Molecular Marker-Based Selection Tools in Spring Bread Wheat Improvement: CIMMYT Experience and Prospects

Dreisigacker, Susanne; Sukumaran, Sivakumar; Guzmán, Carlos; He, Xinyao; Lan, Caixa; Bonnett, David; Crossa, José

doi:10.1007/978-3-319-27090-6_16

Cited by 36 publications

(29 citation statements)

References 205 publications

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“…However, association of Vrn-A1 with seedling resistance to tan spot and its association with spot blotch resistance even after excluding the effect of days to flowering ( Singh et al., 2018 ) implies its possible linkage with an unknown disease resistance gene or its pleiotropic role in resistance to tan spot ( Hu et al., 2019 ). In CIMMYT spring wheat genotypes, the vrn-A1 allele for late flowering and tan spot resistance is almost fixed ( Dreisigacker et al., 2016 ), which is supportive of tan spot resistance and may have contributed to a good level of tan spot resistance in CIMMYT germplasm.…”

Section: Discussionmentioning

confidence: 99%

Association Mapping of Seedling Resistance to Tan Spot (Pyrenophora tritici-repentis Race 1) in CIMMYT and South Asian Wheat Germplasm

Phuke¹,

Juliana

et al. 2020

Front. Plant Sci.

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Tan spot caused by Pyrenophora tritici-repentis ( Ptr ) is an important disease of wheat in many wheat producing areas of the world. A genome wide association study (GWAS) was conducted using 11,401 SNP markers of the Illumina Infinium 15K Bead Chip with whole genome coverage to identify genomic regions associated with resistance to tan spot in a diverse panel of 184 wheat genotypes originating from South Asia and CIMMYT. The GWAS panel was phenotyped for seedling resistance to tan spot with Ptr race 1 in two greenhouse experiments. Besides CIMMYT germplasm, several lines from South Asia (India, Bangladesh and Nepal) showed good degree of resistance to tan spot. Association mapping was conducted separately for individual experiments and for pooled data using mixed linear model (MLM) and Fixed and random model Circulating Probability Unification (FarmCPU) model; no significant MTAs were recorded through the MLM model, whereas FarmCPU model reported nine significant MTAs located on chromosomes 1B, 2A, 2B, 3B, 4A, 5A, 5B, 6A, and 7D. The long arms of chromosomes 5A and 5B were consistent across both environments, in which the Vrn-A1 locus was found in identified region of chromosome 5A, and MTA at IACX9261 on 5BL appears to represent the resistance gene tsn 1 . MTAs observed on chromosomes 1B, 2A, 2B, 3B, 4A, 6A, and 7D have not been reported previously and are likely novel.

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Section: Discussionmentioning

confidence: 99%

Association Mapping of Seedling Resistance to Tan Spot (Pyrenophora tritici-repentis Race 1) in CIMMYT and South Asian Wheat Germplasm

Phuke¹,

Juliana

et al. 2020

Front. Plant Sci.

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“…Although unfeasible for direct selection in breeding programs due to the complexity of manipulating phenological phases, there is an increased use of marker assisted selection techniques that allow breeding programs to incorporate further improvement from complex traits (e.g. fruiting efficiency) to current elite lines ( Dreisigacker et al, 2016 ). The analysis of the relationship showed that within this set of elite lines, traits other than duration of stem elongation phase were determining fruiting efficiency, but that the maximum possible value of fruiting efficiency would be only achievable with relatively long periods of stem elongation.…”

Section: Discussionmentioning

confidence: 99%

Variation in developmental patterns among elite wheat lines and relationships with yield, yield components and spike fertility

González-Navarro

Griffiths

Molero

et al. 2016

Field Crops Research

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“…For the last three decades, molecular markers have acted as a versatile genetic tool in basic and applied research including studies on domestication, phylogenetic analysis, genetic diversity, genetic mapping, gene cloning, marker‐assisted selection, and genomic prediction (Dreisigacker et al., ; Rasheed et al., ). Molecular marker techniques started with the low‐throughput restriction fragment length polymorphism (RFLP) and recently peaked into the single nucleotide polymorphism (SNP) markers based on the next‐generation sequencing approaches.…”

Section: Introductionmentioning

confidence: 99%

Comparison of array‐ and sequencing‐based markers for genome‐wide association mapping and genomic prediction in spring wheat

Liu¹,

Sukumaran²,

Jarquín

et al. 2020

Crop Science

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Notwithstanding the rapid development of high‐throughput genotyping platforms in recent years, several plant research programs find themselves in a dilemma of which marker system to use while conducting genome‐wide association studies (GWAS) and genomic selection. To gain insight into this, we genotyped an elite spring wheat (Triticum aestivum L.) association mapping initiative (WAMI, 287 lines) panel with various array‐based platforms—(i) Diversity Arrays Technology (DArT), (ii) Illumina Infinium BeadChip wheat 9K iSelect (I9K), and (iii) wheat 90K iSelect (I90K)—and sequencing‐based platform DArTseq. The raw markers refined using a common set of protocols after the bioinformatics analysis were compared by performing a series of genetic analyses: estimates of genetic diversity through nucleotide diversity (π), population structure and familial relatedness, marker‐trait associations (MTAs), and genomic prediction. Results indicated that genetic data from DArTseq consisted of a high proportion of rare allele markers (1% < minor allele frequency < 5%). The nucleotide diversity statistic (π) was higher for the array‐based single nucleotide polymorphisms (SNPs) than sequencing‐based SNPs. The I9K detected population structure caused by the variety ‘Kauz’ and grouped the population into two subgroups, whereas I90K, DArT, and DArTseq detected five subgroups driven by key pedigrees. The I90K with the highest marker density identified a high number of significant MTAs. Genomic prediction accuracy varied among traits; DArTseq and I90K produced similar prediction accuracies. Among the marker platforms compared, I90K was the best genotyping platform for GWAS, and DArTseq—given the low cost per SNP—was the best platform for genomic prediction in spring wheat.

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Molecular Marker-Based Selection Tools in Spring Bread Wheat Improvement: CIMMYT Experience and Prospects

Cited by 36 publications

References 205 publications

Association Mapping of Seedling Resistance to Tan Spot (Pyrenophora tritici-repentis Race 1) in CIMMYT and South Asian Wheat Germplasm

Association Mapping of Seedling Resistance to Tan Spot (Pyrenophora tritici-repentis Race 1) in CIMMYT and South Asian Wheat Germplasm

Variation in developmental patterns among elite wheat lines and relationships with yield, yield components and spike fertility

Comparison of array‐ and sequencing‐based markers for genome‐wide association mapping and genomic prediction in spring wheat

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