Code and pipelines for: A chromosome-scale reference genome for the Ural owl (Strix uralensis) demonstrates the applicability of cell cultures as a sources for genomics of endangered species
Creators: name: Chrysostomakis, Ioannis
name: Mozer, Annika
name: Böhne, Astrid
Publisher: name: Zenodo
Year: 2025

description: Tree structure of files:

├── 0.ASM 

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Assemble long-read genome from HiFi reads (and Hi-C reads if available)

For information on how to best run the pipeline, which parts to run first and how, how to set up the configuration file, etc see the README file.In short: the pipeline accepts raw PACBIO circular reads or processed fastq HiFi reads and if desired trim adapters (when provided with an adapter file) and deontaminate using kraken2. There are also scripts for the user to process their Hi-C reads using fastp.Next, the user can perform multiple HiFiasm assemblies and generate statistics for all of them for comparison. The pipeline will output the Hifiassemblies and relevant statistics.

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│   ├── 00.SGE_genome_assembly.sh

│   ├── compleasm.sh

│   ├── README.md

│   ├── config

│   │   └── config.yaml

│   ├── envs

[...]

│   ├── makefiles

│   │   ├── BUSCO.smk

│   │   ├── CCS_DEEPCONSENSUS.smk

│   │   ├── DECONTAM.smk

│   │   ├── FINAL_ASM_STATS.smk

│   │   ├── FLYE.smk

│   │   ├── HIC.smk

│   │   ├── HIFIASM.smk

│   │   ├── MERQURY.smk

│   │   ├── PROCESS_HIC_READS.smk

│   │   ├── PURGEDUPS.smk

│   │   ├── STATS.smk

│   │   └── VISUALIZE.smk

│   └── snakefile.smk

├── 1.MAPPING_&_CONTACTS



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Scripts to map the final assembly to back to the HiC, HiFi and subreads to get quality statistics.

Mapping to the HiC also allows the creation of HiC contact maps in these scripts (pretext for curation, HiCExplorer for visualization)

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│   ├── 00b.Mapping_HiFi_HiC_ASMs_contactmaps.smk

│   ├── 05.SGE_mitomapping.sh

│   ├── HiCExplorer.sh # plot cooler file created with step 05.SGE_mitomapping.sh

│   └── pretext2asm_post_curation.sh

├── 3.EARLGREY

│   └── 02.SGE_annot_earlgrey.sh

├── 4.PROTEIN_ANNOT



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Scripts to do repeat and protein annotation of genome. Edited from previous publication

Repeat annotation part is replaced by EarlGrey.Protein annotation combines BRAKER and GALBA using TSEBRA to get the final gene annotation

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│   ├── BRAKER

│   │   ├── config

│   │   │   └── config.yaml

│   │   ├── SGE_annot.sh

│   │   └── workflow

│   │   ├── envs

[...]

│   │   ├── rules

│   │   │   ├── 01-repeat-masking.smk

│   │   │   ├── 02-rnaseq-mapping-hisat.smk

│   │   │   ├── 02-rnaseq-mapping.smk

│   │   │   ├── 03-braker-run.smk

│   │   │   └── 04-repeatlandscape.smk

│   │   ├── scripts

│   │   │   ├── fasta_split_1.pl

│   │   │   └── repeat_to_gff.pl

│   │   └── Snakefile.smk

│   ├── GALBA

│   │   └── run_galba.sh

│   └── TSEBRA

│   ├── edit_annotation_after_tsebra_braker.sh

│   └── tsebra.sh

├── 5.ORTHOFINDER



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Ortholog gene phylogeny and gain/loss analysis. Input is a folder with species proteomes where only the longest isoform has been retained. Output is an orthofinder and cafe5 output folder.

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│   └── orthofinder.sh

├── 6.MACRO_MICRO



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Macro- and micro-chromosome gene number analysis

After creating 1 file per chromosome we print the gene number and size statistics using agat.

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│   ├── extract_per_chrom_gene_stats.sh

│   └── plot_macromicro_stats.R

├── 7.PSMC



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PSMC analysis using the assembly and the HiFi reads.

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│   ├── 06.psmc.smk

│   ├── 06.SGE_psmc.sh





│   └── psmc_strura.R



├── 8.SNP_CALL



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SNP calling using assembled genome as reference and Illumina reads of passages. We also use do SNP calling using the HiFi reads

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│   ├── config

│   │   └── config.yaml

│   ├── envs





│   ├── gatk_vcf_analysis_FINAL.R



[...]

│   ├── makefiles

│   │   ├── 1.snp_calling_all.smk

│   │   ├── gatk.smk

│   │   ├── mapping.smk

│   │   ├── preprocess.smk

│   │   └── variant_recalibration.smk

│   └── SGE_READQC.sh

├── ROHS

│   ├── extract_bams.sh

│   ├── ExtractTheta.sh

│   ├── index_bams.sh

│   └── ROHan.sh

└── tree.tsv