No abstract

No abstract

The use of the Grewal-Smith statistic in measuring biological distance among skeletal population samples has been questioned since it was first applied to human populations. Recently, in an attempt to stabilize the variance of the Grewal-Smith statistic for use with non-metric analysis, Sjøhivold ('73) and Green and Suchey ('76) have introduced corrections and alternative transformations which may enhance the meaning of biological distance among population samples. Their recommendations improve the statistics for specific variable ranges; i.e., small sample size and low trait frequencies. Thirteen equations representing Grewal-Smith, Freeman-Tukey, Anscombe, and Bartlett transformations and/or corrections, were compared using rank order correlation statistics on actual biological distances generated by real population data as presented in existing literature. Results from testing these actual distance models show little variation between equations based on the populational data sets used. Based on these findings, the distance model resulting from the Grewal-Smith statistic is not inferior to the more sophisticated models, although the latter may be superior allowing specific improvements for small sample size and/or low trait frequencies.

Protein coding genes can contain specific motifs within their nucleotide sequence that function as a signal for various biological pathways. The presence of such sequence motifs within a gene can have beneficial or detrimental effects on the phenotype and fitness of an organism, and this can lead to the enrichment or avoidance of this sequence motif. The degeneracy of the genetic code allows for the existence of alternative synonymous sequences that exclude or include these motifs, while keeping the encoded amino acid sequence intact. This implies that locally, there can be a selective pressure for preferentially using a codon over its synonymous alternative in order to avoid or enrich a specific sequence motif. This selective pressure could –in addition to mutation, drift and selection for translation efficiency and accuracy– contribute to shape the codon usage bias. In this review, we discuss patterns of avoidance of (or enrichment for) the various biological signals contained in specific nucleotide sequence motifs: transcription and translation initiation and termination signals, mRNA maturation signals, and antiviral immune system targets. Experimental data on the phenotypic or fitness effects of synonymous mutations in these sequence motifs confirm that they can be targets of local selection pressures on codon usage. We also formulate the hypothesis that transposable elements could have a similar impact on codon usage through their preferred integration sequences. Overall, selection on codon usage appears to be a combination of a global selection pressure imposed by the translation machinery, and a patchwork of local selection pressures related to biological signals contained in specific sequence motifs.