posted by Victor Hanson-Smith
1. Stochasticity versus determinism in development: a false dichotomy? Magdalena Zernicka-Goetz, et al., Nature Reviews Genetics, November 2010
The developmental trajectory (from embryo to death) of all multicellular organisms involves cell fate decisions, in which pluripotent, multipotent, and bipotent cells differentiate into specific cell types. Cell fate decisions are usually controlled by spatiotemporal variation in protein expression levels; for example, the expression levels of transcription factors CDX2 and OCT4 in inchoate mouse embryos determines if the mouse cell becomes an inner-cell mass (ICM) cell or a trophectoderm (TE) cell. The cells fated to be ICM and TE create a seemingly random heterogenous (“salt-and-pepper”) spatial pattern, leading researchers to conclude that the earliest fate decisions occur stochastically and without regulatory bias.
In this short NRG opinion piece, the authors assert that many seemingly stochastic developmental processes could actually be completely deterministic. In their words:
. . . a multi-step process with deterministic causation can be so complicated as to be practically unpredictable. . . The outcome then seems lawless, but may not be.
The authors ask, “to what extent is the non-deterministic ‘noisy’ component of developmental control due to true, inevitable ontological randomness and to what extent is it due to epistemological unpredictability because of missing information on the complicated history of cells?” Although the answer remains elusive for now, this general philosophical framework should guide future investigations about molecular developmental determinants. I would like to curate a small reading list on this topic, and I encourage you suggest research papers (in the comments field below) that demonstrate regulatory determinism within seemingly-random developmental trajectories.
Zernicka-Goetz M, & Huang S (2010). Stochasticity versus determinism in development: a false dichotomy? Nature reviews. Genetics, 11 (11), 743-4 PMID: 20877326
2. Species delimitation using dominant and codominant multilocus markers, Bernhard Hausdorf and Christian Hennig, Systematic Biology, October 2010
How do we determine the genetic boundaries between species? The problem of species delimitation can be challenging due to admixture between incipient sister species and due to discordance between gene trees and species. For example, species in the earliest stages of speciation will differ by only a few genes (presumably genes responsible for reproductive isolation or differential adaptation), and it can be difficult to detect speciation in these situations.
In this paper, the authors propose a method for species delimitation based on Gaussian clustering (also known as mixture modeling). They compare their method to results from the programs STRUCTURE (Pritchard 2000) and STRUCTURAMA (Huelsenbeck and Andolfatto 2007), which group individuals such that Hardy-Weinberg equilibrium is maximized within each cluster.
The authors observed the accuracy of species delimitation depends on the dominance of genetic markers. The authors analyzed four AFLP datasets, two of which contain dominant genetic markers and two containing co-dominant markers. When using dominant markers, Gaussian clustering was the most accurate method; when using codominant markers, STRUCTURAMA was the most accurate. Based on these preliminary results, it seems that Gaussian clustering is a useful method, but there is no single panacea for the problem of species delimitation.
Hausdorf B, & Hennig C (2010). Species delimitation using dominant and codominant multilocus markers. Systematic biology, 59 (5), 491-503 PMID: 20693311
3. Selection upon Genome Architecture: Conservation of Functional Neighborhoods with Changing Genes, Fatima Al-Shahrour et al., PLoS Computational Biology, October 2010
The authors compared the genomes of eight Eukaryotes, and observed significant evidence supporting the “functional neighborhood” hypothesis, in which genes of related function tend to cluster together in tight genomic regions. I think the most exciting result is this:
. . .there is a significantly higher degree of coexpression in genes belonging to a given functional class [as determined by GO terms] when they are packed within a functional neighborhood than when they are elsewhere in the genome. This result, along with the lack of a significant relative enrichment of tandem duplications. . . points to coexpression as the most plausible driving force for the existence of functional neighborhoods.
The paper includes several other interesting points of discussion, including a syntentic analysis between human and chimp genomes. I think this paper could have been stronger if the authors created syntentic maps for all pairwise combinations of the eight species, but I realize this is an ambitious (and perhaps currently impossible?) task.
The Achille’s heal of their analysis is the reliance on GO terms. Based on these terms, the authors find functional neighborhoods that have been phylogenetically conserved. For example, the functional neighborhood for coagulation genes has been conserved across all fish (including birds and mammals). This result is very appealing, but I wonder if anyone has investigated the accuracy and/or general usefulness of the GO terms? If you can suggest good papers, please leave a comment down below.
Al-Shahrour F, Minguez P, Marqués-Bonet T, Gazave E, Navarro A, & Dopazo J (2010). Selection upon genome architecture: conservation of functional neighborhoods with changing genes. PLoS computational biology, 6 (10) PMID: 20949098