Isoform-Level Gene Expression Profiles of Human Y Chromosome Azoospermia Factor Genes and Their X Chromosome Paralogs in the Testicular Tissue of Non-Obstructive Azoospermia Patients

2015 ◽  
Vol 14 (9) ◽  
pp. 3595-3605 ◽  
Author(s):  
Diba Ahmadi Rastegar ◽  
Mehdi Sharifi Tabar ◽  
Mehdi Alikhani ◽  
Pouria Parsamatin ◽  
Fazel Sahraneshin Samani ◽  
...  
Keyword(s):  
Gene Expression ◽  
Y Chromosome ◽  
X Chromosome ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Testicular Tissue ◽  
Obstructive Azoospermia ◽  
Azoospermia Factor ◽  
Human Y Chromosome

scholarly journals A SVM Model for Candidate Y-chromosome Gene Discovery in Prostate Cancer

10.29007/3nzw ◽  
2019 ◽  
Author(s):  
Wageesha Rasanjana ◽  
Sandun Rajapaksa ◽  
Indika Perera ◽  
Dulani Meedeniya
Keyword(s):  
Gene Expression ◽  
Prostate Cancer ◽  
Y Chromosome ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Support Vector ◽  
Body Tissues ◽  
Average Accuracy ◽  
To Come ◽  
Significant Expression

Prostate cancer is widely known to be one of the most common cancers among men around the world. Due to its high heterogeneity, many of the studies carried out to identify the molecular level causes for cancer have only been partially successful. Among the techniques used in cancer studies, gene expression profiling is seen to be one of the most popular techniques due to its high usage. Gene expression profiles reveal information about the functionality of genes in different body tissues at different conditions. In order to identify cancer-decisive genes, differential gene expression analysis is carried out using statistical and machine learning methodologies. It helps to extract information about genes that have significant expression differences between healthy tissues and cancerous tissues. In this paper, we discuss a comprehensive supervised classification approach using Support Vector Machine (SVM) models to investigate differentially expressed Y-chromosome genes in prostate cancer. 8 SVM models, which are tuned to have 98.3% average accuracy have been used for the analysis. We were able to capture genes like CD99 (MIC2), ASMTL, DDX3Y and TXLNGY to come out as the best candidates. Some of our results support existing findings while introducing novel findings to be possible prostate cancer candidates.

X-Reactivation Impacts Human iPSC Differentiation Potential Towards Blood

Blood ◽  
2013 ◽  
Vol 122 (21) ◽  
pp. 4838-4838
Author(s):  
Roksana Moraghebi ◽  
Agnete Kirkeby ◽  
Marcus Larsson ◽  
Andreas Herbst ◽  
Malin Parmar ◽  
...  
Keyword(s):  
Gene Expression ◽  
Cell Differentiation ◽  
Amniotic Fluid ◽  
Cell Lines ◽  
X Chromosome ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Differentiation Potential ◽  
Ips Cell ◽  
Differentiation Capacity

Abstract To determine novel key regulators that direct ES/iPS cell differentiation to hematopoietic lineages, we compared the gene expression profiles of multiple iPS cell lines with defferential blood forming capacity. We generated multiple iPS cell lines from amniotic fluid derived mesenchymal stromal cells (AF-iPS) which differentiated towards hematopoietic lineages using our standardized and highly reproducible differentiation protocol. Of the 9 AF-iPS cell lines derived from an individual female patient, the average efficiency of CD45+ hematopoietic cells was 14.2 +/- 9% (range 1.6 to 26.3%). To elucidate the possible reasons for this diversity in efficiency, we grouped the AF-iPS cell lines on the basis of lowest and highest blood differentiation capacity and compared their gene expression profiles by microarray. We found very few changes above 1.5-fold, but interestingly, among the 11 genes that were over-expressed in the AF-iPSC lines with poor blood differentiation efficiency 10 were located on X chromosome, and the remaining one reported to be involved in Notch signalling. A combination of cumulative sum analysis and the location of differentially expressed genes on the X chromosome identified putative regions of reactivation at multiple, but distinct locations. The possibility of X-reactivation in these female lines was reinforced further where lower levels of XIST were seen in AF-iPSC lines shown to have low blood forming potential, however only half of the iPS cell lines with high blood differentiation capacity showed normal XIST expression when compared to the amniotic fluid mesenchymal starting cell material. To determine whether the block in differentiation was tissue specific we tested the differentiation capacity of the AF-iPSC lines towards neuronal lineages. Intriguingly we found neural cell differentiation was not hampered within all lines with poor blood potential suggesting that the over-expression of genes as a consequence of X-reactivation can impart a specific negative effect on differentiation towards the blood lineages from pluripotency stage, while not having an effect on neuronal cell development. To further define the source of this block, we have begun working knocking down the overexpressed genes on X chromosome in lines with poor blood differentiation potential to determine whether the efficiency can be increased (or fully rescued) with one, or a combination of these 11 candidate genes. These results have implications for the identification and selection of female iPS lines suitable for therapeutic purposes. Disclosures: No relevant conflicts of interest to declare.

1327: Gene Expression Profiles in Benign Prostatic Hyperplasia

2004 ◽  
Vol 171 (4S) ◽  
pp. 349-350
Author(s):  
Gaelle Fromont ◽  
Michel Vidaud ◽  
Alain Latil ◽  
Guy Vallancien ◽  
Pierre Validire ◽  
...  
Keyword(s):  
Gene Expression ◽  
Benign Prostatic Hyperplasia ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Prostatic Hyperplasia
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