A first look at the ability to use genomic prediction for improving the ratooning ability of sugarcane.

The sugarcane ratooning ability (RA) is the most important target trait for breeders seeking to enhance the profitability of sugarcane production by reducing the planting cost. Understanding the genetics governing the RA could help breeders by identifying molecular markers that could be used for genomics-assisted breeding (GAB). A replicated field trial was conducted for three crop cycles (plant cane, first ratoon, and second ratoon) using 432 sugarcane clones and used for conducting genome-wide association and genomic prediction of five sugar and yield component traits of the RA. The RA traits for economic index (EI), stalk population (SP), stalk weight (SW), tonns of cane per hectare (TCH), and tonns of sucrose per hectare (TSH) were estimated from the yield and sugar data. A total of six putative quantitative trait loci and eight nonredundant single-nucleotide polymorphism (SNP) markers were associated with all five tested RA traits and appear to be unique. Seven putative candidate genes were colocated with significant SNPs associated with the five RA traits. The genomic prediction accuracies for those tested traits were moderate and ranged from 0.21 to 0.36. However, the models fitting fixed effects for the most significant associated markers for each respective trait did not give any advantages over the standard models without fixed effects. As a result of this study, more robust markers could be used in the future for clone selection in sugarcane, potentially helping resolve the genetic control of the RA in sugarcane.

Nanopore sequencing data and structural variants identified in Prunus avium seedlings derived through mutagenesis.

DNA from four sweet cherry seedlings derived from gamma-irradiated female parents was sequenced via nanopore technology (Oxford Nanopore MinION). Total data yield was 8.07 Gb, ranging from 0.92 to 3.36 Gb per sample, with the average length of mapped reads ranging from 22 Kbp-24 Kbp. Sequence data was then analysed to identify and characterize variants using a published sweet cherry reference genome. Small and medium-sized indels (55-135 bp), as well as structural variants, including several large indels and complex variants were detected. Of these, 20 variants were localized within protein-coding gene sequences, including those encoding a putative F-box protein, an ADP-ribose glyxohydrolase protein, a predicted 26S protease regulatory subunit, an E3 ubiquitin protein ligase, a UDP-galactose/UDP-blucose transporter, an alpha/beta hydrolase domain-containing protein, a rhodanese-like domain-containing protein, a cytochrome p450 protein, phosphoinositide phosphatase, cysteine synthase-like, phosphoenolpyruvate carboxylase 4, and several uncharacterized proteins. These variations could have functional and phenotypic consequences that are useful in basic research and breeding.

Detection of Breeding-Relevant Fruit Cracking and Fruit Firmness Quantitative Trait Loci in Sweet Cherry via Pedigree-Based and Genome-Wide Association Approaches.

Breeding for decreased fruit cracking incidence and increased fruit firmness in sweet cherry creates an attractive alternative to variable results from cultural management practices. DNA-informed breeding increases its efficiency, yet upstream research is needed to identify the genomic regions associated with the trait variation of a breeding-relevant magnitude, as well as to identify the parental sources of favorable alleles. The objectives of this research were to identify the quantitative trait loci (QTLs) associated with fruit cracking incidence and firmness, estimate the effects of single nucleotide polymorphism (SNP) haplotypes at the detected QTLs, and identify the ancestral source(s) of functional haplotypes. Fruit cracking incidence and firmness were evaluated for multiple years on 259 unselected seedlings representing 22 important breeding parents. Phenotypic data, in conjunction with genome-wide genotypic data from the RosBREED cherry 6K SNP array, were used in the QTL analysis performed via Pedigree-Based Analysis using the FlexQTL™ software, supplemented by a Genome-Wide Association Study using the BLINK software. Haplotype analysis was conducted on the QTLs to identify the functional SNP haplotypes and estimate their phenotypic effects, and the haplotypes were tracked through the pedigree. Four QTLs (two per trait) were consistent across the years and/or both analysis methods and validated the previously reported QTLs. qCrack-LG1.1m (the label given to a consistent QTL for cracking incidence on chromosome 1) explained 2-15.1% of the phenotypic variance, while qCrack-LG5.1m, qFirm-LG1.2m, and qFirm-LG3.2m explained 7.6-13.8, 8.8-21.8, and 1.7-10.1% of the phenotypic variance, respectively. At each QTL, at least two SNP haplotypes had significant effects and were considered putative functional SNP haplotypes. Putative low-cracking SNP haplotypes were tracked to an unnamed parent of 'Emperor Francis' and 'Schmidt' and unnamed parents of 'Napoleon' and 'Hedelfingen,' among others, and putative high-firmness haplotypes were tracked to an unnamed parent of 'Emperor Francis' and 'Schmidt,' an unnamed grandparent of 'Black Republican,' 'Rube,' and an unknown parent of 'Napoleon.' These four stable QTLs can now be targeted for DNA test development, with the goal of translating information discovered here into usable tools to aid in breeding decisions.

Experimental evaluation of genomic selection prediction for rust resistance in sugarcane.

The total sugarcane (Saccharum L.) production has increased worldwide; however, the rate of growth is lower compared with other major crops, mainly due to a plateauing of genetic gain. Genomic selection (GS) has proven to substantially increase the rate of genetic gain in many crops. To investigate the utility of GS in future sugarcane breeding, a field trial was conducted using 432 sugarcane clones using an augmented design with two replications. Two major diseases in sugarcane, brown and orange rust (BR and OR), were screened artificially using whorl inoculation method in the field over two crop cycles. The genotypic data were generated through target enrichment sequencing technologies. After filtering, a set of 8,825 single nucleotide polymorphic markers were used to assess the prediction accuracy of multiple GS models. Using fivefold cross-validation, we observed GS prediction accuracies for BR and OR that ranged from 0.28 to 0.43 and 0.13 to 0.29, respectively, across two crop cycles and combined cycles. The prediction ability further improved by including a known major gene for resistance to BR as a fixed effect in the GS model. It also substantially reduced the minimum number of markers and training population size required for GS. The nonparametric GS models outperformed the parametric GS suggesting that nonadditive genetic effects could contribute genomic sources underlying BR and OR. This study demonstrated that GS could potentially predict the genomic estimated breeding value for selecting the desired germplasm for sugarcane breeding for disease resistance.

Identification of molecular markers associated with Verticillium wilt resistance in alfalfa (Medicago sativa L.) using high-resolution melting.

Verticillium wilt, caused by the soilborne fungus, Verticillium alfalfae, is one of the most serious diseases of alfalfa (Medicago sativa L.) worldwide. To identify loci associated with resistance to Verticillium wilt, a bulk segregant analysis was conducted in susceptible or resistant pools constructed from 13 synthetic alfalfa populations, followed by association mapping in two F1 populations consisted of 352 individuals. Simple sequence repeat (SSR) and single nucleotide polymorphism (SNP) markers were used for genotyping. Phenotyping was done by manual inoculation of the pathogen to replicated cloned plants of each individual and disease severity was scored using a standard scale. Marker-trait association was analyzed by TASSEL. Seventeen SNP markers significantly associated with Verticillium wilt resistance were identified and they were located on chromosomes 1, 2, 4, 7 and 8. SNP markers identified on chromosomes 2, 4 and 7 co-locate with regions of Verticillium wilt resistance loci reported in M. truncatula. Additional markers identified on chromosomes 1 and 8 located the regions where no Verticillium resistance locus has been reported. This study highlights the value of SNP genotyping by high resolution melting to identify the disease resistance loci in tetraploid alfalfa. With further validation, the markers identified in this study could be used for improving resistance to Verticillium wilt in alfalfa breeding programs.

Species-specific detection and identification of fusarium species complex, the causal agent of sugarcane pokkah boeng in China.

BACKGROUND: Pokkah boeng disease caused by the Fusarium species complex results in significant yield losses in sugarcane. Thus, the rapid and accurate detection and identification of the pathogen is urgently required to manage and prevent the spreading of sugarcane pokkah boeng. METHODS: A total of 101 isolates were recovered from the pokkah boeng samples collected from five major sugarcane production areas in China throughout 2012 and 2013. The causal pathogen was identified by morphological observation, pathogenicity test, and phylogenetic analysis based on the fungus-conserved rDNA-ITS. Species-specific TaqMan real-time PCR and conventional PCR methods were developed for rapid and accurate detection of the causal agent of sugarcane pokkah boeng. The specificity and sensitivity of PCR assay were also evaluated on a total of 84 isolates of Fusarium from China and several isolates from other fungal pathogens of Sporisorium scitamineum and Phoma sp. and sugarcane endophyte of Acremonium sp. RESULT: Two Fusarium species (F. verticillioides and F. proliferatum) that caused sugarcane pokahh boeng were identified by morphological observation, pathogenicity test, and phylogenetic analysis. Species-specific TaqMan PCR and conventional PCR were designed and optimized to target their rDNA-ITS regions. The sensitivity of the TaqMan PCR was approximately 10 pg of fungal DNA input, which was 1,000-fold over conventional PCR, and successfully detected pokkah boeng in the field-grown sugarcane. CONCLUSIONS/SIGNIFICANCE: This study was the first to identify two species, F. verticillioides and F. proliferatum, that were causal pathogens of sugarcane pokkah boeng in China. It also described the development of a species-specific PCR assay to detect and confirm these pathogens in sugarcane plants from mainland China. This method will be very useful for a broad range of research endeavors as well as the regulatory response and management of sugarcane pokkah boeng.

Relationship of Resistance to Meloidogyne chitwoodi (race 2) and M. hapla in Alfalfa.

In the Pacific Northwest, alfalfa (Medicago sativa) is host to two species of root-knot nematodes, including race 2 of the Columbia root-knot nematode (Meloidogyne chitwoodi) and the northern root-knot nematode (Meloidogyne hapla). In addition to the damage caused to alfalfa itself by M. hapla, alfalfa's host status to both species leaves large numbers of nematodes available to damage rotation crops, of which potato is the most important. A nematode-resistant alfalfa germplasm release, W12SR2W1, was challenged with both nematode species, to determine the correlation, if any, of resistance to nematode reproduction. Thirty genotypes were screened in replicated tests with M. chitwoodi race 2 or M. hapla, and the reproductive factor (RF) was calculated. The distribution of natural log-transformed RF values was skewed for both nematode species, but more particularly for M. chitwoodi race 2, where more than half the genotypes screened were non-hosts. Approximately 30 percent of genotypes were non-hosts or very poor hosts of M. hapla, but RF values for M. hapla on susceptible genotypes were generally much higher than RF values for genotypes susceptible to M. chitwoodi race 2. The Spearman rank correlation was positive (0.52) and significant (p-value = 0.003), indicating there is some relationship between resistance to these two species of root-knot nematode in alfalfa. However the relationship is not strong enough to suggest genetic loci for resistance are identical, or closely linked. Breeding for resistance or immunity will require screening with each species separately, or with different DNA markers if marker-assisted breeding is pursued. A number of genotypes were identified which are non-hosts to both species. These plants will be intercrossed to develop a non-host germplasm.

Candidate gene database and transcript map for peach, a model species for fruit trees.

Peach (Prunus persica) is a model species for the Rosaceae, which includes a number of economically important fruit tree species. To develop an extensive Prunus expressed sequence tag (EST) database for identifying and cloning the genes important to fruit and tree development, we generated 9,984 high-quality ESTs from a peach cDNA library of developing fruit mesocarp. After assembly and annotation, a putative peach unigene set consisting of 3,842 ESTs was defined. Gene ontology (GO) classification was assigned based on the annotation of the single "best hit" match against the Swiss-Prot database. No significant homology could be found in the GenBank nr databases for 24.3% of the sequences. Using core markers from the general Prunus genetic map, we anchored bacterial artificial chromosome (BAC) clones on the genetic map, thereby providing a framework for the construction of a physical and transcript map. A transcript map was developed by hybridizing 1,236 ESTs from the putative peach unigene set and an additional 68 peach cDNA clones against the peach BAC library. Hybridizing ESTs to genetically anchored BACs immediately localized 11.2% of the ESTs on the genetic map. ESTs showed a clustering of expressed genes in defined regions of the linkage groups. [The data were built into a regularly updated Genome Database for Rosaceae (GDR), available at (http://www.genome.clemson.edu/gdr/).].