scholarly journals Identification of Single Nucleotide Polymorphism in TaSBEIII and Development of KASP Marker Associated With Grain Weight in Wheat

2021 ◽  
Vol 12 ◽  
Author(s):  
Ahsan Irshad ◽  
Huijun Guo ◽  
Shoaib Ur Rehman ◽  
Xueqing Wang ◽  
Jiayu Gu ◽  
...  
Keyword(s):  
Core Collection ◽  
Agronomic Traits ◽  
Higher Plants ◽  
Allelic Variation ◽  
Wheat Yield ◽  
Starch Synthesis ◽  
Grain Weight ◽  
Branch Points ◽  
Mini Core Collection ◽  
Kasp Marker

Manipulation of genes involved in starch synthesis could significantly affect wheat grain weight and yield. The starch-branching enzyme (SBE) catalyzes the formation of branch points by cleaving the α-1,4 linkage in polyglucans and reattaching the chain via an α-1,6 linkage. Three types of SBE isoforms (SBEI, SBEII, and SBEIII) exist in higher plants, with the number of SBE isoforms being species-specific. In this study, the coding sequence of the wheat TaSBEIII gene was amplified. After the multiple sequence alignment of TaSBEIII genome from 20 accessions in a wheat diversity panel, one SNP was observed in TaSBEIII-A, which formed the allelic marker allele-T. Based on this SNP at 294 bp (C/T), a KASP molecular marker was developed to distinguish allelic variation among the wheat genotypes for thousand grain weight (TGW). The results were validated using 262 accessions of mini core collection (MCC) from China, 153 from Pakistan, 53 from CIMMYT, and 17 diploid and 18 tetraploid genotypes. Association analysis between TaSBEIII-A allelic variation and agronomic traits found that TaSBEIII-A was associated with TGW in mini core collection of China (MCC). The accessions possessing Allele-T had higher TGW than those possessing Allele-C; thus, Allele-T was a favorable allelic variation. By analyzing the frequency of the favorable allelic variation Allele-T in MCC, it increased from pre-1950 (25%) to the 1960s (45%) and increased continuously from 1960 to 1990 (80%). The results suggested that the KASP markers can be utilized in grain weight improvement, which ultimately improves wheat yield by marker-assisted selection in wheat breeding. The favorable allelic variation allele-T should be valuable in enhancing grain yield by improving the source and sink simultaneously. Furthermore, the newly developed KASP marker validated in different genetic backgrounds could be integrated into a breeding kit for screening high TGW wheat.

scholarly journals EcoTILLING Reveals Natural Allelic Variations in Starch Synthesis Key Gene TaSSIV and Its Haplotypes Associated with Higher Thousand Grain Weight

Genes ◽  
2019 ◽  
Vol 10 (4) ◽  
pp. 307 ◽  
Author(s):  
Irshad ◽  
Guo ◽  
Zhang ◽  
Gu ◽  
Zhao ◽  
...  
Keyword(s):  
Core Collection ◽  
Wheat Yield ◽  
Starch Synthesis ◽  
Wheat Breeding ◽  
Grain Weight ◽  
Wheat Starch ◽  
Main Function ◽  
Thousand Grain Weight ◽  
Granule Formation ◽  
Mini Core Collection

Wheat is a staple food commodity grown worldwide, and wheat starch is a valuable source of energy and carbon that constitutes 80% of the grain weight. Manipulation of genes involved in starch synthesis significantly affects wheat grain weight and yield. TaSSIV plays an important role in starch synthesis and its main function is granule formation. To mine and stack more favorable alleles, single nucleotide polymorphisms (SNPs) of TaSSIV-A, B, and D were investigated across 362 wheat accessions by Ecotype-Targeting Induced Local Lesions IN Genome (EcoTILLING). As a result, a total of 38 SNPs in the amplified regions of three TaSSIV genes were identified, of which 10, 15, and 13 were in TaSSIV-A, B, and D, respectively. These 38 SNPs were evaluated by using KASP and six SNPs showed an allele frequency >5% whereas the rest were <5%, i.e., considered to be minor alleles. In the Chinese mini core collection, three haplotypes were detected for TaSSIV–A and three for TaSSIV–B. The results of an association study in the Chinese mini core collection with thousand grain weight (TGW) and spike length (SPL) showed that Hap-2-1A was significantly associated with TGW and Hap-3-1B with SPL. Allelic frequency and geographic distribution indicated that the favored haplotype (Hap-2-1A) has been positively selected in Chinese wheat breeding. These results suggested that the Kompetitive Allele Specific PCR (KASP) markers can be applied in starch improvement to ultimately improve wheat yield by marker assisted selection in wheat breeding.

scholarly journals Genome-wide association studies of ionomic and agronomic traits in USDA mini core collection of rice and comparative analyses of different mapping methods

2020 ◽  
Author(s):  
Shuai Liu ◽  
Hua Zhong ◽  
Xiaoxi Meng ◽  
Tong Sun ◽  
Yangsheng Li ◽  
...  
Keyword(s):  
Heavy Metal ◽  
Candidate Genes ◽  
Metal Contamination ◽  
Core Collection ◽  
Heavy Metal Contamination ◽  
Agronomic Traits ◽  
Association Studies ◽  
P Value ◽  
Genome Wide Association Studies ◽  
Mini Core Collection

Abstract BackgroundRice is an important human staple food vulnerable to heavy metal contamination leading to serious concerns. High yield with low heavy metal contamination is a common but highly challenging goal for rice breeders worldwide due to lack of genetic knowledge and markers. ResultsTo identify candidate QTLs and develop molecular markers for rice yield and heavy metal content, a total of 191 accessions from the USDA Rice mini-core collection with over 3.2 million SNPs were employed to investigate the QTLs. Sixteen ionomic and thirteen agronomic traits were analyzed utilizing two univariate (GLM and MLM) and two multivariate (MLMM and FarmCPU) GWAS methods. 106, 47, and 97 QTLs were identified for ionomics flooded, ionomics unflooded, and agronomic traits, respectively, with the criterium of p-value <1.53×10-8, which was determined by the Bonferroni correction for p-value of 0.05. While 49 (~20%) of the 250 QTLs were coinciding with previous reported QTLs/genes, about 201 (~80%) were new. In addition, several new candidate genes involved in ionomic and agronomic traits control were identified by analyzing the DNA sequence, gene expression, and the homologs of the QTL regions. Our results further showed that each of the four GWAS methods can identify unique as well as common QTLs, suggesting that using multiple GWAS methods can complement each other in QTL identification, especially by combining univariate and multivariate methods. ConclusionsWhile 49 previously reported QTLs/genes were rediscovered, over 200 new QTLs for ionomic and agronomic traits were found in the rice genome. Moreover, multiple new candidate genes for agronomic and ionomic traits were identified. This research provides novel insights into the genetic basis of both ionomic and agronomic variations in rice, establishing the foundation for marker development in breeding and further investigation on reducing heavy-metal contamination and improving crop yields. Finally, the comparative analysis of the GWAS methods showed that each method has unique features and different methods can complement each other.

scholarly journals Genomic tools and germplasm diversity for chickpea improvement

2011 ◽  
Vol 9 (01) ◽  
pp. 45-58 ◽  
Author(s):  
Hari D. Upadhyaya ◽  
Mahendar Thudi ◽  
Naresh Dronavalli ◽  
Neha Gujaria ◽  
Sube Singh ◽  
...  
Keyword(s):  
Core Collection ◽  
Large Scale ◽  
Agronomic Traits ◽  
Genetic Maps ◽  
Genetic Enhancement ◽  
Grain Legume ◽  
Genomic Resources ◽  
Mini Core Collection ◽  
Reference Set ◽  
Germplasm Accessions

Chickpea is the third most important grain legume grown in the arid and semi-arid regions of the world. In spite of vast germplasm accessions available in different genebanks, there has been very limited use of these accessions in genetic enhancement of chickpea. However, in recent years, specialized germplasm subsets such as global composite collection, core collection, mini core collection and reference set have been developed. In parallel, significant genomic resources such as molecular markers including simple sequence repeats (SSRs), single nucleotide polymorphisms (SNPs), diversity arrays technology (DArT) and transcript sequences, e.g. expressed sequence tags, short transcript reads, have been developed. By using SSR, SNP and DArT markers, integrated genetic maps have been developed. It is anticipated that the use of genomic resources and specialized germplasm subsets such as mini core collection and reference set will facilitate identification of trait-specific germplasm, trait mapping and allele mining for resistance to biotic and abiotic stresses and for agronomic traits. Advent of the next generation sequencing technologies coupled with advances in bioinformatics offers the possibility of undertaking large-scale sequencing of germplasm accessions so that modern breeding approaches such as genomic selection and breeding by design can be realized in near future for chickpea improvement.

scholarly journals Genotyping USDA Rice Mini-Core Collection With Functional Markers for Important Agronomic Traits

2021 ◽  
Author(s):  
Kehu Li ◽  
Yongyi Ge ◽  
Lily Yan Wang
Keyword(s):  
Physicochemical Properties ◽  
Core Collection ◽  
Biotic Resistance ◽  
Agronomic Traits ◽  
Brown Planthopper ◽  
Functional Markers ◽  
Rice Breeding ◽  
Breeding Programs ◽  
Exon 2 ◽  
Mini Core Collection

Abstract The USDA rice mini-core collection was established to capture the diversity of an entire collection of over 18,700 accessions of global origins for efficient germplasm evaluation and exploration. Previous studies have investigated its genetic diversity and population structure using genome-wide SSR markers. Many important agronomic traits that are fundamental to rice breeding programs, however, remain to be explored. Functional markers can be developed based on polymorphic sites within genes affecting phenotypic variation in, e.g., starch physicochemical properties, nutritional qualities and biotic resistance. These markers can be used for genotyping and hence differentiating phenotypes among rice accessions. In this study, we employed 12 pairs of functional markers (SNP and Indel) to genotype all 217 accessions constituting the USDA rice mini-core. These markers are highly associated with starch physicochemical properties (intron 1 G/C SNP, 23bp duplication in exon 2, exon 6 C/A SNP, exon 10 C/T SNP of Waxy gene, GC/TT SNPs of SSIIa gene, G/C SNP of SBE3 gene), glutelin content (3.5 kb deletion in Lgc1 gene), grain length (C/A SNP in GS3 gene), brown planthopper resistance (InDel in Bph 14 gene) and rice blast resistance (InDel in Pi54 and Pit gene). Using these functional markers, all the 217 accessions of the mini-core are characterized for aforementioned agronomic traits associated alleles/genes. The results of this study will help breeders select parental materials with desirable allele/gene combinations and phenotypes among mini-core accessions for rice breeding programs.

Association Analysis of Agronomic Traits and Resistance to Aspergillus flavus in the ICRISAT Peanut Mini-Core Collection

2013 ◽  
Vol 38 (6) ◽  
pp. 935-946 ◽  
Author(s):  
Li HUANG ◽  
Xiao-Ping REN ◽  
Xiao-Jie ZHANG ◽  
Yu-Ning CHEN ◽  
Hui-Fang JIANG
Keyword(s):  
Association Analysis ◽  
Aspergillus Flavus ◽  
Core Collection ◽  
Agronomic Traits ◽  
Mini Core Collection

scholarly journals Genome-wide association studies of ionomic and agronomic traits in USDA mini core collection of rice and comparative analyses of different mapping methods

2020 ◽  
Author(s):  
Shuai Liu ◽  
Hua Zhong ◽  
Xiaoxi Meng ◽  
Tong Sun ◽  
Yangsheng Li ◽  
...  
Keyword(s):  
Heavy Metal ◽  
Metal Contamination ◽  
Core Collection ◽  
Heavy Metal Contamination ◽  
Agronomic Traits ◽  
Rice Genome ◽  
P Value ◽  
Multivariate Methods ◽  
Genome Wide Association Studies ◽  
Mini Core Collection

Abstract Background: Rice is an important human staple food vulnerable to heavy metal contamination due to its unique physiology and growth environment. High yield with low heavy metal contamination is a common but highly challenging goal for rice breeders worldwide due to lack of genetic knowledge. To identify candidate QTLs for rice yield and heavy metal content, sixteen ionomic traits and thirteen agronomic traits of the USDA Rice mini-core collection were analyzed using both univariate and multivariate GWAS methods in this study. The USDA Rice Mini-Core Collection contains about 1% of the whole Rice Collection of the National Small Grains Collection (NSGC), USA.Results: Using the p-value <1.53×10-8, this criterium p-value was determined by the Bonferroni correction for p-value of 0.05, 106, 47, and 97 QTLs were identified for ionomics in flooded environment, unflooded environment, and agronomic traits, respectively. A large number of QTLs coincide well with previous report results while many of the QTLs are new QTLs, suggesting the efficiency of GWAS methods and the reliability of this study. Our results further showed that each of the four GWAS methods can identify unique as well as common QTLs. When univariate methods failed to identify QTLs for a trait, the multivariate methods frequently detected QTLs. However, when many QTLs were detected by univariate methods, the number of QTLs detected by multivariate methods were reduced in many cases. These analyses suggest that using multiple GWAS methods can complement each other in QTL identification. In addition, several candidate genes involved in ionomic and agronomic traits control were identified by analyzing the sequences of the candidate QTL regions.Conclusions: Significant QTLs for heavy metal, mineral, and agronomic traits are presented in the rice genome and some of them have been fine mapped in the rice genome in this study. This research provides novel insights into the genetic basis of both ionomic and agronomic variations in rice, establishing an important foundation for further studies on reducing heavy-metal contamination and improving crop yields. In addition, the comparison analysis of the GAWS methods showed that each method has unique feature and different method can complement each other.

scholarly journals Genome-wide association studies of ionomic and agronomic traits in USDA mini core collection of rice and comparative analyses of different mapping methods

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Shuai Liu ◽  
Hua Zhong ◽  
Xiaoxi Meng ◽  
Tong Sun ◽  
Yangsheng Li ◽  
...  
Keyword(s):  
Heavy Metal ◽  
Candidate Genes ◽  
Metal Contamination ◽  
Core Collection ◽  
Heavy Metal Contamination ◽  
Agronomic Traits ◽  
Association Studies ◽  
Rice Genome ◽  
Genome Wide Association Studies ◽  
Mini Core Collection

Abstract Background Rice is an important human staple food vulnerable to heavy metal contamination leading to serious concerns. High yield with low heavy metal contamination is a common but highly challenging goal for rice breeders worldwide due to lack of genetic knowledge and markers. Results To identify candidate QTLs and develop molecular markers for rice yield and heavy metal content, a total of 191 accessions from the USDA Rice mini-core collection with over 3.2 million SNPs were employed to investigate the QTLs. Sixteen ionomic and thirteen agronomic traits were analyzed utilizing two univariate (GLM and MLM) and two multivariate (MLMM and FarmCPU) GWAS methods. 106, 47, and 97 QTLs were identified for ionomics flooded, ionomics unflooded, and agronomic traits, respectively, with the criterium of p-value < 1.53 × 10− 8, which was determined by the Bonferroni correction for p-value of 0.05. While 49 (~ 20%) of the 250 QTLs were coinciding with previously reported QTLs/genes, about 201 (~ 80%) were new. In addition, several new candidate genes involved in ionomic and agronomic traits control were identified by analyzing the DNA sequence, gene expression, and the homologs of the QTL regions. Our results further showed that each of the four GWAS methods can identify unique as well as common QTLs, suggesting that using multiple GWAS methods can complement each other in QTL identification, especially by combining univariate and multivariate methods. Conclusions While 49 previously reported QTLs/genes were rediscovered, over 200 new QTLs for ionomic and agronomic traits were found in the rice genome. Moreover, multiple new candidate genes for agronomic and ionomic traits were identified. This research provides novel insights into the genetic basis of both ionomic and agronomic variations in rice, establishing the foundation for marker development in breeding and further investigation on reducing heavy-metal contamination and improving crop yields. Finally, the comparative analysis of the GWAS methods showed that each method has unique features and different methods can complement each other.

scholarly journals Variation for Photoperiod and Temperature Sensitivity in the Global Mini Core Collection of Sorghum

2021 ◽  
Vol 12 ◽  
Author(s):  
Hari D. Upadhyaya ◽  
M. Vetriventhan ◽  
Vania C. R. Azevedo
Keyword(s):  
Temperature Sensitivity ◽  
Rainy Season ◽  
Core Collection ◽  
Agronomic Traits ◽  
Temperature Sensitive ◽  
Short Day ◽  
Mini Core Collection ◽  
Long Day ◽  
Genomic Studies ◽  
Photoperiod Sensitive

Information on photoperiod and temperature sensitivity of sorghum germplasm is important to identify appropriate sources for developing cultivars with a broad adaptation. The sorghum mini core collection consisting of 242 accessions along with three control cultivars were evaluated for days to 50% flowering (DFL) and plant height in two long-day rainy and two short-day post-rainy seasons, and for grain yield and 100-seed weight in the two post-rainy seasons. Differences in DFL and cumulative growing degree days (CGDD) in the rainy and post-rainy seasons were used to classify the accessions for photoperiod and temperature sensitivity. Results revealed 18 mini core landraces as photoperiod and temperature insensitive (PTINS), 205 as photoperiod sensitive and temperature insensitive (PSTINS), and 19 as photoperiod and temperature-sensitive (PTS) sources. The 19 PTS sources and 80 PSTINS sources took less DFL in the long-day rainy seasons than in the short-day post-rainy season indicating their adaptation to the rainy season and a possible different mechanism than that trigger flowering in the short-day sorghums. In all three groups, several accessions with desirable combinations of agronomic traits were identified for use in the breeding programs to develop climate-resilient cultivars and for genomic studies to identify genes responsible for the photoperiod and temperature responses.

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