Transcript Isoform-Specific Estimation of Poly(A) Tail Length by Nanopore Sequencing of Native RNA.

The poly(A) tail is a homopolymeric stretch of adenosine at the 3'-end of mature RNA transcripts and its length plays an important role in nuclear export, stability, and translational regulation of mRNA. Existing techniques for genome-wide estimation of poly(A) tail length are based on short-read sequencing. These methods are limited because they sequence a synthetic DNA copy of mRNA instead of the native transcripts. Furthermore, they can identify only a short segment of the transcript proximal to the poly(A) tail which makes it difficult to assign the measured poly(A) length uniquely to a single transcript isoform. With the introduction of native RNA sequencing by Oxford Nanopore Technologies, it is now possible to sequence full-length native RNA. A single long read contains both the transcript and the associated poly(A) tail, thereby making transcriptome-wide isoform-specific poly(A) tail length assessment feasible. We developed tailfindr-an R-based package for estimating poly(A) tail length from Oxford Nanopore sequencing data. In this chapter, we describe in detail the pipeline for transcript isoform-specific poly(A) tail profiling based on native RNA Nanopore sequencing-from library preparation to downstream data analysis with tailfindr.

tailfindr: alignment-free poly(A) length measurement for Oxford Nanopore RNA and DNA sequencing.

Polyadenylation at the 3'-end is a major regulator of messenger RNA and its length is known to affect nuclear export, stability, and translation, among others. Only recently have strategies emerged that allow for genome-wide poly(A) length assessment. These methods identify genes connected to poly(A) tail measurements indirectly by short-read alignment to genetic 3'-ends. Concurrently, Oxford Nanopore Technologies (ONT) established full-length isoform-specific RNA sequencing containing the entire poly(A) tail. However, assessing poly(A) length through base-calling has so far not been possible due to the inability to resolve long homopolymeric stretches in ONT sequencing. Here we present tailfindr, an R package to estimate poly(A) tail length on ONT long-read sequencing data. tailfindr operates on unaligned, base-called data. It measures poly(A) tail length from both native RNA and DNA sequencing, which makes poly(A) tail studies by full-length cDNA approaches possible for the first time. We assess tailfindr's performance across different poly(A) lengths, demonstrating that tailfindr is a versatile tool providing poly(A) tail estimates across a wide range of sequencing conditions.

Online decoding of object-based attention using real-time fMRI.

Visual attention is used to selectively filter relevant information depending on current task demands and goals. Visual attention is called object-based attention when it is directed to coherent forms or objects in the visual field. This study used real-time functional magnetic resonance imaging for moment-to-moment decoding of attention to spatially overlapped objects belonging to two different object categories. First, a whole-brain classifier was trained on pictures of faces and places. Subjects then saw transparently overlapped pictures of a face and a place, and attended to only one of them while ignoring the other. The category of the attended object, face or place, was decoded on a scan-by-scan basis using the previously trained decoder. The decoder performed at 77.6% accuracy indicating that despite competing bottom-up sensory input, object-based visual attention biased neural patterns towards that of the attended object. Furthermore, a comparison between different classification approaches indicated that the representation of faces and places is distributed rather than focal. This implies that real-time decoding of object-based attention requires a multivariate decoding approach that can detect these distributed patterns of cortical activity.