A Genome-Wide Association Study of Wheat Spike Related Traits in China

Liu, Jing; Xu, Zhibin; Fan, Xiaoqin; Zhou, Qiang; Cao, Jun; Wang, Fang; Ji, Guangsi; Yang, Li; Feng, Bo; Wang, Tao

doi:10.3389/fpls.2018.01584

Cited by 80 publications

(70 citation statements)

References 83 publications

(98 reference statements)

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“…In other words, SlPS, TKW and SlC were more stable than FTN and KPSl. Consistent with many other reports, FTN had a low heritability and was strongly influenced by environments [5,9,31] and KPSl also displayed relatively low heritability, whereas SlPS, TKW and SlC had relatively higher heritabilities [3,9,[32][33][34].…”

Section: Yield-related Traits Slps Tkw and Slc Exhibited Relativelysupporting

confidence: 90%

Genome-wide association study reveals new loci for yield-related traits in Sichuan wheat germplasm under stripe rust stress

Cheng

et al. 2019

Preprint

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caused by fungus Puccinia striiformis Westend. f. sp. tritici Erikss. (Pst) is a serious threat to wheat production [2]. Therefore, improving wheat yield under stripe rust stress is extremely urgent. Thus, identifying loci associated with yield-related traits under stripe rust stress may provide favourable alleles and their useful markers for breeding wheat cultivars with high yield in combination with stripe rust resistance. The productive spike number per unit area, kernel number per spike (KPS) and thousand-kernel weight (TKW) are key components of wheat yield. The productive spike number per unit area mainly depends on the fertile tiller number (FTN). Most spike-related traits, such as spike length (SL), spikelet number per spike (SlPS), kernel number per spikelet (KPSl) and the spikelet compactness (SlC), affect the KPS and thus also affect the yield [3-5]. Many studies have showed that the SL has a positive correlation with KPS and SlPS [3, 4, 6, 7]. Moreover, Mohsin et al. [8] reported that the SL and the KPS had a positive effect on grain yield. Würschum et al. [7] demonstrated that KPSl was positively correlated with the KPS. The SlC is positively correlated with SlPS, but negatively related to SL [3,6,9]. The TKW, which depends on the kernel weight, is associated with the accumulation of starch produced by photosynthesis [10,11]. Therefore, wheat yield is a complex quantitative trait contributed by many morphological, physiological and biochemical components, all of which can be improved to increase the yield directly or indirectly.Genome-wide association study (GWAS) is a powerful tool to identify loci associated to target traits based on linkage disequilibrium (LD) using natural populations. It is a rapid and cost-effectiveness way to detect target markers for marker-assisted breeding. GWAS was first used in human research and has made great contributions to identify genes associated to human diseases [12][13][14][15][16]. The GWAS approach has been widely used in plant and animal research [17][18][19][20][21]. For wheat, GWAS has been successfully used for identifying quantitative trait loci (QTLs) for disease resistance and yield [22][23][24][25].The release of the high-quality genome reference IWGSC RefSeq v1.0 [26] has provided great assistance to detect linked markers and candidate genes for target traits. The availability of marker arrays for high throughput genotyping is a key for GWAS. There are many SNP arrays have been developed for wheat, such as 9K, 35K, 55K, 90K, 660K and 820K. These arrays are able to provide

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Section: Yield-related Traits Slps Tkw and Slc Exhibited Relativelysupporting

confidence: 90%

Genome-wide association study reveals new loci for yield-related traits in Sichuan wheat germplasm under stripe rust stress

Cheng

et al. 2019

Preprint

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“…The positive relationships between FSS (or FSS%), GNFS with BY, TKW, HI, SPS and GN that found in the current study, indicate that improving grain yield through enhancing spikelet fertility together with TKW, SPS and BY is plausible. It might be attributed to the genetic material (ancient cultivars) used in the current study which are carrying allele(s) that not present, or present at low frequency in breeding lines or elite/modern cultivars used in the previous studies 8, 24,25 . The elite/ modern cultivars were selected for a specific purpose based on origin 8 , and always characterized with low number of kernels per spikelet, and less resistance/tolerance to biotic/abiotic stresses compared with old cultivars 26 .…”

Section: Discussionmentioning

confidence: 96%

“…The newly added spikelet related-traits in this study demonstrated the importance of studying such traits which showed high natural variation. The natural variation of spikelet fertility/sterility traits and grain-yield-related traits has been recently explored in wheat 8,24 .…”

Section: Discussionmentioning

confidence: 99%

“…It has been shown that a negative correlation between TKW with SPS and GN in Chinese wheat 24 might be a consequence of trade-offs between GN and TKW with BY and HI. Such negative correlation restricts the grain yield and genetic gains of these traits 25 , or a competition for assimilates between spikelets that leads to unbalanced distribution of GN within FSS and florets along the spike 8 .…”

Section: Discussionmentioning

confidence: 99%

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Genome-wide and SNP network analyses reveal genetic control of spikelet sterility and yield-related traits in wheat

Alqudah

Haile

Alomari

et al. 2020

Sci Rep

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Revealing the genetic factors underlying yield and agronomic traits in wheat are an imperative need for covering the global food demand. Yield boosting requires a deep understanding of the genetic basis of grain yield-related traits (e.g., spikelet fertility and sterility). Here, we have detected much natural variation among ancient hexaploid wheat accessions in twenty-two agronomic traits collected over eight years of field experiments. A genome-wide association study (GWAS) using 15 K single nucleotide polymorphisms (Snps) was applied to detect the genetic basis of studied traits. Subsequently, the GWAS output was reinforced via other statistical and bioinformatics analyses to detect putative candidate genes. Applying the genome-wide SNP-phenotype network defined the most decisive SNPs underlying the traits. Six pivotal Snps, co-located physically within the genes encoding enzymes, hormone response, metal ion transport, and response to oxidative stress have been identified. Of these, metal ion transport and Gibberellin 2-oxidases (GA2oxs) genes showed strong involvement in controlling the spikelet sterility, which had not been reported previously in wheat. Snp-gene haplotype analysis confirmed that these SNPs influence spikelet sterility, especially the SNP co-located on the exon of the GA2ox gene. interestingly, these genes were highly expressed in the grain and spike, demonstrating their pivotal role in controlling the trait. the integrative analysis strategy applied in this study, including GWAS, SNP-phenotype network, SNP-gene haplotype, expression analysis, and genome-wide prediction (GP), empower the identification of functional SNPs and causal genes. GP outputs obtained in this study are encouraging for the implementation of the traits to accelerate yield improvement by making an early prediction of complex yield-related traits in wheat. Our findings demonstrate the usefulness of the ancient wheat material as a valuable resource for yield-boosting. this is the first comprehensive genome-wide analysis for spikelet sterility in wheat, and the results provide insights into yield improvement.

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“…In the recent past, several genes controlling spike morphology have been investigated and described in temperate cereals (Gauley and Boden 2019; Koppolu and Schnurbusch 2019). From a plant breeder’s viewpoint, most spike morphological traits in wheat such as spike length and spikelet number behave as quantitative traits, and various QTL and association studies have recently been published (Deng et al 2017; Guo et al 2017; Liu et al 2018; Sakuma et al 2019; Würschum et al 2018; Zhai et al 2016). High associations and prediction abilities for total and fertile spikelet number as well as spike length and grain yield were also reported (Guo et al 2018).…”

Section: Introductionmentioning

confidence: 99%

TaAPO-A1, an ortholog of riceABERRANT PANICLE ORGANIZATION 1, is associated with total spikelet number per spike in elite hexaploid winter wheat varieties (Triticum aestivumL.)

Muqaddasi

Brassac

Koppolu

et al. 2019

Preprint

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We dissected the genetic basis of total spikelet number (TSN) along with other traits, namely spike length (SL) and flowering time (FT) in a panel of 518 elite European winter wheat varieties. Genome-wide association studies based on 39,908 SNP markers revealed highly significant quantitative trait loci (QTL) for TSN on chromosomes 2D, 7A, and 7B, for SL on 5A, and FT on 2D, with 2D-QTL being the functional marker for the gene Ppd-D1. The physical region of the 7A-QTL for TSN revealed the presence of an ortholog to APO1 – a rice gene that positively controls spikelet number on panicles. Interspecific analyses of TaAPO-A1 orthologs showed that it is a highly conserved gene important for floral development, and present in a wide range of terrestrial plants. Intraspecific studies of the wheat ortholog TaAPO-A1 across wheat genotypes revealed a polymorphism in the highly conserved F-box domain, defining two haplotypes. A KASP maker developed on the polymorphic site showed a highly significant association of TaAPO-A1 with TSN, explaining 23.2% of the genotypic variance. Also, the TaAPO-A1 alleles showed weak but significant differences for SL and grain yield. Our results demonstrate the importance of wheat sequence resources to identify candidate genes for important traits based on genetic analyses.

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A Genome-Wide Association Study of Wheat Spike Related Traits in China

Cited by 80 publications

References 83 publications

Genome-wide association study reveals new loci for yield-related traits in Sichuan wheat germplasm under stripe rust stress

Genome-wide association study reveals new loci for yield-related traits in Sichuan wheat germplasm under stripe rust stress

Genome-wide and SNP network analyses reveal genetic control of spikelet sterility and yield-related traits in wheat

TaAPO-A1, an ortholog of riceABERRANT PANICLE ORGANIZATION 1, is associated with total spikelet number per spike in elite hexaploid winter wheat varieties (Triticum aestivumL.)

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