Evolution, Variation, Development, and Strains of Artificial Life in the Reading Queue

This content is cross-posted to my micro-blog, Tumbld Thoughts. Many new papers on adaptation and evolution, plus a call for conference participation in Artifical Life XIV.

New Readings on Short- and Long-term Evolution from the Reading Queue

Here are a few new papers on experimental evolution. The first is a paper from Jeffrey Barrick and Rich Lenski [1], who utilize the long-term evolution experiment to look at genome dynamics during bacterial evolution [2]. The first figure shows the types of mutations observed during evolution (occurring on the scale of 10³ generations). The second demonstrates the signatures of optimization, innovation, and epistasis in evolutionary change. Interestingly, a genomic analysis of bacterial populations from the same project suggests that adaptation proceeds without reaching so-called fitness peaks (which is predicted by theory to limit the fitness advantage of a given genotype).

The second paper is from Ted Garland, and involves using artificial selection [4] in mice to find the limits of evolution (or evolvability) over 10-100 generations [5, 6]. A wheel running task is used to assess physical performance. The first figure shows baseline performance, maximum evolved performance, and post-peak performance given genetic (G), environmental (E), and GxE sources of variation. The second figure shows differences in wheel running performance between male and female mice over 30 generations. In this case, behavioral analysis  reveals distinct limits to advantages gained from artificial selection (which are not always due to adaptation). 

New Readings on Human Variation from the Reading Queue

Here are four new papers on human genomic variation. The first [7] is a review of genome mosaicism, or variation across cells in the same human body. Mosaicism results from errors in either chromosome segregation during mitosis or DNA replication. In neurons from the frontal cortex [8], mosaicism is responsible for variation in chromosomal complements and copy number variants (CNVs). This variation comes in the form of aneuploidies, retrotransposons, and large-scale CNV differences (in 13-41% of neurons sampled). 

In [9], variation in chromatin states across the genome is explored. One finding suggests that variable regions are enriched in SNPs relative to nonvariable regions, which may be due to negative selection. The expression of heterozygous SNPs with allele-specific signals are highest for active marks. These is also variation in methylation switches (active/repressed or active/weakly active states) which results in enhancer and core promoter-specific states.

Finally, functional genomic elements can be more explicitly linked to chromatin signatures. This was done in [10] by finding the cis-regulatory variants that most affect chromatin states. In this study, five post-transcriptional modifiers and three transcription factors were used to show these trends across 14 individuals. It was found that allele-specific patterns of association (between genomic function and chromatin regulation) exist.

Calls for Artificial Life

If you enjoy creating artificial life, and want to write an academic paper about it (8 page, single-spaced limit, IEEE format), then you will want to submit your work to the Artificial Life 14 conference, being held Summer 2014 in NYC. Submission deadline (full papers) is March 31.

Topics include: bio-inspired robotics, cellular automata and artificial chemistries, synthetic life, embodied systems, collective behavioral dynamics, ecological/social/evolutionary dynamics, and the art and philosophy of Artificial Life. There is a separate call for workshops/tutorials (due January 15) and a Science Visualization competition (applications due February 1).

And, last but not least, some new Developmental Biology.....

Last but not least, here is a nice article by Carl Zimmer [11] summarizing the cutting-edge work being done on understanding the potential role of senescent cells in embryonic development. The excellent picture shows a mouse embryo (E15) with the areas of senescent cells stained in blue.

NOTES:

[1] Lenski's long-term evolution experiment was recently profiled in Science. Listen to this podcast for more: Crespi, S.   Podcast Interview: Richard Lenski. Science Express, November 14 (2013).

[2] Barrick, J.E. and Lenski, R.E.   Genome dynamics during experimental evolution. Nature Reviews Genetics, 14 827-839 (2013).

[3] Wiser, M.J., Ribeck, N., and Lenski, R.E.   Long-Term Dynamics of Adaptation in Asexual Populations. Science, DOI: 10.1126/science. 1243357.

[4] Postma, E., Visser, J., Van Noordwijk, A.J.   Strong artificial selection in the wild results in predicted small evolutionary change. Journal of Evolutionary Biology, 20, 1823–1832 (2007). 

[5] Careau, V., Wolak, M.E., Carter, P.A., and Garland, T.   Limits to Behavioral Evolution: the quantitative genetics of a complex trait under directional selection. Evolution, 67(11), 3102-3119 (2013).

[6] Barton, N. and Partridge, L.   Limits to natural selection. BioEssays, 22, 1075-1084 (2000).

For a short primer on the concept, please see this primer from Understanding Evolution.

[7] Lupski, J.R. et.al  One Human, Multiple Genomes: Genome Mosaicism. Science, 341, 358-359 (2013).

[8] McConnell, M.J. et.al   Mosaic Copy Number Variation in Human Neurons. Science, 342, 631-637 (2013).

[9] Kasowski, M. et.al  Extensive Variation in Chromatin States Across Humans. 750-752. Science, 342, 750 (2013).

[10] Kilpinen, H. et.al   Chromatin Structure, and Transcription Coordinated Effects of Sequence Variation on DNA Binding. Science, 342, 744-747 (2013).

[11] Zimmer, C.   Signs of Aging, Even in the Embryo. NYT Science, November 21 (2013).