The job description: "This research position focuses on the science
of bacterial evolution. It will consist of researching theoretical
principles, but could include translational applications. Phylogenomic
and bioinformatic analysis of bacterial populations in nature or
in laboratory experiments will be a key component of the work. Prior
experience is an asset though training will be possible at PMI.
Likewise, laboratory microbiological, molecular, and biochemical
skills are an asset though not essential. Communication and critical
thinking skills are essential for performing the work and for
communicating to the local and international scientific communities.
Participating in team or independent grant writing to obtain research
funding will be required. Student mentoring is a part of the NAU
mission and is a partial expectation."

https://hr.peoplesoft.nau.edu/psp/ph92prta/EMPLOYEE/HRMS/c/HRS_HRAM.HRS_APP_SCHJOB.GBL?Page=HRS_APP_JBPST&Action=U&FOCUS=Applicant&SiteId=1&JobOpeningId=608024&PostingSeq=1

Northern Arizona University is located in Flagstaff, Arizona, a
beautiful mountain town with a surprisingly vibrant restaurant
scene. Located a little over an hour from the Grand Canyon and ~45
min from Sedona, Flagstaff is a hiker's paradise. In fact, the city
of Flagstaff operates more than 50 miles of unpaved trails and there
are, on average, 266 sunny days per year with which to enjoy them.
At 7000 ft in elevation, Flagstaff experiences all four seasons,
but thesummers are mild and, in the winter, you can be on the ski
slopes within 30 min! https://www.flagstaffarizona.org/

As mentioned, joint projects with Professor Sheppard at Oxford
University are possible, including travel to his laboratory in the
United Kingdom. https://www.biology.ox.ac.uk/people/samuel-sheppard

Contact Information:
Paul.Keim@nau.edu

Paul S. Keim, Ph.D.
Regents Professor, &
Cowden Endowed Chair of Microbiology
Northern Arizona University
Flagstaff, AZ 86011-4073

Paul S Keim

What is Bacterial Comparative Genomics?

Comparative genomics involves the systematic comparison of genomes across different bacterial species or strains. This approach allows scientists to:

• Identify conserved and unique genes.

• Explore genetic determinants of pathogenicity.

• Understand bacterial evolution and phylogenetics.

• Investigate horizontal gene transfer and its role in antibiotic resistance.

Bioinformatics is central to these analyses, enabling the processing and interpretation of large-scale genomic data.

Key Steps in Bacterial Comparative Genomics

1. Genome Sequencing and Assembly: The process begins with obtaining high-quality bacterial genome sequences. Advances in next-generation sequencing (NGS) technologies have made it faster and more affordable to sequence bacterial genomes. Tools such as SPAdes and Velvet are commonly used for genome assembly.

2. Genome Annotation: Annotating a genome involves identifying genes, regulatory elements, and other genomic features. Automated tools like Prokka and RAST provide functional annotations, allowing researchers to predict the roles of genes and proteins.

3. Genome Alignment: Aligning genomes is crucial for identifying conserved regions, single-nucleotide polymorphisms (SNPs), and structural variations. Tools like Mauve and progressiveMauve are commonly employed for whole-genome alignments.

4. Comparative Analyses:

   • Core and Pan-genome Analysis: The core genome consists of genes shared across all strains of a species, while the pan-genome includes all genes found in any strain. Software like Roary and BPGA can perform core and pan-genome analyses.

   • Phylogenetic Analysis: Comparative genomics often involves reconstructing evolutionary relationships. Tools such as MEGA and IQ-TREE facilitate phylogenetic tree construction based on genomic data.

   • Functional Enrichment Analysis: To understand the biological significance of unique or shared genes, functional enrichment analysis using databases like GO (Gene Ontology) and KEGG is essential.

Here are some additional bioinformatics tools that can aid bacterial comparative genomics:

• OrthoFinder: For accurate ortholog identification across multiple genomes.

• PanOCT: Specifically designed for pan-genome clustering and annotation.

• FASTANI: A tool for calculating Average Nucleotide Identity (ANI) for microbial genome comparisons.

• CIRCOS: For visually comparing genomic data through circular genome plots.

• Galaxy Platform: A user-friendly web-based platform offering numerous genomic analysis tools.

• BLAST: Essential for sequence alignment and similarity searches.

• PhyloSift: Focused on phylogenetic analysis of microbial genomes using marker genes.

These tools, in combination with the methods discussed, provide a robust framework for conducting comprehensive comparative genomic studies.

Applications of Bacterial Comparative Genomics

1. Understanding Pathogenicity: Comparative genomics helps identify virulence factors that distinguish pathogenic strains from non-pathogenic relatives. For instance, comparing genomes of Escherichia coli strains has revealed key genetic determinants of pathogenicity in enterohemorrhagic strains.

2. Antibiotic Resistance Research: The spread of antibiotic resistance genes through horizontal gene transfer is a major global concern. Comparative analyses can trace the origins and dissemination of resistance genes, aiding in the development of countermeasures.

3. Microbial Ecology and Evolution: By studying genomic variations, researchers can understand how bacteria adapt to different environments. This is particularly relevant for extremophiles and symbiotic bacteria.

4. Vaccine Development: Identifying conserved antigens across pathogenic strains is critical for vaccine design. Comparative genomics has been instrumental in developing vaccines against pathogens like Neisseria meningitidis.

5. Biotechnology Applications: Comparative studies can uncover unique metabolic pathways in bacteria, paving the way for applications in bioremediation, synthetic biology, and industrial microbiology.

Challenges in Bacterial Comparative Genomics

While the field has made significant strides, several challenges remain:

• Data Overload: The rapid growth of sequencing data requires robust computational infrastructure and efficient algorithms.

• Genome Plasticity: High rates of horizontal gene transfer and genome rearrangements in bacteria complicate comparative analyses.

• Annotation Accuracy: Automated annotation tools are not infallible, and manual curation is often needed for high-confidence results.

• Interpreting Non-Coding Regions: Understanding the functional significance of non-coding genomic regions remains a challenge.

Future Directions

The integration of bacterial comparative genomics with other ‘omics’ approaches—such as transcriptomics, proteomics, and metabolomics—promises a more comprehensive understanding of bacterial biology. Additionally, advancements in machine learning and artificial intelligence are likely to further enhance bioinformatics analyses, enabling the prediction of complex phenotypes from genomic data.

Conclusion

Bacterial comparative genomics, driven by bioinformatics, continues to unravel the complexities of bacterial life. From combating antibiotic resistance to uncovering the secrets of microbial evolution, this interdisciplinary field holds immense potential for addressing pressing challenges in microbiology and beyond. As technology advances, so too will our ability to harness the power of comparative genomics for scientific and societal benefit.

A walk-in-interview will be held on 15.7.2013 at 12 noon in the Department of Biophysics, Molecular Biology and Bioinformatics, 92 A.P.C Road, Kolkata-700 009 to select one trainee research fellow and two students under DIC. The positions are purely temporary and would be for a period of six months from the date of joining which may be extended by another six months subject to successful performance.

Qualification:

For the Trainee Research Fellow: Should have a master degree in Bioinformatics or allied subjects and should have biological database development experience. Must have at least one publication.

For the Students: Should have a master degree in Bioinformatics or allied subjects and should be proficient in C-programming language. Must be familiar with techniques of Developmental Biology.

The Trainee Research Fellow would be paid a consolidated sum of Rs 10000/- per month and the students would be paid a sum amount Rs. 7000/- per month during the tenure of the project.

Advertisement:
www.caluniv.ac.in/News%20&%20Announcement/trainee_rf_DIC.pdf

What Are piRNAs?

piRNAs are the largest class of small non-coding RNAs, typically 24–32 nucleotides in length. Unlike microRNAs (miRNAs) and small interfering RNAs (siRNAs), piRNAs do not rely on Dicer enzymes for maturation. Instead, they are processed from long single-stranded precursors and associate with PIWI proteins, a subclass of the Argonaute protein family.

The primary functions of piRNAs include:

1. Silencing Transposable Elements: By targeting transposons, piRNAs prevent genomic instability, particularly in germline cells.
2. Regulating Gene Expression: piRNAs modulate gene expression at transcriptional and post-transcriptional levels.
3. Epigenetic Modulation: They guide epigenetic modifications, such as DNA methylation, to specific genomic loci.

Challenges in piRNA Research

Studying piRNAs is fraught with challenges, including:

• Short Length: Their small size complicates sequencing and alignment.
• Lack of Sequence Conservation: Unlike miRNAs, piRNAs exhibit limited sequence conservation across species.
• Complex Biogenesis: The intricate pathways of piRNA generation require sophisticated computational tools to unravel.

Bioinformatics: Illuminating the World of piRNAs

Bioinformatics has emerged as an indispensable tool for studying piRNAs, facilitating their discovery, annotation, and functional analysis. Here's how bioinformatics is transforming piRNA research:

1. Identification and Annotation

The discovery of piRNAs relies on next-generation sequencing (NGS) data. Bioinformatics tools such as piRNApredictor and Piano identify piRNA clusters and predict potential targets. Databases like piRBase and piRNAdb curate information about known piRNAs, their sequences, and associated proteins.

2. Mapping and Alignment

piRNAs often originate from repetitive regions, making their alignment challenging. Tools like Bowtie and STAR handle the unique mapping requirements of piRNAs, enabling accurate identification of piRNA clusters in genomes.

3. Functional Analysis

Bioinformatics approaches predict piRNA functions by analyzing their interactions with transposons, genes, and epigenetic marks. Algorithms such as TargetFinder and RIblast explore piRNA-mRNA interactions, shedding light on regulatory networks.

4. Evolutionary Studies

piRNAs are evolutionarily diverse, reflecting their roles in species-specific genomic defense. Comparative genomics tools help trace the evolution of piRNA clusters and their associated PIWI proteins across species.

5. Epigenomic Insights

piRNAs are key players in epigenetic regulation. Bioinformatics pipelines integrate piRNA data with chromatin immunoprecipitation sequencing (ChIP-seq) and DNA methylation data to uncover their role in shaping the epigenome.

Case Study: piRNAs in Germline Integrity

One of the hallmark functions of piRNAs is the suppression of transposable elements in the germline. For example, in Drosophila melanogaster, piRNAs target retrotransposons like gypsy and copia. Bioinformatics analyses revealed that these piRNAs guide PIWI proteins to transposon-derived RNA, ensuring genome stability during gametogenesis.

Clinical Relevance of piRNAs

Recent studies suggest that piRNAs may serve as biomarkers for diseases such as cancer, infertility, and neurodegenerative disorders. For instance:

• Cancer: Dysregulated piRNA expression has been linked to tumorigenesis, making them potential targets for cancer therapies.
• Infertility: Aberrant piRNA pathways are implicated in male infertility due to their role in spermatogenesis.
• Neurodegeneration: piRNAs may regulate neuronal gene expression, highlighting their potential in neurological research.

Future Directions

The integration of bioinformatics with emerging technologies offers exciting opportunities for piRNA research:

• Single-Cell Sequencing: Unveiling cell-specific piRNA expression and function.
• Machine Learning: Predicting piRNA functions and targets with greater accuracy.
• CRISPR-Based Tools: Editing piRNA clusters to explore their roles in vivo.

Conclusion

piRNAs are the unsung guardians of the genome, safeguarding genetic material from transposable elements and contributing to gene regulation and epigenetic programming. Bioinformatics has opened the floodgates of discovery, unraveling the complexities of piRNAs and their myriad roles in biology and disease.

As we continue to decode the piRNA landscape, these small RNAs promise to unveil big secrets about genome stability, evolution, and human health, cementing their place as a fascinating frontier in molecular biology.

The successful candidate will be in charge of the detection of polymorphisms including structural variants, of the comparison of multiple and diverse genomes of a same species and of the construction of pan- and core-genomes. These challenging tasks will require bioinformatics developments and implementation of methods for accommodating the high level of repetitiveness of complex genomes. The tools will be integrated into pipelines and made available to end-users through the Galaxy platform. The bioinformatician will therefore also have to provide researchers with advices on their experimental designs in order to ensure compliance of produced datasets with pipelines requirements. He/she will be hosted by a bioinformatics/informatics team (7 people) (http://moulon.inra.fr/index.php/fr/equipestransversales/atelier-de-bioinformatique) which has computational facilities and expertise in NGS data analysis, and will benefit as well from national and international collaborative networks (Aplibio http://www.renabi.fr/platforms/aplibio/, Transplant http://transplantdb.eu, AMAIZING http://www.amaizing.fr/).

The position requires a doctoral degree (PhD) in bioinformatics with strong expertise in script writing (Python/Perl) and pipeline development.

Applicants should send a CV and the names of 2 referees willing to provide a letter of recommendation to joets@moulon.inra.fr.

National Bioinformatics Infrastructure Sweden (NBIS) (nbis.se) plays an important role in advancing life science research in Sweden by providing expert support and developing cutting-edge bioinformatics infrastructure. Operating as a truly national initiative, NBIS employs more than 120 bioinformaticians, system developers, and data stewards across multiple locations in Sweden. It serves as the bioinformatics platform at SciLifeLab, a national resource that facilitates research in molecular biosciences by offering access to state-of-the-art technologies and technical expertise. With strong ties to data-producing facilities and ongoing collaborations with leading research groups, NBIS is ideally positioned to support world-class bioinformatics analyses. Furthermore, NBIS is the Swedish node in ELIXIR, the European infrastructure for biological information.

NBIS is seeking an experienced bioinformatician to support both Swedish and international projects. As part of our dynamic team, you will work closely with researchers to process large-scale biological data and contribute to advancing our data analysis infrastructure. Strong problem-solving skills, attention to detail, and the ability to troubleshoot complex bioinformatics pipelines are essential for success in this role. Flexibility and a willingness to learn are also important, as NBIS continually adapts to meet the evolving needs of the Swedish research community.

More at https://www.uu.se/en/about-uu/join-us/jobs-and-vacancies/job-details?query=778701

Research Area

the discovery and on-demand use of biomedical data and services
the formulation, discovery and evaluation of scientific hypotheses
the simulation of biological systems at the level of individual molecules

Link @ http://dumontierlab.com/

Why Remote Session Management is a Must-Have

In bioinformatics, tasks like genome assembly, RNA-seq analyses, and phylogenetic computations often take hours or days. A dropped SSH connection can result in:

• Lost Progress: Restarting a job from scratch wastes valuable time.
• Workflow Interruptions: Disruptions can derail your focus and productivity.
• Corrupted Data: Interrupted processes may lead to incomplete or corrupted outputs.

By integrating screen, tmux, or mosh into your workflow, you can avoid these setbacks and ensure a seamless experience.

Screen: The Classic Workhorse

Screen is a terminal multiplexer that comes pre-installed on most Linux systems. It allows you to manage multiple terminal sessions and reconnect to them even after being disconnected.

Getting Started with Screen:

1. Start a Session:
   screen
2. Detach from a Session:
   Press Ctrl+A, then D.
3. Reattach to a Session:
   screen -r

Pro Tip: Enhance your screen experience with a customized .screenrc configuration file. Download one here: Get .screenrc.

Tmux: A Modern Alternative

Tmux takes everything great about screen and adds modern features, including better key bindings and intuitive session management. It\u2019s perfect for bioinformaticians who want more control over their workflow.

Getting Started with Tmux:

1. Start a Session:
   tmux
2. Detach from a Session:
   Press Ctrl+B, then D.
3. Reattach to a Session:
   tmux attach

Customize Your Tmux Experience:
Use a .tmux.conf file to personalize your setup. Grab one here: Download .tmux.conf.

Mosh: The Mobile Shell for Unreliable Connections

SSH works well for stable networks, but it struggles in areas with spotty connectivity. Enter Mosh, the Mobile Shell. Designed for intermittent networks, Mosh keeps your session alive even when the connection drops temporarily.

Why Mosh is a Game-Changer:

• No lag over high-latency networks.
• Automatically reconnects when the network is restored.
• Ideal for working on the go, from cafes to trains.

Getting Started with Mosh:

1. Install Mosh:
   sudo apt install mosh # For Debian/Ubuntu
2. Connect to a Server:
   mosh username@server

Learn more at mosh.org.

Why This Matters for Bioinformatics

Every bioinformatician knows the value of time and data integrity. Tools like screen, tmux, and mosh provide a lifeline when running long analyses, enabling you to:

• Safeguard your work against disconnections.
• Easily manage multiple workflows in parallel.
• Stay productive, even in challenging environments.

Quickstart Cheat Sheet

• Screen:

  screen # Start a session Ctrl+A, D # Detach screen -r # Reattach

• Tmux:

  tmux # Start a session Ctrl+B, D # Detach tmux attach # Reattach

• Mosh:

  mosh username@server

Final Thoughts

As a bioinformatician, your time is too valuable to spend restarting analyses due to technical hiccups. With screen, tmux, and mosh in your toolkit, you can work smarter, protect your progress, and stay productive no matter where you are. Start using these tools today and transform the way you work with remote systems.

Let me know how these tools work for you, and don\u2019t forget to follow for more bioinformatics tips!

Link : http://www-dsv.cea.fr/en/instituts/institut-de-biologie-et-de-technologies-de-saclay-ibitec-s/unites-de-recherche/service-de-biologie-integrative-et-genetique-moleculaire-sbigem/laboratoire-de-biologie-integrative-lbi/presentation__1