Genetic diversity, linkage disequilibrium, and population structure in a panel of Brazilian rice accessions

Venske, Eduardo; Stafen, Cássia Fernanda; Oliveira, Victoria Freitas de; Maia, Luciano Carlos da; Magalhaes, A. M. de; McNally, Kenneth L.; Oliveira, Antônio Costa de; Pegoraro, Camila

doi:10.1007/s13353-018-0475-0

Cited by 4 publications

(5 citation statements)

References 19 publications

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“…Population structure and linkage disequilibrium, as well as genetic diversity for Fe in grain for this panel were previously reported by Venske et al (2019) and Oliveira et al (2021). Based on the Bonferroni correction methods, a threshold of 5 was applied to the statistic -log10 (p-value) for declaring significant QTLs.…”

supporting

confidence: 84%

“…Genotyping was performed at the Genotyping Services Laboratory of the International Rice Research Institute, Philippines, using 7098 single nucleotide polymorphisms (SNP) markers from 7K Infinium SNP genotyping platform (Illumina). Genotyping data were filtered using Tassel v.5.2.41 (Bradbury et al, 2007), by which accessions with call rates < 0.75, SNPs with missing data > 20%, and minor allele frequency ≤ 5% were removed, remaining 4093 SNP markers, as presented by Venske et al (2019).…”

mentioning

confidence: 99%

“…The population structure matrix was generated from the Bayesian clustering method using the fastStructure software (Raj et al, 2014). From k=1 to k=10, the model components used to explain the structure in data were selected with the command chooseK.py (Venske et al, 2019). Kinship matrix was obtained using the Tassel v.5.2.44 software (Bradbury et al, 2007).…”

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confidence: 99%

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Genome-wide association of iron content in rice grains grown in Southern Brazil

Oliveira,

Venske,

Stafen

et al. 2023

Pesq. agropec. bras.

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The objective of this work was to map the chromosomal regions responsible for iron accumulation in rice grains, in Southern Brazil. Eighty-one rice accessions were genotyped and phenotyped for Fe accumulation. Single nucleotide polymorphisms were mapped in the whole grain on chromosomes 1, 5, 6, and 10, from which 13 candidate genes were identified. Some of the genes, such as O s10g040680 0, seem to have a relationship with Fe homeostasis, while others are related to other metabolic processes or have an unknown function.

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confidence: 84%

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confidence: 99%

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Genome-wide association of iron content in rice grains grown in Southern Brazil

Oliveira,

Venske,

Stafen

et al. 2023

Pesq. agropec. bras.

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“…average extent of LD in O. sativa ranges from approximately 100 kb in aus and indica, to 500 kb in tropical japonica and temperate japonica [23,25]. USDA scientists have created core and mini-core collections of rice germplasm for use in association mapping studies [8,9].…”

Section: Plos Onementioning

confidence: 99%

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

et al. 2020

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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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“…Moreover, it has been well illustrated through genealogy analysis that most Brazilian elite rice cultivars have been originated from only very few ancestors, in breeding programmes which have started just as few as three or four decades ago (Rabelo, Guimarães, Pinheiro, & Silva, 2015; Raimondi, Marschalek, & Nodari, 2014; Rangel, Guimarães, & Neves, 1996). However, another study has already identified this contrast, clustering 'BR Irga 409' and 'Epagri 108' in different groups, applying different clustering approaches (Venske et al., 2019).…”

Section: Resultsmentioning

confidence: 99%

ATG genes, new players on early Fe toxicity response in rice (Oryza sativa)

et al. 2020

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Rice is a staple food for more than half of the world's population and is directly associated with food security. An additional 100 million tonnes of rice production is estimated to be needed to meet the demand of 9.1 billion people by 2050 (Jaggard, Qi, & Ober, 2010; Mahender, Swamy, Anandan, & Ali, 2019). However, the genetic gain for rice grain yield has stagnated over the past decade, resulting in productivity plateaus even in favourable environments. Also, rice growth and development faces different abiotic stresses such as drought, cold, heat, salinity, acidic soils, nutritional deficiencies, and soil toxicities, which cause significant losses in grain yield (Mahender et al., 2019). To deal with the environmental challenges, a better understanding of genetic responses to abiotic stress is needed, particularly those mechanisms that promote plant survival at the cellular and organism level. Autophagy (meaning self-eating) is one of these mechanisms, in which macromolecules and cellular components are recycled into vacuoles for reuse. This process is crucial for the maintenance of cellular homeostasis, acts on normal conditions, and is stimulated under adverse conditions (Avin-Wittenberg, 2019; Signorelli, Tarkowski, Van den Ende, & Bassham, 2019). In plants, autophagy has been described in Arabidopsis

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Genetic diversity, linkage disequilibrium, and population structure in a panel of Brazilian rice accessions

Cited by 4 publications

References 19 publications

Genome-wide association of iron content in rice grains grown in Southern Brazil

Genome-wide association of iron content in rice grains grown in Southern Brazil

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

ATG genes, new players on early Fe toxicity response in rice (Oryza sativa)

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