Germplasm-regression-combined (GRC) marker-trait association identification in plant breeding: a challenge for plant biotechnological breeding under soil water deficit conditions

In the past 20 years, the major effort in plant breeding has changed from quantitative to molecular genetics with emphasis on quantitative trait loci (QTL) identification and marker assisted selection (MAS). However, results have been modest. This has been due to several factors including absence of tight linkage QTL, non-availability of mapping populations, and substantial time needed to develop such populations. To overcome these limitations, and as an alternative to planned populations, molecular marker–trait associations have been identified by the combination between germplasm and the regression technique. In the present preview, the authors (1) survey the successful applications of germplasm–regression–combined (GRC) molecular marker–trait association identification in plants; (2) describe how to do the GRC analysis and its differences from mapping QTL based on a linkage map reconstructed from the planned populations; (3) consider the factors that affect the GRC association identification, including selections of optimal germplasm and molecular markers and testing of identification efficiency of markers associated with traits; and (4) finally discuss the future prospects of GRC marker–trait association analysis used in plant MAS/QTL breeding programs, especially in long-juvenile woody plants when no other genetic information such as linkage maps and QTL are available.     

Allele-specific CAPS markers based on point mutations in resistance alleles at the pvr1 locus encoding eIF4E in Capsicum

Marker-assisted selection has been widely implemented in crop breeding and can be especially useful in cases where the traits of interest show recessive or polygenic inheritance and/or are difficult or impossible to select directly. Most indirect selection is based on DNA polymorphism linked to the target trait, resulting in error when the polymorphism recombines away from the mutation responsible for the trait and/or when the linkage between the mutation and the polymorphism is not conserved in all relevant genetic backgrounds. In this paper, we report the generation and use of molecular markers that define loci for selection using cleaved amplified polymorphic sequences (CAPS). These CAPS markers are based on nucleotide polymorphisms in the resistance gene that are perfectly correlated with disease resistance, the trait of interest. As a consequence, the possibility that the marker will not be linked to the trait in all backgrounds or that the marker will recombine away from the trait is eliminated. We have generated CAPS markers for three recessive viral resistance alleles used widely in pepper breeding, pvr1, pvr1 ¹, and pvr1 ². These markers are based on single nucleotide polymorphisms (SNPs) within the coding region of the pvr1 locus encoding an eIF4E homolog on chromosome 3. These three markers define a system of indirect selection for potyvirus resistance in Capsicum based on genomic sequence. We demonstrate the utility of this marker system using commercially significant germplasm representing two Capsicum species. Application of these markers to Capsicum improvement is discussed.     

Bulked sample analysis in genetics,genomics and crop improvement

Biological assay has been based on analysis of all individuals collected from sample populations. Bulked sample analysis (BSA), which works with selected and pooled individuals, has been extensively used in gene mapping through bulked segregant analysis with biparental populations, mapping by sequencing with major gene mutants and pooled genomewide association study using extreme variants. Compared to conventional entire population analysis, BSA significantly reduces the scale and cost by simplifying the procedure. The bulks can be built by selection of extremes or representative samples from any populations and all types of segregants and variants that represent wide ranges of phenotypic variation for the target trait. Methods and procedures for sampling, bulking and multiplexing are described. The samples can be analysed using individual markers, microarrays and high‐throughput sequencing at all levels of DNA, RNA and protein. The power of BSA is affected by population size, selection of extreme individuals, sequencing strategies, genetic architecture of the trait and marker density. BSA will facilitate plant breeding through development of diagnostic and constitutive markers, agronomic genomics, marker‐assisted selection and selective phenotyping. Applications of BSA in genetics, genomics and crop improvement are discussed with their future perspectives.     

Usefulness of marker‐assisted selection to improve maize for increased resistance to Sesamia nonagrioides attack with no detrimental effect on yield

Two decades of investigations on maize resistance to Mediterranean corn borer (Sesamia nonagrioides Lefebvre; MCB) have shown that breeding for increased resistance to stem tunnelling by MCB often resulted in reduced yield because significant genetic correlation between both traits exists in some backgrounds. Unlike phenotypic selection, marker‐assisted selection (MAS) could differentiate markers linked only to one trait from those linked simultaneously to yield potential and susceptibility to the pest. In the current study, the suitability of MAS for improving resistance to stem tunnelling without adverse effects on yield has been tested. The unfavourable genetic relationship between yield potential and susceptibility could be overcome using MAS. Gains obtained using MAS were weak, because genetic variance explained by the quantitative trait loci (QTL) was low but results encourage us to persevere in using marker information for simultaneous improvement of resistance and yield especially if genome‐wide approaches are applied. Approaches to detect QTL are widely used, but studies on the suitability of markers linked to QTL for performing MAS have been mostly neglected.     

DNA-marking of quantitative traits in corn

Methods of ISSR- and RAPD-analyses were used for marking quantitative trait loci (QTLs) determining the development of some morphological and biological traits in maize. Specificity of marker locus alleles was established for certain levels of polygenic trait phenotype manifestation. Criteria of marker locus informativity are discussed. A possibility of marker-assisted selection for valuable genotypes with desired for breeding trait values was demonstrated.     

The Effects of Selection on Linkage Analysis for Quantitative Traits

The effects of within-sample selection on the outcome of analyses detecting linkage between genetic markers and quantitative traits were studied. It was found that selection by truncation for the trait of interest significantly reduces the differences between marker genotype means thus reducing the power to detect linked quantitative trait loci (QTL). The size of this reduction is a function of proportion selected, the magnitude of the QTL effect, recombination rate between the marker locus and the QTL, and the allele frequency of the QTL. Proportion selected was the most influential of these factors on bias, e.g., for an allele substitution effect of one standard deviation unit, selecting the top 80%, 50% or 20% of the population required 2, 6 or 24 times the number of progeny, respectively, to offset the loss of power caused by this selection. The effect on power was approximately linear with respect to the size of gene effect, almost invariant to recombination rate, and a complex function of QTL allele frequency. It was concluded that experimental samples from animal populations which have been subjected to even minor amounts of selection will be inefficient in yielding information on linkage between markers and loci influencing the quantitative trait under selection.     

Development of a PCR-based SNP marker system for effective selection of kernel length and kernel elongation in rice

Kernel length in rice (Oryza sativa L.) is controlled by various quantitative trait loci of which GS3 is the most important, being responsible for 80–90% of the variation in kernel length. A mutation in the second exon of this gene has been reported to be associated with maximum variations in the kernel length. We have developed a simple PCR-based marker system named DRR-GL which targets the functional nucleotide polymorphism at GS3. This marker system has the advantages that it is easy to use, saves time and cost, and is amenable for large-scale marker-assisted selection for the trait of kernel length. Validation of this marker in a segregating population and 152 rice varieties, which includes 30 elite basmati varieties, reveals its effective co-segregation and association with the traits of kernel length as well as kernel elongation after cooking. We recommend utilization of this simple, low-cost marker system in breeding programs targeted at improvement of key rice grain quality traits, kernel length and kernel elongation.     

A quantitative genetics model for viability selection

Viability selection will change gene frequencies of loci controlling fitness. Consequently, the frequencies of marker loci linked to the viability loci will also change. In genetic mapping, the change of marker allelic frequencies is reflected by the departure from Mendelian segregation ratio. The non-Mendelian segregation of markers has been used to map viability loci along the genome. However, current methods have not been able to detect the amount of selection (s) and the degree of dominance (h) simultaneously. We developed a method to detect both s and h using an F2 mating design under the classical fitness model. We also developed a quantitative genetics model for viability selection by proposing a continuous liability controlling the viability of individuals. With the liability model, mapping viability loci has been formulated as mapping quantitative trait loci. As a result, nongenetic systematic environmental effects can be easily incorporated into the model and subsequently separated from the genetic effects of the viability loci. The quantitative genetic model has been verified with a series of Monte Carlo simulation experiments.     

yellow 0, a marker for low body weight in Drosophila melanogaster

Marker-assisted selection(MAS) is an important modern breeding technique,but it has been found that the effect of the markers for quantitative trait loci(QTL) is inconsistent,leading in some cases to MAS failure and raising doubts about its effectiveness.Here the model organism Drosophila melanogaster was employed to study whether an effective marker could be found and applied to MAS.We crossed the stock carrying the y0 marker(a recessive mutation allele of the yellow gene on the X chromosome) with three ot...     

Moving from QTL experimental results to the utilization of QTL in breeding programmes

Results from quantitative trait loci studies cannot be readily implemented into breeding schemes through marker assisted selection because of uncertainty about whether the quantitative trait loci identified are real and whether the identified quantitative trait loci are segregating in the breeding population. The present paper outlines and discusses strategies to reduce uncertainty in the results from quantitative trait loci studies. One strategy to confirm results from quantitative trait loci studies is to combine P -values from many quantitative trait loci experiments, while another is to establish a confirmation study. The power of a confirmation study must be high to ensure that the postulated quantitative trait loci can be verified. In the calculation of the experimental power, there are many issues that have to be addressed: size of the quantitative trait loci to be detected, significance level required, experimental design and expected heterozygosity for the design. To ensure marker assisted selection can be quickly implemented once quantitative trait loci are confirmed, DNA samples should be retained from daughters, and the sires and dams of elite sires.     

QTL mapping under truncation selection in homozygous lines derived from biparental crosses

In plant breeding, a large number of progenies that will be discarded later in the breeding process must be phenotyped and marker genotyped for conducting QTL analysis. In many cases, phenotypic preselection of lines could be useful. However, in QTL analyses even moderate preselection can have a significant effect on the power of QTL detection and estimation of effects of the target traits. In this study, we provide exact formulas for quantifying the change of allele frequencies within marker classes, expectations of marker contrasts and the variance of the marker contrasts under truncation selection, for the general case of two QTL affecting the target trait and a correlated trait. We focused on homozygous lines derived at random from biparental crosses. The effects of linkage between the marker and the QTL under selection as well as the effect of selection on a correlated trait can be quantified with the given formulas. Theoretical results clearly show that depending on the magnitude of QTL effects, high selection intensities can lead to a dramatic reduction in power of QTL detection and that approximations based on the infinitesimal model deviate substantially from exact solutions. The presented formulas are valuable for choosing appropriate selection intensity when performing QTL mapping experiments on the data on phenotypically preselected traits and enable the calculation and bias correction of the effects of QTL under selection. Application of our theory to experimental data revealed that selection-induced bias of QTL effects can be successfully corrected.     

陆地棉HB红花性状特异SCAR分子标记的开发

利用Operon系列引物筛选到1个与HB红花性状基因连锁的RAPD标记OPA15^1160,对差异条带进行克隆与核苷酸测序,根据测序结果设计SCAR引物,在HB红花近等基因系及其白花轮回亲本中进行PCR扩增程序优化和鉴定,筛选出一对引物可稳定扩增出与HB红花性状基因连锁的特异片段,获得了与HB红花性状基因紧密连锁的SCAR标记HB^-330。利用具黄色花瓣紫红色基斑的海岛棉与粉红花瓣的红叶棉等种质材料以7LHB红花近等基因系与白花轮回亲本杂交的F1、BC1F1、F2群体,对该SCAR标记的特异性与准确性进行了鉴定与验证,在红花植株中扩增出了330bp大小的片段而在白花植株中未扩增出,证明该标记准确性高、重复性好。HB红花是通过远缘杂交转自野生二倍体比克氏棉的性状,已成功地应用于性状标记杂交棉育种。该SCAR标记不仅为HB红花标记杂交种的纯度鉴定提供了有效技术手段,也为新品种保护提供了技术支持,促进了红花性状杂交种的分子标记辅助育种进程。     

作物分子标记辅助选择的研究进展、影响因素及其发展策略

随着分子标记技术及其检测手段的发展,开发和应用成本的降低,分子标记辅助选择(MAS)在作物育种上的应用优势日益明显。本文综述了近年来MAS在基因聚合、基因转移和数量性状改良上的研究进展。总结了MAS的影响因素,包括标记与基因间的距离、目标性状的遗传率、群体大小、所用分子标记的数目、类型和相位等。并提出育种和定位同步进行、选择合适分子标记类型和数量、简化DNA提取方法、背景选择的逐步选择法、确定合适选择方案等MAS发展策略。     

Long-term impacts of genome-enabled selection

The objective was to evaluate the effects of directional selection based on estimated genomic breeding values (GEBVs) for a quantitative trait. Selection affects GEBV prediction accuracy as well as genetic architecture via changes in allelic frequencies and linkage disequilibrium (LD), and the resulting changes are different from those in the absence of selection. How marker density affects long-term GEBV accuracy and selection response needs to be understood as well. Simulations were used to characterize the impact of selection based on GEBVs over generations. Single-nucleotide polymorphism (SNP) marker effects were estimated with the Bayesian Lasso method in the base generation, and these estimates were used to calculate the GEBVs in subsequent generations. GEBV accuracy decreased over generations of selection, and it was lower than under random selection, where a decay took place as well. In the long term, selection response tended to reach a plateau, but, at higher marker density, both the magnitude and duration of the response were larger. Selection changed quantitative trait loci (QTL) allele frequencies and generated new but unfavorable LD for prediction. Family effects had a considerable contribution to GEBV accuracy in early generations of selection.     

Accuracy of genomic selection using different methods to define haplotypes

Genomic selection uses total breeding values for juvenile animals, predicted from a large number of estimated marker haplotype effects across the whole genome. In this study the accuracy of predicting breeding values is compared for four different models including a large number of markers, at different marker densities for traits with heritabilities of 50 and 10%. The models estimated the effect of (1) each single-marker allele [single-nucleotide polymorphism (SNP)1], (2) haplotypes constructed from two adjacent marker alleles (SNP2), and (3) haplotypes constructed from 2 or 10 markers, including the covariance between haplotypes by combining linkage disequilibrium and linkage analysis (HAP_IBD2 and HAP_IBD10). Between 119 and 2343 polymorphic SNPs were simulated on a 3-M genome. For the trait with a heritability of 10%, the differences between models were small and none of them yielded the highest accuracies across all marker densities. For the trait with a heritability of 50%, the HAP_IBD10 model yielded the highest accuracies of estimated total breeding values for juvenile and phenotyped animals at all marker densities. It was concluded that genomic selection is considerably more accurate than traditional selection, especially for a low-heritability trait.     

Verification of marker–trait associations in biparental winter barley (<Emphasis Type="Italic">Hordeum vulgare</Emphasis> L.) DH populations

In previous genome-wide association studies, marker–trait associations for grain yield and additional traits of agronomic importance were identified in the German winter barley (Hordeum vulgare L.) breeding gene pool. In the present study, seven doubled haploid populations segregating for the relevant alleles at the associated loci were used to get information whether these marker–trait associations can be verified in biparental populations and reliably used in applied barley breeding. The doubled haploid populations were phenotyped in field trials at two to five locations each in 1 year and genotyped by 40 trait-associated single nucleotide polymorphisms using an Illumina VeraCode GoldenGate assay. Large phenotypic variation was observed for all traits within at least one doubled haploid population. For 19 out of 58 marker–trait associations tested, the phenotypic means of both marker classes were significantly (p ≤ 0.005) different, thus confirming the association of the respective marker and the quantitative trait locus detected. For example, doubled haploid lines derived from a cross of ‘Malta’ × ‘Goldmine’ carrying different marker alleles differed by 0.41 t/ha in mean grain yield. The 19 (out of 58) marker–trait associations verified correspond to 10 (out of 27) genomic regions. Markers that were verified to be associated with a quantitative trait locus can be implemented directly in winter barley breeding for the selection of parental lines and marker-assisted pedigree selection.     

性状遗传力与QTL方差对标记辅助选择效果的影响

在采用动物模型标记辅助最佳线性无偏预测方法对个体育种值进行估计的基础上,模拟了在一个闭锁群体内连续对单个性状选择10个世代的情形,并系统地比较了性状遗传力和QTL方差对标记辅助选择所获得的遗传进展、QTL增效基因频率和群体近交系数变化的影响。结果表明：在对高遗传力和QTL方差较小的性状实施标记辅助选择时,可望获得更大的遗传进展;遗传力越高,QTL方差越大,则QTL增效基因频率的上升速度越快;遗传力较高时,群体近交系数上升的速度较为缓慢,而QTL方差对群体近交系数上升速度的影响则不甚明显。结合前人关于标记辅助选择相对效率的研究结果,可以认为：当选择性状的遗传力和QTL方差为中等水平时,标记辅助选择可望获得理想的效果。     

DNA markers in plant improvement: an overview

The progress made in DNA marker technology has been tremendous and exciting. DNA markers have provided valuable tools in various analyses ranging from phylogenetic analysis to the positional cloning of genes. The development of high-density molecular maps which has been facilitated by PCR-based markers, have made the mapping and tagging of almost any trait possible. Marker-assisted selection has the potential to deploy favorable gene combinations for disease control. Comparative studies between incompatible species using these markers has resulted in synteny maps which are useful not only in predicting genome organization and evolution but also have practical application in plant breeding. DNA marker technology has found application in fingerprinting genotypes, in determining seed purity, in systematic sampling of germplasm, and in phylogenetic analysis. This review discusses the use of this technology for the genetic improvement of plants.