Address of the bookmark: https://github.com/Reedwarbler/GAPPadder

Protocol Overview / Introduction

In this protocol we discuss and outline the process of de novo assembly for small to medium sized genomes.

https://www.melbournebioinformatics.org.au/tutorials/tutorials/assembly/assembly-protocol/

Address of the bookmark: https://www.melbournebioinformatics.org.au/tutorials/tutorials/assembly/assembly-protocol/

More at https://ucdavis-bioinformatics-training.github.io/

Address of the bookmark: https://ucdavis-bioinformatics-training.github.io/2020-Genome_Assembly_Workshop/snakemake/snakemake_intro

Effective July 10, 2023, NCBI’s Assembly and Genome record pages now redirect to new NCBI Datasets pages. As previously announced, these updates are part of our ongoing effort to modernize and improve your user experience. NCBI Datasets is a new resource that makes it easier to find and download genome data.   

The following pages have been updated:

• The NCBI Assembly record pages now redirect to the new NCBI Datasets Genome record pages that describe assembled genomes and provide links to related NCBI tools such as Genome Data Viewer and BLAST.  
• The NCBI Genome record pages now redirect to the NCBI Datasets Taxonomy record pages that provide a taxonomy-focused portal to genes, genomes, and additional NCBI resources.   

During this transition, you will have the option to return to the legacy Genome and Assembly record pages. We will remove the legacy pages in early 2024.  

What is Genome Assembly?

Genome assembly involves piecing together short DNA sequence reads generated by sequencing platforms (e.g., Illumina, PacBio, Oxford Nanopore) into longer, contiguous sequences called contigs. This can be performed as:

• De Novo Assembly: Without a reference genome.
• Reference-Guided Assembly: Using a reference genome to guide the assembly process.

Step 1: Preparing Your Data

Before starting the assembly, ensure that your raw sequencing data is high quality.

1. Input Data

   • Short Reads: Illumina sequencing generates short, accurate reads ideal for scaffolding.
   • Long Reads: PacBio and Nanopore sequencing provide long reads for resolving repetitive regions.

2. Quality Control (QC)
   Use tools like FastQC or MultiQC to assess the quality of your reads:

   fastqc reads.fastq multiqc .

   Look for issues like low-quality bases, adapter contamination, or overrepresented sequences.

3. Read Trimming and Filtering
   Trim low-quality bases and adapters using Trimmomatic or Cutadapt:

   trimmomatic PE reads_R1.fastq reads_R2.fastq trimmed_R1.fastq trimmed_R2.fastq \ ILLUMINACLIP:adapters.fa:2:30:10 LEADING:3 TRAILING:3 SLIDINGWINDOW:4:20 MINLEN:36

Step 2: Choosing an Assembly Strategy

Select an assembly strategy based on your data type:

• Short-Read Assemblers:

  • SPAdes: Popular for microbial genomes.
  • Velvet: Fast for smaller genomes.

• Long-Read Assemblers:

  • Canu: Ideal for long-read datasets.
  • Flye: Versatile for small and large genomes.

• Hybrid Assemblers:

  • MaSuRCA: Combines short and long reads.
  • Unicycler: Optimized for bacterial genomes.

Step 3: Running the Assembly

3.1. SPAdes (Short-Read Assembly)

SPAdes is an excellent choice for small genomes, such as bacteria.

The output includes assembled contigs (contigs.fasta) and scaffolds (scaffolds.fasta).

3.2. Canu (Long-Read Assembly)

Canu is designed for high-error long reads from PacBio or Nanopore.

The output will be in canu_output/genome.contigs.fasta.

3.3. Hybrid Assembly with Unicycler

Unicycler combines short and long reads for improved assemblies.

Step 4: Assessing Assembly Quality

After assembly, evaluate its quality using the following tools:

1. QUAST
   QUAST generates assembly statistics, such as N50, genome size, and GC content:

   quast contigs.fasta -o quast_output

2. BUSCO
   BUSCO checks genome completeness by identifying conserved genes:

   busco -i contigs.fasta -o busco_output -l fungi_odb10 -m genome

3. Assembly Graph Visualization
   Visualize assembly graphs with Bandage:

   Bandage load assembly_graph.gfa

Step 5: Post-Assembly Steps

1. Polishing
   Improve assembly accuracy using tools like Pilon (for short reads) or Racon (for long reads).

   racon long_reads.fasta mapped_reads.sam contigs.fasta > polished_contigs.fasta

2. Scaffolding
   Link contigs into scaffolds using tools like SSPACE or Opera-LG if required.

3. Annotation
   Annotate the assembled genome using Prokka for prokaryotes or Maker for eukaryotes.

   prokka --outdir annotation_output --prefix genome contigs.fasta

Step 6: Sharing and Archiving

1. Submit to Public Repositories
   Share your assembly in databases like NCBI GenBank, ENA, or DDBJ.

2. Metadata Preparation
   Include detailed metadata for your submission, such as organism name, sequencing platform, and coverage.

Best Practices

• Always perform quality checks at each stage to ensure data integrity.
• Use multiple tools to cross-validate results when working with complex genomes.
• Document parameters and software versions for reproducibility.

Conclusion

Genome assembly is a powerful process that transforms raw sequencing data into a coherent representation of an organism’s genome. By following this step-by-step guide, you can successfully assemble genomes and uncover valuable biological insights. Whether you’re assembling a microbial genome or tackling the complexities of a eukaryotic genome, these tools and strategies will set you on the path to success.

The software is implemented in Python 3 and runs in both Python 2.7 and 3.4– on Macintosh and Linux systems. It is freely available at https://github.com/nigyta/dfast_core/ under the GPLv3 license with external binaries bundled in the software distribution. An on-line version is also available at https://dfast.nig.ac.jp/.

Address of the bookmark: https://dfast.nig.ac.jp/

I'm running "OPERA-LG_v2.0.5/bin/preprocess_reads.pl" and have the following error:

fail to open file './temporarySam'

[bwa_aln_core] write to the disk... 0.09 sec
[bwa_aln_core] 70778880 sequences have been processed.
[bwa_aln_core] calculate SA coordinate... 161.35 sec
[bwa_aln_core] write to the disk... 0.06 sec
[bwa_aln_core] 70989574 sequences have been processed.
[main] Version: 0.7.15-r1140
[main] CMD: bwa aln -t 30 all_p_ctg.fa -
[main] Real time: 2402.523 sec; CPU: 53429.488 sec
[E::hts_open_format] Failed to open file temporarySam
samtools sort: can't open "temporarySam": No such file or directory
[bwa_aln_core] convert to sequence coordinate... 1.00 sec
[bwa_aln_core] refine gapped alignments... 6.07 sec
[bwa_aln_core] print alignments... PREPROCESS:
Fastq format is recognized
[Thu Jun 14 18:16:47 2018] Building bwa index...
bwa index -p all_p_ctg.fa /home/urbe/Tools/OPERA-LG_v2.0.6/all_p_ctg.fa
[Thu Jun 14 18:18:35 2018] Finding the SA coordinates of the reads using BWA aln...
[Thu Jun 14 18:58:37 2018] Generate alignments of reads using bwa sampe...
bwa samse -n 1 all_p_ctg.fa read.sai - | grep '\(^@\|XT:A:U\)' | /usr/local/bin/samtools view -S -h -b -F 0x4 - | /usr/local/bin/samtools sort -@ 20 -no - temporarySam > FALCON-Unzip-Scaff.bam
Mapping long-reads using blasr...
/home/urbe/Tools/SSpace/SSPACE-LongRead_v1-1/blasr -nproc 40 -m 1 -minMatch 5 -bestn 10 -noSplitSubreads -advanceExactMatches 1 -nCandidates 1 -maxAnchorsPerPosition 1 -sdpTupleSize 7 /media/urbe/MyDDrive/ONTdata/allONT/allONT.fasta /home/urbe/Tools/OPERA-LG_v2.0.6/all_p_ctg.fa | cut -d ' ' -f1-5,7-12 | sed 's/ /\t/g' > FALCON-Unzip-Scaff.map
sh: 1: /home/urbe/Tools/SSpace/SSPACE-LongRead_v1-1/blasr: Permission denied
Sorting mapping results...
sort -k1,1 -k9,9g FALCON-Unzip-Scaff.map > FALCON-Unzip-Scaff.map.sort
Analyzing sorted results...
Extracting linking information...
i3 2000 5000
i2 1000 2000
i4 5000 15000
i0 -200 300
i5 15000 40000
i1 300 1000
Repeat detection...
/home/urbe/Tools/OPERA-LG_v2.0.6/bin//filter_conflicting_edge.pl pairedEdges_i0 contig_length.dat 100 2
Illegal division by zero at /home/urbe/Tools/OPERA-LG_v2.0.6/bin//filter_conflicting_edge.pl line 93.
readline() on closed filehandle FILE at bin/OPERA-long-read.pl line 250.
rm anchor_contig_info.dat contig_length.dat filtered_edges.dat filtered_edges_cov.dat *.sai
rm: cannot remove 'anchor_contig_info.dat': No such file or directory
mv FALCON-Unzip-Scaff.bam FALCON-Unzip-Scaff-with-repeat.bam
/home/urbe/Tools/OPERA-LG_v2.0.6/bin//filter_repeat.pl FALCON-Unzip-Scaff-with-repeat.bam repeat.dat | /usr/local/bin/samtools view - -h -S -b > FALCON-Unzip-Scaff.bam
rm FALCON-Unzip-Scaff-with-repeat.bam
/home/urbe/Tools/OPERA-LG_v2.0.6/bin/OPERA-LG config > log
Analyzing 1 library: FALCON-Unzip-Scaff.bam
min library mean : 0
minimum contig length is 500
Current library: 1 out of 7
Analyzing file: pairedEdges_no_repeat_i0
Analyzing file: pairedEdges_no_repeat_i1
Analyzing file: pairedEdges_no_repeat_i2
Analyzing file: pairedEdges_no_repeat_i3
Analyzing file: pairedEdges_no_repeat_i4
Analyzing file: pairedEdges_no_repeat_i5
ln -s results/scaffoldSeq.fasta scaffoldSeq.fasta

To resolve this, try downloading blasr version 1.3 above and re-run :)

An algorithmically novel approach to construct a genome graph representation of long-read-based de novo sequence assemblies. We then provide a proof of principle by creating a genome graph of seven ethnically-diverse human genomes.

https://f1000research.com/articles/7-1391/v1

Address of the bookmark: https://github.com/NCBI-Hackathons/NovoGraph

• Draft assembly fasta file
• Interleaved linked reads file (Barcode sequence expected in the BX tag of the read header or in the form "@readname_barcode" ; Run Long Ranger basic on raw chromium reads to produce this interleaved file)

Address of the bookmark: https://github.com/bcgsc/ARCS/