BOL: Related items

Unlocking Evolutionary Secrets: A Dive into Comparative Genomics Methods

LEGE — Tue, 20 May 2025 00:25:09 -0500

Comparative genomics is the art and science of comparing genomes—across species, within species, or even among individuals—to unravel evolutionary relationships, functional elements, and genetic adaptations. As sequencing technologies have advanced and genome databases have expanded, comparative genomics has become a cornerstone of modern biology, shedding light on everything from antibiotic resistance in bacteria to human disease genetics.

In this post, we’ll explore the core methods used in comparative genomics, the questions they help answer, and how they’re shaping our understanding of life.

1. Whole-Genome Alignment
Whole-genome alignment involves mapping the entire genome of one species to another. Tools like MUMmer, MAUVE, and LASTZ perform large-scale sequence alignments to detect conserved regions, rearrangements, insertions, and deletions.

Use Case:
Comparing human and chimpanzee genomes to identify evolutionary conserved sequences (ECS) and regions of divergence.

Key Challenges:
Handling repetitive sequences and genome rearrangements.

Computational complexity in large genomes.

2. Synteny and Collinearity Analysis
Synteny refers to conserved blocks of gene order across species. Tools like MCScanX, SynMap, or CHITRA (for visualizing synteny interactively) detect these blocks to understand chromosomal evolution.

Use Case:
Studying ancient genome duplications in plants.

Investigating chromosomal rearrangements in cancer genomes.

3. Ortholog and Paralog Detection
Orthologs are genes in different species that evolved from a common ancestor, while paralogs are genes duplicated within a genome. Identifying them is crucial for functional annotation and evolutionary studies.

Popular Tools:
OrthoFinder, Orthologous MAtrix (OMA), InParanoid, and EggNOG.

Use Case:
Functional prediction of uncharacterized genes based on orthologs in model organisms.

Tracing gene family evolution.

4. Phylogenomic Analysis
Phylogenomic methods combine phylogenetics and genomics to infer evolutionary trees based on genome-wide data. These methods can handle dozens to hundreds of genomes, using concatenated alignments or gene trees.

Tools:
RAxML, IQ-TREE, ASTRAL, Phylip, BEAST.

Use Case:
Resolving the evolutionary relationships between microbial species.

Studying speciation events.

5. Pan-Genome Analysis
The pan-genome consists of the core genome (shared by all strains) and the accessory genome (strain-specific genes). This is especially popular in microbial genomics.

Tools:
Roary, Panaroo, BPGA, PGAP.

Use Case:
Understanding virulence factor diversity in E. coli.

Designing broad-spectrum vaccines.

6. Comparative Transcriptomics
Comparing transcriptomes across species or conditions reveals conserved and unique expression patterns. RNA-seq data can be mapped to reference genomes to identify orthologous expression profiles.

Use Case:
Comparing stress response in extremophiles and model species.

Studying conserved regulatory networks.

7. Functional Element Comparison
Beyond genes, comparative genomics also targets non-coding regions—enhancers, promoters, miRNAs. Conservation across species often implies functional importance.

Tools:
PhastCons, GERP, phyloP (based on multiple alignments).

Use Case:
Detecting conserved non-coding elements in vertebrates.

Studying regulatory divergence in human evolution.

8. Horizontal Gene Transfer (HGT) Detection
In microbes, genes often jump across species boundaries. Comparative genomics can detect HGT by identifying genes that defy the expected phylogenetic pattern.

Tools:
HGTector, DarkHorse, AlienHunter, SIGI-HMM.

Use Case:
Tracing antibiotic resistance genes.

Exploring microbial adaptability in extreme environments.

Final Thoughts
Comparative genomics is a powerful lens to observe the diversity and unity of life. With a broad toolkit—from aligners to orthology pipelines, phylogenetic engines to visualization tools—it allows scientists to ask big questions: How did genomes evolve? What makes species unique? Where do new genes come from?

Whether you're studying extremophiles, building better crops, or exploring human ancestry, comparative genomics offers the methods to connect the dots across the tree of life.

GWASpro: A High-Performance Genome-Wide Association Analysis Server

Rahul Nayak — Fri, 07 Dec 2018 08:04:57 -0600

GWASpro supports building complex design matrices, by which complex experimental designs that may include replications, treatments, locations and times, can be accounted for in the linear mixed model (LMM). GWASpro is optimized to handle GWAS data that may consist of up to 10 million markers and 10,000 samples from replicable lines or hybrids. GWASpro provides an interface that significantly reduces the learning curve for new GWAS investigators.

Address of the bookmark: https://bioinfo.noble.org/GWASPRO/

Heatmap Draw !

BioStar — Mon, 06 Mar 2023 04:24:57 -0600

Server for heatmap generation !

https://software.broadinstitute.org/morpheus/

Address of the bookmark: https://software.broadinstitute.org/morpheus/

KOBAS: a web server for gene/protein functional annotation and functional gene set enrichment

Jit — Fri, 19 Oct 2018 09:36:11 -0500

KOBAS 3.0 is a web server for gene/protein functional annotation (Annotate module) and functional gene set enrichment(Enrichment module). For Annotate module, it accepts gene list as input, including IDs or sequences, and generates annotations for each gene based on multiple databases about pathways, diseases, and Gene Ontology. For Enrichment module, it can accept either gene list or gene expression data as input, and generates enriched gene sets, corresponding name, p-value or a probability of enrichment and enrichment score based on results of multiple methods.

Address of the bookmark: http://kobas.cbi.pku.edu.cn/

QuartataWeb: user-friendly server developed for polypharmacological and chemogenomics analyses.

Neel — Wed, 01 Apr 2020 10:30:52 -0500

Data on protein-drug and protein-chemical interactions are rapidly accumulating in databases such as DrugBank and STITCH. These data usually reflect observed interactions, while the lack of data for a given protein-drug/chemical pair does not necessarily mean the lack of interaction. Indeed, recent studies, both computational and experimental, highlighted the promiscuity of both proteins and small molecules: many drugs have side effects i.e. they target proteins other than those known in public databases; and many proteins bind chemicals other than those known, opening the way to design repurposable drugs, new chemicals, or polypharmacological treatments.

https://academic.oup.com/bioinformatics/advance-article/doi/10.1093/bioinformatics/btaa210/5813333

Address of the bookmark: http://quartata.csb.pitt.edu/

Far Manager Commands and Links !

Jit — Tue, 23 Jun 2020 06:24:36 -0500

Far Manager is a program for managing files and archives in Windows operating systems. Far Manager works in text mode and provides a simple and intuitive interface for performing most of the necessary actions:

viewing files and directories;
editing, copying and renaming files;
and many other actions.

https://www.farmanager.com/

Basic instruction at

https://conemu.github.io/en/FarManager.html

Plugins at

https://plugring.farmanager.com/

Address of the bookmark: https://www.farmanager.com/

Kamaleshwar Singh Lab

Fri, 25 Mar 2016 10:46:49 -0500

The focus of Dr. Singh’s research and teaching is on the molecular mechanistic basis for environmental carcinogen-induced genetic (DNA damage) and epigenetic changes, and susceptibility to human cancer development

More at http://www.tiehh.ttu.edu/dr.-kamaleshwar-singh.html

Bioinformatics Centre, Bose Institute vacancy of Research Associate / Senior Research Fellow

Mon, 22 Feb 2016 03:27:17 -0600

Bioinformatics Centre, Bose Institute vacancy of Research Associate / Senior Research Fellow

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 at University of Kalyani

Tue, 22 Dec 2015 01:51:42 -0600

Bioinformatics Trainee
Eligibility : MSc
Location : Kolkata
Last Date : 28 Dec 2015
Hiring Process : Walk - In
University of Kalyani

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

Chekulaevalab

Tue, 12 Jan 2016 02:32:03 -0600

Focusing on understanding the molecular mechanisms that regulate mRNA translation, localization and stability and role of non-coding RNAs in this process. Up to 90% of human DNA is estimated to be transcribed into so called non-coding RNAs that are not translated into proteins. Many of them act as potent modifiers of gene expression. miRNAs are a class of such short non-coding RNAs. They regulate expression of more than a half of eukaryotic genes, thus, affecting multiple biological processes, including cell proliferation, differentiation, apoptosis and senescence. Not surprisingly, miRNAs are involved in many human pathologies, including cancer and neurological disorders and hold great potential as drug targets, disease markers, as well as therapeutic agents.
Our lab is located at the Berlin Institute for Medical Systems Biology (BIMSB), a part of the Max Delbrück Center for Molecular Medicine (MDC).

http://www.chekulaevalab.org/