Biallelic and Genome Wide Association Mapping of Germanium Tolerant Loci in Rice (Oryza sativa L.)

Genome wide association studies and candidate gene mining for understanding the genetic basis of straw silica content in a set of Oryza nivara (Sharma et Shastry) accessions

Rice is a high-silica (SiO₂·nH₂O) accumulator. Silicon (Si) is designated as a beneficial element associated with multiple positive effects on crops. However, the presence of high silica content is detrimental to rice straw management, hampering its use as animal feed and as raw material in multiple industries. Rice straw management is a serious concern in north-western India, and it is eventually burned in situ by farmers, contributing to air pollution. A practical solution could lie in reducing the silica content in rice while also attaining sound plant growth. A set of 258 Oryza nivara accessions along with 25 cultivated varieties of Oryza sativa was used to assess the variation in straw silica content using the molybdenum blue colorimetry method. A large continuous variation was observed for straw silica content in O. nivara accessions, ranging from 5.08% to 16%, while it varied from 6.18% to 15.81% in the cultivated varieties. The O. nivara accessions containing 43%-54% lower straw silica content than the currently prominent cultivated varieties in the region were identified. A set of 22,528 high-quality single nucleotide polymorphisms (SNPs) among 258 O. nivara accessions was used for estimating population structure and genome-wide association studies (GWAS). A weak population structure with 59% admixtures was identified among O. nivara accessions. Further, multi-locus GWAS revealed the presence of 14 marker-trait associations (MTAs) for straw silica content, with six of them co-localizing with previously reported quantitative trait loci (QTL). Twelve out of 14 MTAs showed statistically significant allelic differences. Thorough candidate gene analyses revealed the presence of promising candidate genes, including those encoding the ATP-binding cassette (ABC) transporter, Casparian thickening, multi-drug and toxin extrusion (MATE) protein, F-box, and MYB-transcription factors. Besides, ortho-QTLs among rice and maize genomes were identified, which could open ways for further genetic analysis of this trait. The findings of the study could aid in further understanding and characterizing genes for Si transport and regulation in the plant body. The donors carrying the alleles for lower straw silica content can be used in further marker-assisted breeding programs to develop rice varieties with lower silica content and higher yield potential.

Relationships Among Arsenic-Related Traits, Including Rice Grain Arsenic Concentration and Straighthead Resistance, as Revealed by Genome-Wide Association

There is global concern that rice grains and foods can contain harmful amounts of arsenic (As), motivating breeders to produce cultivars that restrict As accumulation in grains to protect human health. Arsenic is also toxic to plants, with straighthead disorder (StHD), causing panicle sterility, being observed in rice. The genetic variation in StHD resistance suggests that plants have evolved mechanisms that reduce As toxicity, possibly via regulation of As uptake, transport, or detoxification/sequestration. Because these mechanisms could also underlie the wide (3- to 100-fold) differences in grain As concentration (grain-As) observed among diverse rice genotypes, it was hypothesized that some genes reduce both grain-As content and StHD susceptibility and may be detectable as co-located StDH and As quantitative trait loci (QTL). We used a machine-learning Bayesian network approach plus high-resolution genome-wide association study (GWAS) to identify QTL for grain-As and StHD resistance within the USDA Rice Minicore Collection (RMC). Arsenic enters roots through phosphorus (P) and silica (Si) transporters, As detoxification involves sulfur (S), and cell signaling to activate stress tolerance mechanisms is impacted by Si, calcium (Ca), and copper (Cu). Therefore, concentrations of Si, P, S, Ca, and Cu were included in this study to elucidate physiological mechanisms underlying grain-As and StHD QTL. Multiple QTL (from 9 to 33) were identified for each of the investigated As-associated traits. Although the QTL for StHD, Si, and grain-As did not overlap as heavily as our hypothesis predicted (4/33 StHD and 4/15 As QTL co-located), they do provide useful guidance to future research. Furthermore, these are the first StHD and Si QTL to be identified using high-density mapping, resulting in their being mapped to shorter, more precise genomic regions than previously reported QTL. The candidate genes identified provide guidance for future research, such as gene editing or mutation studies to further investigate the role of antioxidants and ROS scavenging to StHD resistance, as indicated by candidate genes around the commonly reported qStHD8-2 QTL. Other genes indicated for future study for improving grain-As and StHD include several multidrug and toxic compound extrusion (MATE) genes, F-box genes, and NIPs not documented to date to transport As.

Emerging Trends in Metalloid-Dependent Signaling in Plants

Metalloids are semiconducting elements that constitute a small group in the periodic table of elements. Their occurrence in nature either poses an environmental threat or benefit to plants. The precise mechanisms or manner of crosstalk of metalloid interference and sensing remain open questions. Standard plant nutrient solutions contain the metalloid boron (B) as a micronutrient, while silicon (Si) is considered a beneficial element routinely supplied only to some plants such as grasses. By contrast, arsenic (As) is a severe environmental hazard to most organisms, including plants, while the less abundant metalloids germanium (Ge), antimony (Sb), and tellurium (Te) display variable degrees of toxicity. Here we review the molecular events and mechanisms that could explain the contrasting (or overlapping) action of metalloids on the cell and cell signaling.

Diverse Roles of MAX1 Homologues in Rice

Cytochrome P450 enzymes encoded by MORE AXILLARY GROWTH1 (MAX1)-like genes produce most of the structural diversity of strigolactones during the final steps of strigolactone biosynthesis. The diverse copies of MAX1 in Oryza sativa provide a resource to investigate why plants produce such a wide range of strigolactones. Here we performed in silico analyses of transcription factors and microRNAs that may regulate each rice MAX1, and compared the results with available data about MAX1 expression profiles and genes co-expressed with MAX1 genes. Data suggest that distinct mechanisms regulate the expression of each MAX1. Moreover, there may be novel functions for MAX1 homologues, such as the regulation of flower development or responses to heavy metals. In addition, individual MAX1s could be involved in specific functions, such as the regulation of seed development or wax synthesis in rice. Our analysis reveals potential new avenues of strigolactone research that may otherwise not be obvious.

Genome Wide Association Mapping of Grain and Straw Biomass Traits in the Rice Bengal and Assam Aus Panel (BAAP) Grown Under Alternate Wetting and Drying and Permanently Flooded Irrigation

Growing demand for staple crops like rice will need to be achieved predominately through agricultural intensification and more efficient use of inputs. To meet this demand it is essential that the genetic diversity within rice is fully utilized. The aus subpopulation is considered an underappreciated resource within that diversity. A new rice panel, the Bengal and Assam Aus Panel (BAAP) of 266 aus accessions was generated with ∼2 million informative SNPs obtained using skim sequencing at ∼4× depth. The BAAP was grown in the field in Bangladesh in the 'boro' season under both continuously flooded and Alternate Wetting and Drying (AWD) irrigation during 2013 and 2014 in Mymensingh and during 2014 in Madhupur. Heading date, grain mass, straw biomass and harvest index were measured. The majority (94%) of BAAP accessions flowered within a relatively small window of 10 days. The AWD irrigation treatment generally caused an increase in grain mass, but no significant genotype by treatment interactions were detected for this trait. Shoot biomass was the only trait that showed evidence of genotype by treatment interaction. The average LD (Linkage Disequilibrium) decay across the genome was 243 Kbp. Genome wide association mapping revealed 115 quantitative trait loci (QTLs). There was little evidence of QTLs specific to the irrigation treatment, and only a few QTLs co-localized with known genes. However, some QTLs were detected across multiple sites and years. These QTLs should be targets for breeding, and include a region around 2.2 Mbp on chromosome 1, a large region in the middle of chromosome 7 and two regions on chromosome 11 (∼10 Mbp and ∼29 Mbp). The BAAP appears to be a valuable addition to the growing collection of GWA mapping populations of rice.