Project description:R&D project to develop low input library construction methods. .
This dataset contains all the data available for this study on 2019-04-01.
Project description:Plant small RNAs are a diverse and complex set of molecules, ranging in length from 21 to 24 nt, involved in a wide range of essential biological processes. Nowadays, high-throughput sequencing is the most commonly used method for the discovery and quantification of small RNAs. However, it is known that several biases can occur during the preparation of small RNA libraries, especially using low input RNA. We used two types of plant biological samples to evaluate the performance of seven commercially available methods for small RNA library construction, using different RNA input amounts. We show that when working with plant material, library construction methods have differing capabilities to capture small RNAs, and that different library construction methods provide better results when applied to the detection of microRNAs, phased small RNAs, or tRNA-derived fragments.
Project description:Advances in Next Generation Sequencing (NGS) have made available a wealth of information that had previously been inaccessible to researchers and clinicians. NGS has been applied to understand genomic, transcriptomic, and epigenomic changes and gained traction as a significant tool capable of accelerating diagnosis, prognosis, and biomarker discovery. However, these NGS assays have yet to be practical methods for patient stratification or diagnosis because of the gap between the tiny quantities of biomaterials provided by a clinical sample and the large DNA input required by most of these assays. Current library preparation methodologies typically require large input amounts of DNA and a long and complicated manual process. Here we present a microfluidic reactor system for NGS library preparation, capable of reducing the number of pipetting steps significantly, automating much of the process, while supporting extremely low DNA input requirement (10 pg per library). This largely automated technology will allow for low-input preparations of 8 libraries simultaneously while reducing batch to batch variation and operator hands-on time.
Project description:We report a set of rapid, efficient and low-cost methods for ATAC-seq library construction and data analysis, realized large-scale and rapid sequencing. These methods can provide a reference for the study of epigenetic regulation of gene expression.