Prenylated Bibenzyls from the Chinese Liverwort Radula constricta and Their Mitochondria-Derived Paraptotic Cytotoxic Activities.

Nine new prenylated bibenzyls, radstrictins A-I (1-9), and 11 known congeners were obtained from the Chinese liverwort Radula constricta. Their structures were identified by analysis of HRMS, NMR, and electronic circular dichroism data. Radstrictins A-F (1-6) were isolated as a racemate or scalemic mixtures. All the isolated compounds were subjected to cytotoxicity assessment. Methyl 2,4-dihydroxy-3-(3-methyl-2-butenyl)-6-phenethylbenzoate (10) exhibited significant activity against human lung cancer cell lines A549 and NCI-H1299 with IC50 values of 6.0 and 5.1 µM, respectively. Further research revealed that cell death triggered by 10 occurred via mitochondria-derived paraptosis.

A curve-free Bayesian decision-theoretic design for two-agent Phase I trials.

Although Bayesian statistical methods are gaining attention in the medical community, as they provide a natural framework for incorporating prior information, the complexity of these methods limited their adoptions in clinical trials. This article proposes a Bayesian design for two-agent Phase I trials that is relatively easy for clinicians to understand and implement, yet performs comparably to more complex designs, so that it is more likely to be adopted in actual trials. In order to reduce model complexity and computational burden, we choose a working model with conjugate priors so that the posterior distributions have analytical expressions. Furthermore, we provide a simple strategy to facilitate the specification of priors based on the toxicity information accrued from single-agent Phase I trials. The proposed method should be useful in terms of the ease of implementation and the savings in sample size without sacrificing performance. Moreover, the conservativeness of the dose-finding algorithm renders it a relatively safe method.

Mapping QTLs for blight resistance and morpho-phenological traits in inter-species hybrid families of chestnut (Castanea spp.).

Chestnut blight (caused by Cryphonectria parasitica), together with Phytophthora root rot (caused by Phytophthora cinnamomi), has nearly extirpated American chestnut (Castanea dentata) from its native range. In contrast to the susceptibility of American chestnut, many Chinese chestnut (C. mollissima) genotypes are resistant to blight. In this research, we performed a series of genome-wide association studies for blight resistance originating from three unrelated Chinese chestnut trees (Mahogany, Nanking and M16) and a Quantitative Trait Locus (QTL) study on a Mahogany-derived inter-species F2 family. We evaluated trees for resistance to blight after artificial inoculation with two fungal strains and scored nine morpho-phenological traits that are the hallmarks of species differentiation between American and Chinese chestnuts. Results support a moderately complex genetic architecture for blight resistance, as 31 QTLs were found on 12 chromosomes across all studies. Additionally, although most morpho-phenological trait QTLs overlap or are adjacent to blight resistance QTLs, they tend to aggregate in a few genomic regions. Finally, comparison between QTL intervals for blight resistance and those previously published for Phytophthora root rot resistance, revealed five common disease resistance regions on chromosomes 1, 5, and 11. Our results suggest that it will be difficult, but still possible to eliminate Chinese chestnut alleles for the morpho-phenological traits while achieving relatively high blight resistance in a backcross hybrid tree. We see potential for a breeding scheme that utilizes marker-assisted selection early for relatively large effect QTLs followed by genome selection in later generations for smaller effect genomic regions.

A simple Bayesian decision-theoretic design for dose-finding trials.

A flexible and simple Bayesian decision-theoretic design for dose-finding trials is proposed in this paper. In order to reduce the computational burden, we adopt a working model with conjugate priors, which is flexible to fit all monotonic dose-toxicity curves and produces analytic posterior distributions. We also discuss how to use a proper utility function to reflect the interest of the trial. Patients are allocated based on not only the utility function but also the chosen dose selection rule. The most popular dose selection rule is the one-step-look-ahead (OSLA), which selects the best-so-far dose. A more complicated rule, such as the two-step-look-ahead, is theoretically more efficient than the OSLA only when the required distributional assumptions are met, which is, however, often not the case in practice. We carried out extensive simulation studies to evaluate these two dose selection rules and found that OSLA was often more efficient than two-step-look-ahead under the proposed Bayesian structure. Moreover, our simulation results show that the proposed Bayesian method's performance is superior to several popular Bayesian methods and that the negative impact of prior misspecification can be managed in the design stage.

A two-dimensional search algorithm for dose-finding trials of two agents.

Existing algorithms for identifying the maximum tolerated combination in dose-finding trials of two agents are mostly one-dimensional. Moreover, these algorithms use only the frequency of observed dose-limiting toxicities as the basis for dose escalations and deescalations. In this article, we propose a two-dimensional algorithm that uses not only the frequency but also the source of dose-limiting toxicities to direct dose escalations and deescalations. In addition, when the doses of both agents are escalated simultaneously, a more conservative design replaces a default aggressive design to evaluate the resulting dose combination. Our method aims to increase in-trial patient safety without unnecessary increase in sample size.

NLR diversity and candidate fusiform rust resistance genes in loblolly pine.

Resistance to fusiform rust disease in loblolly pine (Pinus taeda) is a classic gene-for-gene system. Early resistance gene mapping in the P. taeda family 10-5 identified RAPD markers for a major fusiform rust resistance gene, Fr1. More recently, single nucleotide polymorphism (SNP) markers associated with resistance were mapped to a full-length gene model in the loblolly pine genome encoding for a nucleotide-binding site leucine-rich repeat (NLR) protein. NLR genes are one of the most abundant gene families in plant genomes and are involved in effector-triggered immunity. Inter- and intraspecies studies of NLR gene diversity and expression have resulted in improved disease resistance. To characterize NLR gene diversity and discover potential resistance genes, we assembled de novo transcriptomes from 92 loblolly genotypes from across the natural range of the species. In these transcriptomes, we identified novel NLR transcripts that are not present in the loblolly pine reference genome and found significant geographic diversity of NLR genes providing evidence of gene family evolution. We designed capture probes for these NLRs to identify and map SNPs that stably cosegregate with resistance to the SC20-21 isolate of Cronartium quercuum f.sp. fusiforme (Cqf) in half-sib progeny of the 10-5 family. We identified 10 SNPs and 2 quantitative trait loci associated with resistance to SC20-21 Cqf. The geographic diversity of NLR genes provides evidence of NLR gene family evolution in loblolly pine. The SNPs associated with rust resistance provide a resource to enhance breeding and deployment of resistant pine seedlings.

Mapping quantitative trait loci associated with chilling requirement, heat requirement and bloom date in peach (Prunus persica).

*Chilling requirement, together with heat requirement, determines the bloom date, which has an impact on the climatic distribution of the genotypes of tree species. The molecular basis of floral bud chilling requirement is poorly understood, despite its importance to the adaptation and production of fruit trees. In addition, the genetic nature of heat requirement and the genetic interrelationships among chilling requirement, heat requirement and bloom date remain unclear. *A peach (Prunus persica) F(2) population of 378 genotypes developed from two genotypes with contrasting chilling requirements was used for linkage map construction and quantitative trait loci (QTL) mapping. The floral bud chilling and heat requirements of each genotype were evaluated over 2 yr and the bloom date was scored over 4 yr. *Twenty QTLs with additive effects were identified for three traits, including one major QTL for chilling requirement and two major QTLs for bloom date. The majority of QTLs colocalized with QTLs for other trait(s). In particular, one genomic region of 2 cM, pleiotropic for the three traits, overlapped with the sequenced peach EVG region. *This first report on the QTL mapping of floral bud chilling requirement will facilitate marker-assisted breeding for low chilling requirement cultivars and the map-based cloning of genes controlling chilling requirement. The extensive colocalization of QTLs suggests that there may be one unified temperature sensing and action system regulating chilling requirement, heat requirement and bloom date together.

A curve free Bayesian decision-theoretic design for phase Ia/Ib trials considering both safety and efficacy outcomes.

A curve-free, Bayesian decision-theoretic two-stage design is proposed to select biological efficacious doses (BEDs) for phase Ia/Ib trials in which both toxicity and efficacy signals are observed. No parametric models are assumed to govern the dose-toxicity, dose-efficacy, and toxicity-efficacy relationships. We assume that the dose-toxicity curve is monotonic non-decreasing and the dose-efficacy curve is unimodal. In the phase Ia stage, a Bayesian model on the toxicity rates is used to locate the maximum tolerated dose. In the phase Ib stage, we model the dose-efficacy curve using a step function while continuing to monitor the toxicity rates. Furthermore, a measure of the goodness of fit of a candidate step function is proposed, and the interval of BEDs associated with the best fitting step function is recommended. At the end of phase Ib, if some doses are recommended as BEDs, a cohort of confirmation is recruited and assigned at these doses to improve the precision of estimates at these doses. Extensive simulation studies show that the proposed design has desirable operating characteristics across different shapes of the underlying true toxicity and efficacy curves.

Genetic linkage mapping for molecular dissection of chilling requirement and budbreak in apricot (Prunus armeniaca L.).

Commercial production of apricot is severely affected by sensitivity to climatic conditions, an adaptive feature essential for cycling between vegetative or floral growth and dormancy. Yield losses are due to late winter or early spring frosts and inhibited vegetative or floral growth caused by unfulfilled chilling requirement (CR). Two apricot cultivars, Perfection and A.1740, were selected for high and low CR, respectively, to develop a mapping population of F1 individuals using a two-way pseudo-testcross mapping strategy. High-density male and female maps were constructed using, respectively, 655 and 592 markers (SSR and AFLP) spanning 550.6 and 454.9 cM with average marker intervals of 0.84 and 0.77 cM. CR was evaluated in two seasons on potted trees forced to break buds after cold treatments ranging from 100 to 900 h. A total of 12 putative CR quantitative trait loci (QTLs) were detected on six linkage groups using composite interval mapping and a simultaneous multiple regression fit. QTL main effects of additive and additive x additive interactions accounted for 58.5% +/- 6.7% and 66.1% +/- 5.8% of the total phenotypic variance in the Perfection and A.1740 maps, respectively. We report two apricot high-density maps and QTLs corresponding to map positions of differentially expressed transcripts and suggested candidate genes controlling CR.

Design issues in dose-finding Phase I trials for combinations of two agents.

Combination therapy of two antitumor agents may provide treatment additivity or synergy. Phase I trials for combination therapy search for the maximum tolerated dose (MTD) for combined agents. The conventional approach is to preselect an escalation path, usually increasing the dose of one agent and then another, and to use the standard 3 + 3 design. However, this procedure may miss the optimum dose combination, prolong the time it takes, and increase the number of patients necessary to reach the MTD. In this study, we present strategies for a comprehensive search for MTD for a two-agent combination therapy. We evaluate algorithms based on two-stage and three-stage design as well as variations in cohort size. A two-dimensional isotonic estimation method for toxicity rate is provided. We use simulation methods to compare 2 + 1 + 3 vs. 3 + 3 cohort sizes. We conclude that the comprehensive search proposed in our study can be more practical and efficient in identifying the MTD in combination-therapy of two agents.

The novel lncRNA lnc-NR2F1 is pro-neurogenic and mutated in human neurodevelopmental disorders.

Long noncoding RNAs (lncRNAs) have been shown to act as important cell biological regulators including cell fate decisions but are often ignored in human genetics. Combining differential lncRNA expression during neuronal lineage induction with copy number variation morbidity maps of a cohort of children with autism spectrum disorder/intellectual disability versus healthy controls revealed focal genomic mutations affecting several lncRNA candidate loci. Here we find that a t(5:12) chromosomal translocation in a family manifesting neurodevelopmental symptoms disrupts specifically lnc-NR2F1. We further show that lnc-NR2F1 is an evolutionarily conserved lncRNA functionally enhances induced neuronal cell maturation and directly occupies and regulates transcription of neuronal genes including autism-associated genes. Thus, integrating human genetics and functional testing in neuronal lineage induction is a promising approach for discovering candidate lncRNAs involved in neurodevelopmental diseases.

Genotyping by Sequencing for SNP-Based Linkage Map Construction and QTL Analysis of Chilling Requirement and Bloom Date in Peach [Prunus persica (L.) Batsch].

Low-cost, high throughput genotyping methods are crucial to marker discovery and marker-assisted breeding efforts, but have not been available for many 'specialty crops' such as fruit and nut trees. Here we apply the Genotyping-By-Sequencing (GBS) method developed for cereals to the discovery of single nucleotide polymorphisms (SNPs) in a peach F2 mapping population. Peach is a genetic and genomic model within the Rosaceae and will provide a template for the use of this method with other members of this family. Our F2 mapping population of 57 genotypes segregates for bloom time (BD) and chilling requirement (CR) and we have extensively phenotyped this population. The population derives from a selfed F1 progeny of a cross between 'Hakuho' (high CR) and 'UFGold' (low CR). We were able to successfully employ GBS and the TASSEL GBS pipeline without modification of the original methodology using the ApeKI restriction enzyme and multiplexing at an equivalent of 96 samples per Illumina HiSeq 2000 lane. We obtained hundreds of SNP markers which were then used to construct a genetic linkage map and identify quantitative trait loci (QTL) for BD and CR.

Designs for phase I clinical trials with multiple courses of subjects at different doses.

The goal of this article is to provide a new design framework and its corresponding estimation for phase I trials. Existing phase I designs assign each subject to one dose level based on responses from previous subjects. Yet it is possible that subjects with neither toxicity nor efficacy responses can be treated at higher dose levels, and their subsequent responses to higher doses will provide more information. In addition, for some trials, it might be possible to obtain multiple responses (repeated measures) from a subject at different dose levels. In this article, a nonparametric estimation method is developed for such studies. We also explore how the designs of multiple doses per subject can be implemented to improve design efficiency. The gain of efficiency from "single dose per subject" to "multiple doses per subject" is evaluated for several scenarios. Our numerical study shows that using "multiple doses per subject" and the proposed estimation method together increases the efficiency substantially.

Decision-theoretic designs for dose-finding clinical trials with multiple outcomes.

A decision-theoretic framework is proposed for designing sequential dose-finding trials with multiple outcomes. The optimal strategy is solvable theoretically via backward induction. However, for dose-finding studies involving k doses, the computational complexity is the same as the bandit problem with k-dependent arms, which is computationally prohibitive. We therefore provide two computationally compromised strategies, which is of practical interest as the computational complexity is greatly reduced: one is closely related to the continual reassessment method (CRM), and the other improves CRM and approximates to the optimal strategy better. In particular, we present the framework for phase I/II trials with multiple outcomes. Applications to a pediatric HIV trial and a cancer chemotherapy trial are given to illustrate the proposed approach. Simulation results for the two trials show that the computationally compromised strategy can perform well and appear to be ethical for allocating patients. The proposed framework can provide better approximation to the optimal strategy if more extensive computing is available.