A study of cultural transmission in Taiwan

Our study of cultural transmission in Taiwan is based on a survey of 1000 students, their families, and friends, for characters ranging from religion to various customs and beliefs, as well as entertainment and hygienic habits. The effects of father, mother, and an older sib on a propositus are tested by an additive model of transmission, using a novel statistical procedure, and compared with correlations with friends. For many traits there exist significant influences; older sibs are almost as important as father and mother, with effects differing somewhat with their sex. Formulas for recurrences and equilibrium frequency of a cultural character for which father, mother, and sib are active in transmission are given in the appendices along with formulas for estimation of their effects from real data.This research was supported in part by grant NIH GM 20467 and NIH GM 20816. In early part of this investigation K.H.C. was supported by a grant to SIMS from the Alfred P. Sloan Foundation.     

Variation between mouse major urinary protein genes isolated from a single inbred line

We describe ten Charon 4A genomic DNA clones from BALB/c mice which include at least seven different major urinary protein (MUP) genes. We have established the orientation of all seven sequences, and have placed six of them in precise register by means of restriction site maps and Southern blot hybridization with cloned cDNA sequences. Four of the seven genomic sequences (family I sequences) form hybrids with six independent cDNA clones that have a high thermal stability and hybridize more strongly with mRNA from three inbred mouse lines. Hybrids between the remaining three genomic sequences and the cDNA clones have a lower thermal stability and hybridize less strongly with mRNA from the three inbred lines. Homologies between different cloned sequences extend over as much as 15 kb. No clone contains parts of two MUP genes, and no homology has been detected between the 3' flanking region of one MUP gene and the 5' flanking region of another.     

Shapes and functions of species–area curves (II): a review of new models and parameterizations

This paper has extended and updated my earlier list and analysis of candidate models used in theoretical modelling and empirical examination of species–area relationships (SARs). I have also reviewed trivariate models that can be applied to include a second independent variable (in addition to area) and discussed extensively the justifications for fitting curves to SARs and the choice of model. There is also a summary of the characteristics of several new candidate models, especially extended power models, logarithmic models and parameterizations of the negative-exponential family and the logistic family. I have, moreover, examined the characteristics and shapes of trivariate linear, logarithmic and power models, including combination variables and interaction terms. The choice of models according to best fit may conflict with problems of non-normality or heteroscedasticity. The need to compare parameter estimates between data sets should also affect model choice. With few data points and large scatter, models with few parameters are often preferable. With narrow-scale windows, even inflexible models such as the power model and the logarithmic model may produce good fits, whereas with wider-scale windows where inflexible models do not fit well, more flexible models such as the second persistence (P2) model and the cumulative Weibull distribution may be preferable. When extrapolations and expected shapes are important, one should consider models with expected shapes, e.g. the power model for sample area curves and the P2 model for isolate curves. The choice of trivariate models poses special challenges, which one can more effectively evaluate by inspecting graphical plots.     

QTL identification of grain protein concentration and its genetic correlation with starch concentration and grain weight using two populations in maize (<Emphasis Type="Italic">Zea mays</Emphasis> L.)

Protein is one of the three main storage chemical components in maize grains, and is negatively correlated with starch concentration (SC). Our objective was to analyse the influence of genetic backgrounds on QTL detection for protein concentration (PC) and to reveal the molecular genetic associations between PC and both SC and grain weight (GWP). Two hundred and eighty-four (Pop1) and 265 (Pop2) F_2:3 families were developed from two crosses between one high-oil maize inbred GY220 and two normal maize inbreds 8984 and 8622 respectively, and were genotyped with 185 and 173 pairs of SSR markers. PC, SC and GWP were evaluated under two environments. Composite interval mapping (CIM) and multiple interval mapping (MIM) methods were used to detect single-trait QTL for PC, and multiple-trait QTL for PC with both SC and GWP. No common QTL were shared between the two populations for their four and one PC QTL. Common QTL with opposite signs of effects for PC and SC/GWP were detected on three marker intervals at bins 6.07–6.08, 8.03 and 8.03–8.04. Multiple-traits QTL mapping showed that tightly-linked QTL, pleiotropic QTL and QTL having effects with opposite directions for PC and SC/GWP were all observed in Pop1, while all QTL reflected opposite effects in Pop2.     

The effect of family structure on the likelihood for kin-biased distribution: an empirical study of brown trout populations

This study is aimed at evaluating the likelihood that kin-biased distribution will be expressed or detected in a range of brown trout ( Salmo trutta ) populations as a function of family size. Microsatellite analysis indicated that fewer full- and half-siblings were found in populations with larger effective population sizes, while more full- and half-siblings were found in populations with lower effective population size. It is suggested that kin-biased distribution and hence kin-biased behaviours are not likely to be expressed equally frequently in all populations since the number of close relatives will vary among populations and, hence, the opportunity for relatives to interact differs among populations. These findings can, at least partly, explain the discrepancy among previous studies of kin-biased distribution in wild salmonids under natural conditions. Effective population size could, hence, be used to predict the salmonid populations in which kin-biased distribution are more likely to occur and be detected.     

Identification of chalcone synthase genes and their expression patterns reveal pollen abortion in cotton

Chalcone synthase (CHS) is a key enzyme and producing flavonoid derivatives as well play a vital roles in sustaining plant growth and development. However, the systematic and comprehensive analysis of CHS genes in island cotton (G. barbadense) has not been reported yet especially response to cytoplasmic male sterility (CMS). To fill this knowledge gap, a genome-wide investigation of CHS genes were studied in island cotton. A total of 20 GbCHS genes were identified and grouped into five GbCHSs. The gene structure analysis revealed that most of GbCHS genes consisted of two exons and one intron, and 20 motifs were identified. Twenty five pairs duplicated events (12 GbCHS genes) were identified including 23 segmental duplication pairs and two tandem duplication events, representing that GbCHS gene family amplification mainly owned to segmental duplication events and evolving slowly. Gene expression analysis exhibited that the GbCHS family genes presented a diversity expression patterns in various organs of cotton. Coupled with functional predictions and gene expression, the abnormal expression of GbCHS06, 10, 16 and 19 might be associated with pollen abortion of CMS line in island cotton. Conclusively, GbCHS genes exhibited diversity and conservation in many aspects, which will help to better understand functional studies and a reference for CHS research in island cotton and other plants.     

Recognition of different base tetrads by RHAU (DHX36): X-ray crystal structure of the G4 recognition motif bound to the 3′-end tetrad of a DNA G-quadruplex

G-quadruplexes (G4) are secondary structures of nucleic acids that can form in cells and have diverse biological functions. Several biologically important proteins interact with G-quadruplexes, of which RHAU (or DHX36) – a helicase from the DEAH-box superfamily, was shown to bind and unwind G-quadruplexes efficiently. We report a X-ray co-crystal structure at 1.5 Å resolution of an N-terminal fragment of RHAU bound to an exposed tetrad of a parallel-stranded G-quadruplex. The RHAU peptide folds into an L-shaped α-helix, and binds to a G-quadruplex through π-stacking and electrostatic interactions. X-ray crystal structure of our complex identified key amino acid residues important for G-quadruplex-peptide binding interaction at the 3′-end G•G•G•G tetrad. Together with previous solution and crystal structures of RHAU bound to the 5′-end G•G•G•G and G•G•A•T tetrads, our crystal structure highlights the occurrence of a robust G-quadruplex recognition motif within RHAU that can adapt to different accessible tetrads.     

Using the tools of genetic epidemiology to understand sex differences in neuropsychiatric disorders

Many neuropsychiatric disorders exhibit differences in prevalence, age of onset, symptoms or course of illness between males and females. For the most part, the origins of these differences are not well understood. In this article, we provide an overview of sex differences in psychiatric disorders including autism spectrum disorder (ASD), attention deficit/hyperactivity disorder (ADHD), anxiety, depression, alcohol and substance abuse, schizophrenia, eating disorders and risk of suicide. We discuss both genetic and nongenetic mechanisms that have been hypothesized to underlie these differences, including ascertainment bias, environmental stressors, X‐ or Y‐linked risk loci, and differential liability thresholds in males and females. We then review the use of twin, family and genome‐wide association approaches to study potential genetic mechanisms of sex differences and the extent to which these designs have been employed in studies of psychiatric disorders. We describe the utility of genetic epidemiologic study designs, including classical twin and family studies, large‐scale studies of population registries, derived recurrence risks, and molecular genetic analyses of genome‐wide variation that may enhance our understanding sex differences in neuropsychiatric disorders.