A novel approach for human whole transcriptome analysis based on absolute gene expression of microarray data
Background In spite of the emergence of RNA sequencing (RNA-seq), microarrays remain in widespread use for gene expression analysis in the clinic. There are over 767,000 RNA microarrays from human samples in public repositories, which are an invaluable resource for biomedical research and personaliz...
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PeerJ Inc.
2017-12-01
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Article |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Shirley Bikel Leonor Jacobo-Albavera Fausto Sánchez-Muñoz Fernanda Cornejo-Granados Samuel Canizales-Quinteros Xavier Soberón Rogerio R. Sotelo-Mundo Blanca E. del Río-Navarro Alfredo Mendoza-Vargas Filiberto Sánchez Adrian Ochoa-Leyva |
spellingShingle |
Shirley Bikel Leonor Jacobo-Albavera Fausto Sánchez-Muñoz Fernanda Cornejo-Granados Samuel Canizales-Quinteros Xavier Soberón Rogerio R. Sotelo-Mundo Blanca E. del Río-Navarro Alfredo Mendoza-Vargas Filiberto Sánchez Adrian Ochoa-Leyva A novel approach for human whole transcriptome analysis based on absolute gene expression of microarray data PeerJ Microarray Transcriptome Human Personalized medicine Absolute gene expression Transcriptomics |
author_facet |
Shirley Bikel Leonor Jacobo-Albavera Fausto Sánchez-Muñoz Fernanda Cornejo-Granados Samuel Canizales-Quinteros Xavier Soberón Rogerio R. Sotelo-Mundo Blanca E. del Río-Navarro Alfredo Mendoza-Vargas Filiberto Sánchez Adrian Ochoa-Leyva |
author_sort |
Shirley Bikel |
title |
A novel approach for human whole transcriptome analysis based on absolute gene expression of microarray data |
title_short |
A novel approach for human whole transcriptome analysis based on absolute gene expression of microarray data |
title_full |
A novel approach for human whole transcriptome analysis based on absolute gene expression of microarray data |
title_fullStr |
A novel approach for human whole transcriptome analysis based on absolute gene expression of microarray data |
title_full_unstemmed |
A novel approach for human whole transcriptome analysis based on absolute gene expression of microarray data |
title_sort |
novel approach for human whole transcriptome analysis based on absolute gene expression of microarray data |
publisher |
PeerJ Inc. |
series |
PeerJ |
issn |
2167-8359 |
publishDate |
2017-12-01 |
description |
Background In spite of the emergence of RNA sequencing (RNA-seq), microarrays remain in widespread use for gene expression analysis in the clinic. There are over 767,000 RNA microarrays from human samples in public repositories, which are an invaluable resource for biomedical research and personalized medicine. The absolute gene expression analysis allows the transcriptome profiling of all expressed genes under a specific biological condition without the need of a reference sample. However, the background fluorescence represents a challenge to determine the absolute gene expression in microarrays. Given that the Y chromosome is absent in female subjects, we used it as a new approach for absolute gene expression analysis in which the fluorescence of the Y chromosome genes of female subjects was used as the background fluorescence for all the probes in the microarray. This fluorescence was used to establish an absolute gene expression threshold, allowing the differentiation between expressed and non-expressed genes in microarrays. Methods We extracted the RNA from 16 children leukocyte samples (nine males and seven females, ages 6–10 years). An Affymetrix Gene Chip Human Gene 1.0 ST Array was carried out for each sample and the fluorescence of 124 genes of the Y chromosome was used to calculate the absolute gene expression threshold. After that, several expressed and non-expressed genes according to our absolute gene expression threshold were compared against the expression obtained using real-time quantitative polymerase chain reaction (RT-qPCR). Results From the 124 genes of the Y chromosome, three genes (DDX3Y, TXLNG2P and EIF1AY) that displayed significant differences between sexes were used to calculate the absolute gene expression threshold. Using this threshold, we selected 13 expressed and non-expressed genes and confirmed their expression level by RT-qPCR. Then, we selected the top 5% most expressed genes and found that several KEGG pathways were significantly enriched. Interestingly, these pathways were related to the typical functions of leukocytes cells, such as antigen processing and presentation and natural killer cell mediated cytotoxicity. We also applied this method to obtain the absolute gene expression threshold in already published microarray data of liver cells, where the top 5% expressed genes showed an enrichment of typical KEGG pathways for liver cells. Our results suggest that the three selected genes of the Y chromosome can be used to calculate an absolute gene expression threshold, allowing a transcriptome profiling of microarray data without the need of an additional reference experiment. Discussion Our approach based on the establishment of a threshold for absolute gene expression analysis will allow a new way to analyze thousands of microarrays from public databases. This allows the study of different human diseases without the need of having additional samples for relative expression experiments. |
topic |
Microarray Transcriptome Human Personalized medicine Absolute gene expression Transcriptomics |
url |
https://peerj.com/articles/4133.pdf |
work_keys_str_mv |
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doaj-d450432259ab4802a5d0140f5780be8d2020-11-24T22:24:32ZengPeerJ Inc.PeerJ2167-83592017-12-015e413310.7717/peerj.4133A novel approach for human whole transcriptome analysis based on absolute gene expression of microarray dataShirley Bikel0Leonor Jacobo-Albavera1Fausto Sánchez-Muñoz2Fernanda Cornejo-Granados3Samuel Canizales-Quinteros4Xavier Soberón5Rogerio R. Sotelo-Mundo6Blanca E. del Río-Navarro7Alfredo Mendoza-Vargas8Filiberto Sánchez9Adrian Ochoa-Leyva10Departamento de Microbiología Molecular, Universidad Nacional Autónoma de México, Instituto de Biotecnología, Cuernavaca, Morelos, MéxicoInstituto Nacional de Medicina Genómica, Instituto Nacional de Medicina Genómica, México City, MéxicoDepartamento de Inmunología, Instituto Nacional de Cardiología Ignacio Chávez (INCICh), México City, MéxicoDepartamento de Microbiología Molecular, Universidad Nacional Autónoma de México, Instituto de Biotecnología, Cuernavaca, Morelos, MéxicoUnidad de Genómica de Poblaciones Aplicada la Salud, Instituto Nacional de Medicina Genómica, México City, MéxicoInstituto Nacional de Medicina Genómica, Instituto Nacional de Medicina Genómica, México City, MéxicoLaboratorio de Estructura Biomolecular, Centro de Investigación en Alimentación y Desarrollo, A.C. (CIAD), Hermosillo, Sonora, MéxicoHospital Infantil de México Federico Gómez, Ciudad de México, Ciudad de México, MéxicoInstituto Nacional de Medicina Genómica, Instituto Nacional de Medicina Genómica, México City, MéxicoDepartamento de Microbiología Molecular, Universidad Nacional Autónoma de México, Instituto de Biotecnología, Cuernavaca, Morelos, MéxicoDepartamento de Microbiología Molecular, Universidad Nacional Autónoma de México, Instituto de Biotecnología, Cuernavaca, Morelos, MéxicoBackground In spite of the emergence of RNA sequencing (RNA-seq), microarrays remain in widespread use for gene expression analysis in the clinic. There are over 767,000 RNA microarrays from human samples in public repositories, which are an invaluable resource for biomedical research and personalized medicine. The absolute gene expression analysis allows the transcriptome profiling of all expressed genes under a specific biological condition without the need of a reference sample. However, the background fluorescence represents a challenge to determine the absolute gene expression in microarrays. Given that the Y chromosome is absent in female subjects, we used it as a new approach for absolute gene expression analysis in which the fluorescence of the Y chromosome genes of female subjects was used as the background fluorescence for all the probes in the microarray. This fluorescence was used to establish an absolute gene expression threshold, allowing the differentiation between expressed and non-expressed genes in microarrays. Methods We extracted the RNA from 16 children leukocyte samples (nine males and seven females, ages 6–10 years). An Affymetrix Gene Chip Human Gene 1.0 ST Array was carried out for each sample and the fluorescence of 124 genes of the Y chromosome was used to calculate the absolute gene expression threshold. After that, several expressed and non-expressed genes according to our absolute gene expression threshold were compared against the expression obtained using real-time quantitative polymerase chain reaction (RT-qPCR). Results From the 124 genes of the Y chromosome, three genes (DDX3Y, TXLNG2P and EIF1AY) that displayed significant differences between sexes were used to calculate the absolute gene expression threshold. Using this threshold, we selected 13 expressed and non-expressed genes and confirmed their expression level by RT-qPCR. Then, we selected the top 5% most expressed genes and found that several KEGG pathways were significantly enriched. Interestingly, these pathways were related to the typical functions of leukocytes cells, such as antigen processing and presentation and natural killer cell mediated cytotoxicity. We also applied this method to obtain the absolute gene expression threshold in already published microarray data of liver cells, where the top 5% expressed genes showed an enrichment of typical KEGG pathways for liver cells. Our results suggest that the three selected genes of the Y chromosome can be used to calculate an absolute gene expression threshold, allowing a transcriptome profiling of microarray data without the need of an additional reference experiment. Discussion Our approach based on the establishment of a threshold for absolute gene expression analysis will allow a new way to analyze thousands of microarrays from public databases. This allows the study of different human diseases without the need of having additional samples for relative expression experiments.https://peerj.com/articles/4133.pdfMicroarrayTranscriptomeHumanPersonalized medicineAbsolute gene expressionTranscriptomics |