Biology subjects

Morrow, B.

Publications and source records attributed to Morrow, B..

3 recordsLinked to original sources

bioRxiv2022

Single cell transcriptomics uncovers a non-autonomous Tbx1-dependent genetic program controlling cardiac neural crest cell deployment and progression

Disruption of cardiac neural crest cells (CNCCs) results in congenital heart disease, yet we do not understand the cell fate dynamics as these cells differentiate to vascular smooth muscle cells. Here we utilized single-cell RNA-sequencing of NCCs from the pharyngeal apparatus with heart in control mouse embryos and when Tbx1, the gene for 22q11.2 deletion syndrome, is inactivated. We uncovered three dynamic transitions of pharyngeal NCCs expressing Tbx2 and Tbx3 through differentiated CNCCs expressing cardiac transcription factors with smooth muscle genes, and that these transitions are altered non-autonomously by loss of Tbx1. Further, inactivation of Tbx2 and Tbx3 in early CNCCs resulted in aortic arch branching defects due to failed smooth muscle differentiation. Loss of Tbx1 interrupted mesoderm to CNCC cell-cell communication with upregulation of BMP signaling with reduced MAPK signaling and failed dynamic transitions of CNCCs leading to disruption of aortic arch artery formation and cardiac outflow tract septation.

developmental biology↗

bioRxiv2022

Transcriptomics based prediction of survival and response to therapy in malignant mesothelioma

Malignant mesothelioma is an aggressive cancer with limited treatment options and poor prognosis. Better understanding of mesothelioma genomics and transcriptomics could advance novel therapies. We performed whole-exome and RNA-sequencing of germline and tumors of 122 patients with pleural, peritoneal, and tunica-vaginalis mesothelioma. We identify a 48 gene prognostic signature that is highly predictive of mesothelioma patient survival including CCNB1, whose expression is highly predictive of patient survival on its own. Using a synthetic-lethality (SL) based pipeline for analyzing the patients transcriptomic data, we identified SL-based signatures predictive of response to an anti-PD1 immune checkpoint inhibitor and combination therapies with pemetrexed. These SL-profiles successfully predict the overall patient-response observed across targeted, immuno- and chemotherapies in 11 independent mesothelioma clinical trials spanning 7 different treatments. These findings lay a basis for future studies aimed specifically at testing the ability of these SL profiles to serve as treatment biomarkers in mesothelioma.

cancer biology↗

bioRxiv2018

The 22q11 low copy repeats are characterized by unprecedented size and structure variability

AbstractLow copy repeats (LCRs) are recognized as a significant source of genomic instability, driving genome variability and evolution. The chromosome 22 LCRs (LCR22s) are amongst the most complex regions in the genome and their structure remains unresolved. These LCR22s mediate non-allelic homologous recombination (NAHR) leading to the 22q11 deletion syndrome (22q11DS), causing the most frequent genomic disorder. Using fiber FISH optical mapping, we have de novo assembled the LCR22s in 33 cell lines. We observed a high level of variation in LCR22 structures, including 26 different haplotypes of LCR22A with alleles ranging from 250 Kb to over 2,000 Kb. An additional four haplotypes were detected using Bionano mapping. Further, Bionano maps generated from 154 individuals from different populations suggested significantly different LCR22 haplotype frequencies between populations. Furthermore, haplotype analysis in nine 22q11DS patients resulted in the localization of the NAHR site to a 160 Kb paralog between LCR22A and -D in seven patients and to a 31 Kb region in two individuals with a rearrangement between LCR22A and -B.. This 31 Kb region contains a palindromic AT-rich repeat known to be a driver of chromosomal rearrangements. Our study highlights an unprecedented level of polymorphism in the structure of LCR22s, which are likely still evolving. We present the most comprehensive map of LCR22 variation to date, paving the way towards investigating the role of LCR variation as a driver of 22q11 rearrangements and the phenotypic variability in 22q11DS patients as well as in the general population.

genomics↗