Extensive introgression of mitochondrial DNA relative to nuclear genes in the Drosophila yakuba species group

Studies of gene flow between recently diverged species can illuminate the role of natural selection in the formation of new species. Drosophila santomea and D. yakuba are recently diverged, partially reproductively isolated species that continue to hybridize in the wild, and appear to be reproductively isolated from the more distantly related species D. teissieri. We examine patterns of nucleotide polymorphism and divergence in these three species at multiple X-linked, Y-linked, and mitochondrial markers. All three species harbor drastically reduced variability on the Y chromosome relative to the X, as expected for a nonrecombining chromosome subject to variation-reducing selection. The three species are generally well differentiated at the nuclear markers, with little evidence for recent introgression for either the X- or Y-linked genes. Based on the nuclear genes, we estimate that D. santomea and D. yakuba diverged about one-half million years ago and split from D. teissieri about one million years ago. In contrast to the pattern at nuclear loci, all three species share a very similar mtDNA haplotype. We show that the mtDNA must have recently introgressed across species boundaries in the D. yakuba subgroup and that its fixation was driven by either selection on the mitochondria itself or other cytoplasmic factors. These results demonstrate that different regions of the genome can have distinct evolutionary dynamics in the context of species formation. Although natural selection is usually thought of as accentuating divergence between species, our results imply that it can also act as a homogenizing force.     

A mitogenomic timescale for birds detects variable phylogenetic rates of molecular evolution and refutes the standard molecular clock

Current understanding of the diversification of birds is hindered by their incomplete fossil record and uncertainty in phylogenetic relationships and phylogenetic rates of molecular evolution. Here we performed the first comprehensive analysis of mitogenomic data of 48 vertebrates, including 35 birds, to derive a Bayesian timescale for avian evolution and to estimate rates of DNA evolution. Our approach used multiple fossil time constraints scattered throughout the phylogenetic tree and accounts for uncertainties in time constraints, branch lengths, and heterogeneity of rates of DNA evolution. We estimated that the major vertebrate lineages originated in the Permian; the 95% credible intervals of our estimated ages of the origin of archosaurs (258 MYA), the amniote-amphibian split (356 MYA), and the archosaur-lizard divergence (278 MYA) bracket estimates from the fossil record. The origin of modern orders of birds was estimated to have occurred throughout the Cretaceous beginning about 139 MYA, arguing against a cataclysmic extinction of lineages at the Cretaceous/Tertiary boundary. We identified fossils that are useful as time constraints within vertebrates. Our timescale reveals that rates of molecular evolution vary across genes and among taxa through time, thereby refuting the widely used mitogenomic or cytochrome b molecular clock in birds. Moreover, the 5-Myr divergence time assumed between 2 genera of geese (Branta and Anser) to originally calibrate the standard mitochondrial clock rate of 0.01 substitutions per site per lineage per Myr (s/s/l/Myr) in birds was shown to be underestimated by about 9.5 Myr. Phylogenetic rates in birds vary between 0.0009 and 0.012 s/s/l/Myr, indicating that many phylogenetic splits among avian taxa also have been underestimated and need to be revised. We found no support for the hypothesis that the molecular clock in birds "ticks" according to a constant rate of substitution per unit of mass-specific metabolic energy rather than per unit of time, as recently suggested. Our analysis advances knowledge of rates of DNA evolution across birds and other vertebrates and will, therefore, aid comparative biology studies that seek to infer the origin and timing of major adaptive shifts in vertebrates.     

HUMAN ACTUARIAL AGING INCREASES FASTER WHEN BACKGROUND DEATH RATES ARE LOWER: A CONSEQUENCE OF DIFFERENTIAL HETEROGENEITY?

Many analyses of human populations have found that age-specific mortality rates increase faster across most of adulthood when overall mortality levels decline. This contradicts the relationship often expected from Williams' classic hypothesis about the effects of natural selection on the evolution of senescence. More likely, much of the within-species difference in actuarial aging is not due to variation in senescence, but to the strength of filters on the heterogeneity of frailty in older survivors. A challenge to this differential frailty hypothesis was recently posed by an analysis of life tables from historical European populations and traditional societies that reported variation in actuarial aging consistent with Williams' hypothesis after all. To investigate the challenge, we reconsidered those cases and aging measures. Here we show that the discrepancy depends on Ricklefs' aging rate measure, ω, which decreases as mortality levels drop because it is an index of mortality level itself, not the rate of increase in mortality with age. We also show unappreciated correspondence among the parameters of Gompertz-Makeham and Weibull survival models. Finally, we compare the relationships among mortality parameters of the traditional societies and the historical series, providing further suggestive evidence that differential heterogeneity has strong effects on actuarial aging.     

不同基本培养基对南方高丛蓝浆果丛生枝增殖及生长的影响

比较了MWPM和WPM单一培养基以及MS-WPM、MS-MWPM、MWPM-WPM等体积混合培养基(均含2 mg·L-1 ZT、20 g·L-1蔗糖和7 g·L-1琼脂,pH 5.0)对南方高丛蓝浆果(Vaccinium corymbosum hybrids)品种‘南月’(‘Southmoon’)优选系A47和A167丛生枝增殖及生长的影响。实验结果显示:在MS-WPM和MS-MWPM混合培养基上,优选系A47和A167丛生枝的增殖倍数、总长度及叶片叶绿素含量均高于或显著高于MWPM和WPM单一培养基,丛生枝的鲜质量、干质量和含水量与MWPM和WPM单一培养基相当;而在MWPM-WPM混合培养基上,优选系A47和A167丛生枝的增殖倍数在5种培养基中虽然不是最低的,但丛生枝的各项生长指标均较低或最低。综合分析结果表明:MS-WPM和MS-MWPM混合培养基较目前常用的WPM和MWPM单一培养基更适宜于南方高丛蓝浆果品种‘南月’优选系A47和A167丛生枝的增殖培养。     

Adventitious shoot regeneration from leaf explants of tissue cultured and greenhouse-grown raspberry

Adventitious shoot regeneration was observed using leaf-petiole explants from shoot-proliferating cultures of Comet red raspberry (Rubus idaeus L.). A maximum regeneration rate of 70% (3.7 shoots/explant) was obtained using 4.5–9.1 M (1–2 mg l^–1) N-phenyl-N-1,2,3-thiadiazol-5-ylurea (thidiazuron or TDZ) with 2.5–4.9 M (0.5–1 mg l^–1) 1H-indole-3-butanoic acid (IBA) or 2.3 M (0.5 mg l^–1) TDZ with 4.9 M (1 mg l^–1) IBA in modified Murashige-Skoog medium. TDZ was more effective than N-(phenylmethyl)-1H-purin-6-amine (BA) at promoting regeneration in combinations tested with IBA (maximum 50% regeneration rate; 1.8 shoots/explant). Variation in the agar concentration or incubation temperature, orientation or scoring of the leaf-petiole explants and use of separate leaf or petiole explants had no effect on shoot regeneration. Incubation in the dark for 1, 2 or 3 weeks prior to growth in the light did not influence the percent regeneration rate but depressed the number of adventitious shoots. Explant source, from micropropagated shoots or greenhouse-grown plants, had an effect on shoot regeneration that was genotype dependent. Only 8 of 22 (36%) raspberry cultivars were capable of regeneration from leaf explants derived from greenhouse-grown plants.     

Semiparametric additive time-varying coefficients model for longitudinal data with censored time origin

Statistical analysis of longitudinal data often involves modeling treatment effects on clinically relevant longitudinal biomarkers since an initial event (the time origin). In some studies including preventive HIV vaccine efficacy trials, some participants have biomarkers measured starting at the time origin, whereas others have biomarkers measured starting later with the time origin unknown. The semiparametric additive time-varying coefficient model is investigated where the effects of some covariates vary nonparametrically with time while the effects of others remain constant. Weighted profile least squares estimators coupled with kernel smoothing are developed. The method uses the expectation maximization approach to deal with the censored time origin. The Kaplan–Meier estimator and other failure time regression models such as the Cox model can be utilized to estimate the distribution and the conditional distribution of left censored event time related to the censored time origin. Asymptotic properties of the parametric and nonparametric estimators and consistent asymptotic variance estimators are derived. A two-stage estimation procedure for choosing weight is proposed to improve estimation efficiency. Numerical simulations are conducted to examine finite sample properties of the proposed estimators. The simulation results show that the theory and methods work well. The efficiency gain of the two-stage estimation procedure depends on the distribution of the longitudinal error processes. The method is applied to analyze data from the Merck 023/HVTN 502 Step HIV vaccine study.     

Estimated quadratic inference function for correlated failure time data

An estimated quadratic inference function method is proposed for correlated failure time data with auxiliary covariates. The proposed method makes efficient use of the auxiliary information for the incomplete exposure covariates and preserves the property of the quadratic inference function method that requires the covariates to be completely observed. It can improve the estimation efficiency and easily deal with the situation when the cluster size is large. The proposed estimator which minimizes the estimated quadratic inference function is shown to be consistent and asymptotically normal. A chi-squared test based on the estimated quadratic inference function is proposed to test hypotheses about the regression parameters. The small-sample performance of the proposed method is investigated through extensive simulation studies. The proposed method is then applied to analyze the Study of Left Ventricular Dysfunction (SOLVD) data as an illustration.     

Investigation of the spectral characteristics of Sm3+ ions in lead borosilicate glass for photonic applications

Different concentrations of Sm₂O₃-doped lead borosilicate glass were synthesized using a melt–quenching method and their characteristics were analyzed using X-ray diffraction (XRD) and Fourier transform infrared (FTIR) spectroscopy absorption, emission, and decay curves. From the XRD patterns, the noncrystalline nature of titled glass was confirmed. The structural groups that existed in the host glass were observed from FTIR spectra. The Judd–Ofelt (JO) intensity parameters and oscillator strengths were derived from the absorption spectra and compared with various reported systems. The excitation luminescence levels of the Sm³⁺ ion radiative properties were further computed using the JO intensity parameters. Effective bandwidth, emission cross-sections (σ_e), and several lasing properties were assessed from emission spectra and compared with other reported glass systems. The decay curves of the ⁴G_5/2 level of Sm³⁺ ion were also been measured and examined. Additionally, the colour coordinates of the Commission International de I'Éclairage chromaticity were assessed. The titled glass were suitable for visible reddish orange luminescence devices based on all obtained parameters.     

Quantile Inference with Multivariate Failure Time Data

Quantiles, especially the medians, of survival times are often used as summary statistics to compare the survival experiences between different groups. Quantiles are robust against outliers and preferred over the mean. Multivariate failure time data often arise in biomedical research. For example, in clinical trials, each patient in the study may experience multiple events which may be of the same type or distinct types, while in family studies of genetic diseases or litter matched mice studies, failure times for subjects in the same cluster may be correlated. In this article, we propose nonparametric procedures for the estimation of quantiles with multivariate failure time data. We show that the proposed estimators asymptotically follow a multivariate normal distribution. The asymptotic variance‐covariance matrix of the estimated quantiles is estimated based on the kernel smoothing and bootstrap techniques. Simulation results show that the proposed estimators perform well in finite samples. The methods are illustrated with the burn‐wound infection data and the Diabetic Retinopathy Study (DRS) data.