hisat2 --rna-strandness option and downstream htseq-count analysis

I’ve got some doubts on the hisat2 –rna-strandness option and its output for downstream analysis. Please see below.

I understand that the –rna-strandness option produces an XS tag to indicate where a transcript is from (on the + or – strand) for downstream transcriptome assembly analysis. I have a paired-end stranded sequencing library that was aligned to the genome using hisat2 without specifying the –rna-strandness (in other words, the default unstranded was the usage). Following this, the reads were assigned to genes using htseq-count and this time “-s reverse” was specified given the strand-specific sequencing assay type.

Would the above handling affect the alignment and counting results given the default usage of –rna-strandness in hisat2 followed by htseq-count -s reverse on a strand-specific assay? Since –rna-strandness is for transcriptome assembly using the XS tags generated and htseq does not use XS tags for counting, I presume there should be no practical impact from the above. Could you also shed light on this? in case I may have been overlooking other facts of the usages of the tools.

To help verify the above, I re-aligned and counted the reads from 2 samples by switching on –rna-strandness RF in hisat2. I attach the alignment and count features info. below for assessment.

Overall alignment rate of Sample 1: 94.52% (–rna-strandness RF) vs.94.12% (–rna-strandness unstranded)
Overall alignment rate of Sample 2: 94.57% (–rna-strandness RF) vs.94.15% (–rna-strandness unstranded)

Feature counts of Sample 1 (following –rna-strandness RF + -s reverse):
__no_feature 6327294
__ambiguous 2954776
__too_low_aQual 3784481
__not_aligned 688856
__alignment_not_unique 4858182

Feature counts of Sample 1 (following –rna-strandness unstranded + -s reverse):
__no_feature 6291151
__ambiguous 2911298
__too_low_aQual 4075017
__not_aligned 754400
__alignment_not_unique 16136045

Feature counts of Sample 2 (following –rna-strandness RF + -s reverse):
__no_feature 5417882
__ambiguous 1708510
__too_low_aQual 3532352
__not_aligned 564596
__alignment_not_unique 2859501

Feature counts of Sample 1 (following –rna-strandness unstranded + -s reverse):
__no_feature 5359434
__ambiguous 1676091
__too_low_aQual 3813344
__not_aligned 623122
__alignment_not_unique 2891792

These results look comparable to me across pipelines.

Thanks
Guan