Key message
Genetic atlas, reliable QTL and candidate genes of yield component traits in wheat were figured out, laying concrete foundations for map-based gene cloning and dissection of regulatory ...mechanisms underlying yield.
Mining genetic loci for yield is challenging due to the polygenic nature, large influence of environment and complex relationship among yield component traits (YCT). Many genetic loci related to wheat yield have been identified, but its genetic architecture and key genetic loci for selection are largely unknown. Wheat yield potential can be determined by three YCT, thousand kernel weight, kernel number per spike and spike number. Here, we summarized the genetic loci underpinning YCT from QTL mapping, association analysis and homology-based gene cloning. The major loci determining yield-associated agronomic traits, such as flowering time and plant height, were also included in comparative analyses with those for YCT. We integrated yield-related genetic loci onto chromosomes based on their physical locations. To identify the major stable loci for YCT, 58 QTL-rich clusters (QRC) were defined based on their distribution on chromosomes. Candidate genes in each QRC were predicted according to gene annotation of the wheat reference genome and previous information on validation of those genes in other species. Finally, a technological route was proposed to take full advantage of the resultant resources for gene cloning, molecular marker-assisted breeding and dissection of molecular regulatory mechanisms underlying wheat yield.
•An unmanned aerial vehicle (UAV) was optimized and used for non-destructive high-throughput phenotyping of NDVI.•UAV-NDVI measurements were highly consistent with ground data captured by a handheld ...Greenseeker.•UAV-NDVI explained significant variations in biomass and grain yield.•UAV-NDVI was accurate and can be used for selection of high yielding genotypes during grain-filling stages in large breeding programs.
Wheat improvement programs require rapid assessment of large numbers of individual plots across multiple environments. Vegetation indices (VIs) that are mainly associated with yield and yield-related physiological traits, and rapid evaluation of canopy normalized difference vegetation index (NDVI) can assist in-season selection. Multi-spectral imagery using unmanned aerial vehicles (UAV) can readily assess the VIs traits at various crop growth stages. Thirty-two wheat cultivars and breeding lines grown in limited irrigation and full irrigation treatments were investigated to monitor NDVI across the growth cycle using a Sequoia sensor mounted on a UAV. Significant correlations ranging from R2 = 0.38 to 0.90 were observed between NDVI detected from UAV and Greenseeker (GS) during stem elongation (SE) to late grain gilling (LGF) across the treatments. UAV-NDVI also had high heritabilities at SE (h2 = 0.91), flowering (F)(h2 = 0.95), EGF (h2 = 0.79) and mid grain filling (MGF) (h2 = 0.71) under the full irrigation treatment, and at booting (B) (h2 = 0.89), EGF (h2 = 0.75) in the limited irrigation treatment. UAV-NDVI explained significant variation in grain yield (GY) at EGF (R2 = 0.86), MGF (R2 = 0.83) and LGF (R2 = 0.89) stages, and results were consistent with GS-NDVI. Higher correlations between UAV-NDVI and GY were observed under full irrigation at three different grain-filling stages (R2 = 0.40, 0.49 and 0.45) than the limited irrigation treatment (R2 = 0.08, 0.12 and 0.14) and GY was calculated to be 24.4% lower under limited irrigation conditions. Pearson correlations between UAV-NDVI and GY were also low ranging from r = 0.29 to 0.37 during grain-filling under limited irrigation but higher than GS-NDVI data. A similar pattern was observed for normalized difference red-edge (NDRE) and normalized green red difference index (NGRDI) when correlated with GY. Fresh biomass estimated at late flowering stage had significant correlations of r = 0.30 to 0.51 with UAV-NDVI at EGF. Some genotypes Nongda 211, Nongda 5181, Zhongmai 175 and Zhongmai 12 were identified as high yielding genotypes using NDVI during grain-filling. In conclusion, a multispectral sensor mounted on a UAV is a reliable high-throughput platform for NDVI measurement to predict biomass and GY and grain-filling stage seems the best period for selection.
There is a rapidly rising trend in the development and application of molecular marker assays for gene map- ping and discovery in field crops and trees. Thus far, more than 50 SNP arrays and 15 ...different types of genotyping-by-sequencing （GBS） platforms have been developed in over 25 crop species and perennial trees. However, much less effort has been made on developing ultra-high-throughput and cost-effective genotyping platforms for applied breeding programs. In this review, we discuss the scientific bottlenecks in existing SNP arrays and GBS technologies and the strategies to develop targeted platforms for crop mo- lecular breeding. We propose that future practical breeding platforms should adopt automated genotyping technologies, either array or sequencing based, target functional polymorphisms underpinning economic traits, and provide desirable prediction accuracy for quantitative traits, with universal applications under wide genetic backgrounds in crops. The development of such platforms faces serious challenges at both the technological level due to cost ineffectiveness, and the knowledge level due to large genotype- phenotype gaps in crop plants. It is expected that such genotyping platforms will be achieved in the next ten years in major crops in consideration of （a） rapid development in gene discovery of important traits, （b） deepened understanding of quantitative traits through new analytical models and population designs, （c） integration of multi-layer -omics data leading to identification of genes and pathways responsible for important breeding traits, and （d） improvement in cost effectiveness of large-scale genotyping. Crop breeding chips and genotyping platforms will provide unprecedented opportunities to accelerate the development of cultivars with desired yield potential, quality, and enhanced adaptation to mitigate the effects of climate change.
Functional markers (FM) are developed from sequence polymorphisms present in allelic variants of a functional gene at a locus. FMs accurately discriminate alleles of a targeted gene, and are ideal ...molecular markers for marker-assisted selection in wheat breeding. In this paper, we summarize FMs developed and used in common wheat. To date, more than 30 wheat loci associated with processing quality, agronomic traits, and disease resistance, have been cloned, and 97 FMs were developed to identify 93 alleles based on the sequences of those genes. A general approach is described for isolation of wheat genes and development of FMs based on in silico cloning and comparative genomics. The divergence of DNA sequences of different alleles that affect gene function is summarized. In addition, 14 molecular markers specific for alien genes introduced from common wheat relatives were also described. This paper provides updated information on all FMs and gene-specific STS markers developed so far in wheat and should facilitate their application in wheat breeding programs.
Summary
Timely flowering is essential for optimum crop reproduction and yield. To determine the best flowering‐time genes (FTGs) relevant to local adaptation and breeding, it is essential to compare ...the interspecific genetic architecture of flowering in response to light and temperature, the two most important environmental cues in crop breeding. However, the conservation and variations of FTGs across species lack systematic dissection. This review summarizes current knowledge on the genetic architectures underlying light and temperature‐mediated flowering initiation in Arabidopsis, rice, and temperate cereals. Extensive comparative analyses show that most FTGs are conserved, whereas functional variations in FTGs may be species specific and confer local adaptation in different species. To explore evolutionary dynamics underpinning the conservation and variations in FTGs, domestication and selection of some key FTGs are further dissected. Based on our analyses of genetic control of flowering time, a number of key issues are highlighted. Strategies for modulation of flowering behavior in crop breeding are also discussed. The resultant resources provide a wealth of reference information to uncover molecular mechanisms of flowering in plants and achieve genetic improvement in crops.
Key message
We developed and validated a robust marker toolkit for high-throughput and cost-effective screening of a large number of functional genes in wheat.
Functional markers (FMs) are the most ...valuable markers for crop breeding programs, and high-throughput genotyping for FMs could provide an excellent opportunity to effectively practice marker-assisted selection while breeding cultivars. Here we developed and validated kompetitive allele-specific PCR (KASP) assays for genes that underpin economically important traits in bread wheat including adaptability, grain yield, quality, and biotic and abiotic stress resistances. In total, 70 KASP assays either developed in this study or obtained from public databases were validated for reliability in application. The validation of KASP assays were conducted by (a) comparing the assays with available gel-based PCR markers on 23 diverse wheat accessions, (b) validation of the derived allelic information using phenotypes of a panel comprised of 300 diverse cultivars from China and 13 other countries, and (c) additional testing, where possible, of the assays in four segregating populations. All KASP assays being reported were significantly associated with the relevant phenotypes in the cultivars panel and bi-parental populations, thus revealing potential application in wheat breeding programs. The results revealed 45 times superiority of the KASP assays in speed than gel-based PCR markers. KASP has recently emerged as single-plex high-throughput genotyping technology; this is the first report on high-throughput screening of a large number of functional genes in a major crop. Such assays could greatly accelerate the characterization of crossing parents and advanced lines for marker-assisted selection and can complement the inflexible, high-density SNP arrays. Our results offer a robust and reliable molecular marker toolkit that can contribute towards maximizing genetic gains in wheat breeding programs.
Identification of loci for grain yield (GY) and related traits, and dissection of the genetic architecture are important for yield improvement through marker-assisted selection (MAS). Two genome-wide ...association study (GWAS) methods were used on a diverse panel of 166 elite wheat varieties from the Yellow and Huai River Valleys Wheat Zone (YHRVWD) of China to detect stable loci and analyze relationships among GY and related traits.
A total of 326,570 single nucleotide polymorphism (SNP) markers from the wheat 90 K and 660 K SNP arrays were chosen for GWAS of GY and related traits, generating a physical distance of 14,064.8 Mb. One hundred and twenty common loci were detected using SNP-GWAS and Haplotype-GWAS, among which two were potentially functional genes underpinning kernel weight and plant height (PH), eight were at similar locations to the quantitative trait loci (QTL) identified in recombinant inbred line (RIL) populations in a previous study, and 78 were potentially new. Twelve pleiotropic loci were detected on eight chromosomes; among these the interval 714.4-725.8 Mb on chromosome 3A was significantly associated with GY, kernel number per spike (KNS), kernel width (KW), spike dry weight (SDW), PH, uppermost internode length (UIL), and flag leaf length (FLL). GY shared five loci with thousand kernel weight (TKW) and PH, indicating significantly affected by two traits. Compared with the total number of loci for each trait in the diverse panel, the average number of alleles for increasing phenotypic values of GY, TKW, kernel length (KL), KW, and flag leaf width (FLW) were higher, whereas the numbers for PH, UIL and FLL were lower. There were significant additive effects for each trait when favorable alleles were combined. UIL and FLL can be directly used for selecting high-yielding varieties, whereas FLW can be used to select spike number per unit area (SN) and KNS.
The loci and significant SNP markers identified in the present study can be used for pyramiding favorable alleles in developing high-yielding varieties. Our study proved that both GWAS methods and high-density genetic markers are reliable means of identifying loci for GY and related traits, and provided new insight to the genetic architecture of GY.
Carotenoids play a critical role in animal and human health. Animals and humans are unable to synthesize carotenoids de novo, and therefore rely upon diet as sources of these compounds. However, ...major staple cereals often contain only small amounts of carotenoids in their grains. Consequently, there is considerable interest in genetic manipulation of carotenoid content in cereal grain. In this review, we focus on carotenoid metabolism and regulation in non-green plant tissues, as well as genetic manipulation in staple cereals such as rice, maize, and wheat. Significant progress has been made in three aspects: (1) seven carotenogenes play vital roles in carotenoid regulation in non-green plant tissues, including 1-deoxyxylulose-5-phosphate synthase influencing isoprenoid precursor supply, phytoene synthase, β-cyclase, and ε-cyclase controlling biosynthesis, 1-hydroxy-2-methyl-2-(E)-butenyl 4-diphosphate reductase and carotenoid cleavage dioxygenases responsible for degradation, and orange gene conditioning sequestration sink; (2) provitamin A-biofortified crops, such as rice and maize, were developed by either metabolic engineering or marker-assisted breeding; (3) quantitative trait loci for carotenoid content on chromosomes 3B, 7A, and 7B were consistently identified, eight carotenogenes including 23 loci were detected, and 10 gene-specific markers for carotenoid accumulation were developed and applied in wheat improvement. A comprehensive and deeper understanding of the regulatory mechanisms of carotenoid metabolism in crops will be beneficial in improving our precision in improving carotenoid contents. Genomic selection and gene editing are emerging as transformative technologies for provitamin A biofortification.
Detection of senescence’s dynamics in crop breeding is time consuming and needs considerable details regarding its rate of progression and intensity. Normalized difference red-edge index (NDREI) ...along with four other spectral vegetative indices (SVIs) derived from unmanned aerial vehicle (UAV) based spatial imagery, were evaluated for rapid and accurate prediction of senescence. For this, 32 selected winter wheat genotypes were planted under full and limited irrigation treatments. Significant variations for all five SVIs: green normalize difference vegetation index (GNDVI), simple ratio (SR), green chlorophyll index (GCI), red-edge chlorophyll index (RECI), and normalized difference red-edge index (NDREI) among genotypes and between treatments, were observed from heading to late grain filling stages. The SVIs showed strong relationship (R2 = 0.69 to 0.78) with handheld measurements of chlorophyll and leaf area index (LAI), while negatively correlated (R2 = 0.75 to 0.77) with canopy temperature (CT) across the treatments. NDREI as a new SVI showed higher correlations with ground data under both treatments, similarly as exhibited by other four SVIs. There were medium to strong correlations (r = 0.23–0.63) among SVIs, thousand grain weight (TGW) and grain yield (GY) under both treatments. Senescence rate was calculated by decreasing values of SVIs from their peak values at heading stage, while variance for senescence rate among genotypes and between treatments could be explained by SVIs variations. Under limited irrigation, 10% to 15% higher senescence rate was detected as compared with full irrigation. Principle component analysis corroborated the negative association of high senescence rate with TGW and GY. Some genotypes, such as Beijing 0045, Nongda 5181, and Zhongmai 175, were selected with low senescence rate, stable TGW and GY in both full and limited irrigation treatments, nearly in accordance with the actual performance of these cultivars in field. Thus, SVIs derived from UAV appeared as a promising tool for rapid and precise estimation of senescence rate at maturation stages.
Identification of genes for yield components, plant height (PH), and yield-related physiological traits and tightly linked molecular markers is of great importance in marker-assisted selection (MAS) ...in wheat breeding. In the present study, 246 F8 RILs derived from the cross of Zhou 8425B/Chinese Spring were genotyped using the high-density Illumina iSelect 90K single nucleotide polymorphism (SNP) assay. Field trials were conducted at Zhengzhou and Zhoukou of Henan Province, during the 2012-2013 and 2013-2014 cropping season under irrigated conditions, providing data for four environments. Analysis of variance (ANOVA) of agronomic and physiological traits revealed significant differences (P < 0.01) among RILs, environments, and RILs × environments interactions. Broad-sense heritabilities of all traits including thousand kernel weight (TKW), PH, spike length (SL), kernel number per spike (KNS), spike number/m(2) (SN), normalized difference in vegetation index at anthesis (NDVI-A) and at 10 days post-anthesis (NDVI-10), SPAD value of chlorophyll content at anthesis (Chl-A) and at 10 days post-anthesis (Chl-10) ranged between 0.65 and 0.94. A linkage map spanning 3609.4 cM was constructed using 5636 polymorphic SNP markers, with an average chromosome length of 171.9 cM and marker density of 0.64 cM/marker. A total of 866 SNP markers were newly mapped to the hexaploid wheat linkage map. Eighty-six QTL for yield components, PH, and yield-related physiological traits were detected on 18 chromosomes except 1D, 5D, and 6D, explaining 2.3-33.2% of the phenotypic variance. Ten stable QTL were identified across four environments, viz. QTKW.caas-6A.1, QTKW.caas-7AL, QKNS.caas-4AL, QSN.caas-1AL.1, QPH.caas-4BS.2, QPH.caas-4DS.1, QSL.caas-4AS, QSL.caas-4AL.1, QChl-A.caas-5AL, and QChl-10.caas-5BL. Meanwhile, 10 QTL-rich regions were found on chromosome 1BS, 2AL (2), 3AL, 4AL (2), 4BS, 4DS, 5BL, and 7AL exhibiting pleiotropic effects. These QTL or QTL clusters are tightly linked to SNP markers, with genetic distances to the closest SNPs ranging from 0 to 1.5 cM, and could serve as target regions for fine mapping, candidate gene discovery, and MAS in wheat breeding.
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