Two recombinant inbred (RI) populations having 194 and 222 lines each, derived, respectively, from a highly heterotic inter- (IJ) and intrasubspecific (II) hybrid, were backcrossed to their respective parents. The RI and two backcross populations along with F₁ and its two parents of each hybrid were evaluated for nine important traits, including grain yield and eight other yield-related traits. A total of 76 quantitative trait loci (QTL) for the IJ hybrid and 41 QTL for the II hybrid were detected in the RI population, midparent heterosis of two backcross populations, and two independent sets of data by summation (L₁ + L₂) and by subtraction (L₁ − L₂) of two backcross populations (L₁ and L₂). The variance explained by each QTL ranged from 2.6 to 58.3%. In the IJ hybrid, 42% (32) of the QTL showed an additive effect, 32% (24) a partial-to-complete dominant effect, and 26% (20) an overdominant effect. In the II hybrid, 32% (13) of the QTL demonstrated an additive effect, 29% (12) a partial-to-complete dominant effect, and 39% (16) an overdominant effect. There were 195 digenic interactions detected in the IJ hybrid and 328 in the II hybrid. The variance explained by each digenic interaction ranged from 2.0 to 14.9%. These results suggest that the heterosis in these two hybrids is attributable to the orchestrated outcome of partial-to-complete dominance, overdominance, and epistasis.

Background: Amorphophallus is a genus of perennial plants widely distributed in the tropics or subtropics of West Africa and South Asia. Its corms contain a high level of water-soluble glucomannan; therefore, it has long been used as a medicinal herb and food source. Genetic studies of Amorphophallus have been hindered by a lack of genetic markers. A large number of molecular markers are required for genetic diversity study and improving disease resistance in Amorphophallus. Here, we report large scale of transcriptome sequencing of two species: Amorphophallus konjac and Amorphophallus bulbifer using deep sequencing technology, and microsatellite (SSR) markers were identified based on these transcriptome sequences. Results: cDNAs of A. konjac and A. bulbifer were sequenced using Illumina HiSeq™ 2000 sequencing technology. A total of 135,822 non-redundant unigenes were assembled from about 9.66 gigabases, and 19,596 SSRs were identified in 16,027 non-redundant unigenes. Di-nucleotide SSRs were the most abundant motif (61.6%), followed by tri- (30.3%), tetra- (5.6%), penta- (1.5%), and hexa-nucleotides (1%) repeats. The top di- and tri-nucleotide repeat motifs included AG/CT (45.2%) and AGG/CCT (7.1%), respectively. A total of 10,754 primer pairs were designed for marker development. Of these, 320 primers were synthesized and used for validation of amplification and assessment of polymorphisms in 25 individual plants. The total of 275 primer pairs yielded PCR amplification products, of which 205 were polymorphic. The number of alleles ranged from 2 to 14 and the polymorphism information content valued ranged from 0.10 to 0.90. Genetic diversity analysis was done using 177 highly polymorphic SSR markers. A phenogram based on Jaccard’s similarity coefficients was constructed, which showed a distinct cluster of 25 Amorphophallus individuals. Conclusion: A total of 10,754 SSR markers have been identified in Amorphophallus using transcriptome sequencing. One hundred and seventy-seven polymorphic markers were successfully validated in 25 individuals. The large number of genetic markers developed in the present study should contribute greatly to research into genetic diversity and germplasm characterization in Amorphophallus.

Hybrid breeding is an effective tool to improve yield in rice, while parental selection remains the key and difficult issue. Genomic selection (GS) provides opportunities to predict the performance of hybrids before phenotypes are measured. However, the application of GS is influenced by several genetic and statistical factors. Here, we used a rice North Carolina II (NC II) population constructed by crossing 115 rice varieties with five male sterile lines as a model to evaluate effects of statistical methods, heritability, marker density and training population size on prediction for hybrid performance. From the comparison of six GS methods, we found that predictabilities for different methods are significantly different, with genomic best linear unbiased prediction (GBLUP) and least absolute shrinkage and selection operation (LASSO) being the best, support vector machine (SVM) and partial least square (PLS) being the worst. The marker density has lower influence on predicting rice hybrid performance compared with the size of training population. Additionally, we used the 575 (115 × 5) hybrid rice as a training population to predict eight agronomic traits of all hybrids derived from 120 (115 + 5) rice varieties each mating with 3023 rice accessions from the 3000 rice genomes project (3 K RGP). Of the 362,760 potential hybrids, selection of the top 100 predicted hybrids would lead to 35.5%, 23.25%, 30.21%, 42.87%, 61.80%, 75.83%, 19.24% and 36.12% increase in grain yield per plant, thousand-grain weight, panicle number per plant, plant height, secondary branch number, grain number per panicle, panicle length and primary branch number, respectively. This study evaluated the factors affecting predictabilities for hybrid prediction and demonstrated the implementation of GS to predict hybrid performance of rice. Our results suggest that GS could enable the rapid selection of superior hybrids, thus increasing the efficiency of rice hybrid breeding.

Miscanthus is not only a perennial fiber biomass crop, but also valuable breeding resource for its low-nutrient requirements, photosynthetic efficiency and strong adaptability to environment. In the present study, the codon usage patterns of five different Miscanthus plants and other two related species were systematically analyzed. The results indicated that the cp genomes of the seven representative species were preference to A/T bases and A/T-ending codons. In addition, 21 common high-frequency codons and 4–11 optimal codons were detected in the seven chloroplast genomes. The results of ENc-plot, PR2-plot and neutrality analysis revealed the codon usage patterns of the seven chloroplast genomes are influenced by multiple factors, in which nature selection is the main influencing factor. Comparative analysis of the codon usage frequencies between the seven representative species and four model organisms suggested that Arabidopsis thaliana, Populus trichocarpa and Saccharomyces cerevisiae could be considered as preferential appropriate exogenous expression receptors. These results might not only provide important reference information for evolutionary analysis, but also shed light on the way to improve the expression efficiency of exogenous gene in transgenic research based on codon optimization.

Combining ability effects are very effective genetic parameters in deciding the next phase of breeding programs. Although some breeding strategies on the basis of evaluating combining ability have been utilized extensively in hybrid breeding, little is known about the genetic basis of combining ability. Combining ability is a complex trait that is controlled by polygenes. With the advent and development of molecular markers, it is feasible to evaluate the genetic bases of combining ability and heterosis of elite rice hybrids through QTL analysis. In the present study, we first developed a QTL-mapping method for dissecting combining ability and heterosis of agronomic traits. With three testcross populations and a BCRIL population in rice, biometric and QTL analyses were conducted for ten agronomic traits. The significance of general combining ability and special combining ability for most of the traits indicated the importance of both additive and non-additive effects on expression levels. A large number of additive effect QTLs associated with performance per se of BCRIL and general combining ability, and dominant effect QTLs associated with special combining ability and heterosis were identified for the ten traits. The combining ability of agronomic traits could be analyzed by the QTL mapping method. The characteristics revealed by the QTLs for combining ability of agronomic traits were similar with those by multitudinous QTLs for agronomic traits with performance per se of BCRIL. Several QTLs (1–6 in this study) were identified for each trait for combining ability. It demonstrated that some of the QTLs were pleiotropic or linked tightly with each other. The identification of QTLs responsible for combining ability and heterosis in the present study provides valuable information for dissecting genetic basis of combining ability.