Expression profiling by high throughput sequencing
Summary
To understand how age rewires the chromatin accessibility landscape, we molecularly profiled 23 purified cell types from 11 tissues and organs by assessing the cumulative signature of 15-25 young and aged mice for robust difference detection.
Overall design
We performed RNA-seq for young (2 months) and aged (22-24 months) mice for FACS sorted cell-types.
A 3-prime biased approach was used to generate sequencing libraries as described previously (Sun et al. Nat Comms 2021; https://doi.org/10.1038/s41467-021-22863-0). Barcoded 19bp R1 and 111bp R2 paired-end reads per sequencing lane were assigned to individual samples using the sabre software (version 80faf94) with options “-u –m 2 –l 10" (https://github.com/najoshi/sabre) (Tsyganov et al. JOSS 2018; https://doi.org/10.21105/joss.00583).
Here we present the single-end demultiplexed reads per sample which were mapped to the mouse GRCm38.p6/mm10 genome primary assembly using Spliced Transcripts Alignment to a Reference (STAR) software version 2.5.2b (Dobin et al. Bioinformatics 2013; https://doi.org/10.1093/bioinformatics/bts635). STAR was run with mode alignReads with parameters “--outFileterMatchMinOverLred 0.3 --outFilerScoreMinOverLread 0.3 --twopassMode Basic –sjdbGTFfile –quanMode GeneCounts”. Reads with duplicated UMIs were removed using the software Je version 2.0.RC option markdupes (Girardot et al. BMC Bioinformatics, 2016; https://doi.org/10.1186/s12859-016-1284-2). Transcript quantification was performed using featureCounts version 2.0.1 with parameters “–Q10 -M"" (exonic regions of GENCODE’s vM24 annotation version) (Liao et al. NAR 2019; https://doi.org/10.1093/nar/gkz114).
Less...
More...