Address of the bookmark: https://github.com/legumeinfo/gcv

#Find the reverse complement of a DNA string.
#Given: A DNA string Pattern.
#Return: Pattern, the reverse complement of Pattern.

use strict;
use warnings;

my $string="AAAACCCGGT";
my $finalString="";
my %hash = (
    "C" => "G",
    "A" => "T",
    "T" => "A",
    "G" => "C",
);

for (my $aa=0; $aa<=(length($string)-1); $aa++) {
    my $char=substr $string, $aa, 1;
    #print $hash{$char};
    $finalString="$hash{$char}"."$finalString";
}

print $finalString;
print "\n";

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/

Monthly fellowship (in rupee): 5,000/-

Traineeship

First Class M.Sc Bioinformatics/ Biotechnology/ Botany

Studentship: 5,000/-

M.Phil/M.Tech Bioinformatics/ Biotechnology/ any branch of Life Science students for doing their thesis work in the area of Bioinformatics.

Age limit as on 1.1.2015, 28 years. Age relaxation will be provided for SC, ST, OBC candidates as per Govt. norms.

Interested candidates may appear for walk-in-interview on 16th June 2015 at 10.30 am at JNTBGRI, Palode, Thiruvananthapuram. The candidate should report to the Office at Palode before 10.00 am

More at http://www.jntbgri.in/jntbgri/news/File0001.pdf

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.

Sr Research Fellow & Technical Asst Posts: Indian Institute of Maize Research (IIMR), New Delhi has advertised a notification for the recruitment of Senior Research Fellow & Technical Assistant vacancies for the project titled “Genetic modifications to improve biological nitrogen fixation for augmenting nitrogen needs of cereals” on contractual basis. Eligible candidates may apply in prescribed application format on or before 25-06-2015. Other details like age, educational qualification, selection process, how to apply are given below…

Indian Institute of Maize Research Vacancy Details:
Total No. of Posts: 03
Name of the Posts :
1. Senior Research Fellow: 02 Posts
2. Technical Assistant: 01 Post

Age Limit: Candidates age should be 35 years for Senior Research Fellow, Minimum 21 years and maximum 45 years for Technical Assistant as on the closing date of the application. Age relaxation is 5 years to SC/ST and women candidates and 3 years to OBC candidates as per ICAR rules.

Educational Qualification: Candidates should possess Post graduate degree in Biotechnology/ Molecular Biology/ Bioinformatics/ Plant physiology for Senior Research fellow, Graduate degree in Agriculture/ Biotechnology/ any discipline of life sciences for Technical Assistant with relevant experience.

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

How to Apply: Eligible candidates can send their application in prescribed format along with bio-data to Dr. Pranjal Yadava, Principal Investigator, ICAR Indian Institute of Maize Research, Pusa Campus, New Delhi-110012 or mail to pranjal.yadava@gmail.com on or before 25-06-2015 & attend the interview along with application in the attached format at the time of interview, one passport size photograph, self attested copies of certificates for age, and qualifications, reprints of publications and ‘No Objection Certificate’, original documents on 01-07-2015. Venue details are mentioned below.

Important Dates:
Last Date for Receipt of Application: 25-06-2015
Date & Time of Interview : 01-07-2015.
Venue: IIMR, Pusa Campus, New Delhi

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

Eligibility : BE/B.Tech(CSE, ECE, IT)

Location : Pondicherry

Last Date : 26 Jun 2015

Hiring Process : Face to Face Interview
Pondicherry University - Job DetailsDate of posting:19 May 15

Senior Technical Assistant Job position in Pondicherry University on temporary basis

Project Title : "Bioinformatics National Certification (BINC) for certifying quality human resource in Bioinformatics"

Qualification : i) B.E/ B.Tech Computer Science/ Electronics & Communication Engineering/ Information Technology with 55% or equivalent marks. ii) One year Experience in relevant field in Government/ Public Sector or reputed Private Organizations. Desirable : Working experience in JSP and ASP/PHP

No. of Post : 01

Department : Biotechnology

Pay : Rs. 27,800/-

Age Limit : 30 Yrs
How to apply

Both above-mentioned posts are purely on temporary basis, extended by one year based on performance and will be terminated with the completion of BINC Program at Pondicherry University. Interested Candidates may send their application in the prescribed format with self-attested copies of all mark sheets and certificates to Dr. Basant K. Tiwary, Coordinator (BINC), Centre for Bioinformatics, Pondicherry University, Puducherry-605 014 before June 26, 2015.

Click Here http://www.pondiuni.edu.in/news/requirement-post-one-senior-technical-assistant-one-computer-assistant-–-dept-biotechnologygove

“It’s like a subway map,” she said, “but for DNA.”

That idea is exactly what Sequence Tube Map brings to life.

Instead of showing a genome as one long, confusing sequence, it displays different genomic paths like routes on a metro map. Where sequences are shared, the paths travel together. Where genetic variation occurs, they branch into different routes and may join again later.

This makes complex genome graphs much easier to explore.

Maya could now see how different haplotypes moved through the same genomic region and where they took different paths. She could even view sequencing reads mapped onto the graph, helping her understand what was happening in regions with genetic variation.

What once looked like a tangled network now looked like a journey.

Sequence Tube Map turns the complexity of graph genomes into a visual story—making it easier for scientists to see how DNA can take different routes.

Read more at  https://github.com/vgteam/sequencetubemap 

and

https://academic.oup.com/bioinformatics/article/35/24/5318/5542397

Demo at https://vgteam.github.io/sequenceTubeMap/