MitoFinder: Mitofinder is a pipeline to assemble mitochondrial genomes and annotate mitochondrial genes from trimmed read sequencing data.

MitoHiFi: a python pipeline for mitochondrial genome assembly from PacBio high fidelity reads

MITObim: MITObim is a tool specifically developed for the iterative assembly of mitochondrial genomes. It starts with a reference mitogenome and iteratively refines the assembly using the read data.

MITOS: MITOS is a web-based platform that provides a pipeline for annotating mitochondrial genomes. It integrates multiple software tools for assembly, annotation, and visualization of mitogenomes.

MIRA: MIRA (Mimicking Intelligent Read Assembly) is a versatile genome assembly tool that can be used for mitochondrial genome assembly. It supports various sequencing technologies and allows for reference-based or de novo assembly.

NOVOPlasty: NOVOPlasty is a user-friendly tool designed for de novo assembly of organelle genomes, including mitochondria. It utilizes a seed-and-extend algorithm and is suitable for both short-read and long-read data.

MITOS2: MITOS2 is an updated version of the MITOS pipeline, which automates the annotation of mitochondrial genomes. It provides improved accuracy and additional features for mitochondrial genome analysis.

GetOrganelle: While primarily designed for chloroplast genome assembly, GetOrganelle can also be used for mitochondrial genome assembly. It is particularly useful for dealing with high-throughput sequencing data.

SPAdes: SPAdes (St. Petersburg genome assembler) is a versatile genome assembly tool that can be employed for mitochondrial genome assembly, especially when dealing with complex datasets that may contain nuclear mitochondrial DNA sequences (numts).

IDBA-UD: IDBA-UD (Iterative De Bruijn Graph De Novo Assembler) is another de novo assembly tool that can be used for mitochondrial genome assembly, especially in cases with relatively low coverage.

Velvet: Velvet is a de novo assembly tool that can be applied to mitochondrial genome assembly, especially when working with short-read data.

When selecting a mitochondrial genome assembly tool, it's important to consider the specific characteristics of your sequencing data, such as read length and coverage, as well as the complexity of the mitochondrial genome. Additionally, some tools are better suited for specific organisms or research objectives, so choosing the right tool will depend on your particular project requirements.

WALK- IN –INTERVIEWS

Eligible candidates may appear in Walk-in-Interview on May 23, 2014 at 10 AM for the posts of Research Associates & Senior Research Fellows (SRF) in the following DST/DBT/ICAR funded projects.

1 NPTC Project on Bioinformatics and Comparative Genomics

Research Associate (One)

Rs. 24000/- + 30% HRA for masters degree holder with more than 4 years experience

Essential: Ph D in Plant Molecular Biology & Biotechnology/Genetics 0r Candidates who have already submitted their Ph D thesis in above subjects

Desirable: Research experience in Genomics, Molecular biology, Microarrays analysis, Gene cloning, transgenic Techniques , and computational analysis.

Senior Research Fellow ( UGCCSIR/ DBT/ ICAR Net qualified only): (One)

Rs. 16000/- + 30% HRA and Rs. 18000+30 HRA from 3rd year onwards

Essential:

1. ICAR/ UGCCSIR/DBT Net qualified only

2. M. Sc. (with thesis) in Biotechnology, Life Sciences, Biosciences/ Bioinformatics, Genetics/ Plant Pathology with experience in molecular biology.

Or M.Sc with more than 3 years research experiences

3. B.Sc. Agriculture or Biology

Desirable:
1. M. Sc. with thesis
2. Experience in molecular biology, plant tissue culture
3. Bioinformatics knowledge is important

2 DST JC Bose National Fellowship

Research Associate (Bioinformatics) : One

Rs.22000/- + 30% HRA for 1 & 2nd Yr., Rs. 23000+ 30% HRA for 3rd year and Rs. 24000+30% HRA for 4th &5th yr

Essential: M Ph D in Plant Molecular Biology & Biotechnology/Genetics

Desirable: Research experience in Genomics, Molecular biology, Microarrays analysis, Gene cloning, transgenic Techniques , and computational analysis.

Age limit: Max.35 years (Age relaxation of 5 years for SC/ST & women and 3 years for OBC)

The posts are purely temporary in nature and are co-terminus with the project. Initially the offer will be made for one year only and may be further extendable based on performance of the candidate. The interview will be held on May 23 , 2014 at 10:00 AM at NRCPB, LBS Building, Pusa Campus, IARI, New Delhi- 110012. The candidates must bring four copies of biodata (in the prescribed proforma), original certificates, attested photocopies of each of the certificates and an attested copy of recent passport size photograph. No. TA/DA would be given for the appearance in interview. Only the candidates having essential qualification would be entertained for the interviews. Short-listing of candidates based on academic merit and experience will be done in case of large number of applicants.

Advertisement: http://www.nrcpb.org/sites/default/files/Advertisement%20for%20RA%20and%20SRF%20Position.pdf

What Are Chromosome Rearrangements?

Chromosome rearrangements are structural changes that alter the normal configuration of chromosomes. These changes can involve large segments of DNA — from thousands to millions of base pairs — and can occur spontaneously, be inherited, or result from exposure to mutagens (like radiation or chemicals).

Common Types of Rearrangements:

1. Deletions – Loss of a chromosome segment

2. Duplications – Repetition of a segment

3. Inversions – A segment breaks off, flips, and reattaches

4. Translocations – Segments exchange places between non-homologous chromosomes

5. Insertions – A segment is inserted into another part of the genome

These changes can disrupt genes directly or affect gene regulation, leading to disease.

How Do Chromosome Rearrangements Cause Disease?

The impact of a rearrangement depends on which genes are involved, how much DNA is affected, and when the rearrangement occurs (in development vs. adulthood). Here are some key mechanisms:

• Gene disruption: Breaking a gene can lead to loss of function or the creation of a non-functional protein.

• Gene fusion: Joining parts of two genes may form a novel hybrid gene with new functions (common in cancer).

• Dosage effects: Extra or missing gene copies can disturb the balance of gene expression.

• Position effects: Moving a gene to a new regulatory environment may silence or over-activate it.

Chromosome Rearrangements in Human Disease

1. Developmental Disorders

• Cri-du-chat syndrome: Caused by a deletion on chromosome 5p. Affected infants often have a high-pitched cry and intellectual disability.

• Williams syndrome: Results from a microdeletion on chromosome 7q, affecting genes related to cardiovascular and cognitive function.

2. Cancer

Cancer is perhaps the most striking example of disease caused by chromosome rearrangements.

• Chronic Myeloid Leukemia (CML): Caused by a translocation between chromosomes 9 and 22, forming the Philadelphia chromosome. This creates the BCR-ABL fusion gene, which drives uncontrolled cell growth.

• Burkitt lymphoma: Involves translocation of the MYC gene, leading to excessive cell division.

• Ewing sarcoma: A fusion of EWSR1 and FLI1 genes through translocation promotes tumor development.

3. Infertility and Miscarriages

Balanced rearrangements (like inversions or translocations) in carriers may not cause disease directly but can result in:

• Recurrent miscarriages

• Infertility

• Birth defects in offspring

Detecting Rearrangements

Thanks to modern genomics, chromosome rearrangements can now be detected with high precision using:

• Karyotyping – Classic method for detecting large rearrangements

• FISH (Fluorescence In Situ Hybridization) – Uses fluorescent probes to target specific DNA sequences

• Array CGH (Comparative Genomic Hybridization) – Detects copy number changes across the genome

• Whole Genome Sequencing (WGS) – Identifies even small or complex rearrangements at base-pair resolution

Looking Forward: The Future of Chromosome Medicine

Understanding chromosome rearrangements is now central to:

• Personalized medicine

• Genetic counseling

• Targeted therapies, especially in cancer (e.g., tyrosine kinase inhibitors for BCR-ABL fusion)

With the rise of long-read sequencing and single-cell genomics, even previously “invisible” rearrangements are being uncovered, offering new insights into both rare diseases and common conditions.

Final Thoughts

Chromosome rearrangements remind us that genetics isn't just about which genes we have — but where they are, how they're arranged, and when they're active. As our tools grow sharper, so does our ability to diagnose, understand, and treat diseases rooted in genomic architecture.

In a way, the genome is like a book not just defined by its words, but also by how the chapters are ordered. Rearranging them can create a new story — sometimes harmful, sometimes insightful — and understanding these changes is key to writing a healthier future.

C. Titus Brown http://video.open-bio.org/video/1/a-history-of-bioinformatics-in-the-year-2039

To address the challenges of describing and estimating virodiversity, a team of investigators from Center for Infection and Immunity (CII) and EcoHealth Alliance began in jungles of Bangladesh - home to the flying fox.

Reference:

http://economictimes.indiatimes.com/news/news-by-industry/et-cetera/mammals-harbour-at-least-320000-new-viruses/articleshow/22253268.cms

http://www.bbc.co.uk/news/science-environment-23932400

The Indian scientists working in Bangalore, along with their American counterparts, have mapped more than 17,000 proteins in 30 organs of the human body. Just like the human genome was sequenced around the turn of the millennium, this is an equivalent mapping of the human proteome.

The researcher estimated there are around 20,500 proteins in the human body. These scientists have profiled around 17,294, which account for around 84% of the total proteins. Apart from this, the team also traced around 2,500 of 3,000 proteins that had been categorised as "missing proteins".

The work, done by group of Indian scientists, and Johns Hopkins University, published in the renowned journal Nature ( http://www.nature.com/nature/journal/v509/n7502/full/nature13302.html ). Of the 72 people who worked on the project, 46 are Indians.

Reference:

http://www.nature.com/nature/journal/v509/n7502/full/nature13302.html

http://www.proteinatlas.org/ -The antibody-based Human Protein Atlas programme

http://www.humanproteomemap.org/ -Proteogenomic analysis by identifying translated proteins from annotated pseudogenes, non-coding RNAs and untranslated regions.

https://www.proteomicsdb.org/ -Assembled protein evidence for 18,097 genes in ProteomicsDB

Now a day, geneticists have developed a language of their own. They are pouring lots of money and energy to read the entire genomic text and understand the gods own code ATGC. It is somewhat fascinating, not only for geneticist but also for non-biologist to know that there are several conserved blocks in genome which remain conserved over hundreds of millions of years. There have been several researches on conserved blocks and non-conserved regions to understand the mechanism and importance of all these regions (http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2675965/). The finding indicates conservation and rearrangements of certain evolutionary important genes play an important role in evolution/adaptive changes (http://www.nature.com/nature/journal/v491/n7424/abs/nature11622.html https://academic.oup.com/gbe/article/8/8/2442/2198198/Novel-Insights-into-Chromosome-Evolution-in-Birds , http://science.sciencemag.org/content/346/6215/1311).

But the puzzle remains open, how to correctly define the synteny (presence of two or more genes on the same chromosome) and conserved synteny (presence of two or more genes on chromosome of each of the two species) on several genomes.

Figure: Image generated with Evolution Highway (EH) tool http://eh-demo.ncsa.illinois.edu/ 

Keeping the new approach to define conserved synteny in mind there have been various algorithms developed to identify the conserved homologous synteny blocks (HSB) amongst species. Some of them which were commonly used for synteny detections are:

SyntenyTracker ( http://www-app.igb.uiuc.edu/labs/lewin/donthu/Synteny_assign/html/),

SyntenyTracker was shown to be an efficient and accurate automated tool for defining HSBs using datasets that may contain minor errors resulting from limitations in map construction methodologies.

CoGe (http://genomevolution.org/CoGe/SynFind.pl )

Satsuma (http://evomics.org/learning/genomics/satsuma/)

Cinteny (http://cinteny.cchmc.org/) ,

Cinteny server can be used for finding regions syntenic across multiple genomes and measuring the extent of genome rearrangement using reversal distance as a measure.

OrthoCluster (http://krono.act.uji.es/noticias/orthocluster-a-new-tool-for-mining-syntenic-blocks)

A new tool for mining syntenic blocks in comparative genomics

SynMap (http://genomevolution.org/wiki/index.php/SynMap),

SyMAP (http://www.symapdb.org/)

SyMAP (Synteny Mapping and Analysis Program) v4.0 is an automated system for identifying and displaying genome synteny alignments. The genomes may be represented by sequenced chromosomes (pseudomolecules), by draft sequence contigs, or by FPC physical maps (with BAC-end or marker sequence).

http://genomevolution.org/CoGe/SynMap.pl

RegionMiner (http://www.genomatix.de/online_help/help_regionminer/orthologous.html)

SyntenyMiner is being developed as an application to visualize and interrogate comparisons among multiple complete genome sequences. http://syntenyminer.sourceforge.net/

AutoGRAPH ( http://autograph.genouest.org/),

AutoGRAPH is an integrated web server for multi-species comparative genomic analysis. It is designed for constructing and visualizing synteny maps between two or three species, determination and display of macrosynteny and microsynteny relationships among species, and for highlighting evolutionary breakpoints.

SynChro(http://www.lgm.upmc.fr/CHROnicle/SynChro.html)

SynChro is a tool designed to define conserved synteny blocks. It reconstructs synteny blocks between pairwise comparison of multiple genomes. The reconstructed synteny blocks may overlap each other, be included in one another or duplicated due to micro-rearrangements.

SyntenyView ( http://www.cbs.dtu.dk/dtucourse/cookbooks/nikob/exercises/gf1_output_5.html),

Ensembl 'SyntenyView' shows conservation of large-scale gene order between species pairs. A brief summary of the calculation method appears at the bottom of this help page.  The left of a 'SyntenyView' page displays a diagram of chromosomes with blocks of conserved synteny. The right of a page shows homology matches between individual genes within syntenic blocks.

SynBrowse ( http://www.synbrowse.org/),

SynBrowse (Synteny Browser) is a generic sequence comparison tool for visualizing genome alignments both within and between species. It is intended to help scientists study and analyze synteny, homologous genes and other conserved elements between sequences. This software is useful in studying genome duplication and evolution. It can also aid in identifying uncharacterized genes, putative regulatory elements and novel structural features of study species by comparing to a well annotated reference sequence, thus enabling genome curators to refine and edit annotations of species that have incomplete genome annotations.

Sibelia (http://arxiv.org/abs/1307.7941).

A comparative genomic tool: It assists biologists in analysing the genomic variations that correlate with pathogens, or the genomic changes that help microorganisms adapt in different environments. Sibelia will also be helpful for the evolutionary and genome rearrangement studies for multiple strains of microorganisms.

GSV (http://cas-bioinfo.cas.unt.edu/gsv/homepage.php)

Genome Synteny Viewer allows users to upload files which contain synteny regions between two or more genomes and interactively visualize the synteny between them. GSV also allows users to upload annotation files to visualize annotated regions in addition to synteny regions.

MicroSyn (http://www.lgm.upmc.fr/CHROnicle/SynChro.html)

MicroSyn software as a means of detecting microsynteny in adjacent genomic regions surrounding genes in gene families. MicroSyn searches for conserved, flanking colinear homologous gene pairs between two genomic fragments to determine the relationship between two members in a gene family.

SynOrth (http://synorth.genereg.net/)

Synorth [s n ôrth], named in combination of "synteny" and "ortholog", is designed for the study of evolutionary changes of genomic regulatory blocks (GRBs) in vertebrate genomes, and especially the changes following the whole-genome duplication in teleost fish, by tracing the ortholog genes gain and loss in ancient synteny blocks.

SyDiG (http://www.ncbi.nlm.nih.gov/pubmed/21441096)

Uncovering Synteny in Distant Genomes.

MapSynteny  (http://www.automatizacionysistemas.com/download.html)

MapSynteny is a macro in MS Excel® able to create images to show the relationship between genetic maps and large sequences (scaffolds, chromosomes, BACs, etc.). Based on tab – delimited BLAST results and some formulas, a suitable image of syntenic relationships or physical mapping can be obtained. http://www.automatizacionysistemas.com/Poster_MapSynteny.pdf

One of the best synteny tutorial for beginer @ http://www.nature.com/scitable/topicpage/synteny-inferring-ancestral-genomes-44022

Reference:

http://www.nature.com/scitable/topicpage/synteny-inferring-ancestral-genomes-44022

http://www.nature.com/nature/journal/v491/n7424/full/nature11622.html

http://en.wikipedia.org/wiki/Synteny

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2675965/