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Fungal Resistance gene-directed genome mining (FRIGG) pipeline

Inge Kjærbølling; Tammi C. Vesth; Mikael Rørdam Andersen

Fungal secondary metabolites are a rich source of valuable natural products, and genome sequencing has revealed a proliferation of predicted biosynthetic gene clusters in the genomes. It is however currently an unfeasible task to characterize all biosynthetic gene clusters and to identify possible uses of the compounds. Therefore, a rational approach is needed to identify a shortlist of gene clusters responsible for producing valuable compounds. 
To this end, several bioactive clusters include a resistance gene, which is a paralog of the target gene inhibited by the compound. This mechanism can be used to identify those clusters.

We have developed the FRIGG (Fungal ResIstance Gene-directed Genome mining) pipeline for identifying this type of biosynthetic gene clusters based on homology patterns of the cluster genes. As an example dataset, the FRIGG pipeline has been run using 51 Aspergillus and Penicillium genomes, identifying 72 unique families of putative resistance genes. The dataset is included with the software.

Files (509.5 MB)
Name Size
Input_data_pipeline.txt
md5:fe867cc78cfe09916530ebafbbc2fd5e
2.4 kB Download
Input_data_pipeline_gff.csv
md5:9088182ef66bb5dd496ec80c8f07230f
48.6 MB Download
Input_data_pipeline_InterPro.csv
md5:b7a681162c876d208b5814c1da272f2a
68.5 MB Download
Input_data_pipeline_proteins.csv
md5:c4120debf09d2265c60f21724f5bcb4f
350.6 MB Download
Input_data_pipeline_resistancepipeline_biblast_hfam_july2018.sql
md5:7d92e940921328fe3bfce0cb07bac973
18.3 MB Download
Input_data_pipeline_smurf.csv
md5:994ba9736fb5f5243b314c262984838a
5.2 MB Download
Input_data_pipeline_smurf.xml
md5:f87b7beb6135b1903af4c9f1b5fe9065
18.1 MB Download
LICENSE.txt
md5:e49f4652534af377a713df3d9dec60cb
35.1 kB Download
Python_version_info.txt
md5:0864f2f743717c351c640c19fdecab02
290 Bytes Download
R_version_info.txt
md5:b47d7555cdd16d15278245a5d21e1398
1.9 kB Download
Readme.txt
md5:ae35c45829f34d9adb2542833a7a97b4
6.8 kB Download
SelectedHfam.csv
md5:7a4482fe77c3ad4b36875d0dbb099f50
2.4 kB Download
SMG_Align_Trim_pip.py
md5:161b3978aa4d8f9aac575e321ef253a1
3.6 kB Download
SMG_fam_ver3_Pip.py
md5:56ba24b5147c101bd07d7110592ff394
10.0 kB Download
SMG_PCA_Phylo.R
md5:44ba0477b8e2b9dbcced19c35a0b3623
7.3 kB Download
SMG_prox_fam_ver3_Pip.py
md5:4b6181249da72d29d1f98493c865eb78
6.3 kB Download
SMG_prox_ver3_Pip.py
md5:bc57e26054bede056ef4740f1575ea3c
9.3 kB Download
SMG_resistance_ver3_Pip.py
md5:34b8322ce23cd8d4f3469917898cd845
21.2 kB Download
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