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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
Related Articles

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]

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]

Ethylene-gibberellin signaling underlies adaptation of rice to periodic flooding.

Sat, 07/14/2018 - 06:55
Related Articles

Ethylene-gibberellin signaling underlies adaptation of rice to periodic flooding.

Science. 2018 Jul 13;361(6398):181-186

Authors: Kuroha T, Nagai K, Gamuyao R, Wang DR, Furuta T, Nakamori M, Kitaoka T, Adachi K, Minami A, Mori Y, Mashiguchi K, Seto Y, Yamaguchi S, Kojima M, Sakakibara H, Wu J, Ebana K, Mitsuda N, Ohme-Takagi M, Yanagisawa S, Yamasaki M, Yokoyama R, Nishitani K, Mochizuki T, Tamiya G, McCouch SR, Ashikari M

Abstract
Most plants do poorly when flooded. Certain rice varieties, known as deepwater rice, survive periodic flooding and consequent oxygen deficiency by activating internode growth of stems to keep above the water. Here, we identify the gibberellin biosynthesis gene, SD1 (SEMIDWARF1), whose loss-of-function allele catapulted the rice Green Revolution, as being responsible for submergence-induced internode elongation. When submerged, plants carrying the deepwater rice-specific SD1 haplotype amplify a signaling relay in which the SD1 gene is transcriptionally activated by an ethylene-responsive transcription factor, OsEIL1a. The SD1 protein directs increased synthesis of gibberellins, largely GA4, which promote internode elongation. Evolutionary analysis shows that the deepwater rice-specific haplotype was derived from standing variation in wild rice and selected for deepwater rice cultivation in Bangladesh.

PMID: 30002253 [PubMed - in process]

Genomic regions responsible for seminal and crown root lengths identified by 2D & 3D root system image analysis.

Sun, 04/22/2018 - 06:02
Related Articles

Genomic regions responsible for seminal and crown root lengths identified by 2D & 3D root system image analysis.

BMC Genomics. 2018 Apr 20;19(1):273

Authors: Uga Y, Assaranurak I, Kitomi Y, Larson BG, Craft EJ, Shaff JE, McCouch SR, Kochian LV

Abstract
BACKGROUND: Genetic improvement of root system architecture is a promising approach for improved uptake of water and mineral nutrients distributed unevenly in the soil. To identify genomic regions associated with the length of different root types in rice, we quantified root system architecture in a set of 26 chromosome segment substitution lines derived from a cross between lowland indica rice, IR64, and upland tropical japonica rice, Kinandang Patong, (IK-CSSLs), using 2D & 3D root phenotyping platforms.
RESULTS: Lengths of seminal and crown roots in the IK-CSSLs grown under hydroponic conditions were measured by 2D image analysis (RootReader2D). Twelve CSSLs showed significantly longer seminal root length than the recurrent parent IR64. Of these, 8 CSSLs also exhibited longer total length of the three longest crown roots compared to IR64. Three-dimensional image analysis (RootReader3D) for these CSSLs grown in gellan gum revealed that only one CSSL, SL1003, showed significantly longer total root length than IR64. To characterize the root morphology of SL1003 under soil conditions, SL1003 was grown in Turface, a soil-like growth media, and roots were quantified using RootReader3D. SL1003 had larger total root length and increased total crown root length than did IR64, although its seminal root length was similar to that of IR64. The larger TRL in SL1003 may be due to increased crown root length.
CONCLUSIONS: SL1003 carries an introgression from Kinandang Patong on the long arm of chromosome 1 in the genetic background of IR64. We conclude that this region harbors a QTL controlling crown root elongation.

PMID: 29678154 [PubMed - in process]

Resistance to Multiple Temperate and Tropical Stem and Sheath Diseases of Rice.

Tue, 03/06/2018 - 07:56

Resistance to Multiple Temperate and Tropical Stem and Sheath Diseases of Rice.

Plant Genome. 2018 Mar;11(1):

Authors: Rosas JE, Martínez S, Blanco P, Pérez de Vida F, Bonnecarrère V, Mosquera G, Cruz M, Garaycochea S, Monteverde E, McCouch S, Germán S, Jannink JL, Gutiérrez L

Abstract
Stem rot and aggregated sheath spot are the two major stem and sheath diseases affecting rice (Oryza sativa L.) in temperate areas. A third fungal disease, sheath blight, is a major disease in tropical areas. Resistance to these diseases is a key objective in rice breeding programs but phenotyping is challenged by the confounding effects of phenological and morphological traits such as flowering time (FT) and plant height (PH). This study sought to identify quantitative trait loci (QTL) for resistance to these three diseases after removing the confounding effects of FT and PH. Two populations of advanced breeding germplasm, one with 316 tropical japonica and the other with 325 indica genotypes, were evaluated in field and greenhouse trials for resistance to the diseases. Phenotypic means for field and greenhouse disease resistance, adjusted by FT and PH, were analyzed for associations with 29,000 single nucleotide polymorphisms (SNPs) in tropical japonica and 50,000 SNPs in indica. A total of 29 QTL were found for resistance that were not associated with FT or PH. Multilocus models with selected resistance-associated SNPs were fitted for each disease to estimate their effects on the other diseases. A QTL on chromosome 9 accounted for more than 15% of the phenotypic variance for the three diseases. When resistance-associated SNPs at this locus from both the tropical japonica and indica populations were incorporated into the model, resistance was improved for all three diseases with little impact on FT and PH.

PMID: 29505639 [PubMed - in process]

Redefining 'stress resistance genes', and why it matters.

Fri, 02/02/2018 - 07:32
Related Articles

Redefining 'stress resistance genes', and why it matters.

J Exp Bot. 2016 10;67(19):5588-5591

Authors: Maron LG, Piñeros MA, Kochian LV, McCouch SR

PMID: 27702993 [PubMed - indexed for MEDLINE]

Plant genetic resources for food and agriculture: opportunities and challenges emerging from the science and information technology revolution.

Wed, 01/24/2018 - 08:01

Plant genetic resources for food and agriculture: opportunities and challenges emerging from the science and information technology revolution.

New Phytol. 2018 Jan 23;:

Authors: Halewood M, Chiurugwi T, Sackville Hamilton R, Kurtz B, Marden E, Welch E, Michiels F, Mozafari J, Sabran M, Patron N, Kersey P, Bastow R, Dorius S, Dias S, McCouch S, Powell W

Abstract
Contents Summary I. II. III. IV. V. VI. ORCID References SUMMARY: Over the last decade, there has been an ongoing revolution in the exploration, manipulation and synthesis of biological systems, through the development of new technologies that generate, analyse and exploit big data. Users of Plant Genetic Resources (PGR) can potentially leverage these capacities to significantly increase the efficiency and effectiveness of their efforts to conserve, discover and utilise novel qualities in PGR, and help achieve the Sustainable Development Goals (SDGs). This review advances the discussion on these emerging opportunities and discusses how taking advantage of them will require data integration and synthesis across disciplinary, organisational and international boundaries, and the formation of multi-disciplinary, international partnerships. We explore some of the institutional and policy challenges that these efforts will face, particularly how these new technologies may influence the structure and role of research for sustainable development, ownership of resources, and access and benefit sharing. We discuss potential responses to political and institutional challenges, ranging from options for enhanced structure and governance of research discovery platforms to internationally brokered benefit-sharing agreements, and identify a set of broad principles that could guide the global community as it seeks or considers solutions.

PMID: 29359808 [PubMed - as supplied by publisher]

Large-scale deployment of a rice 6 K SNP array for genetics and breeding applications.

Fri, 09/01/2017 - 07:36

Large-scale deployment of a rice 6 K SNP array for genetics and breeding applications.

Rice (N Y). 2017 Aug 30;10(1):40

Authors: Thomson MJ, Singh N, Dwiyanti MS, Wang DR, Wright MH, Perez FA, DeClerck G, Chin JH, Malitic-Layaoen GA, Juanillas VM, Dilla-Ermita CJ, Mauleon R, Kretzschmar T, McCouch SR

Abstract
BACKGROUND: Fixed arrays of single nucleotide polymorphism (SNP) markers have advantages over reduced representation sequencing in their ease of data analysis, consistently higher call rates, and rapid turnaround times. A 6 K SNP array represents a cost-benefit "sweet spot" for routine genetics and breeding applications in rice. Selection of informative SNPs across species and subpopulations during chip design is essential to obtain useful polymorphism rates for target germplasm groups. This paper summarizes results from large-scale deployment of an Illumina 6 K SNP array for rice.
RESULTS: Design of the Illumina Infinium 6 K SNP chip for rice, referred to as the Cornell_6K_Array_Infinium_Rice (C6AIR), includes 4429 SNPs from re-sequencing data and 1571 SNP markers from previous BeadXpress 384-SNP sets, selected based on polymorphism rate and allele frequency within and between target germplasm groups. Of the 6000 attempted bead types, 5274 passed Illumina's production quality control. The C6AIR was widely deployed at the International Rice Research Institute (IRRI) for genetic diversity analysis, QTL mapping, and tracking introgressions and was intensively used at Cornell University for QTL analysis and developing libraries of interspecific chromosome segment substitution lines (CSSLs) between O. sativa and diverse accessions of O. rufipogon or O. meridionalis. Collectively, the array was used to genotype over 40,000 rice samples. A set of 4606 SNP markers was used to provide high quality data for O. sativa germplasm, while a slightly expanded set of 4940 SNPs was used for O. sativa X O. rufipogon populations. Biparental polymorphism rates were generally between 1900 and 2500 well-distributed SNP markers for indica x japonica or interspecific populations and between 1300 and 1500 markers for crosses within indica, while polymorphism rates were lower for pairwise crosses within U.S. tropical japonica germplasm. Recently, a second-generation array containing ~7000 SNP markers, referred to as the C7AIR, was designed by removing poor-performing SNPs from the C6AIR and adding markers selected to increase the utility of the array for elite tropical japonica material.
CONCLUSIONS: The C6AIR has been successfully used to generate rapid and high-quality genotype data for diverse genetics and breeding applications in rice, and provides the basis for an optimized design in the C7AIR.

PMID: 28856618 [PubMed]

Functional properties of an alternative, tissue-specific promoter for rice NADPH-dependent dihydroflavonol reductase.

Sat, 08/26/2017 - 08:20

Functional properties of an alternative, tissue-specific promoter for rice NADPH-dependent dihydroflavonol reductase.

PLoS One. 2017;12(8):e0183722

Authors: Kim J, Lee HJ, Jung YJ, Kang KK, Tyagi W, Kovach M, Sweeney M, McCouch S, Cho YG

Abstract
NADPH-dependent dihydroflavonol reductase (DFR) plays an important role in both anthocyanin biosynthesis and proanthocyanidin synthesis in plants. A specific and quantitative RT-PCR assay for transcription from the DFR promoter detected high expression with limited variability in rice tissues. A 440 bp minimal promoter region was identified by transfection of β-glucuronidase (GUS) reporter constructs into Jeokjinju variety. Alignment of the region with orthologous promoters revealed three conserved segments containing both bHLH (-386 to -381) and Myb (-368 to -362) binding sites. Transfection of β-glucuronidase constructs with targeted point mutations in the minimal promoter defined two sites important for promoter function to the transcription factor binding consensus sequences. The expression study showed that the bHLH binding domain (-386 to -381) is essential for DFR expression, and that a Myb binding domain (-368 to -362) is also required for full expression of the DFR gene, while the two bHLH binding domains (-104 to -99 and -27 to -22) nearest to the transcriptional start site are not necessary for DFR expression.

PMID: 28841686 [PubMed - in process]

Metabolomics and genomics combine to unravel the pathway for the presence of fragrance in rice.

Sun, 08/20/2017 - 06:26

Metabolomics and genomics combine to unravel the pathway for the presence of fragrance in rice.

Sci Rep. 2017 Aug 18;7(1):8767

Authors: Daygon VD, Calingacion M, Forster LC, Voss JJ, Schwartz BD, Ovenden B, Alonso DE, McCouch SR, Garson MJ, Fitzgerald MA

Abstract
Since it was first characterised in 1983, 2-acetyl-1-pyrroline (2AP) has been considered to be the most important aroma compound in rice. In this study, we show four other amine heterocycles: 6-methyl, 5-oxo-2,3,4,5-tetrahydropyridine (6M5OTP), 2-acetylpyrrole, pyrrole and 1-pyrroline, that correlate strongly with the production of 2AP, and are present in consistent proportions in a set of elite aromatic rice varieties from South East Asia and Australia as well as in a collection of recombinant inbred lines (RILs) derived from indica Jasmine-type varieties, Australian long grain varieties (temperate japonica) and Basmati-type rice (Grp V). These compounds were detected through untargeted metabolite profiling by two-dimensional gas chromatography-time-of-flight mass spectrometry (GC × GC-TOF-MS), and their identity were confirmed by comparison with authentic standards analysed using gas chromatography mass spectrometry (GC-MS) and High Resolution GC × GC-TOF-MS (GC × GC HRT-4D). Genome-wide association analysis indicates that all compounds co-localised with a single quantitative trait locus (QTL) that harbours the FGR gene responsible for the production of GABA. Together, these data provide new insights into the production of 2AP, and evidence for understanding the pathway leading to the accumulation of aroma in fragrant rice.

PMID: 28821745 [PubMed - in process]

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