A Statistical Model for Estimating Maternal-Zygotic Interactions and Parent-of-Origin Effects of QTLs for Seed Development

Proper development of a seed requires coordinated exchanges of signals among the three components that develop side by side in the seed. One of these is the maternal integument that encloses the other two zygotic components, i.e., the diploid embryo and its nurturing annex, the triploid endosperm. Although the formation of the embryo and endosperm contains the contributions of both maternal and paternal parents, maternally and paternally derived alleles may be expressed differently, leading to a so-called parent-of-origin or imprinting effect. Currently, the nature of how genes from the maternal and zygotic genomes interact to affect seed development remains largely unknown. Here, we present a novel statistical model for estimating the main and interaction effects of quantitative trait loci (QTLs) that are derived from different genomes and further testing the imprinting effects of these QTLs on seed development. The experimental design used is based on reciprocal backcrosses toward both parents, so that the inheritance of parent-specific alleles could be traced. The computing model and algorithm were implemented with the maximum likelihood approach. The new strategy presented was applied to study the mode of inheritance for QTLs that control endoreduplication traits in maize endosperm. Monte Carlo simulation studies were performed to investigate the statistical properties of the new model with the data simulated under different imprinting degrees. The false positive rate of imprinting QTL discovery by the model was examined by analyzing the simulated data that contain no imprinting QTL. The reciprocal design and a series of analytical and testing strategies proposed provide a standard procedure for genomic mapping of QTLs involved in the genetic control of complex seed development traits in flowering plants

Global patterns and drivers of ecosystem functioning in rivers and riparian zones

River ecosystems receive and process vast quantities of terrestrial organic carbon, the fate of which depends strongly on microbial activity. Variation in and controls of processing rates, however, are poorly characterized at the global scale. In response, we used a peer-sourced research network and a highly standardized carbon processing assay to conduct a global-scale field experiment in greater than 1000 river and riparian sites. We found that Earth's biomes have distinct carbon processing signatures. Slow processing is evident across latitudes, whereas rapid rates are restricted to lower latitudes. Both the mean rate and variability decline with latitude, suggesting temperature constraints toward the poles and greater roles for other environmental drivers (e.g., nutrient loading) toward the equator. These results and data set the stage for unprecedented "next-generation biomonitoring" by establishing baselines to help quantify environmental impacts to the functioning of ecosystems at a global scale.peerReviewe

Biphasic survival analysis of trypanotolerance QTL in mice

A marker-assisted introgression (MAI) experiment was conducted to transfer trypanotolerance quantitative trait loci (QTL) from a donor mouse strain, C57BL/6, into a recipient mouse strain, A/J. The objective was to assess the effect of three previously identified chromosomal regions on mouse chromosomes 1 (MMU1), 5 (MMU5) and 17 (MMU17) in different genetic backgrounds on the survival pattern following infection with 'Trypanosoma congolense'. An exploratory data analysis revealed a biphasic pattern of time to death, with highly distinct early and late mortality phases. In this paper, we present survival analysis methods that account for the biphasic mortality pattern and results of reanalyzing the data from the MAI experiment. The analysis with a Weibull mixture model confirmed the biphasic pattern of time to death. Mortality phase, an unobserved variable, appears to be an important factor influencing survival time and is modeled as a binary outcome variable using logistic regression analysis. Accounting for this biphasic pattern in the analysis reveals that a previously observed sex effect on average survival is rather an effect on proportion of mice in the two mortality phases. The C57BL/6 (donor) QTL alleles on MMU1 and MMU17 act dominantly in the late mortality phase while the A/J (recipient) QTL allele on MMU17 acts dominantly in the early mortality phase. From this study, we found clear evidence for a biphasic survival pattern and provided models for its analysis. These models can also be used when studying defense mechanisms against other pathogens. Finally, these approaches provide further information on the nature of gene actions