Microsatellite diversity at 18 loci was analysed in 94 individual plants of 10 wild barley, Hordeum spontaneum (C. Koch) Thell., populations sampled from Israel across a southward transect of increasing aridity. Allelic distribution in populations was not distributed randomly. Estimates of mean gene diversity were highest in stressful arid-hot environments. Sixty-four per cent of the genetic variation was partitioned within populations and 36% between populations. Associations between ecogeographical variables and gene diversity, H(e), were established in nine microsatellite loci. By employing principle component analysis we reduced the number of ecogeographical variables to three principal components including water factors, temperature and geography. At three loci, stepwise multiple regression analysis explained significantly the gene diversity by a single principal component (water factors). Based on these observations it is suggested that simple sequence repeats are not necessarily biologically neutral.

BackgroundRice is one of the major staple foods in the world, especially in the developing countries of Asia. Its consumption as a dietary source is also increasing in Africa. To meet the demand for rice to feed the increasing human population, increasing rice yield is essential. Improving the genetic yield potential of rice is one ideal solution. It is imperative to introduce the identified yield-enhancing gene(s) into modern rice cultivars for the rapid improvement of yield potential through marker-assisted breeding.ResultsWe report the development of PCR-gel-based markers for eight yield-related functional genes (Gn1a, OsSPL14, SCM2, Ghd7, DEP1, SPIKE, GS5, and TGW6) to introduce yield-positive alleles from the donor lines. Six rice cultivars, including three each of donor and recipient lines, respectively, were sequenced by next-generation whole-genome sequencing to detect DNA polymorphisms between the genotypes. Additionally, PCR products containing functional nucleotide polymorphism (FNP) or putative FNPs for yield-related genes were sequenced. DNA polymorphisms discriminating yield-positive alleles and non-target alleles for each gene were selected through sequence analysis and the allele-specific PCR-gel-based markers were developed. The markers were validated with our intermediate breeding lines produced from crosses between the donors and 12 elite indica rice cultivars as recipients. Automated capillary electrophoresis was tested and fluorescence-labeled SNP genotyping markers (Fluidigm SNP genotyping platform) for Gn1a, OsSPL14, Ghd7, GS5, and GS3 genes were developed for high-throughput genotyping.ConclusionsThe SNP/indel markers linked to yield related genes functioned properly in our marker-assisted breeding program with identified high yield potential lines. These markers can be utilized in local favorite rice cultivars for yield enhancement. The marker designing strategy using both next generation sequencing and Sanger sequencing methods can be used for suitable marker development of other genes associated with useful agronomic traits.Electronic supplementary materialThe online version of this article (doi:10.1186/s12284-016-0084-7) contains supplementary material, which is available to authorized users.

Rice yield potential has been stagnant since the Green Revolution in the late 1960s, especially in tropical rice cultivars. We evaluated the effect of two major genes that regulate grain number, Gn1a/OsCKX2 and IPA1/WFP/OsSPL14, in elite indica cultivar backgrounds. The yield-positive Gn1a-type 3 and OsSPL14WFP alleles were introgressed respectively through marker-assisted selection (MAS). The grain numbers per panicle (GNPP) were compared between the recipient allele and the donor allele groups using segregating plants in BC3F2 and BC3F3 generations. There was no significant difference in GNPP between the two Gn1a alleles, suggesting that the Gn1a-type 3 allele was not effective in indica cultivars. However, the OsSPL14WFP allele dramatically increased GNPP by 10.6–59.3% in all four different backgrounds across cropping seasons and generations, indicating that this allele provides strong genetic gain to elite indica cultivars. Eventually, five high-yielding breeding lines were bred using the OsSPL14WFP allele by MAS with a conventional breeding approach that showed increased grain yield by 28.4–83.5% (7.87–12.89 t/ha) vis-à-vis the recipient cultivars and exhibited higher yield (~64.7%) than the top-yielding check cultivar, IRRI 156 (7.82 t/ha). We demonstrated a strong possibility to increase the genetic yield potential of indica rice varieties through allele mining and its application.

The genetic diversity produced by the amplified fragment length polymorphism (AFLP) method was studied in 94 genotypes of wild barley, Hordeum spontaneum (C. Koch) Thell., originating from ten ecologically and geographically different locations in Israel. Eight primer pairs produced 204 discernible loci of which 189 (93%) were polymorphic. Each genotype had a unique banding profile and the genetic similarity coefficient varied between 0.74 and 0.98. The phenogram generated from these similarities by the UPGMA method did not group genotypes strictly according to their geographical origin, which pattern was also seen in the principal coordinate (PCO) plot. Genetic diversity was larger within (69%) than among (31%) populations. Associations between ecogeographical variables and the mean gene diversity were found at one primer pair. The results are discussed and compared with data obtained by the simple sequence repeat (SSR) method.

The holistic understanding derived from integrating grain quality and sensory research outcomes in breeding high-quality rice in the light of post-genomics resources has been synthesized. Acceptance of new rice genotypes by producers and consumers hinges not only on their potential for higher yield but recent emphasis has also been on premium-value genotypes that have the ability to satisfy consumer preferences for grain quality. This review article provides insights into how to link grain quality attributes and sensory perception to support breeding superior rice varieties. Recent advances in quality profiling and omics technologies have provided efficient approaches to identify the key genes and biochemical markers involved in rice quality traits. Emphasis has been given to the upcoming area of holistic understanding of grain quality and attributes derived from sensory evaluation to leverage integrative gene discovery strategies that enable breeding programs to efficiently tap the huge genetic diversity in rice for novel genes that enhance rice food quality.