Dear community.

on my way to address alternatively used exons in a bulkRNAseq dataset I used fastq files and aligned reads with Rsubjunc (see in code below).

To get a first impression I fed in the bam files of our control into IGV and looked a gene I know from from earlier studies and was surprised to see that the end of the transcript is split, as if the C-terminus was not connected on mRNA level. This confused be because the mRNA should be connected. Is there something, a setting, or something else I am missing here?

I merged all six bam files in hope the merged file get more read connecting Ex45 with Ex46 (Total exon count is 48).

Additionally, quiet a few reads are also found in the intronic regions, although not connected enough to say this is intron retention?

I am happy to hear your opinion on this.

fastq_files <- list.files("../fastq/raw/", full.names = T, include.dirs = F)
fastq_files_abs <- normalizePath(fastq_files) 

subjunc(index = "/home/chuddy/bioinformatics/ref_genomes/mouse_38/genome/subread/GRCm38",  
      nthreads = 20, 
      readfile1 = fastq_files_abs, 
      sortReadsByCoordinates = TRUE)


> sessionInfo( )
R version 4.3.2 (2023-10-31)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 20.04.6 LTS

Matrix products: default
BLAS:   /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.9.0 
LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.9.0

locale:
 [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C               LC_TIME=de_CH.UTF-8        LC_COLLATE=en_US.UTF-8    
 [5] LC_MONETARY=de_CH.UTF-8    LC_MESSAGES=en_US.UTF-8    LC_PAPER=de_CH.UTF-8       LC_NAME=C                 
 [9] LC_ADDRESS=C               LC_TELEPHONE=C             LC_MEASUREMENT=de_CH.UTF-8 LC_IDENTIFICATION=C       

time zone: Europe/Zurich
tzcode source: system (glibc)

attached base packages:
[1] grid      stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
 [1] gridExtra_2.3   Rsubread_2.14.2 lubridate_1.9.3 forcats_1.0.0   stringr_1.5.1   dplyr_1.1.4     purrr_1.0.2    
 [8] readr_2.1.5     tidyr_1.3.1     tibble_3.2.1    ggplot2_3.4.4   tidyverse_2.0.0

loaded via a namespace (and not attached):
 [1] Matrix_1.6-5      gtable_0.3.4      compiler_4.3.2    tidyselect_1.2.0  scales_1.3.0      lattice_0.22-5   
 [7] R6_2.5.1          generics_0.1.3    knitr_1.45        munsell_0.5.0     pillar_1.9.0      tzdb_0.4.0       
[13] rlang_1.1.3       utf8_1.2.4        stringi_1.8.3     xfun_0.41         timechange_0.3.0  cli_3.6.2        
[19] withr_3.0.0       magrittr_2.0.3    rstudioapi_0.15.0 hms_1.1.3         lifecycle_1.0.4   vctrs_0.6.5      
[25] glue_1.7.0        fansi_1.0.6       colorspace_2.1-0  tools_4.3.2       pkgconfig_2.0.3