Identification of Earliness Per Se Flowering Time Locus in Spring Wheat through a Genome‐Wide Association Study

Sukumaran, Sivakumar; Lopes, Marta S.; Dreisigacker, Susanne; Dixon, Laura E.; Zikhali, Meluleki; Griffiths, Simon; Zheng, Bangyou; Chapman, Scott C.; Reynolds, M.P.

doi:10.2135/cropsci2016.01.0066

Cited by 37 publications

(32 citation statements)

References 94 publications

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“…The DB and DM QTNs on Chr 1B are compatible with previous findings on bread wheat (Fowler et al ., ). The Eps locus controlling flowering time in bread wheat maps on Chr 1D (Sukumaran et al ., ), at a genetic position overlapping our signal for DB, DM on the homoeologous Chr 1B (Table ). QTL for flowering time were already reported in durum wheat at around 40 cM on Chr 2A, in a position compatible to our signal (Maccaferri et al ., ; Mengistu et al ., ; Sanna et al ., ; Sukumaran et al ., ).…”

Section: Discussionsupporting

confidence: 62%

A large nested association mapping population for breeding and quantitative trait locus mapping in Ethiopian durum wheat

Kidane

Gesesse

Hailemariam

et al. 2019

Plant Biotechnology Journal

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Summary The Ethiopian plateau hosts thousands of durum wheat ( Triticum turgidum subsp. durum ) farmer varieties ( FV ) with high adaptability and breeding potential. To harness their unique allelic diversity, we produced a large nested association mapping ( NAM ) population intercrossing fifty Ethiopian FV s with an international elite durum wheat variety (Asassa). The Ethiopian NAM population (Et NAM ) is composed of fifty interconnected bi‐parental families, totalling 6280 recombinant inbred lines ( RIL s) that represent both a powerful quantitative trait loci ( QTL ) mapping tool, and a large pre‐breeding panel. Here, we discuss the molecular and phenotypic diversity of the Et NAM founder lines, then we use an array featuring 13 000 single nucleotide polymorphisms ( SNP s) to characterize a subset of 1200 Et NAM RIL s from 12 families. Finally, we test the usefulness of the population by mapping phenology traits and plant height using a genome wide association ( GWA ) approach. Et NAM RIL s showed high allelic variation and a genetic makeup combining genetic diversity from Ethiopian FV s with the international durum wheat allele pool. Et NAM SNP data were projected on the fully sequenced AB genome of wild emmer wheat, and were used to estimate pairwise linkage disequilibrium ( LD ) measures that reported an LD decay distance of 7.4 Mb on average, and balanced founder contributions across Et NAM families. GWA analyses identified 11 genomic loci individually affecting up to 3 days in flowering time and more than 1.6 cm in height. We argue that the Et NAM is a powerful tool to support the production of new durum wheat varieties targeting local and global agriculture.

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Section: Discussionsupporting

confidence: 62%

A large nested association mapping population for breeding and quantitative trait locus mapping in Ethiopian durum wheat

Kidane

Gesesse

Hailemariam

et al. 2019

Plant Biotechnology Journal

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“…Previous studies reported QTLs for TKW on the same chromosomes (Börner et al, 2002;Pinto et al, 2010;Sukumaran et al, 2016), suggesting that these chromosomes would play a role in controlling kernel weight. In the present study, several MTAs were found to be associated with TKW, of which five were detected both at Sids and Wad Medani.…”

Section: Marker-trait Associationsmentioning

confidence: 91%

“…Marker-trait associations using association mapping have been identified in different crops (Zhu et al, 2008) using different types of molecular markers. Similarly, association mapping studies have been performed in wheat for grain yield (Crossa et al, 2007;Edae et al, 2014;Lopes et al, 2014;Ogbonnaya et al, 2017), resistance to foliar diseases (Crossa et al, 2007;Tadesse et al, 2014;Sukumaran et al, 2015Sukumaran et al, , 2016Jighly et al, 2015), soil-borne pathogens (Mulki et al, 2013), and resistance to major insect pests ( Joukhadar et al, 2013). Similarly, association mapping studies have been performed in wheat for grain yield (Crossa et al, 2007;Edae et al, 2014;Lopes et al, 2014;Ogbonnaya et al, 2017), resistance to foliar diseases (Crossa et al, 2007;Tadesse et al, 2014;Sukumaran et al, 2015Sukumaran et al, , 2016Jighly et al, 2015), soil-borne pathogens (Mulki et al, 2013), and resistance to major insect pests ( Joukhadar et al, 2013).…”

Section: Heat-tolerant Qtls Associated With Grain Yield and Its Compomentioning

confidence: 99%

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Heat‐Tolerant QTLs Associated with Grain Yield and Its Components in Spring Bread Wheat under Heat‐Stressed Environments of Sudan and Egypt

Tadesse¹,

Suleiman

Tahir

et al. 2019

Crop Science

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Heat stress decreases photosynthesis, pollen viability, and grain number and weight and hence lowers yield and quality of wheat (Triticum aestivum L.) by variable amounts among different cultivars and genotypes. The present study was performed to determine genetic variability of spring bread wheat genotypes for yield and other agronomic traits under heat‐stressed (Wad Medani, Sudan) and high‐yielding (Sids, Egypt) environments and to identify linked single nucleotide polymorphism (SNP) markers through association mapping. A heat association panel of 197 spring wheat genotypes from ICARDA was evaluated for yield and agronomic traits at Wad Medani and Sids stations for 2 yr (2014–2015). A total of 111 significant marker‐trait associations were detected. The wsnp_Ex_c12812_20324622 marker on chromosome 4A was significantly correlated with yield at both locations. At Wad Medani, wsnp_Ex_c2526_4715978 on chromosome 5A was significantly correlated with grain yield. Wheat genotypes carrying the cytosine base at the wsnp_Ex_c12812_20324622 and wsnp_Ex_c2526_4715978 markers outyielded the ones carrying the alternative bases by 15%, whereas genotypes carrying the cytosine base at only one of the two markers increased their yield by 7.9 to 10%, suggesting the importance of using these markers for marker‐assisted selection in breeding programs to increase yield under heat stress. The top 20 high‐yielding and heat‐tolerant genotypes identified in this study have been distributed to the national research systems of Central and West Asia and North Africa (CWANA) and sub‐Saharan Africa (SSA) for potential direct release and/or use as parents after local adaptation trials.

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“…To dissect the genetic basis of traits through GWAS, several studies were conducted using array‐based platforms (Liu, Pinto, Cossani, Sukumaran, & Reynolds, ; Lopes, Dreisigacker, Pena, Sukumaran, & Reynolds, ; Sukumaran, Dreisigacker, Lopes, Chavez, & Reynolds, , , ; Valluru, Reynolds, Davies, & Sukumaran, ) in spring wheat and sequencing‐based platforms (Sukumaran, Reynolds, & Sansaloni, ) in durum wheat ( Triticum durum Desf.). Genomic prediction studies were also conducted using the I90K and DArTseq platforms (Christy et al., ; Crossa et al., , , , ; Juliana et al., , ; Rutkoski et al., ; Sukumaran, Crossa, Jarquin, Lopes, & Reynolds, , ).…”

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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Identification of Earliness Per Se Flowering Time Locus in Spring Wheat through a Genome‐Wide Association Study

Cited by 37 publications

References 94 publications

A large nested association mapping population for breeding and quantitative trait locus mapping in Ethiopian durum wheat

A large nested association mapping population for breeding and quantitative trait locus mapping in Ethiopian durum wheat

Heat‐Tolerant QTLs Associated with Grain Yield and Its Components in Spring Bread Wheat under Heat‐Stressed Environments of Sudan and Egypt

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

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