GEvol is unique as it will use, for the first time, a large taxonomic group to focus on one goal: to characterise the dynamics and mechanisms of genomic innovations underlying novel traits using comparative evolutionary genomics (and related data).
Thus, projects participating in GEvol we will ask fundamental evolutionary questions such as:
1. At what level is evolution repeatable?
2. How does genomic plasticity interfere with phenotypic plasticity during evolution?
3. How do inter- and intra-specific interactions influence genomic architectures?
4. How predictable is phenotypic variation given some knowledge about the dynamics and mechanisms of underlying genome evolution?

Address of the bookmark: https://g-evol.uni-muenster.de/open-positions/

There are Neanderthal bones. Denisovan remains. Fossils from ancient relatives of our species. Each specimen gives us another piece of the story of how Homo sapiens came to be.

But now imagine that one of the most important characters in that story has left behind no fossil, no skull, no bone, and no genome.

Nothing that a paleontologist could put behind glass.

And yet, somehow, that ancient population is still speaking.

It is speaking through us.

A fascinating new study published in Science (https://www.science.org/doi/10.1126/science.aef8874?) introduces a computational method called TRACE, which allows scientists to search modern human genomes for genetic traces of ancient populations that have never been directly identified.

For years, scientists have known that our ancestors interacted with Neanderthals and Denisovans. Their DNA still survives in modern human populations. But these may not have been the only ancient humans who crossed paths with our ancestors.

Using TRACE, researchers found evidence of an unknown archaic population that contributed DNA to the ancestors of modern humans before humans spread beyond Africa.

Even more surprisingly, they found evidence of a much older lineage—possibly around 1.8 million years old—whose genetic legacy may have reached some modern humans indirectly through Denisovans.

The extraordinary part is that researchers did not need DNA from these mysterious populations to detect them. Instead, they studied the ancestry of modern genomes and looked for genetic patterns that revealed unusually ancient branches of our family history.

It is almost like finding the footprints of someone who disappeared thousands of years ago—without ever finding the person themselves.

These discoveries suggest that human evolution was far more complicated than a simple family tree. Ancient human populations repeatedly separated, migrated, met and exchanged genes. Some eventually disappeared, but pieces of their genetic legacy survived.

And that means our DNA is more than a biological instruction manual.

It is also an archive of human history.

Some of the people recorded in that archive may never have a name or a fossil. But thanks to methods like TRACE, their genetic echoes are finally becoming visible.

The next big discovery about our ancient past may not come from a fossil in the ground.

It may already be inside us.

Reference: Zhang et al., “Recovering signatures of archaic hominin introgression using ancestral recombination graphs,” Science (2026), DOI: 10.1126/science.aef8874. Detail paper @ https://www.science.org/doi/10.1126/science.aef8874?

The TRACE repository (https://github.com/YulinZhang9806/trace) contains the Python package and command-line tools used to infer archaic admixture tracts from ancestral recombination graphs.

More @ http://www.ncbs.res.in/sowdhamini/groups_sowdhamini.htm

Address of the bookmark: https://sourceforge.net/projects/mimicree2/

Daniel A Dalquen, Maria Anisimova, Gaston H Gonnet, Christophe Dessimoz: ALF - A Simulation Framework for Genome Evolution. Mol Biol Evol, 29(4):1115-1123, April 2012.
http://mbe.oxfordjournals.org/content/29/4/1115

Address of the bookmark: http://alfsim.org/#index

Applications are invited for the position of Lecturer in Evolutionary Biology (Bioinformatics).

We are seeking a person with a relevant doctorate, and demonstrated potential to develop as an outstanding researcher and teacher in evolutionary bioinformatics in the Department of Zoology. The position affords an exciting opportunity for an emerging scholar to research and teach in a vibrant and diverse Department. The successful candidate will develop a transformative and collaborative research program, supporting the university's commitment to excellence in research.

Your skills and experience

A PhD with a background in analysis of high-throughput sequencing data and evolutionary biology.
Knowledge of and familiarity with a range of bioinformatics skills, concepts, and practices as they relate to the biology of animals, including genomic, transcriptomic and metabarcoding data analyses.
A strong interest, and experience, in research and teaching of bioinformatics and evolutionary genomics.
An ability to contribute to teaching and learning environments that support engagement of students and staff with bioinformatics and genomics.
Be committed to and or have established connections or track record of working with national and local bioinformaticians.
Be committed to being a productive collaborator with a track record of working collegially.
Further details

This is a confirmation-path (tenure track) position at the level of Lecturer. The successful candidate is expected to take up duties by 1 July 2021.

To see a full job description and to apply online go to: https://otago.taleo.net/careersection/2/jobdetail.ftl?job=2100342

Research Area

Investigating the role in disease of both the microbe and its host (i.e immune system failure), using genomics and systems biology-based approaches
Using genomics and network analysis to characterize disease outbreaks and their environmental/social/genetic causes, and
Identifying new anti-infective and immune modulating therapies/biomarkers.

Link @ http://www.brinkman.mbb.sfu.ca/

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 ]

For more information visit: http://www.snubi.org/TBC2013/