Members of the activity of bc1 complex (ABC1) family are protein kinases that are widely found in prokaryotes and eukaryotes. Previous studies showed that several plant ABC1 genes participated in the abiotic stress response. Here, we present the systematic identification of rice and Arabidopsis ABC1 genes and the expression analysis of rice ABC1 genes. A total of 15 and 17 ABC1 genes from the rice and Arabidopsis genomes, respectively, were identified using a bioinformatics approach. Phylogenetic analyses of these proteins suggested that the divergence of this family had occurred and their main characteristics were established before the monocot-dicot split. Indeed, species-specific expansion contributed to the evolution of this family in rice and Arabidopsis after the monocot-dicot split. Intron/exon structure analysis indicated that most of the orthologous genes had similar exon sizes, but diverse intron sizes, and the rice genes contained larger introns, moreover, intron gain was an important event accompanying the recent evolution of the rice ABC1 family. Multiple sequence alignment revealed one conserved amino acid segment and four conserved amino acids in the ABC1 domain. Online subcellular localization predicted that nine rice ABC1 proteins were localized in chloroplasts. Real-time RT-PCR established that the rice ABC1 genes were primarily expressed in leaves and the expression could be modulated by a broad range of abiotic factors such as H2O2, abscisic acid, low temperature, drought, darkness and high salinity. These results reveal that the rice ABC1 gene family plays roles in the environmental stress response and specific biological processes of rice.
镉是一种非必需的重金属元素,对动植物有严重毒害作用。几个与ABC1(activity of the bc1 complex)家族有关的基因参与植物镉胁迫的应答。本研究从玉米中克隆并鉴定了一个类ABC1基因,命名为ZmABC1-10。该基因cDNA全长2 519 bp,包含一个2 250 bp的开放阅读框,编码一个预测的叶绿体膜蛋白。启动子顺式元件扫描发现该基因含有大量的非生物胁迫、光以及植物激素应答元件。表达模式分析表明,该基因主要在叶片、茎秆等绿色组织中表达。镉处理实验表明,该基因能够被诱导并且受植物发育时期的调控。除镉之外,该基因还受多种非生物因素包括ABA、H2O2、干旱和黑暗的共同调控。此外,本研究利用基因组序列信息共鉴定出19个玉米ABC1基因。对植物界8个代表性物种中148个ABC1蛋白进行系统发育分析表明,在长期进化过程中植物ABC1蛋白已经发生了分化;物种特异性扩张是植物中该家族进化的主要动力。这些结果表明ZmAbc1-10是一个镉应答因子并且可能在植物对非生物胁迫的适应中发挥重要作用。
Chromosome segment substitution lines have been created in several experimental models,including many plant and animal species,and are useful tools for the genetic analysis and mapping of complex traits.The traditional t-test is usually applied to identify a quantitative trait locus (QTL) that is contained within a chromosome segment to estimate the QTL's effect.However,current methods cannot uncover the entire genetic structure of complex traits.For example,current methods cannot distinguish between main effects and epistatic effects.In this paper,a linear epistatic model was constructed to dissect complex traits.First,all the long substituted segments were divided into overlapping small bins,and each small bin was considered a unique independent variable.The genetic model for complex traits was then constructed.When considering all the possible main effects and epistatic effects,the dimensions of the linear model can become extremely high.Therefore,variable selection via stepwise regression (Bin-REG) was proposed for the epistatic QTL analysis in the present study.Furthermore,we tested the feasibility of using the LASSO (least absolute shrinkage and selection operator) algorithm to estimate epistatic effects,examined the fully Bayesian SSVS (stochastic search variable selection) approach,tested the empirical Bayes (E-BAYES) method,and evaluated the penalized likelihood (PENAL) method for mapping epistatic QTLs.Simulation studies suggested that all of the above methods,excluding the LASSO and PENAL approaches,performed satisfactorily.The Bin-REG method appears to outperform all other methods in terms of estimating positions and effects.
Epistasis between cytoplasmic and nuclear genes is the primary genetic component of complex quantitative traits.Genetic dissection of cytonuclear epistasis is fundamentally important to understand the genetic architecture of complex traits.In this study,a two-dimensional genome scan strategy was employed to evaluate the contribution of cytoplasm,quantitative trait loci (QTL),QTL×QTL interactions and QTL×QTL×cytoplasm interactions to the phenotypic variation.The p-value and parameter value for each genetic effect were calculated by multiple regression analysis.A stepwise approach was suggested to build confidence in candidate QTL on the basis of q-value estimation,false discovery rate calculation and Bonferroni adjustment.A fine-scale grid scan strategy was proposed for further analysis of peaks of interest.Plant height in maize was used as an example to illustrate the efficiency of the two-dimensional genome scan strategy.
