Changes in genetic diversity during seven cycles of recurrent selection for grainyield in oat, Avena sativa L.

Variability for desirable alleles within elite breeding populations is a requirement for long-term genetic improvement. Changes in genetic diversity were evaluated in a recurrent selection programme for enhanced grain yield in oat, Avena sativa L., using coefficient of parentage (r_p) and restriction fragment length polymorphism (RFLP) based genetic similarity (S) estimates. Both r_p and s increased during seven cycles of recurrent selection, indicating a reduction in the level of genetic diversity within the population. The relationship between genetic diversity and agronomic performance was also examined. Genetic similarity measures were poor predictors of the near-homozygous progeny performance and general and specific combining ability effects for three agronomic traits in the recurrent selection programme. In addition, there was no apparent trend for preferential selection of progeny from either more similar or more diverse parents within a given cycle of selection. The overall reduction in genetic diversity in this population has not affected selection response for grain yield. Variability remaining at important loci or de novo variation are possible explanations for the continued selection progress.     

Correlated responses of fatty acid composition, grain quality, and agronomic traits to nine cycles of recurrent selection for increased oil content in oat

Increases in the groat-oil content of oat (Avena sativa L.) increase the energy value of the grain and improve the feasibility of extracting oat oil for use as a vegetable oil. Nine cycles of recurrent selection for greater groat-oil content conducted in a genetically broad-based oat population resulted in dramatic increases in groat-oil content. Our objectives were todetermine if selection for greater groat-oil content affected fatty acid composition, grain quality traits (test weight and seed weight), or agronomic traits (straw yield, biomass, harvest index, heading date, and height). We evaluated 100 random lines from the base (C0) population and each of the nine selection cycle populations in three environments in order to estimate means, genetic variances, heritabilities, and genotypic and phenotypic correlations of grain quality and agronomic traits. We also evaluated 20 random lines from each population to estimate changes in fatty acid contents. Oleate and stearate contents increased over cycles of selection, as did the ratio of unsaturated to saturated fatty acids. Palmitate, linoleate, and linolenate contents and all grain quality and agronomic traits except harvest index decreased over cycles of selection. There was no evidence for reduced genetic variance or heritability in C9 for any trait, but the genotypic and phenotypic correlations between agronomic traits and oil content fluctuated over cycles. Selection for increased groat-oil content improved oil quality but reduced grain quality and agronomic performance of the population. This revised version was published online in August 2006 with corrections to the Cover Date.     

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.     

Genetic relatedness and the ratio of subpopulation‐common alleles are related in genomic prediction across structured subpopulations in maize

Genomic prediction (GP), which could predict the breeding value of crop plants genotyped with molecular markers, has been carried out in multiple species. Prediction accuracy (PA) of GP depends on various factors, including genetic relatedness and genetic basis. In this study, we examined the rationale for the low PA of GP when the training and validation populations were distinct using 170 temperate inbred lines and 210 tropical and subtropical inbred lines, respectively. All inbred lines were evaluated for 17 traits and genotyped with 550K high‐density markers. The results show that: (a) the influences of heritability and marker number on PA reflected variations in phenotypic variance captured by the genetic information; (b) the low PA of GP when the training and validation populations represent structured subpopulation is related to the ratio of subpopulation‐common alleles (RSCA) and the genetic relatedness between the two subpopulations; (c) RSCA and PA increased with the increase of genetic relatedness, suggesting that these three factors were related. Our findings would provide references when performing GP, and guidance when designing breeding populations.     

Genetic diversity in red clover (Trifolium pratense L.) revealed by morphological and microsatellite (SSR) markers

The NPGS-USDA core collection with 85 accessions of red clover, an important forage species, is little described. The goal of the present study was to evaluate the diversity of a set of accessions from the core collection at the morphological and molecular level in order to extract some valuable accessions for Brazilian red clover breeding programs. Twenty-one morphological traits, collected in field and greenhouse in South Brazil, and seven SSR markers were used to describe 57 accessions from the U.S. core collection and one population cultivated in Southern Brazil. Variation between accessions was large for most of the 21 morphological traits. A cluster analysis based on the morphological traits revealed five distinct clusters that separated the populations according to flowering earliness, as already described, but also according to persistency, growth habit and dry matter productivity. Over seven SSR loci, the number of alleles averaged 11.1 alleles per locus. Genetic diversity measured with SSR markers was high, with a mean expected heterozygosity of 0.86. An analysis of molecular variance revealed that the largest proportion of variation (83.6%) resided at the within population level. Although the molecular markers also separated accessions into five clusters, there was no coincidence between the composition of groups found with morphological and molecular data. Use of genetic diversity in breeding programs requires to use the most promising populations, to combine positive traits such as persistency and forage yield, and probably to use within population variation to detect valuable genotypes that could be used as parents of synthetic varieties.     

Genetic diversity of feral alfalfa (<Emphasis Type="Italic">Medicago</Emphasis> <Emphasis Type="Italic">sativa</Emphasis> L.) populations occurring in Manitoba,Canada and comparison with alfalfa cultivars: an analysis using SSR markers and phenotypic traits

Feral populations of cultivated crops may act as reservoirs for novel traits and aid in trait movement across the landscape. Knowledge on the genetic diversity of feral populations may provide new insights into their origin and evolution and may help in the design of efficient novel trait confinement protocols. In this study, the genetic diversity of 12 feral alfalfa (Medicago sativa) populations originating from southern Manitoba (Canada) and 10 alfalfa cultivars and a M. falcata germplasm were investigated using eight SSR markers (i.e., microsatellites) and 14 phenotypic traits. We found that the genetic diversity observed in feral populations was similar to the diversity detected among the 10 cultivars. Analysis of molecular variance revealed that there was great genetic variation within (99.8%) rather than between different feral populations. Cluster analysis (unweighted pair-group method using arithmetic average) revealed no differentiation between feral populations and cultivars for neutral loci. High levels of population differentiation for phenotypic traits (and not for neutral markers) suggest the occurrence of heterogeneous selection for adaptive traits. The phenotypic traits we studied did not distinctly separate feral populations from cultivars but there was evidence of natural selection in feral populations for traits including winter survivability, rhizome production, and prostrate growth habit. Our results suggest that feral alfalfa populations need to be considered in the risk assessment of alfalfa containing novel genetically modified (GM) traits. Further, feral alfalfa populations may be regarded as a source of new germplasm for plant improvement.     

Climatic adaptation of trees: rediscovering provenance tests

Summary Common garden testing of populations of different origin started with forest trees more than two hundred years ago. Since then, so-called provenance tests have been established with most commercially important species. Beyond the strictly silvicultural goals, the tests offer excellent opportunities to study intraspecific genetic variation patterns and represent probably the most powerful available tool for testing hypotheses of climatic adaptation in trees.Analysis of adaptive traits (mostly juvenile height growth) in provenance experiments indicate the existence of very effective constraints on adaptedness. The performance of populations plotted against an ecological-climatic factor exhibits a characteristic pattern and can be described by response functions. The population average of a fitness-related trait for a locally adapted population is often significantly lower than that of populations from other environments; usually the ones from milder climate perform better. The phenomenon is interpreted as adaptation lag. Suboptimal adaptation is compensated by a high level of genetic diversity. Molecular genetic studies confirm the high level of allelic and individual genetic diversity in forest trees. A consequence of individual homeostasis, phenotypic stability of populations is usually also high; the sensitivity to environmental changes is generally moderate. Phenotypically stable populations are valuable not only because of a wider range of potential cultivation but specifically because of a greater ability to adjust to unexpected changes. This trait should receive more attention in the future for obvious reasons.The maintenance of a high within-population genetic variance is favored by the genetic system of the investigated species (effective gene flow, outbreeding, high genetic load, etc.). Random events and long-lasting biotic interactions are further effects impairing the efficiency of natural selection.In view of expected climate instability, genetic adaptability of forest trees causes serious concern due to their long lifespan compared to the rapidity of expected changes in environmental conditions. The potential of provenance tests to interpret long-term adaptational processes should be utilized to analyze, model and predict response of trees to climate change. Although seldomly appreciated, provenance research might be among the most important contributions of forestry to biological sciences.     

Genetic and Phenotypic Association between Yield Components in Hybrid Sorghum (Sorghum bicolor (L.) Moench) populations

Summary The magnitude of genetic expression and associations among traits are important for the prediction of response to selection in diverse environments and provide the basis for planning and evaluating breeding programs. In this regard, a cross classification mating design was used to produce hybrid sorghum populations, which were evaluated in a randomized completed block design with three replications at four environments in Northern Cameroon. Data on grain yield, days to anthesis, plant height, inflorescence length, threshing percentage and seed mass were collected and subjected to statistical genetic analyses. Significant genotype × environment interaction effects were observed for all traits. Genetic variance was essentially attributed to additive gene effects, with dominance variance for grain yield being negligible. However, the reverse was observed for threshability. Genetic variance components were much higher for plant height and grain yield than for days to anthesis, seed mass and threshability. Heritability estimates for plant height and inflorescence length were high (77 and 54 percent respectively) while the estimates for grain yield and threshability were low (14 and 5 percent respectively). Grain yield had positive genotypic correlation with most of the traits. Days to anthesis were negatively correlated with vegetative and reproductive traits. These results suggest that improvement of days to anthesis, plant height, and inflorescence length should be faster because of higher heritabilities and greater phenotypic variation. However, selection for earliness and reduced plant height would not be possible without hampering grain yield. Selecting for yield primary components namely inflorescence length and seed weight would be effective for increasing production. In addition, optimizing agronomic practices and improved experimental design would increase the selection efficiencies.     

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.     

Genomic selection and enablers for agronomic traits in maize (Zea mays): A review

Maize is a commodity crop providing millions of people with food, feed, industrial raw material and economic opportunities. However, maize yields in Africa are relatively stagnant and low, at a mean of 1.7 t ha⁻¹ compared with the global average of 6 t ha⁻¹. The yield gap can be narrowed with accelerated and precision breeding strategies that are required to develop and deploy high-yielding and climate-resilient maize varieties. Genomic and phenotypic selections are complementary methods that offer opportunities for the speedy choice of contrasting parents and derived progenies for hybrid breeding and commercialization. Genomic selection (GS) will shorten the crop breeding cycle by identifying and tracking desirable genotypes and aid the timeous commercialization of market-preferred varieties. The technology, however, has not yet been fully embraced by most public and private breeding programmes, notably in Africa. This review aims to present the importance, current status, challenges and opportunities of GS to accelerate genetic gains for economic traits to speed up the breeding of high-yielding maize varieties. The first section summarizes genomic selection and the contemporary phenotypic selection and phenotyping platforms as a foundation for GS and trait integration in maize. This is followed by highlights on the reported genetic gains and progress through phenotypic selection and GS for grain yield and yield components. Training population development, genetic design and statistical models used in GS in maize breeding are discussed. Lastly, the review summarizes the challenges of GS, including prediction accuracy, and integrates GS with speed breeding, doubled haploid breeding and genome editing technologies to increase breeding efficiency and accelerate cultivar release. The paper will guide breeders in selection and trait introgression using GS to develop cultivars preferred by the marketplace.     

Estimation of genetic parameters and prediction of breeding values in an autotetraploid blueberry breeding population with extensive pedigree data

The strategy for breeding blueberries has been based on phenotypic selection without accounting for pedigree correlation information. A central premise of classical quantitative genetics is that through knowledge of the relationships among individuals in a population, we can make inferences about breeding values (BVs), estimate genetic parameters, and support phenotypic selection. Genetic evaluations using best linear unbiased prediction (BLUP) and restricted maximum likelihood (REML) are founded on pedigree information and have been the standard method used in livestock and forest breeding. Despite theoretical and practical benefits, their application in blueberry breeding programs remains unexploited. The objective of this study was to evaluate the use of REML/BLUP in the University of Florida blueberry breeding program in order to estimate genetic parameters and predict BVs of primary selection traits. To do this, we collected phenotypic data for eight selectable traits (yield, flower bud density, fruit weight, fruit firmness, fruit diameter, fruit soluble solids, fruit pH, and fruit scar diameter) from 1996 individuals. The highest narrow-sense heritabilities were found for fruit weight, scar diameter, and yield. The majority of genetic correlations between traits were under 0.20. The largest genetic gain was achieved when selections from early stages were used as parents and the top 5% of the population was selected. Compared to traditional phenotypic selection, our results are evidencing of the importance of implementing REML/BLUP to estimate genetic parameters that help and support the breeding strategy and maximize genetic gains.     

Genetic diversity among tea cultivars from China, Japan and Kenya revealed by ISSR markers and its implication for parental selection in tea breeding programmes

Tea plant [Camellia sinensis (L.) O. Kuntze] is an important beverage crop in the world. In recent years many clonal tea cultivars have been released, and they play major roles in improving the production and quality of tea. It is important to understand the genetic diversity and relatedness of these cultivars to avoid inbreeding and narrow genetic basis in future tea breeding. In the present study, genetic diversity and relationship of 48 tea cultivars from China, Japan and Kenya were evaluated by inter‐simple sequence repeat (ISSR) markers. A total of 382 ISSR bands were scored, of which 381 (99.7%) were polymorphic. The ISSR primers showed high ability to distinguish between tea cultivars according to their high Resolving Power (R_P) with an average of 7.4. The mean of Nei’s gene diversity (H) and Shannon’s information index (I) were 0.22 and 0.35, respectively. More abundant diversity was revealed among cultivars in China than those in Japan and Kenya. Within Chinese populations, the level of diversity in east China was higher than that in other regions. The coefficient of genetic differentiation (G_ST) was 0.202, which indicates a high degree of genetic variation within populations. This result was further confirmed by analysis of molecular variance, which revealed the variance component within the populations (92.07%) was obviously larger than that among populations (7.93%). The level of gene flow (N_m) was estimated to be 2.0. This could be explained by frequent natural cross‐pollination and seed dispersal among tea populations. The pairwise similarity coefficient between the cultivars varied from 0.162 to 0.538. A dendrogram of 48 tea cultivars was constructed where all the tested cultivars were divided into two groups. Our data show that the genetic relationship among tea cultivars can be determined by the ISSR markers. This will provide valuable information to assist parental selection in current and future tea breeding programmes.     

Farmers' seed management practices open up new base populations for pearl millet breeding in a semi-arid zone of India

Farmers in western Rajasthan (north‐west India) produce and maintain their landrace populations of pearl millet through their own distinct seed management practices. The objective of this study was to characterize morphological and agronomic variability of different traits between and within three farmers' populations using quantitative‐genetic parameters. Populations examined were a typical landrace and two modified landraces, which were generated through farmer introgression of modern varieties with different levels of subsequent selection. From these three populations, 100 random full‐sib progenies were evaluated in field trials at two locations in western Rajasthan over two years. Significant genetic variation existed within the three populations. Estimates of heritability were moderate to high for all observed traits. Predicted selection response for grain yield across environments was 1.6% for the typical landrace and 2.2% for both the modified landraces. Results suggest that the introgression of modern varieties into landraces had increased the genetic diversity. Therefore, farmers' current breeding activities could open up new resources for plant breeding programmes aiming at plant improvement for the semiarid zones of India.     

Molecular diversity and population structure of the Ethiopian lentil (<Emphasis Type="Italic">Lens Culinaris</Emphasis> Medikus) genotype assessment using SSR markers

Knowledge of genetic diversity in germplasm is essential for formulating effective germplasm collection, conservation, utilization strategies in and crop improvement programs. It also provides an opportunity to take corrective steps infusing new genes to avoid risks associated with a narrow genetic bases. Genetic diversity analysis of 119 lentil genotypes of including 83 germplasm and 36 exotic genotypes from International Center for Agricultural Research in the Dry Areas was studied using 27 primers of simple sequence repeat (SSR) marker. Molecular analysis of variance showed variations of 82% within and 18% of the among population variance was explained. Degree of polymorphism observed among the populations was 100%. A total 122 alleles were detected, with 2 to 7 alleles per locus, with a mean of 4.52 alleles per locus. The estimated gene diversity value for 27 loci was 0.64. The average Shannon’s information index value of 1.19 was obtained showed the existence of high genetic variation within the genotypes. The genetic similarity indices ranged from 0.21 to 1.00. The SSR markers showed an average polymorphic information content (PIC) value of 0.58. Cluster analysis grouped the genotypes into five major clusters as distinct genetic populations. Diversity analyses revealed the existence of a high level of genetic variation among genotypes. This molecular diversity information provides a basis for future germplasm collection, utilization, and conservation strategies in gene banks and introducing exotic germplasm to widen the genetic base of the current lentil breeding population.     

Maize participatory breeding in Portugal: Comparison of farmer's and breeder's on‐farm selection

“VASO” is a Portuguese participatory maize breeding project (1984), where several maize landraces such as “Pigarro” have been selected both by a farmer's (phenotypic recurrent selection) and a breeder's approach (S2 lines recurrent selection). The objectives of this study were to determine the phenotypic and genotypic responses to participatory selection using these two different approaches, to clarify to which extent both selection methods preserve genetic diversity, and conclude what is the preferred method to apply in sustainable farming systems. The results, obtained via ANOVA, regression analyses and molecular markers, indicate that for both selection methods, genetic diversity was not significantly reduced, even with the most intensive breeder's selection. Although there were some common outputs, such as the determinated versus indeterminated ears, cob and ear weight ratio per ear and rachis 2, specific phenotypic traits evolved in opposite directions between the two selection approaches. Yield increase was only detected during farmer selection, indicating its interest on PPB. Candidate genes were identified for a few of the traits under selection as potential functional markers in participatory plant breeding.     

Proof of concept to unmask the breeding value of genetic resources of barley (Hordeum vulgare) with a hybrid strategy

Broadening the genetic base of elite breeding programmes is crucial for further breeding success. The absence of major adaption genes, however, often masks the grain yield breeding value of genetic resources. We assessed the ability of a hybrid strategy to provide unbiased performance estimates of 21 barley genetic resources. By crossing them to elite tester lines, 25 three-way hybrids were produced and evaluated together with a part of their parents and eight elite hybrids for important agronomic traits in replicated field trials in four environments. The phenotypic data analyses revealed that the hybrid strategy facilitated to identify promising resources by substantially improving lodging resistance. Combining genotypic data for 5,562 SNPs with the phenotypic data highlighted the potential to boost the diversity of the elite breeding pool via targeted introgression of genetic resources into the male and female heterotic pools. We propose an application of the hybrid strategy for genetic resources of entire genebank collections and to use genome-wide predictions to support a targeted choice of accessions with high value for barley breeding.     

Construction of a crop—wild hybrid population for broadening genetic diversity in cultivated sunflower and first evaluation of its combining ability: the concept of neodomestication

The genetic base of sunflower elite lines is very narrow, due to many years of selection and breeding. To broaden the genetic diversity of the cultivated sunflower, in 1995 73 wild sunflower populations were crossed with 3 cultivated lines (Testers), and 219 hybrid offspring’s were evaluated in the field. GCA and SCA effects were computed suggesting for all traits a genetic potential for improvement through selection. Study of the hybrids revealed that the wild accessions bear different genetic abilities to combine with the testers for traits of morphological architecture, phenology and yield (seed weight and seed oil). The variance due to GCA and SCA showed that gene action was additive for days to flowering, branching and plant height. Genotypes derived from the same geographic origin may have either good or poor general combing ability. The correlation between GCA and per se genotype performance was positive for all traits except for seed oil content. This was the first attempt to evaluate wild-cultivated hybrids in sunflower on a large scale and will be the starting point for the management of hybrid Helianthus annuus populations for breeding. GCA and SCA estimations will facilitate the definition of strategies to manage and exploit the natural diversity for this crop.     

基于果实品质与EST-SSR标记的刺梨居群遗传多样性分析及核心种质构建

通过分析评价野生刺梨(Rosa roxburghii Tratt.)资源居群遗传多样性和遗传结构,同时构建核心种质,为刺梨资源的保护和发掘利用提供科学依据。本研究利用10对EST-SSR引物和9个果实品质性状指标对收集的12个刺梨自然居群(共102份种质)的遗传多样性及遗传结构进行分析,同时结合原贵州省32份初级核心种质,采用位点优先取样策略进一步构建西南地区核心种质。结果表明,黔西(QX)居群拥有最高的Shannon信息指数I=0.6965,基因多样性指数h=0.3935,多态位点百分率p=84.62%;而古丈(GZ)居群则无论在分子数据还是表型数据都表现为遗传多样性最低;AMOVA分析表明刺梨居群内遗传变异在87%以上,居群间基因流Nem在3.5以上、平均Nei’s遗传距离(GD)0.223。构建的19份核心种质等位基因保留率和稀有等位基因保留率均为100%,能够代表原种质的遗传多样性。西南地区野生刺梨的遗传变异主要发生在居群内,居群间具有基因交流频繁、Nei’s遗传距离小等特点,构建的19份核心种质从等位基因保留率、稀有等位基因保留率及地理分布均能够较好地代表原种质的遗传多样性。自然居群以黔西(QX)居群遗传多样性最高。因此,野生刺梨的保护策略可采用就地保护黔西(QX)居群与迁地保护19份核心种质相结合的方法进行。     

燕麦种质资源在晋北寒旱生态区的鉴定

为探索国家现代农业燕麦荞麦产业技术体系提供的100份燕麦资源的利用价值,并从中筛选出可直接利用的优质品种,采用田间观察和综合分析的方法,研究其农艺性状的变异情况和部分性状的遗传多样性表现。农艺性状分析表明：轮层数、株高和千粒重的稳定性相对较好,在育种过程中较容易选择;上数第2片叶长、上数第2片叶宽和穗粒重的变异系数较大,在育种中应放宽标准。若干性状的遗传多样性分析表明：皮裸性、粒色、茎叶蜡质的遗传多样性指数偏小;粒形、芒色、茎粗度和旗叶叶相的遗传多样性指数较大。通过鉴定筛选出13个抗旱、抗病、早熟的优质燕麦品种,20个大穗大粒品种,以及一系列单一性状突出的品种。为燕麦新品种选育和合理利用燕麦种质资源提供理论依据。     

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.