To compare the two RNA-sequencing protocols, ribo-minus RNA-sequencing (rmRNA-seq) and polyA-selected RNA-sequencing (mRNA-seq), we acquired transcriptomic data-52 and 32 million alignable reads of 35 bases in length-from the mouse cerebrum, respectively. We found that a higher proportion, 44% and 25%, of the uniquely alignable rmRNA-seq reads, is in intergenic and intronic regions, respectively, as compared to 23% and 15% from the mRNA-seq dataset. Further analysis made an additional discovery of transcripts of protein-coding genes (such as Histone, Heg1, and Dux), ncRNAs, snoRNAs, snRNAs, and novel ncRNAs as well as repeat elements in rmRNA-seq dataset. This result suggests that rmRNA-seq method should detect more polyA- or bimorphic transcripts. Finally, through comparative analyses of gene expression profiles among multiple datasets, we demonstrated that different RNA sample preparations may result in significant variations in gene expression profiles.
Here, we evaluate the contribution of two major biological processes—DNA replication and transcription—to mutation rate variation in human genomes. Based on analysis of the public human tissue transcriptomics data, high-resolution replicating map of Hela cells and dbSNP data, we present significant correlations between expression breadth, replication time in local regions and SNP density. SNP density of tissue-specific (TS) genes is significantly higher than that of housekeeping (HK) genes. TS genes tend to locate in late-replicating genomic regions and genes in such regions have a higher SNP density compared to those in early-replication regions. In addition, SNP density is found to be positively correlated with expression level among HK genes. We conclude that the process of DNA replication generates stronger mutational pressure than transcription-associated biological processes do, resulting in an increase of mutation rate in TS genes while having weaker effects on HK genes. In contrast, transcription-associated processes are mainly responsible for the accumulation of mutations in highly-expressed HK genes.
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