Tools

Gene Model Translation / Correspondence

The set of allelic genes found in multiple individuals in a species or closely related species may be called a "pangene set," with the gene models that correspond by homology and position being called a pangene. The pangene set calculated for Glycine accessions at SoyBase can be used to find corresponding genes across assemblies and annotations.

There are several good options for identifying corresponding genes in different accessions or annotations. If you have ...

  • One or a few genes to look up? Use the Gene Search tool, then click on the "PANGENE SETS" link.
    Try it out with a sample gene, Glyma.01G000322.
    At the linked pangene report page in InterMine (set "Rows to page" to "All" to see all corresponding genes).
  • Many genes to look up among reference accessions? Download a correspondence table for the reference lines.
    • #pangene
    • glyma.FiskebyIII.gnm1.ann1
    • glyma.JD17.gnm1.ann1
    • glyma.Lee.gnm1.ann1
    • glyma.Lee.gnm2.ann1
    • glyma.Wm82.gnm1.ann1 = Wm82.a1.v1
    • glyma.Wm82.gnm2.ann1 = Wm82.a2.v1
    • glyma.Wm82.gnm4.ann1 = Wm82.a4.v1
    • glyma.Wm82.gnm5.ann1
    • glyma.Wm82.gnm6.ann1 = Wm82.a6.v1
    • glyma.Wm82_NJAU.gnm1.ann1
    • glyma.Zh13.gnm1.ann1
    • glyma.Zh13.gnm2.ann1
    • glyma.Zh13_IGA1005.gnm1.ann1
    • glyma.Zh35_IGA1004.gnm1.ann1
        • To work with this file, uncompress it, then open it using Excel or similar spreadsheet program;
        or if you have a little familiarity with a Unix terminal, you can extract data in many ways (a few examples): 
          cat Glycine.pan5.MKRS.table_ref_lines.tsv | tr '\t' '\n'   # to see the list of headers
  cut -f1,2,8,10 Glycine.pan5.MKRS.table_ref_lines.tsv | head   # to see four selected columns (the first 10 entries)
  grep -f YOUR_LIST_OF_GENES.txt Glycine.pan5.MKRS.table_ref_lines.tsv  # to search a provided list of gene IDs against the file
  • Many genes to look up among non-reference accessions? Download a correspondence table for all pangene accessions.
    • glycy.G1267.gnm1.ann1
    • glyd3.G1403.gnm1.ann1
    • glydo.G1134.gnm1.ann1
    • glyfa.G1718.gnm1.ann1
    • glyma.58-161.gnm1.ann1
    • glyma.Amsoy.gnm1.ann1
    • glyma.DongNongNo_50.gnm1.ann1
    • glyma.FengDiHuang.gnm1.ann1
    • glyma.FiskebyIII.gnm1.ann1
    • glyma.HanDouNo_5.gnm1.ann1
    • glyma.Hefeng25_IGA1002.gnm1.ann1
    • glyma.HeiHeNo_43.gnm1.ann1
    • glyma.Huaxia3_IGA1007.gnm1.ann1
    • glyma.Hwangkeum.gnm1.ann1
    • glyma.JD17.gnm1.ann1
    • glyma.JiDouNo_17.gnm1.ann1
    • glyma.JinDouNo_23.gnm1.ann1
    • glyma.Jinyuan_IGA1006.gnm1.ann1
    • glyma.JuXuanNo_23.gnm1.ann1
    • glyma.KeShanNo_1.gnm1.ann1
    • glyma.Lee.gnm1.ann1
    • glyma.Lee.gnm2.ann1
    • glyma.Lee.gnm3.ann1
    • glyma.PI_398296.gnm1.ann1
    • glyma.PI_548362.gnm1.ann1
    • glyma.QiHuangNo_34.gnm1.ann1
    • glyma.ShiShengChangYe.gnm1.ann1
    • glyma.TieFengNo_18.gnm1.ann1
    • glyma.TieJiaSiLiHuang.gnm1.ann1
    • glyma.TongShanTianEDan.gnm1.ann1
    • glyma.WanDouNo_28.gnm1.ann1
    • glyma.Wenfeng7_IGA1001.gnm1.ann1
    • glyma.Wm82.gnm1.ann1
    • glyma.Wm82.gnm2.ann1
    • glyma.Wm82.gnm4.ann1
    • glyma.Wm82.gnm5.ann1
    • glyma.Wm82.gnm6.ann1
    • glyma.Wm82_IGA1008.gnm1.ann1
    • glyma.Wm82_ISU01.gnm2.ann1
    • glyma.Wm82_NJAU.gnm1.ann1
    • glyma.XuDouNo_1.gnm1.ann1
    • glyma.YuDouNo_22.gnm1.ann1
    • glyma.Zh13.gnm1.ann1
    • glyma.Zh13.gnm2.ann1
    • glyma.Zh13_IGA1005.gnm1.ann1
    • glyma.Zh35_IGA1004.gnm1.ann1
    • glyma.ZhangChunManCangJin.gnm1.ann1
    • glyma.Zhutwinning2.gnm1.ann1
    • glyma.ZiHuaNo_4.gnm1.ann1
    • glyso.F_IGA1003.gnm1.ann1
    • glyso.PI483463.gnm1.ann1
    • glyso.PI_549046.gnm1.ann1
    • glyso.PI_562565.gnm1.ann1
    • glyso.PI_578357.gnm1.ann1
    • glyso.W05.gnm1.ann1
    • glyst.G1974.gnm1.ann1
    • glysy.G1300.gnm1.ann1
        • To work with this file, uncompress it, then open it using Excel or similar spreadsheet program;
        or if you have a little familiarity with a Unix terminal, you can extract data in many ways (a few examples): 
          cat Glycine.pan5.MKRS.table.tsv | head -1 | tr '\t' '\n'   # to see the list of headers
  cut -f1,2,8,10 Glycine.pan5.MKRS.table.tsv| head   # to see four selected columns (the first 10 entries)
  grep -f YOUR_LIST_OF_GENES.txt Glycine.pan5.MKRS.table.tsv  # to search a provided list of gene IDs against the file

Sample data from the correspondence table for the reference lines:

Pangene ID Wm82.gnm1.ann1 / Wm82.a1.v1 Wm82.gnm2.ann1 / Wm82.a2.v1 Wm82.gnm4.ann1 / Wm82.a4.v1 Wm82.gnm6.ann1 / Wm82.a6.v1 more
Glycine.pan5.pan46446 Glyma01g00210 Glyma.01G000100 Glyma.01G000100 Glyma.01G000100 ...
Glycine.pan5.pan46447 Glyma01g00291 Glyma.01G000300 Glyma.01G000322 Glyma.01G000322 ...
Glycine.pan5.pan43005 Glyma01g00300 Glyma.01G000400 Glyma.01G000400 Glyma.01G000400 ...
Glycine.pan5.pan34709 Glyma01g00321 Glyma.01G000600 Glyma.01G000600 Glyma.01G000600 ...
Glycine.pan5.pan74052 NONE NONE NONE Glyma.01G000750 ...
Glycine.pan5.pan99999 ... ... ... ... ...

Methods

The gene correspondences in the lookup tables above were calculated using the Pandagma package for identifying pangenes from a given collection of annotations. The method is described briefly here:

The Pandagma software package (Cannon, Lee, Berendzen) was used to identify pangene and gene family sets. The main steps in Pandagma's pangene process are:

  • Make pairwise homology comparisons between each annotation set;
  • Filter by provided percent identity and coverage parameters;
  • Identify synteny blocks among all annotation sets;
  • Cluster genes in synteny blocks;
  • Add back remaining genes based on homology, constraining by chromosome (e.g., chr1 genes to chr1 clusters)
  • Add "extra" annotation sets (those with more fragmentary assemblies or questionable annotation quality) to clusters identified above.

The Pandagma package is available at https://github.com/legumeinfo/pandagma, including the configuration used to calculate the pangene data above.

The pangene collection for Glycine, including data in several formats and descriptions of the fies, is in the "Glycine/GENUS/pangenes" section of the Data Store.

If you have extensive programmatic work and need to translate among arbitrary accessions, the gene_translate.pl utility in pandagma may be helpful.