S-McCouch PubMed Feed

Genetic architecture of root and shoot ionomes in rice (Oryza sativa L.)

Fri, 05/21/2021 - 06:00

Theor Appl Genet. 2021 May 20. doi: 10.1007/s00122-021-03848-5. Online ahead of print.

ABSTRACT

Association analysis for ionomic concentrations of 20 elements identified independent genetic factors underlying the root and shoot ionomes of rice, providing a platform for selecting and dissecting causal genetic variants. Understanding the genetic basis of mineral nutrient acquisition is key to fully describing how terrestrial organisms interact with the non-living environment. Rice (Oryza sativa L.) serves both as a model organism for genetic studies and as an important component of the global food system. Studies in rice ionomics have primarily focused on above ground tissues evaluated from field-grown plants. Here, we describe a comprehensive study of the genetic basis of the rice ionome in both roots and shoots of 6-week-old rice plants for 20 elements using a controlled hydroponics growth system. Building on the wealth of publicly available rice genomic resources, including a panel of 373 diverse rice lines, 4.8 M genome-wide single-nucleotide polymorphisms, single- and multi-marker analysis pipelines, an extensive tome of 321 candidate genes and legacy QTLs from across 15 years of rice genetics literature, we used genome-wide association analysis and biparental QTL analysis to identify 114 genomic regions associated with ionomic variation. The genetic basis for root and shoot ionomes was highly distinct; 78 loci were associated with roots and 36 loci with shoots, with no overlapping genomic regions for the same element across tissues. We further describe the distribution of phenotypic variation across haplotypes and identify candidate genes within highly significant regions associated with sulfur, manganese, cadmium, and molybdenum. Our analysis provides critical insight into the genetic basis of natural phenotypic variation for both root and shoot ionomes in rice and provides a comprehensive resource for dissecting and testing causal genetic variants.

PMID:34018019 | DOI:10.1007/s00122-021-03848-5

Addressing Research Bottlenecks to Crop Productivity

Sat, 04/24/2021 - 06:00

Trends Plant Sci. 2021 Apr 20:S1360-1385(21)00070-4. doi: 10.1016/j.tplants.2021.03.011. Online ahead of print.

ABSTRACT

Asymmetry of investment in crop research leads to knowledge gaps and lost opportunities to accelerate genetic gain through identifying new sources and combinations of traits and alleles. On the basis of consultation with scientists from most major seed companies, we identified several research areas with three common features: (i) relatively underrepresented in the literature; (ii) high probability of boosting productivity in a wide range of crops and environments; and (iii) could be researched in 'precompetitive' space, leveraging previous knowledge, and thereby improving models that guide crop breeding and management decisions. Areas identified included research into hormones, recombination, respiration, roots, and source-sink, which, along with new opportunities in phenomics, genomics, and bioinformatics, make it more feasible to explore crop genetic resources and improve breeding strategies.

PMID:33893046 | DOI:10.1016/j.tplants.2021.03.011

Genetic mapping identifies a rice naringenin O-glucosyltransferase that influences insect resistance

Sun, 03/21/2021 - 06:00

Plant J. 2021 Mar 20. doi: 10.1111/tpj.15244. Online ahead of print.

ABSTRACT

Naringenin, the biochemical precursor for predominant flavonoids in grasses, provides protection against UV damage, pathogen infection and insect feeding. To identify previously unknown loci influencing naringenin accumulation in rice (Oryza sativa), recombinant inbred lines derived from the Nipponbare and IR64 cultivars were used to map a quantitative trait locus (QTL) for naringenin abundance to a region of 50 genes on rice chromosome 7. Examination of candidate genes in the QTL confidence interval identified four predicted uridine diphosphate (UDP)-dependent glucosyltransferases (UGTs) (Os07g31960, Os07g32010, Os07g32020, and Os07g32060). In vitro assays demonstrated that one of these genes, Os07g32020 (UGT707A3), encodes a glucosyltransferase that converts naringenin and uridine diphosphate-glucose (UDP-Glc) to naringenin-7-O-β-D-glucoside. The function of Os07g32020 was verified with CRISPR/Cas9 mutant lines, which accumulated more naringenin and less naringenin-7-O-β-D-glucoside and apigenin-7-O-β-D-glucoside than wild type Nipponbare. Expression of Os12g13800, which encodes a naringenin 7-O-methyltransferase that produces sakuranetin, was elevated in the mutant lines after treatment with methyl jasmonate and insect pests, Spodoptera litura (cotton leafworm), Oxya hyla intricata (rice grasshopper), and Nilaparvata lugens (brown planthopper), leading to higher accumulation of sakuranetin. Feeding damage from O. hyla intricata and N. lugens was reduced on the Os07g32020 mutant lines relative to Nipponbare. Modification of the Os07g32020 gene could be used to increase the production of naringenin and sakuranetin rice flavonoids in a more targeted manner. These findings may open up new opportunities for selective breeding of this important rice metabolic trait.

PMID:33745166 | DOI:10.1111/tpj.15244

Corrigendum: A Coordinated Suite of Wild-Introgression Lines in <em>Indica</em> and <em>Japonica</em> Elite Backgrounds

Fri, 03/19/2021 - 06:00

Front Plant Sci. 2021 Mar 2;11:640122. doi: 10.3389/fpls.2020.640122. eCollection 2020.

ABSTRACT

[This corrects the article DOI: 10.3389/fpls.2020.564824.].

PMID:33737940 | PMC:PMC7961302 | DOI:10.3389/fpls.2020.640122

Multiple Small-Effect Alleles of Indica Origin Enhance High Iron-Associated Stress Tolerance in Rice Under Field Conditions in West Africa.

Tue, 02/16/2021 - 08:33
Related Articles

Multiple Small-Effect Alleles of Indica Origin Enhance High Iron-Associated Stress Tolerance in Rice Under Field Conditions in West Africa.

Front Plant Sci. 2020;11:604938

Authors: Melandri G, Sikirou M, Arbelaez JD, Shittu A, Semwal VK, Konaté KA, Maji AT, Ngaujah SA, Akintayo I, Govindaraj V, Shi Y, Agosto-Peréz FJ, Greenberg AJ, Atlin G, Ramaiah V, McCouch SR

Abstract
Understanding the genetics of field-based tolerance to high iron-associated (HIA) stress in rice can accelerate the development of new varieties with enhanced yield performance in West African lowland ecosystems. To date, few field-based studies have been undertaken to rigorously evaluate rice yield performance under HIA stress conditions. In this study, two NERICA × O. sativa bi-parental rice populations and one O.sativa diversity panel consisting of 296 rice accessions were evaluated for grain yield and leaf bronzing symptoms over multiple years in four West African HIA stress and control sites. Mapping of these traits identified a large number of QTLs and single nucleotide polymorphisms (SNPs) associated with stress tolerance in the field. Favorable alleles associated with tolerance to high levels of iron in anaerobic rice soils were rare and almost exclusively derived from the indica subpopulation, including the most favorable alleles identified in NERICA varieties. These findings highlight the complex genetic architecture underlying rice response to HIA stress and suggest that a recurrent selection program focusing on an expanded indica genepool could be productively used in combination with genomic selection to increase the efficiency of selection in breeding programs designed to enhance tolerance to this prevalent abiotic stress in West Africa.

PMID: 33584748 [PubMed]

A Coordinated Suite of Wild-Introgression Lines in Indica and Japonica Elite Backgrounds.

Tue, 12/08/2020 - 07:47
Related Articles

A Coordinated Suite of Wild-Introgression Lines in Indica and Japonica Elite Backgrounds.

Front Plant Sci. 2020;11:564824

Authors: Singh N, Wang DR, Ali L, Kim H, Akther KM, Harrington SE, Kang JW, Shakiba E, Shi Y, DeClerck G, Meadows B, Govindaraj V, Ahn SN, Eizenga GC, McCouch SR

Abstract
Rice, Oryza sativa L., is a cultivated, inbreeding species that serves as the staple food for the largest number of people on earth. It has two strongly diverged varietal groups, Indica and Japonica, which result from a combination of natural and human selection. The genetic divergence of these groups reflects the underlying population structure of their wild ancestors, and suggests that a pre-breeding strategy designed to take advantage of existing genetic, geographic and ecological substructure may provide a rational approach to the utilization of crop wild ancestors in plant improvement. Here we describe the coordinated development of six introgression libraries (n = 63 to 81 lines per library) in both Indica (cv. IR64) and Japonica (cv. Cybonnet) backgrounds using three bio-geographically diverse wild donors representing the Oryza rufipogon Species Complex from China, Laos and Indonesia. The final libraries were genotyped using an Infinium 7K rice SNP array (C7AIR) and analyzed under greenhouse conditions for several simply inherited (Mendelian) traits. These six interspecific populations can be used as individual Chromosome Segment Substitution Line libraries and, when considered together, serve as a powerful genetic resource for systematic genetic dissection of agronomic, physiological and developmental traits in rice.

PMID: 33281840 [PubMed]

Genome wide association studies for japonica rice resistance to blast in field and controlled conditions.

Fri, 10/09/2020 - 06:40

Genome wide association studies for japonica rice resistance to blast in field and controlled conditions.

Rice (N Y). 2020 Oct 08;13(1):71

Authors: Volante A, Tondelli A, Desiderio F, Abbruscato P, Menin B, Biselli C, Casella L, Singh N, McCouch SR, Tharreau D, Zampieri E, Cattivelli L, Valè G

Abstract
BACKGROUND: Rice blast, caused by the fungus Pyricularia oryzae, represents the most damaging fungal disease of rice worldwide. Utilization of rice resistant cultivars represents a practical way to control the disease. Most of the rice varieties cultivated in Europe and several other temperate regions are severely depleted of blast resistance genes, making the identification of resistant sources in genetic background adapted to temperate environments a priority. Given these assumptions, a Genome Wide Association Study (GWAS) for rice blast resistance was undertaken using a panel of 311 temperate/tropical japonica and indica accessions adapted to temperate conditions and genotyped with 37,423 SNP markers. The panel was evaluated for blast resistance in field, under the pressure of the natural blast population, and in growth chamber, using a mixture of three different fungal strains.
RESULTS: The parallel screening identified 11 accessions showing high levels of resistance in the two conditions, representing potential donors of resistance sources harbored in rice genotypes adapted to temperate conditions. A general higher resistance level was observed in tropical japonica and indica with respect to temperate japonica varieties. The GWAS identified 14 Marker-Traits Associations (MTAs), 8 of which discovered under field conditions and 6 under growth chamber screening. Three MTAs were identified in both conditions; five MTAs were specifically detected under field conditions while three for the growth chamber inoculation. Comparative analysis of physical/genetic positions of the MTAs showed that most of them were positionally-related with cloned or mapped blast resistance genes or with candidate genes whose functions were compatible for conferring pathogen resistance. However, for three MTAs, indicated as BRF10, BRF11-2 and BRGC11-3, no obvious candidate genes or positional relationships with blast resistance QTLs were identified, raising the possibility that they represent new sources of blast resistance.
CONCLUSIONS: We identified 14 MTAs for blast resistance using both field and growth chamber screenings. A total of 11 accessions showing high levels of resistance in both conditions were discovered. Combinations of loci conferring blast resistance were identified in rice accessions adapted to temperate conditions, thus allowing the genetic dissection of affordable resistances present in the panel. The obtained information will provide useful bases for both resistance breeding and further characterization of the highlighted resistance loci.

PMID: 33030605 [PubMed - as supplied by publisher]

Mobilizing Crop Biodiversity.

Tue, 08/25/2020 - 11:53
Related Articles

Mobilizing Crop Biodiversity.

Mol Plant. 2020 Aug 21;:

Authors: McCouch S, Navabi K, Abberton M, Anglin NL, Barbieri RL, Baum M, Bett K, Booker H, Brown GL, Bryan GJ, Cattivelli L, Charest D, Eversole K, Freitas M, Ghamkhar K, Grattapaglia D, Henry R, Valadares Inglis MC, Islam T, Kehel Z, Kersey PJ, Kresovich S, Marden E, Mayes S, Ndjiondjop MN, Nguyen HT, Paiva S, Papa R, Phillips PWB, Rasheed A, Richards C, Rouard M, Amstalden Sampaio MJ, Scholz U, Shaw PD, Sherman B, Staton SE, Stein N, Svensson J, Tester M, Montenegro Valls JF, Varshney R, Visscher S, von Wettberg E, Waugh R, Wenzl PWB, Rieseberg LH

PMID: 32835887 [PubMed - as supplied by publisher]

Low Additive Genetic Variation in a Trait Under Selection in Domesticated Rice.

Sat, 05/23/2020 - 07:26
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Low Additive Genetic Variation in a Trait Under Selection in Domesticated Rice.

G3 (Bethesda). 2020 May 21;:

Authors: Karavolias NG, Greenberg AJ, Barrero LS, Maron LG, Shi Y, Monteverde E, Piñeros MA, McCouch SR

Abstract
Quantitative traits are important targets of both natural and artificial selection. The genetic architecture of these traits and its change during the adaptive process is thus of fundamental interest. The fate of the additive effects of variants underlying a trait receives particular attention because they constitute the genetic variation component that is transferred from parents to offspring and thus governs the response to selection. While estimation of this component of phenotypic variation is challenging, the increasing availability of dense molecular markers puts it within reach. Inbred plant species offer an additional advantage because phenotypes of genetically identical individuals can be measured in replicate. This makes it possible to estimate marker effects separately from the contribution of the genetic background not captured by genotyped loci. We focused on root growth in domesticated rice, Oryza sativa, under normal and aluminum (Al) stress conditions, a trait under recent selection because it correlates with survival under drought. A dense single nucleotide polymorphism (SNP) map is available for all accessions studied. Taking advantage of this map and a set of Bayesian models, we assessed additive marker effects. While total genetic variation accounted for a large proportion of phenotypic variance, marker effects contributed little information, particularly in the Al-tolerant tropical japonica population of rice. We were unable to identify any loci associated with root growth in this population. Models estimating the aggregate effects of all measured genotypes likewise produced low estimates of marker heritability and were unable to predict total genetic values accurately. Our results support the long-standing conjecture that additive genetic variation is depleted in traits under selection. We further provide evidence that this depletion is due to the prevalence of low-frequency alleles that underlie the trait.

PMID: 32439738 [PubMed - as supplied by publisher]

An improved 7K SNP array, the C7AIR, provides a wealth of validated SNP markers for rice breeding and genetics studies.

Fri, 05/15/2020 - 07:21

An improved 7K SNP array, the C7AIR, provides a wealth of validated SNP markers for rice breeding and genetics studies.

PLoS One. 2020;15(5):e0232479

Authors: Morales KY, Singh N, Perez FA, Ignacio JC, Thapa R, Arbelaez JD, Tabien RE, Famoso A, Wang DR, Septiningsih EM, Shi Y, Kretzschmar T, McCouch SR, Thomson MJ

Abstract
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 trait-specific 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 C7AIR provides valuable information that can be used to select informative and reliable SNP markers for conversion to lower-cost genotyping platforms for genomic selection and other downstream applications in breeding.

PMID: 32407369 [PubMed - as supplied by publisher]

A massively parallel barcoded sequencing pipeline enables generation of the first ORFeome and interactome map for rice.

Thu, 05/14/2020 - 09:15
Related Articles

A massively parallel barcoded sequencing pipeline enables generation of the first ORFeome and interactome map for rice.

Proc Natl Acad Sci U S A. 2020 May 12;:

Authors: Wierbowski SD, Vo TV, Falter-Braun P, Jobe TO, Kruse LH, Wei X, Liang J, Meyer MJ, Akturk N, Rivera-Erick CA, Cordero NA, Paramo MI, Shayhidin EE, Bertolotti M, Tippens ND, Akther K, Sharma R, Katayose Y, Salehi-Ashtiani K, Hao T, Ronald PC, Ecker JR, Schweitzer PA, Kikuchi S, Mizuno H, Hill DE, Vidal M, Moghe GD, McCouch SR, Yu H

Abstract
Systematic mappings of protein interactome networks have provided invaluable functional information for numerous model organisms. Here we develop PCR-mediated Linkage of barcoded Adapters To nucleic acid Elements for sequencing (PLATE-seq) that serves as a general tool to rapidly sequence thousands of DNA elements. We validate its utility by generating the ORFeome for Oryza sativa covering 2,300 genes and constructing a high-quality protein-protein interactome map consisting of 322 interactions between 289 proteins, expanding the known interactions in rice by roughly 50%. Our work paves the way for high-throughput profiling of protein-protein interactions in a wide range of organisms.

PMID: 32398372 [PubMed - as supplied by publisher]

Strategies for Effective Use of Genomic Information in Crop Breeding Programs Serving Africa and South Asia.

Thu, 04/16/2020 - 07:05
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Strategies for Effective Use of Genomic Information in Crop Breeding Programs Serving Africa and South Asia.

Front Plant Sci. 2020;11:353

Authors: Santantonio N, Atanda SA, Beyene Y, Varshney RK, Olsen M, Jones E, Roorkiwal M, Gowda M, Bharadwaj C, Gaur PM, Zhang X, Dreher K, Ayala-Hernández C, Crossa J, Pérez-Rodríguez P, Rathore A, Gao SY, McCouch S, Robbins KR

Abstract
Much of the world's population growth will occur in regions where food insecurity is prevalent, with large increases in food demand projected in regions of Africa and South Asia. While improving food security in these regions will require a multi-faceted approach, improved performance of crop varieties in these regions will play a critical role. Current rates of genetic gain in breeding programs serving Africa and South Asia fall below rates achieved in other regions of the world. Given resource constraints, increased genetic gain in these regions cannot be achieved by simply expanding the size of breeding programs. New approaches to breeding are required. The Genomic Open-source Breeding informatics initiative (GOBii) and Excellence in Breeding Platform (EiB) are working with public sector breeding programs to build capacity, develop breeding strategies, and build breeding informatics capabilities to enable routine use of new technologies that can improve the efficiency of breeding programs and increase genetic gains. Simulations evaluating breeding strategies indicate cost-effective implementations of genomic selection (GS) are feasible using relatively small training sets, and proof-of-concept implementations have been validated in the International Maize and Wheat Improvement Center (CIMMYT) maize breeding program. Progress on GOBii, EiB, and implementation of GS in CIMMYT and International Crops Research Institute for the Semi-Arid Tropics (ICRISAT) breeding programs are discussed, as well as strategies for routine implementation of GS in breeding programs serving Africa and South Asia.

PMID: 32292411 [PubMed]

Bridging old and new: Diversity and evaluation of high iron-associated stress response of rice cultivated in W. Africa.

Sun, 04/12/2020 - 06:56

Bridging old and new: Diversity and evaluation of high iron-associated stress response of rice cultivated in W. Africa.

J Exp Bot. 2020 Apr 11;:

Authors: Diop B, Wang DR, Drame KN, Gracen V, Tongoona P, Dzidzienyo D, Nartey E, Greenberg AJ, Djiba S, Danquah EY, McCouch SR

Abstract
Adoption of rice varieties that perform well under high iron-associated (HIA) stress environments can enhance rice production in West Africa (WA). This study reports the genetic characterization of 323 rice accessions and breeding lines cultivated in WA using Genotyping-by-Sequencing and their phenotypic response to HIA treatments in hydroponic solution (1500 mg L-1 FeSO4.7H2O) and hot-spot fields. The germplasm consisted of four genetic subpopulations: O. glaberrima (14%), O. sativa-japonica (7%), O. sativa-indica Group 1 (45%) and O. sativa-indica Group 2 (25%). Severe versus mild stress in the field was associated with reduced SPAD value (12%), biomass (56%) and grain yield (57%), with leaf bronzing explaining 30% and 21% of the variation for biomass and grain yield, respectively. Association mapping using 175 indica genotypes identified 23 significant single-nucleotide polymorphism (SNP) markers that mapped to 14 genomic-regions. GWAS-signals associated with leaf bronzing, a routinely-used indicator of HIA stress, differed in hydroponic compared to field conditions. Contrastingly, six significant SNPs on chromosomes 8 and 9 were associated with SPAD value under HIA stress in both field and hydroponic experiments, and a candidate potassium transporter gene mapped under the peak on chromosome 8. This study helps define criteria for assessing rice performance under HIA environments.

PMID: 32277700 [PubMed - as supplied by publisher]

Association mapping and genetic dissection of drought-induced canopy temperature differences in rice.

Wed, 12/18/2019 - 06:32

Association mapping and genetic dissection of drought-induced canopy temperature differences in rice.

J Exp Bot. 2019 Dec 17;:

Authors: Melandri G, Prashar A, Mccouch SR, Van Der Linden G, Jones HG, Kadam N, Jagadish K, Bouwmeester H, Ruyter-Spira C

Abstract
Drought-stressed plants display reduced stomatal conductance, which results in increased leaf temperature by limiting transpiration. In this study, thermal imaging was used to quantify the differences in canopy temperature under drought in a rice diversity panel consisting of 293 indica accessions. The population was grown under paddy field conditions and drought stress was imposed for 2 weeks at flowering. The canopy temperature of the accessions during stress negatively correlated with grain yield (r= -0.48) and positively with plant height (r=0.56). Temperature values were used to perform a genome-wide association (GWA) analysis using a 45K single nucleotide polynmorphism (SNP) map. A quantitative trait locus (QTL) for canopy temperature under drought was detected on chromosome 3 and fine-mapped using a high-density imputed SNP map. The candidate genes underlying the QTL point towards differences in the regulation of guard cell solute intake for stomatal opening as the possible source of temperature variation. Genetic variation for the significant markers of the QTL was present only within the tall, low-yielding landraces adapted to drought-prone environments. The absence of variation in the shorter genotypes, which showed lower leaf temperature and higher grain yield, suggests that breeding for high grain yield in rice under paddy conditions has reduced genetic variation for stomatal response under drought.

PMID: 31846000 [PubMed - as supplied by publisher]

A SWEET solution to rice blight.

Wed, 10/30/2019 - 06:25
Related Articles

A SWEET solution to rice blight.

Nat Biotechnol. 2019 Oct 28;:

Authors: Varshney RK, Godwin ID, Mohapatra T, Jones JDG, McCouch SR

PMID: 31659336 [PubMed - as supplied by publisher]

<em>ALUMINUM RESISTANCE TRANSCRIPTION FACTOR 1</em> (<em>ART1</em>) contributes to natural variation in aluminum resistance in diverse genetic backgrounds of rice (<em>O. sativa</em>)

Fri, 06/28/2019 - 06:00

Plant Direct. 2017 Oct 16;1(4):e00014. doi: 10.1002/pld3.14. eCollection 2017 Oct.

ABSTRACT

Transcription factors (TFs) regulate the expression of other genes to indirectly mediate stress resistance mechanisms. Therefore, when studying TF-mediated stress resistance, it is important to understand how TFs interact with genes in the genetic background. Here, we fine-mapped the aluminum (Al) resistance QTL Alt12.1 to a 44-kb region containing six genes. Among them is ART1, which encodes a C2H2-type zinc finger TF required for Al resistance in rice. The mapping parents, Al-resistant cv Azucena (tropical japonica) and Al-sensitive cv IR64 (indica), have extensive sequence polymorphism within the ART1 coding region, but similar ART1 expression levels. Using reciprocal near-isogenic lines (NILs) we examined how allele-swapping the Alt12.1 locus would affect plant responses to Al. Analysis of global transcriptional responses to Al stress in roots of the NILs alongside their recurrent parents demonstrated that the presence of the Alt12.1 from Al-resistant Azucena led to greater changes in gene expression in response to Al when compared to the Alt12.1 from IR64 in both genetic backgrounds. The presence of the ART1 allele from the opposite parent affected the expression of several genes not previously implicated in rice Al tolerance. We highlight examples where putatively functional variation in cis-regulatory regions of ART1-regulated genes interacts with ART1 to determine gene expression in response to Al. This ART1-promoter interaction may be associated with transgressive variation for Al resistance in the Azucena × IR64 population. These results illustrate how ART1 interacts with the genetic background to contribute to quantitative phenotypic variation in rice Al resistance.

PMID:31245663 | PMC:PMC6508803 | DOI:10.1002/pld3.14

Validation of Yield Component Traits Identified by Genome-Wide Association Mapping in a tropical japonica × tropical japonica Rice Biparental Mapping Population.

Sat, 04/06/2019 - 06:22

Validation of Yield Component Traits Identified by Genome-Wide Association Mapping in a tropical japonica × tropical japonica Rice Biparental Mapping Population.

Plant Genome. 2019 Mar;12(1):

Authors: Eizenga GC, Jia MH, Jackson AK, Boykin DL, Ali ML, Shakiba E, Tran NT, McCouch SR, Edwards JD

Abstract
The Rice Diversity Panel 1 (RDP1) was developed for genome-wide association (GWA) studies to explore five rice ( L.) subpopulations (, , , , and ). The RDP1 was evaluated for over 30 traits, including agronomic, panicle architecture, seed, and disease traits and genotyped with 700,000 single nucleotide polymorphisms (SNPs). Most rice grown in the southern United States is and thus the diversity in this subpopulation is interesting to U.S. breeders. Among the RDP1 accessions, 'Estrela' and 'NSFTV199' are both phenotypically and genotypically diverse, thus making them excellent parents for a biparental mapping population. The objectives were to (i) ascertain the GWA QTLs from the RDP1 GWA studies that overlapped with the QTLs uncovered in an Estrela × NSFTV199 recombinant inbred line (RIL) population evaluated for 15 yield traits, and (ii) identify known or novel genes potentially controlling specific yield component traits. The 256 RILs were genotyped with 132 simple sequence repeat markers and 70 QTLs were found. Perl scripts were developed for automatic identification of the underlying candidate genes in the GWA QTL regions. Approximately 100 GWA QTLs overlapped with 41 Estrela × NSFTV199 QTL (RIL QTL) regions and 47 known genes were identified. Two seed trait RIL QTLs with overlapping GWA QTLs were not associated with a known gene. Segregating SNPs in the overlapping GWA QTLs for RIL QTLs with high values will be evaluated as potential DNA markers useful to breeding programs for the associated yield trait.

PMID: 30951093 [PubMed - in process]

Integrating Molecular Markers and Environmental Covariates To Interpret Genotype by Environment Interaction in Rice (Oryza sativa L.) Grown in Subtropical Areas.

Sun, 03/17/2019 - 07:09
Related Articles

Integrating Molecular Markers and Environmental Covariates To Interpret Genotype by Environment Interaction in Rice (Oryza sativa L.) Grown in Subtropical Areas.

G3 (Bethesda). 2019 Mar 15;:

Authors: Monteverde E, Gutierrez L, Blanco P, Pérez de Vida F, Rosas JE, Bonnecarrère V, Quero G, McCouch S

Abstract
Understanding the genetic and environmental basis of genotype × environment interaction (G×E) is of fundamental importance in plant breeding. If we consider G×E in the context of genotype × year interactions (G×Y), predicting which lines will have stable and superior performance across years is an important challenge for breeders. A better understanding of the factors that contribute to the overall grain yield and quality of rice (Oryza sativa L.) will lay the foundation for developing new breeding and selection strategies for combining high quality, with high yield. In this study, we used molecular marker data and environmental covariates (EC) simultaneously to predict rice yield, milling quality traits and plant height in untested environments (years), using both reaction norm models and partial least squares (PLS), in two rice breeding populations (indica and tropical japonica). We also sought to explain G×E by differential quantitative trait loci (QTL) expression in relation to EC. Our results showed that PLS models trained with both molecular markers and EC gave better prediction accuracies than reaction norm models when predicting future years. We also detected milling quality QTL that showed a differential expression conditional on humidity and solar radiation, providing insight for the main environmental factors affecting milling quality in subtropical and temperate rice growing areas.

PMID: 30877079 [PubMed - as supplied by publisher]

Genome-Wide Association Study Using Historical Breeding Populations Discovers Genomic Regions Involved in High-Quality Rice.

Wed, 12/05/2018 - 06:46

Genome-Wide Association Study Using Historical Breeding Populations Discovers Genomic Regions Involved in High-Quality Rice.

Plant Genome. 2018 Nov;11(3):

Authors: Quero G, Gutiérrez L, Monteverde E, Blanco P, Pérez de Vida F, Rosas J, Fernández S, Garaycochea S, McCouch S, Berberian N, Simondi S, Bonnecarrère V

Abstract
Rice ( L.) is one of the most important staple food crops in the world; however, there has recently been a shift in consumer demand for higher grain quality. Therefore, understanding the genetic architecture of grain quality has become a key objective of rice breeding programs. Genome-wide association studies (GWAS) using large diversity panels have successfully identified genomic regions associated with complex traits in diverse crop species. Our main objective was to identify genomic regions associated with grain quality and to identify and characterize favorable haplotypes for selection. We used two locally adapted rice breeding populations and historical phenotypic data for three rice quality traits: yield after milling, percentage of head rice recovery, and percentage of chalky grain. We detected 22 putative quantitative trait loci (QTL) in the same genomic regions as starch synthesis, starch metabolism, and cell wall synthesis-related genes are found. Additionally, we found a genomic region on chromosome 6 in the population that was associated with all quality traits and we identified favorable haplotypes. Furthermore, this region is linked to the gene that codes for a starch branching enzyme I, which is implicated in starch granule formation. In , we also found two putative QTL linked to , , and . Our study provides an insight into the genetic basis of rice grain chalkiness, yield after milling, and head rice, identifying favorable haplotypes and molecular markers for selection in breeding programs.

PMID: 30512035 [PubMed - in process]

An imputation platform to enhance integration of rice genetic resources.

Fri, 08/31/2018 - 08:32
Related Articles

An imputation platform to enhance integration of rice genetic resources.

Nat Commun. 2018 Aug 29;9(1):3519

Authors: Wang DR, Agosto-Pérez FJ, Chebotarov D, Shi Y, Marchini J, Fitzgerald M, McNally KL, Alexandrov N, McCouch SR

Abstract
As sequencing and genotyping technologies evolve, crop genetics researchers accumulate increasing numbers of genomic data sets from various genotyping platforms on different germplasm panels. Imputation is an effective approach to increase marker density of existing data sets toward the goal of integrating resources for downstream applications. While a number of imputation software packages are available, the limitations to utilization for the rice community include high computational demand and lack of a reference panel. To address these challenges, we develop the Rice Imputation Server, a publicly available web application leveraging genetic information from a globally diverse rice reference panel assembled here. This resource allows researchers to benefit from increased marker density without needing to perform imputation on their own machines. We demonstrate improvements that imputed data provide to rice genome-wide association (GWA) results of grain amylose content and show that the major functional nucleotide polymorphism is tagged only in the imputed data set.

PMID: 30158584 [PubMed - in process]

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