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Analysis of age-related CpGs for forensic purpose in Chinese Han population
Forensic Science International: Genetics Supplement Series 5 (2015) e149–e150
Contents lists available at ScienceDirect
Forensic Science International: Genetics Supplement Series journal homepage: www.elsevier.com/locate/FSIGSS
Analysis of age-related CpGs for forensic purpose in Chinese Han population Y. Huang1, J. Yan1, H. Zhuk, X. Fu, Y. Hou* Department of Forensic Genetics, West China School of Basic Science and Forensic Medicine, Sichuan University (West China University of Medical Sciences), Chengdu 610041, Sichuan, China
A R T I C L E I N F O
A B S T R A C T
Article history: Received 19 August 2015 Accepted 14 September 2015 Available online 16 September 2015
Age-related CpGs (AR-CpGs) have been proved to be potential markers for forensic age prediction. However, DNA methylation (DNAm) patterns in particular AR-CpGs may be tissue specific. Meanwhile, variant methylation quantitative platforms might result in discrepant candidate markers. Recent researches carried out either by pyrosequencing or by microarray platforms were based on Caucasian samples. In this study, we aimed to screen out the AR-CpGs as potential forensic age prediction biomarkers in Chinese Han population by pyrosequencing approach. We referred the previous agerelated DNAm studies with different methods or tissue specimens, candidate markers located on 6 gene fragments were selected for DNA methylation analysis. The blood samples both from younger donors aged from 10 to 25 years and from senior donors aged from 55 to 65 years were employed to screen the candidate markers with remarkable difference in methylation values between the two age groups. Our results revealed that there were 7CpG sites resided on 3 gene fragments showed significant difference between the adolescent group and the elderly group. It implied that some of them may be potential markers for forensic age prediction in Chinese Han population and that pyrosequencing was an effective method to screen AR-CpGs and quantify the methylation values of them. ã 2015 Elsevier Ireland Ltd. All rights reserved.
Keywords: Forensic science Age prediction Methylation Pyrosequencing Human blood Chinese Han population
1. Introduction Age-related CpGs (AR-CpGs) have been proved to be effective biomarker for forensic age prediction [1]. It was well known that methylation patterns in particular AR-CpGs may be tissue specific [2]. Blood is commonly found in violent crimes. It, therefore, would be very meaningful to screen out AR-CpG which is applicable for blood. Meanwhile, recent studies have indicated that variant methylation quantitative platforms might result in discrepant candidate markers. Koch described a number of tissues-specific AR-CpGs through DNA methylation (DNAm) profiles of various cell types from public data depositories [2]. Bocklandt and Weidner optimized the pyrosequencing approach to validate AR-CpGs with linear DNAm changes during aging from saliva samples and blood samples, respectively [3,4]. They selected five fragments—ASPA, ITGA2B, PDE4C, NPTX2, and Tom1L1, where NPTX2 was also referred in Koch’s study. Most recently, in Piekarska’s study, the bisulfate pyrosequencing approach was applied to evaluate the methylation of two CpG sites in ELOVL2 [5]. These studies carried
* Corresponding author. Fax: +86 28 85501550. E-mail addresses: [email protected], [email protected] (Y. Hou). Both authors contributed equally to this work.
1
http://dx.doi.org/10.1016/j.fsigss.2015.09.060 1875-1768/ ã 2015 Elsevier Ireland Ltd. All rights reserved.
out by pyrosequencing mentioned above were all based on Caucasian race samples. The aim of this study was to screen out the AR-CpGs as potential forensic age prediction biomarkers in Chinese Han population by pyrosequencing approach in blood specimens. 2. Materials and methods 10 blood samples from younger donors (aged from 10 to 25 years) and 10 blood samples from senior donors (aged from 55 to 65 years) were employed to screen the candidate markers. DNA was extracted from the peripheral venous blood using a DNeasy Blood & Tissue Kit (QIAGEN) following the manufacturer’s instructions. Based on the previous studies of age-related DNAm using different methods or tissue specimens [3–5], thirty-eight candidate markers located on six gene fragments were chosen for DNA methylation analysis by pyrosequencing. 100 ng extracted DNA was bisulfite-converted using the EpiTect Bisulfite Kit (QIAGEN). PCR reactions were carried out by the PyroMark1 PCR Kit (Qiagen). 20 ng of modified DNA template was added to the mixture for a total reaction volume of 25 mL. The amplification program consisted of an initial denaturation step at 95 C for 10 min.
e150
Y. Huang et al. / Forensic Science International: Genetics Supplement Series 5 (2015) e149–e150
Table 1 Mann–Whitney test of the methylation values of candidate markers between younger donors and senior donors. Candidate markers
MapInfo
p-value
Candidate markers
MapInfo
p-value
ASPA_1* ITGA2B_1* ITGA2B_2* NPTX2_1* NPTX2_2* NPTX2_3* NPTX2_4* TOM1L1_1 ZDHHC22_1 ZDHHC22_2 ZDHHC22_3 ZDHHC22_4 ZDHHC22_5 ZDHHC22_6 ZDHHC22_7 ZDHHC22_8 ZDHHC22_9 ZDHHC22_10 ZDHHC22_11
3E+06 4E+07 4E+07 1E+08 1E+08 1E+08 1E+08 5E+07 8E+07 8E+07 8E+07 8E+07 8E+07 8E+07 8E+07 8E+07 8E+07 8E+07 8E+07
0.000 0.019 0.007 0.033 0.003 0.001 0.001 0.703 0.620 0.134 0.939 0.732 0.075 0.095 0.184
ZDHHC22_12 ZDHHC22_13 ZDHHC22_14 ZDHHC22_15 ZDHHC22_16 ZDHHC22_17 ZDHHC22_18 ZDHHC22_19 ZDHHC22_20 ZIC4_1 ZIC4_2 ZIC4_3 ZIC4_4 ZIC4_5 ZIC4_6 ZIC4_7 ZIC4_8 ZIC4_9 ZIC4_10
8E+07 8E+07 8E+07 8E+07 8E+07 8E+07 8E+07 8E+07 8E+07 1E+08 1E+08 1E+08 1E+08 1E+08 1E+08 1E+08 1E+08 1E+08 1E+08
0.181 0.908 0.758 0.878 0.674 0.536 0.297 0.466 0.425 0.784 0.686 0.147 0.676 0.305 0.733 0.288 0.197 0.617 0.471
*
p < 0.05 considered statistically significant.
Followed by 45 cycles, comprising: 94 C denaturation for 30 s; 30 s annealing at 61.5 C (ASPA), 60.5 C (ITGA2B), 61.5 C (NPTX2), 59.0 C (Tom1L1), 64.8 C (ZDHHC22_1), 58.8 C (ZDHHC22_2), 57.9 C (ZDHHC22_3), 58.0 C (ZDHHC22_4), 57.5 C (ZIC4_1) or 63.5 C (ZIC4_1); and 30 s extension at 72 C. Then a final extension of 72 C for 10 min. Pyrosequencing was performed using a PyroMark1 Q96 Pyrosequencer (Qiagen). 20 mL of biotinylated PCR products was immobilized to 3 mL streptavidin-coated Sepharose high-performance beads (GE Healthcare) followed by annealing to 1.6 mL sequencing primer (10 mM) for 2 min at 80 C. The generated pyrograms were automatically analyzed using PyroMark analysis software. The Mann–Whitney test was applied to analysis the remarkable difference in methylation values between the two age groups (p < 0.05 is considered statistically significant).
Subsequently, based on the PyroMark 96 pyrosequencing platform, with at least one “inbuilt bisulfite control”, we could evaluate the portion of bisulfite conversion, only with the internal control indicated that the conversion reached 93%, the results were admitted. Therefore, there was a reliable quality control system of bisulfite conversion in our DNA methylation quantitative analysis. Seven CpG sites resided on three gene fragments were identified as age-related markers. Among them, ASPA_1 and ITGA2B_2 were previously reported [4], however, it is worthy emphasizing that the CpG sites ITGA2B_1, NPTX2_1, NPTX2_2, NPTX2_3 and NPTX2_4 had not been reported yet. In conclusion, the data demonstrated that pyrosequencing was an effective and less costly method to screen AR-CpGs and quantify the methylation values of them. Further study is needed to validate these AR-CpGs in an independent sample set with larger sample size as well as full age distribution.
3. Results Conflict of interest During the screening experiment, we failed to interpret the methylation status of 4CpGs located in fragment ZDHHC22_3 due to the background’s influence in the pyrogram. The remaining 16CpGs in the three fragment ZDHHC22_1, ZDHHC22_2 and ZDHHC22_4 showed no significant difference between the adolescent group and the elderly group (p > 0.05, Table 2), The similar result also occurred in the 11CpGs of fragment Tom1L1, ZIC4_1 and ZIC4_2 (p > 0.05, Table 2). Finally, there were seven CpG sites: ASPA_1, ITGA2B_1, ITGA2B_2, NPTX2_1, NPTX2_2, NPTX2_3 and NPTX2_4 showed significant difference between the adolescent group and the elderly group (p < 0.05, Table 1). 4. Discussion and conclusion A reasonable analysis of methylation quantitative must limit the amount of DNA template in two important links. In our study, the starting amount of template DNA was 100 ng in bisulfite conversion stage, and 20 ng modified DNA template in PCR step. The same basis quantification ensured the comparability of the results. How to accomplish complete conversion was essential in our study. We strictly controlled the temperature and the salt concentration in conversion reaction to maintain the DNA in a single-stranded conformation in order to complete conversion [6].
None. Acknowledgement This work was supported by the grants of the National Natural Science Foundation of China (81273349 and 81330073). References [1] R.S. Alisch, B.G. Barwick, P. Chopra, L.K. Myrick, G.A. Satten, K.N. Conneely, S.T. Warren, Age-associated DNA methylation in pediatric populations, Genome Res. 22 (2012) 623–632. [2] C.M. Koch, W. Wagner, Epigenetic-aging-signature to determine age in different tissues, Aging 3 (2011) 1018–1027. [3] S. Bocklandt, W. Lin, M.E. Sehl, F.J. Sanchez, J.S. Sinsheimer, S. Horvath, E. Vilain, Epigenetic predictor of age, PLoS One 6 (2011) e14821. [4] C.I. Weidner, Q. Lin, C.M. Koch, L. Eisele, F. Beier, P. Ziegler, D.O. Bauerschlag, K.H. Jöckel, R. Erbel, T.W. Mühleisen, M. Zenke, T.H. Brümmendorf, W. Wagner, Aging of blood can be tracked by DNA methylation changes at just three CpG sites, Genome Biol. 2 (2014) R24. _ Makowska, A. Spas, A.P. Proszek, K. [5] R.Z. Piekarska, M. Spólnicka, T. Kupiec, Z. Kucharczyk, R. Płoski, W. Branicki, Examination of DNA methylation status of the ELOVL2 marker may be useful for human age prediction in forensic science, Forensic Sci. Int. Genet. 14 (2015) 161–167. [6] M.F. Fraga, M. Esteller, DNA methylation: a profile of methods and applications, BioTechniques 33 (2002) 636–649.
Contents lists available at ScienceDirect
Forensic Science International: Genetics Supplement Series journal homepage: www.elsevier.com/locate/FSIGSS
Analysis of age-related CpGs for forensic purpose in Chinese Han population Y. Huang1, J. Yan1, H. Zhuk, X. Fu, Y. Hou* Department of Forensic Genetics, West China School of Basic Science and Forensic Medicine, Sichuan University (West China University of Medical Sciences), Chengdu 610041, Sichuan, China
A R T I C L E I N F O
A B S T R A C T
Article history: Received 19 August 2015 Accepted 14 September 2015 Available online 16 September 2015
Age-related CpGs (AR-CpGs) have been proved to be potential markers for forensic age prediction. However, DNA methylation (DNAm) patterns in particular AR-CpGs may be tissue specific. Meanwhile, variant methylation quantitative platforms might result in discrepant candidate markers. Recent researches carried out either by pyrosequencing or by microarray platforms were based on Caucasian samples. In this study, we aimed to screen out the AR-CpGs as potential forensic age prediction biomarkers in Chinese Han population by pyrosequencing approach. We referred the previous agerelated DNAm studies with different methods or tissue specimens, candidate markers located on 6 gene fragments were selected for DNA methylation analysis. The blood samples both from younger donors aged from 10 to 25 years and from senior donors aged from 55 to 65 years were employed to screen the candidate markers with remarkable difference in methylation values between the two age groups. Our results revealed that there were 7CpG sites resided on 3 gene fragments showed significant difference between the adolescent group and the elderly group. It implied that some of them may be potential markers for forensic age prediction in Chinese Han population and that pyrosequencing was an effective method to screen AR-CpGs and quantify the methylation values of them. ã 2015 Elsevier Ireland Ltd. All rights reserved.
Keywords: Forensic science Age prediction Methylation Pyrosequencing Human blood Chinese Han population
1. Introduction Age-related CpGs (AR-CpGs) have been proved to be effective biomarker for forensic age prediction [1]. It was well known that methylation patterns in particular AR-CpGs may be tissue specific [2]. Blood is commonly found in violent crimes. It, therefore, would be very meaningful to screen out AR-CpG which is applicable for blood. Meanwhile, recent studies have indicated that variant methylation quantitative platforms might result in discrepant candidate markers. Koch described a number of tissues-specific AR-CpGs through DNA methylation (DNAm) profiles of various cell types from public data depositories [2]. Bocklandt and Weidner optimized the pyrosequencing approach to validate AR-CpGs with linear DNAm changes during aging from saliva samples and blood samples, respectively [3,4]. They selected five fragments—ASPA, ITGA2B, PDE4C, NPTX2, and Tom1L1, where NPTX2 was also referred in Koch’s study. Most recently, in Piekarska’s study, the bisulfate pyrosequencing approach was applied to evaluate the methylation of two CpG sites in ELOVL2 [5]. These studies carried
* Corresponding author. Fax: +86 28 85501550. E-mail addresses: [email protected], [email protected] (Y. Hou). Both authors contributed equally to this work.
1
http://dx.doi.org/10.1016/j.fsigss.2015.09.060 1875-1768/ ã 2015 Elsevier Ireland Ltd. All rights reserved.
out by pyrosequencing mentioned above were all based on Caucasian race samples. The aim of this study was to screen out the AR-CpGs as potential forensic age prediction biomarkers in Chinese Han population by pyrosequencing approach in blood specimens. 2. Materials and methods 10 blood samples from younger donors (aged from 10 to 25 years) and 10 blood samples from senior donors (aged from 55 to 65 years) were employed to screen the candidate markers. DNA was extracted from the peripheral venous blood using a DNeasy Blood & Tissue Kit (QIAGEN) following the manufacturer’s instructions. Based on the previous studies of age-related DNAm using different methods or tissue specimens [3–5], thirty-eight candidate markers located on six gene fragments were chosen for DNA methylation analysis by pyrosequencing. 100 ng extracted DNA was bisulfite-converted using the EpiTect Bisulfite Kit (QIAGEN). PCR reactions were carried out by the PyroMark1 PCR Kit (Qiagen). 20 ng of modified DNA template was added to the mixture for a total reaction volume of 25 mL. The amplification program consisted of an initial denaturation step at 95 C for 10 min.
e150
Y. Huang et al. / Forensic Science International: Genetics Supplement Series 5 (2015) e149–e150
Table 1 Mann–Whitney test of the methylation values of candidate markers between younger donors and senior donors. Candidate markers
MapInfo
p-value
Candidate markers
MapInfo
p-value
ASPA_1* ITGA2B_1* ITGA2B_2* NPTX2_1* NPTX2_2* NPTX2_3* NPTX2_4* TOM1L1_1 ZDHHC22_1 ZDHHC22_2 ZDHHC22_3 ZDHHC22_4 ZDHHC22_5 ZDHHC22_6 ZDHHC22_7 ZDHHC22_8 ZDHHC22_9 ZDHHC22_10 ZDHHC22_11
3E+06 4E+07 4E+07 1E+08 1E+08 1E+08 1E+08 5E+07 8E+07 8E+07 8E+07 8E+07 8E+07 8E+07 8E+07 8E+07 8E+07 8E+07 8E+07
0.000 0.019 0.007 0.033 0.003 0.001 0.001 0.703 0.620 0.134 0.939 0.732 0.075 0.095 0.184
ZDHHC22_12 ZDHHC22_13 ZDHHC22_14 ZDHHC22_15 ZDHHC22_16 ZDHHC22_17 ZDHHC22_18 ZDHHC22_19 ZDHHC22_20 ZIC4_1 ZIC4_2 ZIC4_3 ZIC4_4 ZIC4_5 ZIC4_6 ZIC4_7 ZIC4_8 ZIC4_9 ZIC4_10
8E+07 8E+07 8E+07 8E+07 8E+07 8E+07 8E+07 8E+07 8E+07 1E+08 1E+08 1E+08 1E+08 1E+08 1E+08 1E+08 1E+08 1E+08 1E+08
0.181 0.908 0.758 0.878 0.674 0.536 0.297 0.466 0.425 0.784 0.686 0.147 0.676 0.305 0.733 0.288 0.197 0.617 0.471
*
p < 0.05 considered statistically significant.
Followed by 45 cycles, comprising: 94 C denaturation for 30 s; 30 s annealing at 61.5 C (ASPA), 60.5 C (ITGA2B), 61.5 C (NPTX2), 59.0 C (Tom1L1), 64.8 C (ZDHHC22_1), 58.8 C (ZDHHC22_2), 57.9 C (ZDHHC22_3), 58.0 C (ZDHHC22_4), 57.5 C (ZIC4_1) or 63.5 C (ZIC4_1); and 30 s extension at 72 C. Then a final extension of 72 C for 10 min. Pyrosequencing was performed using a PyroMark1 Q96 Pyrosequencer (Qiagen). 20 mL of biotinylated PCR products was immobilized to 3 mL streptavidin-coated Sepharose high-performance beads (GE Healthcare) followed by annealing to 1.6 mL sequencing primer (10 mM) for 2 min at 80 C. The generated pyrograms were automatically analyzed using PyroMark analysis software. The Mann–Whitney test was applied to analysis the remarkable difference in methylation values between the two age groups (p < 0.05 is considered statistically significant).
Subsequently, based on the PyroMark 96 pyrosequencing platform, with at least one “inbuilt bisulfite control”, we could evaluate the portion of bisulfite conversion, only with the internal control indicated that the conversion reached 93%, the results were admitted. Therefore, there was a reliable quality control system of bisulfite conversion in our DNA methylation quantitative analysis. Seven CpG sites resided on three gene fragments were identified as age-related markers. Among them, ASPA_1 and ITGA2B_2 were previously reported [4], however, it is worthy emphasizing that the CpG sites ITGA2B_1, NPTX2_1, NPTX2_2, NPTX2_3 and NPTX2_4 had not been reported yet. In conclusion, the data demonstrated that pyrosequencing was an effective and less costly method to screen AR-CpGs and quantify the methylation values of them. Further study is needed to validate these AR-CpGs in an independent sample set with larger sample size as well as full age distribution.
3. Results Conflict of interest During the screening experiment, we failed to interpret the methylation status of 4CpGs located in fragment ZDHHC22_3 due to the background’s influence in the pyrogram. The remaining 16CpGs in the three fragment ZDHHC22_1, ZDHHC22_2 and ZDHHC22_4 showed no significant difference between the adolescent group and the elderly group (p > 0.05, Table 2), The similar result also occurred in the 11CpGs of fragment Tom1L1, ZIC4_1 and ZIC4_2 (p > 0.05, Table 2). Finally, there were seven CpG sites: ASPA_1, ITGA2B_1, ITGA2B_2, NPTX2_1, NPTX2_2, NPTX2_3 and NPTX2_4 showed significant difference between the adolescent group and the elderly group (p < 0.05, Table 1). 4. Discussion and conclusion A reasonable analysis of methylation quantitative must limit the amount of DNA template in two important links. In our study, the starting amount of template DNA was 100 ng in bisulfite conversion stage, and 20 ng modified DNA template in PCR step. The same basis quantification ensured the comparability of the results. How to accomplish complete conversion was essential in our study. We strictly controlled the temperature and the salt concentration in conversion reaction to maintain the DNA in a single-stranded conformation in order to complete conversion [6].
None. Acknowledgement This work was supported by the grants of the National Natural Science Foundation of China (81273349 and 81330073). References [1] R.S. Alisch, B.G. Barwick, P. Chopra, L.K. Myrick, G.A. Satten, K.N. Conneely, S.T. Warren, Age-associated DNA methylation in pediatric populations, Genome Res. 22 (2012) 623–632. [2] C.M. Koch, W. Wagner, Epigenetic-aging-signature to determine age in different tissues, Aging 3 (2011) 1018–1027. [3] S. Bocklandt, W. Lin, M.E. Sehl, F.J. Sanchez, J.S. Sinsheimer, S. Horvath, E. Vilain, Epigenetic predictor of age, PLoS One 6 (2011) e14821. [4] C.I. Weidner, Q. Lin, C.M. Koch, L. Eisele, F. Beier, P. Ziegler, D.O. Bauerschlag, K.H. Jöckel, R. Erbel, T.W. Mühleisen, M. Zenke, T.H. Brümmendorf, W. Wagner, Aging of blood can be tracked by DNA methylation changes at just three CpG sites, Genome Biol. 2 (2014) R24. _ Makowska, A. Spas, A.P. Proszek, K. [5] R.Z. Piekarska, M. Spólnicka, T. Kupiec, Z. Kucharczyk, R. Płoski, W. Branicki, Examination of DNA methylation status of the ELOVL2 marker may be useful for human age prediction in forensic science, Forensic Sci. Int. Genet. 14 (2015) 161–167. [6] M.F. Fraga, M. Esteller, DNA methylation: a profile of methods and applications, BioTechniques 33 (2002) 636–649.