The mammalian hair follicle (HF) is a unique, highly regenerative organ with a distinct developmental cycle. Cashmere goat (Capra hircus) HFs can be divided into two categories based on structure and development time: primary and secondary follicles. To identify differentially expressed genes (DEGs) in the primary and secondary HFs of cashmere goats, the RNA sequencing of six individuals from Arbas, Inner Mongolia, was performed. A total of 617 DEGs were identified; 297 were upregulated while 320 were downregulated.
With the rapid development of next-generation high-throughput sequencing technology, RNA-seq has become a standard and important technique for transcriptome analysis. For multi-sample RNA-seq data, the existing expression estimation methods usually deal with each single-RNA-seq sample, and ignore that the read distributions are consistent across multiple samples. In the current study, we propose a structured sparse regression method, SSRSeq, to estimate isoform expression using multi-sample RNA-seq data.