Wide adoption of direct-seeded rice practices has been hindered by poorly leveled fields, heavy rainfall and poor drainage, which cause accumulation of water in the fields shortly after sowing, leading to poor crop establishment. This is due to the inability of most rice varieties to germinate and reach the water surface under complete submergence. Hence, tolerance of anaerobic conditions during germination is an essential trait for direct-seeded rice cultivation in both rainfed and irrigated ecosystems. A QTL study was conducted to unravel the genetic basis of tolerance of anaerobic conditions during germination using a population derived from a cross between IR42, a susceptible variety, and Ma-Zhan Red, a tolerant landrace from China. Phenotypic data was collected based on the survival rates of the seedlings at 21 days after sowing of dry seeds under 10 cm of water. QTL analysis of the mapping population consisting of 175 F2:3 families genotyped with 118 SSR markers identified six significant QTLs on chromosomes 2, 5, 6, and 7, and in all cases the tolerant alleles were contributed by Ma-Zhan Red. The largest QTL on chromosome 7, having a LOD score of 14.5 and an R (2) of 31.7 %, was confirmed using a BC2F3 population. The QTLs detected in this study provide promising targets for further genetic characterization and for use in marker-assisted selection to rapidly develop varieties with improved tolerance to anaerobic condition during germination. Ultimately, this trait can be combined with other abiotic stress tolerance QTLs to provide resilient varieties for direct-seeded systems.

Single nucleotide polymorphisms (SNPs) are highly abundant, amendable to high-throughput genotyping, and useful for a number of breeding and genetics applications in crops. SNP frequencies vary depending on the species and populations under study, and therefore target SNPs need to be carefully selected to be informative for each application. While multiple SNP genotyping systems are available for rice (Oryza sativa L. and its relatives), they vary in their informativeness, cost, marker density, speed, flexibility, and data quality. In this study, we report the development and performance of the Cornell-IR LD Rice Array (C7AIR), a second-generation SNP array containing 7,098 markers that improves upon the previously released C6AIR. The C7AIR is designed to detect genome-wide polymorphisms within and between subpopulations of O. sativa, as well as O. glaberrima, O. rufipogon and O. nivara. The C7AIR combines top-performing SNPs from several previous rice arrays, including 4,007 SNPs from the C6AIR, 2,056 SNPs from the High Density Rice Array (HDRA), 910 SNPs from the 384-SNP GoldenGate sets, 189 SNPs from the 44K array selected to add information content for elite U.S. tropical japonica rice varieties, and 8 traitspecific SNPs. To demonstrate its utility, we carried out a genome-wide association analysis for plant height, employing the C7AIR across a diversity panel of 189 rice accessions and identified 20 QTLs contributing to plant height. The C7AIR SNP chip has so far been used for genotyping >10,000 rice samples. It successfully differentiates the five subpopulations of Oryza sativa, identifies introgressions from wild and exotic relatives, and is useful for quantitative trait loci (QTL) and association mapping in diverse materials. Moreover, data from the

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The increased severity and frequency of flooding is causing greater yield reductions in most rice-growing areas. To address this, popular cultivars were improved through introgression of SUB1, an FR13A-derived QTL conferring submergence tolerance at the vegetative stage, using marker-assisted backcrossing (MABC). Ciherang-Sub1, one of these improved near isogenic lines (NILs), showed significantly higher tolerance compared to the original cultivar while retaining its desirable agronomic qualities. However, due to the current shift to direct seeding, seed germination may also be adversely affected by flooding; thus the addition of major QTLs which can confer anaerobic germination (AG) tolerance will be highly beneficial. The AG tolerance QTL, qAG-9-2, also referred to as AG1, derived from Khao Hlan On, a Myanmar landrace, has been introgressed into the elite cultivar IR64 to produce IR64-AG1. This research focused on the transfer of AG1 to Ciherang-Sub1 via MABC, using IR64-AG1, a closely-related donor. Introgression of AG1 and recovery of the Ciherang genome was done in two backcross generations followed by one generation of selfing. The use of a closely-related donor shortened the development period to two years which could have been further reduced if a larger BC1F1 population had been used. Phenotypic evaluation showed that introgression of AG1 significantly increased AG tolerance compared to Ciherang-Sub1, and that the newly developed Ciherang-Sub1+AG1 retained the submergence tolerance from SUB1. The approach is very promising for faster development of improved lines using closely-related cultivars or improved lines as donors for introducing key traits.

Background While a multitude of genotyping platforms have been developed for rice, the majority of them have not been optimized for breeding where cost, turnaround time, throughput and ease of use, relative to density and informativeness are critical parameters of their utility. With that in mind we report the development of the 1K-Rice Custom Amplicon , or 1k-RiCA, a robust custom sequencing-based amplicon panel of ~ 1000-SNPs that are uniformly distributed across the rice genome, designed to be highly informative within indica rice breeding pools, and tailored for genomic prediction in elite indica rice breeding programs. Results Empirical validation tests performed on the 1k-RiCA showed average marker call rates of 95% with marker repeatability and concordance rates of 99%. These technical properties were not affected when two common DNA extraction protocols were used. The average distance between SNPs in the 1k-RiCA was 1.5 cM, similar to the theoretical distance which would be expected between 1,000 uniformly distributed markers across the rice genome. The average minor allele frequencies on a panel of indica lines was 0.36 and polymorphic SNPs estimated on pairwise comparisons between indica by indica accessions and indica by japonica accessions were on average 430 and 450 respectively. The specific design parameters of the 1k-RiCA allow for a detailed view of genetic relationships and unambiguous molecular IDs within indica accessions and good cost vs. marker-density balance for genomic prediction applications in elite indica germplasm. Predictive abilities of Genomic Selection models for flowering time, grain yield, and plant height were on average 0.71, 0.36, and 0.65 respectively based on cross-validation analysis. Furthermore the inclusion of important trait markers associated with 11 different genes and QTL adds value to parental selection in crossing schemes and marker-assisted selection in forward breeding applications. Conclusions This study validated the marker quality and robustness of the 1k-RiCA genotypic platform for genotyping populations derived from indica rice subpopulation for genetic and breeding purposes including MAS and genomic selection. The 1k-RiCA has proven to be an alternative cost-effective genotyping system for breeding applications. Electronic supplementary material The online version of this article (10.1186/s12284-019-0311-0) contains supplementary material, which is available to authorized users.