Noncoding translation mitigation

In eukaryotes, sequences that code for the amino acid structure of proteins represent a small fraction of the total sequence space in the genome. These are referred to as coding sequences, whereas the remaining majority of the genome is designated as noncoding. Studies of translation, the process in which a ribosome decodes a coding sequence to synthesize proteins, have primarily focused on coding sequences, mainly due to the belief that translation outside of canonical coding sequences occurs rarely and with little impact on a cell. However, recently developed techniques such as ribosome profiling have revealed pervasive translation in a diverse set of noncoding sequences, including long noncoding RNAs (lncRNAs), introns, and both the 5’ and 3’ UTRs of mRNAs. Although proteins with amino acid sequences derived partially or entirely from noncoding regions may be functional, they will often be nonfunctional or toxic to the cell and therefore need to be removed. Translation outside of canonical coding regions may further expose the noncoding genome to selective pressure at the protein level, leading to the generation of novel functional proteins over evolutionary timescales. Despite the potentially significant impact of these processes on the cell, the cellular mechanisms that function to detect and triage translation in diverse noncoding regions, as well as how peptides that escape triage may evolve into novel functional proteins, remain poorly understood.This thesis will describe novel findings that offer new insight into the process of noncoding translation mitigation revealed by a combination of high-throughput systems-based approaches and validated by biochemical and genetic approaches. Chapter 1 will discuss general concepts in the translation of noncoding sequences and the relevant cellular systems and impacts on human health. Chapter 2 will discuss the results of a high-throughput reporter assay investigating translation in thousands of noncoding sequences from diverse sources. The results discussed in this chapter revealed two factors involved in the mitigation of proteins derived from noncoding sequences: C-terminal hydrophobicity and proteasomal degradation. Chapter 3 will build on Chapter 2 and discuss the results of a genome-wide CRISPR/Cas9 knockout screen that identified the BAG6/TRC35/RNF126 membrane protein chaperone complex as a key cellular pathway in the detection and degradation of proteins with translated noncoding sequences. Having identified the BAG6 complex as targeting a specific reporter of translation of the 3’ UTR in the AMD1 gene, a series of knockout cell lines validated these results and demonstrated the participation of two additional genes, SGTA and UBL4A. Through coimmunoprecipitation western blots and rescue assays with flow cytometry as a readout, we confirmed physical interaction between BAG6 and the 3’ UTR of AMD1, and a similar experiment confirmed interaction between BAG6 and a readthrough mutant of the SMAD4 tumor suppressor gene. Finally, by combining our high-throughput reporter library with our BAG6 knockout cell line, we demonstrated that BAG6 targets hydrophobic C-terminal tails in many noncoding sequences of diverse origin. Finally, Chapter 4 will discuss the evolutionary perspective of noncoding translation through analyses of the sequence content of human and mouse genomes. The findings of this chapter demonstrate a significant trend for increased uracil content in noncoding regions of the genome, which frequently results in the translation of hydrophobic amino acids. We also find that many functional translated noncoding peptides localize to membranes, providing a theoretical link between the shuttling of translated noncoding sequences to a protein complex involved in membrane protein quality control and the emergence of newly evolving proteins from the noncoding genome

The Reading Palaeofire Database : an expanded global resource to document changes in fire regimes from sedimentary charcoal records

Sedimentary charcoal records are widely used to reconstruct regional changes in fire regimes through time in the geological past. Existing global compilations are not geographically comprehensive and do not provide consistent metadata for all sites. Furthermore, the age models provided for these records are not harmonised and many are based on older calibrations of the radiocarbon ages. These issues limit the use of existing compilations for research into past fire regimes. Here, we present an expanded database of charcoal records, accompanied by new age models based on recalibration of radiocarbon ages using IntCal20 and Bayesian age-modelling software. We document the structure and contents of the database, the construction of the age models, and the quality control measures applied. We also record the expansion of geographical coverage relative to previous charcoal compilations and the expansion of metadata that can be used to inform analyses. This first version of the Reading Palaeofire Database contains 1676 records (entities) from 1480 sites worldwide. The database (RPDv1b - Harrison et al., 2021) is available at https://doi.org/10.17864/1947.000345.Peer reviewe

The Reading Palaeofire Database: an expanded global resource to document changes in fire regimes from sedimentary charcoal records

Sedimentary charcoal records are widely used to reconstruct regional changes in fire regimes through time in the geological past. Existing global compilations are not geographically comprehensive and do not provide consistent metadata for all sites. Furthermore, the age models provided for these records are not harmonised and many are based on older calibrations of the radiocarbon ages. These issues limit the use of existing compilations for research into past fire regimes. Here, we present an expanded database of charcoal records, accompanied by new age models based on recalibration of radiocarbon ages using IntCal20 and Bayesian age-modelling software. We document the structure and contents of the database, the construction of the age models, and the quality control measures applied. We also record the expansion of geographical coverage relative to previous charcoal compilations and the expansion of metadata that can be used to inform analyses. This first version of the Reading Palaeofire Database contains 1676 records (entities) from 1480 sites worldwide. The database (RPDv1b – Harrison et al., 2021) is available at https://doi.org/10.17864/1947.000345

Abstract A007: Pancreatic cancer comprises co-existing transcriptional states regulated by distinct master regulator programs

Abstract Despite extensive efforts, reproducible assessment of pancreatic ductal adenocarcinoma (PDA) heterogeneity and plasticity at the single cell level remains elusive. Systematic, network-based analysis of single cell RNA-seq profiles showed that most PDA tumors comprise three coexisting lineages whose aberrant transcriptional state is mechanistically controlled by distinct regulatory programs. These lineages were characterized by the aberrant activation of either gastrointestinal lineage markers (GLS), transcriptional effectors of morphogen pathways (MOS) and acinar to ductal metaplasia markers (ALS). Each lineage was characterized by cells in two different cell states determined by the differential activation of MEK signaling (M+/M-) and high cellular plasticity. These states were confirmed in multiple cohorts, cell lines, PDX models and harmonized with bulk profile analyses. Master regulators (MRs) of GLS and MOS state were predictive of patient’s survival in bulk profiles. Cross-state plasticity was confirmed by lineage tracing assays, while pooled CRISPR/Cas9 assays confirmed the essentiality of identified MR proteins. Finally, mechanistic MR-mediated cell state control was confirmed by MR expression-mediated reprogramming of MOS cells to a GLS state. Our work provided a mechanistic model of pancreatic cancer heterogeneity and testable hypothesis to target cell state-specific pancreatic cancer dependencies. Citation Format: Pasquale Laise, Mikko Turunen, Hans Carlo Maurer, Alvaro Curiel Garcia, Ela Elyada, Bernhard Schmierer, Lorenzo Tomassoni, Jeremy Worley, Mariano J. Alvarez, Jordan Kesner, Xiangtian Tan, Somnath Tagore, Ester Calvo Fernandez, Kelly Wong, Alexander L. E. Wang, Sabrina Ge, Alina C. Iuga, Aaron T. Griffin, Winston Wong, Gulam A. Manji, Faiyaz Notta, David A. Tuveson, Kenneth P. P. Olive, Andrea Califano. Pancreatic cancer comprises co-existing transcriptional states regulated by distinct master regulator programs [abstract]. In: Proceedings of the AACR Special Conference on Pancreatic Cancer; 2022 Sep 13-16; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2022;82(22 Suppl):Abstract nr A007.</jats:p