Key Findings of the Study:

1. Alu Insertion and Tail Loss:
   The researchers discovered an Alu-mediated genetic change in a common ancestor of modern apes and humans. This change disrupted the normal function of a gene involved in tail development, leading to the suppression of tail formation.

2. Gene Disruption Mechanism:
   The Alu insertion was found within a regulatory region of the TBXT gene (also known as T or Brachyury), which is crucial for tail development in vertebrates. This insertion likely altered the gene's expression patterns, leading to tail reduction over evolutionary time.

3. Functional Evidence from Model Organisms:
   To test their hypothesis, the researchers introduced similar genetic modifications in mice. The modified mice exhibited shortened or absent tails, supporting the idea that the identified mutation played a role in tail loss in hominoids.

4. Evolutionary Implications:
   The findings suggest that small, random genomic changes—such as transposable element insertions—can have profound effects on body morphology. This study provides evidence that mobile DNA elements (like Alu) can drive major evolutionary transitions.

5. Relevance to Human Evolution:
   Understanding the genetic basis of tail loss helps in reconstructing the evolutionary history of hominins (the lineage that includes humans and our extinct relatives). It also sheds light on how genetic variations contribute to anatomical diversity among primates.

Significance of the Study:

This research highlights the role of transposable elements in shaping evolutionary traits and provides a concrete genetic explanation for a defining characteristic of humans and great apes. It also demonstrates how mutations in regulatory regions of developmental genes can lead to significant anatomical changes.

Reference

http://blog.bina.com/news/bina-technologies-acquired-by-roche?&__hssc=109677338.1.1419953400266&__hstc=109677338.b8350f2729889b08f1325906d5236cd3.1419953400266.1419953400266.1419953400266.1&hsCtaTracking=96cac941-9372-4bbf-bacb-3ca6f1ff8cfd|3fce0f18-835b-4086-9345-388880861732

http://www.the-scientist.com/?articles.view/articleNo/41750/title/Roche-Buys-Bioinformatics-Firm/

In addition to providing a broad sample of the diversity in S. bicolor, the genotypes included in this study are known to display agronomically important traits including stay-green drought resistance, insect resistance, grain size and grain quality.

Find more at http://www.nature.com/ncomms/2013/130827/ncomms3320/full/ncomms3320.html

Back in August, van Rossum published a proposal on the Python mailing list recommending type-checking annotations as a valuable feature for the next version of Python to improve the performance of editors and IDEs, linter capabilities, standard notation, and refactoring. Van Rossum’s latest proposal, posted late last month, outlined plans to publish a Python Enhancement Proposal (PEP) in early January to put the feature now known as type hinting on track for inclusion in Python 3.5, slated for release this September.

Reference

https://quip.com/r69HA9GhGa7J

The role sits at the critical interface between genetics and cancer systems biology, and would suit a candidate who is interested in developing a career at the confluence of Statistics/Data Mining/Machine Learning and Biology. Ideally, you will have experience in development of analytical approaches to high-throughput and multivariate data mining and integration gained through a PhD (or equivalent) in a quantitative subject (eg mathematics, statistics, physics, engineering or computer science).

Experience of statistics and/or machine learning techniques is highly desirable as is evidence of prior experience of developing bioinformatics software and/or analysing complex *omics data sets. You will be able to work as part of a team and independently and deliver results to the required standard and schedule. You should be able to organise and prioritise your own work, as well as have excellent communication skills, both written and oral. The post will involve interactions with collaborators from such diverse fields as applied mathematics, statistics, computer science and medicine.

This is a full-time post, fixed-term until 31 March 2017. For informal enquiries, contact Dr Anastasia Samsonova (bioinformatics@oncology.ox.ac.uk).

All applicants must complete a short application form and upload a CV and supporting statement.

The closing date for applications is 12.00 noon on 26 January 2015.

More at https://www.recruit.ox.ac.uk/pls/hrisliverecruit/erq_jobspec_version_4.display_form

Note: This image/cartoon is create only for fun. It has nothing to do with any scientific findings.