Prediction of near-term climate change impacts on UK wheat quality and the potential for adaptation through plant breeding

Wheat is a major crop worldwide, mainly cultivated for human consumption and animal feed. Grain quality is paramount in determining its value and downstream use. While we know that climate change threatens global crop yields, a better understanding of impacts on wheat end-use quality is also critical. Combining quantitative genetics with climate model outputs, we investigated UK-wide trends in genotypic adaptation for wheat quality traits. In our approach, we augmented genomic prediction models with environmental characterisation of field trials to predict trait values and climate effects in historical field trial data between 2001 and 2020. Addition of environmental covariates, such as temperature and rainfall, successfully enabled prediction of genotype by environment interactions (G × E), and increased prediction accuracy of most traits for new genotypes in new year cross validation. We then extended predictions from these models to much larger numbers of simulated environments using climate scenarios projected under Representative Concentration Pathways 8.5 for 2050–2069. We found geographically varying climate change impacts on wheat quality due to contrasting associations between specific weather covariables and quality traits across the UK. Notably, negative impacts on quality traits were predicted in the East of the UK due to increased summer temperatures while the climate in the North and South-west may become more favourable with increased summer temperatures. Furthermore, by projecting 167,040 simulated future genotype–environment combinations, we found only limited potential for breeding to exploit predictable G × E to mitigate year-to-year environmental variability for most traits except Hagberg falling number. This suggests low adaptability of current UK wheat germplasm across future UK climates. More generally, approaches demonstrated here will be critical to enable adaptation of global crops to near-term climate change.     

鼎湖山森林群落演替之研究

鼎湖山森林群落在自然状态下遵循一定的客观规律向更优化的气候顶极群落演变。本文分析其1955年至1989年(35年)来的演替结果,总结出鼎湖山森林群落演替的进程和模式,进一步应用植物群落演替系统的线性模型和非线性模型对演替进程进行定量研究,并做出相应的演替进程的数量预测。     

Ranking species based on sensitivity to perturbations under non-equilibrium community dynamics

Managing ecological communities requires fast detection of species that are sensitive to perturbations. Yet, the focus on recovery to equilibrium has prevented us from assessing species responses to perturbations when abundances fluctuate over time. Here, we introduce two data-driven approaches (expected sensitivity and eigenvector rankings) based on the time-varying Jacobian matrix to rank species over time according to their sensitivity to perturbations on abundances. Using several population dynamics models, we demonstrate that we can infer these rankings from time-series data to predict the order of species sensitivities. We find that the most sensitive species are not always the ones with the most rapidly changing or lowest abundance, which are typical criteria used to monitor populations. Finally, using two empirical time series, we show that sensitive species tend to be harder to forecast. Our results suggest that incorporating information on species interactions can improve how we manage communities out of equilibrium.     

Structures of randomly generated mutants of T4 lysozyme show that protein stability can be enhanced by relaxation of strain and by improved hydrogen bonding via bound solvent.

The structures of three mutants of bacteriophage T4 lysozyme selected using a screen designed to identify thermostable variants are described. Each of the mutants has a substitution involving threonine. Two of the variants, Thr 26-->Ser (T26S) and Thr 151-->Ser (T151S), have increased reversible melting temperatures with respect to the wild-type protein. The third, Ala 93-->Thr (A93T), has essentially the same stability as wild type. Thr 26 is in the wall of the active-site cleft. Its replacement with serine results in the rearrangement of nearby residues, most notably Tyr 18, suggesting that the increase in stability may result from the removal of strain. Thr 151 in the wild-type structure is far from the active site and appears to sterically prevent the access of solvent to a preformed binding site. In the mutant, the removal of the methyl group allows access to the solvent binding site and, in addition, the Ser 151 hydroxyl rotates to a new position so that it also contributes to solvent binding. Residue 93 is in a highly exposed site on the surface of the molecule, and presumably is equally solvent exposed in the unfolded protein. It is, therefore, not surprising that the substitution Ala 93-->Thr does not change stability. The mutant structures show how chemically similar mutations can have different effects on both the structure and stability of the protein, depending on the structural context. The results also illustrate the power of random mutagenesis in obtaining variants with a desired phenotype.(ABSTRACT TRUNCATED AT 250 WORDS)     

Modeling of protein loops by simulated annealing.

A method is presented to model loops of protein to be used in homology modeling of proteins. This method employs the ESAP program of Higo et al. (Higo, J., Collura, V., & Garnier, J., 1992, Biopolymers 32, 33-43) and is based on a fast Monte Carlo simulation and a simulated annealing algorithm. The method is tested on different loops or peptide segments from immunoglobulin, bovine pancreatic trypsin inhibitor, and bovine trypsin. The predicted structure is obtained from the ensemble average of the coordinates of the Monte Carlo simulation at 300 K, which exhibits the lowest internal energy. The starting conformation of the loop prior to modeling is chosen to be completely extended, and a closing harmonic potential is applied to N, CA, C, and O atoms of the terminal residues. A rigid geometry potential of Robson and Platt (1986, J. Mol. Biol. 188, 259-281) with a united atom representation is used. This we demonstrate to yield a loop structure with good hydrogen bonding and torsion angles in the allowed regions of the Ramachandran map. The average accuracy of the modeling evaluated on the eight modeled loops is 1 A root mean square deviation (rmsd) for the backbone atoms and 2.3 A rmsd for all heavy atoms.     

Protein structure dynamics by crosslinking mass spectrometry

Crosslinking mass spectrometry captures protein structures in solution. The crosslinks reveal spatial proximities as distance restraints, but do not easily reveal which of these restraints derive from the same protein conformation. This superposition can be reduced by photo-crosslinking, and adding information from protein structure models, or quantitative crosslinking reveals conformation-specific crosslinks. As a consequence, crosslinking MS has proven useful already in the context of multiple dynamic protein systems. We foresee a breakthrough in the resolution and scale of studying protein dynamics when crosslinks are used to guide deep-learning-based protein modelling. Advances in crosslinking MS, such as photoactivatable crosslinking and in-situ crosslinking, will then reveal protein conformation dynamics in the cellular context, at a pseudo-atomic resolution, and plausibly in a time-resolved manner.     

Cross-trait prediction accuracy of summary statistics in genome-wide association studies

In the era of big data, univariate models have widely been used as a workhorse tool for quickly producing marginal estimators; and this is true even when in a high-dimensional dense setting, in which many features are “true,” but weak signals. Genome-wide association studies (GWAS) epitomize this type of setting. Although the GWAS marginal estimator is popular, it has long been criticized for ignoring the correlation structure of genetic variants (i.e., the linkage disequilibrium [LD] pattern). In this paper, we study the effects of LD pattern on the GWAS marginal estimator and investigate whether or not additionally accounting for the LD can improve the prediction accuracy of complex traits. We consider a general high-dimensional dense setting for GWAS and study a class of ridge-type estimators, including the popular marginal estimator and the best linear unbiased prediction (BLUP) estimator as two special cases. We show that the performance of GWAS marginal estimator depends on the LD pattern through the first three moments of its eigenvalue distribution. Furthermore, we uncover that the relative performance of GWAS marginal and BLUP estimators highly depends on the ratio of GWAS sample size over the number of genetic variants. Particularly, our finding reveals that the marginal estimator can easily become near-optimal within this class when the sample size is relatively small, even though it ignores the LD pattern. On the other hand, BLUP estimator has substantially better performance than the marginal estimator as the sample size increases toward the number of genetic variants, which is typically in millions. Therefore, adjusting for the LD (such as in the BLUP) is most needed when GWAS sample size is large. We illustrate the importance of our results by using the simulated data and real GWAS.     

Pattern-based clustering of daily weigh-in trajectories using dynamic time warping

“Smart”-scales are a new tool for frequent monitoring of weight change as well as weigh-in behavior. These scales give researchers the opportunity to discover patterns in the frequency that individuals weigh themselves over time, and how these patterns are associated with overall weight loss. Our motivating data come from an 18-month behavioral weight loss study of 55 adults classified as overweight or obese who were instructed to weigh themselves daily. Adherence to daily weigh-in routines produces a binary times series for each subject, indicating whether a participant weighed in on a given day. To characterize weigh-in by time-invariant patterns rather than overall adherence, we propose using hierarchical clustering with dynamic time warping (DTW). We perform an extensive simulation study to evaluate the performance of DTW compared to Euclidean and Jaccard distances to recover underlying patterns in adherence time series. In addition, we compare cluster performance using cluster validation indices (CVIs) under the single, average, complete, and Ward linkages and evaluate how internal and external CVIs compare for clustering binary time series. We apply conclusions from the simulation to cluster our real data and summarize observed weigh-in patterns. Our analysis finds that the adherence trajectory pattern is significantly associated with weight loss.     

笼养蓝马鸡取食高度偏好

笼养鸟类取食高度对其自然行为表达和动物福利至关重要。然而,相关研究却少见报道。本文以我国二级重点保护野生动物——蓝马鸡(Crossoptilon auritum)为研究对象,观察笼养状态下其对不同高度取食槽内放置的种子或蔬菜的取食次序,并使用回归分析建立取食高度与偏好值的数学模型。结果发现,笼养蓝马鸡取食种子类食物(玉米粒)最佳取食高度为0cm,并且采食偏好随采食槽高度升高而下降(y=-0.564x+43.146,R²=0.946,y为采食偏好值,x为采食槽高度);油麦菜(Lactuca sativa)的最适取食高度范围为15～25 cm,随着取食槽高度的升高,偏好值先上升,至25 cm处后下降(y=-0.014x2+0.543x+26.487,R²=0.952,y为采食偏好值,x为采食槽高度)。当取食槽高度在65 cm及以上时,蓝马鸡拒食率上升(拒食率≥38.9%)。成年蓝马鸡体高对取食高度影响不明显。研究结果可为笼养蓝马鸡饲养管理提供参考。     

Palynological and palaeobotanical investigations in the area of the post-medieval Helsinki Old Town

Pollen, phytolith, and plant macrofossil analyses were carried out on the cultural layers of Helsinki Old Town excavated by the Helsinki City Museum and dated to the 15–17th centuries. Cultural mineral soil layers, a former ditch, a well, one waste pit, one waste heap and three house areas were investigated. The results show that-within certain limits-pollen in the mineral soil reflects the cultural changes of the local settlement from rural to urban. Among the main anthropogenic indicators, the high NAP (non-arboreal pollen) frequencies, the low pollen concentration values, and especially the high frequencies of Cichoriaceae (Liguliflorae) pollen should be emphasized. The macrofossil data were used to determine the species list of the herb pollen and to make a more detailed reconstruction of the local vegetation at Helsinki Old Town.