Evaluation of genomic approaches for marker‐based improvement of lodging tolerance in triticale

Lodging tolerance is an important agronomic trait as it can have a severe negative impact on grain yield and quality. Here, we used a large mapping population of 647 doubled haploid triticale lines derived from four families to dissect the genetic architecture underlying lodging tolerance and to assess different approaches for a genomics‐based improvement of the trait. The plants were evaluated for lodging in two environments and genotyped with 1710 genomewide DArT markers. We observed a large genotypic variation for lodging and transgressive segregation in all families. Employing two complementary QTL mapping approaches, we identified both main effect and epistatic QTL. Using cross‐validation, we showed that the proportion of genotypic variance explained by the detected QTL is low, thus limiting the efficiency of marker‐assisted selection to improve this trait. By contrast, the cross‐validated predictive ability of genomic prediction was approximately twice as high as that of the QTL‐based selection approaches. In conclusion, our results show that lodging tolerance is a complex trait that can be improved by classical breeding but also assisted by marker‐based approaches.     

Accuracy of within‐ and among‐family genomic prediction in triticale

Genomic prediction has emerged as a powerful genomic tool to assist breeding of complex traits. In this study, we employed a population of 647 triticale doubled haploid lines derived from four families to assess the potential of this approach for triticale breeding. All lines were phenotyped for grain yield, thousand‐kernel weight, biomass yield, plant height, frost tolerance and Fusarium head blight resistance. The obtained prediction accuracies were moderate to high and consisted to varying degrees of within‐ and among‐family variance, in line with the different degrees of phenotypic differences between family means. The prediction accuracy within individual families also varied with the genetic complexity of the traits and was generally highest based on effect estimation with lines from the respective family, whereas the prediction accuracy decreased with decreasing relatedness among the families. Taken together, our results illustrate the potential of genomic prediction to increase selection gain in triticale breeding, but the composition of the training set is of utmost importance, and consequently, the implementation of this approach in applied breeding programmes is not straightforward.     

Potential of genomic selection in rapeseed (Brassica napus L.) breeding

Genomic selection employs genome‐wide marker data to predict genomic breeding values. In this study, a population consisting of 391 lines of elite winter oilseed rape derived from nine families was used to evaluate the prospects of genomic selection in rapeseed breeding. All lines have been phenotyped for six morphological, quality‐ and yield‐related traits and genotyped with genome‐wide SNP markers. We used ridge regression best linear unbiased prediction in combination with cross‐validation and obtained medium to high prediction accuracies for the studied traits. Our results illustrate that among‐family variance contributes to the prediction accuracy and can lead to an overestimation of the prospects of genomic selection within single segregating families. We also tested a scenario where estimation of effects was carried out without individuals from the family in which breeding values were predicted, which yielded lower but nevertheless attractive prediction accuracies. Taken together, our results suggest that genomic selection can be a valuable genomic approach for complex agronomic traits towards a knowledge‐based breeding in rapeseed.     

Genomic prediction for yields,processing and nutritional quality traits in cultivated potato (Solanum tuberosum L.)

Current potato breeding approaches are hampered by several factors including costly seed tubers, tetrasomic inheritance and inbreeding depression. Genomic selection (GS) demonstrated interesting results regardless of the ploidy level, and can be harnessed to circumvent these problems. In this work, three GS models were evaluated using 50,107 informative SilicoDArT markers and 11 traits in two values for cultivation and use (VCU) potato trials. Two key breeding problems modelled included predicting the performance of (i) new and unphenotyped clones (cross‐validation) and (ii) a VCU using another as training set (TS). GS models performed comparably. Cross‐validation accuracy was high for D35, D45, DMW and BVAL, in ascending order. Prediction accuracies of the VCUs were highly correlated, but the best prediction was obtained for the smaller VCU using the bigger as TS. Cross‐validation and VCU prediction accuracies were higher when bigger TSs were used. The findings herein indicate that GS can be attractively integrated in potato breeding, particularly in early clonal generations to predict and select for traits with low heritability which would otherwise require more testing years, environments and resources.     

Genome-enabled prediction models for black tea (Camellia sinensis) quality and drought tolerance traits

Genomic selection in tea plant (Camellia sinensis) breeding has the potential to accelerate efficiency of choosing parents with desirable traits at the seedling stage. The study evaluated different genome-enabled prediction models for black tea quality and drought tolerance traits in discovery and validation populations. The discovery population comprised of two segregating tea populations (TRFK St. 504 and TRFK St. 524) with 255 F₁ progeny and 56 individual tea cultivars in validation population genotyped using 1,421 DArTseq markers. Twofold cross-validation was used for training the prediction models in the discovery population on eight different phenotypic traits. The best prediction models in the discovery population were consequently fitted to the validation population. Of all the four model-based prediction approaches, putative QTLs (Quantitative Trait Loci) + annotated proteins + KEGG (Kyoto Encyclopaedia of Genes and Genomes) pathway-based prediction approach showed more robustness. The findings have for the first time opened up a new avenue for future application of genomic selection in tea breeding.     

Genetic interrelationships among medium to late maturing tropical maize inbred lines using selected SSR markers

Understanding the genetic relationships among breeding lines is fundamental in crop improvement programs. The objectives of this study were to apply selected polymorphic single sequence repeat (SSR) DNA markers and cluster medium to late maturing tropical elite maize inbred lines for effective hybrid breeding. Twenty elite inbred lines were genotyped with 20 SSR markers. The analysis detected a total of 108 alleles. The unweighted pair group method with arithmetic mean allocated the inbred lines into five clusters consistent with the known pedigrees. The tested inbred lines that were adapted to mid-altitude, sub-humid agro-ecologies were classified in different clusters, except for a few discrepancies. The greatest genetic distance was identified between the clusters of lines CML-202 and Gibe-1-91-1-1-1-1. The analysis determined the genetic grouping present in the source population, which will assist in effective utilization of the lines in tropical hybrid maize breeding programs to exploit heterosis.     

Genomic prediction and GWAS of Gibberella ear rot resistance traits in dent and flint lines of a public maize breeding program

Gibberella ear rot (GER) is a serious threat to maize cultivation, causing grain yield losses and contamination with mycotoxins. Genomic prediction (GP) has great potential to accelerate resistance breeding against GER. However, small training sets (TS) consisting of both phenotyped and genotyped individuals are a challenge for obtaining high prediction accuracy (ρ) in GP. A potential solution would be combining small-size populations across heterotic pools. However, genetic heterogeneity between populations in terms of segregating QTL, linkage disequilibrium (LD) pattern and genomic relationships can impair ρ of GP. In this study, we investigated the genetic architecture of GER severity, deoxynivalenol concentration (DON) and days to silking with genome-wide association studies within two elite panels of 130 dent and 114 flint lines from the maize breeding program of the University of Hohenheim tested in four environments. We also assessed the consistency of LD pattern and genomic relationships between the two heterotic pools. Furthermore, we compared four GP approaches differing in the composition of the TS with lines from a single or combined pool(s) and statistical models with marker effects identical or different but correlated between pools. We detected two and six QTL for DON within the dent and flint pool, respectively, but no common QTL. The LD pattern was consistent between pools for marker pairs ≤ 10 kb apart. GP across pools yielded low or even negative ρ. Combined-pool GP had no higher ρ than within-pool GP, regardless of the statistical model. Our findings underline the importance of investigating the genetic heterogeneity between populations prior to implementing GP using combined TS.     

Breeding for boron tolerance in lentil (Lens culinaris Medik.) using a high‐throughput phenotypic assay and molecular markers

This study describes the identification of a quantitative trait locus (QTL) in the recombinant inbred line population of ILL2024 × ILL6788 and subsequent validation of associated molecular markers. A high‐quality genetic linkage map was constructed with 758 markers that cover 1,057 cM, with an average intermarker distance of 2 cM. QTL analysis revealed a single genomic region on Lc2 to be associated with B tolerance and accounted for up to 76% of phenotypic variation (Vp). The best markers for B tolerance were assessed for their utility in routine breeding applications using validation panels of diverse lentil germplasm and breeding material derived from ILL2024. A marker generated from the dense genetic map of this study was found to be the most accurate of all markers available for B tolerance in lentil, with a success rate of 93% within a large breeding pool derived from ILL2024. However, given the number of the unrelated lines for which the marker–trait association was not conserved, B tolerance screening is still required at later stages to confirm predicted phenotypes.     

Genomic analysis of maize lines introduced in the early stages of a breeding programme

The diversity analysis and screening of major genes using genomewide association studies (GWAS) for quantitative traits have been exploited in several grass crops, but in maize it has been neglected. This study was conducted to evaluate the genetic diversity of a collection of lines and the potential of genomic analysis as an initial screening tool. For this purpose, a collection of 470 maize inbred lines were genotyped with 23,153 Dart‐seq markers. The genomewide analysis of ear weight was used aiming to perform an initial screening in our germplasm. The diversity analysis allowed the lines to be separated into distinct groups, and most of the lines were in agreement with previous pedigree information. The GWAS revealed ten regions potentially associated with the ear weight trait, one of which was related to drought stress. The results of a multiple marker analysis confirmed four of these regions, presenting a predictive accuracy of 0.6. Based on the molecular data and the results of GWAS, it is possible to infer the potential use of this genetic background for breeding.     

Mitigating the impact of selective phenotyping in training populations on the prediction ability by multi-trait pedigree and genomic selection models

Training populations for pedigree and genomic prediction in plant breeding programmes are largely updated with superior genotypes from multi-environment trials, where they are tested with the goal of variety development. Such a selective phenotyping has, however, a negative impact on prediction abilities, especially when only a subset of breeding lines can be tested, as for laborious and costly to phenotype traits. This study focused, thus, on investigating the impact of selective phenotyping in the training population of an applied wheat breeding programme, and assessing the potential to mitigate this impact by pedigree and genomic multi-trait prediction models as well as bi-directionally selected training populations for several baking quality parameters. Combining both pedigree and genomic information in multi-trait prediction models with pre-existing phenotypic information for protein content and sedimentation value compensated for the observed loss in prediction ability, while entering few inferior breeding lines into the training population further mitigated the impact of selective phenotyping and even led to a slight increase of prediction ability in comparison to a randomly chosen training population.     

Marker‐assisted introgression of lpa2 locus responsible for low‐phytic acid trait into an elite tropical maize inbred (Zea mays L.)

Maize is an important food and feed crop worldwide. Phytic acid (PA), in maize kernel, is an antinutritional factor. PA chelates mineral cations and causes mineral deficiency in humans and phosphorous deficiency in animals. The undigested PA excreted by monogastric animals causes phosphorous eutrophication. Therefore, development of low‐phytate maize is indispensable. The low‐phytate locus (lpa2 allele) has been transferred from low‐phytate mutant line ‘EC 659418’ into an elite inbred UMI 395 through marker‐assisted backcross breeding (MABB). The MABB involved three backcrosses followed by two selfing steps, including ‘foreground selection’, that is, selecting lines with lpa2 allele with the help of a codominant SSR marker ‘umc2230’ and ‘background selection’, that is, selecting plants having genetic background similar to that of the recurrent parent using 50 codominant SSR markers. Two low‐phytate lpa2 lines with genome similar (>90% similarity) to that of recurrent parent have been identified. These lines can be used as parent in future hybridization programmes for obtaining low‐phytate high‐yielding maize hybrids.     

Efficiency of SNP and SSR-based analysis of genetic diversity,population structure,and relationships among cowpea (<Emphasis Type="Italic">Vigna unguiculata</Emphasis> (L.) Walp.) germplasm from East Africa and IITA inbred lines

The extent of genetic diversity and relatedness of cowpea germplasm from East Africa are poorly understood. A set of 13 microsatellites (SSR) and 151 single nucleotide polymorphisms (SNPs) markers were applied to assess the levels of genetic diversity in a sample of 95 accessions of local cowpea germplasm and inbred lines of Vigna unguiculata. The average genetic diversity (D), as quantified by the expected heterozygosity, was higher for SSR loci (0.52) than for SNPs (0.34). The polymorphic information content was 0.48 for SSR and 0.28 for SNP while the fixation index was 0.095 for SSR and 0.15 for SNPs showing moderate differentiation and high gene flow among cowpea accessions from East African countries. The results of data analysis of both SSR and SNP markers showed similar clustering patterns suggesting a substantial degree of association between origin and genotype. Principal coordinate analysis (PCoA) with SSR and SNP markers showed that accessions were grouped into two and three broad groups across the first two axes, respectively. Our study found that SNP markers were more effective than SSR in determining the genetic relationship among East African local cowpea accessions and IITA inbred lines. Based on this analysis, five local cowpea accessions Tvu-13490, Tvu-6378, Tvu-13448, Tvu-16073, and 2305675 were identified to be tightly clustered sharing several common alleles with the drought tolerant variety Danila when analyzed with SSR and SNP markers. The findings will assist and contribute to future genetic diversity studies aimed at the genetic improvement of local Eastern Africa cowpea accessions for improved overall agronomic performance in general and breeding for drought tolerant in particular.     

Construction of chromosomal segment substitution lines and genetic dissection of introgressed segments associated with yield determination in the parents of a super‐hybrid rice

Heterosis is a phenomenon whereby hybrids of inbred lines produce favourable phenotypes that exceed those of their parents. Traits of interest are higher yield and stronger stress tolerance. The two‐line super‐hybrid rice ‘Liangyoupei9’ (LYP9) shows superiority to both its elite inbred line ‘93‐11’ and ‘Pei'ai64s’ (‘PA64s’) parents and conventional hybrids. However, the genetic basis of its hybrid vigour, especially yield determination, remains elusive. In the present study, a set of 156 chromosome segment substitution lines (CSSLs) carrying overlapping segments from ‘PA64s’ in a genetic background of ‘93‐11’ were constructed and planted in six environments. Three major agronomic traits, viz. panicle length (PL), heading date (HD) and plant height (PH), and five yield‐related traits, viz. grain weight per panicle (GWP), number of grains per panicle (GPP), 1000‐grain weight (TGW), seed set (SS) and number of panicles of per plant (PPP), were evaluated over 3 years. Quantitative trait loci (QTL) analysis was conducted using a likelihood ratio test based on stepwise regression. Forty‐six putative QTL distributed on 11 chromosomes were detected in more than one year. Remarkably, GWP of four CSSLs carrying positive yield QTL outperformed the recurrent parent ‘93‐11’ by more than 15%, in at least two environments. These results indicate that CSSLs are effective in identifying yield‐associated traits, and lines harbouring such QTL will be rich in resources for future molecular breeding programmes.     

Genetic diversity among populations and breeding lines from recurrent selection in Brassica napus as revealed by RAPD markers

Recurrent selection facilitated by dominant male sterility has been conducted to broaden the genetic basis for cultivar development in Brassica napus. This study aimed to evaluate the genetic variation in four base populations (C0‐C3) and breeding lines from two of the populations produced during recurrent selection by random amplified polymorphic DNA (Rapd) markers. Genetic variation in four populations declined gradually with the advance of selection cycles as measured by expected genetic heterozygosity (from 0.2058 in C0 to 0.1536 in C3) but the decline was not statistically significant. When compared with the average genetic distances for 21 germplasm collections with wide geographical and genetic origins (0.4712) and seven breeding lines from pedigree selection (0.2059), seven breeding lines selected from the C1 population and 11 from the C3 population had a larger average genetic distance (0.5339 and 0.5486, respectively). Clustering analysis indicated that the lines from recurrent selection had a much lower genetic similarity than lines from pedigree selection. Our results suggest that base populations derived from recurrent selection could provide a wider genetic variation for selection of breeding lines with more broad genetic bases.     

Genome-wide association mapping and genomic prediction of Fusarium head blight resistance,heading stage and plant height in winter rye (Secale cereale)

Rye is a multi-purpose cereal crop grown in Central and Eastern Europe as well as in Western Canada. Fusarium head blight (FHB) is one of the diseases that have a severe negative impact on rye, but knowledge about FHB resistance at the genomic level is totally missing in rye. The objective of this study was to elucidate the genetic architecture of FHB resistance in winter rye using genome-wide association (GWA) mapping complemented by genomic prediction (GP) in comparison with marker-assisted selection (MAS). Additionally, plant height and heading stage were analysed. A panel of 465 S₁-inbred lines of winter rye was phenotyped in three environments (location–year combinations) for FHB resistance by inoculation with Fusarium culmorum and genotyped with a 15k SNP array. Significant genotypic variation and high heritabilities were found for FHB resistance, heading stage and plant height. FHB did not correlate with heading stage, but was moderately correlated with plant height (r = −.52, p < .001) caused by some susceptible short inbred lines. The GWA scan identified 15 QTL for FHB resistance that jointly explained 74% of the genotypic variance. In addition, we detected 11 QTL for heading stage and 8 QTL for plant height, explaining 26% and 14% of the genotypic variance, respectively. A genome-wide prediction approach resulted in 44% higher prediction abilities than marker-assisted selection for FHB resistance. In conclusion, genomic approaches appear promising to improve and accelerate breeding for complex traits in winter rye.     

Identification of the Rf gene conferring fertility restoration of the CMS Dian-type 1 in rice by using simple sequence repeat markers and advanced inbred lines of restorer and maintainer

Cytoplasmic male sterility of Dian‐type 1 (CMS‐D1) was developed 30 years ago in Yunnan. A major gene conferring fertility restoration for the CMS‐D1 system was detected by microsatellite markers in advanced inbred lines consisting of 196 maintainers and 62 restorers developed in breeding programmes of hybrid rice involving the CMS‐D1 system. The gene was mapped between two simple sequence repeat markers, OSR33 and RM228, on chromosome 10, and was temporarily designated as Rf‐D1(t). The genetic distances of the gene to the two microsatellite markers were 3.4 and 5.0 cM, respectively. This linkage was confirmed by using an F2 population derived from a cross between a CMS‐D1 line and a restorer. This study also demonstrated that using OSR33 was reliable and efficient for identification of restoring lines in hybrid rice breeding with the CMS‐D1 system.     

IBD-based QTL detection in inbred pedigrees: A case study of cereal breeding programs

Mapping quantitative trait loci in plants is usually conducted using a population derived from a cross between two lines. The power of such QTL detection and mapping strategies and the estimation of the effects highly depend on the choice of the two parental lines. Thus, the QTL detected in such populations only represent a small part of the genetic architecture of the trait. Besides, the effects of only two alleles are characterized, which is of limited interest to the breeder. On the other hand, common pedigree breeding material remains unexploited for QTL mapping. From a pre-breeding perspective, the utilization of the good quality phenotypic data generated by breeders can be improved through the search and manipulation of QTL. The development of statistical techniques suitable for QTL mapping in general conventional breeding populations is thus challenging. In this study, we extend QTL mapping methodology to a generalized framework, based on a two-step IBD variance component approach, applicable to any type of breeding population coming from inbred parents. The proposed developments attempt to make full use of any inferable relatedness information between the parents. The power and accuracy of this method were assessed on simulated data mimicking conventional breeding programs in cereals, in an effort to reproduce actual conditions of marker and gene allelic frequencies across the parental lines. A wide range of breeding scenarios and of genetic architectures was explored. We demonstrated that taking into account the estimable relatedness between the parents significantly improved the power and accuracy of the QTL parameter estimations. This revised version was published online in July 2006 with corrections to the Cover Date.     

Association analysis of fibre traits in Gossypium arboreum accessions

Advances in the use of diploid Asiatic species in cotton breeding require an understanding of the relatedness and ancestry of diploid cotton accessions, and identification of simple sequence repeat (SSR) markers associated with agronomically important phenotypic traits, for example, fibre quality. Fifty‐six Gossypium arboreum germplasm accessions introduced from nine regions of Africa, Asia and Europe were evaluated for eight fibre characters (lint percentage, lint colour, elongation, micronaire, strength, 50% span length, 2.5% span length and maturity%) and genotyped with 98 SSR markers. When viewed across all accessions most of the SSR markers were polymorphic. Population structure analysis identified six main clusters for the accessions which corresponded to different geographic regions, indicating agreement between genetic and predefined populations. The general linear model method was used to disclose marker–trait associations. Marker–trait associations were investigated by fitting single marker regression models for phenotypic traits on marker band intensities with correction for population structure. This paper illustrates the potential of association mapping in diploid cotton, because existing phenotypic data, a modest number of SSR markers, and a pioneering statistical analysis, identified interesting associations.     

基于SSR分子标记的玉米自交系遗传多样性分析

了解新选育自交系遗传背景,确定其所属的杂种优势群,是组配杂交组合,选育新的杂交种的关键措施。此研究利用SSR标记技术分析了46份玉米自交系的遗传多样性,结果表明：12对稳定的SSR引物共检测出45个等位基因变异,每个SSR的多态性信息量（PIC）的变幅为0.31~0.76,平均为0.57,显示了较高的多态性。聚类分析显示46个玉米自交系可划分为5个类群,每一类群内所包含的自交系与系谱分析的结果基本一致。研究结果还表明,快捷、准确鉴定种质资源亲缘关系的SSR分子标记技术可以广泛应用于育种实践,提高玉米优势组合选配的效率。     

Prediction of heterosis for grain yield in rice using 'key' informative EST-SSR markers

This study was undertaken to assess the comparative potential of 25 Expressed Sequence Tag derived simple sequence repeats (EST-SSRs) and 25 genomic SSRs in the prediction of grain yield heterosis using a set of nine cytoplasmic male sterile (CMS) lines and 32 restorer lines of rice. EST-SSRs and genomic SSRs exhibited an average Polymorphism Information Content value of 0.37 and 0.45, respectively. The coefficient of marker polymorphism among parental lines with respect to a set of hypervariable EST and genomic SSRs was correlated with standard heterosis for grain yield of six public bred rice hybrids. EST-SSRs gave a better correlation (r = 0.75) as compared with genomic SSRs (r = 0.09). When 10 'key' informative EST-SSR markers which showed a higher positive correlation with grain yield heterosis were validated in a new set of 14 experimental hybrids, the markers exhibited a higher correlation (r = 0.79), indicating the predictive value of these EST-SSRs. We recommend these 10 'key' informative EST-SSR markers for analysis of genetic diversity of parental lines and prediction of heterosis in hybrid rice breeding programmes.