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.

Code in almost all popular languages using Coding Ground. Edit, compile, execute and share your projects, 100% cloud.

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Address of the bookmark: http://www.tutorialspoint.com/codingground.htm

Key Findings:

1. Chromosomal Fusion and Its Molecular Signature:

   • The fusion site is located at 2q13–2q14.1 and is characterized by degenerate telomeric sequences appearing interstitially, indicating the historical head-to-head joining of ancestral chromosomes.
   • Despite being a signature of a past fusion event, these telomeric repeats are no longer functional and have undergone sequence degradation over time.

2. Extensive Duplications in the Surrounding Genomic Region:

   • The study identifies large-scale segmental duplications flanking the fusion site, with several of these regions duplicated and scattered across multiple chromosomes.
   • These duplications are predominantly located in subtelomeric and pericentromeric regions, suggesting their role in genomic instability and chromosomal evolution.

3. Paralogous Regions and Their Evolutionary Relationships:

   • A 168-kilobase (kb) segment near the fusion site has 98%–99% sequence identity with three regions on chromosome 9 (9pter, 9p11.2, and 9q13).
   • Another 67-kb region distal to the fusion site shows a high degree of homology to sequences in chromosome 22qter.
   • Additionally, a 100-kb segment exhibits 96% sequence identity with a region in chromosome 2q11.2.

4. Comparative Genomics and Evolutionary Implications:

   • By comparing the duplicated sequences and their arrangement in primates, the researchers traced the order of duplication events leading to their present distribution.
   • The presence of specific repetitive elements within these duplicated segments serves as evolutionary markers that help infer their historical rearrangements.
   • Some of these duplicated regions are associated with chromosomal inversion breakpoints, potentially contributing to evolutionary changes in primates.
   • Recurrent structural rearrangements in these regions have been linked to human chromosomal disorders.

Conclusions and Implications:

• The findings provide valuable insights into the structural evolution of human chromosome 2, which played a crucial role in human speciation.
• Understanding these segmental duplications and their evolutionary trajectories sheds light on genomic instability, which may contribute to human genetic diseases.
• The study highlights how large-scale chromosomal rearrangements, such as fusion and duplication, have influenced the evolutionary divergence of humans from other primates.

This research advances our understanding of human genome evolution and offers a foundation for studying the effects of structural variants in genetic disorders.

DEPARTMENT OF BIOTECHNOLOGY

No. NITW/Bio/ Date: 30th March 2015

ADVERTISEMENT FOR PROJECT FELLOW (Research Staff)

Applications are invited for the post of Project Fellow (Research Staff) for the project entitled ‘Metagenome derived nitroreductases for degradation of nitro compounds’ sponsored by the Department of Science and Technology (DST-INSPIRE), Govt. of India.

Position: Project Fellow (1 No.)

Project Duration: 5 years

Note: The post is purely on temporary basis for a period one year and may be extendable till the end of the project based on the progress of the candidate.

Emoluments: Rs. 14,000/- per month (Consolidated) for first two years and Rs. 16,000/- per month (Consolidated) for next three years.

Essential Qualifications:

i) First class in M.Tech/M.S (Biotechnology/Industrial Biotechnology/Bioinformatics) or equivalent. Or

ii) First class in M.Sc. (Biotechnology/Bioinformatics/Biochemistry/ Microbiology/Molecular biology).

Desirable Qualification: Preference will be given to candidates who have cleared NET/GATE or having prior work experience in Molecular biology/Bioinformatics sequence analysis.

Interested candidates may submit their application in plain paper along with Curriculum Vitae and photocopies of certificates in support of educational/professional qualifications. Application should be sent in a closed cover with a superscription on the cover “Application for the post of project fellow (DST-INSPIRE)” on or before 20.04.2015 (Monday) via Post to the Principal Investigator. Eligible candidates will be intimated through e-mail and called for interview at the Department of Biotechnology, NIT, Warangal. No TA/DA will be paid for attending the interview. Dr. K. Divakar (Principal Investigator) DST-INSPIRE Faculty Department of Biotechnology National Institute of Technology Warangal – 506 004. Telangana, India. E-mail: divakar@nitw.ac.in; kdivak@gmail.com

Advertisement: http://www.nitw.ac.in/nitw/announcements/2015/Notification_Project_Fellow_DST_INSPIRE_Biotechnology_NITW.pdf

You can also add your favourite NGS educational material, or workshop tutorial by commenting on this bookmarks for user benefit. 

Understanding the basics of genome sequencing:

Tutorial by Luke Jostins.

http://www.genetic-inference.co.uk/blog/2009/04/basics-sequencing-dna-part-1/

http://www.genetic-inference.co.uk/blog/2009/08/basics-sequencing-dna-part-2/

A window into third-generation sequencing

http://hmg.oxfordjournals.org/content/19/R2/R227.full.pdf

==============================================

NGS data analysis pipelines

• Detecting and annotating genetic variations using the HugeSeq pipeline  DOI: 10.1038/nbt.2134
• NARWHAL, a primary analysis pipeline for NGS data http://bioinformatics.oxfordjournals.org/cgi/content/abstract/28/2/284?etoc
• RseqFlow: Workflows for RNA-Seq data analysis  DOI: 10.1093/bioinformatics/btr441
• ngs_backbone: a pipeline for read cleaning, mapping and SNP calling using Next Generation Sequence  10.1186/1471-2164-12-285
• A framework for variation discovery and genotyping using next-generation DNA sequencing data  PubMed: 21478889
• SNiPlay: a web-based tool for detection, management and analysis of SNPs. Application to grapevine diversity projects  DOI: 10.1186/1471-2105-12-134 Abstract: http://www.biomedcentral.com/1471-2105/12/134/abstract
• WEP: a high-performance analysis pipeline for whole-exome data http://www.biomedcentral.com/1471-2105/14/S7/S11
• DDBJ read annotation pipeline: a cloud computing-based pipeline for high-throughput analysis of next-generation sequencing data. http://www.ncbi.nlm.nih.gov/pubmed/23657089
• GATK: a Toolkit for Genome Analysis http://www.broadinstitute.org/gatk/
• Metagenomics:http://www.nbic.nl/education/nbic-phd-school/course-schedule/ngsmetagenomics/
• RNASeq:http://www.nbic.nl/education/nbic-phd-school/course-schedule/ngsrnaseq/
• Bioinformatics and Seq courses: http://www.isb-sib.ch/training/training-activities-schedule/archive-2013.html
• Variant Detection (Model organism) Advanced tutorial https://docs.google.com/document/pub?id=1CuKkKylVDb03tnN7RSWl5EUzleetn0ctjmvaidPKLxM
• Variant Detection Introductory tutorial https://docs.google.com/document/pub?id=1ZRzrjjOCvtAu3m-IKL-rbJ1f4On60dDL_IEwG7oejdI
• Microbial de novo Assembly for Illumina Data Introductory tutorial https://docs.google.com/document/pub?id=1N3AB9ptISUu4zULqe1kXpVF0BDyGb5f5yzxWSJd_WNM
• RNAseq Differential Gene Expression Introductory tutorial https://docs.google.com/document/pub?id=1KbTiBHtvHLfPRZ39AY3uriazrINA8TJzgjjwn1zPP7Y

" Please add your favourite NGS link below in comment section for the benefit of bioinformatics community ". 

Address of the bookmark: http://chagall.med.cornell.edu/NGScourse/

The engagement is purely temporary on contractual basis and co-terminus with the project. There will be no provision of absorption of absorption/reemployment in IVRI/DBT on termination of the project.

No TA/DA will be provided for appearing in the interview and no separate letter will be issued.

A. Name tile of the project: “Centre for Agricultural bioinformatics (CABin)”.

B. Position/post to be filled: Research Associate (one)

C. Essential/Desirable qualifications:

•Essential: M.V.Sc./M.Tech./MSc Degree in Biotechnology/ Biochemistry/ Microbiology/Immunology/Bioinformatics/Genetics/Life Sciences or

Masters in Computer Application/ Masters in Computer science with first division.

• Desirable: Experience in cell culture, next generation sequencing, C++ and perl programming. NET/GATE qualified will be preferred.

• Experience : At least 2 years

D. Emoluments: Rs. 23000/- per month + 20% HRA

E. Age Limit: Maximum 40 years for men and 45 years for women

F. Duration of the project: Up to March 2017

G. Name of PI/Contact person: Dr. G.V.P.P.S. Ravi Kumar, Sr. Scientist, Division of Veterinary Biotechnology.

H. Address for correspondence: Dr. G.V.P.P.S. Ravi Kumar, Sr. Scientist, Computational Biology and Genomics facility,Division of Veterinary Biotechnology, I.V.R.I., Izatnagar – 243122

Advertisement: www.ivri.nic.in/jobs/WalkIn_interview_01042015.pdf

Address of the bookmark: http://www.nature.com/srep/2015/150707/srep11996/full/srep11996.html

1. “Development of bioinformatics methods for identifying novel secondary metabolites by genome mining” funded by DBT

JRF (P)/SRF (P) (One Position only)

Dr. Debasisa Mohanty Staff Scientist-VI deb@nii.res.in

Educational Qualifications: JRF (Project): M.Sc (Bioinformatics/ Biophysics/Biotechnology or any other stream of biological/physical sciences) or M.Tech. (Bioinformatics/Biotechnology/Computational Sciences) of M. Pharm.

SRF (Project): M.Sc (Bioinformatics/Biophysics/Biotechnology or any other stream of biological/physical sciences) or M.Tech. (Bioinformatics/Biotechnology/Computational Sciences) of M. Pharm with atleast 03 years of research experience.

Desirable Qualifications: Strong computer programming skills (in PERL/CGI/PHP or C++ or object oriented database management systems like MySQL etc or scripting languages under LINUX/UNIX environment) and sufficient experience in computational analysis of biological/biochemical data.

The candidates must highlight their experience in programming and database development in their CV. Job description: Computational analysis of genomes and development of bioinformatics tools and software’s for sequence and structure based analysis of biosynthetic pathways.

Emoluments: The selected candidates will draw consolidated emoluments as per Institute Rules, depending upon qualifications & experience JRF (Project): Rs. 12,000/- per month plus 30% HRA SRF (Project): Rs. 14,000/- per month plus 30% HRA (*Candidates possessing qualifications as per latest DST OM, will be given revised scales).

More at http://www1.nii.res.in/sites/default/files/projectappointments-Dr.DebasisaMohanty-30April2015.pdf

Address of the bookmark: https://github.com/vice87/gam-ngs

IGIB Vacancy Details:
Total No. of Posts: 04
Name of the Posts:
1. Project Scientist (Biology): 02 Posts
2. Project Scientist (Bioinformatics): 01 Post
3. Sr Project Fellow (Ayurveda): 01 Post

Age Limit: Candidates age should be 35 years for post 1, 32 years for post 2

Educational Qualification: Candidates should have Ph.D/ Ph.D submitted in any branch of Biological Science/ Life Science for post 1, Ph.D/ Ph.D submitted in Bioinformatics for post 2, BAMS degree with one year internship for post 3.

Selection Process: Candidates will be selected based on their performance in interview.

How to Apply: Eligible candidates may send their application along with all relevant documents on or before 23-04-2015.

Important Dates:
Last Date for Receipt of Application for Post 1 & 2: 23-04-2015.
Date of Interview for Post 3: 27-04-2015.

For other details like pay scale, age relaxation, educational qualification, selection process, how to apply, etc., click on the link given below…

http://www.freejobalert.com/wp-content/uploads/2015/03/Notification-IGIB-Project-Scientist-SPF-Posts.pdf

http://www.igib.res.in/sites/default/files/27042015.pdf