Huge difference in mapping rates between two mouse tissues?

[jdrnevich]

I have a bulk RNA-Seq data set of 2x150 PE for 36 mouse samples, half from liver tissue and half from muscle (gastrocnemius). FastQC shows the muscle samples with only a slight increase in % Duplicates and % GC content over the liver samples. Both aligned to the same GRCm39/Gencode M33 genome using STAR/2.7.10a in a custom nextflow script using the following parameters (we add the gtf in on the fly rather than in the index):

      STAR --runThreadN 8 \
      --genomeDir star-2.7.10a-gencode-GRCm39.primary_assembly \
      --readFilesIn ${read1} ${read2} \
      --sjdbGTFfile gencode.vM33.primary_assembly.annotation.gtf \
      --readFilesCommand gunzip -c \
      --outFileNamePrefix ${pair_id}_ \
      --sjdbGTFtagExonParentGene gene_id \
      --outSAMtype BAM SortedByCoordinate \
      --quantMode GeneCounts \
      --runDirPerm All_RWX \
      --sjdbOverhang 149

The liver samples mapped at a normal rate of ~150 million of reads per hour but the muscle samples are only mapping around 2 M rph, and with ~80 million reads per sample, they are taking ~2 days each! All samples including muscle had 80-90% uniquely mapping reads. What could be causing the huge slow down in mapping the muscle reads? I've googled a bit and found #996 but neither the number of contigs or low mappability seem to apply to the muscle samples. I've attached a full Log.final.out for one muscle and one liver sample, and also pulled out mapping speed and % uniquely mapped reads for all. Thanks for any advice (other than wait for the last few muscle samples to finish)!

$ cat Gastroc_DEPOWER_SPo_16_CAACAATTCG-GCGACCGATT_L006_Log.final.out
                                 Started job on |       Nov 25 05:17:43
                             Started mapping on |       Nov 25 05:21:29
                                    Finished on |       Nov 26 22:57:38
       Mapping speed, Million of reads per hour |       2.31

                          Number of input reads |       96288036
                      Average input read length |       281
                                    UNIQUE READS:
                   Uniquely mapped reads number |       86806641
                        Uniquely mapped reads % |       90.15%
                          Average mapped length |       281.25
                       Number of splices: Total |       101457314
            Number of splices: Annotated (sjdb) |       100750020
                       Number of splices: GT/AG |       100754298
                       Number of splices: GC/AG |       542168
                       Number of splices: AT/AC |       52426
               Number of splices: Non-canonical |       108422
                      Mismatch rate per base, % |       0.24%
                         Deletion rate per base |       0.01%
                        Deletion average length |       3.50
                        Insertion rate per base |       0.01%
                       Insertion average length |       1.55
                             MULTI-MAPPING READS:
        Number of reads mapped to multiple loci |       6886393
             % of reads mapped to multiple loci |       7.15%
        Number of reads mapped to too many loci |       355315
             % of reads mapped to too many loci |       0.37%
                                  UNMAPPED READS:
  Number of reads unmapped: too many mismatches |       0
       % of reads unmapped: too many mismatches |       0.00%
            Number of reads unmapped: too short |       2196405
                 % of reads unmapped: too short |       2.28%
                Number of reads unmapped: other |       43282
                     % of reads unmapped: other |       0.04%
                                  CHIMERIC READS:
                       Number of chimeric reads |       0
                            % of chimeric reads |       0.00%


$ cat Liver_DEPOWER_SPo_16_GTAGGTACAA-CACTCAAGAA_L006_Log.final.out
                                 Started job on |       Nov 23 03:19:24
                             Started mapping on |       Nov 23 03:23:09
                                    Finished on |       Nov 23 04:07:09
       Mapping speed, Million of reads per hour |       115.39

                          Number of input reads |       84622906
                      Average input read length |       281
                                    UNIQUE READS:
                   Uniquely mapped reads number |       69449931
                        Uniquely mapped reads % |       82.07%
                          Average mapped length |       280.69
                       Number of splices: Total |       69362082
            Number of splices: Annotated (sjdb) |       68898721
                       Number of splices: GT/AG |       68788068
                       Number of splices: GC/AG |       470609
                       Number of splices: AT/AC |       28236
               Number of splices: Non-canonical |       75169
                      Mismatch rate per base, % |       0.24%
                         Deletion rate per base |       0.01%
                        Deletion average length |       3.25
                        Insertion rate per base |       0.01%
                       Insertion average length |       1.94
                             MULTI-MAPPING READS:
        Number of reads mapped to multiple loci |       5974139
             % of reads mapped to multiple loci |       7.06%
        Number of reads mapped to too many loci |       286417
             % of reads mapped to too many loci |       0.34%
                                  UNMAPPED READS:
  Number of reads unmapped: too many mismatches |       0
       % of reads unmapped: too many mismatches |       0.00%
            Number of reads unmapped: too short |       2416728
                 % of reads unmapped: too short |       2.86%
                Number of reads unmapped: other |       6495691
                     % of reads unmapped: other |       7.68%
                                  CHIMERIC READS:
                       Number of chimeric reads |       0
                            % of chimeric reads |       0.00%



$ grep "speed" *Log.final.out
Gastroc_DEPOWER_SPo_16_CAACAATTCG-GCGACCGATT_L006_Log.final.out:       Mapping speed, Million of reads per hour |       2.31
Gastroc_DEPOWER_SPo_25_TAGATCCGAA-ACTTCGATAG_L006_Log.final.out:       Mapping speed, Million of reads per hour |       1.67
Gastroc_DEPOWER_TPo_14_TCTTAACTGG-TTCAGGCCGA_L006_Log.final.out:       Mapping speed, Million of reads per hour |       1.76
Gastroc_DEPOWER_TPo_17_GTCACATCCG-AGAACAGTGA_L006_Log.final.out:       Mapping speed, Million of reads per hour |       1.99
Gastroc_DEPOWER_TPo_21_TGAAGCATCT-GTTAGATACC_L006_Log.final.out:       Mapping speed, Million of reads per hour |       2.27
Gastroc_POWER_SPo_10_TGCGTGCGAA-ATCGGTATGA_L006_Log.final.out:       Mapping speed, Million of reads per hour | 2.14
Gastroc_POWER_SPo_1_TTGACCTAGC-GGAACACCAA_L006_Log.final.out:       Mapping speed, Million of reads per hour |  2.57
Gastroc_POWER_SPo_6_GCTTCAATCA-TTCCACCTGG_L006_Log.final.out:       Mapping speed, Million of reads per hour |  1.96
Gastroc_POWER_TPo_3_AATGGTACCT-ACAACCGTCG_L006_Log.final.out:       Mapping speed, Million of reads per hour |  1.85
Gastroc_POWER_TPo_8_GTAACATTGG-TCGTGGCCAA_L006_Log.final.out:       Mapping speed, Million of reads per hour |  1.71
Gastroc_REPOWER_SPo_27_CGGACTACTT-CCTTAATACG_L006_Log.final.out:       Mapping speed, Million of reads per hour |       2.19
Gastroc_REPOWER_SPo_31_AACGGAGTCC-GACACTCCTA_L006_Log.final.out:       Mapping speed, Million of reads per hour |       2.23
Gastroc_REPOWER_SPo_36_AGGTGTGACC-GAGTTCGGAG_L006_Log.final.out:       Mapping speed, Million of reads per hour |       2.05
Gastroc_REPOWER_TPo_27_CCAGAGTTCC-CGAGAGACAT_L006_Log.final.out:       Mapping speed, Million of reads per hour |       2.15
Gastroc_REPOWER_TPo_33_GACTGACATA-ATGCGGCCAA_L006_Log.final.out:       Mapping speed, Million of reads per hour |       2.75
Liver_DEPOWER_SPo_16_GTAGGTACAA-CACTCAAGAA_L006_Log.final.out:       Mapping speed, Million of reads per hour | 115.39
Liver_DEPOWER_SPo_24_TGCGACTTCG-TTGTTGCAGA_L006_Log.final.out:       Mapping speed, Million of reads per hour | 157.89
Liver_DEPOWER_SPo_25_TTGTCACGTT-TGTGTAGCGG_L006_Log.final.out:       Mapping speed, Million of reads per hour | 149.13
Liver_DEPOWER_TPo_14_CAACGACTGA-CCTGACAGAG_L006_Log.final.out:       Mapping speed, Million of reads per hour | 167.74
Liver_DEPOWER_TPo_17_GATTCGGCTA-AGACCGTTAA_L006_Log.final.out:       Mapping speed, Million of reads per hour | 148.09
Liver_DEPOWER_TPo_21_TGGTGGCTAG-AAGGTCATCG_L006_Log.final.out:       Mapping speed, Million of reads per hour | 147.29
Liver_POWER_SPo_10_ATCCAATAGG-TCGTCATCTT_L006_Log.final.out:       Mapping speed, Million of reads per hour |   153.41
Liver_POWER_SPo_1_GCGATCCTTG-CTCAGACACC_L006_Log.final.out:       Mapping speed, Million of reads per hour |    143.57
Liver_POWER_SPo_6_TGTTCCACTT-AATGGCACGG_L006_Log.final.out:       Mapping speed, Million of reads per hour |    131.55
Liver_POWER_TPo_3_AGACCGTTAA-TGGCAATACA_L006_Log.final.out:       Mapping speed, Million of reads per hour |    140.22
Liver_POWER_TPo_4_ACTATTGACC-GCCGATGGTT_L006_Log.final.out:       Mapping speed, Million of reads per hour |    126.06
Liver_POWER_TPo_8_GCCTAATTCC-AGGTTGCACG_L006_Log.final.out:       Mapping speed, Million of reads per hour |    132.88
Liver_REPOWER_SPo_27_AGGCCAGGAT-ACTCCTGCCT_L006_Log.final.out:       Mapping speed, Million of reads per hour | 134.40
Liver_REPOWER_SPo_31_AACGCCTGTG-CGAGTCCGTT_L006_Log.final.out:       Mapping speed, Million of reads per hour | 138.02
Liver_REPOWER_SPo_36_CGTGTGAGTG-GCCGAACCAA_L006_Log.final.out:       Mapping speed, Million of reads per hour | 122.46
Liver_REPOWER_TPo_27_CGTATGTGAA-AGGTAGTGCG_L006_Log.final.out:       Mapping speed, Million of reads per hour | 147.61
Liver_REPOWER_TPo_29_TACGTCACAA-CGTGGTATGG_L006_Log.final.out:       Mapping speed, Million of reads per hour | 151.13
Liver_REPOWER_TPo_33_GGAAGATCCG-TACCGAATTC_L006_Log.final.out:       Mapping speed, Million of reads per hour | 137.76

$ grep "Uniquely mapped reads %" *Log.final.out
Gastroc_DEPOWER_SPo_16_CAACAATTCG-GCGACCGATT_L006_Log.final.out:                        Uniquely mapped reads % |       90.15%
Gastroc_DEPOWER_SPo_25_TAGATCCGAA-ACTTCGATAG_L006_Log.final.out:                        Uniquely mapped reads % |       91.53%
Gastroc_DEPOWER_TPo_14_TCTTAACTGG-TTCAGGCCGA_L006_Log.final.out:                        Uniquely mapped reads % |       90.46%
Gastroc_DEPOWER_TPo_17_GTCACATCCG-AGAACAGTGA_L006_Log.final.out:                        Uniquely mapped reads % |       87.99%
Gastroc_DEPOWER_TPo_21_TGAAGCATCT-GTTAGATACC_L006_Log.final.out:                        Uniquely mapped reads % |       90.25%
Gastroc_POWER_SPo_10_TGCGTGCGAA-ATCGGTATGA_L006_Log.final.out:                        Uniquely mapped reads % | 89.67%
Gastroc_POWER_SPo_1_TTGACCTAGC-GGAACACCAA_L006_Log.final.out:                        Uniquely mapped reads % |  91.37%
Gastroc_POWER_SPo_6_GCTTCAATCA-TTCCACCTGG_L006_Log.final.out:                        Uniquely mapped reads % |  89.79%
Gastroc_POWER_TPo_3_AATGGTACCT-ACAACCGTCG_L006_Log.final.out:                        Uniquely mapped reads % |  88.38%
Gastroc_POWER_TPo_8_GTAACATTGG-TCGTGGCCAA_L006_Log.final.out:                        Uniquely mapped reads % |  87.24%
Gastroc_REPOWER_SPo_27_CGGACTACTT-CCTTAATACG_L006_Log.final.out:                        Uniquely mapped reads % |       89.29%
Gastroc_REPOWER_SPo_31_AACGGAGTCC-GACACTCCTA_L006_Log.final.out:                        Uniquely mapped reads % |       88.53%
Gastroc_REPOWER_SPo_36_AGGTGTGACC-GAGTTCGGAG_L006_Log.final.out:                        Uniquely mapped reads % |       90.11%
Gastroc_REPOWER_TPo_27_CCAGAGTTCC-CGAGAGACAT_L006_Log.final.out:                        Uniquely mapped reads % |       86.86%
Gastroc_REPOWER_TPo_33_GACTGACATA-ATGCGGCCAA_L006_Log.final.out:                        Uniquely mapped reads % |       89.51%
Liver_DEPOWER_SPo_16_GTAGGTACAA-CACTCAAGAA_L006_Log.final.out:                        Uniquely mapped reads % | 82.07%
Liver_DEPOWER_SPo_24_TGCGACTTCG-TTGTTGCAGA_L006_Log.final.out:                        Uniquely mapped reads % | 87.17%
Liver_DEPOWER_SPo_25_TTGTCACGTT-TGTGTAGCGG_L006_Log.final.out:                        Uniquely mapped reads % | 87.47%
Liver_DEPOWER_TPo_14_CAACGACTGA-CCTGACAGAG_L006_Log.final.out:                        Uniquely mapped reads % | 86.13%
Liver_DEPOWER_TPo_17_GATTCGGCTA-AGACCGTTAA_L006_Log.final.out:                        Uniquely mapped reads % | 86.30%
Liver_DEPOWER_TPo_21_TGGTGGCTAG-AAGGTCATCG_L006_Log.final.out:                        Uniquely mapped reads % | 87.53%
Liver_POWER_SPo_10_ATCCAATAGG-TCGTCATCTT_L006_Log.final.out:                        Uniquely mapped reads % |   82.40%
Liver_POWER_SPo_1_GCGATCCTTG-CTCAGACACC_L006_Log.final.out:                        Uniquely mapped reads % |    84.71%
Liver_POWER_SPo_6_TGTTCCACTT-AATGGCACGG_L006_Log.final.out:                        Uniquely mapped reads % |    83.50%
Liver_POWER_TPo_3_AGACCGTTAA-TGGCAATACA_L006_Log.final.out:                        Uniquely mapped reads % |    85.10%
Liver_POWER_TPo_4_ACTATTGACC-GCCGATGGTT_L006_Log.final.out:                        Uniquely mapped reads % |    82.24%
Liver_POWER_TPo_8_GCCTAATTCC-AGGTTGCACG_L006_Log.final.out:                        Uniquely mapped reads % |    83.67%
Liver_REPOWER_SPo_27_AGGCCAGGAT-ACTCCTGCCT_L006_Log.final.out:                        Uniquely mapped reads % | 84.21%
Liver_REPOWER_SPo_31_AACGCCTGTG-CGAGTCCGTT_L006_Log.final.out:                        Uniquely mapped reads % | 83.51%
Liver_REPOWER_SPo_36_CGTGTGAGTG-GCCGAACCAA_L006_Log.final.out:                        Uniquely mapped reads % | 81.85%
Liver_REPOWER_TPo_27_CGTATGTGAA-AGGTAGTGCG_L006_Log.final.out:                        Uniquely mapped reads % | 87.42%
Liver_REPOWER_TPo_29_TACGTCACAA-CGTGGTATGG_L006_Log.final.out:                        Uniquely mapped reads % | 85.76%
Liver_REPOWER_TPo_33_GGAAGATCCG-TACCGAATTC_L006_Log.final.out:                        Uniquely mapped reads % | 83.89%

[ChristopherBottomsOMRF]

Total outsider here (not part of STAR team), but if it were me, I would create a small version of several of the FASTQ files and retry the alignments several times to see if the trend holds.