The universal ancestor

A genetic annealing model for the universal ancestor of all extant life is presented; the name of the model derives from its resemblance to physical annealing. The scenario pictured starts when “genetic temperatures” were very high, cellular entities (progenotes) were very simple, and information processing systems were inaccurate. Initially, both mutation rate and lateral gene transfer levels were elevated. The latter was pandemic and pervasive to the extent that it, not vertical inheritance, defined the evolutionary dynamic. As increasingly complex and precise biological structures and processes evolved, both the mutation rate and the scope and level of lateral gene transfer, i.e., evolutionary temperature, dropped, and the evolutionary dynamic gradually became that characteristic of modern cells. The various subsystems of the cell “crystallized,” i.e., became refractory to lateral gene transfer, at different stages of “cooling,” with the translation apparatus probably crystallizing first. Organismal lineages, and so organisms as we know them, did not exist at these early stages. The universal phylogenetic tree, therefore, is not an organismal tree at its base but gradually becomes one as its peripheral branchings emerge. The universal ancestor is not a discrete entity. It is, rather, a diverse community of cells that survives and evolves as a biological unit. This communal ancestor has a physical history but not a genealogical one. Over time, this ancestor refined into a smaller number of increasingly complex cell types with the ancestors of the three primary groupings of organisms arising as a result.

Comparative mapping of Andropogoneae: Saccharum L. (sugarcane) and its relation to sorghum and maize

Comparative genetic maps of Papuan Saccharum officinarum L. (2n = 80) and S. robustum (2n = 80) were constructed by using single-dose DNA markers (SDMs). SDM-framework maps of S. officinarum and S. robustum were compared with genetic maps of sorghum and maize by way of anchor restriction fragment length polymorphism probes. The resulting comparisons showed striking colinearity between the sorghum and Saccharum genomes. There were no differences in marker order between S. officinarum and sorghum. Furthermore, there were no alterations in SDM order between S. officinarum and S. robustum. The S. officinarum and S. robustum maps also were compared with the map of the polysomic octoploid S. spontaneum ‘SES 208’ (2n = 64, x = 8), thus permitting relations to homology groups (“chromosomes”) of S. spontaneum to be studied. Investigation of transmission genetics in S. officinarum and S. robustum confirmed preliminary results that showed incomplete polysomy in these species. Because of incomplete polysomy, multiple-dose markers could not be mapped for lack of a genetic model for their segregation. To coalesce S. officinarum and S. robustum linkage groups into homology groups (composed of homologous pairing partners), they were compared with sorghum (2n = 20), which functioned as a synthetic diploid. Groupings suggested by comparative mapping were found to be highly concordant with groupings based on highly polymorphic restriction fragment length polymorphism probes detecting multiple SDMs. The resulting comparative maps serve as bridges to allow information from one Andropogoneae to be used by another, for breeding, ecology, evolution, and molecular biology.

Prediction of operons in microbial genomes

Operon structure is an important organization feature of bacterial genomes. Many sets of genes occur in the same order on multiple genomes; these conserved gene groupings represent candidate operons. This study describes a computational method to estimate the likelihood that such conserved gene sets form operons. The method was used to analyze 34 bacterial and archaeal genomes, and yielded more than 7600 pairs of genes that are highly likely (P ≥ 0.98) to belong to the same operon. The sensitivity of our method is 30–50% for the Escherichia coli genome. The predicted gene pairs are available from our World Wide Web site http://www.tigr.org/tigr-scripts/operons/operons.cgi.

Comparison of circumsporozoite proteins from avian and mammalian malarias: biological and phylogenetic implications.

The circumsporozoite (CS) protein of malaria parasites (Plasmodium) covers the surface of sporozoites that invade hepatocytes in mammalian hosts and macrophages in avian hosts. CS genes have been characterized from many Plasmodium that infect mammals; two domains of the corresponding proteins, identified initially by their conservation (region I and region II), have been implicated in binding to hepatocytes. The CS gene from the avian parasite Plasmodium gallinaceum was characterized to compare these functional domains to those of mammalian Plasmodium and for the study of Plasmodium evolution. The P. gallinaceum protein has the characteristics of CS proteins, including a secretory signal sequence, central repeat region, regions of charged amino acids, and an anchor sequence. Comparison with CS signal sequences reveals four distinct groupings, with P. gallinaceum most closely related to the human malaria Plasmodium falciparum. The 5-amino acid sequence designated region I, which is identical in all mammalian CS and implicated in hepatocyte invasion, is different in the avian protein. The P. gallinaceum repeat region consists of 9-amino acid repeats with the consensus sequence QP(A/V)GGNGG(A/V). The conserved motif designated region II-plus, which is associated with targeting the invasion of liver cells, is also conserved in the avian protein. Phylogenetic analysis of the aligned Plasmodium CS sequences yields a tree with a topology similar to the one obtained using sequence data from the small subunit rRNA gene. The phylogeny using the CS gene supports the proposal that the human malaria P. falciparum is significantly more related to avian parasites than to other parasites infecting mammals, although the biology of sporozoite invasion is different between the avian and mammalian species.

Primate photopigments and primate color vision.

The past 15 years have brought much progress in our understanding of several basic features of primate color vision. There has been particular success in cataloging the spectral properties of the cone photopigments found in retinas of a number of primate species and in elucidating the relationship between cone opsin genes and their photopigment products. Direct studies of color vision show that there are several modal patterns of color vision among groupings of primates: (i) Old World monkeys, apes, and humans all enjoy trichromatic color vision, although the former two groups do not seem prone to the polymorphic variations in color vision that are characteristic of people; (ii) most species of New World monkeys are highly polymorphic, with individual animals having any of several types of dichromatic or trichromatic color vision; (iii) less is known about color vision in prosimians, but evidence suggests that at least some diurnal species have dichromatic color vision; and (iv) some nocturnal primates may lack color vision completely. In many cases the photopigments and photopigment gene arrangements underlying these patterns have been revealed and, as a result, hints are emerging about the evolution of color vision among the primates.

Neural-network-based classification of cognitively normal, demented, Alzheimer disease and vascular dementia from single photon emission with computed tomography image data from brain.

Single photon emission with computed tomography (SPECT) hexamethylphenylethyleneamineoxime technetium-99 images were analyzed by an optimal interpolative neural network (OINN) algorithm to determine whether the network could discriminate among clinically diagnosed groups of elderly normal, Alzheimer disease (AD), and vascular dementia (VD) subjects. After initial image preprocessing and registration, image features were obtained that were representative of the mean regional tissue uptake. These features were extracted from a given image by averaging the intensities over various regions defined by suitable masks. After training, the network classified independent trials of patients whose clinical diagnoses conformed to published criteria for probable AD or probable/possible VD. For the SPECT data used in the current tests, the OINN agreement was 80 and 86% for probable AD and probable/possible VD, respectively. These results suggest that artificial neural network methods offer potential in diagnoses from brain images and possibly in other areas of scientific research where complex patterns of data may have scientifically meaningful groupings that are not easily identifiable by the researcher.