DNA sequence analysis of a 5.27-kb direct repeat occurring adjacent to the regions of S-episome homology in maize mitochondria.

The DNA sequence of the 5270-bp repeated DNA element from the mitochondrial genome of the fertile cytoplasm of maize has been determined. The repeat is a major site of recombination within the mitochondrial genome and sequences related to the R1(S1) and R2(S2) linear episomes reside immediately adjacent to the repeat. The terminal inverted repeats of the R1 and R2 homologous sequences form one of the two boundaries of the repeat. Frame-shift mutations have introduced 11 translation termination codons into the transcribed S2/R2 URFI gene. The repeated sequence, though recombinantly active, appears to serve no biological function.     

Growth of Chikungunya Virus in Baby Hamster Kidney Cell (BHK-21-Clone 13) Suspension Cultures

This report describes the methods used to obtain high titers of chikungunya virus with suspension cultures of BHK-21-clone 13 cells. The cells were grown at 37 C to a cell concentration of 10(6) to 2 x 10(6) per ml. After maximum cell growth, the cells were inoculated with chikungunya virus at a multiplicity of 1 to 2 50% suckling mouse intracerebral lethal doses (SMICLD(50)) per cell in the spent Eagle's minimum essential medium for suspension cultures (MEMS), or the cell cultures were centrifuged at 200 x g and resuspended in either fresh MEMS or medium 199 prior to inoculation. The medium used had no effect on virus titer. The inoculated cultures were incubated at 34 C until the cell viability dropped to 30%, which usually occurred 28 to 30 hr postinoculation. After these procedures, chikungunya virus titers of log(10) 10.3 to 11.8 SMICLD(50) per ml were obtained.     

Sensitivity of lod scores to changes in diagnostic status.

This paper investigates effects on lod scores when one individual in a data set changes diagnostic or recombinant status. First we examine the situation in which a single offspring in a nuclear family changes status. The nuclear-family situation, in addition to being of interest in its own right, also has general theoretical importance, since nuclear families are "transparent"; that is, one can track genetic events more precisely in nuclear families than in complex pedigrees. We demonstrate that in nuclear families log10 [(1-theta)/theta] gives an upper limit on the impact that a single offspring's change in status can have on the lod score at that recombination fraction (theta). These limits hold for a fully penetrant dominant condition and fully informative marker, in either phase-known or phase-unknown matings. Moreover, log10 [(1-theta)/theta] (where theta denotes the value of theta at which Zmax occurs) gives an upper limit on the impact of a single offspring's status change on the maximum lod score (Zmax). In extended pedigrees, in contrast to nuclear families, no comparable limit can be set on the impact of a single individual on the lod score. Complex pedigrees are subject to both stabilizing and destabilizing influences, and these are described. Finally, we describe a "sensitivity analysis," in which, after all linkage analysis is completed, every informative individual in the data set is changed, one at a time, to see the effect which each separate change has on the lod scores. The procedure includes identifying "critical individuals," i.e., those who would have the greatest impact on the lod scores, should their diagnostic status in fact change. To illustrate use of the sensitivity analysis, we apply it to the large bipolar pedigree reported by Egeland et al. and Kelsoe et al. We show that the changes in lod scores observed there, on the order of 1.1-1.2 per person, are not unusual. We recommend that investigators include a sensitivity analysis as a standard part of reporting the results of a linkage analysis.     

The problem of ascertainment for linkage analysis.

It is generally believed that ascertainment corrections are unnecessary in linkage analysis, provided individuals are selected for study solely on the basis of trait phenotype and not on the basis of marker genotype. The theoretical rationale for this is that standard linkage analytic methods involve conditioning likelihoods on all the trait data, which may be viewed as an application of the ascertainment assumption-free (AAF) method of Ewens and Shute. In this paper, we show that when the observed pedigree structure depends on which relatives within a pedigree happen to have been the probands (proband-dependent, or PD, sampling) conditioning on all the trait data is not a valid application of the AAF method and will result in asymptotically biased estimates of genetic parameters (except under single ascertainment). Furthermore, this result holds even if the recombination fraction R is the only parameter of interest. Since the lod score is proportional to the likelihood of the marker data conditional on all the trait data, this means that when data are obtained under PD sampling the lod score will yield asymptotically biased estimates of R, and that so-called mod scores (i.e., lod scores maximized over both R and parameters theta of the trait distribution) will yield asymptotically biased estimates of R and theta. Furthermore, the problem appears to be intractable, in the sense that it is not possible to formulate the correct likelihood conditional on observed pedigree structure. In this paper we do not investigate the numerical magnitude of the bias, which may be small in many situations. On the other hand, virtually all linkage data sets are collected under PD sampling. Thus, the existence of this bias will be the rule rather than the exception in the usual applications.     

Linkage analysis versus association analysis: distinguishing between two models that explain disease-marker associations.

Human genetics researchers have been intrigued for many years by weak-to-moderate associations between markers and diseases. However, in most cases of association, the cause of this phenomenon is still not known. Recently, interest has grown in pursuing association studies for complex diseases, either instead of or in addition to linkage studies. Hence, it is timely to reconsider what a disease-marker association, particularly in the weak-to-moderate range (relative risk < 10), can tell us about disease etiology. To this end, this study accomplishes three aims: (1) It formulates two different models explaining weak-to-moderate associations and derives the relationship between them. One is a linkage disequilibrium model, and the other is a "susceptibility," or pure association, model. The importance of drawing the distinction between these two models and the implications for our understanding of the genetics of human disease will also be discussed. It will be argued that the linkage disequilibrium model represents true linkage but that the susceptibility model does not. (2) It examines two family-based association tests proposed recently by Parsian et al. and Spielman et al. and derives formulas for their behavior under the two models described above. It demonstrates that these tests yield almost identical results under these two models. It shows that, whereas these tests can confirm an association, they cannot determine whether the association is caused by the linkage disequilibrium model or the susceptibility model. The study also characterizes the probabilities yielded by the family association tests in the presence of weak-to-moderate associations, which will aid researchers using these tests. (3) It proposes two approaches, both based on linkage analysis, which can distinguish between the two models described above. One approach involves a straightforward linkage analysis of the data; the other involves a partitioned association-linkage (PAL) test, as suggested by Greenberg. Formulas are derived for testing identity by descent in affected sib pairs by using both approaches. (4) Finally, the formulas and arguments are illustrated with two examples from the literature and one computer-simulated data set.     

Fatty Acid Methyl Ester Profiles for Characterization of Glomalean Fungi and Their Endomycorrhizae

Arbuscule-forming fungi in the order Glomales form obligate endomycorrhizal associations with plants that make them difficult to quantify, and taxonomy of the group is only beginning to be objectively understood. Fatty acid methyl ester (FAME) profiles were analyzed to assess the diversity and quantity of fatty acids in 53 isolates of 24 glomalean species. Spores and endomycorrhizal roots of sudan grass (Sorghum sudanense) and the citrus rootstock Carrizo citrange (Poncirus trifoliata x Citrus sinensis) were examined. Spores yielded reproducible FAME profiles from replicate spore collections extracted from soil pot cultures despite being grown in association with a host plant and with contaminating microorganisms present. Unweighted pair group analysis revealed relatively tight clusters of groups at the intraspecific, specific, and generic levels; however, lipid profiles at the family level were convergent. Thus, FAME profile comparisons provided a robust measure of similarity below the family level. FAME profiles in sudan grass roots containing vesicles and/or spores of Glomus intraradices were more similar to spore profiles than to profiles from nonmycorrhizal roots. The FAME profiles for Gigaspora species, which do not form vesicles or spores in roots, were less distinct from nonmycorrhizal roots. G. intraradices and G. rosea produced fatty acids in roots that were distinguishable from each other as well as from the host root. Production in citrus roots of the fatty acid 16:1(inf(omega)5) cis by two Glomus species was correlated with the development of mycorrhizal colonization as measured by clearing and staining procedures and by estimates of total incidence and vesicle intensity. FAME analysis of roots not only provided a measure of colonization development but also served as an index of carbon allocated to intraradical fungal growth and lipid storage.