Jtdylktuy

I have this GTF file and I use the command below on a Linux machine to extract the coding regions of the genome:

awk '{if($3=="transcript" && $20==""protein_coding";"){print $0}}' gencode.gtf

How I could do the inverse and keep only non coding regions?

If you want all transcripts from that gtf file whose type isn't "protein_coding", you can use almost the same command, just change the == ("is") to != ("isn't"):

awk '{if($3=="transcript" && $20!=""protein_coding";"){print $0}}' gencode.gtf 

Or, a simpler version:

awk '$3=="transcript" && $20!=""protein_coding";"' gencode.gtf 

Note that this will not include any of the havana transcripts in the file, but I am assuming that's what you want since that's what your original command did.

Specifically, the command will return the following types of transcript (the numbers on the left are the number of such transcripts in the file):

awk '$3=="transcript" && $20!=""protein_coding";"{print $20}' gencode.gtf  | sort | uniq -c | sort -nk1

      1 "translated_processed_pseudogene";

      2 "Mt_rRNA";

      3 "IG_J_pseudogene";

      3 "TR_D_gene";

      4 "TR_J_pseudogene";

      5 "TR_C_gene";

     10 "IG_C_pseudogene";

     18 "IG_C_gene";

     18 "IG_J_gene";

     22 "Mt_tRNA";

     25 "3prime_overlapping_ncrna";

     27 "TR_V_pseudogene";

     37 "IG_D_gene";

     58 "non_stop_decay";

     59 "polymorphic_pseudogene";

     74 "TR_J_gene";

     97 "TR_V_gene";

    144 "IG_V_gene";

    182 "unitary_pseudogene";

    196 "IG_V_pseudogene";

    330 "sense_overlapping";

    387 "pseudogene";

    442 "transcribed_processed_pseudogene";

    531 "rRNA";

    802 "sense_intronic";

    860 "transcribed_unprocessed_pseudogene";

   1529 "snoRNA";

   1923 "snRNA";

   2050 "misc_RNA";

   2549 "unprocessed_pseudogene";

   3116 "miRNA";

   9710 "antisense";

  10623 "processed_pseudogene";

  11780 "lincRNA";

  13052 "nonsense_mediated_decay";

  25955 "retained_intron";

  28082 "processed_transcript";

You might also want to remove that "translated_processed_pseudogene" since that is actually translated into protein and is therefore technically coding:

awk '$3=="transcript" && 

     $20!=""protein_coding";" &&

     $20!=""translated_processed_pseudogene";"' gencode.gtf  

Getting the non coding regions of a protein coding transcript, sounds like you are looking for UTR.

UTR has its own feature in the gtf file. So you can do this:

$ awk -v FS="t" '$3=="UTR"' gencode.gtf

If the gtf file is compressed use this instead:

$ zcat gencode.gtf.gz | awk -v FS="t" '$3=="UTR"'

BTW: Why are you using such an old release of gencode? The current version is v29.

This isn't a problem that's easily solved with awk. It's not like you're extracting a feature that's annotated in the GTF file. Instead, you want the empty space between annotated features.

A few years ago I wrote a program called LocusPocus for a similar task. It uses a gene annotation to break down a genome into gene loci and intergenic regions. It handles overlapping annotations and other weirdness pretty robustly. The output will include both coding regions and non-coding regions, but you can identify the intergenic spaces as those with iLocus_type equal to iiLocus or fiLocus.

Note: the --delta parameter will extend each gene/transcript by 500bp by default.

Caveat: the program only accepts GFF3 input by default. Hopefully it won't be too hard to convert your GTF to GFF3.

Another caveat: eventual interpretation of these data will depend on what features are annotated in the genome and which annotations you include vs ignore. Do you want your non-coding regions to include non-coding genes, or should these be treated separately? Some non-coding regions will be full of transposable elements and other repetitive DNA, while others will have enhancers, promoters, or other regulatory elements. It's important to tread carefully before you jump to any conclusions.

Likely non-coding regions of genome are here

https://elifesciences.org/download/aHR0cHM6Ly9jZG4uZWxpZmVzY2llbmNlcy5vcmcvYXJ0aWNsZXMvMjE3NzgvZWxpZmUtMjE3Nzgtc3VwcDQtdjMueGxzeA==/elife-21778-supp4-v3.xlsx?_hash=KQi5jfO3kT2c4Qw44j4Rg6YAyCBQilYuWHVYXcRDuuo%3D