Impact of Gene Annotation on RNA-seq Data Analysis

RNA-seq has become increasingly popular in transcriptome profiling. One of the major challenges in RNA-seq data analysis is the accurate mapping of junction reads to their genomic origins. To detect splicing sites in short reads, many RNA-seq aligners use reference transcriptome to inform placement of junction reads. However, no systematic evaluation has been performed to assess or quantify the benefits of incorporating reference transcriptome in mapping RNA-seq reads. Meanwhile, there exist multiple human genome annotation databases, including RefGene (RefSeq Gene), Ensembl, and the UCSC annotation database. The impact of the choice of an annotation on estimating gene expression remains insufficiently investigated

Genome-Wide Identification of ARF Transcription Factor Gene Family and Their Expression Analysis in Sweet Potato

Auxin response factors (ARFs) are a family of transcription factors that play an important role of auxin regulation through their binding with auxin response elements. ARF genes are represented by a large multigene family in plants; however, to our knowledge, the ARF gene family has not been well studied and characterized in sweet potatoes. In this study, a total of 25 ARF genes were identified in Ipomea trifida. The identified ItrARF genes’ conserved motifs, chromosomal locations, phylogenetic relationships, and their protein characteristics were systemically investigated using different bioinformatics tools. The expression patterns of ItfARF genes were analyzed within the storage roots and normal roots at an early stage of development. ItfARF16b and ItfARF16c were both highly expressed in the storage root, with minimal to no expression in the normal root. ItfARF6a and ItfARF10a exhibited higher expression in the normal root but not in the storage root. Subsequently, ItfARF1a, ItfARF2b, ItfARF3a, ItfARF6b, ItfARF8a, ItfARF8b, and ItfARF10b were expressed in both root types with moderate to high expression for each. All ten of these ARF genes and their prominent expression signify their importance within the development of each respective root type. This study provides comprehensive information regarding the ARF family in sweet potatoes, which will be useful for future research to discover further functional verification of these ItfARF genesECU Open Access Publishing Support Fun

Cloud Computing for Next-Generation Sequencing Data Analysis

High-throughput next-generation sequencing (NGS) technologies have evolved rapidly and are reshaping the scope of genomics research. The substantial decrease in the cost of NGS techniques in the past decade has led to its rapid adoption in biological research and drug development. Genomics studies of large populations are producing a huge amount of data, giving rise to computational issues around the storage, transfer, and analysis of the data. Fortunately, cloud computing has recently emerged as a viable option to quickly and easily acquire the computational resources for large-scale NGS data analyses. Some cloud-based applications and resources have been developed specifically to address the computational challenges of working with very large volumes of data generated by NGS technology. In this chapter, we will review some cloud-based systems and solutions for NGS data analysis, discuss the practical hurdles and limitations in cloud computing, including data transfer and security, and share the lessons we learned from the implementation of Rainbow, a cloud-based tool for large-scale genome sequencing data analysis