01. Scientist II 01
Essential: Ph.D. degree in Life Sciences from a recognized university along with a minimum of 2 years of research experience in Bioinformatics as evidenced by publications in the peer reviewed journals.

OR
Ph.D. degree in Bioinformatics from a recognized university.

OR
M.Sc. in Bioinformatics from a recognized university along with a minimum of 3 years of research experience in Bioinformatics as evidenced by publications in the peer reviewed journals.

Desirable:
Thorough Knowledge about In silico genome analysis and comparative genomics.
Experience with in silico identification of novel virulence factors of pathogens, host-pathogen interactions and Systems Biology.
Additional Postdoctoral research experience in relevant subjects from a recognized institutions.

Rs. 44,000/- p.m. (consolidated) plus 30% HRA

Below 40 years

Applications along with Bio-Data containing detail work experience and full list of publications may be sent via email tosantasabujdas@yahoo.com latest by October 27, 2014.

Short-listed candidates will be called via email for an interview to be held at the institute in the second week of November, 2014.

Advertisement: www.niced.org.in/placements.htm

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.

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.

Good communication skills and fluency in spoken and written English are required.
Please apply sending a curriculum vitae, the names of at least two referees and a letter of motivation describing past experience and future goals to anna.tramontano@uniroma1.it with subject: “Application for post-doctoral position November 2014 YOUR LAST NAME”

Deadline: No later than November 28th, 2014.
Duration: 2 years

Salary on grant: Commeasured to the experience of the candidate
Contact Person (Referent): Anna Tramontano
Ref. E-Mail: anna.tramontano@uniroma1.it
Group Web Page: http:/www.biocomputing.it

Is this available, or still under trial mode? 

https://www.nanoporetech.com/

https://www.nanoporetech.com/technology/the-minion-device-a-miniaturised-sensing-system/the-minion-device-a-miniaturised-sensing-system

Essential Qualification
For Research Fellow:-
M.Sc. in Systems Biology and Bioinformatics / Life
Sciences with minimum 55% marks.
Preference will be given to NET/GATE/ICMR qualified candidates without fellowship however, candidates who have cleared the Panjab University Ph.D. entrance test in Systems Biology & Bioinformatics will also be eligible.

Applications should be reach on or before 19-11-2014 in the office of the undersigned. Interview will be held on 21-11-2014 in the office of the Coordinator, Centre for Systems Biology & Bioinformatics, South Campus, Block-3, Sector-25, Panjab University, Chandigarh. No TA/DA will be paid.

more at http://jobs.puchd.ac.in/includes/jobs/2014/20141110143634-Advertisement.pdf

Our main advantages over other similar tools are:

• GeneAnalytics is very simple and intuitive to use.
• GeneAnalytics is based on our proprietary databases – GeneCards, MalaCards, PathCards and LifeMap Discovery, each of them integrates information from a very large number of resources.
• GeneAnalytics supplies links for extensive background information on each of the matched results.

I invite you to try it out for free at geneanalytics.genecards.org, and would be happy to hear your comments and thoughts on how we can improve.

Yours,

Shani Ben-Ari Fuchs

LifeMap Sciences Team

Candidates having the below mentioned qualifications may appear for walk in interview at ICPO on 2nd December 2014 between 10.00 AM and 12:00 PM under the below time bound projects under Dr. Subhash M. Agarwal, Scientist C. The post is purely temporary and co-terminus with the project.

Research Assistant (One)
25650/- consolidated
Discovery of EGFR secondary mutant inhibitors using structure based screening approach (ICMR)
Duration: 7 months

Essential: M.Sc./ M.Tech in Bioinformatics or any other related subject with good academic record.

Desirable: Experience in scripting and molecular docking.

Below 30 years

Junior Research Fellow (One)

16,000 + 30% HRA = Rs. 20800/-

Identification of novel inhibitors targeting EGFR using an integrated ligand and structure based approach (DBT)

Duration: 9 months

Essential: M.Sc./ M.Tech in Bioinformatics or any other related subject with good academic record. Candidates with CSIR-UGC / ICMR, NET qualification will be preferred

Desirable: Experience in scripting, QSAR and molecular docking.

Below 28 years

Interested eligible candidates may send their applications with Bio-data by email at (smagarwal@gmail.com) or by post addressed to Dr. Subhash M Agarwal, Scientist C, Institute of Cytology and Preventive Oncology (ICPO) I-7, Sector-39, Noida-201301 so as to reach latest by 1st December, 2014. The candidates may appear for interview at ICPO along with 3 copies of CV, photo and relevant certificates of qualifications in original and reprints of publications at the time of interview. It should be noted that No TA/DA will be paid for the walk in Interview.

Advertisement: www.icpo.org.in/advt-walk-in-interview.docx

Address of the bookmark: https://bernatgel.github.io/karyoploter_tutorial/