation ◽  
Blood Neutrophils

scholarly journals Effects of Globin mRNA Reduction Methods on Gene Expression Profiles from Whole Blood

2006 ◽  
Vol 8 (5) ◽  
pp. 551-558 ◽  
Author(s):  
Jinny Liu ◽  
Elizabeth Walter ◽  
David Stenger ◽  
Dzung Thach
Keyword(s):  
Gene Expression ◽  
Whole Blood ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Globin Mrna ◽  
Reduction Methods
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