Key questions in the genetics and genomics of eco-evolutionary dynamics

Increasing acceptance that evolution can be ‘rapid'' (or ‘contemporary'') has generated growing interest in the consequences for ecology. The genetics and genomics of these ‘eco-evolutionary dynamics'' will be—to a large extent—the genetics and genomics of organismal phenotypes. In the hope of stimulating research in this area, I review empirical data from natural populations and draw the following conclusions. (1) Considerable additive genetic variance is present for most traits in most populations. (2) Trait correlations do not consistently oppose selection. (3) Adaptive differences between populations often involve dominance and epistasis. (4) Most adaptation is the result of genes of small-to-modest effect, although (5) some genes certainly have larger effects than the others. (6) Adaptation by independent lineages to similar environments is mostly driven by different alleles/genes. (7) Adaptation to new environments is mostly driven by standing genetic variation, although new mutations can be important in some instances. (8) Adaptation is driven by both structural and regulatory genetic variation, with recent studies emphasizing the latter. (9) The ecological effects of organisms, considered as extended phenotypes, are often heritable. Overall, the study of eco-evolutionary dynamics will benefit from perspectives and approaches that emphasize standing genetic variation in many genes of small-to-modest effect acting across multiple traits and that analyze overall adaptation or ‘fitness''. In addition, increasing attention should be paid to dominance, epistasis and regulatory variation.     

Genomic screening for artificial selection during domestication and improvement in maize

BACKGROUND: Artificial selection results in phenotypic evolution. Maize (Zea mays L. ssp. mays) was domesticated from its wild progenitor teosinte (Zea mays subspecies parviglumis) through a single domestication event in southern Mexico between 6000 and 9000 years ago. This domestication event resulted in the original maize landrace varieties. The landraces provided the genetic material for modern plant breeders to select improved varieties and inbred lines by enhancing traits controlling agricultural productivity and performance. Artificial selection during domestication and crop improvement involved selection of specific alleles at genes controlling key morphological and agronomic traits, resulting in reduced genetic diversity relative to unselected genes. SCOPE: This review is a summary of research on the identification and characterization by population genetics approaches of genes affected by artificial selection in maize. CONCLUSIONS: Analysis of DNA sequence diversity at a large number of genes in a sample of teosintes and maize inbred lines indicated that approx. 2 % of maize genes exhibit evidence of artificial selection. The remaining genes give evidence of a population bottleneck associated with domestication and crop improvement. In a second study to efficiently identify selected genes, the genes with zero sequence diversity in maize inbreds were chosen as potential targets of selection and sequenced in diverse maize landraces and teosintes, resulting in about half of candidate genes exhibiting evidence for artificial selection. Extended gene sequencing demonstrated a low false-positive rate in the approach. The selected genes have functions consistent with agronomic selection for plant growth, nutritional quality and maturity. Large-scale screening for artificial selection allows identification of genes of potential agronomic importance even when gene function and the phenotype of interest are unknown. These approaches should also be applicable to other domesticated species if specific demographic conditions during domestication exist.     

关联分析及其在植物遗传学研究中的应用

植物的很多重要经济性状均属于复杂性状。基于连锁分析的QTL作图是研究复杂性状的有效手段, 但其尚存在一定的局限性。随着现代生物学的发展, 一种基于连锁不平衡的新剖分复杂性状方法--关联分析法, 开始应用于植物遗传学研究。与QTL作图法相比, 应用关联分析法具有不需要构建特殊的群体, 可同时对多个等位基因进行分析, 定位QTL精度可达到单基因水平等优势。该文介绍了关联分析方法学的基础和特性, 简述了其在植物遗传学研究中的进展情况, 并对其未来发展和在植物遗传学研究中的应用进行了展望。     

玉米叶夹角形成的遗传基础与分子机制解析*

玉米产量取决于植株捕获光能和固定CO₂合成有机化合物的效率。叶夹角是株型重要性状之一,较小叶夹角有利于提高玉米植株光合作用效率和种植密度,因而有利于提高玉米产量。研究表明玉米叶夹角为多基因控制的复杂数量性状,其遗传力较高,主要受基因的加性效应调控。目前,利用数量性状位点(quantitative trait loci, QTL)定位和全基因组关联分析(genome-wide association study, GWAS)等方法已鉴定数百个玉米叶夹角相关QTL;结合突变体分析等方法,已克隆数十个调控叶夹角关键基因,这为了解玉米叶夹角遗传机制提供了重要参考。由于前人研究所采用群体、分析方法及参考基因组版本不同,各研究之间所鉴定QTL差异较大,因此无法客观揭示叶夹角性状的遗传规律。为此,通过总结前人所定位叶夹角相关QTL和单核苷酸多态性(single nucleotide polymorphism,SNP)位点并构建一致性图谱,鉴定出叶夹角性状定位热点区间,并对调控叶夹角的已知基因进行功能分类。这不仅为了解玉米叶夹角的遗传结构、推动叶夹角相关重要基因克隆提供数据支撑,也对进一步开发叶夹角相关分子标记,指导玉米分子育种和提高玉米产量提供有益指导。     

The evolution of genetic architectures underlying quantitative traits

In the classic view introduced by R. A. Fisher, a quantitative trait is encoded by many loci with small, additive effects. Recent advances in quantitative trait loci mapping have begun to elucidate the genetic architectures underlying vast numbers of phenotypes across diverse taxa, producing observations that sometimes contrast with Fisher''s blueprint. Despite these considerable empirical efforts to map the genetic determinants of traits, it remains poorly understood how the genetic architecture of a trait should evolve, or how it depends on the selection pressures on the trait. Here, we develop a simple, population-genetic model for the evolution of genetic architectures. Our model predicts that traits under moderate selection should be encoded by many loci with highly variable effects, whereas traits under either weak or strong selection should be encoded by relatively few loci. We compare these theoretical predictions with qualitative trends in the genetics of human traits, and with systematic data on the genetics of gene expression levels in yeast. Our analysis provides an evolutionary explanation for broad empirical patterns in the genetic basis for traits, and it introduces a single framework that unifies the diversity of observed genetic architectures, ranging from Mendelian to Fisherian.     

Genome‐wide identification and analysis of heterotic loci in three maize hybrids

Heterosis, or hybrid vigour, is a predominant phenomenon in plant genetics, serving as the basis of crop hybrid breeding, but the causative loci and genes underlying heterosis remain unclear in many crops. Here, we present a large‐scale genetic analysis using 5360 offsprings from three elite maize hybrids, which identifies 628 loci underlying 19 yield‐related traits with relatively high mapping resolutions. Heterotic pattern investigations of the 628 loci show that numerous loci, mostly with complete–incomplete dominance (the major one) or overdominance effects (the secondary one) for heterozygous genotypes and nearly equal proportion of advantageous alleles from both parental lines, are the major causes of strong heterosis in these hybrids. Follow‐up studies for 17 heterotic loci in an independent experiment using 2225 F₂ individuals suggest most heterotic effects are roughly stable between environments with a small variation. Candidate gene analysis for one major heterotic locus (ub3) in maize implies that there may exist some common genes contributing to crop heterosis. These results provide a community resource for genetics studies in maize and new implications for heterosis in plants.     

玉米雄穗性状遗传结构与形成分子机制*

玉米为雌雄同株异花植物,其雄穗着生于植株顶部,雌穗腋生。雄穗一方面需产生足量花粉以保证雌穗授粉结实,另一方面由于对下部叶片的遮蔽作用和自身营养需求,其生长发育会同时影响叶片光合作用效率和能量分配,因此优化雄穗结构是提高玉米产量的重要措施之一。玉米雄穗性状包括雄穗分枝数、雄穗分枝长度、雄穗主轴长度、雄穗分枝总长度、雄穗分枝角度等,均为多基因控制的数量性状。自20世纪90年代,研究者开始利用数量性状位点(quantitative trait locus,QTL)定位方法解析玉米雄穗性状遗传结构;随着玉米自交系B73等参考基因组释放,以及DNA微阵列、基因组重测序等高通量基因分型技术的日益成熟,全基因组关联分析(genome-wide association study, GWAS)成为数量性状遗传研究的主流方法,目前已鉴定出大量玉米雄穗性状遗传位点。通过总结雄穗性状遗传定位研究结果,构建一致性图谱并挖掘定位热点区间,有助于进一步了解雄穗性状遗传结构特征及指导雄穗性状候选基因克隆。此外,通过对调控雄穗发育的已知基因进行功能分类,可为解析玉米雄穗发育的遗传网络和调控通路提供理论支撑。     

Evolution of quantitative traits in the wild: mind the ecology

Recent advances in the quantitative genetics of traits in wild animal populations have created new interest in whether natural selection, and genetic response to it, can be detected within long-term ecological studies. However, such studies have re-emphasized the fact that ecological heterogeneity can confound our ability to infer selection on genetic variation and detect a population''s response to selection by conventional quantitative genetics approaches. Here, I highlight three manifestations of this issue: counter gradient variation, environmentally induced covariance between traits and the correlated effects of a fluctuating environment. These effects are symptomatic of the oversimplifications and strong assumptions of the breeder''s equation when it is applied to natural populations. In addition, methods to assay genetic change in quantitative traits have overestimated the precision with which change can be measured. In the future, a more conservative approach to inferring quantitative genetic response to selection, or genomic approaches allowing the estimation of selection intensity and responses to selection at known quantitative trait loci, will provide a more precise view of evolution in ecological time.     

The evolutionary response of mating system to heterosis

Isolation allows populations to diverge and to fix different alleles. Deleterious alleles that reach locally high frequencies contribute to genetic load, especially in inbred or selfing populations, in which selection is relaxed. In the event of secondary contact, the recessive portion of the genetic load is masked in the hybrid offspring, producing heterosis. This advantage, only attainable through outcrossing, should favour evolution of greater outcrossing even if inbreeding depression has been purged from the contributing populations. Why, then, are selfing‐to‐outcrossing transitions not more common? To evaluate the evolutionary response of mating system to heterosis, we model two monomorphic populations of entirely selfing individuals, introduce a modifier allele that increases the rate of outcrossing and investigate whether the heterosis among populations is sufficient for the modifier to invade and fix. We find that the outcrossing mutation invades for many parameter choices, but it rarely fixes unless populations harbour extremely large unique fixed genetic loads. Reversions to outcrossing become more likely as the load becomes more polygenic, or when the modifier appears on a rare background, such as by dispersal of an outcrossing genotype into a selfing population. More often, the outcrossing mutation instead rises to moderate frequency, which allows recombination in hybrids to produce superior haplotypes that can spread without the mutation's further assistance. The transience of heterosis can therefore explain why secondary contact does not commonly yield selfing‐to‐outcrossing transitions.     

Digest: Exposing the role of rare alleles in inbreeding depression in monkeyflower*

Outcrossing is maintained in many hermaphroditic species despite theoretical work suggesting that alleles increasing selfing should invade outcrossing populations. Brown and Kelly (2019) identify reasons why this may not have occurred in an outcrossing population of monkeyflower, namely that inbreeding depression causes strong reductions in fitness, resulting in selection for the maintenance of outcrossing. They find that genetic load imposed by rare alleles is inversely correlated with fitness-associated traits, providing evidence that recessive, deleterious alleles contribute to inbreeding depression.     

Beyond pathways: genetic dissection of tocopherol content in maize kernels by combining linkage and association analyses

Although tocopherols play an important role in plants and animals, the genetic architecture of tocopherol content in maize kernels has remained largely unknown. In this study, linkage and association analyses were conducted to examine the genetic architecture of tocopherol content in maize kernels. Forty‐one unique quantitative trait loci (QTLs) were identified by linkage mapping in six populations of recombinant inbred lines (RILs). In addition, 32 significant loci were detected via genome‐wide association study (GWAS), 18 of which colocalized with the QTLs identified by linkage mapping. Fine mapping of a major QTL validated the accuracy of GWAS and QTL mapping results and suggested a role for nontocopherol pathway genes in the modulation of natural tocopherol variation. We provided genome‐wide evidence that genes involved in fatty acid metabolism, chlorophyll metabolism and chloroplast function may affect natural variation in tocopherols. These findings were confirmed through mutant analysis of a particular gene from the fatty acid pathway. In addition, the favourable alleles for many of the significant SNPs/QTLs represented rare alleles in natural populations. Together, our results revealed many novel genes that are potentially involved in the variation of tocopherol content in maize kernels. Pyramiding of the favourable alleles of the newly elucidated genes and the well‐known tocopherol pathway genes would greatly improve tocopherol content in maize.     

Efficient Multiple-Trait Association and Estimation of Genetic Correlation Using the Matrix-Variate Linear Mixed Model

Multiple-trait association mapping, in which multiple traits are used simultaneously in the identification of genetic variants affecting those traits, has recently attracted interest. One class of approaches for this problem builds on classical variance component methodology, utilizing a multitrait version of a linear mixed model. These approaches both increase power and provide insights into the genetic architecture of multiple traits. In particular, it is possible to estimate the genetic correlation, which is a measure of the portion of the total correlation between traits that is due to additive genetic effects. Unfortunately, the practical utility of these methods is limited since they are computationally intractable for large sample sizes. In this article, we introduce a reformulation of the multiple-trait association mapping approach by defining the matrix-variate linear mixed model. Our approach reduces the computational time necessary to perform maximum-likelihood inference in a multiple-trait model by utilizing a data transformation. By utilizing a well-studied human cohort, we show that our approach provides more than a 10-fold speedup, making multiple-trait association feasible in a large population cohort on the genome-wide scale. We take advantage of the efficiency of our approach to analyze gene expression data. By decomposing gene coexpression into a genetic and environmental component, we show that our method provides fundamental insights into the nature of coexpressed genes. An implementation of this method is available at http://genetics.cs.ucla.edu/mvLMM.     

Evaluation of maize genotypes for fodder quality traits and SSR diversity

Maize is an important fodder resource for ruminants. The yield and quality of fodder is governed by genetic variability and interaction of genotypes with environment. Therefore, it is prerequisite to evaluate the available variability for fodder traits in maize. For this, 75 genotypes were evaluated in three replications for 2 years. Data were recorded on eight morphological traits including green fodder yield and dried fodder samples were evaluated for eight fodder quality traits. Wide range of estimates for fodder quality and productivity characters except DFF and LSR reflects the existence of significant variations among genotypes. ANOVA revealed significant variety × year interaction for seven traits. Plant height, stem girth, leaf-length and -width demonstrated positive correlation with green fodder yield per plant. Inverse association was observed between crude protein and cell wall component (NDF, hemicellulose). First three principle components explained 44.28% of the total variation. Two-way clustering grouped the genotypes and traits into five and three major clusters, respectively. During SSR analysis, a total of 133 alleles from 21 primers were generated with mean PIC value was 0.58. The genetic distance between genotypes was ranging between 0.16 and 0.75 with an average of 0.49. All genotypes were clustered in three main groups and clustering was consistent with genotype origin. A weak correlation was identified between morphological and molecular distance. Eventually results suggested that both morphotypes and molecular markers should exploit simultaneously to reveal the true genetic diversity to get maximum heterosis through hybridization.     

玉米雌穗性状遗传分析与形成机制*

雌穗是玉米重要的生殖器官,雌穗发育决定成熟果穗大小及单穗粒重,进而直接影响玉米产量。雌穗性状主要包括穗长、穗粗、穗行数、行粒数、穗重、单穗粒重等,均为多基因控制的数量遗传性状,且其遗传结构各不相同。解析雌穗性状的遗传基础,优化雌穗结构,是玉米增产的重要途径。前人通过数量性状位点(quantitative trait locus mapping,QTL)定位和全基因组关联分析(genome-wide association study, GWAS)等方法,已经鉴定出较多雌穗性状相关的遗传位点,但是目前已鉴定功能的基因较少,所建立的遗传位点一致性图谱并不完整,因此难以全面揭示雌穗性状遗传结构。通过综合前人雌穗性状遗传定位进展,现将已鉴定QTL位点和显著关联SNP整合至玉米B73参考基因组V4版本,并鉴定出雌穗性状定位热点区间,对深入解析雌穗性状遗传结构、指导雌穗性状基因克隆和理解雌穗发育分子机制均具有重要意义。     

Genomic-based-breeding tools for tropical maize improvement

Maize has traditionally been the main staple diet in the Southern Asia and Sub-Saharan Africa and widely grown by millions of resource poor small scale farmers. Approximately, 35.4 million hectares are sown to tropical maize, constituting around 59% of the developing worlds. Tropical maize encounters tremendous challenges besides poor agro-climatic situations with average yields recorded <3 tones/hectare that is far less than the average of developed countries. On the contrary to poor yields, the demand for maize as food, feed, and fuel is continuously increasing in these regions. Heterosis breeding introduced in early 90 s improved maize yields significantly, but genetic gains is still a mirage, particularly for crop growing under marginal environments. Application of molecular markers has accelerated the pace of maize breeding to some extent. The availability of array of sequencing and genotyping technologies offers unrivalled service to improve precision in maize-breeding programs through modern approaches such as genomic selection, genome-wide association studies, bulk segregant analysis-based sequencing approaches, etc. Superior alleles underlying complex traits can easily be identified and introgressed efficiently using these sequence-based approaches. Integration of genomic tools and techniques with advanced genetic resources such as nested association mapping and backcross nested association mapping could certainly address the genetic issues in maize improvement programs in developing countries. Huge diversity in tropical maize and its inherent capacity for doubled haploid technology offers advantage to apply the next generation genomic tools for accelerating production in marginal environments of tropical and subtropical world. Precision in phenotyping is the key for success of any molecular-breeding approach. This article reviews genomic technologies and their application to improve agronomic traits in tropical maize breeding has been reviewed in detail.     

Domestication reshaped the genetic basis of inbreeding depression in a maize landrace compared to its wild relative,teosinte

Inbreeding depression is the reduction in fitness and vigor resulting from mating of close relatives observed in many plant and animal species. The extent to which the genetic load of mutations contributing to inbreeding depression is due to large-effect mutations versus variants with very small individual effects is unknown and may be affected by population history. We compared the effects of outcrossing and self-fertilization on 18 traits in a landrace population of maize, which underwent a population bottleneck during domestication, and a neighboring population of its wild relative teosinte. Inbreeding depression was greater in maize than teosinte for 15 of 18 traits, congruent with the greater segregating genetic load in the maize population that we predicted from sequence data. Parental breeding values were highly consistent between outcross and selfed offspring, indicating that additive effects determine most of the genetic value even in the presence of strong inbreeding depression. We developed a novel linkage scan to identify quantitative trait loci (QTL) representing large-effect rare variants carried by only a single parent, which were more important in teosinte than maize. Teosinte also carried more putative juvenile-acting lethal variants identified by segregation distortion. These results suggest a mixture of mostly polygenic, small-effect partially recessive effects in linkage disequilibrium underlying inbreeding depression, with an additional contribution from rare larger-effect variants that was more important in teosinte but depleted in maize following the domestication bottleneck. Purging associated with the maize domestication bottleneck may have selected against some large effect variants, but polygenic load is harder to purge and overall segregating mutational burden increased in maize compared to teosinte.     

MATING SYSTEM,HALDANE'S SIEVE,AND THE DOMESTICATION PROCESS

Mating systems are expected to have a strong influence on both the dynamic of adaptation and the genetic architecture of adaptive traits. In particular, the bias toward the fixation of dominant or partially dominant beneficial mutations predicted under outcrossing (Haldane's sieve) is expected to be reduced under self‐fertilization. To test this prediction in plants, we considered domestication as an example of adaptation. We compiled data from studies reporting the degree of dominance of quantitative trait loci (QTL) involved in the domestication syndrome. We found that adaptation to cultivation mostly proceeded through the selection of recessive and partially recessive genes in predominantly selfing species whereas a much larger fraction of domestication‐related QTL were dominant or partially dominant in outcrossers, as expected under Haldane's sieve. Our study also showed that levels of dominance in mixed mating crop species resemble those observed in selfers, suggesting that recessive alleles can contribute to adaptation even under moderate selfing rates. Although these results rely on a particular example of adaptation, they constitute one of the first attempts to test theoretical expectations on the level of dominance of genes involved in plant adaptation.