Evaluating and Predicting the Performance of Sorghum Lines in an Elite by Exotic Backcross-Nested Association Mapping Population.

Maintaining or introducing genetic diversity into plant breeding programs is necessary for continual genetic gain; however, diversity at the cost of reduced performance is not something sought by breeders. To this end, backcross-nested association mapping (BC-NAM) populations, in which the recurrent parent is an elite line, can be employed as a strategy to introgress diversity from unadapted accessions while maintaining agronomic performance. This study evaluates (i) the hybrid performance of sorghum lines from 18 BC1-NAM families and (ii) the potential of genomic prediction to screen lines from BC1-NAM families for hybrid performance prior to phenotypic evaluation. Despite the diverse geographical origins and agronomic performance of the unadapted parents for BC1-NAM families, many BC1-derived lines performed significantly better in the hybrid trials than the elite recurrent parent, R.Tx436. The genomic prediction accuracies for grain yield, plant height, and days to mid-anthesis were acceptable, but the prediction accuracies for plant height were lower than expected. While the prediction accuracies increased when including more individuals in the training set, improvements tended to plateau between two and five lines per family, with larger training sets being required for more complex traits such as grain yield. Therefore, genomic prediction models can be optimized in a large BC1-NAM population with a relatively low fraction of individuals needing to be evaluated. These results suggest that genomic prediction is an effective method of pre-screening lines within BC1-NAM families prior to evaluation in extensive hybrid field trials.

Pedigree-based QTL analysis of flower size traits in two multi-parental diploid rose populations.

Rose (Rosa spp.) is one of the most economically important ornamental species worldwide. Flower diameter, flower weight, and the number of petals and petaloids are key flower-size parameters and attractive targets for DNA-informed breeding. Pedigree-based analysis (PBA) using FlexQTL software was conducted using two sets of multi-parental diploid rose populations. Phenotypic data for flower diameter (Diam), flower weight (fresh (FWT)/dry (DWT)), number of petals (NP), and number of petaloids (PD) were collected over six environments (seasons) at two locations in Texas. The objectives of this study were to 1) identify new and/or validate previously reported QTL(s); 2) identify SNP haplotypes associated with QTL alleles (Q-/q-) of a trait and their sources; and 3) determine QTL genotypes for important rose breeding parents. Several new and previously reported QTLs for NP and Diam traits were identified. In addition, QTLs associated with flower weight and PD were identified for the first time. Two major QTLs with large effects were mapped for all traits. The first QTL was at the distal end of LG1 (60.44-60.95 Mbp) and was associated with Diam and DWT in the TX2WOB populations. The second QTL was consistently mapped in the middle region on LG3 (30.15-39.34 Mbp) and associated with NP, PD, and flower weight across two multi-parent populations (TX2WOB and TX2WSE). Haplotype results revealed a series of QTL alleles with differing effects at important loci for most traits. This work is distinct from previous studies by conducting co-factor analysis to account for the DOUBLE FLOWER locus while mapping QTL for NP. Sources of high-value (Q) alleles were identified, namely, 'Old Blush' and Rosa wichuraiana from J14-3 for Diam, while 'Violette' and PP-J14-3 were sources for other traits. In addition, the source of the low-value (q) alleles for Diam was 'Little Chief', and Rosa wichuraiana through J14-3 was the source for the remaining traits. Hence, our results can potentially inform parental/seedling selections as means to improve ornamental quality in roses and a step towards implementing DNA-informed techniques for use in rose breeding programs.

QTL discovery for resistance to black spot and cercospora leaf spot, and defoliation in two interconnected F1 bi-parental tetraploid garden rose populations.

Garden roses are an economically important horticultural crop worldwide, and two major fungal pathogens, black spot (Diplocarpon rosae F.A. Wolf) and cercospora leaf spot of rose (Rosisphaerella rosicola Pass.), affect both the health and ornamental value of the plant. Most studies on black spot disease resistance have focused on diploid germplasm, and little work has been performed on cercospora leaf spot resistance. With the use of newly developed software tools for autopolyploid genetics, two interconnected tetraploid garden rose F1 populations (phenotyped over the course of 3 years) were used for quantitative trait locus (QTL) analysis of black spot and cercospora leaf spot resistance as well as plant defoliation. QTLs for black spot resistance were mapped to linkage groups (LGs) 1-6. QTLs for cercospora resistance and susceptibility were found in LGs 1, 4, and 5 and for defoliation in LGs 1, 3, and 5. The major locus on LG 5 for black spot resistance coincides with the previously discovered Rdr4 locus inherited from Rosa L. 'Radbrite' (Brite Eyes™), the common parent used in these mapping populations. This work is the first report of any QTL for cercospora resistance/susceptibility in tetraploid rose germplasm and the first report of defoliation QTL in roses. A major QTL for cercospora susceptibility coincides with the black spot resistance QTL on LG 5 (Rdr4). A major cercospora resistance QTL was found on LG 1. These populations provide a genetic resource that will further the knowledge base of rose genetics as more traits are studied. Studying more traits from these populations will allow for the stacking of various QTLs for desirable traits.

Use of genomic prediction to screen sorghum B-lines in hybrid testcrosses.

Use of trifluoromethanesulfonamide (TFMSA), a male gametocide, increases the opportunities to identify promising B-lines because large quantities of F1 seed can be generated prior to the laborious task of B-line sterilization. Combining TFMSA technology with genomic selection could efficiently evaluate sorghum B-lines in hybrid combination to maximize the rates of genetic gain of the crop. This study used two recombinant inbred B-line populations, consisting of 217 lines, which were testcrossed to two R-lines to produce 434 hybrids. Each population of testcross hybrids were evaluated across five environments. Population-based genomic prediction models were assessed across environments using three different cross-validation (CV) schemes, each with 70% training and 30% validation sets. The validation schemes were as follows: CV1-hybrids chosen randomly for validation; CV2-B-lines were randomly chosen, and each chosen B-line had one of the two corresponding testcross hybrids randomly chosen for the validation; and CV3-B-lines were randomly chosen, and each chosen B-line had both corresponding testcross hybrids chosen for the validation. CV1 and CV2 presented the highest prediction accuracies; nonetheless, the prediction accuracies of the CV schemes were not statistically different in many environments. We determined that combining the B-line populations could improve prediction accuracies, and the genomic prediction models were able to effectively rank the poorest 70% of hybrids even when genomic prediction accuracies themselves were low. Results indicate that combining genomic prediction models and TFMSA technology can effectively aid breeders in predicting B-line hybrid performance in early generations prior to the laborious task of generating A/B-line pairs.

Genomic prediction can be used to screen sorghum B-lines for hybrid grain yield and days to mid-anthesis. Using genomic prediction and the chemical gametocide TFMSA can increase the rate of genetic gain in sorghum B-lines. Using testers to screen sorghum B-line populations is an effective method for screening with genomic prediction. Genomic prediction can effectively predict hybrid performance within and across populations of sorghum B-lines. The ability to accurately rank hybrid performance remained relatively consistent regardless of prediction accuracy.

Evaluating Introgression Sorghum Germplasm Selected at the Population Level While Exploring Genomic Resources as a Screening Method.

To exploit the novel genetic diversity residing in tropical sorghum germplasm, an expansive backcross nested-association mapping (BC-NAM) resource was developed in which novel genetic diversity was introgressed into elite inbreds. A major limitation of exploiting this type of genetic resource in hybrid improvement programs is the required evaluation in hybrid combination of the vast number of BC-NAM populations and lines. To address this, the utility of genomic information was evaluated to predict the hybrid performance of BC-NAM populations. Two agronomically elite BC-NAM populations were chosen for evaluation in which elite inbred RTx436 was the recurrent parent. Each BC1F3 line was evaluated in hybrid combination with an elite tester in two locations with phenotypes of grain yield, plant height, and days to anthesis collected on all test cross hybrids. Lines from both populations were found to outperform their recurrent parent. Efforts to utilize genetic distance based on genotyping-by-sequence (GBS) as a predictive tool for hybrid performance was ineffective. However, utilizing genomic prediction models using additive and dominance GBLUP kernels to screen germplasm appeared to be an effective method to eliminate inferior-performing lines that will not be useful in a hybrid breeding program.

Genetic modification of PIN genes induces causal mechanisms of stay-green drought adaptation phenotype.

The stay-green trait is recognized as a key drought adaptation mechanism in cereals worldwide. Stay-green sorghum plants exhibit delayed senescence of leaves and stems, leading to prolonged growth, a reduced risk of lodging, and higher grain yield under end-of-season drought stress. More than 45 quantitative trait loci (QTL) associated with stay-green have been identified, including two major QTL (Stg1 and Stg2). However, the contributing genes that regulate functional stay-green are not known. Here we show that the PIN FORMED family of auxin efflux carrier genes induce some of the causal mechanisms driving the stay-green phenotype in sorghum, with SbPIN4 and SbPIN2 located in Stg1 and Stg2, respectively. We found that nine of 11 sorghum PIN genes aligned with known stay-green QTL. In transgenic studies, we demonstrated that PIN genes located within the Stg1 (SbPIN4), Stg2 (SbPIN2), and Stg3b (SbPIN1) QTL regions acted pleiotropically to modulate canopy development, root architecture, and panicle growth in sorghum, with SbPIN1, SbPIN2, and SbPIN4 differentially expressed in various organs relative to the non-stay-green control. The emergent consequence of such modifications in canopy and root architecture is a stay-green phenotype. Crop simulation modelling shows that the SbPIN2 phenotype can increase grain yield under drought.

Rose Rosette Disease Resistance Loci Detected in Two Interconnected Tetraploid Garden Rose Populations.

Rose rosette disease (RRD), caused by the Rose rosette emaravirus (RRV), is a major threat to the garden rose industry in the United States. There has been limited work on the genetics of host plant resistance to RRV. Two interconnected tetraploid garden rose F1 biparental mapping populations were created to develop high-quality tetraploid rose linkage maps that allowed the discovery of RRD resistance quantitative trait loci (QTLs) on linkage groups (LGs) 5, 6, and 7. These QTLs individually accounted for around 18-40% of the phenotypic variance. The locus with the greatest effect on partial resistance was found in LG 5. Most individuals with the LG 5 QTL were in the simplex configuration; however, two individuals were duplex (likely due to double reduction). Identification of resistant individuals and regions of interest can help the development of diagnostic markers for marker-assisted selection in a breeding program.

Identification of QTLs for Reduced Susceptibility to Rose Rosette Disease in Diploid Roses.

Resistance to rose rosette disease (RRD), a fatal disease of roses (Rosa spp.), is a high priority for rose breeding. As RRD resistance is time-consuming to phenotype, the identification of genetic markers for resistance could expedite breeding efforts. However, little is known about the genetics of RRD resistance. Therefore, we performed a quantitative trait locus (QTL) analysis on a set of inter-related diploid rose populations phenotyped for RRD resistance and identified four QTLs. Two QTLs were found in multiple years. The most consistent QTL is qRRV_TX2WSE_ch5, which explains approximately 20% and 40% of the phenotypic variation in virus quantity and severity of RRD symptoms, respectively. The second, a QTL on chromosome 1, qRRD_TX2WSE_ch1, accounts for approximately 16% of the phenotypic variation for severity. Finally, a third QTL on chromosome 3 was identified only in the multiyear analysis, and a fourth on chromosome 6 was identified in data from one year only. In addition, haplotypes associated with significant changes in virus quantity and severity were identified for qRRV_TX2WSE_ch5 and qRRD_TX2WSE_ch1. This research represents the first report of genetic determinants of resistance to RRD. In addition, marker trait associations discovered here will enable better parental selection when breeding for RRD resistance and pave the way for marker-assisted selection for RRD resistance.

Ethylene Response Factor109 Attunes Immunity, Photosynthesis, and Iron Homeostasis in Arabidopsis Leaves.

Iron (Fe) is an essential micronutrient element for all organisms including plants. Chlorosis of young leaves is a common symptom of Fe deficiency, reducing the efficiency of photosynthesis, and, ultimately, crop yield. Previous research revealed strong responsiveness of the putative key transcription factor ERF109 to the Fe regime. To elucidate the possible role of ERF109 in leaf Fe homeostasis and photosynthesis, we subjected Arabidopsis thaliana erf109 knockout lines and Col-0 wild-type plants to transcriptome profiling via RNA-seq. The transcriptome profile of Fe-sufficient erf109 leaves showed a 71% overlap with Fe-deficient Col-0 plants. On the other hand, genes that were differentially expressed between Fe-deficient and Fe-sufficient Col-0 plants remained unchanged in erf109 plants under conditions of Fe deficiency. Mutations in ERF109 increased the expression of the clade Ib bHLH proteins bHLH38, bHLH39, bHLH101, the nicotianamine synthase NAS4, and the Fe storage gene FER1. Moreover, mutations in ERF109 led to significant down-regulation of defense genes, including CML37, WRKY40, ERF13, and EXO70B2. Leaves of erf109 exhibited increased Fe levels under both Fe-sufficient and Fe-deficient conditions. Reduced Fv/Fm and Soil Plant Analysis Development (SPAD) values in erf109 lines under Fe deficiency indicate curtailed ability of photosynthesis relative to the wild-type. Our findings suggest that ERF109 is a negative regulator of the leaf response to Fe deficiency. It further appears that the function of ERF109 in the Fe response is critical for regulating pathogen defense and photosynthetic efficiency. Taken together, our study reveals a novel function of ERF109 and provides a systematic perspective on the intertwining of the immunity regulatory network and cellular Fe homeostasis.

Genetic control of source-sink relationships in grain sorghum.

MAIN CONCLUSION: QTL hotspots identified for selected source-sink-related traits provide the opportunity for pyramiding favorable alleles for improving sorghum productivity under diverse environments. A sorghum bi-parental mapping population was evaluated under six different environments at Hays and Manhattan, Kansas, USA, in 2016 and 2017, to identify genomic regions controlling source-sink relationships. The population consisted of 210 recombinant inbred lines developed from US elite post-flowering drought susceptible (RTx430) and a known post-flowering drought tolerant cultivar (SC35). Selected physiological traits related to source (effective quantum yield of photosystem II and chlorophyll index), sink (grain yield per panicle) and panicle neck diameter were recorded during grain filling. The results showed strong phenotypic and genotypic association between panicle neck diameter and grain yield per panicle during mid-grain filling and at maturity. Multiple QTL model revealed 5-12 including 2-5 major QTL for each trait. Among them 3, 7 and 8 QTL for quantum yield, panicle neck diameter and chlorophyll index, respectively, have not been identified previously in sorghum. Phenotypic variation explained by QTL identified across target traits ranged between 5.5 and 25.4%. Panicle neck diameter and grain yield per panicle were positively associated, indicating the possibility of targeting common co-localized QTL to improve both traits simultaneously through marker-assisted selection. Three major QTL hotspots, controlling multiple traits were identified on chromosome 1 (52.23-61.18 Mb), 2 (2.52-11.43 Mb) and 3 (1.32-3.95 Mb). The identified genomic regions and underlying candidate genes can be utilized in pyramiding favorable alleles for improving source-sink relationships in sorghum under diverse environments.

Pedigree-based analysis in multi-parental diploid rose populations reveals QTLs for cercospora leaf spot disease resistance.

Cercospora leaf spot (CLS) (Cercospora rosicola) is a major fungal disease of roses (Rosa sp.) in the southeastern U.S. Developing CLS-resistant cultivars offers a potential solution to reduce pesticide use. Yet, no work has been performed on CLS resistance. This study aimed to identify QTLs and to characterize alleles for resistance to CLS. The study used pedigree-based QTL analysis to dissect the genetic basis of CLS resistance using two multi-parental diploid rose populations (TX2WOB and TX2WSE) evaluated across five years in two Texas locations. A total 38 QTLs were identified across both populations and distributed over all linkage groups. Three QTLs on LG3, LG4, and LG6 were consistently mapped over multiple environments. The LG3 QTL was mapped in a region between 18.9 and 27.8 Mbp on the Rosa chinensis genome assembly. This QTL explained 13 to 25% of phenotypic variance. The LG4 QTL detected in the TX2WOB population spanned a 35.2 to 39.7 Mbp region with phenotypic variance explained (PVE) up to 48%. The LG6 QTL detected in the TX2WSE population was localized to 17.9 to 33.6 Mbp interval with PVE up to 36%. Also, this study found multiple degrees of favorable allele effects (q-allele) associated with decreasing CLS at major loci. Ancestors 'OB', 'Violette', and PP-M4-4 were sources of resistance q-alleles. These results will aid breeders in parental selection to develop CLS-resistant rose cultivars. Ultimately, high throughput DNA tests that target major loci for CLS could be developed for routine use in a DNA-informed breeding program.

QTL mapping and characterization of black spot disease resistance using two multi-parental diploid rose populations.

Black spot disease (BSD) (Diplocarpon rosae) is the most common and damaging fungal disease in garden roses (Rosa sp.). Although qualitative resistance to BSD has been extensively investigated, the research on quantitative resistance lags behind. The goal of this research was to study the genetic basis of BSD resistance in two multi-parental populations (TX2WOB and TX2WSE) through a pedigree-based analysis approach (PBA). Both populations were genotyped and evaluated for BSD incidence over five years in three locations in Texas. A total of 28 QTLs, distributed over all linkage groups (LGs), were detected across both populations. Consistent minor effect QTLs included two on LG1 and LG3 (TX2WOB and TX2WSE), two on LG4 and LG5 (TX2WSE), and one QTL on LG7 (TX2WOB). In addition, one major QTL detected in both populations was consistently mapped on LG3. This QTL was localized to an interval ranging from 18.9 to 27.8 Mbp on the Rosa chinensis genome and explained 20 and 33% of the phenotypic variation. Furthermore, haplotype analysis showed that this QTL had three distinct functional alleles. The parent PP-J14-3 was the common source of the LG3 BSD resistance in both populations. Taken together, this research presents the characterization of new SNP-tagged genetic determinants of BSD resistance, the discovery of marker-trait associations to enable parental choice based on their BSD resistance QTL haplotypes, and substrates for the development of trait-predictive DNA tests for routine use in marker-assisted breeding for BSD resistance.

Assessing combining abilities, genomic data, and genotype × environment interactions to predict hybrid grain sorghum performance.

Genomic selection in maize (Zea mays L.) has been one factor that has increased the rate of genetic gain when compared with other cereals. However, the technological foundations in maize also exist in other cereal crops that would allow prediction of hybrid performance based on general (GCA) and specific (SCA) combining abilities applied through genomic-enabled prediction models. Further, the incorporation of genotype × environment (G × E) interaction effects present an opportunity to deploy hybrids to targeted environments. To test these concepts, a factorial mating design of elite yet divergent grain sorghum lines generated hybrids for evaluation. Inbred parents were genotyped, and markers were used to assess population structure and develop the genomic relationship matrix (GRM). Grain yield, height, and days to anthesis were collected for hybrids in replicated trials, and best linear unbiased estimates were used to train classical GCA-SCA-based and genomic (GB) models under a hierarchical Bayesian framework. To incorporate population structure, GB was fitted using the GRM of both parents and hybrids. For GB models, G × E interaction effects were included by the Hadamard product between GRM and environments. A leave-one-out cross-validation scheme was used to study the prediction capacity of models. Classical and genomic models effectively predicted hybrid performance and prediction accuracy increased by including genomic data. Genomic models effectively partitioned the variation due to GCA, SCA, and their interaction with the environment. A strategy to implement genomic selection for hybrid sorghum [Sorghum bicolor (L.) Moench] breeding is presented herein.

Four chromosome scale genomes and a pan-genome annotation to accelerate pecan tree breeding.

Genome-enabled biotechnologies have the potential to accelerate breeding efforts in long-lived perennial crop species. Despite the transformative potential of molecular tools in pecan and other outcrossing tree species, highly heterozygous genomes, significant presence-absence gene content variation, and histories of interspecific hybridization have constrained breeding efforts. To overcome these challenges, here, we present diploid genome assemblies and annotations of four outbred pecan genotypes, including a PacBio HiFi chromosome-scale assembly of both haplotypes of the 'Pawnee' cultivar. Comparative analysis and pan-genome integration reveal substantial and likely adaptive interspecific genomic introgressions, including an over-retained haplotype introgressed from bitternut hickory into pecan breeding pedigrees. Further, by leveraging our pan-genome presence-absence and functional annotation database among genomes and within the two outbred haplotypes of the 'Lakota' genome, we identify candidate genes for pest and pathogen resistance. Combined, these analyses and resources highlight significant progress towards functional and quantitative genomics in highly diverse and outbred crops.

Phenotypic, Phytochemical, and Transcriptomic Analysis of Black Sorghum (Sorghum bicolor L.) Pericarp in Response to Light Quality.

Black sorghum [Sorghum bicolor (L.) Moench] is characterized by the black appearance of the pericarp and production of 3-deoxyanthocyanidins (3-DOA), which are valued for their cytotoxicity to cancer cells and as natural food colorants and antioxidant additives. The black pericarp phenotype is not fully penetrant in all environments, which implicates the light spectrum and/or photoperiod as the critical factor for trait expression. In this study, black- or red-pericarp genotypes were grown under regimes of visible light, visible light supplemented with UVA or supplemented with UVA plus UVB (or dark control). Pericarp 3-DOAs and pericarp pigmentation were maximized in the black genotype exposed to a light regime supplemented with UVB. Changes in gene expression during black pericarp development revealed that ultraviolet light activates genes related to plant defense, reactive oxygen species, and secondary metabolism, suggesting that 3-DOA accumulation is associated with activation of flavonoid biosynthesis and several overlapping defense and stress signaling pathways.

Elevated Temperatures Impose Transcriptional Constraints and Elicit Intraspecific Differences Between Coffee Genotypes.

The projected impact of global warming on coffee production may require the heat-adapted genotypes in the next decades. To identify cellular strategies in response to warmer temperatures, we compared the effect of elevated temperature on two commercial Coffea arabica L. genotypes exploring leaf physiology, transcriptome, and carbohydrate/protein composition. Growth temperatures were 23/19°C (day/night), as optimal condition (OpT), and 30/26°C (day/night) as a possible warmer scenario (WaT). The cv. Acauã showed lower levels of leaf temperature (Tleaf) under both conditions compared to cv. Catuaí, whereas slightly or no differences for other leaf physiological parameters. Therefore, to explore temperature responsive pathways the leaf transcriptome was examined using RNAseq. Genotypes showed a marked number of differentially-expressed genes (DEGs) under OpT, however DEGs strongly decrease in both at WaT condition indicating a transcriptional constraint. DEGs responsive to WaT revealed shared and genotype-specific genes mostly related to carbohydrate metabolism. Under OpT, leaf starch content was greater in cv. Acauã and, as WaT temperature was imposed, the leaf soluble sugar did not change in contrast to cv. Catuaí, although the levels of leaf starch, sucrose, and leaf protein decreased in both genotypes. These findings revealed intraspecific differences in the underlying transcriptional and metabolic interconnected pathways responsive to warmer temperatures, which is potentially linked to thermotolerance, and thus may be useful as biomarkers in breeding for a changing climate.

A single polyploidization event at the origin of the tetraploid genome of Coffea arabica is responsible for the extremely low genetic variation in wild and cultivated germplasm.

The genome of the allotetraploid species Coffea arabica L. was sequenced to assemble independently the two component subgenomes (putatively deriving from C. canephora and C. eugenioides) and to perform a genome-wide analysis of the genetic diversity in cultivated coffee germplasm and in wild populations growing in the center of origin of the species. We assembled a total length of 1.536 Gbp, 444 Mb and 527 Mb of which were assigned to the canephora and eugenioides subgenomes, respectively, and predicted 46,562 gene models, 21,254 and 22,888 of which were assigned to the canephora and to the eugeniodes subgenome, respectively. Through a genome-wide SNP genotyping of 736 C. arabica accessions, we analyzed the genetic diversity in the species and its relationship with geographic distribution and historical records. We observed a weak population structure due to low-frequency derived alleles and highly negative values of Taijma's D, suggesting a recent and severe bottleneck, most likely resulting from a single event of polyploidization, not only for the cultivated germplasm but also for the entire species. This conclusion is strongly supported by forward simulations of mutation accumulation. However, PCA revealed a cline of genetic diversity reflecting a west-to-east geographical distribution from the center of origin in East Africa to the Arabian Peninsula. The extremely low levels of variation observed in the species, as a consequence of the polyploidization event, make the exploitation of diversity within the species for breeding purposes less interesting than in most crop species and stress the need for introgression of new variability from the diploid progenitors.

Four Parent Maize (FPM) Population: Effects of Mating Designs on Linkage Disequilibrium and Mapping Quantitative Traits.

Multiparent advanced generation inter-cross (MAGIC) populations can provide improved genetic mapping resolution by increasing allelic diversity and effective recombination. The Four Parent Maize (FPM; L.) population implemented five different mating designs used in MAGIC and bi-parental populations to compare empirical effects on genetic resolution and power of quantitative trait locus (QTL) detection; the combined population here comprised of 1149 individuals with 118,509 genetic markers. Measurements were recorded for plant height (PH), ear height (EH), days to anthesis (DTA) and silking (DTS) in seven environments, spanning three years. Linkage disequilibrium (LD) analysis of subpopulations indicated MAGIC population designs should incorporate generations of intermating to overcome initial LD increase caused by population admixture in a non-intermated four parent population (4way0sib). A 3- to 4-fold increase in genetic resolution (<0.8) and a 2.5-fold decrease in the extent of LD decay (<0.2) compared to the biparental populations was found for the four parent cross at the third generation of intermating (4way3sib). Power of QTL detection was affected to a greater extent by sample size rather than by mating designs. The FPM power simulations indicated that MAGIC populations have the ability to meet or exceed the mapping power of nested association panels with fewer individuals and diversity inputs. Using association mapping software we identified 2, 5, 7, and 6 QTL for PH, EH, DTA, and DTS, respectively. The FPM population is a valuable resource for quantifying empirical improvements of parent number, intermating, and the number of progeny for QTL linkage mapping.

Genotyping-by-sequencing application on diploid rose and a resulting high-density SNP-based consensus map.

Roses, which have been cultivated for at least 5000 years, are one of the most important ornamental crops in the world. Because of the interspecific nature and high heterozygosity in commercial roses, the genetic resources available for rose are limited. To effectively identify markers associated with QTL controlling important traits, such as disease resistance, abundant markers along the genome and careful phenotyping are required. Utilizing genotyping by sequencing technology and the strawberry genome (Fragaria vesca v2.0.a1) as a reference, we generated thousands of informative single nucleotide polymorphism (SNP) markers. These SNPs along with known bridge simple sequence repeat (SSR) markers allowed us to create the first high-density integrated consensus map for diploid roses. Individual maps were first created for populations J06-20-14-3×"Little Chief" (J14-3×LC), J06-20-14-3×"Vineyard Song" (J14-3×VS) and "Old Blush"×"Red Fairy" (OB×RF) and these maps were linked with 824 SNPs and 13 SSR bridge markers. The anchor SSR markers were used to determine the numbering of the rose linkage groups. The diploid consensus map has seven linkage groups (LGs), a total length of 892.2 cM, and an average distance of 0.25 cM between 3527 markers. By combining three individual populations, the marker density and the reliability of the marker order in the consensus map was improved over a single population map. Extensive synteny between the strawberry and diploid rose genomes was observed. This consensus map will serve as the tool for the discovery of marker-trait associations in rose breeding using pedigree-based analysis. The high level of conservation observed between the strawberry and rose genomes will help further comparative studies within the Rosaceae family and may aid in the identification of candidate genes within QTL regions.

Rust and Thinning Management Effect on Cup Quality and Plant Performance for Two Cultivars of Coffea arabica L.

Beverage quality is a complex attribute of coffee ( Coffea arabica L.). Genotype (G), environment (E), management (M), postharvest processing, and roasting are all involved. However, little is known about how G × M interactions influence beverage quality. We investigated how yield and coffee leaf rust (CLR) disease (caused by Hemileia vastatrix Berk. et Br.) management affect cup quality and plant performance, in two coffee cultivars. Sensory and chemical analyses revealed that 10 of 70 attributes and 18 of 154 chemical volatile compounds were significantly affected by G and M. Remarkably, acetaminophen was found for the first time in roasted coffee and in higher concentrations under more stressful conditions. A principal component analysis described 87% of the variation in quality and plant overall performance. This study is a first step in understanding the complexity of the physiological, metabolic, and molecular changes in coffee production, which will be useful for the improvement of coffee cultivars.