Hi, I am in bit of a confusion regarding different comparisons in RNASeq data analysis.

Here is what i have and already done.

Dataset 1: I have a mutant-strain and its wildtype. these were used to infact plant. Then RNA was extracted and sequenced with Illumina Paired-end 150bp sequencing with 3-replicates each

Analysis 1: DEGs analysis of plant-infection-mutants(A) vs plant-infection-wildtype(B) (A-vs-B)

1. Quality check of fastq files with FastQC
2. Quality trimming with FastP ( I did not perform any Quality Trimming as Data already seemed quality trimmed)
3. Read Split to get reference specific reads using bbsplit from bbmap package (with this i got plant specific reads and mutant-strain specific reads)
4. Reads alignment using Hisat2 version 2.2.1 to ref-genome using paired-end reads
5. Quantification using featureCounts with paired-end flags
6. DEG analysis using DESeq2

Dataset 2: Again, a mutant-strain and its wildtype. these were grown in flask. Then RNA was extracted and sequenced with Illumina Single-end 75bp sequencing with 4-replicates each. (this is an old data)

Analysis 2: DEGs analysis of flask-grown-mutants(C) vs flask-grown-wildtype(D) (C-vs-D)

1. Quality check of fastq files with FastQC
2. Quality trimming with FastP ( I did not perform any Quality Trimming as Data already seemed quality trimmed)
3. Reads alignment using Hisat2 version 2.2.1 to ref-genome using paired-end reads
4. Quantification using featureCounts with paired-end flags
5. DEG analysis using DESeq2

Now their are two more analysis which i want to do.

Analysis 3: DEGs analysis of plant-infection-mutants(A) vs flask-grown-mutants(C) (A-vs-C)

For Analysis-3 i did try this approach so far,

1. extracted the plant-infection-mutants(A) featurecounts data from the Analysis-1 featurecount matrix which is based on illumina paired-end 150bp sequencing (first 6 columns GeneID Chr Start End Strand Length + 3 columns which contain mutant expression values in plants)
2. extracted the flask-grown-mutants(C) feature counts data from the Analysis-2 featurecount matrix which is based on illumina single-end 75bp sequencing (first 6 columns GeneID Chr Start End Strand Length + 4 columns which contain mutant expression values in flask)
   1. Merged both based on the GeneIDs, (Note: A has 3 replicates, C has 4 replicates)
   2. DEG analysis using DESeq2 using the same commands as in A-vs-B and C-vs-D

Analysis 4: DEGs analysis of plant-infection-wildtype(B) vs flask-grown-wildtype(D) (C-vs-D)

For this i went with similar approach to Analysis-3

Questions

1. For analysis-1 and analysis-2 is my approach correct ? As far as i know, DESeq2 itself performs Median Ratio Normalization (MRN) so i didnot perfrom any other normalization.
2. I am confused about the analysis-3 and analysis-4. are they correct? or the Different sequence-type (paired vs single), difference in read-length (150bp-x2 vs 75bp-x1) will have any technical or batch effect ?
3. if analysis 3 and 4 are not correct, what should i do ? do i need to normalize them? by what method ?
4. Any other thoughts or points you have to raise.

Your thoughts and suggestions will be really helpful.

Regards