An improved technique for obtaining well-spread metaphases from plants with numerous large chromosomes

Preparations that contain well-spread metaphase chromosomes are critical for plant cytogenetic analyses including chromosome counts, banding procedures, in situ hybridization, karyotyping and construction of ideograms. Chromosome spreading is difficult for plants with large and numerous chromosomes. We report here a technique for obtaining cytoplasm-free, well-spread metaphases from two Amaryllidaceae species: Sprekelia formosissima (2n = 120) and Hymenocallis howardii (2n = 96). The technique has three main steps: 1) pretreatment to cause chromosome condensation, 2) dripping onto tilted slides coated with a thin layer of pure acetic acid and 3) application of steam and acetic acid to produce cytoplasmic hydrolysis, which spreads the chromosomes.     

Materials for a study in animal competition

The incidence of the sewage fly, Psychoda alternata Say, breeding almost free from other insect competitors in a bacteria bed at Huddersfield is examined. Its general seasonal trend is marked by periods of peak output explained on the theory that there are two successions of generations running persistently and alternating with one another. Such behaviour has previously been demonstrated for another sewage fly, Spaniotoma minima , and has been shown to be instituted by irregular temperatures in autumn and spring. In Psychoda alternata a special type of intraspecific competition is set-up in the warmer months when the cycles are rapid, for the larvae of one succession must start life in a bed just depleted of food by the other. Therefore large and small outbursts of the fly tend to alternate. The discharges of solids from the bed have a detailed periodicity corresponding to the alternations in the successions of the fly.     

<Emphasis Type="Italic">Scoredist</Emphasis>: A simple and robust protein sequence distance estimator

Background  

Distance-based methods are popular for reconstructing evolutionary trees thanks to their speed and generality. A number of methods exist for estimating distances from sequence alignments, which often involves some sort of correction for multiple substitutions. The problem is to accurately estimate the number of true substitutions given an observed alignment. So far, the most accurate protein distance estimators have looked for the optimal matrix in a series of transition probability matrices, e.g. the Dayhoff series. The evolutionary distance between two aligned sequences is here estimated as the evolutionary distance of the optimal matrix. The optimal matrix can be found either by an iterative search for the Maximum Likelihood matrix, or by integration to find the Expected Distance. As a consequence, these methods are more complex to implement and computationally heavier than correction-based methods. Another problem is that the result may vary substantially depending on the evolutionary model used for the matrices. An ideal distance estimator should produce consistent and accurate distances independent of the evolutionary model used.