Stretched histone regions, such as super-enhancers and broad H3K4me3 domains, are associated with maintenance of cell identity and cancer. We connected super-enhancers and broad H3K4me3 domains in the K562 chronic myelogenous leukemia cell line as well as the MCF-7 breast cancer cell line with chromatin interactions. Super-enhancers and broad H3K4me3 domains showed higher association with chromatin interactions than their typical counterparts. Interestingly, we identified a subset of super-enhancers that overlap with broad H3K4me3 domains and show high association with cancer-associated genes including tumor suppressor genes. Besides cell lines, we could observe chromatin interactions by a Chromosome Conformation Capture (3C)-based method, in primary human samples. Several chromatin interactions involving super-enhancers and broad H3K4me3 domains are constitutive and can be found in both cancer and normal samples. Taken together, these results reveal a new layer of complexity in gene regulation by super-enhancers and broad H3K4me3 domains.

The recent advent of third-generation sequencing technologies brings promise for better characterization of genomic structural variants by virtue of having longer reads. However, long-read applications are still constrained by their high sequencing error rates and low sequencing throughput. Here, we present NanoVar, an optimized structural variant caller utilizing low-depth (8X) whole-genome sequencing data generated by Oxford Nanopore Technologies. NanoVar exhibits higher structural variant calling accuracy when benchmarked against current tools using low-depth simulated datasets. In patient samples, we successfully validate structural variants characterized by NanoVar and uncover normal alternative sequences or alleles which are present in healthy individuals.

Polymer axial drawing enables the design of optimal microarchitectured scaffolds for tendon regeneration.

DNA alterations have been extensively reported in multiple myeloma (MM); however, they cannot yet fully explain all the biological and molecular abnormalities in MM, which remains to this day an incurable disease with eventual emergence of refractory disease. Recent years have seen abnormalities at the RNA levels being reported to possess potential biological relevance in cancers. ADAR1-mediated A-to-I editing is an important posttranscriptional mechanism in human physiology, and the biological implication of its abnormality, especially at the global level, is underexplored in MM. In this study, we define the biological implications of A-to-I editing and how it contributes to MM pathogenesis. Here, we identified that the MM transcriptome is aberrantly hyperedited because of the overexpression of ADAR1. These events were associated with patients' survival independent of 1q21 amplifications and could affect patients' responsiveness to different treatment regimes. Our functional assays established ADAR1 to be oncogenic, driving cellular growth and proliferation in an editing-dependent manner. In addition, we identified NEIL1 (base-excision repair gene) as an essential and a ubiquitously edited ADAR1 target in MM. The recoded NEIL1 protein showed defective oxidative damage repair capacity and loss-of-function properties. Collectively, our data demonstrated that ADAR1-mediated A-to-I editing is both clinically and biologically relevant in MM. These data unraveled novel insights into MM molecular pathogenesis at the global RNA level.

Despite the increasing relevance of structural variants (SV) in the development of many human diseases, progress in novel pathological SV discovery remains impeded, partly due to the challenges of accurate and routine SV characterization in patients. The recent advent of third-generation sequencing (3GS) technologies brings promise for better characterization of genomic aberrations by virtue of having longer reads. However, the applications of 3GS are restricted by their high sequencing error rates and low sequencing throughput. To overcome these limitations, we present NanoVar, an accurate, rapid and low-depth (4X) 3GS SV caller utilizing long-reads generated by Oxford Nanopore Technologies. NanoVar employs split-reads and hard-clipped reads for SV detection and utilizes a neural network classifier for true SV enrichment. In simulated data, NanoVar demonstrated the highest SV detection accuracy (F1 score = 0.91) amongst other long-read SV callers using 12 gigabases (4X) of sequencing data. In patient samples, besides the detection of genomic aberrations, NanoVar also uncovered many normal alternative sequences or alleles which were present in healthy individuals. The low sequencing depth requirements of NanoVar enable the use of Nanopore sequencing for accurate SV characterization at a lower sequencing cost, an approach compatible with clinical studies and largescale SV-association research. ________________________________________________________________________________________