Features

• Circular and linear views of genomes

• Capable of drawing genomes up to 10 Mbp with 1000's of features and 100's contigs

• Smooth zooming down to the sequence level

• Easily generate features and plots directly form the sequence (e.g. ORFs, GC-content and GC-Skew)

• Save high resolution PNG maps up to 8000x8000px

• Fully documented API for interacting with CGView.js maps

Address of the bookmark: https://js.cgview.ca/

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.

Human genetic variation
Inference of human evolutionary history from genetic markers
Statistical analysis of population-genetic data
Mathematical models of gene genealogies
Theoretical population genetics
Combinatorics of evolutionary trees
The relationship between gene trees and species trees
The role of human evolutionary genetics in the search for genes that contribute to disease-susceptibility
More at https://web.stanford.edu/group/rosenberglab/index.html

We have developed panHiTE, a comprehensive and accurate pipeline for TE detection in large-scale population genomes. It has been successfully applied to hundreds of plant population genomes, demonstrating its effectiveness and scalability.

For detailed instructions, please refer to the panHiTE tutorial.

Address of the bookmark: https://github.com/CSU-KangHu/HiTE

Address of the bookmark: http://sysomics.com/deephic

Desirable : Research or teaching experience in Bioinformatics and Computational Biology.
Honorarium : Rs. 1,000/- per lecture (subject to a maximum of 25,000/- per month)
How to apply

Interested eligible candidates may attend the 'walk-in' interview along with all original certificates and testimonials with a copy of their bio-data. Walk-in-interview will be held on 28.09.2015 (Monday), 03:00 P.M. at the office of the Dean, School of Life Sciences, Science Block — I, Pondicherry University, Puducherry — 605 014. Candidates reporting after 03:00 P.M. will not be entertained.

More at http://www.pondiuni.edu.in/news/walk-interview-guest-faculty-centre-bioinformatics

Location where with post of Research Associate / Senior Research Fellow is available:
Bioinformatics Centre, Bose Institute in Kolkata, West Bengal

Title of the Project: "Setting up of National Facility on Interactive Graphics Computer System".

No. of the Post: 01 One

Salary: Rs. 22000/- per month plus admissible HRA and Medical Benefits for RA and Rs. 20000/- per month plus admissible HRA and Medical Benefits for SRF (Extended).

Age Limit: Max. 35 years for RA and Max. 33 years for SRF (Extended)

Required Job Profile:

Candidate must possess PhD degree in biological or chemical sciences with in depth understanding of protein structure and function; experience on protein crystallization and various modeling software will be advantages and candidate who have submitted PhD thesis can be considered as extended SRF.

The project would involve cloning, expression, crustallization of vibrio cholera toxin, Ace and modeling of its admissible HRA and medical benefits for SRF (Extended).

How to apply:

Eligible and interested candidates should need to appear before the selection committee along with typed application addressed to the above mentioned address along with biodata with complete details and attested copies of certificates on 02.03.2016 at 11:30 am. No TA or DA will be paid for attending the interview. No TA or DA will be paid for attending the interview.

Refer to http://www.boseinst.ernet.in/ADVT/15/p_30.pdf

Bioinformatics Trainee Job position in University of Kalyani
Number of Posts : 02
Qualification : M.Sc. in any branch of life science with prior knowledge of Bioinformatics
Fellowship / Stipend / Salary : As per DBT rules
Duration of the Post : Six months starting from January, 2016
How to apply
Walk-in-interview will be held on 28.12.2015 at Department of Biochemistry and Biophysics, University of Kalyani.

More at http://www.klyuniv.ac.in/index.php/recruitments

http://www.chekulaevalab.org/

No. of Post : 01

Department : Science and Technology

Qualifications : Ph.D. with specialization in Bioinformatics/Machine Learning/ Mathematical Biology/ Computational Biology/ Systems Biology with a minimum of 55% marks in M. Sc. (50% for candidates belongs to reserved category) or equivalent grade. Candidates who have submitted their Ph.D. thesis and are waiting for award of Ph.D. are also eligible. OR M. Sc. Bioinformatics with two years of research experience in the areas mentioned above, a minimum of 55% marks in M.Sc. (50% for candidates belongs to reserved categories) or equivalent grade and at least one publication in Science Citation Index (SCI) journal. Preference will be given to B.I.N.C. /J.R.F. /N.E.T. /S.E.T. qualified candidates.

Emoluments : Rs. 20,000/- (Including H.R.A.) per month.
How to apply

The complete application along with necessary documents and certificates should reach to 'The Director, Bioinformatics Centre, Savitribai Phule Pune University (Formerly University of Pune), Caneshkhind Road. Pune - 411 007 on or before 21st March, 2016 within official hours except Sundays (i.e. 10.20 am to 06.00 pm).

More at http://collegecirculars.unipune.ac.in/sites/documents/Job%20Openings/Forms/AllItems.aspx