Estimation of Expression Levels in Spotted Microarrays with Saturated Pixels

2007 ◽  
Vol 6 (1) ◽  
Author(s):  
Chris A Glasbey ◽  
Thorsten Forster ◽  
Peter Ghazal
Keyword(s):  
Gene Expression ◽  
Linear Model ◽  
Principal Components ◽  
Laser Scanning ◽  
Dynamic Range ◽  
Biological Data ◽  
Hyperbolic Model ◽  
Expression Levels ◽  
Biased Estimates ◽  
Gene Expression Levels

Digital images obtained by the laser scanning of spotted microarrays often include saturated pixel values. These arise when the scan settings are sufficiently high and some pixels exceed the limit L=65535 and are instead set to L. Failure to adjust for this censoring leads to biased estimates of gene expression levels. To impute censored values, we propose a linear model based on the principal components of uncensored spots on the same array. This is computationally fast, flexible to adapt to distinctive spot shapes and profiles on different arrays, and is shown to be more effective than the polynomial-hyperbolic model in correcting for the bias. The application to biological data demonstrates the potential for enhancing the dynamic range of detection. Fortran90 subroutines implementing these methods are available at http://www.bioss.ac.uk/~chris.

O-152 Investigation of the relationship of sperm motility and Kisspeptin in subfertile men

2021 ◽  
Vol 36 (Supplement_1) ◽  
Author(s):  
A Kocaman ◽  
B Ayas
Keyword(s):  
Gene Expression ◽  
Intracellular Calcium ◽  
Sperm Motility ◽  
Laser Scanning ◽  
Calcium Release ◽  
Expression Levels ◽  
Significant Difference ◽  
Motility Parameters ◽  
Gene Expression Levels

Abstract Study question Does kisspeptin administration affect the motility parameters in sperm samples of subfertile cases? Summary answer Kisspeptin administration significantly increased gene expression levels related with sperm motility as well as intracellular calcium concentrations. What is known already Sperm motility problems are among the most important causes of male infertility. In recent years, a peptide named kisspeptin has been discovered that may have effects on sperm motility. Kisspeptin is known to trigger calcium release in hypothalamic neurons. In addition, kisspeptin administration increased sperm progressive motility in studies conducted on normozoospermic individuals. Furthermore, it is suggested that kisspeptin protein in seminal plasma is positively associated with semen quality. However, there is no evidence that how kisspeptin can affect sperm in men with infertility problems. Study design, size, duration This basic research study was an in vitro experimental approach involving the use of semen samples from an infertil cases between September to December in 2020. 40 men were included in both control and experimental groups. Participants/materials, setting, methods All analyses were performed on semen samples from 10 normozoospermic (NZ), 10 asthenozoospermic (AZ), 10 oligoasthenozoospermic (OAZ) and 10 oligoastenoteratozoospermic (OATZ) men, aging between (21-40) years. Basal serum and seminal kisspeptin levels were analyzed by ELISA. Sperm were divided into two groups. Kisspeptin-13 administered in vitro. KISS1, KISS1R, CATSPER1, AKAP4 gene expressions analyzed by qRT-PCR using 2−ΔΔCt algorithm. Intracellular calcium concentration was determined with floresence spectroflurometer and laser scanning confocal microscope. Main results and the role of chance The serum kisspeptin level of NZ was significantly higher than other groups (p < 0.05). The semen kisspeptin level was significantly higher than OAZ and OATZ (p < 0.05), but not in NZ (p > 0.05). Also, KISS1 gene expression was higher in AZ compared to other groups (p < 0.05). Biochemical and gene expression analysis of kisspeptin were consistent with each other. There was a significant increase in the expression of CATSPER1 gene in AZ compared to other groups (p < 0.05). Also, AKAP4 gene expression was significantly higher in OATZ compared to other groups (p < 0.05). No significant difference was documented for the expression of KISS1R (p > 0.05). Intracellular calcium was significantly increased in AZ and NZ after kisspeptin administration. The intracellular calcium increase is consistent with increased CATSPER1 gene expression levels in AZ. Kisspeptin administration may have a significant effect on sperm motility parameters. Limitations, reasons for caution The biochemical and gene expression levels of KISS1 were consistent. However, gene expression was explored at the mRNA level for CATSPER1 and AKAP4. The protein expression analyses of these genes may confirm the results. Also, using kisspeptin antagonists may strength the results of intracellular calcium analysis. Wider implications of the findings Kisspeptin treatment for individuals diagnosed with asthenozoospermia may have therapeutic results. KISS1 quantitation may be a determining factor for the subfertility in routine semen analysis. Trial registration number OMU KAEK 2019/462

Correlation Between Gene Expression Levels and Limitations of the Empirical Bayes Methodology for Finding Differentially Expressed Genes

2005 ◽  
Vol 4 (1) ◽  
Author(s):  
Xing Qiu ◽  
Lev Klebanov ◽  
Andrei Yakovlev
Keyword(s):  
Gene Expression ◽  
Statistical Inference ◽  
Differentially Expressed Genes ◽  
Empirical Bayes ◽  
Biological Data ◽  
Differentially Expressed ◽  
Test Statistics ◽  
Gene Expressions ◽  
Expression Levels ◽  
Gene Expression Levels

Stochastic dependence between gene expression levels in microarray data is of critical importance for the methods of statistical inference that resort to pooling test statistics across genes. The empirical Bayes methodology in the nonparametric and parametric formulations, as well as closely related methods employing a two-component mixture model, represent typical examples. It is frequently assumed that dependence between gene expressions (or associated test statistics) is sufficiently weak to justify the application of such methods for selecting differentially expressed genes. By applying resampling techniques to simulated and real biological data sets, we have studied a potential impact of the correlation between gene expression levels on the statistical inference based on the empirical Bayes methodology. We report evidence from these analyses that this impact may be quite strong, leading to a high variance of the number of differentially expressed genes. This study also pinpoints specific components of the empirical Bayes method where the reported effect manifests itself.

scholarly journals A Sparse and Low-Rank Regression Model for Identifying the Relationships Between DNA Methylation and Gene Expression Levels in Gastric Cancer and the Prediction of Prognosis

Genes ◽  
2021 ◽  
Vol 12 (6) ◽  
pp. 854
Author(s):  
Yishu Wang ◽  
Lingyun Xu ◽  
Dongmei Ai
Keyword(s):  
Gene Expression ◽  
Gastric Cancer ◽  
Dna Methylation ◽  
Regression Model ◽  
The Cancer Genome Atlas ◽  
Low Rank ◽  
Expression Levels ◽  
Rank Regression ◽  
Prediction Of Prognosis ◽  
Gene Expression Levels

DNA methylation is an important regulator of gene expression that can influence tumor heterogeneity and shows weak and varying expression levels among different genes. Gastric cancer (GC) is a highly heterogeneous cancer of the digestive system with a high mortality rate worldwide. The heterogeneous subtypes of GC lead to different prognoses. In this study, we explored the relationships between DNA methylation and gene expression levels by introducing a sparse low-rank regression model based on a GC dataset with 375 tumor samples and 32 normal samples from The Cancer Genome Atlas database. Differences in the DNA methylation levels and sites were found to be associated with differences in the expressed genes related to GC development. Overall, 29 methylation-driven genes were found to be related to the GC subtypes, and in the prognostic model, we explored five prognoses related to the methylation sites. Finally, based on a low-rank matrix, seven subgroups were identified with different methylation statuses. These specific classifications based on DNA methylation levels may help to account for heterogeneity and aid in personalized treatments.

scholarly journals High heterogeneity undermines generalization of differential expression results in RNA-Seq analysis

2021 ◽  
Vol 15 (1) ◽  
Author(s):  
Weitong Cui ◽  
Huaru Xue ◽  
Lei Wei ◽  
Jinghua Jin ◽  
Xuewen Tian ◽  
...  
Keyword(s):  
Gene Expression ◽  
Differential Expression ◽  
Small Sample ◽  
Differentially Expressed ◽  
Cancer Type ◽  
Rna Seq ◽  
Sample Sizes ◽  
Large Sample ◽  
Expression Levels ◽  
Gene Expression Levels

Abstract Background RNA sequencing (RNA-Seq) has been widely applied in oncology for monitoring transcriptome changes. However, the emerging problem that high variation of gene expression levels caused by tumor heterogeneity may affect the reproducibility of differential expression (DE) results has rarely been studied. Here, we investigated the reproducibility of DE results for any given number of biological replicates between 3 and 24 and explored why a great many differentially expressed genes (DEGs) were not reproducible. Results Our findings demonstrate that poor reproducibility of DE results exists not only for small sample sizes, but also for relatively large sample sizes. Quite a few of the DEGs detected are specific to the samples in use, rather than genuinely differentially expressed under different conditions. Poor reproducibility of DE results is mainly caused by high variation of gene expression levels for the same gene in different samples. Even though biological variation may account for much of the high variation of gene expression levels, the effect of outlier count data also needs to be treated seriously, as outlier data severely interfere with DE analysis. Conclusions High heterogeneity exists not only in tumor tissue samples of each cancer type studied, but also in normal samples. High heterogeneity leads to poor reproducibility of DEGs, undermining generalization of differential expression results. Therefore, it is necessary to use large sample sizes (at least 10 if possible) in RNA-Seq experimental designs to reduce the impact of biological variability and DE results should be interpreted cautiously unless soundly validated.

scholarly journals Genome-Wide Expression and Alternative Splicing in Domesticated Sunflowers (Helianthus annuus L.) under Flooding Stress

Agronomy ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 92
Author(s):  
Joon Seon Lee ◽  
Lexuan Gao ◽  
Laura Melissa Guzman ◽  
Loren H. Rieseberg
Keyword(s):  
Gene Expression ◽  
Alternative Splicing ◽  
Mixed Model ◽  
Agricultural Land ◽  
Alcohol Fermentation ◽  
Expression Levels ◽  
Flooding Stress ◽  
Genome Wide ◽  
And Control ◽  
Gene Expression Levels

Approximately 10% of agricultural land is subject to periodic flooding, which reduces the growth, survivorship, and yield of most crops, reinforcing the need to understand and enhance flooding resistance in our crops. Here, we generated RNA-Seq data from leaf and root tissue of domesticated sunflower to explore differences in gene expression and alternative splicing (AS) between a resistant and susceptible cultivar under both flooding and control conditions and at three time points. Using a combination of mixed model and gene co-expression analyses, we were able to separate general responses of sunflower to flooding stress from those that contribute to the greater tolerance of the resistant line. Both cultivars responded to flooding stress by upregulating expression levels of known submergence responsive genes, such as alcohol dehydrogenases, and slowing metabolism-related activities. Differential AS reinforced expression differences, with reduced AS frequencies typically observed for genes with upregulated expression. Significant differences were found between the genotypes, including earlier and stronger upregulation of the alcohol fermentation pathway and a more rapid return to pre-flooding gene expression levels in the resistant genotype. Our results show how changes in the timing of gene expression following both the induction of flooding and release from flooding stress contribute to increased flooding tolerance.

Sign in / Sign up

Export Citation Format

Share Document