Prosimian hemoglobins: IV. The structural difference responsible for the hemoglobin phenotype of Lemur catta.

The ring-tailed lemur, Lemur catta, shows a two-component hemoglobin phenotype after alkaline electrophoresis. A difference in the amino acid sequence of the isolated α-globins was observed at position 15 (α I-Gly, α II-Lys) and can account for the electrophoretic pattern of two hemoglobin components. Only one other amino acid difference was found in the sequence of the two globin chains: a neutral substitution occurs at position 53 (α I-Gly, α II-Ala).

Prosimian hemoglobins. III. The primary structures of the duplicated alpha-globin chains of Lemur variegatus.

The amino acid sequences of the alpha chains of hemoglobins purified from Lemur variegatus erythrocytes have been determined. The sequences were determined primarily from peptides generated from treatment of the isolated alpha chains with cyanogen bromide or warm formic acid. The ordering of the peptides from both alpha globins was based on the homology between lemur hemoglobins and those of other primates.

Demographic components of gene frequency change in free-ranging macaques on Cayo Santiago.

Gene frequency profiles from January 1973 to January 1977 for three polymorphic loci were examined in Cayo Santiago rhesus social groups. The effects of demographic components (i.e.

Models for lineal effects in rhesus group fissions.

Gene distributions in daughter groups produced by three rhesus monkey group fissions are analyzed. Data employed are for the Tf, 6PGD, and CA II electrophoretic marker systems in the fissions producing new daughter groups F and M, F and O, and J and N in the Cayo Santiago rhesus colony. Wide variations in FST values were observed among the different markers in the various fissions.

Statistical methods for analyzing data on daily activity cycles of primates.

Many field studies on primates have recently been carried out in which quantitative data have been collected using instantaneous scan sampling techniques. However, data collected in this manner are difficult to analyze statistically because of the problem of independence of samples, and a number of investigators have analyzed such data incorrectly. In this paper, we evaluate such analyses and suggest alternative techniques that may be more appropriate.