Determining Histories of Slip on Normal Faults With Bedrock Scarps Using Cosmogenic Nuclide Exposure Data

Cosmogenic exposure data can be used to calculate time-varying fault slip rates on normal faults with exposed bedrock scarps. The method relies on assumptions related to how the scarp is preserved, which should be consistent at multiple locations along the same fault. Previous work commonly relied on cosmogenic data from a single sample locality to determine the slip rate of a fault. Here we show that by applying strict sampling criteria and using geologically informed modeling parameters in a Bayesian-inference Markov chain Monte Carlo method, similar patterns of slip rate changes can be modeled at multiple sites on the same fault. Consequently, cosmogenic data can be used to resolve along-strike fault activity. We present cosmogenic 36Cl concentrations from seven sites on two faults in the Italian Apennines. The average slip rate varies between sites on the Campo Felice Fault (0.84 ± 0.23 to 1.61 ± 0.27 mm yr−1), and all sites experienced a period of higher than average slip rate between 0.5 and 2 ka and a period of lower than average slip rate before 3 ka. On the Roccapreturo fault, slip rate in the center of the fault is 0.55 ± 0.11 and 0.35 ± 0.05 mm yr−1 at the fault tip near a relay zone. The estimated time since the last earthquake is the same at each site along the same fault (631 ± 620 years at Campo Felice and 2,603 ± 1,355 years at Roccapreturo). These results highlight the potential for cosmogenic exposure data to reveal the detailed millennial history of earthquake slip on active normal faults

Extensive transcriptional responses are co-ordinated by microRNAs as revealed by Exon-Intron Split Analysis (EISA)

Epithelial-mesenchymal transition (EMT) has been a subject of intense scrutiny as it facilitates metastasis and alters drug sensitivity. Although EMT-regulatory roles for numerous miRNAs and transcription factors are known, their functions can be difficult to disentangle, in part due to the difficulty in identifying direct miRNA targets from complex datasets and in deciding how to incorporate 'indirect' miRNA effects that may, or may not, represent biologically relevant information. To better understand how miRNAs exert effects throughout the transcriptome during EMT, we employed Exon-Intron Split Analysis (EISA), a bioinformatic technique that separates transcriptional and post-transcriptional effects through the separate analysis of RNA-Seq reads mapping to exons and introns. We find that in response to the manipulation of miRNAs, a major effect on gene expression is transcriptional. We also find extensive co-ordination of transcriptional and post-transcriptional regulatory mechanisms during both EMT and mesenchymal to epithelial transition (MET) in response to TGF-β or miR-200c respectively. The prominent transcriptional influence of miRNAs was also observed in other datasets where miRNA levels were perturbed. This work cautions against a narrow approach that is limited to the analysis of direct targets, and demonstrates the utility of EISA to examine complex regulatory networks involving both transcriptional and post-transcriptional mechanisms.Katherine A. Pillman, Kaitlin G. Scheer, Emily Hackett-Jones, Klay Saunders, Andrew G Bert, John Toubia, Holly J Whitfield, Sunil Sapkota, Laura Sourdin, Hoang Pham, Thuc D. Le, Joseph Cursons, Melissa J. Davis, Philip A. Gregory, Gregory J. Goodall and Cameron P. Bracke