Comprehensive whole-genome structural variation detection is challenging with current approaches. With diploid cells as DNA source and the presence of numerous repetitive elements, short-read DNA sequencing cannot be used to detect structural variation efficiently. In this report, we show that genome mapping with long, fluorescently labeled DNA molecules imaged on nanochannel arrays can be used for whole-genome structural variation detection without sequencing. While whole-genome haplotyping is not achieved, local phasing (across >150-kb regions) is routine, as molecules from the parental chromosomes are examined separately. In one experiment, we generated genome maps from a trio from the 1000 Genomes Project, compared the maps against that derived from the reference human genome, and identified structural variations that are >5 kb in size. We find that these individuals have many more structural variants than those published, including some with the potential of disrupting gene function or regulation.

Motivation: Optical mapping is a technique for capturing fluorescent signal patterns of long DNAmolecules (in the range of 0.1 Mbp to 1 Mbp). Recently, it has been complementing the widely-used short-read sequencing technology by assisting with scaffolding and detecting large and complex structural variations. Here, we introduce a fast, robust and accurate tool called OMBlast for aligning optical maps, the set of signal locations on the molecules generated from optical mapping. Our method is based on the seed-and-extend approach from sequence alignment, with modifications specific to optical mapping.

Optical mapping is a molecular technique capturing specific patterns of fluorescent labels along DNA molecules. It has been widely applied in assisted-scaffolding in sequence assemblies, microbial strain typing and detection of structural variations. Various computational methods have been developed to analyze optical mapping data. However, existing tools for processing and visualizing optical map data still have many shortcomings. Here, we present OMTools, an efficient and intuitive data processing and visualization suite to handle and explore large-scale optical mapping profiles. OMTools includes modules for visualization (OMView), data processing and simulation. These modules together form an accessible and convenient pipeline for optical mapping analyses. OMTools is implemented in Java 1.8 and released under a GPL license. OMTools can be downloaded from https://github.com/aldenleung/OMTools and run on any standard desktop computer equipped with a Java virtual machine. Supplementary data are available at Bioinformatics online.

We present a new method, OMSV, for accurately and comprehensively identifying structural variations (SVs) from optical maps. OMSV detects both homozygous and heterozygous SVs, SVs of various types and sizes, and SVs with or without creating or destroying restriction sites. We show that OMSV has high sensitivity and specificity, with clear performance gains over the latest method. Applying OMSV to a human cell line, we identified hundreds of SVs >2 kbp, with 68 % of them missed by sequencing-based callers. Independent experimental validation confirmed the high accuracy of these SVs. The OMSV software is available at http://yiplab.cse.cuhk.edu.hk/omsv/ .

RNA-sequencing is a powerful tool in studying RNomics. However, the highly abundance of ribosomal RNAs (rRNA) and transfer RNA (tRNA) have predominated in the sequencing reads, thereby hindering the study of lowly expressed genes. Therefore, rRNA depletion prior to sequencing is often performed in order to preserve the subtle alteration in gene expression especially those at relatively low expression levels. One of the commercially available methods is to use DNA or RNA probes to hybridize to the target RNAs. However, there is always a concern with the non-specific binding and unintended removal of messenger RNA (mRNA) when the same set of probes is applied to different organisms. The degree of such unintended mRNA removal varies among organisms due to organism-specific genomic variation. We developed a computer-based method to design probes to deplete rRNA in an organism-specific manner. Based on the computation results, biotinylated-RNA-probes were produced by in vitro transcription and were used to perform rRNA depletion with subtractive hybridization. We demonstrated that the designed probes of 16S rRNAs and 23S rRNAs can efficiently remove rRNAs from Mycobacterium smegmatis. In comparison with a commercial subtractive hybridization-based rRNA removal kit, using organism-specific probes is better in preserving the RNA integrity and abundance. We believe the computer-based design approach can be used as a generic method in preparing RNA of any organisms for next-generation sequencing, particularly for the transcriptome analysis of microbes.

Proteolysis-targeting chimera (PROTAC) therapies degrading SWI/SNF ATPases interfere with androgen receptor (AR) signaling in AR-dependent castration-resistant prostate cancer (CRPC-AR). To explore the utility of SWI/SNF therapy beyond AR-sensitive CRPC, we investigated SWI-/SNF-targeting agents in AR-negative CRPC. SWI-/SNF-targeting PROTAC treatment of cell lines and organoid models reduced the viability of not only CRPC-AR but also WNT signaling–dependent AR-negative CRPC (CRPC-WNT). The CRPC-WNT subgroup represents 11% of around 400,000 cases of CRPC worldwide that die yearly. SWI/SNF ATPase SMARCA4 depletion interfered with the master transcriptional regulator TCF7L2 in CRPC-WNT. Functionally, TCF7L2 maintained proliferation via the MAPK signaling axis in this subtype of CRPC. Together, these data provide a mechanistic rationale for interventions that perturb DNA binding of the proproliferative transcription factor TCF7L2 and/or direct MAPK signaling inhibition in the CRPC-WNT subclass of advanced prostate cancer. Significance: SWI/SNF-targeting agents interfere with a lineage-defining molecular axis in the WNT signaling–dependent, androgen receptor-negative subtype of prostate cancer, which accounts for around 10% of castration-resistant tumors.