(T1130-03-16) Integration of RNA-Seq and ATAC-Seq Unveils Chromatin Accessibility and Gene Expression Changes in Acute Myeloid Leukemia Cells

Purpose: Chromatin accessibility and gene expression changes contribute to the initiation and progression of acute myeloid leukemia (AML).  In this study we are comparing the chromatin configuration and gene expression in normal cord blood cells and bone marrow mononuclear AML cells.

Methods: De-identified human mononuclear AML samples obtained from the bone marrow aspirates of 8 AML patients and 4 de-identified mononuclear cord blood cells were used to compare their chromatin configuration and gene expression using ATAC-Seq and RNA-Seq, respectively. RNA-Seq was performed by isolating total RNA from the cells using the Qiagen RNeasy Mini Kit. For each sample, 2 ug of total RNA was then used in Illumina’s TruSeq Stranded mRNA Library kit. Libraries were sequenced on Illumina NovaSeq 6000 as paired-end 150-nt reads. Sequence reads were analyzed with the STAR alignment – DESeq2 software.  ATAC-Seq was performed after thawing cryopreserved cells in a 37^oC water bath, pelleted, washed with cold PBS, and tagmented. Briefly, cell pellets were resuspended in lysis buffer, pelleted, and tagmented using the enzyme and buffer provided in the Nextera Library Prep Kit (Illumina). Tagmented DNA was then purified using the MinElute PCR purification kit (Qiagen), amplified with 10 cycles of PCR, and purified using Agencourt AMPure SPRI beads (Beckman Coulter).  Resulting material was quantified using the KAPA Library Quantification Kit for Illumina platforms (KAPA Biosystems) and sequenced with PE42 sequencing on the NovaSeq 6000 sequencer (Illumina). Analysis of ATAC-seq data was performed using a group of software. Reads were aligned using the BWA algorithm. Peaks were identified using the MACS 2.1.0 algorithm. Signal maps and peak locations were used as input data to an analysis program, which creates Excel tables containing detailed information on sample comparison, peak metrics, peak locations and gene annotations.

Results: RNA-Seq data showed both induction of 180 genes and repression of 329 genes for a total of 509 differentially expressed genes (DEG).  When compared to normal samples, multiple AML samples showed repression of DKK3, an inhibitor of the Wnt signaling pathway.  Additionally, multiple AML sample demonstrated induced expression of the immunoglobulin heavy constant chain genes IGHG1, IGHG2, and IGHA1, as well as the colony stimulating factor CSF3.  ATAC-Seq analysis demonstrated a significant decrease in chromatin accessibility in the promoter regions of the AML samples compared to the normal samples.  In contrast, the data displayed a significant increase in chromatin accessibility in the introns and distal intergenic regions of the AML cells compared to normal cells. Specific motif ATAC-Seq data evidenced increased accessibility of several transcription factors related to AML including MAFF, NF1, PU.1, and MYB.  The data additionally displayed decreased accessibility to the transcription factor CEBP in AML samples.

Conclusion: According to the ATAC-Seq and RNA-Seq data, chromatin accessibility and gene expression appear altered in ways that promote unregulated cell cycle progression and abnormal protein production.  Repression of DKK3 in AML samples is consistent with increased Wnt signaling in the leukemia cells contributing to proliferation.  Overexpression of immunoglobulin heavy constant chains (IGHG and IGHA) has been correlated with shorter periods of disease-free survival time for AML patients.  Furthermore, AML patients with CSF3 mutations have been shown to have greater relapse rates and lower 5-year survival rates than AML patients without CSF3 mutations.  The decreased accessibility to CEBP transcription factor is consistent with previous studies identifying CEBP to be mutated in 20% of all AML cases. Integrating the data from ATAC-Seq and RNA-Seq showed a concordant decrease in the accessibility to promoter regions in AML samples and a higher number of repressed genes compared to induced genes in AML cells. Further analysis of the differentially expressed genes in the AML samples is currently undergoing to identify connections between gene expression and chromatin accessibility contributing to the molecular pathogenesis of AML.

Acknowledgements: Research reported in this publication (or presentation) was supported by the National Institute Of General Medical Sciences of the National Institutes of Health under Award Number P20GM103434 to the West Virginia IDeA Network of Biomedical Research Excellence (WV-INBRE). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. We are grateful to the patients (and healthy volunteers) who provided tissue samples for these studies to the OSU Comprehensive Cancer Center Leukemia Tissue Bank Shared Resource (supported by NIH NCI P30 CA016058)