Genetic diversity and association mapping of agronomic yield traits in eighty six synthetic hexaploid wheat

Hong-xia, Zhang; Zhang, Fangning; Li, Guidong; Zhang, Sini; Zhang, Zigang; Ma, Lingjian

doi:10.1007/s10681-017-1887-3

Cited by 11 publications

(19 citation statements)

References 67 publications

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“…Genetic advance in wheat breeding has been frequently hindered by negative correlations among yield components that have been often observed in segregating populations and germplasm collections (see reviews [ 6 , 13 ]). Particularly, the phenotypic correlation between KNS and TKW has been generally found negative even though not always consistent [ 14 – 16 ], while the correlations between GYS and the sub-components KNS and TKW have been always found consistent and positives. Phenotypic correlations may be attributed to genetic linkage, pleiotropy, environmental factors, and yield component compensations due to competition for a common limited nutrient supply.…”

Section: Introductionmentioning

confidence: 99%

“…Mapping studies for the several components of grain yield potential have identified QTL on all 21 chromosomes of wheat genome by classical linkage mapping using biparental populations and by GWAS using wheat collections (see reviews [ 32 – 34 ]). Major QTL associated to thousand grain weight were detected on chromosomes 1B, 2A, 2D, 3A, 3B, 4B, 4D, 5A, 5B, 6A, 7B and 7D [ 16 , 35 – 52 ], and QTL for grain number per spike on chromosomes 2B, 3B, 4A, 4B, 4D, 5A, 5D, 7A and 7B [ 33 , 36 – 38 , 43 , 48 , 53 – 59 ]. Current development of advanced biotechnologies have recently allowed the identification of some key genes for significant increases in grain weight or grain number per spike in wheat by comparative genomics with rice [ 60 ].…”

Section: Introductionmentioning

confidence: 99%

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Genetic dissection of the relationships between grain yield components by genome-wide association mapping in a collection of tetraploid wheats

Mangini

Gadaleta²,

Colasuonno³

et al. 2018

PLoS ONE

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Increasing grain yield potential in wheat has been a major target of most breeding programs. Genetic advance has been frequently hindered by negative correlations among yield components that have been often observed in segregant populations and germplasm collections. A tetraploid wheat collection was evaluated in seven environments and genotyped with a 90K SNP assay to identify major and stable quantitative trait loci (QTL) for grain yield per spike (GYS), kernel number per spike (KNS) and thousand-kernel weight (TKW), and to analyse the genetic relationships between the yield components at QTL level. The genome-wide association analysis detected eight, eleven and ten QTL for KNS, TKW and GYS, respectively, significant in at least three environments or two environments and the mean across environments. Most of the QTL for TKW and KNS were found located in different marker intervals, indicating that they are genetically controlled independently by each other. Out of eight KNS QTL, three were associated to significant increases of GYS, while the increased grain number of five additional QTL was completely or partially compensated by decreases in grain weight, thus producing no or reduced effects on GYS. Similarly, four consistent and five suggestive TKW QTL resulted in visible increase of GYS, while seven additional QTL were associated to reduced effects in grain number and no effects on GYS. Our results showed that QTL analysis for detecting TKW or KNS alleles useful for improving grain yield potential should consider the pleiotropic effects of the QTL or the association to other QTLs.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Genetic dissection of the relationships between grain yield components by genome-wide association mapping in a collection of tetraploid wheats

Mangini

Gadaleta²,

Colasuonno³

et al. 2018

PLoS ONE

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“…However, Cavanagh et al (2013) [35] reported that the majority of SNPs were located in the A genome and the lowest number in the D genome. Zhang et al (2017) [10] used 271 SSR markers to detect the highest number of alleles in the D genome, the lowest number were in the A genome. The highest average number of alleles was detected in the B genome, followed by the D genome and the A genome, using 17 SSR markers, as reported by Salem et al (2015) [36].…”

Section: Discussionmentioning

confidence: 99%

“…However, domestication and strong selection pressure by humans, and the use of modern breeding techniques, have increasingly narrowed the gene pool of wheat [8,9]. Therefore, it is essential to enrich wheat germplasm resources by introducing favorable mutations into the cultivated gene pool [8,9,10].…”

Section: Introductionmentioning

confidence: 99%

Genetic Diversity and Population Structure of Asian and European Common Wheat Accessions Based on Genotyping-By-Sequencing

Yang

Tan

et al. 2019

Preprint

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Background Availability of information on the genetic diversity and population structure of germplasm facilitates its use in wheat breeding programs. Recently, with the development of next-generation sequencing technology, genotyping-by-sequencing (GBS) has been used as a high-throughput and cost-effective molecular tool for examination of the genetic diversity of wheat breeding lines. In this study, GBS was used to characterize a population of 180 accessions of common wheat originating from Asia and Europe between the latitudes 30° and 45°N.Results In total, 24,767 high-quality single-nucleotide polymorphism (SNP) markers were used for analysis of genetic diversity and population structure. The B genome contained the highest number of SNPs, followed by the A and D genomes. The polymorphism information content ranged from 0.1 to 0.4, with an average of 0.26. The distribution of SNPs markers on the 21 chromosomes ranged from 243 on chromosome 4D to 2,337 on chromosome 3B. Structure and cluster analyses divided the panel of accessions into two subgroups (G1 and G2). G1 principally consisted of European and partial Asian accessions, and G2 comprised mainly accessions from the Middle East and partial Asia. Molecular analysis of variance showed that the genetic variation was greater within groups (99%) than between groups (1%). Comparison of the two subgroups indicated that G1 and G2 contained a high level of genetic diversity. The genetic diversity of G2 was higher as indicated by the Shannon’s information index ( I ) = 0.512, diversity index ( h ) = 0.334, observed heterozygosity ( H o ) = 0.226, and unbiased diversity index (uh) = 0.338.Conclusion The present results will not only help breeders to understand the genetic diversity of wheat germplasm on the Eurasian continent between the latitudes of 30° and 45°N, but also provide valuable information for wheat genetic improvement through introgression of novel genetic variation in this region.

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“…The average yield of the SHW-derived cultivars was 13.5% higher than that of the non-synthetic cultivars (Tang et al 2017). Recently, phenotypic and genetic diversity were evaluated, and favorable alleles or QTLs of yield-related traits were identified in the SHW varieties (lines) (Emebiri et al 2015;Das et al 2016;Zhang et al 2017;Yan et al 2017). In our lab, a synthetic hexaploid wheat SHW-L1 was used to insert alien alleles into common wheat.…”

Section: Introductionmentioning

confidence: 99%

Genome-wide association analysis of kernel morphology in breeding lines derived from synthetic hexaploid wheat in Qinghai Province, China

Wang

Cao

Chen

et al. 2018

Cereal Research Communications

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Wheat kernel morphology is a very important trait for wheat yield improvement. This is the first report of association analysis of kernel morphology traits in wheat breeding lines. In Qinghai, China, the research described here involved genome-wide association analysis in breeding lines derived from synthetic hexaploid wheat with a mixed linear model to identify the quantitative trait loci (QTLs) related to kernel morphology. The 8033 effective Diversity Array Technology (DArT) markers produced a genetic map of 5901.84 cM with an average density of 1.36 markers/cM. Population structure analysis classified 507 breeding lines into three groups by Bayesian structure analysis using unlinked markers. Linkage disequilibrium decay was observed with a map coverage of 2.78 cM. Marker-trait association analysis showed that 15 DArT markers for kernel morphology were detected, located on nine chromosomes, and explained 2.6%-4.0% of the phenotypic variation of kernel area (KA), kernel width (KW), kernel length (KL) and thousand-kernel weight (TKW). The marker 1139297 was related to both the KL and KA traits. Only six DArT markers were close to known QTLs. The parent SHW-L1 carried eight favored alleles, while other seven favored alleles were derived from elite common wheat cultivars. These QTLs, identified in elite breeding lines, should help us understand the kernel morphology trait better, and to provide germplasm for breeding new wheat cultivars for Qinghai Province or other regions.

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Genetic diversity and association mapping of agronomic yield traits in eighty six synthetic hexaploid wheat

Cited by 11 publications

References 67 publications

Genetic dissection of the relationships between grain yield components by genome-wide association mapping in a collection of tetraploid wheats

Genetic dissection of the relationships between grain yield components by genome-wide association mapping in a collection of tetraploid wheats

Genetic Diversity and Population Structure of Asian and European Common Wheat Accessions Based on Genotyping-By-Sequencing

Genome-wide association analysis of kernel morphology in breeding lines derived from synthetic hexaploid wheat in Qinghai Province, China

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