Nucleated red blood cells impact DNA methylation and expression analyses of cord blood hematopoietic cells

Abstract

BackgroundGenome-wide DNA methylation (DNAm) studies have proven extremely useful to understand human hematopoiesis. Due to their active DNA content, nucleated red blood cells (nRBCs) contribute to epigenetic and transcriptomic studies derived from whole cord blood. Genomic studies of cord blood hematopoietic cells isolated by fluorescence-activated cell sorting (FACS) may be significantly altered by heterotopic interactions with nRBCs during conventional cell sorting.ResultsWe report that cord blood T cells, and to a lesser extent monocytes and B cells, physically engage with nRBCs during FACS. These heterotopic interactions resulted in significant cross-contamination of genome-wide epigenetic and transcriptomic data. Formal exclusion of erythroid lineage-specific markers yielded DNAm profiles (measured by the Illumina 450K array) of cord blood CD4 and CD8 T lymphocytes, B lymphocytes, natural killer (NK) cells, granulocytes, monocytes, and nRBCs that were more consistent with expected hematopoietic lineage relationships. Additionally, we identified eight highly differentially methylated CpG sites in nRBCs (false detection rate <5 %, |Δβ| >0.50) that can be used to detect nRBC contamination of purified hematopoietic cells or to assess the impact of nRBCs on whole cord blood DNAm profiles. Several of these erythroid markers are located in or near genes involved in erythropoiesis (ZFPM1, HDAC4) or immune function (MAP3K14, IFIT1B), reinforcing a possible immune regulatory role for nRBCs in early life.ConclusionsHeterotopic interactions between erythroid cells and white blood cells can result in contaminated cell populations if not properly excluded during cell sorting. Cord blood nRBCs have a distinct DNAm profile that can significantly skew epigenetic studies. Our findings have major implications for the design and interpretation of genome-wide epigenetic and transcriptomic studies using human cord blood.Electronic supplementary materialThe online version of this article (doi:10.1186/s13148-015-0129-6) contains supplementary material, which is available to authorized users.

An Immunological Perspective on Neonatal Sepsis

“…Of note, significant cross-contamination can occur between nRBCs and other white blood cells types during cell purification for ex vivo immune studies [74]. This type of technical problem therefore raises concern that previous conclusions from functional and genomic analyses of cord blood immune cells may have been biased because of the heterotopic cellular interactions with DNA/high rRNAcontaining an potentially suppressing nRBCs that go undetected unless formally excluded by FACS [74].…”

Maternal BMI at the start of pregnancy and offspring epigenome-wide DNA methylation: Findings from the Pregnancy and Childhood Epigenetics (PACE) consortium

“…NHBCS, RICHS and Project Viva included five estimated cell types (omitting granulocytes) and all other cohorts included six. When cord blood references became available (28)(29)(30), a sensitivity analysis was run in ALSPAC adjusting for cell proportions estimated using these reference sets. One of these reference sets includes nucleated red blood cells, which can contribute greatly to cord blood DNA methylation profiles (28).…”

Cell type-specific DNA methylation in neonatal cord tissue and cord blood: a 850K-reference panel and comparison of cell types

“…To achieve this, we compared the different cell types isolated from CB with those identified in 3 previously reported studies (Figure 3(a)). These reported CB datasets/reference panels by de Goede et al (2015), Bakulski et al (2016), and Gervin et al (2016) were processed similar to the CB reference panel in the current study [12–14], except that they were generated on lower coverage DNA methylation arrays. We compared the 6 CB cell types that were common to all 4 datasets and performed a PCA on each dataset separately.…”

“…To benchmark the reference panel for CB, we compared cell type proportions measured from unsorted leukocytes by flow cytometry with cellular proportions estimated using our and 3 previously published reference panels [12–14], 2 of which were previously benchmarked [14,32]. As described before, cellular proportions were estimated following the method described by Houseman et al (2012) [5], where pairwise t-tests were used to identify 1000 cell type specific CpGs that best distinguished each cell type from the remainder cell populations.…”

“…First, while infant CB reference panels are available [12–14], an adequate reference panel for infant CT has not yet been developed. We anticipate that the use of CT for DNA methylation profiling is complementary to that of CB, since these originate from a similar developmental timepoint, but are yet representative of different germinal origins and cell fates.…”