Identification of Novel SNP in Promoter Sequence of TaGW2-6A Associated with Grain Weight and Other Agronomic Traits in Wheat (Triticum aestivum L.)

Wheat improvement through advances in single nucleotide polymorphism (SNP) detection and genotyping with a special emphasis on rust resistance

KEY MESSAGE

Single nucleotide polymorphism (SNP) markers in wheat and their prospects in breeding with special reference to rust resistance. Single nucleotide polymorphism (SNP)-based markers are increasingly gaining momentum for screening and utilizing vital agronomic traits in wheat. To date, more than 260 million SNPs have been detected in modern cultivars and landraces of wheat. This rapid SNP discovery was made possible through the release of near-complete reference and pan-genome assemblies of wheat and its wild relatives, coupled with whole genome sequencing (WGS) of thousands of wheat accessions. Further, genotyping customized SNP sites were facilitated by a series of arrays (9 to 820Ks), a cost effective substitute WGS. Lately, germplasm-specific SNP arrays have been introduced to characterize novel traits and detect closely linked SNPs for marker-assisted breeding. Subsequently, the kompetitive allele-specific PCR (KASP) assay was introduced for rapid and large-scale screening of specific SNP markers. Moreover, with the advances and reduction in sequencing costs, ample opportunities arise for generating SNPs artificially through mutations and in combination with next-generation sequencing and comparative genomic analyses. In this review, we provide historical developments and prospects of SNP markers in wheat breeding with special reference to rust resistance where over 50 genetic loci have been characterized through SNP markers. Rust resistance is one of the most essential traits for wheat breeding as new strains of the Puccinia fungus, responsible for rust diseases, evolve frequently and globally.

Deciphering the differential expression patterns of yield-related negative regulators in hexaploid wheat cultivars and hybrids at different growth stages

BACKGROUND

Hexaploid bread wheat underwent a series of polyploidization events through interspecific hybridizations that conferred adaptive plasticity and resulted in duplication and neofunctionalization of major agronomic genes. The genetic architecture of polyploid wheat not only confers adaptive plasticity but also offers huge genetic diversity. However, the contribution of different gene copies (homeologs) encoded from different subgenomes (A, B, D) at different growth stages remained unexplored.

METHODS

In this study, hybrid of elite cultivars of wheat were developed via reciprocal crosses (cytoplasm swapping) and phenotypically evaluated. We assessed differential expression profiles of yield-related negative regulators in these cultivars and their F1 hybrids and identified various cis-regulatory signatures by employing bioinformatics tools. Furthermore, the preferential expression patterns of the syntenic triads encoded from A, B, and D subgenomes were assessed to decipher their functional redundancy at six different growth stages.

RESULTS

Hybrid progenies showed better heterosis such as up to 17% increase in the average number of grains and up to 50% increase in average thousand grains weight as compared to mid-parents. Based on the expression profiling, our results indicated significant dynamic transcriptional expression patterns, portraying the different homeolog-dominance at the same stage in the different cultivars and their hybrids. Albeit belonging to same syntenic triads, a dynamic trend was observed in the regulatory signatures of these genes that might be influencing their expression profiles.

CONCLUSION

These findings can substantially contribute and provide insights for the selective introduction of better cultivars into traditional and hybrid breeding programs which can be harnessed for the improvement of future wheat.

Fine mapping of a major QTL, qKl-1BL controlling kernel length in common wheat

KEY MESSAGE

A major stable QTL, qKl-1BL, for kernel length of wheat was narrowed down to a 2.04-Mb interval on chromosome 1BL; the candidate genes were predicated and the genetic effects on yield-related traits were characterized. As a key factor influencing kernel weight, wheat kernel shape is closely related to yield formation, and in turn affects both wheat processing quality and market value. Fine mapping of the major quantitative trait loci (QTL) for kernel shape could provide genetic resources and a theoretical basis for the genetic improvement of wheat yield-related traits. In this study, a major QTL for kernel length (KL) on 1BL, named qKl-1BL, was identified from the recombinant inbred lines (RIL) in multiple environments based on the genetic map and physical map, with 4.76-21.15% of the phenotypic variation explained. To fine map qKl-1BL, the map-based cloning strategy was used. By using developed InDel markers, the near-isogenic line (NIL) pairs and eight key recombinants were identified from a segregating population containing 3621 individuals derived from residual heterozygous lines (RHLs) self-crossing. In combination with phenotype identification, qKl-1BL was finely positioned into a 2.04-Mb interval, KN1B:698.15-700.19 Mb, with eight differentially expressed genes enriched at the key period of kernel elongation. Based on transcriptome analysis and functional annotation information, two candidate genes for qKl-1BL controlling kernel elongation were identified. Additionally, genetic effect analysis showed that the superior allele of qKl-1BL from Jing411 could increase KL, thousand kernel weight (TKW), and yield per plant (YPP) significantly, as well as kernel bulk density and stability time. Taken together, this study identified a QTL interval for controlling kernel length with two possible candidate genes, which provides an important basis for qKl-1BL cloning, functional analysis, and application in molecular breeding programs.

Genetic dissection of major QTL for grain number per spike on chromosomes 5A and 6A in bread wheat (Triticum aestivum L.)

Grain number per spike (GNS) is a crucial component of grain yield and plays a significant role in improving wheat yield. To identify quantitative trait loci (QTL) associated with GNS, a recombinant inbred line (RIL) population derived from the cross of Zhongkemai 13F10 and Chuanmai 42 was employed to conduct QTL mapping across eight environments. Based on the bulked segregant exome sequencing (BSE-Seq), genomic regions associated with GNS were detected on chromosomes 5A and 6A. According to the constructed genetic maps, two major QTL QGns.cib-5A (LOD = 4.35-8.16, PVE = 8.46-14.43%) and QGns.cib-6A (LOD = 3.82-30.80, PVE = 5.44-12.38%) were detected in five and four environments, respectively. QGns.cib-6A is a QTL cluster for other seven yield-related traits. QGns.cib-5A and QGns.cib-6A were further validated using linked Kompetitive Allele Specific PCR (KASP) markers in different genetic backgrounds. QGns.cib-5A exhibited pleiotropic effects on productive tiller number (PTN), spike length (SL), fertile spikelet number per spike (FSN), and ratio of grain length to grain width (GL/GW) but did not significantly affect thousand grain weight (TGW). Haplotype analysis revealed that QGns.cib-5A and QGns.cib-6A were the targets of artificial selection during wheat improvement. Candidate genes for QGns.cib-5A and QGns.cib-6A were predicted by analyzing gene annotation, spatiotemporal expression patterns, and orthologous and sequence differences. These findings will be valuable for fine mapping and map-based cloning of genes underlying QGns.cib-5A and QGns.cib-6A.

Precisely mapping a major QTL for grain weight on chromosome 5B of the founder parent Chuanmai42 in the wheat-growing region of southwestern China

KEY MESSAGE

QTgw.saas-5B was validated as a major thousand-grain weight-related QTL in a founder parent used for wheat breeding and then precisely mapped to a 0.6 cM interval. Increasing the thousand-grain weight (TGW) is considered to be one of the most important ways to improve yield, which is a core objective among wheat breeders. Chuanmai42, which is a wheat cultivar with high TGW and a high and stable yield, is a parent of more than 30 new varieties grown in southwestern China. In this study, a Chuanmai42-derived recombinant inbred line (RIL) population was used to dissect the genetic basis of TGW. A major QTL (QTgw.saas-5B) mapped to the Xgwm213-Xgwm540 interval on chromosome 5B of Chuanmai42 explained up to 20% of the phenotypic variation. Using 71 recombinants with a recombination in the QTgw.saas-5B interval identified from a secondary RIL population comprising 1818 lines constructed by crossing the QTgw.saas-5B near-isogenic line with the recurrent parent Chuannong16, QTgw.saas-5B was delimited to a 0.6 cM interval, corresponding to a 21.83 Mb physical interval in the Chinese Spring genome. These findings provide the foundation for QTgw.saas-5B cloning and its use in molecular marker-assisted breeding.

Genome-Wide Tissue-Specific Genes Identification for Novel Tissue-Specific Promoters Discovery in Soybean

Promoters play a crucial role in controlling the spatial and temporal expression of genes at transcriptional levels in the process of higher plant growth and development. The spatial, efficient, and correct regulation of exogenous genes expression, as desired, is the key point in plant genetic engineering research. Constitutive promoters widely used in plant genetic transformation are limited because, sometimes, they may cause potential negative effects. This issue can be solved, to a certain extent, by using tissue-specific promoters. Compared with constitutive promoters, a few tissue-specific promoters have been isolated and applied. In this study, based on the transcriptome data, a total of 288 tissue-specific genes were collected, expressed in seven tissues, including the leaves, stems, flowers, pods, seeds, roots, and nodules of soybean (Glycine max). KEGG pathway enrichment analysis was carried out, and 52 metabolites were annotated. A total of 12 tissue-specific genes were selected via the transcription expression level and validated through real-time quantitative PCR, of which 10 genes showed tissue-specific expression. The 3-kb 5' upstream regions of ten genes were obtained as putative promoters. Further analysis showed that all the 10 promoters contained many tissue-specific cis-elements. These results demonstrate that high-throughput transcriptional data can be used as effective tools, providing a guide for high-throughput novel tissue-specific promoter discovery.

Genetic Localization and Homologous Genes Mining for Barley Grain Size

Grain size is an important agronomic trait determining barley yield and quality. An increasing number of QTLs (quantitative trait loci) for grain size have been reported due to the improvement in genome sequencing and mapping. Elucidating the molecular mechanisms underpinning barley grain size is vital for producing elite cultivars and accelerating breeding processes. In this review, we summarize the achievements in the molecular mapping of barley grain size over the past two decades, highlighting the results of QTL linkage analysis and genome-wide association studies. We discuss the QTL hotspots and predict candidate genes in detail. Moreover, reported homologs that determine the seed size clustered into several signaling pathways in model plants are also listed, providing the theoretical basis for mining genetic resources and regulatory networks of barley grain size.

Genome-wide association analysis of spike and kernel traits in the U.S. hard winter wheat

A better understanding of the genetic control of spike and kernel traits that have higher heritability can help in the development of high-yielding wheat varieties. Here, we identified the marker-trait associations (MTAs) for various spike- and kernel-related traits in winter wheat (Triticum aestivum L.) through genome-wide association studies (GWAS). An association mapping panel comprising 297 hard winter wheat accessions from the U.S. Great Plains was evaluated for eight spike- and kernel-related traits in three different environments. A GWAS using 15,590 single-nucleotide polymorphisms (SNPs) identified a total of 53 MTAs for seven spike- and kernel-related traits, where the highest number of MTAs were identified for spike length (16) followed by the number of spikelets per spike (15) and spikelet density (11). Out of 53 MTAs, 14 were considered to represent stable quantitative trait loci (QTL) as they were identified in multiple environments. Five multi-trait MTAs were identified for various traits including the number of spikelets per spike (NSPS), spikelet density (SD), kernel width (KW), and kernel area (KA) that could facilitate the pyramiding of yield-contributing traits. Further, a significant additive effect of accumulated favorable alleles on the phenotype of four spike-related traits suggested that breeding lines and cultivars with a higher number of favorable alleles could be a valuable resource for breeders to improve yield-related traits. This study improves the understanding of the genetic basis of yield-related traits in hard winter wheat and provides reliable molecular markers that will facilitate marker-assisted selection (MAS) in wheat breeding programs.

Fine mapping and characterization of a major QTL for grain weight on wheat chromosome arm 5DL

We fine mapped QTL QTKW.caas-5DL for thousand kernel weight in wheat, predicted candidate genes and developed a breeding-applicable marker. Thousand kernel weight (TKW) is an important yield component trait in wheat, and identification of the underlying genetic loci is helpful for yield improvement. We previously identified a stable quantitative trait locus (QTL) QTKW.caas-5DL for TKW in a Doumai/Shi4185 recombinant inbred line (RIL) population. Here we performed fine mapping of QTKW.caas-5DL using secondary populations derived from 15 heterozygous recombinants and delimited the QTL to an approximate 3.9 Mb physical interval from 409.9 to 413.8 Mb according to the Chinese Spring (CS) reference genome. Analysis of genomic synteny showed that annotated genes in the physical interval had high collinearity among CS and eight other wheat genomes. Seven genes with sequence variation and/or differential expression between parents were predicted as candidates for QTKW.caas-5DL based on whole-genome resequencing and transcriptome assays. A kompetitive allele-specific PCR (KASP) marker for QTKW.caas-5DL was developed, and genotyping confirmed a significant association with TKW but not with other yield component traits in a panel of elite wheat cultivars. The superior allele of QTKW.caas-5DL was frequent in a panel of cultivars, suggesting that it had undergone positive selection. These findings not only lay a foundation for map-based cloning of QTKW.caas-5DL but also provide an efficient tool for marker-assisted selection.

Quantitative trait loci identification and breeding value estimation of grain weight-related traits based on a new wheat 50K single nucleotide polymorphism array-derived genetic map

Mining novel and less utilized thousand grain weight (TGW) related genes are useful for improving wheat yield. In this study, a recombinant inbred line population from a cross between Zhongkemai 138 (ZKM138, high TGW) and Chuanmai 44 (CM44, low TGW) was used to construct a new Wheat 50K SNP array-derived genetic map that spanned 1,936.59 cM and contained 4, 139 markers. Based on this map, ninety-one quantitative trait loci (QTL) were detected for eight grain-related traits in six environments. Among 58 QTLs, whose superior alleles were contributed by ZKM138, QTgw.cib-6A was a noticeable major stable QTL and was also highlighted by bulked segregant analysis with RNA sequencing (BSR-Seq). It had a pyramiding effect on TGW enhancement but no significant trade-off effect on grain number per spike or tiller number, with two other QTLs (QTgw.cib-2A.2 and QTgw.cib-6D), possibly explaining the excellent grain performance of ZKM138. After comparison with known loci, QTgw.cib-6A was deduced to be a novel locus that differed from nearby TaGW2 and TaBT1. Seven simple sequence repeat (SSR) and thirty-nine kompetitive allele-specific PCR (KASP) markers were finally developed to narrow the candidate interval of QTgw.cib-6A to 4.1 Mb. Only six genes in this interval were regarded as the most likely candidate genes. QTgw.cib-6A was further validated in different genetic backgrounds and presented 88.6% transmissibility of the ZKM138-genotype and a 16.4% increase of TGW in ZKM138 derivatives. And the geographic pattern of this locus revealed that its superior allele is present in only 6.47% of 433 Chinese modern wheat varieties, indicating its potential contribution to further high-yield breeding.

Genes Impacting Grain Weight and Number in Wheat (Triticum aestivum L. ssp. aestivum)

The primary goal of common wheat (T. aestivum) breeding is increasing yield without negatively impacting the agronomic traits or product quality. Genetic approaches to improve the yield increasingly target genes that impact the grain weight and number. An energetic trade-off exists between the grain weight and grain number, the result of which is that most genes that increase the grain weight also decrease the grain number. QTL associated with grain weight and number have been identified throughout the hexaploid wheat genome, leading to the discovery of numerous genes that impact these traits. Genes that have been shown to impact these traits will be discussed in this review, including TaGNI, TaGW2, TaCKX6, TaGS5, TaDA1, WAPO1, and TaRht1. As more genes impacting the grain weight and number are characterized, the opportunity is increasingly available to improve common wheat agronomic yield by stacking the beneficial alleles. This review provides a synopsis of the genes that impact grain weight and number, and the most beneficial alleles of those genes with respect to increasing the yield in dryland and irrigated conditions. It also provides insight into some of the genetic mechanisms underpinning the trade-off between grain weight and number and their relationship to the source-to-sink pathway. These mechanisms include the plant size, the water soluble carbohydrate levels in plant tissue, the size and number of pericarp cells, the cytokinin and expansin levels in developing reproductive tissue, floral architecture and floral fertility.

Wheat E3 ubiquitin ligase TaGW2-6A degrades TaAGPS to affect seed size

TaGW2 has been identified as a key determinant of the grain weight in wheat (Triticum aestivum L.). In our previous study, we found that the grain size differs in Chinese Spring (CS) and its TaGW2-6A allelic variant (NIL31). In addition, the expression of the key starch biosynthesis enzyme gene TaAGPS differs significantly in the two materials. However, the underlying molecular mechanism associated with the action of TaGW2-6A has not been reported. In the present study, we found that TaGW2-6A-CS interacted with TaAGPS, whereas TaGW2-6A-NIL31 did not interact with it in vitro and in vivo. Furthermore, we found that the C-terminal LXLX domain (376-424 aa) of TaGW2-6A recognized TaAGPS. However, the TaGW2-6A allelic variant lacked this key interaction region due to premature translation termination. We also found that TaGW2-6A-CS can ubiquitinate TaAGPS and degrade it via the 26 S proteasome pathway. In addition, our analysis of the activity of ADP-glucose pyrophosphorylase (AGPase) indicated that the AGPase level in the endosperm cells was lower in CS than NIL31. Cytological observations demonstrated that the average number of starch granules and the average area of starch granules in endosperm cells were lower in CS than NIL31. The overexpression of TaAGPS positively regulated the seed size in transgenic Arabidopsis. Our findings provide novel insights into the molecular mechanism that allows TaGW2-6A-TaAGPS to regulate seed size via the starch synthesis pathway.

N6-Methyladenosine dynamic changes and differential methylation in wheat grain development

More methylation changes occur in late interval than in early interval of wheat seed development with protein and the starch synthesis-related pathway enriched in the later stages. Wheat seed development is a critical process to determining wheat yield and quality, which is controlled by genetics, epigenetics and environments. The N6-methyladenosine (m⁶A) modification is a reversible and dynamic process and plays regulatory role in plant development and stress responses. To better understand the role of m⁶A in wheat grain development, we characterized the m⁶A modification at 10 day post-anthesis (DPA), 20 DPA and 30 DPA in wheat grain development. m⁶A-seq identified 30,615, 30,326, 27,676 high confidence m⁶A peaks from the 10DPA, 20DPA, and 30DPA, respectively, and enriched at 3'UTR. There were 29,964, 29,542 and 26,834 unique peaks identified in AN0942_10d, AN0942_20d and AN0942_30d. One hundred and forty-two genes were methylated by m⁶A throughout seed development, 940 genes methylated in early grain development (AN0942_20d vs AN0942_10d), 1542 genes in late grain development (AN0942_30d vs AN0942_20d), and 1190 genes between early and late development stage (AN0942_30d vs AN0942_10d). KEGG enrichment analysis found that protein-related pathways and the starch synthesis-related pathway were significantly enriched in the later stages of seed development. Our results provide novel knowledge on m⁶A dynamic changes and its roles in wheat grain development.

agReg-SNPdb-Plants: A Database of Regulatory SNPs for Agricultural Plant Species

Simple Summary

In breeding research, the investigation of regulatory SNPs (rSNPs) is becoming increasingly important due to their potential causal role for specific functional traits. Especially for crop species, there is still a lack of systematic analyses to detect rSNPs and their predicted effects on the binding of transcription factors. In this study, we present agReg-SNPdb-Plants, a database storing genome-wide collections of regulatory SNPs for agricultural plant species which can be queried via a web interface.

Abstract

Single nucleotide polymorphisms (SNPs) that are located in the promoter regions of genes and affect the binding of transcription factors (TFs) are called regulatory SNPs (rSNPs). Their identification can be highly valuable for the interpretation of genome-wide association studies (GWAS), since rSNPs can reveal the biologically causative variant and decipher the regulatory mechanisms behind a phenotype. In our previous work, we presented agReg-SNPdb, a database of regulatory SNPs for agriculturally important animal species. To complement this previous work, in this study we present the extension agReg-SNPdb-Plants storing rSNPs and their predicted effects on TF-binding for 13 agriculturally important plant species and subspecies (Brassica napus, Helianthus annuus, Hordeum vulgare, Oryza glaberrima, Oryza glumipatula, Oryza sativa Indica, Oryza sativa Japonica, Solanum lycopersicum, Sorghum bicolor, Triticum aestivum, Triticum turgidum, Vitis vinifera, and Zea mays). agReg-SNPdb-Plants can be queried via a web interface that allows users to search for SNP IDs, chromosomal regions, or genes. For a comprehensive interpretation of GWAS results or larger SNP-sets, it is possible to download the whole list of SNPs and their impact on transcription factor binding sites (TFBSs) from the website chromosome-wise.

The physiology and genetics behind fruiting efficiency: a promising spike trait to improve wheat yield potential

Fruiting efficiency (FE, grains per g of spike dry weight at anthesis) was proposed as a promising spike trait to improve wheat yield potential, based on its functional relationship with grain number determination and the evidence of trait variability in elite germplasm. During the last few years, we have witnessed great advances in the understanding of the physiological and genetic basis of this trait. The present review summarizes the recent heritability estimations and the genetic gains obtained when fruiting efficiency was measured at maturity (FEm, grains per g of chaff) and used as selection criterion. In addition, we propose spike ideotypes for contrasting fruiting efficiencies based on the fertile floret efficiency (FFE, fertile florets per g of spike dry weight at anthesis) and grain set (grains per fertile floret), together with other spike fertility-related traits. We also review novel genes and quantitative trait loci available for using marker-assisted selection for fruiting efficiency and other spike fertility traits. The possible trade-off between FE and grain weight and the genes reported to alter this relation are also considered. Finally, we discuss the benefits and future steps towards the use of fruiting efficiency as a selection criterion in breeding programs.

Genetic Mapping by Integration of 55K SNP Array and KASP Markers Reveals Candidate Genes for Important Agronomic Traits in Hexaploid Wheat

Agronomic traits such as heading date (HD), plant height (PH), thousand grain weight (TGW), and spike length (SL) are important factors affecting wheat yield. In this study, we constructed a high-density genetic linkage map using the Wheat55K SNP Array to map quantitative trait loci (QTLs) for these traits in 207 recombinant inbred lines (RILs). A total of 37 QTLs were identified, including 9 QTLs for HD, 7 QTLs for PH, 12 QTLs for TGW, and 9 QTLs for SL, which explained 3.0-48.8% of the phenotypic variation. Kompetitive Allele Specific PCR (KASP) markers were developed based on sequencing data and used for validation of the stably detected QTLs on chromosomes 3A, 4B and 6A using 400 RILs. A QTL cluster on chromosome 4B for PH and TGW was delimited to a 0.8 Mb physical interval explaining 12.2-22.8% of the phenotypic variation. Gene annotations and analyses of SNP effects suggested that a gene encoding protein Photosynthesis Affected Mutant 68, which is essential for photosystem II assembly, is a candidate gene affecting PH and TGW. In addition, the QTL for HD on chromosome 3A was narrowed down to a 2.5 Mb interval, and a gene encoding an R3H domain-containing protein was speculated to be the causal gene influencing HD. The linked KASP markers developed in this study will be useful for marker-assisted selection in wheat breeding, and the candidate genes provide new insight into genetic study for those traits in wheat.

In Silico Identification of the Complex Interplay between Regulatory SNPs, Transcription Factors, and Their Related Genes in Brassica napus L. Using Multi-Omics Data

Regulatory SNPs (rSNPs) are a special class of SNPs which have a high potential to affect the phenotype due to their impact on DNA-binding of transcription factors (TFs). Thus, the knowledge about such rSNPs and TFs could provide essential information regarding different genetic programs, such as tissue development or environmental stress responses. In this study, we use a multi-omics approach by combining genomics, transcriptomics, and proteomics data of two different Brassica napus L. cultivars, namely Zhongshuang11 (ZS11) and Zhongyou821 (ZY821), with high and low oil content, respectively, to monitor the regulatory interplay between rSNPs, TFs and their corresponding genes in the tissues flower, leaf, stem, and root. By predicting the effect of rSNPs on TF-binding and by measuring their association with the cultivars, we identified a total of 41,117 rSNPs, of which 1141 are significantly associated with oil content. We revealed several enriched members of the TF families DOF, MYB, NAC, or TCP, which are important for directing transcriptional programs regulating differential expression of genes within the tissues. In this work, we provide the first genome-wide collection of rSNPs for B. napus and their impact on the regulation of gene expression in vegetative and floral tissues, which will be highly valuable for future studies on rSNPs and gene regulation.

Mapping QTL for agronomic traits under two levels of salt stress in a new constructed RIL wheat population

QTL for 15 agronomic traits under two levels of salt stress in dry salinity field were mapped in a new constructed RIL population utilizing a Wheat55K SNP array. Furthermore, eight QTL were validated in a collected natural population. Soil salinity is one of the major abiotic stresses causing serious impact on crop growth, development and yield. As one of the three most important crops in the world, bread wheat (Triticum aestivum L.) is severely affected by salinity, too. In this study, an F₇ recombinant inbred line (RIL) population derived from a cross between high-yield wheat cultivar Zhongmai 175 and salt-tolerant cultivar Xiaoyan 60 was constructed. The adult stage performances of the RIL population and their parent lines under low and high levels of salt stress were evaluated for three consecutive growing seasons. Utilizing a Wheat55K SNP array, a high-density genetic linkage map spinning 3250.71 cM was constructed. QTL mapping showed that 90 stable QTL for 15 traits were detected, and they were distributed on all wheat chromosomes except 4D, 6B and 7D. These QTL individually explained 2.34-32.43% of the phenotypic variation with LOD values ranging from 2.68 to 47.15. It was found that four QTL clusters were located on chromosomes 2D, 3D, 4B and 6A, respectively. Notably, eight QTL from the QTL clusters were validated in a collected natural population. Among them, QPh-4B was deduced to be an allele of Rht-B1. In addition, three kompetitive allele-specific PCR (KASP) markers derived from SNPs were successfully designed for three QTL clusters. This study provides an important base for salt-tolerant QTL (gene) cloning in wheat, and the markers, especially the KASP markers, will be useful for marker-assisted selection in salt-tolerant wheat breeding.

Identification and Validation of New Stable QTLs for Grain Weight and Size by Multiple Mapping Models in Common Wheat

Improvement of grain weight and size is an important objective for high-yield wheat breeding. In this study, 174 recombinant inbred lines (RILs) derived from the cross between Jing 411 and Hongmangchun 21 were used to construct a high-density genetic map by specific locus amplified fragment sequencing (SLAF-seq). Three mapping methods, including inclusive composite interval mapping (ICIM), genome-wide composite interval mapping (GCIM), and a mixed linear model performed with forward-backward stepwise (NWIM), were used to identify QTLs for thousand grain weight (TGW), grain width (GW), and grain length (GL). In total, we identified 30, 15, and 18 putative QTLs for TGW, GW, and GL that explain 1.1-33.9%, 3.1%-34.2%, and 1.7%-22.8% of the phenotypic variances, respectively. Among these, 19 (63.3%) QTLs for TGW, 10 (66.7%) for GW, and 7 (38.9%) for GL were consistent with those identified by genome-wide association analysis in 192 wheat varieties. Five new stable QTLs, including 3 for TGW (Qtgw.ahau-1B.1, Qtgw.ahau-4B.1, and Qtgw.ahau-4B.2) and 2 for GL (Qgl.ahau-2A.1 and Qgl.ahau-7A.2), were detected by the three aforementioned mapping methods across environments. Subsequently, five cleaved amplified polymorphic sequence (CAPS) markers corresponding to these QTLs were developed and validated in 180 Chinese mini-core wheat accessions. In addition, 19 potential candidate genes for Qtgw.ahau-4B.2 in a 0.31-Mb physical interval were further annotated, of which TraesCS4B02G376400 and TraesCS4B02G376800 encode a plasma membrane H+-ATPase and a serine/threonine-protein kinase, respectively. These new QTLs and CAPS markers will be useful for further marker-assisted selection and map-based cloning of target genes.

RING finger ubiquitin E3 ligase gene TaSDIR1-4A contributes to determination of grain size in common wheat

Salt and drought-induced RING finger1 (SDIR1) is a RING-type E3 ubiquitin ligase that plays a key role in ABA-mediated responses to salinity and drought stress via the ubiquitination pathway in some plant species. However, its function in wheat (Triticum aestivum) is unknown. Here, we isolated a SDIR1 member in wheat, TaSDIR1-4A, and characterized its E3 ubiquitin ligase activity. DNA polymorphism assays showed the presence of two nucleotide variation sites in the promoter region of TaSDIR1-4A, leading to the detection of the haplotypes Hap-4A-1 and Hap-4A-2 in wheat populations. Association analysis showed that TaSDIR1-4A haplotypes were associated with 1000-grain weight (TGW) across a variety of different environments, including well-watered and heat-stress conditions. Genotypes with Hap-4A-2 had higher TGW than those with Hap-4A-1. Phenotypes in both gene-silenced wheat and transgenic Arabidopsis showed that TaSDIR1-4A was a negative regulator of grain size. Gene expression assays indicated that TaSDIR1-4A was most highly expressed in flag leaves, and expression was higher in Hap-4A-1 accessions than in Hap-4A-2 accessions. The difference might be attributable to the fact that TaERF3 (ethylene response factor) can act as a transcriptional repressor of TaSDIR1-4A in Hap-4A-2 but not in Hap-4A-1. Examination of modern wheat varieties shows that the favorable haplotype has been positively selected in breeding programs in China. The functional marker for TaSDIR1-4A developed in this study should be helpful for future wheat breeding.

Appraising the Genetic Architecture of Kernel Traits in Hexaploid Wheat Using GWAS

Kernel morphology is one of the major yield traits of wheat, the genetic architecture of which is always important in crop breeding. In this study, we performed a genome-wide association study (GWAS) to appraise the genetic architecture of the kernel traits of 319 wheat accessions using 22,905 single nucleotide polymorphism (SNP) markers from a wheat 90K SNP array. As a result, 111 and 104 significant SNPs for Kernel traits were detected using four multi-locus GWAS models (mrMLM, FASTmrMLM, FASTmrEMMA, and pLARmEB) and three single-locus models (FarmCPU, MLM, and MLMM), respectively. Among the 111 SNPs detected by the multi-locus models, 24 SNPs were simultaneously detected across multiple models, including seven for kernel length, six for kernel width, six for kernels per spike, and five for thousand kernel weight. Interestingly, the five most stable SNPs (RAC875_29540_391, Kukri_07961_503, tplb0034e07_1581, BS00074341_51, and BobWhite_049_3064) were simultaneously detected by at least three multi-locus models. Integrating these newly developed multi-locus GWAS models to unravel the genetic architecture of kernel traits, the mrMLM approach detected the maximum number of SNPs. Furthermore, a total of 41 putative candidate genes were predicted to likely be involved in the genetic architecture underlining kernel traits. These findings can facilitate a better understanding of the complex genetic mechanisms of kernel traits and may lead to the genetic improvement of grain yield in wheat.

Genetics of yield, abiotic stress tolerance and biofortification in wheat (Triticum aestivum L.)

A review of the available literature on genetics of yield and its component traits, tolerance to abiotic stresses and biofortification should prove useful for future research in wheat in the genomics era. The work reviewed in this article mainly covers the available information on genetics of some important quantitative traits including yield and its components, tolerance to abiotic stresses (heat, drought, salinity and pre-harvest sprouting = PHS) and biofortification (Fe/Zn and phytate contents with HarvestPlus Program) in wheat. Major emphasis is laid on the recent literature on QTL interval mapping and genome-wide association studies, giving lists of known QTL and marker-trait associations. Candidate genes for different traits and the cloned and characterized genes for yield traits along with the molecular mechanism are also described. For each trait, an account of the present status of marker-assisted selection has also been included. The details of available results have largely been presented in the form of tables; some of these tables are included as supplementary files.

Identification of the quantitative trait loci controlling spike-related traits in hexaploid wheat (Triticum aestivum L.)

Totally, 48 loci responsible for six spike-related traits were identified in wheat, and a major locus QGl-4A for grain length was mapped and validated for marker-assisted selection in breeding. Wheat yield is determined by the number of spikes, number of grains per spike (GN), and one-thousand kernel weight (TKW), among which GN and TKW are greatly related to the spike development and thus the spike-related traits, including spike length (SL), number of spikelet per spike (SN), grain length (GL) and grain width (GW). To identify the key loci governing the spike-related traits (SL, SN, GN, TKW, GL and GW), we conducted the quantitative trait loci (QTL) analysis combined with wheat 660K SNP chip and Kompetitive allele-specific PCR (KASP) assay, using the F₂ and F_2:3 populations derived from Luohan6 (LH6) with big spike and grain and Zhengmai366 with small spike and grain, and identified a total of 48 QTLs on 18 chromosomes. Moreover, a major stable QTL for GL on chromosome 4A, designated as QGl-4A, was mapped into a 0.37 cM interval between KASP markers Xib4A-10 and Xib4A-12, corresponding to 20 Mb physical region in the Chinese Spring genome. This QTL explained 17.30% and 5.12% of the phenotypic variation for GL in the F₂ and F_2:3 populations. Further association analysis of flanking markers Xib4A-10 and Xib4A-12 in 192 wheat varieties showed that these two markers could be used for marker-assisted selection in breeding. These results provide valuable information for map-based cloning of the target genes involved in the regulation of spike-related traits in common wheat.

Dissecting the Genetic Basis of Grain Size and Weight in Barley (Hordeum vulgare L.) by QTL and Comparative Genetic Analyses

Grain size and weight are crucial components of barley yield and quality and are the target characteristics of domestication and modern breeding. Despite this, little is known about the genetic and molecular mechanisms of grain size and weight in barley. Here, we evaluated nine traits determining grain size and weight, including thousand grain weight (Tgw), grain length (Gl), grain width (Gw), grain length-width ratio (Lwr), grain area (Ga), grain perimeter (Gp), grain diameter (Gd), grain roundness (Gr), and factor form density (Ffd), in a double haploid (DH) population for three consecutive years. Using five mapping methods, we successfully identified 60 reliable QTLs and 27 hotspot regions that distributed on all chromosomes except 6H which controls the nine traits of grain size and weight. Moreover, we also identified 164 barley orthologs of 112 grain size/weight genes from rice, maize, wheat and 38 barley genes that affect grain yield. A total of 45 barley genes or orthologs were identified as potential candidate genes for barley grain size and weight, including 12, 20, 9, and 4 genes or orthologs for barley, rice, maize, and wheat, respectively. Importantly, 20 of them were located in the 14 QTL hotspot regions on chromosome 1H, 2H, 3H, 5H, and 7H, which controls barley grain size and weight. These results indicated that grain size/weight genes of other cereal species might have the same or similar functions in barley. Our findings provide new insights into the understanding of the genetic basis of grain size and weight in barley, and new information to facilitate high-yield breeding in barley. The function of these potential candidate genes identified in this study are worth exploring and studying in detail.

Genomic Regions From an Iranian Landrace Increase Kernel Size in Durum Wheat

Kernel size and shape are important parameters determining the wheat profitability, being main determinants of yield and its technological quality. In this study, a segregating population of 118 recombinant inbred lines, derived from a cross between the Iranian durum landrace accession "Iran_249" and the Iranian durum cultivar "Zardak", was used to investigate durum wheat kernel morphology factors and their relationships with kernel weight, and to map the corresponding QTLs. A high density genetic map, based on wheat 90k iSelect Infinium SNP assay, comprising 6,195 markers, was developed and used to perform the QTL analysis for kernel length and width, traits related to kernel shape and weight, and heading date, using phenotypic data from three environments. Overall, a total of 31 different QTLs and 9 QTL interactions for kernel size, and 21 different QTLs and 5 QTL interactions for kernel shape were identified. The landrace Iran_249 contributed the allele with positive effect for most of the QTLs related to kernel length and kernel weight suggesting that the landrace might have considerable potential toward enhancing the existing gene pool for grain shape and size traits and for further yield improvement in wheat. The correlation among traits and co-localization of corresponding QTLs permitted to define 11 clusters suggesting causal relationships between simplest kernel size trait, like kernel length and width, and more complex secondary trait, like kernel shape and weight related traits. Lastly, the recent release of the T. durum reference genome sequence allowed to define the physical interval of our QTL/clusters and to hypothesize novel candidate genes inspecting the gene content of the genomic regions associated to target traits.

Enhancing grain size in durum wheat using RNAi to knockdown GW2 genes

Knocking down GW2 enhances grain size by regulating genes encoding the synthesis of cytokinin, gibberellin, starch and cell wall. Raising crop yield is a priority task in the light of the continuing growth of the world's population and the inexorable loss of arable land to urbanization. Here, the RNAi approach was taken to reduce the abundance of Grain Weight 2 (GW2) transcript in the durum wheat cultivar Svevo. The effect of the knockdown was to increase the grains' starch content by 10-40%, their width by 4-13% and their surface area by 3-5%. Transcriptomic profiling, based on a quantitative real-time PCR platform, revealed that the transcript abundance of genes encoding both cytokinin dehydrogenase 1 and the large subunit of ADP-glucose pyrophosphorylase was markedly increased in the transgenic lines, whereas that of the genes encoding cytokinin dehydrogenase 2 and gibberellin 3-oxidase was reduced. A proteomic analysis of the non-storage fraction extracted from mature grains detected that eleven proteins were differentially represented in the transgenic compared to wild-type grain: some of these were involved, or at least potentially involved, in cell wall development, suggesting a role of GW2 in the regulation of cell division in the wheat grain.

Gene editing and mutagenesis reveal inter-cultivar differences and additivity in the contribution of TaGW2 homoeologues to grain size and weight in wheat

KEY MESSAGE

CRISPR-Cas9-based genome editing and EMS mutagenesis revealed inter-cultivar differences and additivity in the contribution of TaGW2 homoeologues to grain size and weight in wheat. The TaGW2 gene homoeologues have been reported to be negative regulators of grain size (GS) and thousand grain weight (TGW) in wheat. However, the contribution of each homoeologue to trait variation among different wheat cultivars is not well documented. We used the CRISPR-Cas9 system and TILLING to mutagenize each homoeologous gene copy in cultivars Bobwhite and Paragon, respectively. Plants carrying single-copy nonsense mutations in different genomes showed different levels of GS/TGW increase, with TGW increasing by an average of 5.5% (edited lines) and 5.3% (TILLING mutants). In any combination, the double homoeologue mutants showed higher phenotypic effects than the respective single-genome mutants. The double mutants had on average 12.1% (edited) and 10.5% (TILLING) higher TGW with respect to wild-type lines. The highest increase in GS and TGW was shown for triple mutants of both cultivars, with increases in 16.3% (edited) and 20.7% (TILLING) in TGW. The additive effects of the TaGW2 homoeologues were also demonstrated by the negative correlation between the functional gene copy number and GS/TGW in Bobwhite mutants and an F2 population. The highest single-genome increases in GS and TGW in Paragon and Bobwhite were obtained by mutations in the B and D genomes, respectively. These inter-cultivar differences in the phenotypic effects between the TaGW2 gene homoeologues coincide with inter-cultivar differences in the homoeologue expression levels. These results indicate that GS/TGW variation in wheat can be modulated by the dosage of homoeologous genes with inter-cultivar differences in the magnitude of the individual homoeologue effects.

Wheat seed transcriptome reveals genes controlling key traits for human preference and crop adaptation

Analysis of the transcriptome of the developing wheat grain has associated expression of genes with traits involving production (e.g. yield) and quality (e.g. bread quality). Photosynthesis in the grain may be important in retaining carbon that would be lost in respiration during grain filling and may contribute to yield in the late stages of seed formation under warm and dry environments. A small number of genes have been identified as having been selected by humans to optimize the performance of wheat for foods such as bread. Genes determining flour yield in milling have been discovered. Hardness is explained by variations in expression of pin genes. Knowledge of these genes should dramatically improve the efficiency of breeding better climate adapted wheat genotypes.

Genome-Wide Association Studies to Identify Loci and Candidate Genes Controlling Kernel Weight and Length in a Historical United States Wheat Population

Although kernel weight (KW) is a major component of grain yield, its contribution to yield genetic gain during breeding history has been minimal. This highlights an untapped potential for further increases in yield via improving KW. We investigated variation and genetics of KW and kernel length (KL) via genome-wide association studies (GWAS) using a historical and contemporary soft red winter wheat population representing 200 years of selection and breeding history in the United States. The observed changes of KW and KL over time did not show any conclusive trend. The population showed a structure, which was mainly explained by the time and location of germplasm development. Cluster sharing by germplasm from more than one breeding population was suggestive of episodes of germplasm exchange. Using 2 years of field-based phenotyping, we detected 26 quantitative trait loci (QTL) for KW and 27 QTL for KL with -log₁₀(p) > 3.5. The search for candidate genes near the QTL on the wheat genome version IWGSCv1.0 has resulted in over 500 genes. The predicted functions of several of these genes are related to kernel development, photosynthesis, sucrose and starch synthesis, and assimilate remobilization and transport. We also evaluated the effect of allelic polymorphism of genes previously reported for KW and KL by using Kompetitive Allele Specific PCR (KASP) markers. Only TaGW2 showed significant association with KW. Two genes, i.e., TaSus2-2B and TaGS-D1 showed significant association with KL. Further physiological studies are needed to decipher the involvement of these genes in KW and KL development.

Analysis of the functions of TaGW2 homoeologs in wheat grain weight and protein content traits

GW2 is emerging as a key genetic determinant of grain weight in cereal crops; it has three homoeologs (TaGW2-A1, -B1 and -D1) in hexaploid common wheat (Triticum aestivum L.). Here, by analyzing the gene editing mutants that lack one (B1 or D1), two (B1 and D1) or all three (A1, B1 and D1) homoeologs of TaGW2, several insights are gained into the functions of TaGW2-B1 and -D1 in common wheat grain traits. First, both TaGW2-B1 and -D1 affect thousand-grain weight (TGW) by influencing grain width and length, but the effect conferred by TaGW2-B1 is stronger than that of TaGW2-D1. Second, there exists functional interaction between TaGW2 homoeologs because the TGW increase shown by a double mutant (lacking B1 and D1) was substantially larger than that of their single mutants. Third, both TaGW2-B1 and -D1 modulate cell number and length in the outer pericarp of developing grains, with TaGW2-B1 being more potent. Finally, TaGW2 homoeologs also affect grain protein content as this parameter was generally increased in the mutants, especially in the lines lacking two or three homoeologs. Consistent with this finding, two wheat end-use quality-related parameters, flour protein content and gluten strength, were considerably elevated in the mutants. Collectively, our data shed light on functional difference between and additive interaction of TaGW2 homoeologs in the genetic control of grain weight and protein content traits in common wheat, which may accelerate further research on this important gene and its application in wheat improvement.

Genetic analysis of multi-environmental spring wheat trials identifies genomic regions for locus-specific trade-offs for grain weight and grain number

GWAS on multi-environment data identified genomic regions associated with trade-offs for grain weight and grain number. Grain yield (GY) can be dissected into its components thousand grain weight (TGW) and grain number (GN), but little has been achieved in assessing the trade-off between them in spring wheat. In the present study, the Wheat Association Mapping Initiative (WAMI) panel of 287 elite spring bread wheat lines was phenotyped for GY, GN, and TGW in ten environments across different wheat growing regions in Mexico, South Asia, and North Africa. The panel genotyped with the 90 K Illumina Infinitum SNP array resulted in 26,814 SNPs for genome-wide association study (GWAS). Statistical analysis of the multi-environmental data for GY, GN, and TGW observed repeatability estimates of 0.76, 0.62, and 0.95, respectively. GWAS on BLUPs of combined environment analysis identified 38 loci associated with the traits. Among them four loci-6A (85 cM), 5A (98 cM), 3B (99 cM), and 2B (96 cM)-were associated with multiple traits. The study identified two loci that showed positive association between GY and TGW, with allelic substitution effects of 4% (GY) and 1.7% (TGW) for 6A locus and 0.2% (GY) and 7.2% (TGW) for 2B locus. The locus in chromosome 6A (79-85 cM) harbored a gene TaGW2-6A. We also identified that a combination of markers associated with GY, TGW, and GN together explained higher variation for GY (32%), than the markers associated with GY alone (27%). The marker-trait associations from the present study can be used for marker-assisted selection (MAS) and to discover the underlying genes for these traits in spring wheat.

A novel allele of TaGW2-A1 is located in a finely mapped QTL that increases grain weight but decreases grain number in wheat (Triticum aestivum L.)

A novel TaGW2-A1 allele was identified from a stable, robust QTL region, which is pleiotropic for thousand grain weight, grain number per spike, and grain morphometric parameters in wheat. Thousand grain weight (TGW) and grain number per spike (GNS) are two crucial determinants of wheat spike yield, and genetic dissection of their relationships can help to fine-tune these two components and maximize grain yield. By evaluating 191 recombinant inbred lines in 11 field trials, we identified five genomic regions on chromosomes 1B, 3A, 3B, 5B, or 7A that solely influenced either TGW or GNS, and a further region on chromosome 6A that concurrently affected TGW and GNS. The QTL of interest on chromosome 6A, which was flanked by wsnp_BE490604A_Ta_2_1 and wsnp_RFL_Contig1340_448996 and designated as QTgw/Gns.cau-6A, was finely mapped to a genetic interval shorter than 0.538 cM using near isogenic lines (NILs). The elite NILs of QTgw/Gns.cau-6A increased TGW by 8.33%, but decreased GNS by 3.05% in six field trials. Grain Weight 2 (TaGW2-A1), a well-characterized gene that negatively regulates TGW and grain width in wheat, was located within the finely mapped interval of QTgw/Gns.cau-6A. A novel and rare TaGW2-A1 allele with a 114-bp deletion in the 5' flanking region was identified in the parent with higher TGW, and it reduced TaGW2-A1 promoter activity and expression. In conclusion, these results expand our knowledge of the genetic and molecular basis of TGW-GNS trade-offs in wheat. The QTLs and the novel TaGW2-A1 allele are likely useful for the development of cultivars with higher TGW and/or higher GNS.

Transgenerational CRISPR-Cas9 Activity Facilitates Multiplex Gene Editing in Allopolyploid Wheat

The CRISPR-Cas9-based multiplexed gene editing (MGE) provides a powerful method to modify multiple genomic regions simultaneously controlling different agronomic traits in crops. We applied the MGE construct built by combining the tandemly arrayed tRNA–gRNA units to generate heritable mutations in the TaGW2, TaLpx-1, and TaMLO genes of hexaploid wheat. The knockout mutations generated by this construct in all three homoeologous copies of one of the target genes, TaGW2, resulted in a substantial increase in seed size and thousand grain weight. We showed that the non-modified gRNA targets in the early generation plants can be edited by CRISPR-Cas9 in the following generations. Our results demonstrate that transgenerational gene editing activity can serve as the source of novel variation in the progeny of CRISPR-Cas9-expressing plants and suggest that the Cas9-inducible trait transfer for crop improvement can be achieved by crossing the plants expressing the gene editing constructs with the lines of interest.

Application of CRISPR/Cas9 Genome Editing Technology for the Improvement of Crops Cultivated in Tropical Climates: Recent Progress, Prospects, and Challenges

The world population is expected to increase from 7.3 to 9.7 billion by 2050. Pest outbreak and increased abiotic stresses due to climate change pose a high risk to tropical crop production. Although conventional breeding techniques have significantly increased crop production and yield, new approaches are required to further improve crop production in order to meet the global growing demand for food. The Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)/Cas9 (CRISPR-associated protein9) genome editing technology has shown great promise for quickly addressing emerging challenges in agriculture. It can be used to precisely modify genome sequence of any organism including plants to achieve the desired trait. Compared to other genome editing tools such as zinc finger nucleases (ZFNs) and transcriptional activator-like effector nucleases (TALENs), CRISPR/Cas9 is faster, cheaper, precise and highly efficient in editing genomes even at the multiplex level. Application of CRISPR/Cas9 technology in editing the plant genome is emerging rapidly. The CRISPR/Cas9 is becoming a user-friendly tool for development of non-transgenic genome edited crop plants to counteract harmful effects from climate change and ensure future food security of increasing population in tropical countries. This review updates current knowledge and potentials of CRISPR/Cas9 for improvement of crops cultivated in tropical climates to gain resiliency against emerging pests and abiotic stresses.

TaGW2-6A allelic variation contributes to grain size possibly by regulating the expression of cytokinins and starch-related genes in wheat

Functional allelic variants of TaGW2 - 6A produce large grains, possibly via changes in endosperm cells and dry matter by regulating the expression of cytokinins and starch-related genes via the ubiquitin-proteasome system. In wheat, TaGW2-6A coding region allelic variants are closely related to the grain width and weight, but how this region affects grain development has not been fully elucidated; thus, we explored its influence on grain development based mainly on histological and grain filling analyses. We found that the insertion type (NIL31) TaGW2-6A allelic variants exhibited increases in cell numbers and cell size, thereby resulting in a larger (wider) grain size with an accelerated grain milk filling rate, and increases in grain width and weight. We also found that cytokinin (CK) synthesis genes and key starch biosynthesis enzyme AGPase genes were significantly upregulated in the TaGW2-6A allelic variants, while CK degradation genes and starch biosynthesis-negative regulators were downregulated in the TaGW2-6A allelic variants, which was consistent with the changes in cells and grain filling. Thus, we speculate that TaGW2-6A allelic variants are linked with CK signaling, but they also influence the accumulation of starch by regulating the expression of related genes via the ubiquitin-proteasome system to control the grain size and grain weight.

The Conserved and Unique Genetic Architecture of Kernel Size and Weight in Maize and Rice

Maize (Zea mays) is a major staple crop. Maize kernel size and weight are important contributors to its yield. Here, we measured kernel length, kernel width, kernel thickness, hundred kernel weight, and kernel test weight in 10 recombinant inbred line populations and dissected their genetic architecture using three statistical models. In total, 729 quantitative trait loci (QTLs) were identified, many of which were identified in all three models, including 22 major QTLs that each can explain more than 10% of phenotypic variation. To provide candidate genes for these QTLs, we identified 30 maize genes that are orthologs of 18 rice (Oryza sativa) genes reported to affect rice seed size or weight. Interestingly, 24 of these 30 genes are located in the identified QTLs or within 1 Mb of the significant single-nucleotide polymorphisms. We further confirmed the effects of five genes on maize kernel size/weight in an independent association mapping panel with 540 lines by candidate gene association analysis. Lastly, the function of ZmINCW1, a homolog of rice GRAIN INCOMPLETE FILLING1 that affects seed size and weight, was characterized in detail. ZmINCW1 is close to QTL peaks for kernel size/weight (less than 1 Mb) and contains significant single-nucleotide polymorphisms affecting kernel size/weight in the association panel. Overexpression of this gene can rescue the reduced weight of the Arabidopsis (Arabidopsis thaliana) homozygous mutant line in the AtcwINV2 gene (Arabidopsis ortholog of ZmINCW1). These results indicate that the molecular mechanisms affecting seed development are conserved in maize, rice, and possibly Arabidopsis.

Translational genomics of grain size regulation in wheat

Identifying and mapping grain size candidate genes in the wheat genome greatly empowers reverse genetics approaches to improve grain yield potential of wheat. Grain size (GS) or grain weight is believed to be a major driving force for further improvement of wheat yield. Although the large, polyploid genome of wheat poses an obstacle to identifying GS determinants using map-based cloning, a translational genomics approach using GS regulators identified in the model plants rice and Arabidopsis as candidate genes appears to be effective and supports a hypothesis that a conserved genetic network regulates GS in rice and wheat. In this review, we summarize the progress in the studies on GS in the model plants and wheat and identify 45 GS candidate loci in the wheat genome. In silico mapping of these GS loci in the diploid wheat and barley genomes showed (1) several gene families amplified in the wheat lineage, (2) a significant number of the GS genes located in the proximal regions surrounding the centromeres, and (3) more than half of candidate genes to be negative regulators, or their expression negatively related by microRNAs. Identifying and mapping the wheat GS gene homologs will not only facilitate candidate gene analysis, but also open the door to improving wheat yield using reverse genetics approaches by mining desired alleles in landraces and wild ancestors and to developing novel germplasm by TILLING and genome editing technologies.

TaGW2, a Good Reflection of Wheat Polyploidization and Evolution

Hexaploid wheat consists of three subgenomes, namely, A, B, and D. These well-characterized ancestral genomes also exist at the diploid and tetraploid levels, thereby rendering wheat as a good model species for studying polyploidization. Here, we performed intra- and inter-species comparative analyses of wheat and its relatives to dissect polymorphism and differentiation of the TaGW2 genes. Our results showed that genetic diversity of TaGW2 decreased with progression from the diploids to tetraploids and hexaploids. The strongest selection occurred in the promoter regions of TaGW2-6A and TaGW2-6B. Phylogenetic trees clearly indicated that Triticum urartu and Ae. speltoides were the donors of the A and B genomes in tetraploid and hexaploid wheats. Haplotypes detected among hexaploid genotypes traced back to the tetraploid level. Fst and π values revealed that the strongest selection on TaGW2 occurred at the tetraploid level rather than in hexaploid wheat. This infers that grain size enlargement, especially increased kernel width, mainly occurred in tetraploid genotypes. In addition, relative expression levels of TaGW2s significantly declined from the diploid level to tetraploids and hexaploids, further indicating that these genes negatively regulate kernel size. Our results also revealed that the polyploidization events possibly caused much stronger differentiation than domestication and breeding.

Mining and Analysis of SNP in Response to Salinity Stress in Upland Cotton (Gossypium hirsutum L.)

Salinity stress is a major abiotic factor that affects crop output, and as a pioneer crop in saline and alkaline land, salt tolerance study of cotton is particularly important. In our experiment, four salt-tolerance varieties with different salt tolerance indexes including CRI35 (65.04%), Kanghuanwei164 (56.19%), Zhong9807 (55.20%) and CRI44 (50.50%), as well as four salt-sensitive cotton varieties including Hengmian3 (48.21%), GK50 (40.20%), Xinyan96-48 (34.90%), ZhongS9612 (24.80%) were used as the materials. These materials were divided into salt-tolerant group (ST) and salt-sensitive group (SS). Illumina Cotton SNP 70K Chip was used to detect SNP in different cotton varieties. SNPv (SNP variation of the same seedling pre- and after- salt stress) in different varieties were screened; polymorphic SNP and SNPr (SNP related to salt tolerance) were obtained. Annotation and analysis of these SNPs showed that (1) the induction efficiency of salinity stress on SNPv of cotton materials with different salt tolerance index was different, in which the induction efficiency on salt-sensitive materials was significantly higher than that on salt-tolerant materials. The induction of salt stress on SNPv was obviously biased. (2) SNPv induced by salt stress may be related to the methylation changes under salt stress. (3) SNPr may influence salt tolerance of plants by affecting the expression of salt-tolerance related genes.

Identification of Key Proteins and Networks Related to Grain Development in Wheat (Triticum aestivum L.) by Comparative Transcription and Proteomic Analysis of Allelic Variants in TaGW2-6A

In wheat, coding region allelic variants of TaGW2-6A are closely associated with grain width and weight, but the genetic mechanisms involved remain unclear. Thus, to obtain insights into the key functions regulated by TaGW2-6A during wheat grain development, we performed transcriptional and proteomic analyses of TaGW2-6A allelic variants. The transcription results showed that the TaGW2-6A allelic variants differed significantly by several orders of magnitude. Each allelic variant of TaGW2-6A reached its first transcription peak at 6 days after anthesis (DAA), but the insertion type TaGW2-6A allelic variant reached its second peak earlier than the normal type, i.e., at 12 DAA rather than 20 DAA. In total, we identified 228 differentially accumulated protein spots representing 138 unique proteins by two-dimensional gel electrophoresis and tandem MALDI-TOF/TOF-MS in these three stages. Based on the results, we found some key proteins that are closely related to wheat grain development. The results of this analysis improve our understanding of the genetic mechanisms related to TaGW2-6A during wheat grain development as well as providing insights into the biological processes involved in seed formation.