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Review

Genetic Localization and Homologous Genes Mining for Barley Grain Size

by
Yi Hong
1,2,3,4,†,
Mengna Zhang
1,2,3,4,† and
Rugen Xu
1,2,3,4,*
1
Key Laboratory of Plant Functional Genomics of the Ministry of Education, Yangzhou University, Yangzhou 225127, China
2
Jiangsu Key Laboratory of Crop Genomics and Molecular Breeding, Yangzhou University, Yangzhou 225127, China
3
Jiangsu Co-Innovation Center for Modern Production Technology of Grain Crops, Yangzhou University, Yangzhou 225127, China
4
Joint International Research Laboratory of Agriculture and Agri-Product Safety of Ministry of Education of China, Yangzhou University, Yangzhou 225009, China
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Int. J. Mol. Sci. 2023, 24(5), 4932; https://doi.org/10.3390/ijms24054932
Submission received: 29 January 2023 / Revised: 27 February 2023 / Accepted: 27 February 2023 / Published: 3 March 2023
(This article belongs to the Special Issue Genetics and Genomics-Based Crop Improvement and Breeding)
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Abstract

:
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.

1. Introduction

Barley (Hordeum vulgare L.) is one of the earliest domesticated crops, which has a variety of uses and wide adaptability in agriculture [1]. The introduction of semi-dwarf alleles (e.g., uzu, sdw1/denso) increased barley lodging resistance and fertilizer utilization in agricultural production, leading to a large increase in grain yield [2,3,4]. Thanks to the Green Revolution, the global barley yield performance has increased from 1328.2 kg/ha to 2975.5 kg/ha during the past 60 years with an overall increase of 124.02% (FAO 2022, https://www.fao.org/faostat/en/ (accessed on 26 February 2023)). However, with the harsh climatic conditions, excessive exploitation, and stalling breeding process, the barley yield will be threatened [5,6]. How to improve yield to meet the increasing global food demand remains a key issue.
Grain size is a desirable alternative target trait that is closely related to yield and quality. With the technical advances in high-throughput sequencing, positional cloning of the genes regulating grain size has been sequentially reported in monocot and dicot plants including rice (Oryza sativa) [7,8], wheat (Triticum aestivum) [9], maize (Zea mays) [10], Arabidopsis (Arabidopsis thaliana) [11,12], and soybean (Glycine max) [13]. By literally studying genes mostly reported in the model plants Arabidopsis and rice, multiple genetic pathways regulating grain sizes have been proposed. These include the ubiquitin-proteasome pathway, mitogen-activated protein kinase signaling, G protein signaling, phytohormone signaling pathway, HAIKU pathway, and transcriptional regulators [14].
Apart from the Green Revolution genes (e.g., sdw1, uzu1.a) [15,16], row-number genes (e.g., vrs1, Int-c) [17,18] and the naked gene (nud) [19] are also associated with grain size. However, not a single gene in barley associated with grain size has been cloned yet via a map-based cloning technique. This is not only due to its diploid nature, but also because of the large and complex genome in barley, making it more difficult to complete sequence parse and gene annotation. In 2016, the first barley reference genome was released, which offered entry level access for genomic research given that a large number of bases are unknown [20]. Subsequently, the reference genome has been improved and updated, along with the recent release of the barley pan-genome [21,22,23]. Highly abundant repetitive elements in barley genome raise difficulties in assembly, affecting the integrity of the reference genome. Not only is the huge genome size affecting gene mapping and cloning in barley, but also the technical difficulties that sit as bottlenecks in gene functional verification. For instance, compared to rice, suitable materials that can be efficiently used for barley genetic transformation have thus far been very limited. To the best of our knowledge, only the Scottish malting barley cultivar Golden Promise has been recognized as the most efficient genotype for genetic transformation given its best shoot recovery from callus [24,25].
Marker-based mapping approaches such as QTL linkage analysis and whole-genome association studies are the current mainstream methods for identifying the preliminary QTL of grain size in barley. A segregating population used for linkage analysis usually requires bi-parents with significant differences in target traits for better QTL identifications [26]. However, the construction process is time-consuming and labor-intensive due to its specificity. The whole-genome association analysis is based on linkage disequilibrium [27], so the population employed in such an approach requires abundant genetic diversity. Combined with the algorithm, we can detect more loci associated with target traits including rare variations and minor-effect loci.
Furthermore, homology-based cloning and transcriptomic analyses are also performed for gene mining. In general, more accurate and reliable localization results can be achieved through combinations of multiple methods. For example, a major QTL for kernel length–width ratio was identified using QTL mapping and further validated through bulked segregant analysis in wheat [28]. The genetic architecture of the maize kernel size was characterized by the combination of association and linkage mapping [29]. The P1pet locus with pleiotropic effects on the spike and grain-related traits was fine mapped at a genomic interval of less than 1 Mb using linkage analysis, and further RNA-Seq was performed to predict the most possible candidate gene [30].
In this review, we summarized the achievements in the barley grain size research with an emphasis on the results of QTL linkage analysis and genome-wide association studies. Our discussion covers several important QTL hotspots and candidate or homologous genes that have been reported to function on grain size. Additionally, we also list a number of barley homologs from rice, wheat, maize, and Arabidopsis, which offers a theoretical basis for homology-based cloning and molecular mechanism studies.

2. Characteristics of Barley Grain Size

Grain size is one of the yield components with high heritability [31,32], which is closely related to grain shape and weight. Before grain filling, the spikelet hull has already developed and set the volume of the cavity within which the integuments formed the seed coat after fertilization [14]. Both spikelet hull and seed coat affect the final shape of the barley grain. Grain filling is mainly a process of assimilate accumulation, and saccharides, proteins, and lipids are the three primary storage substances accounting for the total dry matter weight [33]. This is a key stage that determines the final grain weight and yield.
The grain size affects not only the yield, but also the quality [34]. Although the quality requirements of malting barley vary among different industry standards (in different countries), the bulk density or thousand-grain weight, proportion of screenings (<2.5 mm), and protein content are all important evaluation metrics [35]. These physicochemical properties reflect the uniformity and commercial value of barley grain, which are closely associated with length, width, plumpness, and weight. A plumper and more uniform grain is preferred to ensure consistent processing and high malt extract yields [17]. Thus, genetic regions associated with grain size tend to coincide with those associated with the malt extract [36].

3. QTL Mapping and Association Studies on Barley Grain Size

During the past 20 years, QTL mapping of barley grain size has produced ample results. The loci controlling grain size was distributed on all seven chromosomes including ~200 QTLs and ~270 MTAs (marker-trait associations) obtained through linkage analysis and whole-genome wide association analysis, respectively. A considerable number of these have been co-detected in multiple studies due to overlapping regions and/or inter-trait correlations. We condensed 78 QTLs and 31 MTAs into 14 QTL hotspots on seven chromosomes (Table 1). Identification of the QTL hotspots was based on the physical positions of the QTLs/MTAs previously reported during the last two decades. Generally, the physical map position of QTLs/MTAs is usually disclosed in published research cases. However, if not, genetic markers associated with the QTLs/MTAs were then used for online blasting against the barley reference genome (Marker (ipk-gatersleben.de)), which identifies the corresponding physical position on the chromosomes. Thresholds were followed when deciding the QTL hotspot: one QTL locus was repeatedly identified by over three independent research cases (overlapped physiological position exist), subsequently, the total spanning physical distance by these QTLs/MTAs was regarded as one QTL hotspot. The QTL hotspots on various chromosomes will be discussed in conjunction with a review of genes related to grain yield in barley and the homologs controlling the seed size, which are reported in other plants (Table 2).

3.1. QTL Hotspots on Chromosome 1H

Based on multiple studies, we identified three QTL hotspots on chromosome 1H involving ten QTLs and six MTAs [5,6,36,37]. There was no QTL hotspot near the centromeric region within which high LD suppresses recombination frequencies. Located in 19–38 Mb, the QTL hotspot1H-1 contains three QTLs and two MTAs from four different studies. Among these, qSL1.1 explained the highest phenotypic variation of 16.40%, which was identified from a panel of BC3-DH lines derived from a cross between Brenda and HS584 [37]. There were two candidate genes in this region, namely, HvGSN1 and HvRSR1. HvGSN1 is an ortholog of rice GSN1 (GRAIN SIZE AND NUMBER1). GSN1 encodes the mitogen-activated protein kinase phosphatase OsMKP1 and negatively regulates the seed size in rice [47]. HvRSR1 is orthologous to rice RSR1, an APETALA2/ethylene-responsive element binding protein family transcription factor. RSR1 indirectly affects the seed size and quality by negatively regulating the expression of type I starch synthesis genes to alter the starch component and fine structure in rice [48]. Having a content ranging from 50.5% to 75.5% in barley, starch inherently affects the grain yield and starch/protein ratios, since grain filling is also a process of starch accumulation [81]. Consequently, further functional characterization of this gene may be of importance.
QTL hotspot1H-2 spans 58 Mb from 333 Mb to 391 Mb and consists of three QTLs and one MTA [5,38,39,40]. QGl.NaTx-1H explained the highest phenotypic variation of 11.90%, which was identified using a DH population derived from a cross between Naso Nijo and TX9425. Despite their lower PVE (phenotypic variation explanation) than 10%, QTL_1H-6 and SCRI_RS_141598 were responsible for more than two grain-related traits. In this hotspot, HvCO9 is considered as one of the candidate genes that regulate flowering under short-day conditions. HvCO9 overexpression in rice plants caused a remarkable delay in flowering, as did Ghd7, which affected the grain size [51]. vrs3 encodes a histone demethylase and controls lateral spikelet development in barley, however, it is an independent recessive gene that has only been reported in two-rowed mutants [50]. We therefore concluded that vrs3 is not the major contributor to this hotspot, but its natural variations remain unclear. Another possible source of this QTL hotspot is suggested by the region’s overlap with two rice grain size genes, OsBSK2 and OsSM1 [49,52]. The rice OsBSK2 encodes a putative brassinosteroid-signaling kinase and positively controls the grain size. Considering that the orthologs of OsBSK2 are extremely conserved among plants (identity >80%), this gene is suggested to be an important candidate.
As for QTL hotspot1H-3 (474–500 Mb), loci controlling the grain size and flowering time are located in this region, which overlap the photoperiod gene PPD-H2/HvFT3 [5,17,39,41,42]. PPD-H2 was considered to be one of the main loci affecting the heading date and yield of barley in numerous studies [54,55]. In general, spring barley varieties with PPD-H2 have an earlier heading period under short-day conditions than long-day conditions, indicating its sensitivity to a short photoperiod. While ppd-H2 is mainly distributed in winter varieties and shows relatively late maturity [56], it can be a reliable candidate for this region. Additionally, we also identified two orthologs from rice and maize co-localizing at QTL hotspot1H-3, namely, HvSLG and Hvincw1 [53,57].

3.2. QTL Hotspots on Chromosome 2H

Chromosome 2H is the longest chromosome with numerous loci that associate with biotic and abiotic stresses. There are two QTL hotspots identified on this chromosome involving 16 QTLs and five MTAs. As for hotspot2H-1 (17–45 Mb), three QTLs (QTL_2H-2, QTL_2H-3, and QTL_2H-4) with high LOD values but low PVE displayed pleiotropic effects and affected the multiple grain traits as described by Sharma et al. [5]. BK_12 and QTL-GL1 are associated with grain length and both showed relatively high LOD values and PVE [41,43]. In this region, another photoperiod gene PPD-H1 can be considered as a candidate gene. PPD-H1 is a major gene affecting the heading date under long-day conditions in barley and has significant effects on agronomic traits including yield components [59,60]. HvSDG725, an ortholog of rice SDG725, which encodes a H3K36 methyltransferase, is also located in this region. SDG725 plays an important role in rice plant growth and wide-ranging defects occur when SDG725 is downregulated including dwarfism, small seeds, shortened internodes, and erect leaves [58].
In hotspot2H-2, the grain size QTLs and MTAs detected in all studies overlapped in this region when the populations consisted of different row-type barleys [6,17,31,39,40,44]. A candidate gene for this hotspot is VRS1, which specifically expresses in lateral spikelets and inhibits their development. Wild and two-rowed cultivated barleys carry the VRS1 while six-rowed barley carries its recessive allele and has fertile lateral spikelets [61]. Despite the number of grains in six-rowed barley being greater, there were generally fewer assimilates accumulated in a single grain and, as a result, a smaller grain size than the two-rowed barley.

3.3. QTL Hotspots on Chromosome 3H

Three hotspots are located in between 0–58 Mb, 454–484 Mb, and 562–565 Mb on chromosome 3H, respectively, where 19 QTLs and five MTAs were identified [5,32,36,37,39,40,41]. For hotspot3H-1, at least three candidate genes have been inferred, namely, HvGI, vrs4, and HvCKX2. HvGI, an ortholog of Arabidopsis GIGANTEA, participates in multiple processes from developmental regulation to physiological metabolism in plants [64]. vrs4 was identified from six-rowed mutants with lateral spikelet fertility and loss of determinacy. Despite this, vrs4 and vrs3 may account for the within-sample variation of grain size, as they were all derived from induced mutants and their roles in natural variations remain unknown [62]. HvCKX2 is orthologous to the rice Gn1a/OsCKX2 gene, which encodes a cytokinin oxidase. It has been identified as a major contributor to grain yield improvement in rice breeding practice [76].
uzu and sdw1/denso are two important candidate genes for QTL hotspot3H-2 and hotspot3H-3, respectively. Semi-dwarf breeding improves the lodging resistance and fertilizer utilization of crops, leading to the enhanced yield. In barley, sdw1/denso and uzu have been designated as Green Revolution genes and possess pleiotropic effects. sdw1/denso encodes a gibberellic acid 20 oxidase enzyme, which is orthologous to sd1, and has negative effects on grain weight and quality [65]. Notably, there was no evidence that sd1 was directly involved in the regulation of grain shape in rice while QTL intervals that overlapped with the sdw1/denso gene were detected to be closely associated with grain area, grain length, grain width, and grain diameter in barley [6,31].
uzu encodes a BR-receptor protein that is orthologous to D61. The BR-insensitive mutants formed small and short grains in the model plants (Arabidopsis and rice) and the uzu also reduced the grain weight by 18.8% in barley, suggesting that the phytohormone brassinosteroid plays an important role in regulating grain development [16,66,82]. In recent research, a major QTL (QGl.NaTx-3H) for grain length was identified near the uzu and explained 6.8–29.8% of the phenotypic variation, and this QTL showed a linkage to uzu but not due to gene pleiotropy [38]. However, cv.TX9425, a semi-dwarf variety carrying uzu used in this study, exhibited a similar small-grain phenotype as BR-insensitive mutants. Therefore, sufficiently strong recombination events are required to demonstrate whether such co-detection is due to the linkage drag or a novel locus controlling grain size.

3.4. QTL Hotspots on Chromosome 4H

There is a hotspot consisting of seven stable QTLs and four MTAs on chromosome 4H. The hotspot4H spans 34 Mb from 6 to 40 Mb and contains seven candidate genes. Vrn-H2 is one of the three vernalization genes in barley that affects heading and flowering [71]. In breeding practice, the selection and utilization of different allelic combinations of vernalization and photoperiod genes can directly affect the grain yield. Another gene of interest involved in spike morphology is INT-C, an ortholog of the maize TB1. INT-C and VRS1 are functionally opposed and show effects interaction, that is, the dominant VRS1 inhibits the development of lateral spikelets, while INT-C promotes fertile spikelets [18]. Since grains from central spikelets are generally expected to be larger and more symmetrical than those from lateral spikelets, INT-C may be an essential factor affecting the grain uniformity in six-rowed barley.
Five orthologs from rice (HvRGB1), maize (HvDek35, Hvemp4), and Arabidopsis (HvAHKs, HvDAR1) were identified in hotspot4H. RGB1 encodes the β-subunit (Gβ) of heterotrimeric G protein. Loss of function and suppression of Gβ result in short seeds in rice, suggesting that Gβ positively regulates the seed length [67]. Dek35 and emp4 mutants with developmental deficiency confer a seed-lethal phenotype in maize [68,70]. Genetic analysis indicated that cytokinin-dependent endospermal and/or maternal control can affect embryo size. Three histidine kinases perceive the cytokinin signal in Arabidopsis: AHK2, AHK3, and CRE1/AHK4 [69]. DA1 affects the seed size in the maternal control by regulating cell proliferation in the integuments redundantly with DAR1 in Arabidopsis [11].

3.5. QTL Hotspots on Chromosome 5H

Chromosome 5H shows significance across almost all grain-related traits (grain length, width, thickness, plumpness, and thousand-grain weight). A total of 16 QTLs and nine MTAs are clustered into three hotspots [5,6,36,39,40,42,43]. As for hotspot5H-1 (0–23 Mb), HvIKU2 and HvPPKL3 are two putative candidates. In Arabidopsis, IKU2 functions zygotically to control the seed size by affecting endosperm development [72]. PPKL3 encodes a protein phosphatase with the Kelch-like repeat domain, and the T-DNA insertion mutants displayed a longer grain phenotype in rice [73].
Hvdep1, a noncanonical Gγ of G protein, is a causal gene for another semi-dwarf locus (ari-e) in barley as described by Wendt et al. [75], which is located in hotspot5H-2 (427–431 Mb). The overexpression and downregulation of DEP1 result in larger and smaller grains in rice, respectively [74]. Genetic transformation also demonstrated that HvDEP1 positively regulates grain size and culm elongation in barley [75].
The QTL hotspot5H-3 (541–588 Mb) consists of seven QTLs and five MTAs and displays associations for all grain-related traits. Among these, QTL-GT2 (grain thickness) and QTL-GP2 (grain plumpness) were two consensus QTLs identified using a DH population derived from the cross Vlamingh × Buloke. There was a high PVE of 15.3% for QTL-GP2, and the linkage maker 8682-406 can be used to screen well-filled varieties in maker assisted breeding. In this region, there are three orthologs from rice (HvDST and HvSK41) and Arabidopsis (HvABA2). Rice zinc finger protein DST associated with abiotic stresses regulates CKX2 expression to enhance grain production [76]. OsSK41 is responsible for a major QTL that controls the grain size and weight in rice [83]. Abscisic acid was reported to control the seed size by regulating the HAIKU pathway, and seeds from ABA-deficient mutants exhibited increased size, mass, and embryo cellularity in Arabidopsis [77].

3.6. QTL Hotspots on Chromosome 6H

A total of seven QTLs and one MTA overlapped an interval of 31 Mb from 463 to 494 Mb for all grain-related traits on chromosome 6H [5,17,32,37,43]. Of these QTLs, qTGW6.1 explained the highest phenotypic variation ranging from 19.60% to 38.30% in multiple environments [37]. The linkage maker of this major QTL can also be used for marker-assisted selection. HvDEK1, an ortholog of maize DEK1, encodes a Calpain-Type Cysteine Protease and is located within this hotspot. In recent years, numerous studies have indicated that DEK1 is important for the development and mechanical stimulation of seeds, leaves, and flowers. Kernels from maize dek1 mutants are small and lacking plumpness, and deeper investigations showed that the normal DEK1 gene products are required for aleurone cell fate specification [78,84]. Another candidate gene is LEC1, which encodes a transcriptional factor that regulates seed development. Mutation in the LEC1 gene not only alters the normal developmental rhythm and pattern, resulting in abnormal embryos, but also affects the accumulation of storage substances in Arabidopsis and maize [80,85].

3.7. QTL Hotspots on Chromosome 7H

There are many QTLs and MTAs across the entire 7H chromosome, but most of these occupy separate positions according to multiple studies. We clustered four consensus QTLs and one MTA within this chromosomal interval from 519 Mb to 540 Mb into a QTL hotspot, where the Nud gene is a candidate for grain size [6,19,31,40,41]. Similar to VRS1 and INT-C, this region can be detected in almost all studies if the populations consist of naked and hulled barley. With the deletion of Nud, naked barley is produced free-threshing after maturity, resulting in altered grain dimension and weight compared to hulled barley. Previous studies have also reported that yield-related QTLs are tightly linked to the nud gene [86,87].

3.8. Interrelationships of QTL Hotspots

As above-mentioned, numerous mapping experiments revealed multiple QTL hotspots that control the barley grain size on seven chromosomes. According to these candidate genes, several QTL hotspots are found to share common features, especially containing phytohormone-related genes, indicating potential interactions with each other.
Plant hormones play important roles in seed formation and can affect the grain size directly or indirectly. Among the 14 QTL hotspots we summarized, eight contained candidate genes related to plant hormones. Brassinosteroid (BR) is one of the hormones essential for plant height, spike architecture, and organ size. BSK2 (Hotspot1H-2) and SLG (Hotspot1H-3) affect the seed size by altering the length of the epidermal cells of the spikelet hull through cell expansion in rice [49,53]. BSK2 interacts directly with BRI1 (hotspot3H-2) and affects grain size independent of the BR signaling pathway, while SLG is involved in BR homeostasis by positively regulating endogenous BR levels. SDG725 (hotspot2H-1) can modulate brassinosteroid-related gene expression through epigenetic regulation including BRI1 to affect plant growth and development in rice [58]. Cytokinin (CK) is another key regulator of plant growth and cytokinin oxidase/dehydrogenases (CKXs) catalyze CK degradation irreversibly. In previous studies, the iku2-2 (hotspot5H-1) seed size phenotype can be partially restored by overexpressing CKX2 (hotspot3H-1) in Arabidopsis [63]. Moreover, the DST-directed (hotspot5H-3) expression of rice CKX2 affects CK accumulation in the shoot apical meristem, which controls the reproductive organ number [76].

4. Homologous Gene Mining of Grain Size

Grain size regulation involves a complex genetic network controlling the development of spikelet hulls, integuments, and endosperms, which are all determined components of the final grain size. Recent advances have cloned numerous genes that are involved in several networks to control the grain size including the ubiquitin-proteasome pathway, mitogen-activated protein kinase signaling, G protein signaling, phytohormone signaling pathway, HAIKU pathway, and transcriptional regulators. Some of them also exhibit genetic interactions and integrate multiple signaling pathways. These findings not only shed new light on our understanding of molecular mechanisms, but also provide key ideas for the research of homologs in other crops. For instance, TaGW2 and TaTGW6-A1, which encode E3 ubiquitin ligase and indole-3-acetic acid (IAA)-glucose hydrolase, respectively, have been cloned by comparative genomics approaches. Polymorphism and haplotype analysis indicated that they are strongly associated with grain size and weight in wheat [88,89].
Orthology, which is of great interest, paralogy, and xenology are three main subclasses of homology used to describe the evolutionary relationships between species. As more high-quality genomes are being released, whole-genome alignment (WGA) is becoming a powerful tool for gaining insights into the evolutionary scope. Despite species divergence, numerous genetic features of ancestry are retained, resulting in a high level of genome collinearity among closely related species. Gene type, order, and orientation are relatively conserved within collinear blocks [90]. Based on collinearity and gene homolog analyses, 29 candidate genes related to seed shattering were identified in Chinese wild rice [91].
To facilitate homology-based cloning, here we list 190 barley orthologs of 142 grain size genes in other plants according to the Ensemble database (http://plants.ensembl.org/index.html (accessed on 26 February 2023)) (Table S1). Rice is responsible for 110 of them, maize for 46, Arabidopsis for 25, and wheat for nine. Unsurprisingly, 21 grain size genes do not create a one-to-one correspondence in barley. Some of these orthologs (e.g., HvZM-INVINH1) are the results of tandem gene duplication, while others (e.g., HvMADS87) are distributed on several chromosomes due to interspersed gene duplication. Collinearity analyses using TBtools software showed extensive genome collinearity between barley and gramineous crops, but a low degree of genome collinearity between barley and Arabidopsis [92]. In the 190 barley orthologs analyzed, 81 shared significant collinearity with other plants, indicating deeply conserved functions (Figure 1 and Table S1, References [93,94,95,96,97,98,99,100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,122,123,124,125,126,127,128,129,130,131,132,133,134,135,136,137,138,139,140,141,142,143,144,145,146,147,148,149,150,151,152,153,154,155,156,157,158,159,160,161,162,163,164,165,166,167,168,169,170,171,172,173,174,175,176,177,178,179,180,181,182,183,184,185,186,187,188,189,190,191,192,193,194,195,196,197,198,199,200,201,202,203,204,205,206,207,208,209,210,211,212] are cited in Table S1). We finally mapped these collinearity genes to the reference genome, which can provide a theoretical basis for further studies (Figure 2).

5. Conclusions and Perspectives

During the past two decades, significant achievements have been witnessed in crop yield and yield components, despite the threat of both biotic and abiotic stress. Grain size with high heritability has long been a primary target of breeding, which is closely related to final yield and quality. Thanks to linkage analysis and whole-genome association analysis, hundreds of grain size QTLs were identified. However, the PVE of these QTLs varied depending on the study materials and methods. How to systematically evaluate the genetic effects of these QTLs and the potential application of linkage markers in different genetic contexts are crucial in marker-assisted breeding.
According to the published data, the cloning of barley genes has been relatively rare, making it hard to identify the regulatory networks of grain size. In the future, more efforts should be invested in the fine-mapping of these reported QTLs to isolate the causal gene. On the other hand, substantial evidence from genetics and molecular biology has suggested that large SVs (structure variations) identified from the pan-genome can cause the phenotypic variance affecting many important agronomic traits [22,212,213]. Compared to traditional SNP-based GWAS, PAV-based GWAS (presence and absence variation, PAV) enable the precise identification of trait-associated genomic regions and can complement SNP-based GWAS. In barley, therefore, taking full advantage of the published pan-genomic data to mine variations will become a new strategy.
The CRISPR/Cas9 system serves as a revolutionary technique in molecular design breeding and varietal improvement in many crops. With gene editing, target function-deficient mutants can be created rapidly and efficiently without introducing exogenous genes into the genetic background. It can directly influence gene expression at the transcriptional levels, making it a mainstream tool for gene functional validation. The combination of comparative genomics and gene-editing technology will be very practical for the study of unknown genes or orthologs, and will help constantly refine the regulatory network of grain size in barley.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/ijms24054932/s1.

Author Contributions

R.X. designed the article; Y.H. and M.Z. collected all the data and wrote the manuscript. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by the National Key Research and Development Program of China (2021YFD1000301); the National Modern Agriculture Industry Technology System, China (CARS-05); and the Priority Academic Program Development of Jiangsu Higher Education Institutions, China (PAPD).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Data sharing not applicable.

Acknowledgments

The authors would like to thank Juan Zhu (Yangzhou University) and Meixue Zhou (University of Tasmania) for their help in polishing the language.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Pankin, A.; Altmüller, J.; Becker, C.; von Korff, M. Targeted Resequencing Reveals Genomic Signatures of Barley Domestication. New Phytol. 2018, 218, 1247–1259. [Google Scholar] [CrossRef] [Green Version]
  2. Chono, M.; Honda, I.; Zeniya, H.; Yoneyama, K.; Saisho, D.; Takeda, K.; Takatsuto, S.; Hoshino, T.; Watanabe, Y. A Semidwarf Phenotype of Barley Uzu Results from a Nucleotide Substitution in the Gene Encoding a Putative Brassinosteroid Receptor. Plant Physiol. 2003, 133, 1209–1219. [Google Scholar] [CrossRef] [Green Version]
  3. Jia, Q.; Zhang, J.; Westcott, S.; Zhang, X.-Q.; Bellgard, M.; Lance, R.; Li, C. GA-20 Oxidase as a Candidate for the Semidwarf Gene Sdw1/Denso in Barley. Funct. Integr. Genom. 2009, 9, 255–262. [Google Scholar] [CrossRef] [Green Version]
  4. Nadolska-Orczyk, A.; Rajchel, I.K.; Orczyk, W.; Gasparis, S. Major Genes Determining Yield-Related Traits in Wheat and Barley. Theor. Appl. Genet. 2017, 130, 1081–1098. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  5. Sharma, R.; Draicchio, F.; Bull, H.; Herzig, P.; Maurer, A.; Pillen, K.; Thomas, W.T.B.; Flavell, A.J. Genome-Wide Association of Yield Traits in a Nested Association Mapping Population of Barley Reveals New Gene Diversity for Future Breeding. J. Exp. Bot. 2018, 69, 3811–3822. [Google Scholar] [CrossRef] [PubMed]
  6. Wang, Q.; Sun, G.; Ren, X.; Du, B.; Cheng, Y.; Wang, Y.; Li, C.; Sun, D. Dissecting the Genetic Basis of Grain Size and Weight in Barley (Hordeum vulgare L.) by QTL and Comparative Genetic Analyses. Front. Plant Sci. 2019, 10, 496. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  7. Si, L.; Chen, J.; Huang, X.; Gong, H.; Luo, J.; Hou, Q.; Zhou, T.; Lu, T.; Zhu, J.; Shangguan, Y.; et al. OsSPL13 Controls Grain Size in Cultivated Rice. Nat. Genet. 2016, 48, 447–456. [Google Scholar] [CrossRef]
  8. Tang, Z.; Gao, X.; Zhan, X.; Fang, N.; Wang, R.; Zhan, C.; Zhang, J.; Cai, G.; Cheng, J.; Bao, Y.; et al. Natural Variation in OsGASR7 Regulates Grain Length in Rice. Plant Biotechnol. J. 2021, 19, 14–16. [Google Scholar] [CrossRef] [PubMed]
  9. Hu, M.-J.; Zhang, H.-P.; Liu, K.; Cao, J.-J.; Wang, S.-X.; Jiang, H.; Wu, Z.-Y.; Lu, J.; Zhu, X.F.; Xia, X.-C.; et al. Cloning and Characterization of TaTGW-7A Gene Associated with Grain Weight in Wheat via SLAF-Seq-BSA. Front. Plant Sci. 2016, 7, 1902. [Google Scholar] [CrossRef] [Green Version]
  10. Li, Y.; Ma, S.; Zhao, Q.; Lv, D.; Wang, B.; Xiao, K.; Zhu, J.; Li, S.; Yang, W.; Liu, X.; et al. ZmGRAS11, Transactivated by Opaque2, Positively Regulates Kernel Size in Maize. J. Integr. Plant Biol. 2021, 63, 2031–2037. [Google Scholar] [CrossRef]
  11. Li, Y.; Zheng, L.; Corke, F.; Smith, C.; Bevan, M.W. Control of Final Seed and Organ Size by the DA1 Gene Family in Arabidopsis Thaliana. Genes Dev. 2008, 22, 1331–1336. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  12. Fang, W.; Wang, Z.; Cui, R.; Li, J.; Li, Y. Maternal Control of Seed Size by EOD3/CYP78A6 in Arabidopsis Thaliana. Plant J. 2012, 70, 929–939. [Google Scholar] [CrossRef] [PubMed]
  13. Lu, X.; Xiong, Q.; Cheng, T.; Li, Q.-T.; Liu, X.-L.; Bi, Y.-D.; Li, W.; Zhang, W.-K.; Ma, B.; Lai, Y.-C.; et al. A PP2C-1 Allele Underlying a Quantitative Trait Locus Enhances Soybean 100-Seed Weight. Mol. Plant 2017, 10, 670–684. [Google Scholar] [CrossRef] [Green Version]
  14. Li, N.; Xu, R.; Li, Y. Molecular Networks of Seed Size Control in Plants. Annu. Rev. Plant Biol. 2019, 70, 435–463. [Google Scholar] [CrossRef] [PubMed]
  15. Jia, Q.; Zhang, X.-Q.; Westcott, S.; Broughton, S.; Cakir, M.; Yang, J.; Lance, R.; Li, C. Expression Level of a Gibberellin 20-Oxidase Gene Is Associated with Multiple Agronomic and Quality Traits in Barley. Theor. Appl. Genet. 2011, 122, 1451–1460. [Google Scholar] [CrossRef]
  16. Chen, G.; Li, H.; Wei, Y.; Zheng, Y.-L.; Zhou, M.; Liu, C. Pleiotropic Effects of the Semi-Dwarfing Gene Uzu in Barley. Euphytica 2016, 209, 749–755. [Google Scholar] [CrossRef]
  17. Ayoub, M.; Symons, S.; Edney, M.; Mather, D. QTLs Affecting Kernel Size and Shape in a Two-Rowed by Six-Rowed Barley Cross. Theor. Appl. Genet. 2002, 105, 237–247. [Google Scholar] [CrossRef] [PubMed]
  18. Ramsay, L.; Comadran, J.; Druka, A.; Marshall, D.F.; Thomas, W.T.B.; MacAulay, M.; MacKenzie, K.; Simpson, C.; Fuller, J.; Bonar, N.; et al. INTERMEDIUM-C, a Modifier of Lateral Spikelet Fertility in Barley, Is an Ortholog of the Maize Domestication Gene TEOSINTE BRANCHED 1. Nat. Genet. 2011, 43, 169–172. [Google Scholar] [CrossRef]
  19. Taketa, S.; Amano, S.; Tsujino, Y.; Sato, T.; Saisho, D.; Kakeda, K.; Nomura, M.; Suzuki, T.; Matsumoto, T.; Sato, K.; et al. Barley Grain with Adhering Hulls Is Controlled by an ERF Family Transcription Factor Gene Regulating a Lipid Biosynthesis Pathway. Proc. Natl. Acad. Sci. USA 2008, 105, 4062–4067. [Google Scholar] [CrossRef] [Green Version]
  20. Mascher, M.; Gundlach, H.; Himmelbach, A.; Beier, S.; Twardziok, S.O.; Wicker, T.; Radchuk, V.; Dockter, C.; Hedley, P.E.; Russell, J.; et al. A Chromosome Conformation Capture Ordered Sequence of the Barley Genome. Nature 2017, 544, 427–433. [Google Scholar] [CrossRef] [Green Version]
  21. Monat, C.; Padmarasu, S.; Lux, T.; Wicker, T.; Gundlach, H.; Himmelbach, A.; Ens, J.; Li, C.; Muehlbauer, G.J.; Schulman, A.H.; et al. TRITEX: Chromosome-Scale Sequence Assembly of Triticeae Genomes with Open-Source Tools. Genome Biol. 2019, 20, 284. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  22. Jayakodi, M.; Padmarasu, S.; Haberer, G.; Bonthala, V.S.; Gundlach, H.; Monat, C.; Lux, T.; Kamal, N.; Lang, D.; Himmelbach, A.; et al. The Barley Pan-Genome Reveals the Hidden Legacy of Mutation Breeding. Nature 2020, 588, 284–289. [Google Scholar] [CrossRef] [PubMed]
  23. Mascher, M.; Wicker, T.; Jenkins, J.; Plott, C.; Lux, T.; Koh, C.S.; Ens, J.; Gundlach, H.; Boston, L.B.; Tulpová, Z.; et al. Long-Read Sequence Assembly: A Technical Evaluation in Barley. Plant Cell 2021, 33, 1888–1906. [Google Scholar] [CrossRef] [PubMed]
  24. Hensel, G.; Valkov, V.; Middlefell-Williams, J.; Kumlehn, J. Efficient Generation of Transgenic Barley: The Way Forward to Modulate Plant-Microbe Interactions. J. Plant Physiol. 2008, 165, 71–82. [Google Scholar] [CrossRef]
  25. Shawky Ibrahim, A.; Mohamed El-Shihy, O.; Hussein Fahmy, A. Highly Efficient Agrobacterium Tumefaciens-Meditaed Transformation of Elite Egyptian Barley Cultivars. Am. J. Sustain. Agric. 2010, 4, 403–413. [Google Scholar]
  26. Soller, M.; Beckmann, J.S. Marker-Based Mapping of Quantitative Trait Loci Using Replicated Progenies. Theor. Appl. Genet. 1990, 80, 205–208. [Google Scholar] [CrossRef]
  27. Gupta, P.K.; Rustgi, S.; Kulwal, P.L. Linkage Disequilibrium and Association Studies in Higher Plants: Present Status and Future Prospects. Plant Mol. Biol. 2005, 57, 461–485. [Google Scholar] [CrossRef]
  28. Xin, F.; Zhu, T.; Wei, S.; Han, Y.; Zhao, Y.; Zhang, D.; Ma, L.; Ding, Q. QTL Mapping of Kernel Traits and Validation of a Major QTL for Kernel Length-Width Ratio Using SNP and Bulked Segregant Analysis in Wheat. Sci. Rep. 2020, 10, 25. [Google Scholar] [CrossRef] [Green Version]
  29. Liu, M.; Tan, X.; Yang, Y.; Liu, P.; Zhang, X.; Zhang, Y.; Wang, L.; Hu, Y.; Ma, L.; Li, Z.; et al. Analysis of the Genetic Architecture of Maize Kernel Size Traits by Combined Linkage and Association Mapping. Plant Biotechnol. J. 2020, 18, 207–221. [Google Scholar] [CrossRef] [Green Version]
  30. Xiao, J.; Chen, Y.; Lu, Y.; Liu, Z.; Si, D.; Xu, T.; Sun, L.; Wang, Z.; Yuan, C.; Sun, H.; et al. A Natural Variation of an SVP MADS-Box Transcription Factor in Triticum Petropavlovskyi Leads to Its Ectopic Expression and Contributes to Elongated Glume. Mol. Plant 2021, 14, 1408–1411. [Google Scholar] [CrossRef]
  31. Du, B.; Wang, Q.; Sun, G.; Ren, X.; Cheng, Y.; Wang, Y.; Gao, S.; Li, C.; Sun, D. Mapping Dynamic QTL Dissects the Genetic Architecture of Grain Size and Grain Filling Rate at Different Grain-Filling Stages in Barley. Sci. Rep. 2019, 9, 18823. [Google Scholar] [CrossRef] [Green Version]
  32. Zhou, H.; Luo, W.; Gao, S.; Ma, J.; Zhou, M.; Wei, Y.; Zheng, Y.; Liu, Y.; Liu, C. Identification of Loci and Candidate Genes Controlling Kernel Weight in Barley Based on a Population for Which Whole Genome Assemblies Are Available for Both Parents. Crop J. 2021, 9, 854–861. [Google Scholar] [CrossRef]
  33. Henry, R.J. The Carbohydrates of Barley Grains—A Review. J. Inst. Brew. 1988, 94, 71–78. [Google Scholar] [CrossRef]
  34. Coventry, S.J.; Barr, A.R.; Eglinton, J.K.; McDonald, G.K. The Determinants and Genome Locations Influencing Grain Weight and Size in Barley (Hordeum vulgare L.). Aust. J. Agric. Res. 2003, 54, 1103. [Google Scholar] [CrossRef]
  35. Zheng, M.; Yue, H.; Guo, X. Comparative Analysis of Quality Standards of Brewing Barley in China and Australia. Glob. Alcinfo 2019, 23–33. [Google Scholar]
  36. Walker, C.K.; Ford, R.; Muñoz-Amatriaín, M.; Panozzo, J.F. The Detection of QTLs in Barley Associated with Endosperm Hardness, Grain Density, Grain Size and Malting Quality Using Rapid Phenotyping Tools. Theor. Appl. Genet. 2013, 126, 2533–2551. [Google Scholar] [CrossRef]
  37. Kalladan, R.; Worch, S.; Rolletschek, H.; Harshavardhan, V.T.; Kuntze, L.; Seiler, C.; Sreenivasulu, N.; Röder, M.S. Identification of Quantitative Trait Loci Contributing to Yield and Seed Quality Parameters under Terminal Drought in Barley Advanced Backcross Lines. Mol. Breed. 2013, 32, 71–90. [Google Scholar] [CrossRef]
  38. Wang, J.; Wu, X.; Yue, W.; Zhao, C.; Yang, J.; Zhou, M. Identification of QTL for Barley Grain Size. PeerJ 2021, 9, e11287. [Google Scholar] [CrossRef]
  39. Xu, X.; Sharma, R.; Tondelli, A.; Russell, J.; Comadran, J.; Schnaithmann, F.; Pillen, K.; Kilian, B.; Cattivelli, L.; Thomas, W.T.B.; et al. Genome-Wide Association Analysis of Grain Yield-Associated Traits in a Pan-European Barley Cultivar Collection. Plant Genome 2018, 11, 170073. [Google Scholar] [CrossRef]
  40. Pasam, R.K.; Sharma, R.; Malosetti, M.; van Eeuwijk, F.A.; Haseneyer, G.; Kilian, B.; Graner, A. Genome-Wide Association Studies for Agronomical Traits in a World Wide Spring Barley Collection. BMC Plant Biol. 2012, 12, 16. [Google Scholar] [CrossRef] [Green Version]
  41. Gordon, T.; Wang, R.; Bowman, B.; Klassen, N.; Wheeler, J.; Bonman, J.M.; Bockelman, H.; Chen, J. Agronomic and Genetic Assessment of Terminal Drought Tolerance in Two-row Spring Barley. Crop Sci. 2020, 60, 1415–1427. [Google Scholar] [CrossRef]
  42. Fang, Y.; Zhang, X.; Zhang, X.; Tong, T.; Zhang, Z.; Wu, G.; Hou, L.; Zheng, J.; Niu, C.; Li, J.; et al. A High-Density Genetic Linkage Map of SLAFs and QTL Analysis of Grain Size and Weight in Barley (Hordeum vulgare L.). Front. Plant Sci. 2020, 11, 620922. [Google Scholar] [CrossRef] [PubMed]
  43. Watt, C.; Zhou, G.; McFawn, L.A.; Chalmers, K.J.; Li, C. Fine Mapping of QGL5H, a Major Grain Length Locus in Barley (Hordeum vulgare L.). Theor. Appl. Genet. 2019, 132, 883–893. [Google Scholar] [CrossRef]
  44. Wang, J.; Sun, G.; Ren, X.; Li, C.; Liu, L.; Wang, Q.; Du, B.; Sun, D. QTL Underlying Some Agronomic Traits in Barley Detected by SNP Markers. BMC Genet. 2016, 17, 103. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  45. Zhou, H.; Liu, S.; Liu, Y.; Liu, Y.; You, J.; Deng, M.; Ma, J.; Chen, G.; Wei, Y.; Liu, C.; et al. Mapping and Validation of Major Quantitative Trait Loci for Kernel Length in Wild Barley (Hordeum vulgare ssp. Spontaneum). BMC Genet. 2016, 17, 130. [Google Scholar] [CrossRef] [Green Version]
  46. Watt, C.; Zhou, G.; McFawn, L.A.; Li, C. Fine Mapping QGL2H, a Major Locus Controlling Grain Length in Barley (Hordeum vulgare L.). Theor. Appl. Genet. 2020, 133, 2095–2103. [Google Scholar] [CrossRef] [Green Version]
  47. Guo, T.; Chen, K.; Dong, N.Q.; Shi, C.L.; Ye, W.W.; Gao, J.P.; Shan, J.X.; Lin, H.X. GRAIN SIZE AND NUMBER1 Negatively Regulates the OSMKKK10-OSMKK4-OSMPK6 Cascade to Coordinate the Trade-off between Grain Number per Panicle and Grain Size in Rice. Plant Cell 2018, 30, 871–888. [Google Scholar] [CrossRef] [Green Version]
  48. Fu, F.F.; Xue, H.W. Coexpression Analysis Identifies Rice Starch Regulator1, a Rice AP2/EREBP Family Transcription Factor, as a Novel Rice Starch Biosynthesis Regulator. Plant Physiol. 2010, 154, 927–938. [Google Scholar] [CrossRef]
  49. Yuan, H.; Xu, Z.; Chen, W.; Deng, C.; Liu, Y.; Yuan, M.; Gao, P.; Shi, H.; Tu, B.; Li, T.; et al. OsBSK2, a Putative Brassinosteroid-Signalling Kinase, Positively Controls Grain Size in Rice. J. Exp. Bot. 2022, 73, 5529–5542. [Google Scholar] [CrossRef]
  50. van Esse, G.W.; Walla, A.; Finke, A.; Koornneef, M.; Pecinka, A.; von Korff, M. Six-Rowed Spike3 (VRS3) Is a Histone Demethylase That Controls Lateral Spikelet Development in Barley. Plant Physiol. 2017, 174, 2397–2408. [Google Scholar] [CrossRef] [Green Version]
  51. Kikuchi, R.; Kawahigashi, H.; Oshima, M.; Ando, T.; Handa, H. The Differential Expression of HvCO9, a Member of the CONSTANS-like Gene Family, Contributes to the Control of Flowering under Short-Day Conditions in Barley. J. Exp. Bot. 2012, 63, 773–784. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  52. Aya, K.; Hobo, T.; Sato-Izawa, K.; Ueguchi-Tanaka, M.; Kitano, H.; Matsuoka, M. A Novel AP2-Type Transcription Factor, SMALL ORGAN SIZE1, Controls Organ Size Downstream of an Auxin Signaling Pathway. Plant Cell Physiol. 2014, 55, 897–912. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  53. Feng, Z.; Wu, C.; Wang, C.; Roh, J.; Zhang, L.; Chen, J.; Zhang, S.; Zhang, H.; Yang, C.; Hu, J.; et al. SLG Controls Grain Size and Leaf Angle by Modulating Brassinosteroid Homeostasis in Rice. J. Exp. Bot. 2016, 67, 4241–4253. [Google Scholar] [CrossRef] [Green Version]
  54. Casao, M.C.; Karsai, I.; Igartua, E.; Gracia, M.P.; Veisz, O.; Casas, A.M. Adaptation of Barley to Mild Winters: A Role for PPDH2. BMC Plant Biol. 2011, 11, 164. [Google Scholar] [CrossRef] [Green Version]
  55. Zitzewitz, J.; Cuesta-Marcos, A.; Condon, F.; Castro, A.J.; Chao, S.; Corey, A.; Filichkin, T.; Fisk, S.P.; Gutierrez, L.; Haggard, K.; et al. The Genetics of Winterhardiness in Barley: Perspectives from Genome-Wide Association Mapping. Plant Genome 2011, 4, 76–91. [Google Scholar] [CrossRef] [Green Version]
  56. Faure, S.; Higgins, J.; Turner, A.; Laurie, D.A. The FLOWERING LOCUS T-like Gene Family in Barley (Hordeum vulgare). Genetics 2007, 176, 599–609. [Google Scholar] [CrossRef] [Green Version]
  57. Liu, J.; Huang, J.; Guo, H.; Lan, L.; Wang, H.; Xu, Y.; Yang, X.; Li, W.; Tong, H.; Xiao, Y.; et al. The Conserved and Unique Genetic Architecture of Kernel Size and Weight in Maize and Rice. Plant Physiol. 2017, 175, 774–785. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  58. Sui, P.; Jin, J.; Ye, S.; Mu, C.; Gao, J.; Feng, H.; Shen, W.H.; Yu, Y.; Dong, A. H3K36 Methylation Is Critical for Brassinosteroid-Regulated Plant Growth and Development in Rice. Plant J. 2012, 70, 340–347. [Google Scholar] [CrossRef]
  59. Karsai, I.; Eszaros, K.M.; Szucs, P.; Hayes, P.M.; Lang, L.; Bedo, Z. Effects of Loci Determining Photoperiod Sensitivity (Ppd-H1) and Vernalization Response (Sh2) on Agronomic Traits in the “Dicktoo” x “Morex” Barley Mapping Population. Plant Breed. 1999, 118, 399–403. [Google Scholar] [CrossRef]
  60. Turner, A.; Beales, J.; Faure, S.; Dunford, R.P.; Laurie, D.A. The Pseudo-Response Regulator Ppd-H1 Provides Adaptation to Photoperiod in Barley. Science 2005, 310, 1031–1034. [Google Scholar] [CrossRef]
  61. Komatsuda, T.; Pourkheirandish, M.; He, C.; Azhaguvel, P.; Kanamori, H.; Perovic, D.; Stein, N.; Graner, A.; Wicker, T.; Tagiri, A.; et al. Six-Rowed Barley Originated from a Mutation in a Homeodomain-Leucine Zipper I-Class Homeobox Gene. Proc. Natl. Acad. Sci. USA 2007, 104, 1424–1429. [Google Scholar] [CrossRef] [Green Version]
  62. Koppolu, R.; Anwar, N.; Sakuma, S.; Tagiri, A.; Lundqvist, U.; Pourkheirandish, M.; Rutten, T.; Seiler, C.; Himmelbach, A.; Ariyadasa, R.; et al. Six-Rowed Spike4 (Vrs4) Controls Spikelet Determinacy and Row-Type in Barley. Proc. Natl. Acad. Sci. USA 2013, 110, 13198–13203. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  63. Li, J.; Nie, X.; Tan, J.L.H.; Berger, F. Integration of Epigenetic and Genetic Controls of Seed Size by Cytokinin in Arabidopsis. Proc. Natl. Acad. Sci. USA 2013, 110, 15479–15484. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  64. Mishra, P.; Panigrahi, K.C. GIGANTEA—An Emerging Story. Front. Plant Sci. 2015, 6, 8. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  65. Kuczyńska, A.; Surma, M.; Adamski, T.; Mikołajczak, K.; Krystkowiak, K.; Ogrodowicz, P. Effects of the Semi-Dwarfing Sdw1/Denso Gene in Barley. J. Appl. Genet. 2013, 54, 381–390. [Google Scholar] [CrossRef] [Green Version]
  66. Morinaka, Y.; Sakamoto, T.; Inukai, Y.; Agetsuma, M.; Kitano, H.; Ashikari, M.; Matsuoka, M. Morphological Alteration Caused by Brassinosteroid Insensitivity Increases the Biomass and Grain Production of Rice. Plant Physiol. 2006, 141, 924–931. [Google Scholar] [CrossRef] [Green Version]
  67. Utsunomiya, Y.; Samejima, C.; Takayanagi, Y.; Izawa, Y.; Yoshida, T.; Sawada, Y.; Fujisawa, Y.; Kato, H.; Iwasaki, Y. Suppression of the Rice Heterotrimeric G Protein β-Subunit Gene, RGB1, Causes Dwarfism and Browning of Internodes and Lamina Joint Regions. Plant J. 2011, 67, 907–916. [Google Scholar] [CrossRef]
  68. Chen, X.; Feng, F.; Qi, W.; Xu, L.; Yao, D.; Wang, Q.; Song, R. Dek35 Encodes a PPR Protein That Affects Cis-Splicing of Mitochondrial Nad4 Intron 1 and Seed Development in Maize. Mol. Plant 2017, 10, 427–441. [Google Scholar] [CrossRef] [Green Version]
  69. Riefler, M.; Novak, O.; Strnad, M.; Schmülling, T. Arabidopsis Cytokinin Receptors Mutants Reveal Functions in Shoot Growth, Leaf Senescence, Seed Size, Germination, Root Development, and Cytokinin Metabolism. Plant Cell 2006, 18, 40–54. [Google Scholar] [CrossRef] [Green Version]
  70. Gutiérrez-Marcos, J.F.; Dal Prà, M.; Giulini, A.; Costa, L.M.; Gavazzi, G.; Cordelier, S.; Sellam, O.; Tatout, C.; Paul, W.; Perez, P.; et al. Empty Pericarp4 Encodes a Mitochondrion-Targeted Pentatricopeptide Repeat Protein Necessary for Seed Development and Plant Growth in Maize. Plant Cell 2007, 19, 196–210. [Google Scholar] [CrossRef] [Green Version]
  71. Taheripourfard, Z.S.; Izadi-darbandi, A.; Ghazvini, H.; Ebrahimi, M.; Mortazavian, S.M.M. Characterization of Specific DNA Markers at VRN-H1 and VRN-H2 Loci for Growth Habit of Barley Genotypes. J. Genet. 2018, 97, 87–95. [Google Scholar] [CrossRef]
  72. Garcia, D.; Saingery, V.; Chambrier, P.; Mayer, U.; Jürgens, G.; Berger, F.F.; Juürgens, G.; Berger, F.F. Arabidopsis Haiku Mutants Reveal New Controls of Seed Size by Endosperm. Plant Physiol. 2003, 131, 1661–1670. [Google Scholar] [CrossRef] [Green Version]
  73. Zhang, X.; Wang, J.; Huang, J.; Lan, H.; Wang, C.; Yin, C.; Wu, Y.; Tang, H.; Qian, Q.; Li, J.; et al. Rare Allele of OsPPKL1 Associated with Grain Length Causes Extra-Large Grain and a Significant Yield Increase in Rice. Proc. Natl. Acad. Sci. USA 2012, 109, 21534–21539. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  74. Sun, S.; Wang, L.; Mao, H.; Shao, L.; Li, X.; Xiao, J.; Ouyang, Y.; Zhang, Q. A G-Protein Pathway Determines Grain Size in Rice. Nat. Commun. 2018, 9, 851. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  75. Wendt, T.; Holme, I.; Dockter, C.; Preuß, A.; Thomas, W.; Druka, A.; Waugh, R.; Hansson, M.; Braumann, I. HvDep1 Is a Positive Regulator of Culm Elongation and Grain Size in Barley and Impacts Yield in an Environment-Dependent Manner. PLoS ONE 2016, 11, e0168924. [Google Scholar] [CrossRef] [PubMed]
  76. Li, S.; Zhao, B.; Yuan, D.; Duan, M.; Qian, Q.; Tang, L.; Wang, B.; Liu, X.; Zhang, J.; Wang, J.; et al. Rice Zinc Finger Protein DST Enhances Grain Production through Controlling Gn1a/OsCKX2 Expression. Proc. Natl. Acad. Sci. USA 2013, 110, 3167–3172. [Google Scholar] [CrossRef] [Green Version]
  77. Cheng, Z.J.; Zhao, X.Y.; Shao, X.X.; Wang, F.; Zhou, C.; Liu, Y.G.; Zhang, Y.; Zhang, X.S. Abscisic Acid Regulates Early Seed Development in Arabidopsis by ABI5-Mediated Transcription of SHORT HYPOCOTYL UNDER BLUE1. Plant Cell 2014, 26, 1053–1068. [Google Scholar] [CrossRef] [Green Version]
  78. Lid, S.E.; Gruis, D.; Jung, R.; Lorentzen, J.A.; Ananiev, E.; Chamberlin, M.; Niu, X.; Meeley, R.; Nichols, S.; Olsen, O.-A. The Defective Kernel 1 (Dek1) Gene Required for Aleurone Cell Development in the Endosperm of Maize Grains Encodes a Membrane Protein of the Calpain Gene Superfamily. Proc. Natl. Acad. Sci. USA 2002, 99, 5460–5465. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  79. Shen, B.; Allen, W.B.; Zheng, P.; Li, C.; Glassman, K.; Ranch, J.; Nubel, D.; Tarczynski, M.C. Expression of ZmLEC1 and ZmWRI1 Increases Seed Oil Production in Maize. Plant Physiol. 2010, 153, 980–987. [Google Scholar] [CrossRef] [Green Version]
  80. Zhang, S.; Wong, L.; Meng, L.; Lemaux, P.G. Similarity of Expression Patterns of Knotted1 and ZmLEC1 during Somatic and Zygotic Embryogenesis in Maize (Zea mays L.). Planta 2002, 215, 191–194. [Google Scholar] [CrossRef]
  81. Guo, G.; Lv, D.; Yan, X.; Subburaj, S.; Ge, P.; Li, X.; Hu, Y.; Yan, Y. Proteome Characterization of Developing Grains in Bread Wheat Cultivars (Triticum aestivum L.). BMC Plant Biol. 2012, 12, 147. [Google Scholar] [CrossRef] [Green Version]
  82. Jiang, W.B.; Huang, H.Y.; Hu, Y.W.; Zhu, S.W.; Wang, Z.Y.; Lin, W.H. Brassinosteroid Regulates Seed Size and Shape in Arabidopsis. Plant Physiol. 2013, 162, 1965–1977. [Google Scholar] [CrossRef]
  83. Hu, Z.; Lu, S.J.; Wang, M.J.; He, H.; Sun, L.; Wang, H.; Liu, X.H.; Jiang, L.; Sun, J.L.; Xin, X.; et al. A Novel QTL QTGW3 Encodes the GSK3/SHAGGY-Like Kinase OsGSK5/OsSK41 That Interacts with OsARF4 to Negatively Regulate Grain Size and Weight in Rice. Mol. Plant 2018, 11, 736–749. [Google Scholar] [CrossRef] [Green Version]
  84. Becraft, P.W.; Li, K.; Dey, N.; Asuncion-Crabb, Y. The Maize Dek1 Gene Functions in Embryonic Pattern Formation and Cell Fate Specification. Development 2002, 129, 5217–5225. [Google Scholar] [CrossRef]
  85. Song, J.; Xie, X.; Chen, C.; Shu, J.; Thapa, R.K.; Nguyen, V.; Bian, S.; Kohalmi, S.E.; Marsolais, F.; Zou, J.; et al. LEAFY COTYLEDON1 Expression in the Endosperm Enables Embryo Maturation in Arabidopsis. Nat. Commun. 2021, 12, 3963. [Google Scholar] [CrossRef] [PubMed]
  86. Barabaschi, D.; Francia, E.; Tondelli, A.; Gianinetti, A.; Stanca, A.M.; Pecchioni, N. Effect of the Nud Gene on Grain Yield in Barley. Czech J. Genet. Plant Breed. 2012, 48, 10–22. [Google Scholar] [CrossRef] [Green Version]
  87. Gong, X.; Wheeler, R.; Bovill, W.D.; McDonald, G.K. QTL Mapping of Grain Yield and Phosphorus Efficiency in Barley in a Mediterranean-like Environment. Theor. Appl. Genet. 2016, 129, 1657–1672. [Google Scholar] [CrossRef] [PubMed]
  88. Jaiswal, V.; Gahlaut, V.; Mathur, S.; Agarwal, P.; Khandelwal, M.K.; Khurana, J.P.; Tyagi, A.K.; Balyan, H.S.; Gupta, P.K. Identification of Novel SNP in Promoter Sequence of TaGW2-6A Associated with Grain Weight and Other Agronomic Traits in Wheat (Triticum aestivum L.). PLoS ONE 2015, 10, e0129400. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  89. Hanif, M.; Gao, F.; Liu, J.; Wen, W.; Zhang, Y.; Rasheed, A.; Xia, X.; He, Z.; Cao, S. TaTGW6-A1, an Ortholog of Rice TGW6, Is Associated with Grain Weight and Yield in Bread Wheat. Mol. Breed. 2016, 36, 1. [Google Scholar] [CrossRef]
  90. Dewey, C.N. Whole-Genome Alignment. In Methods in Molecular Biology; Springer: Berlin/Heidelberg, Germany, 2019; Volume 1910, pp. 121–147. ISBN 9781493990740. [Google Scholar]
  91. Yan, N.; Yang, T.; Yu, X.-T.; Shang, L.-G.; Guo, D.-P.; Zhang, Y.; Meng, L.; Qi, Q.-Q.; Li, Y.-L.; Du, Y.-M.; et al. Chromosome-Level Genome Assembly of Zizania Latifolia Provides Insights into Its Seed Shattering and Phytocassane Biosynthesis. Commun. Biol. 2022, 5, 36. [Google Scholar] [CrossRef]
  92. Chen, C.; Chen, H.; Zhang, Y.; Thomas, H.R.; Frank, M.H.; He, Y.; Xia, R. TBtools: An Integrative Toolkit Developed for Interactive Analyses of Big Biological Data. Mol. Plant 2020, 13, 1194–1202. [Google Scholar] [CrossRef] [PubMed]
  93. Heang, D.; Sassa, H. Antagonistic Actions of HLH/BHLH Proteins Are Involved in Grain Length and Weight in Rice. PLoS ONE 2012, 7, e31325. [Google Scholar] [CrossRef] [Green Version]
  94. Guo, X.; Fu, Y.; Lee, Y.J.; Chern, M.; Li, M.; Cheng, M.; Dong, H.; Yuan, Z.; Gui, L.; Yin, J.; et al. The PGS1 Basic Helix-loop-helix Protein Regulates Fl3 to Impact Seed Growth and Grain Yield in Cereals. Plant Biotechnol. J. 2022, 20, 1311–1326. [Google Scholar] [CrossRef] [PubMed]
  95. Kitagawa, K.; Kurinami, S.; Oki, K.; Abe, Y.; Ando, T.; Kono, I.; Yano, M.; Kitano, H.; Iwasaki, Y. A Novel Kinesin 13 Protein Regulating Rice Seed Length. Plant Cell Physiol. 2010, 51, 1315–1329. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  96. Tong, H.; Liu, L.; Jin, Y.; Du, L.; Yin, Y.; Qian, Q.; Zhu, L.; Chu, C. Dwarf and Low-Tillering Acts as a Direct Downstream Target of a GSK3/SHAGGY-like Kinase to Mediate Brassinosteroid Responses in Rice. Plant Cell 2012, 24, 2562–2577. [Google Scholar] [CrossRef] [PubMed]
  97. Li, T.; Jiang, J.; Zhang, S.; Shu, H.; Wang, Y.; Lai, J.; Du, J.; Yang, C. OsAGSW1, an ABC1-like Kinase Gene, Is Involved in the Regulation of Grain Size and Weight in Rice. J. Exp. Bot. 2015, 66, 5691–5701. [Google Scholar] [CrossRef] [Green Version]
  98. Zhang, J.J.; Xue, H.W. OsLEC1/OsHAP3E Participates in the Determination of Meristem Identity in Both Vegetative and Reproductive Developments of Rice. J. Integr. Plant Biol. 2013, 55, 232–249. [Google Scholar] [CrossRef]
  99. Li, C.; Qiao, Z.; Qi, W.; Wang, Q.; Yuan, Y.; Yang, X.; Tang, Y.; Mei, B.; Lv, Y.; Zhao, H.; et al. Genome-Wide Characterization of Cis-Acting DNA Targets Reveals the Transcriptional Regulatory Framework of Opaque2 in Maize. Plant Cell 2015, 27, 532–545. [Google Scholar] [CrossRef] [Green Version]
  100. Gómez, E.; Royo, J.; Guo, Y.; Thompson, R.; Hueros, G. Establishment of Cereal Endosperm Expression Domains: Identification and Properties of a Maize Transfer Cell-Specific Transcription Factor, ZmMRP-1. Plant Cell 2002, 14, 599–610. [Google Scholar] [CrossRef]
  101. Fu, C.; Yang, X.O.; Chen, X.; Chen, W.; Ma, Y.; Hu, J.; Li, S. OsEF3, a Homologous Gene of Arabidopsis ELF3, Has Pleiotropic Effects in Rice. Plant Biol. 2009, 11, 751–757. [Google Scholar] [CrossRef]
  102. Bai, X.; Huang, Y.; Hu, Y.; Liu, H.; Zhang, B.; Smaczniak, C.; Hu, G.; Han, Z.; Xing, Y. Duplication of an Upstream Silencer of FZP Increases Grain Yield in Rice. Nat. Plants 2017, 3, 885–893. [Google Scholar] [CrossRef] [PubMed]
  103. Chen, C.; Begcy, K.; Liu, K.; Folsom, J.J.; Wang, Z.; Zhang, C.; Walia, H. Heat Stress Yields a Unique MADS Box Transcription Factor in Determining Seed Size and Thermal Sensitivity. Plant Physiol. 2016, 171, 606–622. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  104. Jiang, Q.; Hou, J.; Hao, C.; Wang, L.; Ge, H.; Dong, Y.; Zhang, X. The Wheat (T. aestivum) Sucrose Synthase 2 Gene (TaSus2) Active in Endosperm Development Is Associated with Yield Traits. Funct. Integr. Genom. 2011, 11, 49–61. [Google Scholar] [CrossRef] [PubMed]
  105. Abe, Y.; Mieda, K.; Ando, T.; Kono, I.; Yano, M.; Kitano, H.; Iwasaki, Y. The SMALL AND ROUND SEED1 (SRS1/DEP2) Gene Is Involved in the Regulation of Seed Size in Rice. Genes Genet. Syst. 2010, 85, 327–339. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  106. Wang, S.; Li, S.; Liu, Q.; Wu, K.; Zhang, J.; Wang, S.; Wang, Y.; Chen, X.; Zhang, Y.; Gao, C.; et al. The OsSPL16-GW7 Regulatory Module Determines Grain Shape and Simultaneously Improves Rice Yield and Grain Quality. Nat. Genet. 2015, 47, 949–954. [Google Scholar] [CrossRef]
  107. Wang, Y.; Xiong, G.; Hu, J.; Jiang, L.; Yu, H.; Xu, J.; Fang, Y.; Zeng, L.; Xu, E.; Xu, J.; et al. Copy Number Variation at the GL7 Locus Contributes to Grain Size Diversity in Rice. Nat. Genet. 2015, 47, 944–948. [Google Scholar] [CrossRef]
  108. Nagasawa, N.; Hibara, K.-I.; Heppard, E.P.; Vander Velden, K.A.; Luck, S.; Beatty, M.; Nagato, Y.; Sakai, H. GIANT EMBRYO Encodes CYP78A13, Required for Proper Size Balance between Embryo and Endosperm in Rice. Plant J. 2013, 75, 592–605. [Google Scholar] [CrossRef]
  109. Tang, Y.; Liu, H.; Guo, S.; Wang, B.; Li, Z.; Chong, K.; Xu, Y. OsmiR396d Affects Gibberellin and Brassinosteroid Signaling to Regulate Plant Architecture in Rice. Plant Physiol. 2018, 176, 946–959. [Google Scholar] [CrossRef] [Green Version]
  110. Kurepa, J.; Wang, S.; Li, Y.; Zaitlin, D.; Pierce, A.J.; Smalle, J.A. Loss of 26S Proteasome Function Leads to Increased Cell Size and Decreased Cell Number in Arabidopsis Shoot Organs. Plant Physiol. 2009, 150, 178–189. [Google Scholar] [CrossRef] [Green Version]
  111. Meng, L.S.; Jian, J.H. Why Are Seedlings of Large-Seeded Plants Considered to Withstand Drought Stresses Efficiently? Cloning Transgenes 2016, 5, 283–291. [Google Scholar] [CrossRef] [Green Version]
  112. He, Z.; Zeng, J.; Ren, Y.; Chen, D.; Li, W.; Gao, F.; Cao, Y.; Luo, T.; Yuan, G.; Wu, X.; et al. OsGIF1 Positively Regulates the Sizes of Stems, Leaves, and Grains in Rice. Front. Plant Sci. 2017, 8, 1730. [Google Scholar] [CrossRef]
  113. Zhu, X.-F.; Zhang, H.-P.; Hu, M.-J.; Wu, Z.-Y.; Jiang, H.; Cao, J.-J.; Xia, X.-C.; Ma, C.-X.; Chang, C. Cloning and Characterization of Tabas1-B1 Gene Associated with Flag Leaf Chlorophyll Content and Thousand-Grain Weight and Development of a Gene-Specific Marker in Wheat. Mol. Breed. 2016, 36, 142. [Google Scholar] [CrossRef]
  114. Tanabe, S.; Ashikari, M.; Fujioka, S.; Takatsuto, S.; Yoshida, S.; Yano, M.; Yoshimura, A.; Kitano, H.; Matsuoka, M.; Fujisawa, Y.; et al. A Novel Cytochrome P450 Is Implicated in Brassinosteroid Biosynthesis via the Characterization of a Rice Dwarf Mutant, Dwarf11, with Reduced Seed Length. Plant Cell 2005, 17, 776–790. [Google Scholar] [CrossRef] [Green Version]
  115. Qi, P.; Lin, Y.S.; Song, X.J.; Shen, J.B.; Huang, W.; Shan, J.X.; Zhu, M.Z.; Jiang, L.; Gao, J.P.; Lin, H.X. The Novel Quantitative Trait Locus GL3.1 Controls Rice Grain Size and Yield by Regulating Cyclin-T1;3. Cell Res. 2012, 22, 1666–1680. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  116. Hua, L.; Wang, D.R.; Tan, L.; Fu, Y.; Liu, F.; Xiao, L.; Zhu, Z.; Fu, Q.; Sun, X.; Gu, P.; et al. LABA1, a Domestication Gene Associated with Long, Barbed Awns in Wild Rice. Plant Cell 2015, 27, 1875–1888. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  117. Tan, J.; Wang, M.; Shi, Z.; Miao, X. OsEXPA10 Mediates the Balance between Growth and Resistance to Biotic Stress in Rice. Plant Cell Rep. 2018, 37, 993–1002. [Google Scholar] [CrossRef]
  118. Jiang, Y.; Bao, L.; Jeong, S.Y.; Kim, S.K.; Xu, C.; Li, X.; Zhang, Q. XIAO Is Involved in the Control of Organ Size by Contributing to the Regulation of Signaling and Homeostasis of Brassinosteroids and Cell Cycling in Rice. Plant J. 2012, 70, 398–408. [Google Scholar] [CrossRef]
  119. Yi, G.; Neelakandan, A.K.; Gontarek, B.C.; Vollbrecht, E.; Becraft, P.W. The Naked Endosperm Genes Encode Duplicate INDETERMINATE Domain Transcription Factors Required for Maize Endosperm Cell Patterning and Differentiation. Plant Physiol. 2015, 167, 443–456. [Google Scholar] [CrossRef] [Green Version]
  120. Xu, R.; Duan, P.; Yu, H.; Zhou, Z.; Zhang, B.; Wang, R.; Li, J.; Zhang, G.; Zhuang, S.; Lyu, J.; et al. Control of Grain Size and Weight by the OsMKKK10-OsMKK4-OsMAPK6 Signaling Pathway in Rice. Mol. Plant 2018, 11, 860–873. [Google Scholar] [CrossRef] [Green Version]
  121. Wang, S.; Lei, C.; Wang, J.; Ma, J.; Tang, S.; Wang, C.; Zhao, K.; Tian, P.; Zhang, H.; Qi, C.; et al. SPL33, Encoding an EEF1A-like Protein, Negatively Regulates Cell Death and Defense Responses in Rice. J. Exp. Bot. 2017, 68, 899–913. [Google Scholar] [CrossRef]
  122. Bate, N.J.; Niu, X.; Wang, Y.; Reimann, K.S.; Helentjaris, T.G. An Invertase Inhibitor from Maize Localizes to the Embryo Surrounding Region during Early Kernel Development. Plant Physiol. 2004, 134, 246–254. [Google Scholar] [CrossRef] [Green Version]
  123. Jofuku, K.D.; Omidyar, P.K.; Gee, Z.; Okamuro, J.K. Control of Seed Mass and Seed Yield by the Floral Homeotic Gene APETALA2. Proc. Natl. Acad. Sci. USA 2005, 102, 3117–3122. [Google Scholar] [CrossRef] [Green Version]
  124. She, K.C.; Kusano, H.; Koizumi, K.; Yamakawa, H.; Hakata, M.; Imamura, T.; Fukuda, M.; Naito, N.; Tsurumaki, Y.; Yaeshima, M.; et al. A Novel Factor FLOURY ENDOSPERM2 Is Involved in Regulation of Rice Grain Size and Starch Quality. Plant Cell 2010, 22, 3280–3294. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  125. Grimault, A.; Gendrot, G.; Chaignon, S.; Gilard, F.; Tcherkez, G.; Thévenin, J.; Dubreucq, B.; Depège-Fargeix, N.; Rogowsky, P.M. Role of B3 Domain Transcription Factors of the AFL Family in Maize Kernel Filling. Plant Sci. 2015, 236, 116–125. [Google Scholar] [CrossRef] [PubMed]
  126. Zhou, W.; Wang, X.; Zhou, D.; Ouyang, Y.; Yao, J. Overexpression of the 16-KDa α-Amylase/Trypsin Inhibitor RAG2 Improves Grain Yield and Quality of Rice. Plant Biotechnol. J. 2017, 15, 568–580. [Google Scholar] [CrossRef] [PubMed]
  127. Zhang, B.; Wang, X.; Zhao, Z.; Wang, R.; Huang, X.; Zhu, Y.; Yuan, L.; Wang, Y.; Xu, X.; Burlingame, A.L.; et al. OsBRI1 Activates BR Signaling by Preventing Binding between the TPR and Kinase Domains of OsBSK3 via Phosphorylation. Plant Physiol. 2016, 170, 1149–1161. [Google Scholar] [CrossRef]
  128. Li, H.; Jiang, L.; Youn, J.; Sun, W.; Cheng, Z.; Jin, T.; Ma, X.; Guo, X.; Wang, J.; Zhang, X.; et al. A Comprehensive Genetic Study Reveals a Crucial Role of CYP90D2/D2 in Regulating Plant Architecture in Rice Oryza sativa). New Phytol. 2013, 200, 1076–1088. [Google Scholar] [CrossRef]
  129. Ashikari, M.; Sakakibara, H.; Lin, S.; Yamamoto, T.; Takashi, T.; Nishimura, A.; Angeles, E.R.; Qian, Q.; Kitano, H.; Matsuoka, M. Plant Science: Cytokinin Oxidase Regulates Rice Grain Production. Science 2005, 309, 741–745. [Google Scholar] [CrossRef]
  130. Iwamoto, M.; Higo, K.; Takano, M. Circadian Clock- and Phytochrome-Regulated Dof-like Gene, Rdd1, Is Associated with Grain Size in Rice. Plant Cell Environ. 2009, 32, 592–603. [Google Scholar] [CrossRef]
  131. Chen, Y.; Xu, Y.; Luo, W.; Li, W.; Chen, N.; Zhang, D.; Chong, K. The F-Box Protein OsFBK12 Targets OsSAMS1 for Degradation and Affects Pleiotropic Phenotypes, Including Leaf Senescence, in Rice. Plant Physiol. 2013, 163, 1673–1685. [Google Scholar] [CrossRef] [Green Version]
  132. Sun, Q.; Hu, A.; Mu, L.; Zhao, H.; Qin, Y.; Gong, D.; Qiu, F. Identification of a Candidate Gene Underlying QHKW3, a QTL for Hundred-Kernel Weight in Maize. Theor. Appl. Genet. 2022, 135, 1579–1589. [Google Scholar] [CrossRef] [PubMed]
  133. Xiu, Z.; Sun, F.; Shen, Y.; Zhang, X.; Jiang, R.; Bonnard, G.; Zhang, J.; Tan, B.C. EMPTY PERICARP16 Is Required for Mitochondrial Nad2 Intron 4 Cis-Splicing, Complex i Assembly and Seed Development in Maize. Plant J. 2016, 85, 507–519. [Google Scholar] [CrossRef]
  134. Liu, L.; Tong, H.; Xiao, Y.; Che, R.; Xu, F.; Hu, B.; Liang, C.; Chu, J.; Li, J.; Chu, C. Activation of Big Grain1 Significantly Improves Grain Size by Regulating Auxin Transport in Rice. Proc. Natl. Acad. Sci. USA 2015, 112, 11102–11107. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  135. McCarty, D.R.; Hattori, T.; Carson, C.B.; Vasil, V.; Lazar, M.; Vasil, I.K. The Viviparous-1 Developmental Gene of Maize Encodes a Novel Transcriptional Activator. Cell 1991, 66, 895–905. [Google Scholar] [CrossRef]
  136. Hutchison, C.E.; Li, J.; Argueso, C.; Gonzalez, M.; Lee, E.; Lewis, M.W.; Maxwell, B.B.; Perdue, T.D.; Schaller, G.E.; Alonso, J.M.; et al. The Arabidopsis Histidine Phosphotransfer Proteins Are Redundant Positive Regulators of Cytokinin Signaling. Plant Cell 2006, 18, 3073–3087. [Google Scholar] [CrossRef] [Green Version]
  137. Jang, S.; Li, H.-Y. Oryza Sativa BRASSINOSTEROID UPREGULATED1 LIKE1 Induces the Expression of a Gene Encoding a Small Leucine-Rich-Repeat Protein to Positively Regulate Lamina Inclination and Grain Size in Rice. Front. Plant Sci. 2017, 8, 1253. [Google Scholar] [CrossRef] [Green Version]
  138. Yun, P.; Li, Y.; Wu, B.; Zhu, Y.; Wang, K.; Li, P.; Gao, G.; Zhang, Q.; Li, X.; Li, Z.; et al. OsHXK3 Encodes a Hexokinase-like Protein That Positively Regulates Grain Size in Rice. Theor. Appl. Genet. 2022, 135, 3417–3431. [Google Scholar] [CrossRef]
  139. Liu, Y.J.; Xiu, Z.H.; Meeley, R.; Tan, B.C. Empty Pericarp5 Encodes a Pentatricopeptide Repeat Protein That Is Required for Mitochondrial RNA Editing and Seed Development in Maize. Plant Cell 2013, 25, 868–883. [Google Scholar] [CrossRef] [Green Version]
  140. Zhang, Z.-G.; Lv, G.; Li, B.; Wang, J.-J.; Zhao, Y.; Kong, F.-M.; Guo, Y.; Li, S.-S. Isolation and Characterization of the TaSnRK2.10 Gene and Its Association with Agronomic Traits in Wheat (Triticum aestivum L.). PLoS ONE 2017, 12, e0174425. [Google Scholar] [CrossRef] [Green Version]
  141. Li, X.J.; Zhang, Y.F.; Hou, M.; Sun, F.; Shen, Y.; Xiu, Z.H.; Wang, X.; Chen, Z.L.; Sun, S.S.M.; Small, I.; et al. Small Kernel 1 Encodes a Pentatricopeptide Repeat Protein Required for Mitochondrial Nad7 Transcript Editing and Seed Development in Maize (Zea mays) and Rice (Oryza sativa). Plant J. 2014, 79, 797–809. [Google Scholar] [CrossRef] [PubMed]
  142. Zhang, Y.; Du, L.; Xu, R.; Cui, R.; Hao, J.; Sun, C.; Li, Y. Transcription Factors SOD7/NGAl2 and DPA4/NGAL3 Act Redundantly to Regulate Seed Size by Directly Repressing KLU Expression in Arabidopsis Thaliana. Plant Cell 2015, 27, 620–632. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  143. Disch, S.; Anastasiou, E.; Sharma, V.K.; Laux, T.; Fletcher, J.C.; Lenhard, M. The E3 Ubiquitin Ligase BIG BROTHER Controls Arabidopsis Organ Size in a Dosage-Dependent Manner. Curr. Biol. 2006, 16, 272–279. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  144. Gao, Q.; Zhang, N.; Wang, W.-Q.; Shen, S.-Y.; Bai, C.; Song, X.-J. The Ubiquitin-Interacting Motif-Type Ubiquitin Receptor HDR3 Interacts with and Stabilizes the Histone Acetyltransferase GW6a to Control the Grain Size in Rice. Plant Cell 2021, 33, 3331–3347. [Google Scholar] [CrossRef]
  145. Hu, X.; Qian, Q.; Xu, T.; Zhang, Y.; Dong, G.; Gao, T.; Xie, Q.; Xue, Y. The U-Box E3 Ubiquitin Ligase TUD1 Functions with a Heterotrimeric G α Subunit to Regulate Brassinosteroid-Mediated Growth in Rice. PLoS Genet. 2013, 9, e1003391. [Google Scholar] [CrossRef] [Green Version]
  146. Yang, F.; Zhang, J.; Zhao, Y.; Liu, Q.; Islam, S.; Yang, W.; Ma, W. Wheat Glutamine Synthetase TaGSr-4B Is a Candidate Gene for a QTL of Thousand Grain Weight on Chromosome 4B. Theor. Appl. Genet. 2022, 135, 2369–2384. [Google Scholar] [CrossRef]
  147. Arite, T.; Umehara, M.; Ishikawa, S.; Hanada, A.; Maekawa, M.; Yamaguchi, S.; Kyozuka, J. D14, a Strigolactone-Insensitive Mutant of Rice, Shows an Accelerated Outgrowth of Tillers. Plant Cell Physiol. 2009, 50, 1416–1424. [Google Scholar] [CrossRef] [Green Version]
  148. Heang, D.; Sassa, H. An Atypical BHLH Protein Encoded by POSITIVE REGULATOR OF GRAIN LENGTH 2 Is Involved in Controlling Grain Length and Weight of Rice through Interaction with a Typical BHLH Protein APG. Breed. Sci. 2012, 62, 133–141. [Google Scholar] [CrossRef] [Green Version]
  149. Yang, Y.Z.; Ding, S.; Wang, Y.; Li, C.L.; Shen, Y.; Meeley, R.; McCarty, D.R.; Tan, B.C. Small Kernel2 Encodes a Glutaminase in Vitamin B6biosynthesis Essential for Maize Seed Development. Plant Physiol. 2017, 174, 1127–1138. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  150. Yu, J.; Xiong, H.; Zhu, X.; Zhang, H.; Li, H.; Miao, J.; Wang, W.; Tang, Z.; Zhang, Z.; Yao, G.; et al. OsLG3 Contributing to Rice Grain Length and Yield Was Mined by Ho-LAMap. BMC Biol. 2017, 15, 28. [Google Scholar] [CrossRef] [Green Version]
  151. Choi, B.; Kim, Y.; Markkandan, K.; Koo, Y.; Song, J.; Seo, H. GW2 Functions as an E3 Ubiquitin Ligase for Rice Expansin-Like 1. Int. J. Mol. Sci. 2018, 19, 1904. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  152. He, S.L.; Jiang, J.Z.; Chen, B.H.; Kuo, C.H.; Ho, S.L. Overexpression of a Constitutively Active Truncated Form of OsCDPK1 Confers Disease Resistance by Affecting OsPR10a Expression in Rice. Sci. Rep. 2018, 8, 403. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  153. Jin, J.; Huang, W.; Gao, J.P.; Yang, J.; Shi, M.; Zhu, M.Z.; Luo, D.; Lin, H.X. Genetic Control of Rice Plant Architecture under Domestication. Nat. Genet. 2008, 40, 1365–1369. [Google Scholar] [CrossRef] [PubMed]
  154. Xu, X.H.; Zhao, H.J.; Liu, Q.L.; Frank, T.; Engel, K.H.; An, G.; Shu, Q.Y. Mutations of the Multi-Drug Resistance-Associated Protein ABC Transporter Gene 5 Result in Reduction of Phytic Acid in Rice Seeds. Theor. Appl. Genet. 2009, 119, 75–83. [Google Scholar] [CrossRef]
  155. Su’udi, M.; Cha, J.Y.; Jung, M.H.; Ermawati, N.; Han, C.D.; Kim, M.G.; Woo, Y.M.; Son, D. Potential Role of the Rice OsCCS52A Gene in Endoreduplication. Planta 2012, 235, 387–397. [Google Scholar] [CrossRef] [PubMed]
  156. Jin, P.; Guo, T.; Becraft, P.W. The Maize CR4 Receptor-like Kinase Mediates a Growth Factor-like Differentiation Response. Genesis 2000, 27, 104–116. [Google Scholar] [CrossRef]
  157. Dong, H.; Dumenil, J.; Lu, F.H.; Na, L.; Vanhaeren, H.; Naumann, C.; Klecker, M.; Prior, R.; Smith, C.; McKenzie, N.; et al. Ubiquitylation Activates a Peptidase That Promotes Cleavage and Destabilization of Its Activating E3 Ligases and Diverse Growth Regulatory Proteins to Limit Cell Proliferation in Arabidopsis. Genes Dev. 2017, 31, 197–208. [Google Scholar] [CrossRef] [Green Version]
  158. Ur Rehman, S.; Wang, J.; Chang, X.; Zhang, X.; Mao, X.; Jing, R. A Wheat Protein Kinase Gene TaSnRK2.9-5A Associated with Yield Contributing Traits. Theor. Appl. Genet. 2019, 132, 907–919. [Google Scholar] [CrossRef] [Green Version]
  159. He, Y.; Li, L.; Shi, W.; Tan, J.; Luo, X.; Zheng, S.; Chen, W.; Li, J.; Zhuang, C.; Jiang, D. Florigen Repression Complexes Involving Rice CENTRORADIALIS2 Regulate Grain Size. Plant Physiol. 2022, 190, 1260–1274. [Google Scholar] [CrossRef]
  160. Pouvreau, B.; Baud, S.; Vernoud, V.; Morin, V.; Py, C.; Gendrot, G.; Pichon, J.P.; Rouster, J.; Paul, W.; Rogowsky, P.M. Duplicate Maize Wrinkled1 Transcription Factors Activate Target Genes Involved in Seed Oil Biosynthesis. Plant Physiol. 2011, 156, 674–686. [Google Scholar] [CrossRef] [Green Version]
  161. Garcia, D.; Gerald, J.N.F.; Berger, F. Maternal Control of Integument Cell Elongation and Zygotic Control of Endosperm Growth Are Coordinated to Determine Seed Size in Arabidopsis. Plant Cell 2005, 17, 52–60. [Google Scholar] [CrossRef] [Green Version]
  162. Zhang, M.; Zhang, B.; Qian, Q.; Yu, Y.; Li, R.; Zhang, J.; Liu, X.; Zeng, D.; Li, J.; Zhou, Y. Brittle Culm 12, a Dual-Targeting Kinesin-4 Protein, Controls Cell-Cycle Progression and Wall Properties in Rice. Plant J. 2010, 63, 312–328. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  163. Huang, X.; Qian, Q.; Liu, Z.; Sun, H.; He, S.; Luo, D.; Xia, G.; Chu, C.; Li, J.; Fu, X. Natural Variation at the DEP1 Locus Enhances Grain Yield in Rice. Nat. Genet. 2009, 41, 494–497. [Google Scholar] [CrossRef] [PubMed]
  164. Zhao, D.-S.; Li, Q.-F.; Zhang, C.-Q.; Zhang, C.; Yang, Q.-Q.; Pan, L.-X.; Ren, X.-Y.; Lu, J.; Gu, M.-H.; Liu, Q.-Q. GS9 Acts as a Transcriptional Activator to Regulate Rice Grain Shape and Appearance Quality. Nat. Commun. 2018, 9, 1240. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  165. Nakagawa, H.; Tanaka, A.; Tanabata, T.; Ohtake, M.; Fujioka, S.; Nakamura, H.; Ichikawa, H.; Mori, M. SHORT GRAIN1 Decreases Organ Elongation and Brassinosteroid Response in Rice. Plant Physiol. 2012, 158, 1208–1219. [Google Scholar] [CrossRef] [Green Version]
  166. Chettoor, A.M.; Yi, G.; Gomez, E.; Hueros, G.; Meeley, R.B.; Becraft, P.W. A Putative Plant Organelle RNA Recognition Protein Gene Is Essential for Maize Kernel Development. J. Integr. Plant Biol. 2015, 57, 236–246. [Google Scholar] [CrossRef]
  167. Jang, S.; An, G.; Li, H.Y. Rice Leaf Angle and Grain Size Are Affected by the OsBUL1 Transcriptional Activator Complex. Plant Physiol. 2017, 173, 688–702. [Google Scholar] [CrossRef] [Green Version]
  168. Hu, Z.; He, H.; Zhang, S.; Sun, F.; Xin, X.; Wang, W.; Qian, X.; Yang, J.; Luo, X. A Kelch Motif-Containing Serine/Threonine Protein Phosphatase Determines the Large Grain QTL Trait in Rice. J. Integr. Plant Biol. 2012, 54, 979–990. [Google Scholar] [CrossRef]
  169. Cai, M.; Li, S.; Sun, F.; Sun, Q.; Zhao, H.; Ren, X.; Zhao, Y.; Tan, B.-C.; Zhang, Z.; Qiu, F. Emp10 Encodes a Mitochondrial PPR Protein That Affects the Cis -Splicing of Nad2 Intron 1 and Seed Development in Maize. Plant J. 2017, 91, 132–144. [Google Scholar] [CrossRef] [Green Version]
  170. Manavski, N.; Guyon, V.; Meurer, J.; Wienand, U.; Brettschneidera, R. An Essential Pentatricopeptide Repeat Protein Facilitates 5′ Maturation and Translation Initiation of Rps3 MRNA in Maize Mitochondria. Plant Cell 2012, 24, 3087–3105. [Google Scholar] [CrossRef] [Green Version]
  171. Wang, G.; Zhong, M.; Shuai, B.; Song, J.; Zhang, J.; Han, L.; Ling, H.; Tang, Y.; Wang, G.; Song, R. E+ Subgroup PPR Protein Defective Kernel 36 Is Required for Multiple Mitochondrial Transcripts Editing and Seed Development in Maize and Arabidopsis. New Phytol. 2017, 214, 1563–1578. [Google Scholar] [CrossRef] [Green Version]
  172. Wu, L.; Ren, D.; Hu, S.; Li, G.; Dong, G.; Jiang, L.; Hu, X.; Ye, W.; Cui, Y.; Zhu, L.; et al. Mutation of OsNaPRT1 in the NAD Salvage Pathway Leads to Withered Leaf Tips in Rice. Plant Physiol. 2016, 171, 1085–1098. [Google Scholar] [CrossRef] [Green Version]
  173. Zhang, Y.F.; Hou, M.M.; Tan, B.C. The Requirement of WHIRLY1 for Embryogenesis Is Dependent on Genetic Background in Maize. PLoS ONE 2013, 8, e67369. [Google Scholar] [CrossRef] [Green Version]
  174. Li, C.; Shen, Y.; Meeley, R.; McCarty, D.R.; Tan, B.C. Embryo Defective 14 Encodes a Plastid-Targeted CGTPase Essential for Embryogenesis in Maize. Plant J. 2015, 84, 785–799. [Google Scholar] [CrossRef] [Green Version]
  175. Qi, W.; Tian, Z.; Lu, L.; Chen, X.; Chen, X.; Zhang, W.; Song, R. Editing of Mitochondrial Transcripts Nad3 and Cox2 by Dek10 Is Essential for Mitochondrial Function and Maize Plant Development. Genetics 2017, 205, 1489–1501. [Google Scholar] [CrossRef] [Green Version]
  176. Hu, J.; Huang, L.; Chen, G.; Liu, H.; Zhang, Y.; Zhang, R.; Zhang, S.; Liu, J.; Hu, Q.; Hu, F.; et al. The Elite Alleles of OsSPL4 Regulate Grain Size and Increase Grain Yield in Rice. Rice 2021, 14, 90. [Google Scholar] [CrossRef]
  177. Yang, X.; Wu, F.; Lin, X.; Du, X.; Chong, K.; Gramzow, L.; Schilling, S.; Becker, A.; Theißen, G.; Meng, Z. Live and Let Die—The Bsister MADS-Box Gene OsMADS29 Controls the Degeneration of Cells in Maternal Tissues during Seed Development of Rice (Oryza sativa). PLoS ONE 2012, 7, e51435. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  178. Toyota, K.; Tamura, M.; Ohdan, T.; Nakamura, Y. Expression Profiling of Starch Metabolism-Related Plastidic Translocator Genes in Rice. Planta 2006, 223, 248–257. [Google Scholar] [CrossRef] [PubMed]
  179. Song, X.J.; Huang, W.; Shi, M.; Zhu, M.Z.; Lin, H.X. A QTL for Rice Grain Width and Weight Encodes a Previously Unknown RING-Type E3 Ubiquitin Ligase. Nat. Genet. 2007, 39, 623–630. [Google Scholar] [CrossRef] [PubMed]
  180. Chen, J.; Gao, H.; Zheng, X.M.; Jin, M.; Weng, J.F.; Ma, J.; Ren, Y.; Zhou, K.; Wang, Q.; Wang, J.; et al. An Evolutionarily Conserved Gene, FUWA, Plays a Role in Determining Panicle Architecture, Grain Shape and Grain Weight in Rice. Plant J. 2015, 83, 427–438. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  181. Li, J.; Fu, J.; Chen, Y.; Fan, K.; He, C.; Zhang, Z.; Li, L.; Liu, Y.; Zheng, J.; Ren, D.; et al. The U6 Biogenesis-Like 1 Plays an Important Role in Maize Kernel and Seedling Development by Affecting the 3′ End Processing of U6 SnRNA. Mol. Plant 2017, 10, 470–482. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  182. Ingram, G.C.; Magnard, J.L.; Vergne, P.; Dumas, C.; Rogowsky, P.M. ZmOCL1, an HDGL2 Family Homeobox Gene, Is Expressed in the Outer Cell Layer throughout Maize Development. Plant Mol. Biol. 1999, 40, 343–354. [Google Scholar] [CrossRef]
  183. Zhang, X.; Sun, J.; Cao, X.; Song, X. Epigenetic Mutation of RAV6 Affects Leaf Angle and Seed Size in Rice. Plant Physiol. 2015, 169, 2118–2128. [Google Scholar] [CrossRef] [Green Version]
  184. Hu, J.; Wang, Y.; Fang, Y.; Zeng, L.; Xu, J.; Yu, H.; Shi, Z.; Pan, J.; Zhang, D.; Kang, S.; et al. A Rare Allele of GS2 Enhances Grain Size and Grain Yield in Rice. Mol. Plant 2015, 8, 1455–1465. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  185. Bernard, S.M.; Møller, A.L.B.; Dionisio, G.; Kichey, T.; Jahn, T.P.; Dubois, F.; Baudo, M.; Lopes, M.S.; Tercé-Laforgue, T.; Foyer, C.H.; et al. Gene Expression, Cellular Localisation and Function of Glutamine Synthetase Isozymes in Wheat (Triticum aestivum L.). Plant Mol. Biol. 2008, 67, 89–105. [Google Scholar] [CrossRef] [PubMed]
  186. Duan, P.; Rao, Y.; Zeng, D.; Yang, Y.; Xu, R.; Zhang, B.; Dong, G.; Qian, Q.; Li, Y. SMALL GRAIN 1, Which Encodes a Mitogen-Activated Protein Kinase Kinase 4, Influences Grain Size in Rice. Plant J. 2014, 77, 547–557. [Google Scholar] [CrossRef]
  187. Shen, Y.; Li, C.; McCarty, D.R.; Meeley, R.; Tan, B.C. Embryo Defective12 Encodes the Plastid Initiation Factor 3 and Is Essential for Embryogenesis in Maize. Plant J. 2013, 74, 792–804. [Google Scholar] [CrossRef] [PubMed]
  188. Yang, X.; Ren, Y.; Cai, Y.; Niu, M.; Feng, Z.; Jing, R.; Mou, C.; Liu, X.; Xiao, L.; Zhang, X.; et al. Overexpression of OsbHLH107, a Member of the Basic Helix-Loop-Helix Transcription Factor Family, Enhances Grain Size in Rice (Oryza sativa L.). Rice 2018, 11, 41. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  189. Ma, X.; Cheng, Z.; Wu, F.; Jin, M.; Zhang, L.; Zhou, F.; Wang, J.; Zhou, K.; Ma, J.; Lin, Q.; et al. BEAK LIKE SPIKELET1 Is Required for Lateral Development of Lemma and Palea in Rice. Plant Mol. Biol. Report. 2013, 31, 98–108. [Google Scholar] [CrossRef]
  190. Fujisawa, Y.; Kato, T.; Ohki, S.; Ishikawa, A.; Kitano, H.; Sasaki, T.; Asahi, T.; Iwasaki, Y. Suppression of the Heterotrimeric G Protein Causes Abnormal Morphology, Including Dwarfism, in Rice. Proc. Natl. Acad. Sci. USA 1999, 96, 7575–7580. [Google Scholar] [CrossRef] [Green Version]
  191. Tong, H.; Jin, Y.; Liu, W.; Li, F.; Fang, J.; Yin, Y.; Qian, Q.; Zhu, L.; Chu, C. DWARF and LOW-TILLERING, a New Member of the GRAS Family, Plays Positive Roles in Brassinosteroid Signaling in Rice. Plant J. 2009, 58, 803–816. [Google Scholar] [CrossRef]
  192. Bernardi, J.; Lanubile, A.; Li, Q.B.; Kumar, D.; Kladnik, A.; Cook, S.D.; Ross, J.J.; Marocco, A.; Chourey, P.S. Impaired Auxin Biosynthesis in the Defective Endosperm18 Mutant Is Due to Mutational Loss of Expression in the ZmYuc1 Gene Encoding Endosperm-Specific YUCCA1 Protein in Maize. Plant Physiol. 2012, 160, 1318–1328. [Google Scholar] [CrossRef] [Green Version]
  193. Liu, S.; Hua, L.; Dong, S.; Chen, H.; Zhu, X.; Jiang, J.; Zhang, F.; Li, Y.; Fang, X.; Chen, F. OsMAPK6, a Mitogen-Activated Protein Kinase, Influences Rice Grain Size and Biomass Production. Plant J. 2015, 84, 672–681. [Google Scholar] [CrossRef]
  194. Li, J.; Chu, H.; Zhang, Y.; Mou, T.; Wu, C.; Zhang, Q.; Xu, J. The Rice HGW Gene Encodes a Ubiquitin-Associated (UBA) Domain Protein That Regulates Heading Date and Grain Weight. PLoS ONE 2012, 7, e34231. [Google Scholar] [CrossRef] [PubMed]
  195. Sosso, D.; Mbelo, S.; Vernoud, V.; Gendrot, G.; Dedieu, A.; Chambrier, P.; Dauzat, M.; Heurtevin, L.; Guyon, V.; Takenaka, M.; et al. PPR2263, a DYW-Subgroup Pentatricopeptide Repeat Protein, Is Required for Mitochondrial Nad5 and Cob Transcript Editing, Mitochondrion Biogenesis, and Maize Growth. Plant Cell 2012, 24, 676–691. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  196. Clancy, M.; Hannah, L.C. Splicing of the Maize Sh1 First Intron Is Essential for Enhancement of Gene Expression, and a T-Rich Motif Increases Expression without Affecting Splicing. Plant Physiol. 2002, 130, 918–929. [Google Scholar] [CrossRef] [Green Version]
  197. Adamski, N.M.; Simmonds, J.; Brinton, J.F.; Backhaus, A.E.; Chen, Y.; Smedley, M.; Hayta, S.; Florio, T.; Crane, P.; Scott, P.; et al. Ectopic Expression of Triticum Polonicum VRT-A2 Underlies Elongated Glumes and Grains in Hexaploid Wheat in a Dosage-Dependent Manner. Plant Cell 2021, 33, 2296–2319. [Google Scholar] [CrossRef]
  198. Tanaka, A.; Nakagawa, H.; Tomita, C.; Shimatani, Z.; Ohtake, M.; Nomura, T.; Jiang, C.J.; Dubouzet, J.G.; Kikuchi, S.; Sekimoto, H.; et al. Brassinosteroid Upregulated1, Encoding a Helix-Loop-Helix Protein, Is a Novel Gene Involved in Brassinosteroid Signaling and Controls Bending of the Lamina Joint in Rice. Plant Physiol. 2009, 151, 669–680. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  199. Miura, K.; Ikeda, M.; Matsubara, A.; Song, X.J.; Ito, M.; Asano, K.; Matsuoka, M.; Kitano, H.; Ashikari, M. OsSPL14 Promotes Panicle Branching and Higher Grain Productivity in Rice. Nat. Genet. 2010, 42, 545–549. [Google Scholar] [CrossRef]
  200. Kim, S.-R.; Ramos, J.M.; Hizon, R.J.M.; Ashikari, M.; Virk, P.S.; Torres, E.A.; Nissila, E.; Jena, K.K. Introgression of a Functional Epigenetic OsSPL14WFP Allele into Elite Indica Rice Genomes Greatly Improved Panicle Traits and Grain Yield. Sci. Rep. 2018, 8, 3833. [Google Scholar] [CrossRef]
  201. Liu, C.; Ma, T.; Yuan, D.; Zhou, Y.; Long, Y.; Li, Z.; Dong, Z.; Duan, M.; Yu, D.; Jing, Y.; et al. The OsEIL1-OsERF115-target Gene Regulatory Module Controls Grain Size and Weight in Rice. Plant Biotechnol. J. 2022, 20, 1470–1486. [Google Scholar] [CrossRef]
  202. Wang, S.; Wu, K.; Yuan, Q.; Liu, X.; Liu, Z.; Lin, X.; Zeng, R.; Zhu, H.; Dong, G.; Qian, Q.; et al. Control of Grain Size, Shape and Quality by OsSPL16 in Rice. Nat. Genet. 2012, 44, 950–954. [Google Scholar] [CrossRef] [PubMed]
  203. Huang, K.; Wang, D.; Duan, P.; Zhang, B.; Xu, R.; Li, N.; Li, Y. WIDE AND THICK GRAIN 1, Which Encodes an Otubain-like Protease with Deubiquitination Activity, Influences Grain Size and Shape in Rice. Plant J. 2017, 91, 849–860. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  204. Wu, T.; Ali, A.; Wang, J.; Song, J.; Fang, Y.; Zhou, T.; Luo, Y.; Zhang, H.; Chen, X.; Liao, Y.; et al. A Homologous Gene of OsREL2/ASP1, ASP-LSL Regulates Pleiotropic Phenotype Including Long Sterile Lemma in Rice. BMC Plant Biol. 2021, 21, 390. [Google Scholar] [CrossRef] [PubMed]
  205. Lin, Y.; Zhao, Z.; Zhou, S.; Liu, L.; Kong, W.; Chen, H.; Long, W.; Feng, Z.; Jiang, L.; Wan, J. Top Bending Panicle1 Is Involved in Brassinosteroid Signaling and Regulates the Plant Architecture in Rice. Plant Physiol. Biochem. 2017, 121, 1–13. [Google Scholar] [CrossRef]
  206. Luo, M.; Platten, D.; Chaudhury, A.; Peacock, W.J.; Dennis, E.S. Expression, Imprinting, and Evolution of Rice Homologs of the Polycomb Group Genes. Mol. Plant 2009, 2, 711–723. [Google Scholar] [CrossRef]
  207. Zhang, B.; Liu, X.; Xu, W.; Chang, J.; Li, A.; Mao, X.; Zhang, X.; Jing, R. Novel Function of a Putative MOC1 Ortholog Associated with Spikelet Number per Spike in Common Wheat. Sci. Rep. 2015, 5, 12211. [Google Scholar] [CrossRef] [Green Version]
  208. Sun, F.; Wang, X.; Bonnard, G.; Shen, Y.; Xiu, Z.; Li, X.; Gao, D.; Zhang, Z.; Tan, B.C. Empty Pericarp7 Encodes a Mitochondrial E-Subgroup Pentatricopeptide Repeat Protein That Is Required for CcmFN Editing, Mitochondrial Function and Seed Development in Maize. Plant J. 2015, 84, 283–295. [Google Scholar] [CrossRef]
  209. Song, X.J.; Kuroha, T.; Ayano, M.; Furuta, T.; Nagai, K.; Komeda, N.; Segami, S.; Miura, K.; Ogawa, D.; Kamura, T.; et al. Rare Allele of a Previously Unidentified Histone H4 Acetyltransferase Enhances Grain Weight, Yield, and Plant Biomass in Rice. Proc. Natl. Acad. Sci. USA 2015, 112, 76–81. [Google Scholar] [CrossRef] [Green Version]
  210. Sheng, M.; Ma, X.; Wang, J.; Xue, T.; Li, Z.; Cao, Y.; Yu, X.; Zhang, X.; Wang, Y.; Xu, W.; et al. KNOX II Transcription Factor HOS59 Functions in Regulating Rice Grain Size. Plant J. 2022, 110, 863–880. [Google Scholar] [CrossRef]
  211. Hong, Z.; Ueguchi-Tanaka, M.; Fujioka, S.; Takatsuto, S.; Yoshida, S.; Hasegawa, Y.; Ashikari, M.; Kitano, H.; Matsuoka, M. The Rice Brassinosteroid-Deficient Dwarf2 Mutant, Defective in the Rice Homolog of Arabidopsis DIMINUTO/DWARF1, Is Rescued by the Endogenously Accumulated Alternative Bioactive Brassinosteroid, Dolichosterone. Plant Cell 2005, 17, 2243–2254. [Google Scholar] [CrossRef] [Green Version]
  212. Song, J.M.; Guan, Z.; Hu, J.; Guo, C.; Yang, Z.; Wang, S.; Liu, D.; Wang, B.; Lu, S.; Zhou, R.; et al. Eight High-Quality Genomes Reveal Pan-Genome Architecture and Ecotype Differentiation of Brassica Napus. Nat. Plants 2020, 6, 34–45. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  213. Guan, J.; Xu, Y.; Yu, Y.; Fu, J.; Ren, F.; Guo, J.; Zhao, J.; Jiang, Q.; Wei, J.; Xie, H. Genome Structure Variation Analyses of Peach Reveal Population Dynamics and a 1.67 Mb Causal Inversion for Fruit Shape. Genome Biol. 2021, 22, 13. [Google Scholar] [CrossRef] [PubMed]
Ijms 24 04932 g001 550
Figure 1. Collinearity analysis between genomes and the grain size genes of barley and other plants. Grain size genes in other plants are shown in Table S1. The grey lines represent the collinearity of genome between H. vulgare and other plants, and the red lines represent the collinearity of the grain size genes between H. vulgare and other plants.
Figure 1. Collinearity analysis between genomes and the grain size genes of barley and other plants. Grain size genes in other plants are shown in Table S1. The grey lines represent the collinearity of genome between H. vulgare and other plants, and the red lines represent the collinearity of the grain size genes between H. vulgare and other plants.
Ijms 24 04932 g001
Ijms 24 04932 g002 550
Figure 2. Distribution of the collinearity genes across seven barley chromosomes. The red font represents the collinearity genes from maize, the green represents the collinearity genes from Arabidopsis, the orange represents the collinearity genes from wheat, and the purple represents the collinearity genes from rice.
Figure 2. Distribution of the collinearity genes across seven barley chromosomes. The red font represents the collinearity genes from maize, the green represents the collinearity genes from Arabidopsis, the orange represents the collinearity genes from wheat, and the purple represents the collinearity genes from rice.
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Table
Table 1. Information of the grain size of the QTL hotspots across all seven chromosomes.
Table 1. Information of the grain size of the QTL hotspots across all seven chromosomes.
ChrQTL
Hotspots		Position
(Mb)		QTLs or MTAsTypeReferences
1Hhotspot1H-119–38QTL_1H-4, qGw1-3, qSL1.1QTL[5,6,36,37]
1_0186, SCRI_RS_123187MTA
1Hhotspot1H-2333–391QTL_1H-6, QGl.NaTx-1H, QTL1_TGWQTL[5,38,39,40]
SCRI_RS_141598MTA
1Hhotspot1H-3474–500QTL_1H-12, QTL_1H-13, QTL_1H-14, qGL1QTL[5,17,39,41,42]
SCRI_RS_188218, Cmwg706, 12_30191MTA
2Hhotspot2H-117–45QTL-GL1, QTL_2H-2, QTL_2H-3, QTL_2H-4, QTL4_TGWQTL[5,40,41,43]
BK_12MTA
2Hhotspot2H-2562–583qGL2, QTL_2H-8, QTL6_TGW, qGl2-1, qGw2-3, qTgw2-1, KW-MA-2H, cqGW2–3, cqGW2–4, QTL_2H-9, KW-BA-2HQTL[5,6,17,31,32,39,40,42,44]
SCRI_RS_200291, SCRI_RS_171032, SCRI_RS_138463, vrs1MTA
3Hhotspot3H-10–58QTL_3H-1, KW-MA-3H, QTL_3H-2, QTL_3H-3, QTL_3H-4, QTL9_TGW, qSB3.1QTL[5,32,37,39,40,41]
2_0662, 12_11414, SCRI_RS_230486, SCRI_RS_115045MTA
3Hhotspot3H-2454–484KW-BA-3H.1, qGw3-5, QGl.NaTx-3H, QTL_3H-6QTL[5,6,32,38,39,41]
SCRI_RS_145300, SCRI_RS_235065MTA
3Hhotspot3H-3562–565qGw3-4, QTL_3H-10, qGl3-1, cqGL3, cqGW3–1, cqGW3–2, LEN-3HQTL[5,6,31,45]
4Hhotspot4H6–40QTL_4H-1, QTL_4H-2, QTL_4H-3, QTL12_TGW, QTL_4H-4, qGL4, QTL13_TGWQTL[4,17,36,39,40,41]
1_0113, SCRI_RS_180891, 12_30793, int-cMTA
5Hhotspot5H-10–23qTgw5-1, QTL_5H-1, QTL_5H-2, QTL_5H-3QTL[5,6,39]
SCRI_RS_168359, 11_10580MTA
5Hhotspot5H-2427–431QTL-GL2, qGL5H, QTL_5H-6, qTGW5, qGL5QTL[5,36,42,43,46]
1_0641, 2_1239MTA
5Hhotspot5H-3541–588QTL_5H-14, QTL-GP2, QTL-GT2, QTL_5H-15, QTL_5H-16, QTL16_TGW, QTL_5H-17QTL[5,36,39,40,43]
1_1071, 1_1490, SCRI_RS_159482, 11_10236, 12_30504MTA
6Hhotspot6H463–494QTL-GP3, QTL-GT3, QTL-GW2, QTL_6H-6, qTGW6.1, KW-BA-6H, KW-MA-6HQTL[5,17,32,37,43]
ABC175MTA
7Hhotspot7H519–540QTL19_TGW, qGl7-1, qGw7-1, cqGL7–1QTL[6,31,40,41]
12_30996MTA
Table
Table 2. Candidate or homologous genes for the barley grain size QTL hotspots.
Table 2. Candidate or homologous genes for the barley grain size QTL hotspots.
QTL HotspotsCandidate GenesBarley Gene_IDOther PlantsAccession NumberFunctional AnnotationReference
hotspot1H-1HvGSN1HORVU.MOREX.r3.1HG0008520RiceOs05g0115800Dual specificity phosphatase[47]
HvRSR1HORVU.MOREX.r3.1HG0012250RiceOs05g0121600AP2-like ethylene-responsive transcription factor[48]
hotspot1H-2HvBSK2HORVU.MOREX.r3.1HG0052470RiceOs10g0571300Serine/threonine-protein kinase BSK2[49]
vrs3/int-aHORVU.MOREX.r3.1HG0053590NANALysine-specific demethylase[50]
HvCO9HORVU.MOREX.r3.1HG0058180NANACONSTANS-like protein[51]
HvSM1HORVU.MOREX.r3.1HG0058550RiceOs05g0389000AP2-like ethylene-responsive transcription factor[52]
hotspot1H-3HvSLGHORVU.MOREX.r3.1HG0076820RiceOs08g0562500HXXXD-type acyl-transferase family protein[53]
PPD-H2/HvFT3HORVU.MOREX.r3.1HG0077240NANARNA ligase/cyclic nucleotide phosphodiesterase family protein[54,55,56]
Hvincw1HORVU.MOREX.r3.1HG0087260MaizeZm00001eb242820Cell wall invertase[57]
hotspot2H-1HvSDG725HORVU.MOREX.r3.2HG0096180RiceOs02g0554000Histone-lysine N-methyltransferase[58]
PPD-H1HORVU.MOREX.r3.2HG0107710NANAPseudo-response regulator[59,60]
hotspot2H-2VRS1/Int-dHORVU.MOREX.r3.2HG0184740NANAHomeobox leucine zipper protein[61]
hotspot3H-1vrs4HORVU.MOREX.r3.3HG0233930NANALOB domain protein[62]
HvCKX2HORVU.MOREX.r3.3HG0236930ArabidopsisAt2g19500Cytokinin oxidase/dehydrogenase[63]
HvGIHORVU.MOREX.r3.3HG0238250ArabidopsisAt1g22770Gigantea-like protein[64]
hotspot3H-2uzuHORVU.MOREX.r3.3HG0285210RiceOs01g0718300Receptor kinase[38,65,66]
hotspot3H-3sdw1/densoHORVU.MOREX.r3.3HG0307130RiceOs07g0169700Gibberellin 20 oxidase 2[6,31]
hotspot4HHvRGB1HORVU.MOREX.r3.4HG0333750RiceOs03g0669100Deoxyuridine 5′-triphosphate nucleotidohydrolase[67]
INT-C/Vrs5HORVU.MOREX.r3.4HG0336720MaizeZm00001eb054440Teosinte branched 1 protein[18]
Hvdek35HORVU.MOREX.r3.4HG0337450MaizeZm00001eb055010Pentatricopeptide repeat-containing protein[68]
HvAHKsHORVU.MOREX.r3.4HG0337770ArabidopsisAt2g01830Histidine kinase[69]
Hvemp4HORVU.MOREX.r3.4HG0339220MaizeZm00001eb055980Pentatricopeptide repeat-containing protein[70]
Vrn-H2HORVU.MOREX.r3.4HG0340200NANARING finger and CHY zinc finger protein[71]
HvDAR1HORVU.MOREX.r3.4HG0341060ArabidopsisAt4g36860Protein DA1-related 1[11]
hotspot5H-1HvIKU2HORVU.MOREX.r3.5HG0421310ArabidopsisAt3g19700Receptor protein kinase, putative[72]
HvPPKL3HORVU.MOREX.r3.5HG0426290RiceOs12g0617900Serine/threonine-protein phosphatase[73]
hotspot5H-2HvDEP1HORVU.MOREX.r3.5HG0480200RiceOs09g0441900Guanine nucleotide-binding protein subunit gamma 3[74,75]
hotspot5H-3HvDSTHORVU.MOREX.r3.5HG0516880RiceOs03g0786400Zinc finger protein, putative[76]
HvABA2HORVU.MOREX.r3.5HG0524120ArabidopsisAt1g52340Short-chain dehydrogenase/reductase[77]
hotspot6HHvdek1HORVU.MOREX.r3.6HG0608170MaizeZm00001eb014030Calpain-like protein[78]
HvLec1HORVU.MOREX.r3.6HG0611100MaizeZm00001eb253260Nuclear transcription factor Y subunit B[79,80]
hotspot7HNudHORVU.MOREX.r3.7HG0719680NANAEthylene-responsive transcription factor[19]
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Hong, Y.; Zhang, M.; Xu, R. Genetic Localization and Homologous Genes Mining for Barley Grain Size. Int. J. Mol. Sci. 2023, 24, 4932. https://doi.org/10.3390/ijms24054932

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Hong Y, Zhang M, Xu R. Genetic Localization and Homologous Genes Mining for Barley Grain Size. International Journal of Molecular Sciences. 2023; 24(5):4932. https://doi.org/10.3390/ijms24054932

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Hong, Yi, Mengna Zhang, and Rugen Xu. 2023. "Genetic Localization and Homologous Genes Mining for Barley Grain Size" International Journal of Molecular Sciences 24, no. 5: 4932. https://doi.org/10.3390/ijms24054932

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