A wild rice CSSL population facilitated identification of salt tolerance genes and rice germplasm innovation.

Salt stress is one of the major factors that limits rice production. Therefore, identification of salt-tolerant alleles from wild rice is important for rice breeding. In this study, we constructed a set of chromosome segment substitution lines (CSSLs) using wild rice as the donor parent and cultivated rice Nipponbare (Nip) as the recurrent parent. Salt tolerance germinability (STG) was evaluated, and its association with genotypes was determined using this CSSL population. We identified 17 QTLs related to STG. By integrating the transcriptome and genome data, four candidate genes were identified, including the previously reported AGO2 and WRKY53. Compared with Nip, wild rice AGO2 has a structure variation in its promoter region and the expression levels were upregulated under salt treatments; wild rice WRKY53 also has natural variation in its promoter region, and the expression levels were downregulated under salt treatments. Wild rice AGO2 and WRKY53 alleles have combined effects for improving salt tolerance at the germination stage. One CSSL line, CSSL118 that harbors these two alleles was selected. Compared with the background parent Nip, CSSL118 showed comprehensive salt tolerance and higher yield, with improved transcript levels of reactive oxygen species scavenging genes. Our results provided promising genes and germplasm resources for future rice salt tolerance breeding.

Fault Detection and Exclusion for Tightly Coupled GNSS/INS System Considering Fault in State Prediction.

To ensure navigation integrity for safety-critical applications, this paper proposes an efficient Fault Detection and Exclusion (FDE) scheme for tightly coupled navigation system of Global Navigation Satellite Systems (GNSS) and Inertial Navigation System (INS). Special emphasis is placed on the potential faults in the Kalman Filter state prediction step (defined as "filter fault"), which could be caused by the undetected faults occurring previously or the Inertial Measurement Unit (IMU) failures. The integration model is derived first to capture the features and impacts of GNSS faults and filter fault. To accommodate various fault conditions, two independent detectors, which are respectively designated for GNSS fault and filter fault, are rigorously established based on hypothesis-test methods. Following a detection event, the newly-designed exclusion function enables (a) identifying and removing the faulty measurements and (b) eliminating the effect of filter fault through filter recovery. Moreover, we also attempt to avoid wrong exclusion events by analyzing the underlying causes and optimizing the decision strategy for GNSS fault exclusion accordingly. The FDE scheme is validated through multiple simulations, where high efficiency and effectiveness have been achieved in various fault scenarios.

A Subset-Reduced Method for FDE ARAIM of Tightly-Coupled GNSS/INS.

The advanced receiver autonomous integrity monitoring (advanced RAIM, ARAIM) is the next generation of RAIM which is widely used in civil aviation. However, the current ARAIM needs to evaluate hundreds of subsets, which results in huge computational loads. In this paper, a method using the subset excluding entire constellation to evaluate the single satellite fault subsets and the simultaneous multiple satellites fault subsets is presented. The proposed ARAIM algorithm is based on the tight integration of the global navigation satellite system (GNSS) and inertial navigation system (INS). The number of subsets that the proposed GNSS/INS ARAIM needs to consider is about 2% of that of the current ARAIM, which reduces the computational load dramatically. The detailed fault detection (FD) process and fault exclusion (FE) process of the proposed GNSS/INS ARAIM are provided. Meanwhile, the method to obtain the FD-only integrity bound and the after-exclusion integrity bound is also presented in this paper. The simulation results show that the proposed GNSS/INS ARAIM is able to find the failing satellite accurately and its integrity performance is able to meet the integrity requirements of CAT-I precision approach.

Haplotype-resolved gapless genome and chromosome segment substitution lines facilitate gene identification in wild rice.

The abundant genetic variation harbored by wild rice (Oryza rufipogon) has provided a reservoir of useful genes for rice breeding. However, the genome of wild rice has not yet been comprehensively assessed. Here, we report the haplotype-resolved gapless genome assembly and annotation of wild rice Y476. In addition, we develop two sets of chromosome segment substitution lines (CSSLs) using Y476 as the donor parent and cultivated rice as the recurrent parents. By analyzing the gapless reference genome and CSSL population, we identify 254 QTLs associated with agronomic traits, biotic and abiotic stresses. We clone a receptor-like kinase gene associated with rice blast resistance and confirm its wild rice allele improves rice blast resistance. Collectively, our study provides a haplotype-resolved gapless reference genome and demonstrates a highly efficient platform for gene identification from wild rice.

Global whole-genome comparison and analysis to classify subpopulations and identify resistance genes in weedy rice relevant for improving crops.

Common weedy rice plants are important genetic resources for modern breeding programs because they are the closest relatives to rice cultivars and their genomes contain elite genes. Determining the utility and copy numbers of WRKY and nucleotide-binding site (NBS) resistance-related genes may help to clarify their variation patterns and lead to crop improvements. In this study, the weedy rice line LM8 was examined at the whole-genome level. To identify the Oryza sativa japonica subpopulation that LM8 belongs to, the single nucleotide polymorphisms (SNPs) of 180 cultivated and 23 weedy rice varieties were used to construct a phylogenetic tree and a principal component analysis and STRUCTURE analysis were performed. The results indicated that LM8 with admixture components from japonica (GJ) and indica (XI) belonged to GJ-admixture (GJ-adm), with more than 60% of its genetic background derived from XI-2 (22.98%), GJ-tropical (22.86%), and GJ-subtropical (17.76%). Less than 9% of its genetic background was introgressed from weedy rice. Our results also suggested LM8 may have originated in a subtropical or tropical geographic region. Moreover, the comparisons with Nipponbare (NIP) and Shuhui498 (R498) revealed many specific structure variations (SVs) in the LM8 genome and fewer SVs between LM8 and NIP than between LM8 and R498. Next, 96 WRKY and 464 NBS genes were identified and mapped on LM8 chromosomes to eliminate redundancies. Three WRKY genes (ORUFILM02g002693, ORUFILM05g002725, and ORUFILM05g001757) in group III and one RNL [including the resistance to powdery mildew 8 (RPW8) domain, NBS, and leucine rich repeats (LRRs)] type NBS gene (ORUFILM12g000772) were detected in LM8. Among the NBS genes, the RPW8 domain was detected only in ORUFILM12g000772. This gene may improve plant resistance to pathogens as previously reported. Its classification and potential utility imply LM8 should be considered as a germplasm resource relevant for rice breeding programs.

LncPheDB: a genome-wide lncRNAs regulated phenotypes database in plants.

LncPheDB (https://www.lncphedb.com/) is a systematic resource of genome-wide long non-coding RNAs (lncRNAs)-phenotypes associations for multiple species. It was established to display the genome-wide lncRNA annotations, target genes prediction, variant-trait associations, gene-phenotype correlations, lncRNA-phenotype correlations, and the similar non-coding regions of the queried sequence in multiple species. LncPheDB sorted out a total of 203,391 lncRNA sequences, 2000 phenotypes, and 120,271 variants of nine species (Zea mays L., Gossypium barbadense L., Triticum aestivum L., Lycopersicon esculentum Mille, Oryza sativa L., Hordeum vulgare L., Sorghum bicolor L., Glycine max L., and Cucumis sativus L.). By exploring the relationship between lncRNAs and the genomic position of variants in genome-wide association analysis, a total of 68,862 lncRNAs were found to be related to the diversity of agronomic traits. More importantly, to facilitate the study of the functions of lncRNAs, we analyzed the possible target genes of lncRNAs, constructed a blast tool for performing similar fragmentation studies in all species, linked the pages of phenotypic studies related to lncRNAs that possess similar fragments and constructed their regulatory networks. In addition, LncPheDB also provides a user-friendly interface, a genome visualization platform, and multi-level and multi-modal convenient data search engine. We believe that LncPheDB plays a crucial role in mining lncRNA-related plant data. Supplementary Information: The online version contains supplementary material available at 10.1007/s42994-022-00084-3.

Identification of candidate genes and clarification of the maintenance of the green pericarp of weedy rice grains.

The weedy rice (Oryza sativa f. spontanea) pericarp has diverse colors (e.g., purple, red, light-red, and white). However, research on pericarp colors has focused on red and purple, but not green. Unlike many other common weedy rice resources, LM8 has a green pericarp at maturity. In this study, the coloration of the LM8 pericarp was evaluated at the cellular and genetic levels. First, an examination of their ultrastructure indicated that LM8 chloroplasts were normal regarding plastid development and they contained many plastoglobules from the early immature stage to maturity. Analyses of transcriptome profiles and differentially expressed genes revealed that most chlorophyll (Chl) degradation-related genes in LM8 were expressed at lower levels than Chl a/b cycle-related genes in mature pericarps, suggesting that the green LM8 pericarp was associated with inhibited Chl degradation in intact chloroplasts. Second, the F2 generation derived from a cross between LM8 (green pericarp) and SLG (white pericarp) had a pericarp color segregation ratio of 9:3:4 (green:brown:white). The bulked segregant analysis of the F2 populations resulted in the identification of 12 known genes in the chromosome 3 and 4 hotspot regions as candidate genes related to Chl metabolism in the rice pericarp. The RNA-seq and sqRT-PCR assays indicated that the expression of the Chl a/b cycle-related structural gene DVR (encoding divinyl reductase) was sharply up-regulated. Moreover, genes encoding magnesium-chelatase subunit D and the light-harvesting Chl a/b-binding protein were transcriptionally active in the fully ripened dry pericarp. Regarding the ethylene signal transduction pathway, the CTR (encoding an ethylene-responsive protein kinase) and ERF (encoding an ethylene-responsive factor) genes expression profiles were determined. The findings of this study highlight the regulatory roles of Chl biosynthesis- and degradation-related genes influencing Chl accumulation during the maturation of the LM8 pericarp.