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| Status |
Public on May 23, 2021 |
| Title |
A KMT2A-AFF1 gene regulatory network highlights the role of core transcription factors and reveals the regulatory logic of key downstream target genes [ChIP-seq] |
| Organism |
Homo sapiens |
| Experiment type |
Genome binding/occupancy profiling by high throughput sequencing
|
| Summary |
Regulatory interactions mediated by transcription factors (TFs) make up complex networks that control cellular behavior. Fully understanding these gene regulatory networks (GRNs) offers greater insight into the consequences of disease-causing perturbations than can be achieved by studying single TF binding events in isolation. Chromosomal translocations of the lysine methyltransferase 2A (KMT2A) produce KMT2A fusion proteins such as KMT2A-AFF1 (also known as MLL-AF4), causing poor prognosis acute lymphoblastic leukemias (ALLs) that sometimes relapse as acute myeloid leukemias (AMLs). KMT2A-AFF1 is thought to drive leukemogenesis through direct binding and inducing aberrant overexpression of key gene targets, such as the anti-apoptotic factor BCL2 and the proto-oncogene MYC. However, studying direct binding alone doesn’t allow for network generated regulatory outputs, including the indirect induction of gene repression. To better understand the KMT2A-AFF1 driven regulatory landscape, we integrated ChIP-seq, patient RNA-seq and CRISPR essentiality screens to generate a model GRN. This GRN identified several key transcription factors, including RUNX1, that regulate target genes downstream of KMT2A-AFF1 using feed-forward loop (FFL) and cascade motifs. A core set of nodes are present in both ALL and AML, and CRISPR screening revealed several factors that help mediate response to the drug venetoclax. Using our GRN, we then identified an KMT2A-AFF1:RUNX1 cascade that represses CASP9, as well as KMT2A-AFF1 driven FFLs that regulate BCL2 and MYC through combinatorial TF activity. This illustrates how our GRN can be used to better connect KMT2A-AFF1 behavior to downstream pathways that contribute to leukemogenesis, and potentially predict shifts in gene expression that mediate drug response.
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| Overall design |
ChIP-seq profiling of SEM, RS4;11 and THP1 cell lines, and patient ALL blasts. Antibodies used against MAZ, RUNX1, MLL-N and AF4-C. Reference normalised ChIP-seq performed with SEM cells following RUNX1/non-targeting siRNA treatment.
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| Contributor(s) |
Harman JR, Thorne R, Jamilly M, Crump NT, Milne TA |
| Citation(s) |
34088716 |
| |
| Submission date |
May 28, 2020 |
| Last update date |
Aug 22, 2021 |
| Contact name |
Thomas Milne |
| E-mail(s) |
[email protected]
|
| Organization name |
University of Oxford
|
| Department |
Radcliffe Department of Medicine
|
| Lab |
Milne Lab
|
| Street address |
MRC MHU, WIMM, John Radcliffe Hospital
|
| City |
Oxford |
| ZIP/Postal code |
OX3 9DS |
| Country |
United Kingdom |
| |
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| Platforms (1) |
| GPL16791 |
Illumina HiSeq 2500 (Homo sapiens) |
|
| Samples (15)
|
| GSM4577112 |
ChIP-seq input for MLL-N and AF4-C in MLL-AF4 ALL patient blasts |
| GSM5220549 |
RUNX1 ChIP-seq in THP1 cells |
| GSM5220550 |
ChIP-seq input for RUNX1 in THP1 cell line |
| GSM5220551 |
Reference normalised RUNX1 ChIP-seq in SEM cells following NT siRNA treatment |
| GSM5220552 |
Reference normalised MLL-N ChIP-seq in SEM cells following NT siRNA treatment |
| GSM5220553 |
Reference normalised ChIP-seq input for RUNX1 and MLL-N in SEM cells following NT siRNA treatment |
| GSM5220554 |
Reference normalised RUNX1 ChIP-seq in SEM cells following KD siRNA treatment |
| GSM5220555 |
Reference normalised MLL-N ChIP-seq in SEM cells following KD siRNA treatment |
| GSM5220556 |
Reference normalised ChIP-seq input for RUNX1 and MLL-N in SEM cells following KD siRNA treatment |
| GSM5220557 |
MLL-N ChIP-seq in RS4;11 cells |
| GSM5220558 |
AF4-C ChIP-seq in RS4;11 cells |
| GSM5220559 |
ChIP-seq input for MLL-N and AF4-C in RS4;11 cells |
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| This SubSeries is part of SuperSeries: |
| GSE151390 |
A KMT2A-AFF1 gene regulatory network highlights the role of core transcription factors and reveals the regulatory logic of key downstream target genes. |
|
| Relations |
| BioProject |
PRJNA635662 |
| SRA |
SRP265129 |
| Supplementary file |
Size |
Download |
File type/resource |
| GSE151386_ALL_blast_AF4_peaks.txt.gz |
77.1 Kb |
(ftp)(http) |
TXT |
| GSE151386_ALL_blast_MLL_peaks.txt.gz |
560.0 Kb |
(ftp)(http) |
TXT |
| GSE151386_RS411_AF4-C_peaks.txt.gz |
253.3 Kb |
(ftp)(http) |
TXT |
| GSE151386_RS411_MLL-N_peaks.txt.gz |
575.6 Kb |
(ftp)(http) |
TXT |
| GSE151386_SEM_MAZ_peaks.txt.gz |
576.8 Kb |
(ftp)(http) |
TXT |
| GSE151386_SEM_RUNX1-KD_MLL-N_peaks.txt.gz |
587.7 Kb |
(ftp)(http) |
TXT |
| GSE151386_SEM_RUNX1-KD_RUNX1_peaks.txt.gz |
279.2 Kb |
(ftp)(http) |
TXT |
| GSE151386_SEM_RUNX1-NT_MLL-N_peaks.txt.gz |
549.5 Kb |
(ftp)(http) |
TXT |
| GSE151386_SEM_RUNX1-NT_RUNX1_peaks.txt.gz |
310.7 Kb |
(ftp)(http) |
TXT |
| GSE151386_THP1_RUNX1_peaks.txt.gz |
629.5 Kb |
(ftp)(http) |
TXT |
SRA Run Selector |
| Raw data are available in SRA |
| Processed data are available on Series record |
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