Most people who have a balanced translocation have the right amount of chromosome material but it has been rearranged in some way. This may happen if two chromosomes swap pieces (a reciprocal translocation). In other cases two whole chromosomes may become stuck together (a Robertsonian translocation). This page describes what happens when someone has a reciprocal translocation.

Reciprocal chromosomal translocations occur following double-strand breaks (DSBs) in DNA when a section of one chromosome is exchanged with that of another, non-homologous chromosome. These exchanges may produce a dysfunctional fusion gene that disrupts cell growth and survival pathways, such as the translocations seen in leukemia and childhood sarcomas.

Chromosomal translocations have been well studied in cancer cell lines which are associated with two types of cancer, acute myeloid leukemia and Ewing's sarcoma, but determining how they contribute to cancer development is complicated by additional mutations and altered gene expression profiles in these cultured cells. Now, Juan Carlos Ramirez, head of the Viral Vector Facility at the Fundacion Centro Nacional de Investigaciones Cardiovasculares (CNIC) and his colleagues Raul Torres at CNIC and Sandra Rodriguez-Peralez at the Spanish National Cancer Center (CNIO) in Madrid, Spain have used a new genome editing tool, CRISPR-Cas9, to induce chromosomal translocations for the first time in a human cell line and in primary cells. The study's authors conclude by stating that the use of this technology will allow for the clarification of how and why chromosomal translocation occurs, which without doubt will allow new anti-cancer therapeutic strategies to be tackled.

Using RNA-Guided Endonuclease (RGEN) technology or CRISPR/Cas9 genome engineering technology, CNIO and CNIC researchers have shown that it is possible to obtain such chromosomal translocations. The CRISPR-Cas9 system is extremely simple to introduce a cut at the desired locus, easier to design, and cheaper than many other systems. Using the CRISPR-Cas9 system, Ramirez and his colleagues reproduced the translocations observed in Ewing’s Sarcoma (ES) and Acute Myeloid Leukemia (AML) patient cell lines in HEK293 cells and also generated the ES translocation in human mesenchymal stem cells and the AML translocation in umbilical cord blood cells.

By focusing on chromosomal translocation without the confounding characteristics of established cell lines, these new cells lines should help answer the fundamental question of what causes a cell to become cancerous. Ramirez and his team now look forward to modeling other chromosome translocations in a variety of cell types.

Reference:

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

http://www.nature.com/ncomms/2014/140603/ncomms4964/abs/ncomms4964.html

The next step after reading genetic code is writing a script to analyse and explore the hidden information. This tutorial is aimed to introduce you new biological programming languages with their packages/libraries, and assist in your scripting work.

Navigate the sub-section of this page [ see right hand side of the page for it ]

Brief description: We are looking for suitable candidates in the area o computational biology/bioinformatics/genomics or related field for next-generation sequencing (NGS) data analysis for small-RNAs, RNA-Seq and targeted resequencing of plants and associated organisms. We are an interdisciplinary group where projects equally involve bioinformatics and systems biology (specially microarrays and next-generation sequencing (NGS) data analysis and its use), along with plant molecular biology, genetic engineering, field biology, and analytical plant chemistry for understanding response of plants to biotic stresses.

Essential qualification: MSc/BTech/MTech/PhD (or other suitable qualification) in disciplines preferable to bioinformatics, computational biology, computer application (or equivalent)/ ‘Advance Post-Graduate Diploma in Bioinformatics’. Proficiency in programming languages (such as Perl, C++) and/or statistics (proficient in R for example) is compulsory.

Desirable qualification: Experience in the field of genomics e.g. microarray analysis, NGS, genome annotation, database development and management, software development, systems and network biology (or related fields) will be preferred.

Application process: Applications should contain CV along with brief description (maximum 1 page) of research conducted (highlighting skills and experience) till now. Applications should be sent by e-mail to Shree Prakash Pandey, Department of Biological Sciences, Indian Institute of Science Education and Research Kolkata, Mohanpur Campus, WB, India within 14 days of this advertisement.

E-mail: sppiiserkol@gmail.com, sppandey@iiserkol.ac.in

Advertisement:

http://www.iiserkol.ac.in/announcements/adverts/671-advt_ra_shree_prakash_july_2014

17 Nov 2013 -22 Nov 2013

More at http://events.embo.org/13-large-scale-data/

Online Registration: https://www.conference-service.com/pc13-47/welcome.cgi

Scientists with a long-running Framingham Heart Study looked at 1,932 people (examination of about 1.5 million markers of genetic variations), comparing unrelated friends to unrelated strangers. They found that friends shared about 1% of their genes — a percentage much higher than those shared with strangers.This new findings made it clear that people have more DNA in common with those who are selected as friends than with strangers in the same population. 

The genes that lined up the most were olfactory genes, which deal with smell. The ones that lined up the least were immune system genes. The researchers weren't sure why that happened :/. Olfactory genes might be a straightforward explanation: People who like the same smells tend to be drawn to similar environments, where they meet others with the same tendencies.

Reference:

http://www.pnas.org/content/111/Supplement_3/10796.full

Image : http://i.kinja-img.com

Address of the bookmark: https://peerj.com/preprints/453.pdf

ICRISAT is headquartered in Patancheru near Hyderabad, India, with two regional hubs and five country offices in sub-Saharan Africa. ICRISAT, established in 1972, is a member of the CGIAR Consortium. For more details, see www.icrisat.org.

Job Responsibilities:
Planning and execution of different NGS/genomics data analysis
Apply, maintain, and support cutting-edge pipelines for the analysis and interpretation of NGS data
Analyze large-scale genomic datasets generated internally and through collaboration with others
Genome wide analysis- LD analysis, hapmap, genetic map construction and qtl mapping
Expression analysis based on RNA-seq, gene ontology and metabolic pathway data
Sequence level analysis like gene family analysis, orthology/paralogy etc.
Familiarity with genomic and biological information databases
Compilation and interpretation of results and writing reports
Experience working independently and in a team environment
Requirements:

PhD or M.Sc with 2-3 years experience from reputed institute in the area of life science or similar Knowledge in Next Generation Sequencing (NGS) data analysis. Should be familiar with various sequencing platforms. Sound knowledge of genomics and molecular biology is must. Proficient in any one of the programming/scripting in languages: Python, Perl, PHP, R, Shell Scripting. Must be experienced in working on Linux and CLI environment. Ability to work as team as well as independently with minimal support. Fluency in spoken and written English is essential.

NGS techniques like sequence alignment, variant calling based on whole genome re-sequencing and genotyping-by-sequencing (GBS), RNA-Seq/transcriptome analysis
Knowledge of various standard NGS related tool
Ability to solve complex problems in advanced genomics research areas
Ease and interest in working with people from diverse backgrounds
Excellent oral/written communication and interpersonal/networking skills
General:
This position is contract for a period of two years.

How to apply:
Applicants should apply on or before 27-July-2017, with latest Curriculum Vitae, and the names and contact information of three references that are knowledgeable about your professional qualifications and work experience. All applications will be acknowledged, however only short listed candidates will be contacted
Please CLICK HERE to submit your application.
ICRISAT is an equal opportunity employer

http://icrisat.careersitemanager.com/job-listings-Visiting-Scientist-Computational-Genomics-ICRISAT-Hyderabad-Secunderabad-2-to-4-years-060717000278

Developing New Molecular Methods

Genomic Approaches to Developmental Biology

Massively Parallel Functional Genomics

Translating Genomics to the Clinic

Genetic Basis of Human Disease

Genome Sequencing Technologies

http://krishna.gs.washington.edu/index.html
http://www.gs.washington.edu/faculty/shendure.htm