On blocking rules for the bootstrap with dependent data

We address the issue of optimal block choice in applicationsof the block bootstrap to dependent data. It is shown that optimalblock size depends significantly on context, being equal ton^1/3, n^1/4 and n^1/5 in the cases of variance or bias estimation,estimation of a onesided distribution function, and estimationof a two-sided distribution function, respectively. A clearintuitive explanation of this phenomenon is given, togetherwith outlines of theoretical arguments in specific cases. Itis shown that these orders of magnitude of block sizes can beused to produce a simple, practical rule for selecting blocksize empirically. That technique is explored numerically.     

Conditional Maximum Likelihood Estimation Following a Group Sequential Test

We consider estimation after a group sequential test. An estimator that is unbiased or has small bias may have substantial conditional bias (Troendle and Yu, 1999, Coburger and Wassmer, 2001). In this paper we derive the conditional maximum likelihood estimators of both the primary parameter and a secondary parameter, and investigate their properties within a conditional inference framework. The method applies to both the usual and adaptive group sequential test designs. (© 2004 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

Nature of selective constraints on synonymous codon usage of rice differs in GC-poor and GC-rich genes

Synonymous codon usage and cellular tRNA abundance are thought to be co-evolved in optimizing translational efficiencies in highly expressed genes. Here in this communication by taking the advantage of publicly available gene expression data of rice and Arabidopsis we demonstrated that tRNA gene copy number is not the only driving force favoring translational selection in all highly expressed genes of rice. We found that forces favoring translational selection differ between GC-rich and GC-poor classes of genes. Supporting our results we also showed that, in highly expressed genes of GC-poor class there is a perfect correspondence between majority of preferred codons and tRNA gene copy number that confers translational efficiencies to this group of genes. However, tRNA gene copy number is not fully consistent with models of translational selection in GC-rich group of genes, where constraints on mRNA secondary structure play a role to optimize codon usage in highly expressed genes.     

Targeted expression of redesigned and codon optimised synthetic gene leads to recrystallisation inhibition and reduced electrolyte leakage in spring wheat at sub-zero temperatures

Antifreeze proteins (AFPs) adsorb to ice crystals and inhibit their growth, leading to non-colligative freezing point depression. Crops like spring wheat, that are highly susceptible to frost damage, can potentially be made frost tolerant by expressing AFPs in the cytoplasm and apoplast where ice recrystallisation leads to cellular damage. The protein sequence for HPLC-6 α-helical antifreeze protein from winter flounder was rationally redesigned after removing the prosequences in the native protein. Wheat nuclear gene preferred amino acid codons were used to synthesize a recombinant antifreeze gene, rAFPI. Antifreeze protein was targeted to the apoplast using a Murine leader peptide sequence from the mAb24 light chain or retained in the endoplasmic reticulum using C-terminus KDEL sequence. The coding sequences were placed downstream of the rice Actin promoter and Actin-1 intron and upstream of the nopaline synthase terminator in the plant expression vectors. Transgenic wheat lines were generated through micro projectile bombardment of immature embryos of spring wheat cultivar Seri 82. Levels of antifreeze protein in the transgenic lines without any targeting peptide were low (0.06–0.07%). The apoplast-targeted protein reached a level of 1.61% of total soluble protein, 90% of which was present in the apoplast. ER-retained protein accumulated in the cells at levels up to 0.65% of total soluble proteins. Transgenic wheat line T-8 with apoplast-targeted antifreeze protein exhibited the highest levels of antifreeze activity and provided significant freezing protection even at temperatures as low as −7°C.     

Lactic acid bacteria as prime candidates for codon optimization

In species having a strong correlation of expressivity and codon bias it has been shown that heterologous expression can be optimized by changing codons of the introduced gene towards the set of codons that the host organism naturally uses in its highly expressed genes. Even though two lactic acid bacteria are fully sequenced, there are no reports on attempts of codon optimization in the literature. In this report it is demonstrated that codons used in highly expressed genes tend to differ from the codons in lowly expressed genes, and that there is a strong correlation of codon bias and empirical expressivity (codon adaptation index) in Lactococcus lactis and Lactobacillus plantarum. This strongly suggests that codon optimization strategies could be applied to expression systems with lactic acid bacteria as producer strains. A good example of a candidate for codon optimization is the mouse interleukin-2 gene, which in its natural form has an extremely low codon adaptation index for expression in Lc. lactis.     

Codon Bias and Mutability in HIV Sequences

A survey of the patterns of synonymous codon preference in the HIV env gene reveals a correlation between the codon bias and the mutability requirements of different regions of the protein. At hypervariable regions in gp120 one finds a greater proportion of codons that tend to mutate nonsynonymously, but to a target that is similar in hydrophobicity and volume. We argue that this strategy results from a compromise between the selective pressure placed on the virus by the induced immune response, which favors amino acid substitutions in the complementarity determining regions, and the negative selection against missense mutations that violate structural constraints of the env protein. Received: 9 June 1997 / Accepted: 25 May 1998     

The Impact of Message Mutation on the Fitness of a Genetic Code

The Standard Genetic Code is organized such that similar codons encode similar amino acids. One explanation suggested that the Standard Code is the result of natural selection to reduce the fitness ``load' that derives from the mutation and mistranslation of protein-coding genes. We review the arguments against the mutational load-minimizing hypothesis and argue that they need to be reassessed. We review recent analyses of the organization of the Standard Code and conclude that under cautious interpretation they support the mutational load-minimizing hypothesis. We then present a deterministic asexual model with which we study the mode of selection for load minimization. In this model, individual fitness is determined by a protein phenotype resulting from the translation of a mutable set of protein-coding genes. We show that an equilibrium fitness may be associated with a population with the same genetic code and that genetic codes that assign similar codons to similar amino acids have a higher fitness. We also show that the number of mutant codons in each individual at equilibrium, which determines the strength of selection for load minimization, reflects a long-term evolutionary balance between mutations in messages and selection on proteins, rather than the number of mutations that occur in a single generation, as has been assumed by previous authors. We thereby establish that selection for mutational load minimization acts at the level of an individual in a single generation. We conclude with comments on the shortcomings and advantages of load minimization over other hypotheses for the origin of the Standard Code. Received: 4 April 2001 / Accepted: 22 October 2001