A transient species of poly(A)+ RNA detected by a myosin heavy chain cDNA probe in muscle cell culture during terminal differentiation

Primary cell cultures were prepared from breast muscles of 11 day 4 hour-embryonic chicks. Cytoplasmic RNAs were isolated from the cultured cells at various time intervals from day 3 to day 8. A [P32] DNA probe complementary to messenger RNA of myosin heavy chain was used to hybridize with the RNAs after gel electrophoresis. A transient species of polyadenylated RNA with a decreased mobility in electrophoresis was detected during a period of time when contractions of syncytial fibers were first observed.     

Variability and genetics of spacer DNA sequences between the ribosomal-RNA genes of hexaploid wheat (Triticum aestivum)

Summary Using restriction enzyme digests of genomic DNA extracted from the leaves of 25 hexaploid wheat (Triticum aestivum L. em. Thell.) cultivars and their hybrids, restriction fragment length polymorphisms of the spacer DNA which separates the ribosomal-RNA genes have been examined. (From one to three thousand of these genes are borne on chromosomes 1B and 6B of hexaploid wheat). The data show that there are three distinct alleles of the 1B locus, designated Nor-B1a, Nor-B1b, and Nor-B1c, and at least five allelic variants of the 6B locus, designated Nor-B2a, Nor-B2b, Nor-B2c, Nor-B2d, and Nor-B2e. A further, previously reported allele on 6B has been named Nor-B2f. Chromosome 5D has only one allelic variant, Nor-D3. Whereas the major spacer variants of the 1B alleles apparently differ by the loss or gain of one or two of the 133 bp sub-repeat units within the spacer DNA, the 6B allelic variants show major differences in their compositions and lengths. This may be related to the greater number of rDNA repeat units at this locus. The practical implications of these differences and their application to wheat breeding are discussed.     

Heat stress in the presence of low RNA polymerase activity increases chromosome copy number of Escherichia coli

Summary A temperature shift-up accompanied by a reduction in RNA polymerase activity in Escherichia coli causes an increased rate of initiation leading to a 1.7- to 2.2-fold increase in chromosome copy number. A temperature shift-up without a reduction in polymerase activity induces only a transient non-scheduled initiation of chromosome replication caused by heat shock with no detectable effect on chromosome copy number.     

Role of methyl groups in dynamics and evolution of biomolecules

Recent studies have discovered strong differences between the dynamics of nucleic acids (RNA and DNA) and proteins, especially at low hydration and low temperatures. This difference is caused primarily by dynamics of methyl groups that are abundant in proteins, but are absent or very rare in RNA and DNA. In this paper, we present a hypothesis regarding the role of methyl groups as intrinsic plasticizers in proteins and their evolutionary selection to facilitate protein dynamics and activity. We demonstrate the profound effect methyl groups have on protein dynamics relative to nucleic acid dynamics, and note the apparent correlation of methyl group content in protein classes and their need for molecular flexibility. Moreover, we note the fastest methyl groups of some enzymes appear around dynamical centers such as hinges or active sites. Methyl groups are also of tremendous importance from a hydrophobicity/folding/entropy perspective. These significant roles, however, complement our hypothesis rather than preclude the recognition of methyl groups in the dynamics and evolution of biomolecules.     

Parameter estimation for the distribution of single cell lag times

In Quantitative Microbial Risk Assessment, it is vital to understand how lag times of individual cells are distributed over a bacterial population. Such identified distributions can be used to predict the time by which, in a growth-supporting environment, a few pathogenic cells can multiply to a poisoning concentration level.We model the lag time of a single cell, inoculated into a new environment, by the delay of the growth function characterizing the generated subpopulation. We introduce an easy-to-implement procedure, based on the method of moments, to estimate the parameters of the distribution of single cell lag times. The advantage of the method is especially apparent for cases where the initial number of cells is small and random, and the culture is detectable only in the exponential growth phase.     

Can transposable element copy number distribution parameters be estimated from natural populations of Drosophila melanogaster?

The copy frequency distribution of a transposable element family in a Drosophila melanogaster natural population is generally characterised by the values of the Charlesworths' model parameters α and β (Charlesworth & Charlesworth, 1983). The estimation of these parameters is made using the observed distribution of the occupied sites in a population sample. Several results have been interpreted as due either to the influence of stochastic factors or to deterministic factors (transposition, excision, selection…). The accuracy of this method was tested by estimations performed on samples from simulated populations. The results show that with the sample size usually used for natural population studies, the confidence intervals are too large to reasonably deduce either the element copy number distribution or the values of transposition and excision rate and selective coefficients.     

Confidence Intervals for the Risk Ratio in Cohort Studies under Inverse Sampling

Three simple interval estimates for the risk ratio in inverse sampling are considered. The first two interval estimates are derived on the basis of Fieller's Theorem and the delta method with the logarithmic transformation, respectively. The third interval estimate is derived on the basis of an F-test statistic proposed by BENNETT (1981) for testing equal probabilities of a disease between two comparison groups when the disease is rare. To evaluate the performance of these three methods, a Monte Carlo simulation is used to compare the actual coverage probability with the nominal confidence level for each method and to estimate the expected length of the corresponding confidence interval in a variety of situations. On the basis of the results found in the simulation, we have concluded that the method with the logarithmic transformation is either equivalent to or better than the other two methods for all situations considered here.