构树: 一种新型木本模式植物

构树(Broussonetia papyrifera)属于桑科(Moraceae)构属(Broussonetia)多年生乔木, 是一种具有重要价值的多功能树种。构树叶可做蛋白饲料, 树皮是造纸的优质原料, 根、茎、叶、果实及种子均可入药。构树具有分布广和适应性强的特性, 其有性繁殖和无性繁殖迅速, 雌雄异株, 严格异交, 世代周期短, 后代种子数量大, 株型多样, 基因组紧凑, 易转化, 表型性状和遗传多样性丰富, 可以作为研究木质素和纤维素合成、黄酮类和氮代谢、异形叶形成、植物性别分化机制以及植物抗性和环境适应性进化等植物学领域重大关键问题的模式材料。该文重点阐述构树作为模式植物的主要依据, 简要介绍构树的研究进展, 并对今后构树的研究框架进行初步设计。     

Genome‐wide signatures of flowering adaptation to climate temperature: Regional analyses in a highly diverse native range of Arabidopsis thaliana

Current global change is fueling an interest to understand the genetic and molecular mechanisms of plant adaptation to climate. In particular, altered flowering time is a common strategy for escape from unfavourable climate temperature. In order to determine the genomic bases underlying flowering time adaptation to this climatic factor, we have systematically analysed a collection of 174 highly diverse Arabidopsis thaliana accessions from the Iberian Peninsula. Analyses of 1.88 million single nucleotide polymorphisms provide evidence for a spatially heterogeneous contribution of demographic and adaptive processes to geographic patterns of genetic variation. Mountains appear to be allele dispersal barriers, whereas the relationship between flowering time and temperature depended on the precise temperature range. Environmental genome‐wide associations supported an overall genome adaptation to temperature, with 9.4% of the genes showing significant associations. Furthermore, phenotypic genome‐wide associations provided a catalogue of candidate genes underlying flowering time variation. Finally, comparison of environmental and phenotypic genome‐wide associations identified known (Twin Sister of FT, FRIGIDA‐like 1, and Casein Kinase II Beta chain 1) and new (Epithiospecifer Modifier 1 and Voltage‐Dependent Anion Channel 5) genes as candidates for adaptation to climate temperature by altered flowering time. Thus, this regional collection provides an excellent resource to address the spatial complexity of climate adaptation in annual plants.     

Systematic characterization of Escherichia coli genes/ORFs affecting biofilm formation

To understand the nature and function of bacterial biofilm and the process of its formation, we have performed systematic screening of a complete set of Escherichia coli genes/open reading frames (ORFs) to identify those that affect biofilm development upon over-expression. In contrast to the biofilm of strain AG1 used as a control, some of the genes/ORFs when over-expressed led to the formation of an abnormal biofilm such as thin, mat-like, filamentous or one easily detaching from various surfaces. Disruptants of selected genes were constructed in order to clarify their roles in the different stages of biofilm formation. Our results suggest that diverse metabolic pathways contribute to the development of biofilm.     

Genetic Mapping and Genomic Selection Using Recombination Breakpoint Data

The correct models for quantitative trait locus mapping are the ones that simultaneously include all significant genetic effects. Such models are difficult to handle for high marker density. Improving statistical methods for high-dimensional data appears to have reached a plateau. Alternative approaches must be explored to break the bottleneck of genomic data analysis. The fact that all markers are located in a few chromosomes of the genome leads to linkage disequilibrium among markers. This suggests that dimension reduction can also be achieved through data manipulation. High-density markers are used to infer recombination breakpoints, which then facilitate construction of bins. The bins are treated as new synthetic markers. The number of bins is always a manageable number, on the order of a few thousand. Using the bin data of a recombinant inbred line population of rice, we demonstrated genetic mapping, using all bins in a simultaneous manner. To facilitate genomic selection, we developed a method to create user-defined (artificial) bins, in which breakpoints are allowed within bins. Using eight traits of rice, we showed that artificial bin data analysis often improves the predictability compared with natural bin data analysis. Of the eight traits, three showed high predictability, two had intermediate predictability, and two had low predictability. A binary trait with a known gene had predictability near perfect. Genetic mapping using bin data points to a new direction of genomic data analysis.     

小麦-大麦2H异代换系的鉴定

通过基因组原位杂交、重双端体测交及RFLP分析,解析了来自小麦品种"中国春"(Triticum aestivumL.cv."Chinese Spring"(CS))×大麦品种"Betzes"(Hordeum vulgare L.cv."Betzes")杂种后代15份材料的遗传组成,鉴定出6个二体异代换系;对与"中国春"重双端体DDT2A、DDT2B及DDT2D测交的F1代花粉母细胞减数分裂中期染色体构型进行观察,同时以小麦第二部分同源群短臂探针psr131进行RFLP分析,鉴定出一套遗传稳定的小麦-大麦2H二体异代换系2H(A)、2H(B)和2H(D).小麦第二部分同源群短臂探针psr131可作为追踪大麦2H染色体的RFLP标记.从代换系的生长势及其他农艺性状看,大麦2H染色体对小麦染色体2B和2D的补偿作用较好.通过考种观察到携带大麦α淀粉酶抑制蛋白基因的2H染色体导入小麦后,淀粉品质发生了改变,外观品质由原来"中国春"的半粉质转变为代换系的半角质.     

Translating insights from the seed metabolome into improved prediction for lipid-composition traits in oat (Avena sativa L.)

Oat (Avena sativa L.) seed is a rich resource of beneficial lipids, soluble fiber, protein, and antioxidants, and is considered a healthful food for humans. Little is known regarding the genetic controllers of variation for these compounds in oat seed. We characterized natural variation in the mature seed metabolome using untargeted metabolomics on 367 diverse lines and leveraged this information to improve prediction for seed quality traits. We used a latent factor approach to define unobserved variables that may drive covariance among metabolites. One hundred latent factors were identified, of which 21% were enriched for compounds associated with lipid metabolism. Through a combination of whole-genome regression and association mapping, we show that latent factors that generate covariance for many metabolites tend to have a complex genetic architecture. Nonetheless, we recovered significant associations for 23% of the latent factors. These associations were used to inform a multi-kernel genomic prediction model, which was used to predict seed lipid and protein traits in two independent studies. Predictions for 8 of the 12 traits were significantly improved compared to genomic best linear unbiased prediction when this prediction model was informed using associations from lipid-enriched factors. This study provides new insights into variation in the oat seed metabolome and provides genomic resources for breeders to improve selection for health-promoting seed quality traits. More broadly, we outline an approach to distill high-dimensional “omics” data to a set of biologically meaningful variables and translate inferences on these data into improved breeding decisions.     

Copy number variants (CNVs) in primate species using array-based comparative genomic hybridization

A substantial amount of genomic variation is now known to exist in humans and other primate species. Single nucleotide polymorphisms (SNPs) are thought to represent the vast majority of genomic differences among individuals in a given primate species and comprise about 0.1% of the genomes of two humans. However, recent studies have now shown that structural variation msay account for as much as 0.7% of the genomic differences in humans, of which copy number variants (CNVs) are the largest component. CNVs are segments of DNA that can range in size from hundreds of bases to millions of base pairs in length and have different number of copies between individuals. Recent technological advancements in array technologies led to genome-wide identification of CNVs and consequently revealed thousands of variable loci in humans, comprising as much as 12% of the human genome [A.J. Iafrate, L. Feuk, M.N. Rivera, M.L. Listewnik, P.K. Donahoe, Y. Qi, S.W. Scherer, C. Lee, Nat. Genet. 36 (2004) 949–951, [3]]. CNVs in humans have already been associated with susceptibility to certain complex diseases, dietary adaptation, and several neurological conditions. In addition, recent studies have shown that CNVs can be successfully implemented in population genetics research, providing important insights into human genetic variation. Nevertheless, the important role of CNVs in primate evolution and genetic diversity is still largely unknown. This article aims to outline the strengths and weaknesses of current comparative genomic hybridization array technologies that have been employed to detect CNV variation and the applications of these techniques to primate genetic research.     

THE GENOMIC TRAJECTORY OF HYBRID SWARMS: OUTCOMES OF REPEATED CROSSES BETWEEN POPULATIONS OF TIGRIOPUS CALIFORNICUS

Introgressive hybridization between genetically divergent populations is an important evolutionary process. The degree to which repeated hybridization events between the same parental taxa lead to similar genomic outcomes is unknown. This study addressed this question by following genomic trajectories of replicate hybrid swarms of the copepod Tigriopus californicus over many generations of free mating. Swarm composition was determined both by differential reproductive success of founder individuals and subsequent selection on hybrid genotypes. For one cross, between two populations showing differential fitness in the laboratory and no hybrid breakdown, the genetic trajectory was highly repeatable: replicates rapidly became dominated by alleles from the fitter parent. In a second cross, between two populations showing similar fitness and significant F2 hybrid breakdown, alleles from alternative populations dominated different replicates. Swarms exhibited a general temporal trend of decreasing cytonuclear mismatch. Some patterns of differential introgression across the genome were strikingly congruent amongst swarm replicates, both within and between cross types, and reflected patterns of segregation distortion previously observed within controlled crosses between the same parental populations. Differences in heterozygosity between the sexes, and evidence for a previously suspected sex‐distortion locus, suggest that complex interactions between sex and genotype influence hybrid swarm outcome.     

A place to land: spatiotemporal drivers of stopover habitat use by migrating birds

Migrating birds require en route habitats to rest and refuel. Yet, habitat use has never been integrated with passage to understand the factors that determine where and when birds stopover during spring and autumn migration. Here, we introduce the stopover‐to‐passage ratio (SPR), the percentage of passage migrants that stop in an area, and use 8 years of data from 12 weather surveillance radars to estimate over 50% SPR during spring and autumn through the Gulf of Mexico and Atlantic coasts of the south‐eastern US, the most prominent corridor for North America’s migratory birds. During stopovers, birds concentrated close to the coast during spring and inland in forested landscapes during autumn, suggesting seasonal differences in habitat function and highlighting the vital role of stopover habitats in sustaining migratory communities. Beyond advancing understanding of migration ecology, SPR will facilitate conservation through identification of sites that are disproportionally selected for stopover by migrating birds.     

Genomic Imprinting As a Window into Human Language Evolution

Humans spend large portions of their time and energy talking to one another, yet it remains unclear whether this activity is primarily selfish or altruistic. Here, it is shown how parent‐of‐origin specific gene expression—or “genomic imprinting”—may provide an answer to this question. First, it is shown why, regarding language, only altruistic or selfish scenarios are expected. Second, it is pointed out that an individual's maternal‐origin and paternal‐origin genes may have different evolutionary interests regarding investment into language, and that this intragenomic conflict may drive genomic imprinting which—as the direction of imprint depends upon whether investment into language is relatively selfish or altruistic—may be used to discriminate between these two possibilities. Third, predictions concerning the impact of various mutations and epimutations at imprinted loci on language pathologies are derived. In doing so, a framework is developed that highlights avenues for using intragenomic conflicts to investigate the evolutionary drivers of language.