Hoxa9 and Meis1 Bind Highly Conserved Elements Near Targets Regulated in Leukemia Cells.
Bibliographic record
Abstract
Abstract The homeobox transcription factors Hoxa9 and Meis1 are critical mediators of transformation by MLL fusion proteins and have also been associated with poor prognosis in other AML subtypes. Despite their pivotal role in leukemia, their mechanism of cooperation and their direct target genes are largely unknown. We have established an experimental model to address these questions by transforming murine hematopoietic progenitors with epitope-tagged forms of Hoxa9 and Meis1. Chromatin immunoprecipitation and massively parallel Illumina sequencing (ChIP-seq) was used to identify binding sites for Hoxa9 and Meis1 across the genome in leukemic cells. We generated 1.7 Gb of sequence data for immunoprecipitated DNA and an untagged control, using two biological replicates, and filtered out (1) regions with nonspecific binding, (2) enriched regions that overlapped certain types of repetitive elements, and (3) nonreproducible enriched regions. We validated a subset of enriched regions by ChIP-chip and ChIP-PCR. De novo motif discovery verified that the resulting set of regions contained a motif that corresponded (E value = 6E-16) to a published Hoxa9 binding motif (Shen et al.; Mol. Cell. Biol. 1999, 19:3051–61). Overlapping or immediately adjacent binding of Hoxa9 and Meis1 was seen for 52% of Hoxa9 and 33% of Meis1 enriched regions, suggesting that these two transcription factors cooperate directly in oncogenesis rather than acting through parallel pathways. Only 7% of enriched regions fell within 2 Kb of known transcriptional start sites, while 46% of regions were within gene boundaries; the remaining peaks were intergenic. Remarkably, given the low overall level of intergenic sequence conservation, over 95% of enriched regions overlapped evolutionarily highly conserved regions (Phastcons for 17 mammalian species >50%; P value<0.0001 [compared to untagged control peaks]). Our experiments suggest that targets of Hoxa9 and Meis1 in both hematopoiesis and leukemic transformation are regulated in part by highly conserved non-coding elements (HCNE), which are recently recognized genomic elements whose functions remain elusive and which are typically absent from widely used promoter microarrays. RNA expression analysis by our group and others confirms that Hoxa9 and Meis1 influence a large number of downstream targets. We used an inducible Hoxa9 expression system to identify genes that were differentially expressed at 72, 96, and 120 h after Hoxa9 withdrawal; 753, 1116, and 2975 transcripts showed >2-fold change, respectively. Phenotypic changes are evident by 96 h; therefore, the 72 h timepoint is most informative of direct Hoxa9 targets. We compared these data to genes containing ChIP-seq peaks and genes with transcription start sites closest to intergenic peaks. ~10% of genes altered at 72 h were associated with a ChIP-seq peak. Another group of investigators identified targets of Meis1 through comparison of Hoxa9- and Hoxa9+Meis1-immortalized cells (Wang et al.; Blood 2005, 106:254–63); ~14% of reported Meis1 targets were associated with a ChIP-seq peak. Hoxa9 and Meis1 binding sites in selected target genes, such the tyrosine kinase Flt3 and the surface marker Cd34, have been confirmed by ChIP-PCR/ChIP-chip. Our current data support a model in which Hoxa9 and Meis1 directly modulate a substantial number of downstream effectors through co-occupancy of regulatory motifs within proximal promoters, intragenic elements, and distally located regions. Studies are underway to determine whether Hoxa9/Meis1 binding influences gene expression and epigenetic modification at promoters and particularly at HCNEs.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".