Biology subjects

Anyoha, R.

Publications and source records attributed to Anyoha, R..

3 recordsLinked to original sources

bioRxiv2023

Selective Enhancer Dependencies in MYC-Intact and MYC-Rearranged Germinal Center B-cell Diffuse Large B-cell Lymphoma

High expression of MYC and its target genes define a subset of germinal center B-cell diffuse large B-cell lymphoma (GCB-DLBCL) associated with poor outcomes. Half of these high-grade cases show chromosomal rearrangements between the MYC locus and heterologous enhancer-bearing loci, while focal deletions of the adjacent non-coding gene PVT1 are enriched in MYC-intact cases. To identify genomic drivers of MYC activation, we used high-throughput CRISPR-interference (CRISPRi) profiling of candidate enhancers in the MYC locus and rearrangement partner loci in GCB-DLBCL cell lines and mantle cell lymphoma (MCL) comparators that lacked common rearrangements between MYC and immunoglobulin (Ig) loci. Rearrangements between MYC and non-Ig loci were associated with unique dependencies on specific enhancer subunits within those partner loci. Notably, fitness dependency on enhancer modules within the BCL6 super-enhancer (BCL6-SE) cluster regulated by a transcription factor complex of MEF2B, POU2F2, and POU2AF1 was higher in cell lines bearing a recurrent MYC::BCL6-SE rearrangement. In contrast, GCB-DLBCL cell lines without MYC rearrangement were highly dependent on a previously uncharacterized 3 enhancer within the MYC locus itself (GCBME-1), that is regulated in part by the same triad of factors. GCBME-1 is evolutionarily conserved and active in normal germinal center B cells in humans and mice, suggesting a key role in normal germinal center B cell biology. Finally, we show that the PVT1 promoter limits MYC activation by either native or heterologous enhancers and demonstrate that this limitation is bypassed by 3 rearrangements that remove PVT1 from its position in cis with the rearranged MYC gene. Key pointsO_LICRISPR-interference screens identify a conserved germinal center B cell MYC enhancer that is essential for GCB-DLBCL lacking MYC rearrangements. C_LIO_LIFunctional profiling of MYC partner loci reveals principles of MYC enhancer-hijacking activation by non-immunoglobulin rearrangements. C_LI

cancer biology↗

bioRxiv2021

Striatal dopamine explains novelty-induced behavioral dynamics and individual variability in threat prediction

Animals exhibit diverse behavioral responses, such as exploration and avoidance, to novel cues in the environment. However, it remains unclear how dopamine neuron-related novelty responses influence behavior. Here, we characterized dynamics of novelty exploration using multi-point tracking (DeepLabCut) and behavioral segmentation (MoSeq). Novelty elicits a characteristic sequence of behavior, starting with investigatory approach and culminating in object engagement or avoidance. Dopamine in the tail of striatum (TS) suppresses engagement, and dopamine responses were predictive of individual variability in behavior. Behavioral dynamics and individual variability were explained by a novel reinforcement learning (RL) model of threat prediction, in which behavior arises from a novelty-induced initial threat prediction (akin to "shaping bonus"), and a threat prediction that is learned through dopamine-mediated threat prediction errors. These results uncover an algorithmic similarity between reward- and threat-related dopamine sub-systems. HighlightsO_LINovelty-induced behaviors are analyzed using modern machine-learning methods C_LIO_LINovelty induces risk assessment which develops into engagement or avoidance C_LIO_LIDopamine in the tail of striatum correlates with individual behavioral variability C_LIO_LIReinforcement learning with shaping bonus and uncertainty explains the data C_LI

neuroscience↗

bioRxiv2019

Activity-by-Contact model of enhancer specificity from thousands of CRISPR perturbations

Mammalian genomes harbor millions of noncoding elements called enhancers that quantitatively regulate gene expression, but it remains unclear which enhancers regulate which genes. Here we describe an experimental approach, based on CRISPR interference, RNA FISH, and flow cytometry (CRISPRi-FlowFISH), to perturb enhancers in the genome, and apply it to test >3,000 potential regulatory enhancer-gene connections across multiple genomic loci. A simple equation based on a mechanistic model for enhancer function performed remarkably well at predicting the complex patterns of regulatory connections we observe in our CRISPR dataset. This Activity-by-Contact (ABC) model involves multiplying measures of enhancer activity and enhancer-promoter 3D contacts, and can predict enhancer-gene connections in a given cell type based on chromatin state maps. Together, CRISPRi-FlowFISH and the ABC model provide a systematic approach to map and predict which enhancers regulate which genes, and will help to interpret the functions of the thousands of disease risk variants in the noncoding genome.

genetics↗