Biology lost in megabits
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Rescooped by Joao Machado from Bioinformatics, Comparative Genomics and Molecular Evolution
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GigaScience | Full text | Ten recommendations for creating usable bioinformatics command line software

Bioinformatics software varies greatly in quality. In terms of usability, the command line interface is the first experience a user will have of a tool. Unfortunately, this is often also the last time a tool will be used. Here I present ten recommendations for command line software author’s tools to follow, which I believe would greatly improve the uptake and usability of their products, waste less user’s time, and improve the quality of scientific analyses.

Via Arjen ten Have
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Arjen ten Have's curator insight, August 12, 2014 11:55 AM

An old one but of good help. Do you code? Then do it good and in a way anyone can use it!

Rescooped by Joao Machado from Bioinformatics Software: Sequence Analysis
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GigaScience | User comments | Ten recommendations for creating usable bioinformatics command line software

Bioinformatics software varies greatly in quality. In terms of usability, the command line interface is the first experience a user will have of a tool. Unfortunately, this is often also the last time a tool will be used.

Via Mel Melendrez-Vallard
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Rescooped by Joao Machado from Journal of Molecular Biology
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Targeting ageing disorders

Targeting ageing disorders | Biology lost in megabits | Scoop.it
Ageing is a normal phenomenon which is characterised by several physical, psychological and social changes in a life of a human being. Recent research on ...

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Rescooped by Joao Machado from Bioinformatics, Comparative Genomics and Molecular Evolution
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Is Evolution Predictable?

Is Evolution Predictable? | Biology lost in megabits | Scoop.it

Stick insects show that evolution is more random than some biologists believed


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Arjen ten Have's curator insight, May 22, 2014 9:59 AM

Stick insects show that evolution is more random than some biologists believed. That is the conclusion of journal Science, I wonder. I would agree for this case but I also think it will really depend on the possibilities. Imagine a trait that involves only 1 gene and a trait that depends on 20 genes. It will be clear that if you put a constraint related to these two traits, in the simple case, evolution will have to change that one gene, whereas in second complex case there might me many solutions. I can make it stronger by restricting further the example: the one locus case needs to evolve an enzyme with a larger substrate binding cleft. Would we be really surprised to find enzymes with a larger substrate binding cleft?  The authors are correct in this case but it will always depend on the case. Certain cases will have a very restricted solution space whereas others might have a very large solution space.

Rescooped by Joao Machado from Amazing Science
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Evolution of new species requires only a few genetic changes

Evolution of new species requires only a few genetic changes | Biology lost in megabits | Scoop.it

Only a few genetic changes are needed to spur the evolution of new species—even if the original populations are still in contact and exchanging genes. Once started, however, evolutionary divergence evolves rapidly, ultimately leading to fully genetically isolated species, report scientists from the University of Chicago in the Oct 31 Cell Reports.

 

"Speciation is one of the most fundamental evolutionary processes, but there are still aspects that we do not fully understand, such as how the genome changes as one species splits into two," said Marcus Kronforst, Ph.D., Neubauer Family assistant professor of ecology and evolution, and lead author of the study.

 

To reveal genetic differences critical for speciation, Kronforst and his team analyzed the genomes of two closely related butterfly species, Heliconius cydno and H. pachinus, which only recently diverged. Occupying similar ecological habitats and able to interbreed, these butterfly species still undergo a small amount of genetic exchange.

 

The researchers found that this regular gene flow mutes genetic variants unimportant to speciation—allowing them to identify key genetic areas affected by natural selection. The butterfly species, they discovered, differed in only 12 small regions of their genomes, while remaining mostly identical throughout the rest. Eight of these coded for wing color patterning, a trait important for mating and avoiding predation, and under intense selection pressure, while the other four remain undescribed.

 

"These 12 spots appear to only function well in the environment their species occupies, and so are prevented from moving between gene pools, even though other parts of the genomes are swapped back and forth," Kronforst said.

 

The team also compared the genomes of these two groups to a third species, still closely related but further removed on an evolutionary time scale. Here, they found hundreds of genomic changes, indicating that the rate of genetic divergence accelerated rapidly after the initial changes took hold.

 

"Our work suggests that a few advantageous mutations are enough to cause a 'tug-of-war' between natural selection and gene flow, which can lead to rapidly diverging genomes," Kronforst said.


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Rescooped by Joao Machado from Plant Pathogenomics
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Mol Plant Pathol: Pseudogenization in pathogenic fungi with different host plants and lifestyles might reflect their evolutionary past (2013)

Mol Plant Pathol: Pseudogenization in pathogenic fungi with different host plants and lifestyles might reflect their evolutionary past (2013) | Biology lost in megabits | Scoop.it

Pseudogenes are genes with significant homology to functional genes, but contain disruptive mutations (DMs) leading to the production of non- or partially functional proteins. Little is known about pseudogenization in pathogenic fungi with different lifestyles. Here, we report the identification of DMs causing pseudogenes in the genomes of the fungal plant pathogens Botrytis cinerea, Cladosporium fulvum,Dothistroma septosporum, Mycosphaerella fijiensis, Verticillium dahliae and Zymoseptoria tritici. In these fungi, we identified 1740 gene models containing 2795 DMs obtained by an alignment-based gene prediction method. The contribution of sequencing errors to DMs was minimized by analyses of resequenced genomes to obtain a refined dataset of 924 gene models containing 1666 true DMs. The frequency of pseudogenes varied from 1% to 5% in the gene catalogues of these fungi, being the highest in the asexually reproducing fungus C. fulvum (4.9%), followed by D. septosporum (2.4%) and V. dahliae (2.1%). The majority of pseudogenes do not represent recent gene duplications, but members of multi-gene families and unitary genes. In general, there was no bias for pseudogenization of specific genes in the six fungi. Single exceptions were those encoding secreted proteins, including proteases, which appeared more frequently pseudogenized in C. fulvum than in D. septosporum. Most pseudogenes present in these two phylogenetically closely related fungi are not shared, suggesting that they are related to adaptation to a different host (tomato versus pine) and lifestyle (biotroph versus hemibiotroph).


Via Kamoun Lab @ TSL
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Arjen ten Have's curator insight, December 3, 2013 10:51 AM

Pseudogenes are among the poorly understood. Pseudogenes are not necessarily without function. Gene duplication results in functional redundancy. This can result in the complete los of selection or in functional diversification. Here pseudogenes are defined as genes with disruptive mutations, which is likely to results in loss of function. But still.... Pseudogenes are junk dna, junk is what we keep around, just in case you might have a function for it in the future. Plasticity!

 

I find the defintion of pseudogene a bit odd, but it makes sense.

Rescooped by Joao Machado from CBiB - Bordeaux Bioinformatics Center
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BMC Bioinformatics | Abstract | Sequencing error correction without a reference genome

BMC Bioinformatics | Abstract | Sequencing error correction without a reference genome | Biology lost in megabits | Scoop.it
Next (second) generation sequencing is an increasingly important tool for many areas of molecular biology, however, care must be taken when interpreting its output.

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