A More Complete Story of the Genetic Bases of Resistance to the Rice Hoja Blanca Virus

Rice hoja blanca is one of the most serious diseases in rice growing areas in tropical Americas. Its causal agent is the Rice hoja blanca virus (RHBV), transmitted by the planthopper Tagosodes orizicolus Müir. Genetic resistance is the most effective and environment-friendly way of controlling the disease. So far, only one major quantitative trait locus (QTL) of Oryza sativa ssp. japonica origin, qHBV4.1, that alters incidence of the virus symptoms in two Colombian cultivars has been reported. This resistance has already started to be broken, stressing the urgent need for diversifying the resistance sources. In the present study we performed a search for new QTLs of O. sativa indica origin associated with RHBV resistance. We used four F2:3 segregating populations derived from indica resistant varieties crossed with a highly susceptible japonica pivot parent. Beside the standard method for measuring disease incidence, we developed a new method based on computer-assisted image processing to determine the affected leaf area (ALA) as a measure of symptoms severity. Based on the disease severity and incidence scores in the F3 families under greenhouse conditions, and SNP genotyping of the F2 individuals, we identified four new indica QTLs for RHBV resistance on rice chromosomes 4, 6 and 11, namely qHBV4.2WAS208, qHBV6.1PTB25, qHBV11.1 and qHBV11.2. We also confirmed the wide-range action of qHBV4.1. Among the five QTLs, qHBV4.1 and qHBV11.1 had the largest effects on incidence and severity, respectively. These results provide a more complete understanding of the genetic bases of RHBV resistance in the cultivated rice gene pool, and can be used to develop marker-aided breeding strategies to improve RHBV resistance. The power of joint- and meta- analyses allowed precise mapping and candidate genes identification, providing the basis for positional cloning of the two major QTLs qHBV4.1 and qHBV11.1.

Identification and verification of grain shape QTLs by SNP array in rice

Grain shape strongly influences the economic value and grain yield of rice. Thus, identifying quantitative trait loci (QTLs) for grain shape has been a longstanding goal in rice genetic research and breeding programs. Single nucleotide polymorphism (SNP) markers are ubiquitous in the rice genome and are more abundant and evenly distributed on the 12 rice chromosomes than traditional markers. An F2 population was genotyped using the RICE6K SNP array to elucidate the mechanisms governing grain shape. Thirty-five QTLs for grain shape were detected on 11 of 12 chromosomes over 2 years. The major QTL cluster qGS7 was detected in both years and displayed strong genetic effects on grain length and width, showing consistency with GL7/GW7. Some minor QTLs were also detected, and the effects of four QTLs on seed size were then validated using BC1F6 populations with residual heterozygous lines in each QTL region. Our findings provide insights into the molecular basis of grain shape as well as additional resources and approaches for producing hybrid high-yield rice varieties.

Development and verification of SSR markers from drought stress-responsive miRNAs in common wild rice

PREMISE: Dongxiang wild rice (Oryza rufipogon Griff., DXWR) is the northernmost common wild rice found in the world, which possesses abundant elite genetic resources. We developed a set of drought stress-responsive microRNA (miRNA)-based single sequence repeat (SSR) markers for DXWR, which will help breed drought stress-resistant rice varieties. METHODS AND RESULTS: Ninety-nine SSR markers were developed from the drought stress-responsive miRNAs of DXWR. The SSR loci were distributed in all 12 rice chromosomes and most were in chromosomes 2 and 6, with di- and trinucleotides being the most abundant repeat motifs. Nine out of ten synthesized SSR markers were displayed high levels of genetic diversity in the genomes of DXWR and 41 modern rice varieties worldwide. The number of alleles per locus ranged from 2 to 6, and the observed and expected heterozygosity ranged from 0.000 to 0.024 and 0.461 to 0.738, respectively. CONCLUSIONS: These SSR markers developed from drought stress-responsive miRNAs in DXWR could be additional tools for elite genes mapping and useful for drought stress-resistant rice breeding.

Iron Biofortification in Rice: An Update on Quantitative Trait Loci and Candidate Genes

Rice is the most versatile model for cereals and also an economically relevant food crop; as a result, it is the most suitable species for molecular characterization of Fe homeostasis and biofortification. Recently there have been significant efforts to dissect genes and quantitative trait loci (QTL) associated with Fe translocation into rice grains; such information is highly useful for Fe biofortification of cereals but very limited in other species, such as maize (Zea mays) and wheat (Triticum aestivum). Given rice’s centrality as a model for Poaceae species, we review the current knowledge on genes playing important roles in Fe transport, accumulation, and distribution in rice grains and QTLs that might explain the variability in Fe concentrations observed in different genotypes. More than 90 Fe QTLs have been identified over the 12 rice chromosomes. From these, 17 were recorded as stable, and 25 harbored Fe-related genes nearby or within the QTL. Among the candidate genes associated with Fe uptake, translocation, and loading into rice grains, we highlight the function of transporters from the YSL and ZIP families; transporters from metal-binding molecules, such as nicotianamine and deoxymugineic acid; vacuolar iron transporters; citrate efflux transporters; and others that were shown to play a role in steps leading to Fe delivery to seeds. Finally, we discuss the application of these QTLs and genes in genomics assisted breeding for fast-tracking Fe biofortification in rice and other cereals in the near future.

High-resolution mapping of the quantitative trait locus (QTLs) conferring resistance to false smut disease in rice

Decoding the genetic mechanisms underlying disease resistance is of great importance for crop improvement. Rice false smut (RFS) is a major fungal disease caused by Ustilaginoidea virens that hampers the grain quality and yield of rice worldwide. It causes 2.8-49% global yield loss depending upon disease severity and varieties grown. In India, the severity of yield loss ranged from 2-75%. Keeping the economic importance of this disease, identification of the genes/QTLs governing disease resistance is of prime importance for the development of the linked markers and cloning of the genes. Here, we report mapping of QTLs using a recombinant inbred line (RIL) population derived from a cross between resistant line, RYT2668, and a highly susceptible variety, PR116. The population was evaluated for rice false smut disease under field conditions for three cropping seasons 2013, 2015, and 2016. A total of seven QTLs were mapped on rice chromosomes 2, 4, 5, 7, and 9 of rice using 2326 single nucleotide polymorphism (SNP) markers. Among them, a novel QTL qRFSr9.1 affecting total smut ball (TSB)/panicle on chromosome 9 exhibited the largest phenotypic effect. The prediction of putative candidate genes within the qRFSr9.1 spanned in 994.1Kb revealed four NBS-LRR domain-containing disease resistance proteins. We identified SNPs/Indels associated with the disease resistance which could be used for accelerating breeding programs using marker-assisted selection. In summary, our findings mark the ‘hot-spot’ region on rice chromosomes along with the identification of disease resistance genes in conferring resistance to the rice false smut disease.

In Silico Identification of QTL-Based Polymorphic Genes as Salt-Responsive Potential Candidates through Mapping with Two Reference Genomes in Rice

Recent advances in next generation sequencing have created opportunities to directly identify genetic loci and candidate genes for abiotic stress responses in plants. With the objective of identifying candidate genes within the previously identified QTL-hotspots, the whole genomes of two divergent cultivars for salt responses, namely At 354 and Bg 352, were re-sequenced using Illumina Hiseq 2500 100PE platform and mapped to Nipponbare and R498 genomes. The sequencing results revealed approximately 2.4 million SNPs and 0.2 million InDels with reference to Nipponbare while 1.3 million and 0.07 million with reference to R498 in two parents. In total, 32,914 genes were reported across all rice chromosomes of this study. Gene mining within QTL hotspots revealed 1236 genes, out of which 106 genes were related to abiotic stress. In addition, 27 abiotic stress-related genes were identified in non-QTL regions. Altogether, 32 genes were identified as potential genes containing polymorphic non-synonymous SNPs or InDels between two parents. Out of 10 genes detected with InDels, tolerant haplotypes of Os01g0581400, Os10g0107000, Os11g0655900, Os12g0622500, and Os12g0624200 were found in the known salinity tolerant donor varieties. Our findings on different haplotypes would be useful in developing resilient rice varieties for abiotic stress by haplotype-based breeding studies.

Identification and Validation of Quantitative Trait Loci for Grain Number in Rice (Oryza sativa L.)

Grains number is one of the most important agronomic traits in the determination of rice productivity. To explore the underlying genetic basis of grain number in rice, quantitative trait locus (QTL) analysis was performed using three recombinant inbred line populations derived from indica rice crosses of Teqing/IRBB lines, Zhenshan 97/Milyang 46, and Xieqingzao/Milyang 46, respectively. A total of 58 QTLs distributed on all 12 rice chromosomes were identified, including 22 for number of grains per panicle (NGP), 17 for number of spikelets per panicle, and 19 for spikelet fertility. The individual QTL counted for 1.5 to 22.1% of phenotypic variation. Among them, 15 QTLs shared by two or three populations and eight QTLs showed large effects with R2 larger than 10%. Furthermore, three QTLs with minor effects for NGP, qNGP5.5, qNGP9.1, and qNGP12.1, were detected and validated by eliminating the segregation of major-effect QTL using four residual heterozygote-derived populations. These results not only enrich our understanding of the mechanism of grain number, but also provide a foundation for cloning and selecting candidate for marker-assisted selection breeding in rice.

Application of SV markers developed from Dongxiang common wild rice in analysis of cultivated rice

Dongxiang common wild rice (Oryza rufipogon Griff., DXWR) is an important genetic resource for the improvement of cultivated rice. For the past three decades, great achievements have been made in the field of molecular marker development. Although structural variations (SVs) had been studied between DXWR and Nipponbare (Oryza sativa L. ssp. japonica), the development and application of SV markers in DXWR has not been reported. In this study, based on the genome-wide SV loci, we developed and synthesized a total of 195 SV markers that were evenly distributed across the 12 rice chromosomes. Then, these markers were tested for their stabilities and polymorphisms. Of these 195 markers, 147 (75.4%) were successfully amplified and displayed abundant polymorphisms between DXWR and Nipponbare. Meanwhile, through the genotyping of 20 rice varieties from 13 countries and areas, we concluded that these SV markers have a wide application prospect in the analysis of cultivated rice. Therefore, these molecular markers greatly enrich the number of markers available for DXWR, which will facilitate genomic research and molecular breeding for this important and endangered germplasm resource.

Genetic Diversity Analysis of 53 Indonesian Rice Genotypes using 6K Single Nucleotide Polymorphism Markers

<p>Indonesia is rich in rice genetic resources, however, only a small number has been used in variety improvement programs. This study aimed to determine the genetic diversity of Indonesian rice varieties using 6K SNP markers. The study was conducted at ICABIOGRAD for DNA isolation and IRRI for SNP marker analysis. Genetic materials were 53 rice genotypes consisting of 49 varieties and 4 check genotypes. SNP markers used were 6K loci. Results showed that among the markers analyzed, only 4,606 SNPs (76.77%) were successfully read. The SNP markers covered all twelve rice chromosomes of 945,178.27 bp. The most common allele observed was GG, whereas the least allele was TG. Dendrograms of the 53 rice varieties analyzed with 4,606 SNPs demonstrated several small groups containing genotypic mixtures between indica and japonica rice, and no groups were found to contain firmly indica or japonica type. Structure analysis (K = 2) with value of 0.8 showed that the 53 rice varieties were divided into several groups and each group consisted of 4 japonica, 2 tropical japonica, 46 indica, and 1 aus rice type, respectively. IR64 and Ciherang proved to have an indica genome, while Rojolele has japonica one. Dupa and Hawara Bunar, usually grouped into tropical japonica rice, were classified as indica type, and Hawara Bunar has perfectly 100% indica type. The results of this study indicated that rice classification (indica-japonica) which is usually classified based only on morphological characters, e.g. grain and leaf shapes, is not enough and classification based on SNP markers should be considered for that purpose.</p>

Evaluasi Molekuler dan Lapangan terhadap Galur-galur Padi Berumur Genjah dan Produktivitas Tinggi Turunan Ciherang

Improving Ciherang rice variety for earliness and higher productivity was obtained using Marker Assisted Backcrossing (MAB). Among 78 lines of BC2F4 generation of Ciherang x Nipponbare were obtained from greenhouse and molekuler analysis selection. Field evaluations were conducted at two locations, namely field station of Sukamandi (Indonesian Center for Rice Research, West Java), and field station of Maros (Indonesian Cereals Research Institute, South Sulawesi). Molecular analysis was performed using markers RM1362 and RM7601 which are flanking markers for the QTL region for Hd2 gene, located on chromosome 7. Flowering time and grain yield were evaluated among BC2 F4 lines. Five lines flowered earlier and yielded higher than Ciherang were selected for background analysis using microsatellites covering the rice chromosomes. The earliest flowering line was BC2F4 CihNip-60 (at 74 days, 4 days earlier than that of Ciherang), and the highest yield (which flowered earlier than Ciherang) was BC2 F4 CihNip-23, namely (2.20 t/ha higher than Ciherang). A total of 74 (95%) BC2 F4 lines showed QTL region of Hd2 gene in homozygous condition. This showed that molecular selection from F1 generation of BC2 F4 was able to identify homozygous gens and almost free of contaminant plant. Genetic backgrounds of the five BC2 F2 selected lines were similar to that of Ciherang. Based on the agronomic and molecular marker, twenty five lines of BC2 F4 flowered earlier than did Ciherang and yielded higher than did Ciherang. These lines should be further evaluated for their stability