Genetic Prediction: What are the Limits?

The spectre of determinism stalks many of the concerns surrounding the impact of genetic research into both disease and normal behaviour. The ability accurately to predict a person's actions would certainly have profound implications for notions of individuality and free will. But to what extent will the current explosion in genetic research provide more accurate predictors than have been available for millennia in the form of wealth, social status and perceived family resemblance? The genetic research program is at too early a stage to answer this question with confidence, but various indicators tend to point in the same direction: the predictive ability of genetic analysis will generally be low. This conclusion runs counter to widely perceived popular notions. The deconstruction of genetic determinism is an essential safeguard against the real concern that genetic information may be used for discrimination by unscrupulous powers.     

What are the implications of evolvable molecules?

James Shapiro’s view of evolution is inspired by looking at the molecular mechanisms of mutation. Finding these systems to be intelligent and the mutations non-gradual, Shapiro concludes that neither the role of DNA in development, nor and the role of natural selection in evolution are what we thought them to be. The cases discussed are interesting and may require some modification of theory in biology, but this reviewer finds many of Shapiro’s conclusions unwarranted.     

What are the baselines for protein fold recognition?

MOTIVATION: What constitutes a baseline level of success for protein fold recognition methods? As fold recognition benchmarks are often presented without any thought to the results that might be expected from a purely random set of predictions, an analysis of fold recognition baselines is long overdue. Given varying amounts of basic information about a protein-ranging from the length of the sequence to a knowledge of its secondary structure-to what extent can the fold be determined by intelligent guesswork? Can simple methods that make use of secondary structure information assign folds more accurately than purely random methods and could these methods be used to construct viable hierarchical classifications? EXPERIMENTS PERFORMED: A number of rapid automatic methods which score similarities between protein domains were devised and tested. These methods ranged from those that incorporated no secondary structure information, such as measuring absolute differences in sequence lengths, to more complex alignments of secondary structure elements. Each method was assessed for accuracy by comparison with the Class Architecture Topology Homology (CATH) classification. Methods were rated against both a random baseline fold assignment method as a lower control and FSSP as an upper control. Similarity trees were constructed in order to evaluate the accuracy of optimum methods at producing a classification of structure. RESULTS: Using a rigorous comparison of methods with CATH, the random fold assignment method set a lower baseline of 11% true positives allowing for 3% false positives and FSSP set an upper benchmark of 47% true positives at 3% false positives. The optimum secondary structure alignment method used here achieved 27% true positives at 3% false positives. Using a less rigorous Critical Assessment of Structure Prediction (CASP)-like sensitivity measurement the random assignment achieved 6%, FSSP-59% and the optimum secondary structure alignment method-32%. Similarity trees produced by the optimum method illustrate that these methods cannot be used alone to produce a viable protein structural classification system. CONCLUSIONS: Simple methods that use perfect secondary structure information to assign folds cannot produce an accurate protein taxonomy, however they do provide useful baselines for fold recognition. In terms of a typical CASP assessment our results suggest that approximately 6% of targets with folds in the databases could be assigned correctly by randomly guessing, and as many as 32% could be recognised by trivial secondary structure comparison methods, given knowledge of their correct secondary structures.     

What are the genuine action potentials in plants?

This is a comment on the paper by Pyatygin in this issue [Biophysics 53(1), 81–86 (2008)], indicating some points that should be clarified to comprehensively assess the apparent diversity of plant electrical signaling.     

What are the organismic elements of vegetation science?

The recent inclusion of communities of planktonic algae and microbial crusts into the system of European vegetation types is critically discussed. It is argued that formal vegetation classification should be limited to plant taxa represented by macroscopic individuals within a plot, including all vascular plants, bryophytes, lichens, charophyta and macrophytic chlorophyta, rhodophyta or phaeophyta. In the interest of comparability and methodological stringency, all microscopic algae and all prokaryotes, including cyanobacteria, and the habitats dominated by such microorganisms (e.g. plankton, biofilms and crusts), should be excluded from vegetation classification.     

What are decision trees?

Decision trees have been applied to problems such as assigning protein function and predicting splice sites. How do these classifiers work, what types of problems can they solve and what are their advantages over alternatives?     

What are cultural attractors?

Concepts from cultural attractor theory are now used in domains far from their original home in anthropology and cultural evolution. Yet these concepts have not been consistently characterised. I here distinguish four ways in which the cultural attractor concept has been used and identify three kinds of factors of attraction typically appealed to. Clarifying these explanatory concepts identifies problems and ambiguities in the work of cultural epidemiologists and commentators alike.     

What are housekeeping genes?

The concept of “housekeeping gene” has been used for four decades but remains loosely defined. Housekeeping genes are commonly described as “essential for cellular existence regardless of their specific function in the tissue or organism”, and “stably expressed irrespective of tissue type, developmental stage, cell cycle state, or external signal”. However, experimental support for the tenet that gene essentiality is linked to stable expression across cell types, conditions, and organisms has been limited. Here we use genome-scale functional genomic screens together with bulk and single-cell sequencing technologies to test this link and optimize a quantitative and experimentally validated definition of housekeeping gene. Using the optimized definition, we identify, characterize, and provide as resources, housekeeping gene lists extracted from several human datasets, and 10 other animal species that include primates, chicken, and C. elegans. We find that stably expressed genes are not necessarily essential, and that the individual genes that are essential and stably expressed can considerably differ across organisms; yet the pathways enriched among these genes are conserved. Further, the level of conservation of housekeeping genes across the analyzed organisms captures their taxonomic groups, showing evolutionary relevance for our definition. Therefore, we present a quantitative and experimentally supported definition of housekeeping genes that can contribute to better understanding of their unique biological and evolutionary characteristics.