Biparental Populations Research Articles

Utilization of Evolutionary Plant Breeding Increases Stability and Adaptation of Winter Wheat Across Diverse Precipitation Zones

Evolutionary plant breeding (EPB) is a breeding method that was used to create wheat (Triticum aestivum L.)-evolving populations (EP), bi-parental and composite-cross populations (BPPs and CCPs), by using natural selection and bulking of seed to select the most adaptable, diverse population in an environment by increasing the frequency of favorable alleles in a heterogeneous population. This study used seven EPs to evaluate EPB in its ability to increase the performance of agronomic, quality, and disease resistance traits and adaptability across different precipitation zones. The populations were tested in field trials in three diverse locations over 2 years. Least significant differences showed the EPs performance was dependent on their pedigree and were statistically similar and even out-performed some of their respective parents in regards to grain yield, grain protein concentration, and disease resistance. Stability models including Eberhart and Russel’s deviation from Regression (S2di), Shukla’s Stability Variance (σi2), Wricke’s Ecovalance (Wi), and the multivariate Additive Main Effects and Multiplicative Interaction (AMMI) model were used to evaluate the adaptability of the EPs and their parents. The BPPs and CCPs demonstrated significantly greater stability over the parents across precipitation zones, confirming the capacity of genetically diverse EP populations to adapt to different environments.

Candidate genes underlying QTL for flowering time and their interactions in a wide spring barley (Hordeum vulgare L.) cross

Response to vernalization and photoperiod are the main determinants controlling the time to flowering in temperate cereals. While the individual genes that determine a plant’s response to these environmental signals are well characterized, the combinatorial effect on flowering time of allelic variants for multiple genes remains unresolved. This study investigated the genetic control of flowering-time in a biparental population of spring barley, derived from a wide cross between a late-flowering European and an early-flowering North-American cultivar. While the major flowering time genes are not segregating in the Beka × Logan cross, large variation in flowering was observed. We identified five QTL, with both parents found to contribute early alleles. The catalog of QTL discovered aligns with several candidate genes affecting flowering time in barley. The combination of particular alleles at HvCEN, HvELF3 and HvFT1 in Logan are responsible for the earliness of this cultivar. Interestingly, earliness for flowering could be further enhanced, with Beka found to contribute three early alleles, including a QTL co-locating with a HvFD-like gene, suggesting that there are diverse aspects of the flowering-time pathway that have been manipulated in these two cultivars. Epistatic interactions between flowering-time QTL or candidate genes were observed in field data and confirmed under controlled conditions. The results of this study link photoperiod-dependent flowering-time genes with earliness per se genes into a single model, thus providing a unique framework that can be used by geneticists and breeders to optimize flowering time in barley.

Assessment of the Genetic Diversity of the Breeding Lines and a Genome Wide Association Study of Three Horticultural Traits Using Worldwide Cucumber (Cucumis spp.) Germplasm Collection

Cucumbers are an important economic vegetable crop that is used for fresh or processing purposes worldwide. In this study, we used 264 accessions that consisted of world-wide wild germplasms and advanced breeding lines in order to understand the genetic diversity and the genetic correlation among the germplasm collection. A genotyping-by-sequencing (GBS) approach was applied to obtain dense genome-wide markers coverage (>12,082 SNPs) to construct a high-density haplotype map. Various population stratification methods were performed, and three subgroups were divided based on the genetic diversity, which reflected their geographic regions. According to the phylogenetic analysis, the breeding lines were separated from wild germplasms, and the two distinct groups were divided within the breeding lines. One of the groups mainly consisted of East-Asian varieties, which showed the unique homogenous genotype patterns. Using this germplasm collection, three important horticultural traits of cucumbers—powdery mildew resistance, spine color, and fruit stalk-end color—were evaluated and used to conduct the genome-wide association study (GWAS). All of the significant SNPs and two novel candidate genes (Csa5G453160 and Csa5G471070) for the powdery mildew were identified in chromosome 5 from the natural population, which is where reported major QTLs from various bi-parental population are located. Furthermore, two candidate genes, Csa1G006300 and Csa3G824850, and four candidate genes, Csa2G368270, Csa3G236570, Csa5G175680, and Csa6G448170, were identified for the spine color and the fruit stalk-end color, respectively. These results are expected to be helpful to develop molecular markers of the horticultural traits in cucumbers.

Genetic Dissection of Resistance to Gray Leaf Spot by Combining Genome-Wide Association, Linkage Mapping, and Genomic Prediction in Tropical Maize Germplasm.

Gray leaf spot (GLS) is one of the major maize foliar diseases in sub-Saharan Africa. Resistance to GLS is controlled by multiple genes with additive effect and is influenced by both genotype and environment. The objectives of the study were to dissect the genetic architecture of GLS resistance through linkage mapping and genome-wide association study (GWAS) and assessing the potential of genomic prediction (GP). We used both biparental populations and an association mapping panel of 410 diverse tropical/subtropical inbred lines that were genotyped using genotype by sequencing. Phenotypic evaluation in two to four environments revealed significant genotypic variation and moderate to high heritability estimates ranging from 0.43 to 0.69. GLS was negatively and significantly correlated with grain yield, anthesis date, and plant height. Linkage mapping in five populations revealed 22 quantitative trait loci (QTLs) for GLS resistance. A QTL on chromosome 7 (qGLS7-105) is a major-effect QTL that explained 28.2% of phenotypic variance. Together, all the detected QTLs explained 10.50, 49.70, 23.67, 18.05, and 28.71% of phenotypic variance in doubled haploid (DH) populations 1, 2, 3, and F3 populations 4 and 5, respectively. Joint linkage association mapping across three DH populations detected 14 QTLs that individually explained 0.10–15.7% of phenotypic variance. GWAS revealed 10 significantly (p < 9.5 × 10–6) associated SNPs distributed on chromosomes 1, 2, 6, 7, and 8, which individually explained 6–8% of phenotypic variance. A set of nine candidate genes co-located or in physical proximity to the significant SNPs with roles in plant defense against pathogens were identified. GP revealed low to moderate prediction correlations of 0.39, 0.37, 0.56, 0.30, 0.29, and 0.38 for within IMAS association panel, DH pop1, DH pop2, DH pop3, F3 pop4, and F3 po5, respectively, and accuracy was increased substantially to 0.84 for prediction across three DH populations. When the diversity panel was used as training set to predict the accuracy of GLS resistance in biparental population, there was 20–50% reduction compared to prediction within populations. Overall, the study revealed that resistance to GLS is quantitative in nature and is controlled by many loci with a few major and many minor effects. The SNPs/QTLs identified by GWAS and linkage mapping can be potential targets in improving GLS resistance in breeding programs, while GP further consolidates the development of high GLS-resistant lines by incorporating most of the major- and minor-effect genes.

Genetic Characterization of Multiple Components Contributing to Fusarium Head Blight Resistance of FL62R1, a Canadian Bread Wheat Developed Using Systemic Breeding.

Fusarium head blight (FHB) is a devastating fungal disease of small-grain cereals that results in severe yield and quality losses. FHB resistance is controlled by resistance components including incidence, field severity, visual rating index, Fusarium damaged kernels (FDKs), and the accumulation of the mycotoxin deoxynivalenol (DON). Resistance conferred by each of these components is partial and must be combined to achieve resistance sufficient to protect wheat from yield losses. In this study, two biparental mapping populations were analyzed in Canadian FHB nurseries and quantitative trait loci (QTL) mapped for the traits listed above. Nine genomic loci, on 2AS, 2BS, 3BS, 4AS, 4AL, 4BS, 5AS, 5AL, and 5BL, were enriched for the majority of the QTL controlling FHB resistance. The previously validated FHB resistance QTL on 3BS and 5AS affected resistance to severity, FDK, and DON in these populations. The remaining seven genomic loci colocalize with flowering time and/or plant height QTL. The QTL on 4B was a major contributor to all field resistance traits and plant height in the field. QTL on 4AL showed contrasting effects for FHB resistance between Eastern and Western Canada, indicating a local adapted resistance to FHB. In addition, we also found that the 2AS QTL contributed a major effect for DON, and the 2BS for FDK, while the 5AL conferred mainly effect for both FDK/DON. Results presented here provide insight into the genetic architecture underlying these resistant components and insight into how FHB resistance in wheat is controlled by a complex network of interactions between genes controlling flowering time, plant height, local adaption, and FHB resistance components.

Quantitative Trait Loci Mapping for Spot Blotch Resistance in Two Biparental Mapping Populations of Bread Wheat.

Spot blotch (SB), caused by Bipolaris sorokiniana, is a major fungal disease of wheat in South Asia and South America. Two biparental mapping populations with 232 F2:7 progenies each were generated, with CIMMYT breeding lines CASCABEL and KATH as resistant parents and CIANO T79 as the common susceptible parent. The two populations were evaluated for field SB resistance in CIMMYT's Agua Fria station for three consecutive cropping seasons, with artificial inoculation. Genotyping was done with the DArTseq platform and approximately 1,500 high quality and nonredundant markers were used for quantitative trait loci (QTL) mapping. In both populations, a major QTL was found on chromosome 5A in the Vrn-A1 region, explaining phenotypic variations of 13.5 to 25.9%, which turned up to be less- or nonsignificant when days to heading and plant height were used as covariates in the analysis, implying a disease escape mechanism. Another major QTL was located on chromosome 5B in CASCABEL, accounting for 8.9 to 21.4% of phenotypic variation. Minor QTL were found on 4A and 4B in CASCABEL; 1B, 4B, and 4D in KATH; and 1B, 2B, and 4B in CIANO T79. Through an analysis of QTL projection onto the IWGSC Chinese Spring reference genome, the 5B QTL in CASCABEL was mapped in the Sb2 region, delimited by the single nucleotide polymorphism marker wsnp_Ku_c50354_55979952 and the simple sequence repeat marker gwm213, with a physical distance of about 14 Mb to the Tsn1 locus.

Association mapping and genomic selection for sorghum adaptation to tropical soils of Brazil in a sorghum multiparental random mating population.

A multiparental random mating population used in sorghum breeding is amenable for the detection of QTLs related to tropical soil adaptation, fine mapping of underlying genes and genomic selection approaches. Tropical soils where low phosphorus (P) and aluminum (Al) toxicity limit sorghum [Sorghum bicolor (L.) Moench] production are widespread in the developing world. We report on BRP13R, a multiparental random mating population (MP-RMP), which is commonly used in sorghum recurrent selection targeting tropical soil adaptation. Recombination dissipated much of BRP13R's likely original population structure and average linkage disequilibrium (LD) persisted up to 2.5Mb, establishing BRP13R as a middle ground between biparental populations and sorghum association panels. Genome-wide association mapping (GWAS) identified conserved QTL from previous studies, such as for root morphology and grain yield under low-P, and indicated the importance of dominance in the genetic architecture of grain yield. By overlapping consensus QTL regions, we mapped two candidate P efficiency genes to a ~ 5Mb region on chromosomes 6 (ALMT) and 9 (PHO2). Remarkably, we find that only 200 progeny genotyped with ~ 45,000 markers in BRP13R can lead to GWAS-based positional cloning of naturally rare, subpopulation-specific alleles, such as for SbMATE-conditioned Al tolerance. Genomic selection was found to be useful in such MP-RMP, particularly if markers in LD with major genes are fitted as fixed effects into GBLUP models accommodating dominance. Shifts in allele frequencies in progeny contrasting for grain yield indicated that intermediate to minor-effect genes on P efficiency, such as SbPSTOL1 genes, can be employed in pre-breeding via allele mining in the base population. Therefore, MP-RMPs such as BRP13R emerge as multipurpose resources for efficient gene discovery and deployment for breeding sorghum cultivars adapted to tropical soils.

How Machine Learning Methods Helped Find Putative Rye Wax Genes Among GBS Data.

The standard approach to genetic mapping was supplemented by machine learning (ML) to establish the location of the rye gene associated with epicuticular wax formation (glaucous phenotype). Over 180 plants of the biparental F2 population were genotyped with the DArTseq (sequencing-based diversity array technology). A maximum likelihood (MLH) algorithm (JoinMap 5.0) and three ML algorithms: logistic regression (LR), random forest and extreme gradient boosted trees (XGBoost), were used to select markers closely linked to the gene encoding wax layer. The allele conditioning the nonglaucous appearance of plants, derived from the cultivar Karlikovaja Zelenostebelnaja, was mapped at the chromosome 2R, which is the first report on this localization. The DNA sequence of DArT-Silico 3585843, closely linked to wax segregation detected by using ML methods, was indicated as one of the candidates controlling the studied trait. The putative gene encodes the ABCG11 transporter.

Maximizing efficiency of genomic selection in CIMMYT\u2019s tropical maize breeding program

Key messageHistorical data from breeding programs can be efficiently used to improve genomic selection accuracy, especially when the training set is optimized to subset individuals most informative of the target testing set.The current strategy for large-scale implementation of genomic selection (GS) at the International Maize and Wheat Improvement Center (CIMMYT) global maize breeding program has been to train models using information from full-sibs in a “test-half-predict-half approach.” Although effective, this approach has limitations, as it requires large full-sib populations and limits the ability to shorten variety testing and breeding cycle times. The primary objective of this study was to identify optimal experimental and training set designs to maximize prediction accuracy of GS in CIMMYT’s maize breeding programs. Training set (TS) design strategies were evaluated to determine the most efficient use of phenotypic data collected on relatives for genomic prediction (GP) using datasets containing 849 (DS1) and 1389 (DS2) DH-lines evaluated as testcrosses in 2017 and 2018, respectively. Our results show there is merit in the use of multiple bi-parental populations as TS when selected using algorithms to maximize relatedness between the training and prediction sets. In a breeding program where relevant past breeding information is not readily available, the phenotyping expenditure can be spread across connected bi-parental populations by phenotyping only a small number of lines from each population. This significantly improves prediction accuracy compared to within-population prediction, especially when the TS for within full-sib prediction is small. Finally, we demonstrate that prediction accuracy in either sparse testing or “test-half-predict-half” can further be improved by optimizing which lines are planted for phenotyping and which lines are to be only genotyped for advancement based on GP.

QTL mapping and validation of bread wheat flag leaf morphology across multiple environments in different genetic backgrounds.

Eight major and stably expressed QTL for flag leaf morphology across eleven environments were identified and validated using newly developed KASP markers in seven biparental populations with different genetic backgrounds. Flag leaf morphology is a determinant trait influencing plant architecture and yield potential in wheat (Triticum aestivum L.). A recombinant inbred line (RIL) population with a 55K SNP-based constructed genetic map was used to map quantitative trait loci (QTL) for flag leaf length (FLL), width (FLW), area (FLA), angle (FLANG), opening angle (FLOA), and bend angle (FLBA) in eleven environments. Eight major QTL were detected in 11 environments with 5.73-54.38% of explained phenotypic variation. These QTL were successfully verified using the newly developed Kompetitive Allele Specific PCR (KASP) markers in six biparental populations with different genetic backgrounds. Among these 8 major QTL, two co-located intervals were identified. Significant interactions for both FLL- and FLW-related QTL were detected. Comparison analysis showed that QFll.sau-SY-2B and QFla.sau-SY-2B are likely new loci. Significant relationships between flag leaf- and yield-related traits were observed and discussed. Several genes associated with leaf development including the ortholog of maize ZmRAVL1, a B3-domain transcription factor involved in regulation of leaf angle, were predicted in physical intervals harboring these major QTL on reference genomes of bread wheat 'Chinese spring', T. turgidum, and Aegilops tauschii. Taken together, these results broaden our understanding on genetic basis of flag leaf morphology and provide clues for fine mapping and marker-assisted breeding wheat with optimized plant architecture for promising loci.

Applications of genotyping-by-sequencing (GBS) in maize genetics and breeding

Genotyping-by-Sequencing (GBS) is a low-cost, high-throughput genotyping method that relies on restriction enzymes to reduce genome complexity. GBS is being widely used for various genetic and breeding applications. In the present study, 2240 individuals from eight maize populations, including two association populations (AM), backcross first generation (BC1), BC1F2, F2, double haploid (DH), intermated B73 × Mo17 (IBM), and a recombinant inbred line (RIL) population, were genotyped using GBS. A total of 955,120 of raw data for SNPs was obtained for each individual, with an average genotyping error of 0.70%. The rate of missing genotypic data for these SNPs was related to the level of multiplex sequencing: ~ 25% missing data for 96-plex and ~ 55% for 384-plex. Imputation can greatly reduce the rate of missing genotypes to 12.65% and 3.72% for AM populations and bi-parental populations, respectively, although it increases total genotyping error. For analysis of genetic diversity and linkage mapping, unimputed data with a low rate of genotyping error is beneficial, whereas, for association mapping, imputed data would result in higher marker density and would improve map resolution. Because imputation does not influence the prediction accuracy, both unimputed and imputed data can be used for genomic prediction. In summary, GBS is a versatile and efficient SNP discovery approach for homozygous materials and can be effectively applied for various purposes in maize genetics and breeding.

Genetic variation among biparental progenies in okra [Abelmoschus esculentus L. (Moench)] using coefficient of racial likeness and Mahalanobis D2 statistics

A study was carried out in Nigeria to determine the extent of genetic variation within a biparental population inokra. Sixteen crosses were made and evaluated with nine parents in a randomized complete block design withthree replications. Observations were made on important agronomic traits including pod yield. Data collected were subjected to Coefficient of Racial Likeness (CRL) and Mahalanobis D2 statistic and dendrogram was constructed. The maximum CRL distance (24.70) was between NGB00347 x NGB00350 and NGB00371 x NGB00326 while the largest Mahalanobis D2 distance (216.34) was between NGB00302 and NGB00356.The twenty-five genotypes were grouped into six clusters based on CRL while Mahalanobis D2 statistic identified four clusters. The NGB00297 x NGB00326 in cluster 6 had earliness to flowering, longest pod, heaviest pod, widest pods, the highest number of pod/plant and yield/plant. The genotype would be useful in the future development program in okra breeding.

Variation of Phenotypic Traits in Twelve Bambara Groundnut (Vigna subterranea (L.) Verdc.) Genotypes and Two F2 Bi-Parental Segregating Populations

Underutilised species such as bambara groundnut (Vigna subterranea (L.) Verdc.) have the potential to contribute significantly to meeting food and nutritional needs worldwide. We evaluated phenotypic traits in twelve bambara groundnut genotypes from East, West and Southern Africa and Southeast Asia and two F2 bi-parental segregating populations derived from IITA-686 ×Tiga Nicuru and S19-3 ×DodR to determine phenotypic trait variation and their potential contribution to the development of improved crop varieties. All phenotypic traits in twelve genotypes were significantly influenced (p &lt; 0.01) by genotypes. Principal component analysis (PCA) showed that PC1 accounted for 97.33% variation and was associated with four genotypes collected from East and Southern Africa. PC2 accounted for 2.48% of the variation and was associated with five genotypes collected from East, West and Southern Africa. Transgressive segregation for a number of traits was observed in the two F2 bi-parental populations, as some individual lines in the segregating populations showed trait values greater or less than their parents. The variability between twelve genotypes and the two F2 bi-parental segregating populations and the negative relationship between plant architectural traits and yield related traits provide resources for development of structured populations and breeding lines for bambara groundnut breeding programme.

Soybean BARCSoySNP6K: An assay for soybean genetics and breeding research.

SUMMARYThe limited number of recombinant events in recombinant inbred lines suggests that for a biparental population with a limited number of recombinant inbred lines, it is unnecessary to genotype the lines with many markers. For genomic prediction and selection, previous studies have demonstrated that only 1000–2000 genome‐wide common markers across all lines/accessions are needed to reach maximum efficiency of genomic prediction in populations. Evaluation of too many markers will not only increase the cost but also generate redundant information. We developed a soybean (Glycine max) assay, BARCSoySNP6K, containing 6000 markers, which were carefully chosen from the SoySNP50K assay based on their position in the soybean genome and haplotype block, polymorphism among accessions and genotyping quality. The assay includes 5000 single nucleotide polymorphisms (SNPs) from euchromatic and 1000 from heterochromatic regions. The percentage of SNPs with minor allele frequency >0.10 was 95% and 91% in the euchromatic and heterochromatic regions, respectively. Analysis of progeny from two large families genotyped with SoySNP50K versus BARCSoySNP6K showed that the position of the common markers and number of unique bins along linkage maps were consistent based on the SNPs genotyped with the two assays; however, the rate of redundant markers was dramatically reduced with the BARCSoySNP6K. The BARCSoySNP6K assay is proven as an excellent tool for detecting quantitative trait loci, genomic selection and assessing genetic relationships. The assay is commercialized by Illumina Inc. and being used by soybean breeders and geneticists and the list of SNPs in the assay is an ideal resource for SNP genotyping by targeted amplicon sequencing.

Phenolic compounds identified in apricot branch tissues and their role in the control of Monilinia laxa growth

Secondary metabolites, such as phenolics, are plant defence substances. In the present study, the impact of Monilinia laxa inoculation under controlled conditions on phenolic content of apricot branches was investigated. A bi-parental hybrid population issued from Bergeron and Bakour cultivars (BerBa) and consisting of 192 hybrids was studied. The susceptibility of the BerBa population to M. laxa was evaluated by measuring the length of the necrosed tissues and the concentration of fungal DNA by qPCR in the branches 8 days post-inoculation. The results exhibit significant differences between the two parental cultivars in terms of necrosis length, which confirm their different susceptibility to the pathogen. A considerably high content of 2′,6′-dihydroxy-4′–methoxyacetophenone hexoside was found in branch tissues of Bakour (tolerant parental cultivar), amounting to 1.72 mg/g and 1.41 mg/g of fresh weight in non-inoculated and inoculated samples, respectively. The content of this compound in Bergeron branch tissues was several times lower, amounting to 0.24 mg/g and 0.14 mg/g of fresh weight in non-inoculated and inoculated samples, respectively. In the inoculated branches, scopolin was almost twice as abundant in the tolerant parental cultivar branch tissues as in the susceptible ones. In general, after inoculation a lower content of phenolic compounds was observed for hybrids with longer necrosed tissue. A Principal Component Analysis showed that at 8 days post-inoculation M. laxa concentration in the branches and the content of phenolic compounds, such as scopolin and chlorogenic acids, were negatively correlated. Additionally, the antifungal activity of pure phenolic compounds against M. laxa mycelial growth and spore germination was investigated. At a concentration of 500 mg/L, up to 40 % inhibition of M. laxa mycelial growth by scopoletin, up to 60 % inhibition by 2′,4′,6′-trihydroxyacetophenone and total inhibition by 2′-hydroxy-4′-methoxyacetophenone was observed. Scopoletin and 2′,4′,6′-trihydroxyacetophenone also inhibited spore germination by about 50 %. These results can serve to improve breeding programs aiming to develop apricot cultivars resistant to brown rot blossom blight.

Divergence of defensive cucurbitacins in independent Cucurbita pepo domestication events leads to differences in specialist herbivore preference.

Crop domestication and improvement often concurrently affect plant resistance to pests and production of secondary metabolites, creating challenges for isolating the ecological implications of selection for specific metabolites. Cucurbitacins are bitter triterpenoids with extreme phenotypic differences between Cucurbitaceae lineages, yet we lack integrated models of herbivore preference, cucurbitacin accumulation, and underlying genetic mechanisms. In Cucurbita pepo, we dissected the effect of cotyledon cucurbitacins on preference of a specialist insect pest (Acalymma vittatum) for multiple tissues, assessed genetic loci underlying cucurbitacin accumulation in diverse germplasm and a biparental F2 population (from a cross between two independent domesticates), and characterized quantitative associations between gene expression and metabolites during seedling development. Acalymma vittatum affinity for cotyledons is mediated by cucurbitacins, but other traits contribute to whole-plant resistance. Cotyledon cucurbitacin accumulation was associated with population structure, and our genetic mapping identified a single locus, Bi-4, containing genes relevant to transport and regulation - not biosynthesis - that diverged between lineages. These candidate genes were expressed during seedling development, most prominently a putative secondary metabolite transporter. Taken together, these findings support the testable hypothesis that breeding for plant resistance to insects involves targeting genes for regulation and transport of defensive metabolites, in addition to core biosynthesis genes.

Localization of the Stem Rust Resistance Gene Pg2 to Linkage Group Mrg20 in Cultivated Oat (Avena sativa).

Stem rust is an important disease of cultivated oat (Avena sativa) caused by Puccinia graminis f. sp. avenae. In North America, host resistance is the primary strategy to control this disease and is conferred by a relatively small number of resistance genes. Pg2 is a widely deployed stem rust resistance gene that originates from cultivated oat. Oat breeders wish to develop cultivars with multiple Pg genes to slow the breakdown of single gene resistance, and often require DNA markers suited for marker-assisted selection. Our objectives were to (i) construct high density linkage maps for a major oat stem rust resistance gene using three biparental mapping populations, (ii) develop Kompetitive allele-specific PCR (KASP) assays for Pg2-linked single-nucleotide polymorphisms (SNPs), and (iii) test the prediction accuracy of those markers with a diverse panel of spring oat lines and cultivars. Genotyping-by-sequencing SNP markers linked to Pg2 were identified in an AC Morgan/CDC Morrison recombinant inbred line (RIL) population. Pg2-linked SNPs were then analyzed in an AC Morgan/RL815 F2 population and an AC Morgan/CDC Dancer RIL population. Linkage analysis identified a common location for Pg2 in all three populations on linkage group Mrg20 of the oat consensus genetic map. The most predictive markers were identified and converted to KASP assays for use in oat breeding programs. When used in combination, the KASP assays for the SNP loci avgbs2_126549.1.46 and avgbs_cluster_23819.1.27 were highly predictive of Pg2 status in panel of 54 oat breeding lines and cultivars.

Combination of Linkage Mapping, GWAS, and GP to Dissect the Genetic Basis of Common Rust Resistance in Tropical Maize Germplasm

Common rust (CR) caused by Puccina sorghi is one of the destructive fungal foliar diseases of maize and has been reported to cause moderate to high yield losses. Providing CR resistant germplasm has the potential to increase yields. To dissect the genetic architecture of CR resistance in maize, association mapping, in conjunction with linkage mapping, joint linkage association mapping (JLAM), and genomic prediction (GP) was conducted on an association-mapping panel and five F3 biparental populations using genotyping-by-sequencing (GBS) single-nucleotide polymorphisms (SNPs). Analysis of variance for the biparental populations and the association panel showed significant genotypic and genotype x environment (GXE) interaction variances except for GXE of Pop4. Heritability (h2) estimates were moderate with 0.37–0.45 for the individual F3 populations, 0.45 across five populations and 0.65 for the association panel. Genome-wide association study (GWAS) analyses revealed 14 significant marker-trait associations which individually explained 6–10% of the total phenotypic variances. Individual population-based linkage analysis revealed 26 QTLs associated with CR resistance and together explained 14–40% of the total phenotypic variances. Linkage mapping revealed seven QTLs in pop1, nine QTL in pop2, four QTL in pop3, five QTL in pop4, and one QTL in pop5, distributed on all chromosomes except chromosome 10. JLAM for the 921 F3 families from five populations detected 18 QTLs distributed in all chromosomes except on chromosome 8. These QTLs individually explained 0.3 to 3.1% and together explained 45% of the total phenotypic variance. Among the 18 QTL detected through JLAM, six QTLs, qCR1-78, qCR1-227, qCR3-172, qCR3-186, qCR4-171, and qCR7-137 were also detected in linkage mapping. GP within population revealed low to moderate correlations with a range from 0.19 to 0.51. Prediction correlation was high with r = 0.78 for combined analysis of the five F3 populations. Prediction of biparental populations by using association panel as training set reveals positive correlations ranging from 0.05 to 0.22, which encourages to develop an independent but related population as a training set which can be used to predict diverse but related populations. The findings of this study provide valuable information on understanding the genetic basis of CR resistance and the obtained information can be used for developing functional molecular markers for marker-assisted selection and for implementing GP to improve CR resistance in tropical maize.

Sequencing depth and genotype quality: accuracy and breeding operation considerations for genomic selection applications in autopolyploid crops

Key messagePolypoid crop breeders can balance resources between density and sequencing depth, dosage information and fewer highly informative SNPs recommended, non-additive models and QTL advantages on prediction dependent on trait architecture.The autopolyploid nature of potato and sweetpotato ensures a wide range of meiotic configurations and linkage phases leading to complex gene-action and pose problems in genotype data quality and genomic selection analyses. We used a 315-progeny biparental F1 population of hexaploid sweetpotato and a diversity panel of 380 tetraploid potato, genotyped using different platforms to answer the following questions: (i) do polyploid crop breeders need to invest more for additional sequencing depth? (ii) how many markers are required to make selection decisions? (iii) does considering non-additive genetic effects improve predictive ability (PA)? (iv) does considering dosage or quantitative trait loci (QTL) offer significant improvement to PA? Our results show that only a small number of highly informative single nucleotide polymorphisms (SNPs; ≤ 1000) are adequate for prediction in the type of populations we analyzed. We also show that considering dosage information and models considering only additive effects had the best PA for most traits, while the comparative advantage of considering non-additive genetic effects and including known QTL in the predictive model depended on trait architecture. We conclude that genomic selection can help accelerate the rate of genetic gains in potato and sweetpotato. However, application of genomic selection should be considered as part of optimizing the entire breeding program. Additionally, since the predictions in the current study are based on single populations, further studies on the effects of haplotype structure and inheritance on PA should be studied in actual multi-generation breeding populations.

Identification and validation of major QTLs associated with low seed coat deficiency of natto soybean seeds (Glycine max L.)

Key messageTwo major QTLs associated with low seed coat deficiency of soybean seeds were identified in two biparental populations, and three SNP markers were validated to assist low-SCD natto soybean breeding selection.Soybean seed coat deficiency (SCD), known as seed coat cracking during soaking in the natto production process, is problematic because split or broken beans clog production lines and increases production costs. Development of natto soybean cultivars with low SCD is crucial to support the growth of the natto industry. Unfortunately, information on the genetic control of SCD in soybean, which is desperately needed to facilitate breeding selection, remains sparse. In this study, two F2 populations derived from V11-0883 × V12-1626 (Pop 1) and V11-0883 × V12-1885 (Pop 2) were developed and genotyped with BARCSoySNP6K Beadchips and F2-derived lines were evaluated for SCD in three consecutive years (2016–2018) in order to identify quantitative trait loci (QTLs) associated with low SCD in soybean. A total of 17 QTLs underlying SCD were identified in two populations. Among these, two major and stable QTLs, qSCD15 on chromosome 15 and qSCD20 on chromosome 20, were detected across multiple years. These QTLs explained up to 30.3% of the phenotypic variation for SCD in Pop 1 and 6.1% in Pop 2 across years. Three SNP markers associated with the qSCD20 were validated in additional four biparental populations. The average selection efficiency of low-SCD soybean was 77% based on two tightly linked markers, Gm20_34626867 and Gm20_34942502, and 64% based on the marker Gm20_35625615. The novel and stable QTLs identified in this study will facilitate elucidation of the genetic mechanism controlling SCD in soybean, and the markers will significantly accelerate breeding for low-SCD soybean through marker-assisted selection.