Interpreting this PCA plot for RNA-seq

Question

I have RNA-seq from two sequencing batches; Lab technician says that he has run the RNA expression quantification two times in bathes 1 and 2 for example tumor 1 in batch 1 and tumor 1 in batch 2 , normal 2 in batch1 and normal 2 in batch 2. This is my design for DESeq2

> head(mycols)
        condition batch
N_1_305         N     1
N_1_310         N     1
N_1_337         N     1
N_1_353         N     1
T_1_305         T     1
T_1_310         T     1
> tail(mycols)
        condition batch
T_2_337         T     2
T_2_338         T     2
T_2_344         T     2
T_2_346         T     2
T_2_349         T     2
T_2_353         T     2
>

I got this PCA plot

And this is biplot of samples

In PCA plot I am seeing for instance , T_1_337 (batch1) has been placed too close to T_2_337 (batch2)

Then I used svd for detecting hidden batch

Does this mean that there is no big batch effect between experimental runs and I can concatenate the fastqs from both batches for each sample (technical replication) or collapse technical replicates afterwards?

Please help me to interpret these Thank you

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EDITED

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Sorry @Devon, I have 4 lanes for each samples (paired end) in each of experimental runs; For concatenating fastq files can I do like this ?

cat fastq1_lane1_batch1 fastq1_lane1_batch2 fastq1_lane2_batch1   fastq1_lane2_batch2  fastq1_lane3_batch1 fastq1_lane3_batch2 fastq1_lane4_batch1 fastq1_lane4_batch2  > fastq1  

cat fastq2_lane1_batch1 fastq2_lane1_batch2 fastq2_lane2_batch1   fastq2_lane2_batch2  fastq2_lane3_batch1 fastq2_lane3_batch2 fastq2_lane4_batch1 fastq2_lane4_batch2 > fastq2

Answer 1

Yes, you can safely concatenate the technical replicates. Odds are good that these are even the same libraries just sequenced twice, so even labeling them as replicates is a bit of a stretch. As an aside, it would be surprising if you actually had a batch effect in a situation like this. You will commonly see sequencing facilities just sequence a given sample a second time if it didn't get the number of reads requested by the client to begin with. They then just have the client concatenate the files.

Answer 2

Prepping the RNA on different days, or making Illumina libraries on different days, or having different technicians handle different samples; that can lead to batch effects. Running samples on two different days does not cause a significant batch effect, as you can plainly see in your PCA. You should just combine the fastqs.