Cited by 230Molecular Biology Techniques and ApplicationsGene expression and cancer classificationSingle-cell and spatial transcriptomics

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Quality control parameters on a large dataset of regionally dissected human control brains for whole genome expression studies

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Trabzuni, Daniah, Ryten, Mina, Walker, Robert, Smith, Colin, Imran, Sabaena, Ramasamy, Adaikalavan, Weale, Michael E., Hardy, John·2011·Journal of Neurochemistry

DOI 10.1111/j.1471-4159.2011.07432.xPMC PMC3664422

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Abstract

We are building an open-access database of regional human brain expression designed to allow the genome-wide assessment of genetic variability on expression. Array and RNA sequencing technologies make assessment of genome-wide expression possible. Human brain tissue is a challenging source for this work because it can only be obtained several and variable hours post-mortem and after varying agonal states. These variables alter RNA integrity in a complex manner. In this report, we assess the effect of post-mortem delay, agonal state and age on gene expression, and the utility of pH and RNA integrity number as predictors of gene expression as measured on 1266 Affymetrix Exon Arrays. We assessed the accuracy of the array data using QuantiGene, as an independent non-PCR-based method. These quality control parameters will allow database users to assess data accuracy. We report that within the parameters of this study post-mortem delay, agonal state and age have little impact on array quality, array data are robust to variable RNA integrity, and brain pH has only a small effect on array performance. QuantiGene gave very similar expression profiles as array data. This study is the first step in our initiative to make human, regional brain expression freely available.

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Fig. 1 Description of the data used in the analysis.CC BY · PubMed Central

Fig. 2 (a) Scatter plot for total RNA samples with linear regression line of RIN numbers for pH. Plot shows the effect of pH on RIN number for RNA samples isolated from 13 region of control brain tissue. Test p-values is test p-value = 1.0 × 10−4, r-value = 0.145. Including the low pH values of < 5.9. (b) Scatter plot for total RNA samples with linear regression line of RIN numbers for pH. Plot shows the effect of pH on RIN number for RNA samples isolated from 13 region of control brain tissue. No significant correlation was obtained with r-value = 0.0016 and p-value = 0.82. Samples with low pH value of < 5.9 were excluded.CC BY · PubMed Central

Fig. 3 Bar chart to show variation in %P by brain region (CRBL, WHMT).This graph shows the different performance of samples from specific brain regions on the array. These results are highly significant p-values (1.3 × 10−24 ). The heights of the bars represent the mean. The error bars represent the SEM.CC BY · PubMed Central

Fig. 4 Scatter plot for total RNA samples with linear regression line of Present call (%P) for pH. Scatter plot shows that pH significantly explains 12.0% of the variation in %P (p = 2.3 × 10−9, r = 0.353), including samples with low pH values. Low pH values are driving the regression analysis.CC BY · PubMed Central

Fig. 5 QuantiGene validation of microarray expression data. (a) SCN8A expression level between different regions. The graph shows high expression in OCTX compare with other regions. It is clear that this gene in mostly not expressed in WHMT region (expression level close to zero) also it presenting large error bar. (b) MAPT, showing higher expression in OCTX compare with other brain regions. These results confirm the array data with significant p-values of < 0.01. The expression level is presenting the mean and the error bars is SEM.CC BY · PubMed Central

Fig. 6 QuantiGene validation of microarray expression data for LRRK2 expression level in different regions. The graph shows higher expression in OCTX compare with other regions. Wilcoxon-signed rank test was performed and these results confirm the difference between regions in array data is significant. The expression level is presenting the median and the stars indicating the significant difference in expression with p-values of < 0.01. In this case, as LRRK2 expression level was very low, it was unreliable to use SEM and Wilcoxon’s test was performed using the median values.CC BY · PubMed Central

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Single-Step Method of RNA Isolation by Acid Guanidinium Thiocyanate–Phenol–Chloroform Extraction
Chomczynski, P., & Sacchi, N. (1987) · Analytical Biochemistry · doi:10.1006/abio.1987.9999 · Cited by 65,515 · cited 1×
“Total RNA was isolated from human post-mortem brain tissues based on the single-step method of RNA isolation (Chomczynski and Sacchi 1987) using the miRNeasy 96 kit (Qiagen, Crawley, UK).”
Method
The RIN: an RNA integrity number for assigning integrity values to RNA measurements
Schroeder, A., Mueller, O., Stocker, S., Salowsky, R., Leiber, M., Gassmann, M., Lightfoot, S., Menzel, W., Granzow, M., & Ragg, T. (2006) · BMC Molecular Biology · doi:10.1186/1471-2199-7-3 · Cited by 2,623
mRNA stability in mammalian cells
Ross, J. (1995) · Microbiological Reviews · doi:10.1128/mr.59.3.423-450.1995 · Cited by 1,411
Evidence Based Selection of Housekeeping Genes
de Jonge, H. J. M., Fehrmann, R. S. N., de Bont, E. S. J. M., Hofstra, R. M. W., Gerbens, F., Kamps, W. A., de Vries, E. G. E., van der Zee, A. G. J., Meerman, G. J. T., & ter Elst, A. (2007) · PLoS ONE · doi:10.1371/journal.pone.0000898 · Cited by 748
Evaluation of DNA microarray results with quantitative gene expression platforms
Canales, R. D., Luo, Y., Willey, J. C., Austermiller, B., Bárbácioru, C., Boysen, C., Hunkapiller, K., Jensen, R. V., Knight, C. R., Lee, K. Y., et al. (2006) · Nature Biotechnology · doi:10.1038/nbt1236 · Cited by 622
Towards standardization of RNA quality assessment using user-independent classifiers of microcapillary electrophoresis traces
Imbeaud, S. (2005) · Nucleic Acids Research · doi:10.1093/nar/gni054 · Cited by 556 · cited 2×
“The calculation of RIN value is largely based on ribosomal RNA separation although this measure has been shown to be inconsistent (Imbeaud et al. 2005; Schroeder et al. 2006; Sherwood et al. 2011).”
A survey of genetic human cortical gene expression
Myers, A. J., Gibbs, J. R., Webster, J. A., Rohrer, K., Zhao, A., Marlowe, L., Kaleem, M., Leung, D., Bryden, L., Nath, P., et al. (2007) · Nature Genetics · doi:10.1038/ng.2007.16 · Cited by 479
Self-citation
Validity of nucleic acid purities monitored by 260nm/280nm absorbance ratios.
Glasel, J. A. (1995) · PubMed · Cited by 437
Human postmortem tissue: What quality markers matter?
Stan, A. D., Ghose, S., Gao, X.-M., Roberts, R. C., Lewis-Amezcua, K., Hatanpaa, K. J., & Tamminga, C. A. (2006) · Brain Research · doi:10.1016/j.brainres.2006.09.025 · Cited by 361
The relative importance of premortem acidosis and postmortem interval for human brain gene expression studies: selective mRNA vulnerability and comparison with their encoded proteins
Harrison, P. J., Heath, P. R., Eastwood, S. L., Burnet, P. W. J., McDonald, B., & Pearson, R. C. A. (1995) · Neuroscience Letters · doi:10.1016/0304-3940(95)12102-a · Cited by 342
Effect of agonal and postmortem factors on gene expression profile: quality control in microarray analyses of postmortem human brain
Tomita, H., Vawter, M. P., Walsh, D. M., Evans, S. J., Choudary, P. V., Li, J., Overman, K. M., Atz, M. E., Myers, R. M., Jones, E. G., et al. (2004) · Biological Psychiatry · doi:10.1016/j.biopsych.2003.10.013 · Cited by 331 · cited 4×
“The most reliable and widely used parameter is the present call (%P) (Tomita et al. 2004; Weis et al. 2007).”
BackgroundMethodResultInfluential
The Sun Health Research Institute Brain Donation Program: Description and Eexperience, 1987–2007
Beach, T. G., Sue, L. I., Walker, D. G., Roher, A. E., Lue, L., Vedders, L. J., Connor, D. J., Sabbagh, M. N., & Rogers, J. (2008) · Cell and Tissue Banking · doi:10.1007/s10561-008-9067-2 · Cited by 254
The patients dying after long terminal phase have acidotic brains; implications for biochemical measurements on autopsy tissue
Hardy, J. A., Wester, P., Winblad, B., Gezelius, C., Bring, G., & Eriksson, A. (1985) · Journal of Neural Transmission · doi:10.1007/bf01251916 · Cited by 185
Self-citation
Cross-platform comparison of SYBR® Green real-time PCR with TaqMan PCR, microarrays and other gene expression measurement technologies evaluated in the MicroArray Quality Control (MAQC) study
Arikawa, E., Sun, Y., Wang, J., Zhou, Q., Ning, B., Dial, S. L., Guo, L., & Yang, J. (2008) · BMC Genomics · doi:10.1186/1471-2164-9-328 · Cited by 170
Effects of Antemortem and Postmortem Variables on Human Brain mRNA Quality: A BrainNet Europe Study
Durrenberger, P. F., Fernando, S., Kashefi, S. N., Ferrer, I., Hauw, J.-J., Seilhean, D., Smith, C., Walker, R., Al-Sarraj, S., Troakes, C., et al. (2010) · Journal of Neuropathology & Experimental Neurology · doi:10.1097/nen.0b013e3181c7e32f · Cited by 161
Self-citation
Postmortem interval effect on RNA and gene expression in human brain tissue
Birdsill, A. C., Walker, D. G., Lue, L., Sue, L. I., & Beach, T. G. (2010) · Cell and Tissue Banking · doi:10.1007/s10561-010-9210-8 · Cited by 157
pH measurement as quality control on human post mortem brain tissue: a study of the BrainNet Europe consortium
Monoranu, C. M., Apfelbacher, M., Grünblatt, E., Puppe, B., Alafuzoff, I., Ferrer, I., Al‐Saraj, S., Keyvani, K., Schmitt, A., Falkai, P., et al. (2009) · Neuropathology and Applied Neurobiology · doi:10.1111/j.1365-2990.2008.01003a.x · Cited by 121
Identification of valid reference genes for the normalization of RT qPCR gene expression data in human brain tissue
Coulson, D. T. R., Brockbank, S., Quinn, J. G., Murphy, S., Ravid, R., Irvine, G. B., & Johnston, J. A. (2008) · BMC Molecular Biology · doi:10.1186/1471-2199-9-46 · Cited by 120 · cited 2×
“The approach to the selection of reference genes is explained in previous studies (de Jonge et al. 2007; Coulson et al. 2008).”
Background
Quality control for microarray analysis of human brain samples: The impact of postmortem factors, RNA characteristics, and histopathology
Weis, S., Llenos, I. C., Dulay, J. R., Elashoff, M. R., Martínez-Murillo, F., & Miller, C. L. (2007) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2007.06.001 · Cited by 118 · cited 1×
“The most reliable and widely used parameter is the present call (%P) (Tomita et al. 2004; Weis et al. 2007).”
Method
Selection of optimal reference genes for normalization in quantitative RT-PCR
Chervoneva, I., Li, Y., Schulz, S., Croker, S. P., Wilson, C., Waldman, S. A., & Hyslop, T. (2010) · BMC Bioinformatics · doi:10.1186/1471-2105-11-253 · Cited by 112
mRNA profiling in forensic genetics I: Possibilities and limitations
Vennemann, M., & Koppelkamm, A. (2010) · Forensic Science International · doi:10.1016/j.forsciint.2010.07.006 · Cited by 111 · cited 1×
“It remains possible that there may be selective loss of RNA within an hour because the half-life of some mRNA species has been reported to be as short as 15 min, while others may be as long as 22 days depending on the tissue type and storage conditions (Ross 1995; Barrachina et al. 2006; Bahar et al. 2007; Beach et al…”
Background
Exon array data analysis using Affymetrix power tools and R statistical software
Lockstone, H. E. (2011) · Briefings in Bioinformatics · doi:10.1093/bib/bbq086 · Cited by 100
Tissue and organ donation for research in forensic pathology: the MRC Sudden Death Brain and Tissue Bank
Millar, T., WALKER, R. E., Arango, J. C., Ironside, J. W., Harrison, D. J., MacIntyre, D. J., Blackwood, D., Smith, C., & Bell, J. E. (2007) · The Journal of Pathology · doi:10.1002/path.2247 · Cited by 82
Self-citation
TaqMan PCR assay in the control of RNA normalization in human post-mortem brain tissue
Barrachina, M., Castaño, E., & Ferrer, I. (2006) · Neurochemistry International · doi:10.1016/j.neuint.2006.01.018 · Cited by 73 · cited 1×
“It remains possible that there may be selective loss of RNA within an hour because the half-life of some mRNA species has been reported to be as short as 15 min, while others may be as long as 22 days depending on the tissue type and storage conditions (Ross 1995; Barrachina et al. 2006; Bahar et al. 2007; Beach et al…”
Background
Effect of pre- and postmortem variables on specific mRNA levels in human brain
Burke, W. J., O’Malley, K. L., Chung, H. D., Harmon, S., Miller, J. P., & van den Berg, L. H. (1991) · Molecular Brain Research · doi:10.1016/0169-328x(91)90018-s · Cited by 71
Brain pH has a significant impact on human postmortem hippocampal gene expression profiles
Mexal, S., Berger, R., Adams, C. E., Ross, R. G., Freedman, R., & Leonard, S. S. (2006) · Brain Research · doi:10.1016/j.brainres.2006.05.043 · Cited by 66 · cited 1×
“We found that pH is the most important post-mortem factor influencing RIN-based RNA integrity, a result consistent with previous studies (Hardy et al. 1985; Mexal et al. 2006; Chevyreva et al. 2008; Monoranu et al. 2009; Durrenberger et al. 2010).”
Result
Long-term stability of RNA in post-mortem bovine skeletal muscle, liver and subcutaneous adipose tissues
Bahar, B., Monahan, F. J., MOLONEY, A. P., Schmidt, O., MacHugh, D. E., & Sweeney, T. (2007) · BMC Molecular Biology · doi:10.1186/1471-2199-8-108 · Cited by 65 · cited 1×
“It remains possible that there may be selective loss of RNA within an hour because the half-life of some mRNA species has been reported to be as short as 15 min, while others may be as long as 22 days depending on the tissue type and storage conditions (Ross 1995; Barrachina et al. 2006; Bahar et al. 2007; Beach et al…”
Background
Assessing RNA quality in postmortem human brain tissue
Chevyreva, I., Faull, R. L. M., Green, C. R., & Nicholson, L. F. B. (2007) · Experimental and Molecular Pathology · doi:10.1016/j.yexmp.2007.08.019 · Cited by 52 · cited 1×
“We found that pH is the most important post-mortem factor influencing RIN-based RNA integrity, a result consistent with previous studies (Hardy et al. 1985; Mexal et al. 2006; Chevyreva et al. 2008; Monoranu et al. 2009; Durrenberger et al. 2010).”
Result
The Preparation of Biologically Active Messenger RNA from Human Postmortem Brain Tissue
Gilbert, J. M., Brown, B. A., Strocchi, P., Bird, E. D., & Marotta, C. A. (1981) · Journal of Neurochemistry · doi:10.1111/j.1471-4159.1981.tb01689.x · Cited by 47
Exon-array profiling unlocks clinically and biologically relevant gene signatures from formalin-fixed paraffin-embedded tumour samples
Hall, J., Leong, H. S., Armenoult, L., Newton, G., Valentine, H. R., Irlam, J. J., Möller‐Levet, C. S., Sikand, K. A., Pepper, S. D. V., Miller, C. J., et al. (2011) · British Journal of Cancer · doi:10.1038/bjc.2011.66 · Cited by 28
RNA integrity in post mortem human variant Creutzfeldt-Jakob disease (vCJD) and control brain tissue
Sherwood, K. R., Head, M. W., WALKER, R. E., Smith, C., Ironside, J. W., & Fazakerley, J. K. (2011) · Neuropathology and Applied Neurobiology · doi:10.1111/j.1365-2990.2011.01162.x · Cited by 26
Self-citation
Expression Profile Analysis of Neurodegenerative Disease: Advances in Specificity and Resolution
Glanzer, J. G., Haydon, P. G., & Eberwine, J. H. (2004) · Neurochemical Research · doi:10.1023/b:nere.0000023603.17615.8c · Cited by 24
The postmortem Alzheimer brain is a source of structurally and functionally intact astrocytic messenger RNA
Sajdel, E. M., Majocha, R. E., Salim, M., Zain, S. B., & Marotta, C. A. (1988) · Journal of Neuroscience Methods · doi:10.1016/0165-0270(88)90189-6 · Cited by 24
Sample matching by inferred agonal stress in gene expression analyses of the brain
Li, J. Z., Meng, F., Tsavaler, L., Evans, S. J., Choudary, P. V., Tomita, H., Vawter, M. P., Walsh, D. M. A., Shokoohi, V., Chung, T. R., et al. (2007) · BMC Genomics · doi:10.1186/1471-2164-8-336 · Cited by 19
Whole genome expression as a quantitative trait
Hardy, J., Trabzuni, D., & Ryten, M. (2009) · Biochemical Society Transactions · doi:10.1042/bst0371276 · Cited by 9 · cited 2×
“Furthermore, this study is the first step of an ongoing multi-regional human brain expression project that has been established to build an open-access database of identified genome-wide genetic variability in relation with gene eQTLs and sQTL as well as for detailed expression analysis (Hardy et al. 2009).”
BackgroundSelf-citation

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Authors: Trabzuni, D., Ryten, M., Walker, R., Smith, C., Imran, S., Ramasamy, A., Weale, M. E., & Hardy, J.
Affiliations: UCL Queen Square Institute of Neurology (GB)
University of Edinburgh (GB)
Guy's Hospital (GB)
Corresponding author: Hardy, John
ORCID: Trabzuni, Daniah
Ryten, Mina
Walker, Robert
Smith, Colin
Ramasamy, Adaikalavan
Weale, Michael E.
Hardy, John
Venue: Journal of Neurochemistry
Publisher: Wiley
Published: 2011-09-20
Volume: 119
Issue: 2
Pages: 275-282
ISSN: 0022-3042 (ISSN-L)
1471-4159
DOI: 10.1111/j.1471-4159.2011.07432.x
PMC: PMC3664422
OpenAlex: W2066399252
Cited by: 229
References: 36
Citations by year: 2026: 5 · 2025: 7 · 2024: 4 · 2023: 10 · 2022: 10 · 2021: 22 · 2020: 13 · 2019: 24 · 2018: 23 · 2017: 25 · 2016: 24 · 2015: 20 · 2014: 16 · 2013: 14 · 2012: 9
FWCI: 5.45
Type: journal article
Language: en
Open access: green
www.ncbi.nlm.nih.gov
Licence: cc-by
onlinelibrary.wiley.com/termsAndConditions#vor (vor)
Locations: Journal of Neurochemistry (publishedVersion)
Europe PMC (PubMed Central) (publishedVersion, cc-by)
PubMed Central (publishedVersion, cc-by)
PubMed (publishedVersion)
Research Portal (King's College London) (publishedVersion, other-oa)
UCL Discovery (University College London) (submittedVersion)
Edinburgh Research Explorer (University of Edinburgh) (submittedVersion, other-oa)
Funders: Wellcome Trust (089698)
King Faisal Specialist Hospital and Research Centre
Medical Research Council (MC_G1000735)
Army Research Office
Topics: Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Molecular Biology Techniques and Applications
Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene expression and cancer classification
Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
Keywords: postmortem delay, agonal state, brain age, RNA integrity number, brain pH
MeSH terms: Adolescent, Adult, Aged, Aging, Brain Chemistry, Cause of Death, Exons, Female, United Kingdom, Humans, Hydrogen-Ion Concentration, Male, Middle Aged, Quality Control, RNA, Sex Characteristics, Tissue Banks, United States, Reproducibility of Results, DNA, Complementary, Reverse Transcriptase Polymerase Chain Reaction, Oligonucleotide Array Sequence Analysis, Gene Expression Profiling, Databases, Genetic, Microarray Analysis, Young Adult

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Quality control parameters on a large dataset of regionally dissected human control brains for whole genome expression studies

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