The human T2T-CHM13 genome assembly provides unprecedented accuracy and completeness, offering invaluable insights into various research fields including transcriptomics. However, current gene annotations of T2T-CHM13 reference genome do not follow universal standards in format, which brings challenges in transcriptomics analysis. Here, we present a pipeline for RNA-seq differential gene expression, differential transcript expression and differential transcript usage analysis using T2T-CHM13 reference. The R/Bioconductor packages GenomicRanges and plyranges were used to efficiently organize T2T-CHM13 gene and transcript annotation information from GFF files. Using this pipeline, we analyzed an RNA-seq dataset of human CD4+ T cells at 3 different time points after activation from 10 healthy donors. By comparing the results to the results obtained using GRCh38 (hg38) reference genome, we showed the strength of using T2T-CHM13 reference for transcriptomics analysis in better read mapping and assignment rate.