Next Article in Journal
Progress in Mechanized Harvesting Technologies and Equipment for Minor Cereals: A Review
Previous Article in Journal
Phenotypic Trait Acquisition Method for Tomato Plants Based on RGB-D SLAM
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Agriculture
Volume 15
Issue 15
10.3390/agriculture15151575
agriculture-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Review

The Genetic Basis of Wheat Spike Architecture

by
Zhen Ji
†,
Xin Liu
†,
Fei Yan
,
Shouqing Wu
and
Yanfang Du
*
State Key Laboratory of Wheat Improvement, College of Life Sciences, Shandong Agricultural University, Tai’an 271018, China
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Agriculture 2025, 15(15), 1575; https://doi.org/10.3390/agriculture15151575
Submission received: 21 May 2025 / Revised: 15 July 2025 / Accepted: 19 July 2025 / Published: 22 July 2025
(This article belongs to the Section Crop Genetics, Genomics and Breeding)
Browse Figures
Versions Notes

Abstract

Wheat is one of the three major staple crops globally. The wheat spike serves as the primary structure bearing wheat grains. Spike architectures of wheat have a direct impact on the number of grains per spike, and thus the grain yield per spike. The development of wheat spike morphology is conserved to some extent in cereal crops, yet also exhibits differences, being strictly regulated by photoperiod and temperature. This paper compiles QTLs and genes related to wheat spike traits that have been published over the past two decades, summarizes the photoperiod and vernalization pathways influencing the transition from vegetative to reproductive growth, and organizes the key regulatory networks controlling spikelet and floret development. Additionally, it anticipates advancements in wheat gene cloning methods, challenges in optimizing wheat spike architecture for high yield and future directions in wheat spike trait research.

1. Introduction

Wheat yield is primarily influenced by three factors: the number of grains per spike, thousand-grain weight, and effective spikes per acre. The development of wheat spikes is closely linked to grain yield per spike. Molecular genetic studies on spike yield traits in wheat began in the 2000s. Despite over three decades of research, progress has been impeded by challenges such as the complexity of the wheat genome, difficulty in locating major-effect genes, low genetic transformation efficiency, and the strong influence of environmental factors on quantitative traits. Consequently, research has mainly focused on the quantitative genetic analysis of yield traits, while the cloning of key genes, their functional analysis, and understanding their mechanisms have advanced slowly. Breakthroughs in applying molecular breeding to improve yield traits have also been difficult to achieve.
In the past decade, with the completion of the wheat genome sequencing [1,2,3,4,5,6], the fast-cloning methods of quantitative trait genes [7,8,9,10], the maturation of the wheat genetic transformation system [11,12,13] and the establishment of excellent mutant libraries for spike traits [8,14], molecular genetic research on spike yield traits in wheat has advanced rapidly. The yield potential of key genes controlling spike architecture, such as wheat CONSTANS-like 5 (TaCol-B5) and Reduced height-B1b (Rht-B1b)/EamA-B/Zinc-finger RING-type E3 ligase-B (ZnF-B) [15,16], suggests that research on the genetic basis of spike traits is of great significance for breeding high-yield wheat varieties.
In recent years, several comprehensive reviews have summarized significant advancements in wheat multi-omics, pan-genomics, the genetic basis of key traits, and breeding improvements. These reviews also provide insights into the future directions of wheat molecular breeding [17,18,19,20,21]. This article focuses on the development patterns of wheat spike architecture, recent QTLs identified for controlling spike traits, and key genes and genetic regulatory networks involved. We discussed four critical frontiers in wheat research and breeding strategies: anticipated progress in gene cloning technologies, ongoing obstacles in spike architecture optimization for higher yields, future trajectories for spike trait investigation, and strategies to improve wheat yield by combining genetic potential with agrotechnical factors.

2. The Development of Wheat Inflorescence

The spike architecture of wheat is tightly associated with grain yield, which is unbranched like most inflorescences of Triticeae species, and differs from the branched panicle of rice and the branched tassel inflorescence of maize [22,23,24]. On the determinate and compound spike of wheat, 15–30 spikelets are attached to the flanking region of the rachis, each spikelet generates 5–8 florets, and 3–5 of them will be fertilized to form seeds, and the basal portion of the rachis typically bears 1–2 sterile spikelets [23,24,25]. Thus, the number of fertile spikelets and florets determines the grain number per spike (GNS), which typically ranges between 30 to 60 grains. The rachis or spike axis, which bears the spikelets, typically ranges from 4 to 18 cm in length. The number of spikelets per spike and the length of the spike determine the compactness of the spikelet, typically ranging from 1.5 to 4 spikelets per centimeter.
The developmental progression of wheat spikes exhibits a temporally regulated developmental continuum, in which the inflorescence continues its current growth program, and it also begins stage-specific differentiation. This ontogenetic process encompasses six critical developmental transitions: vegetative-to-reproductive phase transition, single ridge (SR) morphogenesis, double ridge (DR) determination, spikelet differentiation, floret specification, and floral organogenesis (Figure 1A) [22,23,24], and these key developmental events directly influence the composition of spike traits. Upon perceiving intrinsic signals from the plant and external environmental cues such as photoperiod and temperature, the shoot apical meristem (SAM) first elongates and differentiates into leaf ridges, marking the single ridge stage. Subsequently, the adaxial side of each leaf ridge initiates the formation of spikelet ridges, marking the DR stage (Figure 1A). As the spikelet ridges develop into spikelet meristem (SM) along the flanking regions of the rachis, the growth of the leaf primordium is suppressed and eventually ceases (Figure 1A). Spikelet primordia are initially initiated in the mid-region of the rachis, followed by basipetal (downward) and acropetal (upward) extension. A critical developmental transition occurs with the emergence of the terminal spikelet (TS) at the apex, which establishes the final spikelet number through cessation of rachis meristem activity (Figure 1A). Thus, delaying TS differentiation through genetic/photoperiodic modulation can extend the spikelet differentiation window, resulting in spikelet number increase and subsequent grain yield improvement per spike. The primary spikelet primordia in the mid-spike region undergo three consecutive developmental phases: glume differentiation phase, floret initiation phase with basipetal progression, and floral organogenesis phase. Apical florets (positions 4–6) exhibit developmental arrest probability under suboptimal conditions (Figure 1A). Therefore, increasing fertile floret number presents a viable complementary approach to TS differentiation delay for enhancing GNS.
In notation, spikelet is a unique structural unit characteristic of grasses (Poaceae) but differs in the species (Figure 1B). The development process of SMs in wheat is much simpler than that in rice and maize. In rice paniclare attachedpikelet meristems produced from the primary branches meristems and secondary branches meristems, and each SM produces one floret primordium [26]; while in maize tassel, two SMs initiated from spikelet pair meristem that attached on the primary and secondary branches meristems, and then each SM produces two floret primordia (Figure 1B) [22,27].

3. The Major QTLs Controlling Wheat Spike Architecture

Spike morphology emerges through well-orchestrated meristematic activities and cellular expansion processes, constituting an important yield-related trait that has garnered significant research attention. Based on the long-term genetic study of wheat spike architecture, particularly in quantitative genetics, a large amount of data has been accumulated, which makes contributions to understanding the genetic basis of wheat spike architecture. Recent advances in high-quality reference genome sequencing data, whole-genome sequence data of large-scale wheat natural accessions, the creation of diverse mutant pools, and fast-cloning gene mapping pipelines have accelerated the discovery of wheat genes, especially those controlling spike architecture [1,2,5,7,8,10]. Here, we summarize recent findings in molecular quantitative genetics of wheat inflorescence architecture. We collected a total of 1158 QTLs with a logarithm of odds (LOD) score > 2.5 and have precise physical position (CS ref 1.0) that controls spike length (SL), spikelet compactness (SC), total spikelet number per spike (SNS), and GNS from the publicly available databases. We grouped QTLs within each trait if their distance was less than 10 Mb, resulting in a total of 743 QTL clusters; if a QTL was associated with only one marker, then a 10 Mb flanking region around the marker was considered the QTL interval (Table 1, Figure 2, Table S1). 59 known genes controlling wheat inflorescence development were also labeled based on their physical positions (Figure 2, Table S2).

3.1. QTLs Controlling Spike Length and Spike Compactness

SL and SC are direct indicators of spike type; a short rachis with more spikelets characterizes a compact spikelet arrangement, whereas a longer rachis with fewer spikelets results in a looser configuration. The length of the wheat spike axis changes throughout the development process of the wheat spike: during the spikelet differentiation stage, a longer spike axis provides growth space for the formation of more branches and spikelets, the longer rachilla has the potential to produce more spikelet; in the booting and heading stages, as the volume of the florets and spikelets expands, the spike axis rapidly elongates, ultimately determining whether the arrangement of spikelets and florets is loose or compact [18,28,29,30,31]. Here we collect 225 QTLs within 126 QTL clusters controlling SL, distributed on 21 wheat chromosomes, chr3B and chr5A could be the QTL hotspots (Table 1, Figure 2, Table S1). Especially, QTLs clusters (SL-cluster2D.1) on the short arm of chr2D, which intervals from 17.61–26.40 Mb, could be the same SL QTL (Table 1 and Table 2, Figure 2), this consist QTLs is identified in eight distinct mapping populations, and the PVE ranges from 11.36% and 42.33% [18,32,33,34,35,36,37,38,39]. An early study of this QTL was precisely mapped to the 5.9-cM Xgwm261–XRPP5 interval and explained up to 20% of the phenotypic variation [38]. Recent studies have shown that Reduced height8 (Rht8), a well-known “Green Revolution gene” located in this region (SL-cluster2D.1), not only controls plant height but also exerts pleiotropic effects on spike length by modulating the gibberellin and ethylene pathways [32,40].
SC is the ratio of SNS to SL, reflecting the compact or looser shape of the spike. Here we collect 99 SL QTLs within 49 QTL clusters covered on 17 chromosomes of the wheat genome, of which the PVE ranges from 9.68–23.41% (Table 1, Figure 2, Table S1), most of the QTLs are located on chr2D and chr5A. We found 21 clusters where the intervals for SL and spikelet density overlap, for example, SC-cluster2D.1 and SL-cluster2D.1, SC-cluster3B.2 and SL-cluster3B.7, SC-cluster4B.1 and SL-cluster4B.1, SC-cluster5A.3 and SL-cluster5A.5, SC-cluster5B.4 and SL-cluster5B.5, SC-cluster7B.1 and SL-cluster7B.2 (Table 2), respectively. Several spike related genes have been identified in this region, including Ta-AUXIN RESPONSE FACTOR12 (TaARF12), Rht8, TaLAX PANICLE1 (TaLAX1), Rht-B1b, ZnF-B, VERNALIZATION2 (VRN2), WHEAT SUPPRESSOR OF OVEREXPRESSION OF CO1 (WSOC1), SHORT VEGETATIVE PHASE 1 (SVP1), Ta-PIN-FORMED 1 (TaPIN1), Ta-tetratricopeptide repeat-6B1 (TaTPR-B1), and WHEAT ABERRANT PANICLE ORGANIZATION 1 (WAPO1) (Table 2). The auxin response factor, TaARF12, regulates spike rachis development via gibberellin signaling, and its homologs TaARF12-2A and TaARF12-2B are located in SL/SC-cluster2A and SL/SC-cluster2B, respectively (Figure 2, Table 2) [41]. TaLAX1 gene, located in SL-cluster3B.7 and SC-cluster3B.2, positively regulates SL and negatively regulates SC via interaction with domestication gene Q (Figure 2, Table 2) [42]. TaTPR-B1, encoding a TPR-like superfamily protein, is located within both the SL-cluster6B.5 and SC-cluster6B.2. A 32-bp insertion/deletion (InDel) within its coding region was associated with increased SC and reduced SL. This effect may be mediated through multiple regulatory pathways, including responses to heat stress and cytokinin biosynthesis [43]. This strongly suggests that SL and SC have a similar genetic foundation, which is reasonable because SC is defined as the ratio of the number of spikelets to the spike length.

3.2. QTLs Controlling Spikelet Number per Spike

SNS is positively associated with the GNS. Usually, there are 15–30 spikelets arranged on the flanked rachis, and 1–2 spikelets at the base of the rachis are sterile. Here we collect 309 SNS QTLs within 221 QTL clusters distributed on 21 chromosomes controlling the total number of spikelets, and the PVE ranges from 9–52%. A total of 44 genes (containing homology genes on the sub-genome) that control spike development are located in these intervals, including genes controlling vernalization, flowering time or heading date, spikelet and floral formation (Table 1, Figure 2, Table S1). SNS hotspot regions SNS-cluster5A.6 and SNS-cluster5A.7 contain two previously reported genes regulating wheat vernalization, VERNALIZATION1 (VRN1) and VRN2, indicating that vernalization status is closely related to spikelet development [44,45]. Besides vernalization status, flowering or heading time is an important factor that affects SNS, the collected data showed that flowering time regulators FLOWERING LOCUS T3-B1 (TaFT3-B1), EARLY FLOWERING 3-D1 (TaELF3-D1), A-genome copy of FLOWERING LOCUS T2 (FT-A2), wheat PCL1/LUX (WPCL1), wheat O-LINKED N-ACETYLGLUCOSAMINE (O-GLCNAC) TRANSFERASE (OGT) 1 (TAOGT1), wheat HEADING DATE 1 (TaHD1-6A) located in SNS intervals SNS-cluster1B.9, SNS-cluster1D.7, SNS-cluster3A.2, SNS-cluster3A.7, SNS-cluster6A.3 and SNS-cluster6A.7, respectively [46,47,48,49]. Additionally, homologous genes affecting spikelet or branch development in related species are also located in the SNS clusters, such as RARE TRIPLE SPIKELET (TRS1)/WHEAT FRIZZY PANICLE (WFZP), wheat SQUAMOSA PROMOTER BINDING PROTEIN-LIKE 17 (TaSPL17), and WAPO1 [50,51,52,53,54,55,56] (Figure 2, Tables S1 and S2). The TaCol-B5 was in SNS-cluster7B.15 that explained 10.3% PVE. The overexpression of TaCol-B5 in transgenic plants has led to an 11.9% enhancement in yield under field conditions. TaCOL-B5 encodes a plant CONSTANS-like protein; allelic variation in TaCOL-B5 leads to amino acid substitutions, which in turn cause differential phosphorylation of the protein by the kinase TaK4. This phosphorylation event consequently affects both heading date and the number of spikelets. Given that this allele is present at an exceptionally low frequency in common wheat varieties and remains untapped, it suggests that TaCOL-B5 holds substantial promise for enhancing wheat breeding efforts [16].

3.3. QTLs Controlling Grain Number per Spike

The number of grains per spike is an important target for improvement in wheat breeding and a complex quantitative trait controlled by multiple genes, which are determined by the number of spikelets and the number of fertile florets. According to genetic studies, the heritability of GNS in wheat is high, indicating that genetic factors contribute significantly to this trait [57,58]. Despite its relatively high heritability, the GNS is still strongly influenced by environmental conditions such as water availability, light, and nutrient supply. We have collected 221 GNS-clusters consisting of 309 GNS QTLs; these QTLs are distributed on the whole genome, chr2A and chr5B have more QTLs compared to others, and the PVE ranges from 5–26.57% (Table 1, Figure 2, Table S1). Though a huge number of loci have been identified, a few genes have been identified. The homeodomain leucine zipper class I transcription factor, Grain Number Increase 1 (GNI1), expressed in the apical floret primordia and in parts of the rachilla, has the potential to increase grain number by regulating the floret fertility [59]. The wheat AGAMOUS LIKE 6 (AGL6) (SNS-cluster6A.5) regulates GNS by manipulating both floral organ identity and SM development. The mutation of AGL6 exhibited a deficiency in the development of all four whorls of floral organs, while overexpression of AGL6 increased SNS [60]. Additionally, FT2 regulates GNS by targeting SNS; the natural variation in FT-A2 is associated with significant increases in SNS and has no negative effects on fertility in tetraploid wheat (Figure 2, Tables S1 and S2) [46]. This indicates that key genes affecting SNS and floret number contribute to variations in GNS. By improving spike structure, yield can be increased, thereby achieving the goal of boosting production.
The broad-sense heritability (h2) of wheat spike traits, including SL, SC, SNS, and GNS, ranged from 50% to 90%, with SL exhibiting the highest heritability and the SNS and GNS showing relatively lower heritability. These findings suggest that genotype, environment, and genotype-by-environment interactions have a significant impact on wheat panicle traits. The PVE for these traits ranged from 5% to 52%, indicating substantial potential for improvement. Therefore, identifying key genes controlling spike traits to enhance yield by simultaneously improving genetic effects, optimizing environmental conditions, and effectively leveraging genotype-by-environment interactions is an effective strategy to ensure wheat food security.

4. The Genetic Regulating Network in Shaping Spike Morphology

Despite the identification of hundreds of spike-related yield-associated traits, only a limited number of corresponding genes have been successfully cloned. The majority of these genes were identified through the analysis of mutants or by cloning homologous genes from different species. These genes play important roles in regulating the transition of the wheat shoot apical meristem from vegetative to reproductive growth, and in modulating the development of spikelets (including supernumerary spikelets, SS) and florets through various molecular mechanisms.

4.1. The Transition from the Shoot Apical Meristem to Inflorescence Meristem: The Photoperiod and Vernalization Pathway

Flowering time represents a key determinant of cereal crop adaptation to environmental fluctuations, ensuring successful reproduction and contributing to high yield potential. At this pivotal developmental stage, plants undergo the transition from the shoot apical meristem (SAM) to the inflorescence meristem (IM), thereby shifting from vegetative to reproductive growth. The transition processes have integrated various endogenous and environmental signals, such as the crosstalk of various plant hormones, the activation and deactivation of receptors that respond to environmental changes, along with photoperiod and temperature signals, all of which enable plants to flower (Figure 3A). Winter wheat and barley (rather than spring wheat and barley), as temperate grasses, flower in the spring or early summer in response to shortening nights (lengthening photoperiods) and are referred to as long-day (LD) plants; thus, the photoperiod is a significant factor influencing the transition to reproductive growth [61,62]. Additionally, vernalization is essential for winter wheat to complete its reproductive transition, ensuring that flowering occurs only after winter signals are sensed, thereby preventing premature autumn flowering and subsequent grain failure [63]. The photoperiod and vernalization pathway are integrated to activate the expression of FLOWERING LOCUS T (FT)-like genes in the leaves, which play the central role in initiating the flowering process in all the flowering plants [64,65].
There has been considerable research on the regulation of reproductive transition by photoperiod and vernalization pathways in wheat. Photoperiod1 (Ppd1) is the major determinant of photoperiod response in barley and wheat, the mutation of which results in delayed flowering. It encodes a pseudo-receiver domain and a CCT domain and is homologous to Arabidopsis PSEUDO-RESPONSE REGULATOR7 (PRR7) and rice PRR3. Notably, Ppd1 negatively regulates the expression of the PHOTOPERIOD-1-DEPENDENT BZIP TRANSCRIPTION FACTOR (PDB1) at the DR stage, thereby suppressing flowering and the development of the TS [66]. Under LD conditions, Ppd1 activates the expression of wheat FT1 to promote flowering [61]. Upstream of Ppd1, EARLY FLOWERING 3 (ELF3), a component of the evening complex in the circadian clock, interacts with the phytochromes PHYTOCHROME B (PHYB) and PHYC and directly binds to the Ppd1 promoter region to repress its expression (Figure 3A). The elf3 mutant exhibits early flowering, like what is observed in barley [67]. In notation, the promotion of flowering by Ppd1 under LD conditions requires light, which is mediated by PHYB and PHYC. The phyC loss-of-function mutant shows a dramatically delayed flowering under LD photoperiods through altering the expression profiles of photoperiod and clock-related genes (Figure 3A) [68,69,70].
Vernalization refers to the process by which plants acquire the ability to flower or accelerate flowering after being exposed to a period of low temperatures. This process allows temperate grasses to adapt to seasonal changes and regulate their response to photoperiod [63]. In winter wheat, VRN1, VRN2, and VRN3 (FT), FLC-like genes, and cold sensors form a finely coordinated system that regulates the transition from vegetative growth to reproductive growth (Figure 3A) [71,72]. VRN1 encodes a MADS-box transcription factor and is the master gene controlling vernalization in wheat. Its expression is induced by low temperatures, and after prolonged cold treatment, its expression significantly increases. When vernalization is complete, the high expression of VRN1 initiates the plant’s flowering process [44]. In contrast, VRN2, which encodes a zinc finger transcription factor, inhibits flowering by repressing the expression of VRN1 [45]. When VRN1 is activated, VRN3 expression increases, which in turn promotes wheat flowering [65]. SVP-like protein VEGETATIVE TO REPRODUCTIVE TRANSITION 2 (VRT2) interacts with VRN1 and binds to the VRN1 promoter to promote vernalization-induced flowering in wheat (Figure 3A) [73]. Meanwhile, a SUPPRESSOR OF OVEREXPRESSION OF CONSTANS1 (SOC1)-like MADS-box transcription factor competes with VRT2 for binding to VRN1, thereby repressing flowering [73,74] (Figure 3A). The results of light and cold signaling induced the FT expression in the leaves, and then the FT protein moved to the SAM [64]. FT interacts with 14-3-3 and FDL (rice FD homologs) proteins to form a florigen activation complex (FAC) that binds to the promoter of the VRN1 and activates its expression to trigger the transition, and VRN1 represses VRN2 which suppresses flowering, thus generating a positive feedback loop that accelerates flowering (Figure 3A) [75,76].

4.2. The Regulator Network of Spikelet Development: The Normal Spikelet and Supernumerary Spikelets

The spikelet is the basic unit of the flower organ in Poaceae plants. The SM originates from the axillary meristem (AM) during the DR stage and ceases activity upon the formation of the TS at the apex of the spike in wheat [24]. Disrupting the activity of the IM and extending the differentiation time of the TS can increase the number of spikelets. Additionally, the formation of supernumerary spikelets (SS: including paired or multi-row spikelets, where two or more spikelets develop at a single rachis node) and the occurrence of branching spikes also present significant potential for enhancing SNS. In the past two decades, with the continuous improvement of hexaploid wheat genome sequencing and the updating of gene cloning methods, multiple genes involved in the regulation of spikelet development have been identified using wheat mutant materials and homologous gene function research.
The wheat SQUAMOSA clade MADS-box genes VRN1, FRUITFULL 2 (FUL2), and FUL3 are the homologs of the Arabidopsis APETALA1 (AP1), CAULIFLOWER (CAL), and FUL, play critical and redundant roles in promoting the transition from IM to TS and for spikelet development (designated as Pathway 1, Figure 3B) [44,77,78,79]. In the vrn1 and ful2 single mutants, the differentiation of the TS is delayed, leading to an increase in the number of spikelets. However, in the vrn1 ful2 double mutants or vrn1 ful2 ful3 triple mutants, all lateral spikelets are replaced by leaf-like branches (inflorescence tillers) [77]. Interestingly, further study showed that three SVP MADS-box genes VRT2 and SVP1 were repressed by these SQUAMOSA genes in specifying the SM identity (designated as Pathway 2, Figure 3B) [80]. vrt2 or svp1 mutations had higher SNS caused by delayed flowering than the wild-type; the vrt2 svp1 mutant enhanced the phenotype, while the constitutive expression of VRT2 resulted in spikelets with leaf-like glumes, which seems like the reversion of spikelets to spikes [80]. The expression pattern identified by in situ hybridization and multiplexed error-robust fluorescence in situ hybridization (MERFISH) in wheat spikes shows that FUL2, FUL3, and SOC1 are expressed in the apical meristem of the inflorescence (https://www.wheat-spatial.com/), suggesting their roles in controlling IM-TS transition. Additionally, these genes are expressed in the adaxial and abaxial boundaries of spikelets and the basal part of the spike at the early DR stage (Figure 3C), indicating their involvement in regulating SM identity specification.
Spikelet number and heading date are key factors considered by breeders, and therefore, critical genes regulating these factors can also be identified using cultivated wheat varieties, such as the WHEAT ORTHOLOG OF APO1 (WAPO1-A1) and TaCOL-B5 (designated as Pathway 3 and 4). WAPO1-A1, encoding an F-box protein, was located within the SNS QTL region on chromosome arm 7AL, WAPO1 positively regulates the SNS by delaying the time of TS formation, and the WAPO-H2 haplotype with the strongest effects in increasing SNS has already been used in most modern common wheat varieties [53,56]. Plant-specific transcription factor LEAFY (LFY) physically and genetically interacts with WAPO1, which plays a conserved role as in Arabidopsis; mutations in lfy also reduce SNS (Figure 3B). The single-molecule fluorescence in-situ hybridization showed that LFY expression was higher in the basal region and lower in central-distal regions of the SM, whereas WAPO1 transcripts were accumulated in the distal part of the spikelet (Figure 3C). The partially overlapped expression region showed LFY interacts with WAPO1 in regulating SNS [81,82]. Integrating multi-omics data of wheat spikes has identified several transcription factors regulating SNS, such as TaWRKY37-A1, TaMYC2-A1, and TaMYB30-A1. However, the precise mechanisms by which these transcription factors orchestrate spikelet development warrant further investigation [83].
Moreover, microRNAs play key roles in regulating spikelet development. The miR156-SPL module and the miR172-AP2/ERF pathway are well-characterized in mediating the transition from vegetative to reproductive phases in plants. The overexpression of tae-miR156 in bread wheat results in an extremely shortened rachis with a single spikelet positioned at the apex, which might be regulated through miR156-SPL3/17-TaBA1 (ortholog of maize barren stalk1 and rice LAX1) pathway (designated as Pathway 5, Figure 3B) [84]. In addition, a class III homeodomain-leucine zipper transcription factor, HOMEOBOX DOMAIN-2 (HB-2), which is expressed in the periphery layer of the spikelet, harboring the miR165/166 targeting site, the mutation of the binding site of HB-2 generates SS (designated as Pathway 6, Figure 3B) [85,86].
SS in wheat, similar to clustered spikelets in rice, are a desirable trait as they can boost grain yield by increasing the number of spikelets per spike, while also potentially balancing the trade-off between grain number and size [87]. Genes in the photoperiod pathway influence the development of compound spikelets, with Ppd-1 playing a dual role. It not only contributes to photoperiod adaptation by regulating FT expression but also promotes SS formation by controlling the stage-specific expression of genes related to auxin signaling, meristem identity, and protein turnover. Ppd-1 gene suppresses the expression of the ALOG transcription factor ALOG1, which is orthologous to OsG1L1 in rice. ALOG1 transcripts are localized to the lower region of spikelet primordia, and their downregulation by Ppd-1 inhibits flowering-time and the formation of SS (designated as Pathway 7, Figure 3C) [66,88]. Additionally, the other conserved role of homologous genes in regulating SS development is also common in wheat, including genes such as TEOSINTE BRANCHED-D1 (TB-D1), WFZP-B1, DUO-B1 [51,54,75,89]. TCP TF, TB1 is first identified in maize, which suppresses the AMs initiation by targeting core cell cycle genes during maize domestication [90,91,92,93]. In wheat, TB1 interacts with FT, and increased dosage of TB1 competitively binds to FT in the FAC, thus reducing expression of meristem identity genes and promoting SS formation; while at the normal levels of TB1, FAC formed and suppressed the SS development (designated as Pathway 7, Figure 3C) [75]. In rice, the FRIZZY PANICLE (FZP) gene and its maize counterpart, BRANCHED SILKLESS1 (BD1), encode an AP2/ERF transcription factor that is specifically expressed in the lateral domains of the SM. This transcription factor regulates the maintenance of the SM and its transition to the floret meristem [94,95]. In bread wheat, WFZP is expressed at the inner domain of the SM and initiation sites of the floral meristem, controlling the fate of the spikelet and floret, partially mediated by VRN1 and TaHOX4 (designated as Pathway 8, Figure 3C). The wfzp mutant in wheat results in a SS phenotype with multi-row spikes developing at a rachis node, highlighting the conserved role of FZP in controlling axillary meristem development across cereal species [51,52,54]. Another AP2/ERF transcription factor DUO-B1, identified in Brachypodium distachyon and orthologous in wheat, results in the development of mild SS when mutated, thereby increasing the number of grains per spike and boosting grain yield under field conditions. This effect is achieved through the promotion of cell division and the suppression of WFZP expression (designated as Pathway 8, Figure 3C) [89].
Compared to the expression pattern of the gene controlling SM formation, these genes were dynamically and specifically expressed in the SM, from the early DR to the floret developing stage. For example, FUL2 and FUL3 were expressed at the boundary of SM at early DR, then expanded to the whole region in the SM. TaSPL17 was expressed in a border part at the adaxial side of SM and then limited to a narrow region later, while LFY was abundant in the lower ridge and later in the bird’s nest located distal to the lemma primordia (Figure 3C) (https://www.wheat-spatial.com/) [11,77,81,82]. These findings suggest that the development of SM in wheat is a highly temporal and spatial process, which hinges on the precise and spatially restricted temporal expression of genes, along with their intricate interplay. Investigating the roles of these genes is vital for comprehending spikelet development and enhancing crop productivity.

4.3. The Genes Controlling Floret Development: The Floret Number and Floral Organ Identity

The number of florets per spikelet in wheat, particularly the quantity of fertile florets, directly determines the GNS. Unlike maize and rice which possess determinate spikelets, wheat exhibits indeterminate spikelet development (capable of continuous floret initiation). Each wheat spikelet typically differentiates 5–8 florets, with the basal florets formed earlier (usually 3–5) being fertile and developing into grains following successful fertilization (Figure 1B). Current understanding of genetic control over floret number per spikelet remains limited. Homeodomain leucine zipper class I (HD-Zip I) transcription factor, GNI1, has been identified as a key regulator governing both total floret number and fertile floret count. Spatial expression analysis reveals GNI1 is predominantly expressed in the apical floret primordia and in parts of the rachilla, suggesting GNI1 may restrict floret growth space by suppressing rachilla elongation (designated as Pathway 9, Figure 3D) [59]. The WFZP-TaMYB30-A1 module, identified via multi-omics integration, regulates floret fertility with spatiotemporal precision. TaMYB30-A1 exhibits stage-specific expression in stamen, gynoecium, and carpel differentiation regions (Pathway 8, Figure 3D) [83]. The miR156-TaSPL13 module represents an additional regulatory pathway controlling floret number per spike. Overexpression of TaSPL13 significantly increases both floret quantity and grain number per spikelet and even per spike (Pathway 5, Figure 3D) [96,97]. Emerging insights from spike transcriptomics reveal that phytohormone pathways, including auxin, salicylic acid (SA), and jasmonic acid (JA) signaling, and ERF, WRKY, NF-Y, and SBP transcription factors are implicated in floret meristem establishment (designated as Pathway 10, Figure 3D) [83,98]. Further elucidation of the genetic basis regulating spikelet primordia differentiation into floret primordia may necessitate single-cell transcriptome sequencing and complementary genetic validation.
The wheat floret, like other cereal crops, develops four concentric whorls of floral organs: lemma, palea, two lodicules, three stamens, and one pistil. Due to the lack of flower organ mutants in wheat, only a few genes that control floral organs have been identified, and these genes mainly belong to the MADS-box transcription factor family. AGL6, an ancient subfamily of MADS-box, interacts with all classes of MADS-box proteins in the ABCDE model in controlling floral organ development with dosage-dependent effect. Interestingly, it targets TaAPETALA3 (AP3) to regulate stamen development (designated as Pathway 11, Figure 3D) [60,99]. LFY not only regulates SNS but also plays a role in the development of floral organs. In the lfy mutant, except for glumes and lemmas, the paleas, lodicules, stamens, and pistils exhibit abnormal structures or numbers compared to the wild type. The expression patterns suggest that LFY directly or indirectly targets MADS-box class-B, class-C, and class-E genes to regulate floral organ identity (Pathway 3, Figure 3D) [81]. Additionally, miR172 targets two AP2-like transcription factors, Q (AP2L5) and AP2L2, in specifying floral meristem development and lemma identity (designated as Pathway 12, Figure 3D) [100].
In summary, we have summarized eight pathways (Pathway 1–Pathway 8) regulating spikelet development and seven pathways (Pathway 3, 5, 8, 9, 10, 11, and 12) regulating floret development. From the regulatory networks outlined above, some modules involved in spikelet development also play a role in floret development, such as the LFY modules in Pathway 3, the miR156-SPL13 module in Pathway 5, and the WFZP-MYB30 module in Pathway 8 (Figure 3). There is still limited research on the genes and genetic regulatory networks involved in wheat floret development, and this area should be further explored in future studies.

5. Perspective

5.1. Wheat Gene Cloning Is Becoming Easier

Optimizing the genetic basis of spike traits in cereal crops can significantly enhance crop yields through molecular design breeding. In recent years, the steady improvement in grain crop yields in China has been driven by the ongoing advancement of fundamental research and breeding technologies [101]. This progress has paralleled the evolution of breeding technologies, transitioning from early domestication and selection to conventional breeding, molecular breeding, and, more recently, molecular design breeding. Consequently, dissecting key genes and their regulatory networks for vital agronomic traits in cereal crops plays an essential role in driving the transformation of breeding technologies.
Over the past two decades, the identification of genes related to wheat yield traits has primarily been achieved through the functional analysis of homologous genes, as well as the classical strategy of positional cloning by mining EMS-induced mutants or natural germplasm for functional genes. Recent advances in available reference sequences, large-scale functional genomics research, diverse mutant pools, and gene mapping pipelines have accelerated the discovery of wheat genes, especially those controlling spike architecture [1,2,5,7,8,10]. Interactive web servers such as the wheat integrative gene regulatory network (wGRN) (http://wheat.cau.edu.cn/wGRN, accessed on 5 March 2025) and wheat spike multi-omic database (http://39.98.48.156:8800/#/, accessed on 5 March 2025) were constructed for the community to explore the genes controlling spike traits [83,102,103]. Robust gene capture approaches such as mutagenesis with resistance gene enrichment sequencing (MutRenSeq), quantitative trait gene sequencing (QTG-Seq), MutIsoSeq, and uni-BSA have been developed to identify and characterize R genes and developmental QTLs [7,9,10,104]. Importantly, the integration of single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics has provided powerful tools to dissect the cellular and molecular complexity of crop IM development at unprecedented resolution, uncovering novel marker genes and regulatory circuits specific to determinacy, branching, and floral organ initiation [105,106,107]. This study will offer valuable resources and powerful strategies for unraveling the intricacies of wheat complex spike traits and make gene cloning easier.

5.2. Improving Wheat Yield Through Spike Traits: Remaining Challenges

In wheat, grain yield is determined by three main components, and improving any of these traits can significantly enhance yield [17]. Although key genes controlling spike-yield traits have been cloned, few genes have been applied in wheat breeding. The reasons may include the following: (1) Trade-off between spike size and tiller number: Over the past years, the remarkable increase in wheat yield in China has been predominantly attributed to a rise in grains per spike, which is closely associated with the breeding of large-spike cultivars [108]. However, many of these high-yielding, large-spike varieties exhibit a reduced tillering capacity, indicating a trade-off between spike size and spike number per unit area. This antagonistic relationship poses a major constraint on further yield improvement. Therefore, it is important to identify and characterize genes and molecular pathways that specifically regulate spike architecture and tiller development [109,110,111]. (2) Complexity of wheat spike-yield traits and gene regulation network: From the formation of inflorescence meristems and differentiation of spikelet primordia to the formation of terminal spikelets, each developmental stage is closely related to spike shape, therefore spike yield traits are usually determined by the interaction of multiple genes, the effects of a single gene may be obscured by other genes, which limits their application in breeding. (3) Complexity of genotype-by-environment interactions: Wheat is a globally cultivated crop, and high-yielding varieties of the same genotype may exhibit poor performance in different environmental conditions, highlighting the importance of considering genotype-by-environment interactions. Environmental factors encompass both biotic and abiotic components, as well as regional variations and fluctuating climatic conditions. Consequently, the manipulation of individual functional genes is challenging, as it may not effectively adapt to diverse growing regions or respond to variable environmental stresses.

5.3. Future Directions in Wheat Spike Trait Research

The future research on cloning related genes and molecular mechanisms of wheat spike traits can be summarized in three points: 1. Fine-tuning gene expression via genome editing to enhance crop yield: As crop yield is a polygenic and environmentally sensitive trait, the precise and context-dependent control of gene expression opens new avenues for molecular breeding, fine-tuning the expression of key agronomic genes through promoter replacement, cis-regulatory element editing, UTR engineering using CRISPR/Cas system will offers a powerful approach to balance complex traits such as yield, stress tolerance, and developmental timing. 2. Deepening our understanding of gene regulatory networks in wheat spike development and their conservation across cereal crops: The complex gene regulatory networks involved in the meristem transition of the wheat spike remain incompletely understood. Further research in this area could enhance our understanding of the parallel domestication of cereal crop inflorescences, shedding light on how these mechanisms are conserved or vary across species. 3. Exploring environmental interactions: The transition of wheat inflorescences is sensitive to temperature and photoperiod. Investigating how wheat perceives and responds to these environmental signals at the molecular level can aid in developing crops better suited to thrive under changing environmental conditions, such as those driven by climate change. This is particularly important in the context of global climate change, where temperature shifts and other environmental changes pose significant challenges to crop production.

5.4. Enhancing Wheat Yield: Via Genetics and Agronomy

As noted in Section 5.2, there remain significant challenges in improving wheat yield solely through optimizing spike architecture or relying only on genetic improvement. Therefore, it is necessary to effectively enhance wheat yield by combining the improvement of genetic potential with advances in agronomic practices. For example: (1) In terms of enhancing genetic potential, given the complexity of gene regulatory networks, efficient gene editing systems can be employed to knock out or knock in multiple molecular modules, aiming to improve several breeding traits simultaneously. For instance, editing genes that control both spike architecture and tillering could help reduce the trade-off between spike size and tiller number [112,113,114]. (2) The right variety with the right practices, considering genotype-environment interactions: Strategies such as optimizing planting density are important. In addition to breeding wheat varieties with large spikes and high tillering capacity, optimal planting density can ensure an adequate number of effective spikes per unit area and promote efficient photosynthesis [115,116,117]. Another example is the rational use of photoperiod sensitivity. When introducing wheat varieties between northern and southern regions, besides ensuring timely flowering and grain setting, autumn sowing of spring wheat varieties with strong frost resistance can have a positive impact on yield, which is meaningful in the context of climate change [118,119,120].

Supplementary Materials

The following supporting information can be downloaded at https://www.mdpi.com/article/10.3390/agriculture15151575/s1, Table S1: All the spike traits related QTLs collected in this paper; Table S2: All the spike traits related genes collected in this paper.

Author Contributions

Writing—original draft preparation, Y.D.; writing—review and editing, Z.J., X.L., S.W., F.Y. and Y.D. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported in part by the National Natural Science Foundation of China (32201840), the Natural Science Foundation of Shandong Province (ZR2022QC048), and the funding of Shandong Province Higher Education Young Innovation Team Development Program (2023KJ339).

Institutional Review Board Statement

Not applicable.

Data Availability Statement

Not applicable.

Conflicts of Interest

All the authors declare that they have no known competing financial interests or personal relationships.

Abbreviations

The following abbreviations are used in this manuscript:
SAMShoot Apical Meristem
IMInflorescence Meristem
SMSpikelet Meristem
TSTerminal Spikelets
SRSingle Ridge
DRDouble Ridge
SLSpike Length
SCSpikelet Compactness
SNSTotal Spikelet Number Per Spike
GNSGrain Number Per Spike
SSSupernumerary Spikelets

References

  1. International Wheat Genome Sequencing Consortium (IWGSC). Shifting the limits in wheat research and breeding using a fully annotated reference genome. Science 2018, 361, eaar7191. [Google Scholar] [CrossRef] [PubMed]
  2. Jia, J.; Zhao, G.; Li, D.; Wang, K.; Kong, C.; Deng, P.; Yan, X.; Zhang, X.; Lu, Z.; Xu, S.; et al. Genome resources for the elite bread wheat cultivar Aikang 58 and mining of elite homeologous haplotypes for accelerating wheat improvement. Mol. Plant 2023, 16, 1893–1910. [Google Scholar] [CrossRef] [PubMed]
  3. Jiao, C.; Xie, X.; Hao, C.; Chen, L.; Xie, Y.; Garg, V.; Zhao, L.; Wang, Z.; Zhang, Y.; Li, T.; et al. Pan-genome bridges wheat structural variations with habitat and breeding. Nature 2024, 637, 384–393. [Google Scholar] [CrossRef]
  4. International Wheat Genome Sequencing Consortium (IWGSC). A chromosome-based draft sequence of the hexaploid bread wheat (Triticum aestivum) genome. Science 2014, 345, 1251788. [Google Scholar] [CrossRef]
  5. Shi, X.; Cui, F.; Han, X.; He, Y.; Zhao, L.; Zhang, N.; Zhang, H.; Zhu, H.; Liu, Z.; Ma, B.; et al. Comparative genomic and transcriptomic analyses uncover the molecular basis of high nitrogen-use efficiency in the wheat cultivar Kenong 9204. Mol. Plant 2022, 15, 1440–1456. [Google Scholar] [CrossRef]
  6. Sato, K.; Abe, F.; Mascher, M.; Haberer, G.; Gundlach, H.; Spannagl, M.; Shirasawa, K.; Isobe, S. Chromosome-scale genome assembly of the transformation-amenable common wheat cultivar ‘Fielder’. DNA Res. 2021, 28, dsab008. [Google Scholar] [CrossRef]
  7. Steuernagel, B.; Periyannan, S.K.; Hernández-Pinzón, I.; Witek, K.; Rouse, M.N.; Yu, G.; Hatta, A.; Ayliffe, M.; Bariana, H.; Jones, J.D.; et al. Rapid cloning of disease-resistance genes in plants using mutagenesis and sequence capture. Nat. Biotechnol. 2016, 34, 652–655. [Google Scholar] [CrossRef]
  8. Wang, D.; Li, Y.; Wang, H.; Xu, Y.; Yang, Y.; Zhou, Y.; Chen, Z.; Zhou, Y.; Gui, L.; Guo, Y.; et al. Boosting wheat functional genomics via an indexed EMS mutant library of KN9204. Plant Commun. 2023, 4, 100593. [Google Scholar] [CrossRef]
  9. Yuan, Y.; Lyu, B.; Qi, J.; Liu, X.; Wang, Y.; Delaplace, P.; Du, Y. A novel regulator of wheat tillering LT1 identified by using an upgraded BSA method, uni-BSA. Mol. Breed. 2024, 44, 47. [Google Scholar] [CrossRef]
  10. Zhang, H.; Wang, X.; Pan, Q.; Li, P.; Liu, Y.; Lu, X.; Zhong, W.; Li, M.; Han, L.; Li, J.; et al. QTG-Seq Accelerates QTL Fine Mapping through QTL Partitioning and Whole-Genome Sequencing of Bulked Segregant Samples. Mol. Plant 2019, 12, 426–437. [Google Scholar] [CrossRef]
  11. Liu, X.; Bie, X.M.; Lin, X.; Li, M.; Wang, H.; Zhang, X.; Yang, Y.; Zhang, C.; Zhang, X.S.; Xiao, J. Uncovering the transcriptional regulatory network involved in boosting wheat regeneration and transformation. Nat. Plants 2023, 9, 908–925. [Google Scholar] [CrossRef]
  12. Wang, K.; Riaz, B.; Ye, X. Wheat genome editing expedited by efficient transformation techniques: Progress and perspectives. Crop J. 2018, 6, 22–31. [Google Scholar] [CrossRef]
  13. Wang, K.; Shi, L.; Liang, X.; Zhao, P.; Wang, W.; Liu, J.; Chang, Y.; Hiei, Y.; Yanagihara, C.; Du, L.; et al. The gene TaWOX5 overcomes genotype dependency in wheat genetic transformation. Nat. Plants 2022, 8, 110–117. [Google Scholar] [CrossRef]
  14. Krasileva, K.V.; Vasquez-Gross, H.A.; Howell, T.; Bailey, P.; Paraiso, F.; Clissold, L.; Simmonds, J.; Ramirez-Gonzalez, R.H.; Wang, X.; Borrill, P.; et al. Uncovering hidden variation in polyploid wheat. Proc. Natl. Acad. Sci. USA 2017, 114, 913–921. [Google Scholar] [CrossRef]
  15. Song, L.; Liu, J.; Cao, B.; Liu, B.; Zhang, X.; Chen, Z.; Dong, C.; Liu, X.; Zhang, Z.; Wang, W.; et al. Reducing brassinosteroid signalling enhances grain yield in semi-dwarf wheat. Nature 2023, 617, 118–124. [Google Scholar] [CrossRef] [PubMed]
  16. Zhang, X.; Jia, H.; Li, T.; Wu, J.; Nagarajan, R.; Lei, L.; Powers, C.; Kan, C.C.; Hua, W.; Liu, Z.; et al. TaCol-B5 modifies spike architecture and enhances grain yield in wheat. Science 2022, 376, 180–183. [Google Scholar] [CrossRef] [PubMed]
  17. Cao, S.; Xu, D.; Hanif, M.; Xia, X.; He, Z. Genetic architecture underpinning yield component traits in wheat. Theor. Appl. Genet. 2020, 133, 1811–1823. [Google Scholar] [CrossRef] [PubMed]
  18. Luo, X.; Yang, Y.; Lin, X.; Xiao, J. Deciphering spike architecture formation towards yield improvement in wheat. J. Genet. Genom. 2023, 50, 835–845. [Google Scholar] [CrossRef]
  19. Shaheen, A.; Li, Z.; Yang, Y.; Xie, J.; Zhu, L.; Li, C.; Nie, F.; Wang, M.; Rasheed, A.; Li, H.; et al. Genetic regulation of wheat plant architecture and future prospects for its improvement. New Crops 2025, 2, 100048. [Google Scholar] [CrossRef]
  20. Xiao, J.; Liu, B.; Yao, Y.; Guo, Z.; Jia, H.; Kong, L.; Zhang, A.; Ma, W.; Ni, Z.; Xu, S.; et al. Wheat genomic study for genetic improvement of traits in China. Sci. China Life Sci. 2022, 65, 1718–1775. [Google Scholar] [CrossRef]
  21. Yao, Y.; Guo, W.; Gou, J.; Hu, Z.; Liu, J.; Ma, J.; Zong, Y.; Xin, M.; Chen, W.; Li, Q.; et al. Wheat2035: Integrating Pan-omics and Advanced Biotechnology for Future Wheat Design. Mol. Plant 2025, 18, 272–297. [Google Scholar] [CrossRef]
  22. Bommert, P.; Satoh-Nagasawa, N.; Jackson, D.; Hirano, H.Y. Genetics and evolution of inflorescence and flower development in grasses. Plant Cell Physiol. 2005, 46, 69–78. [Google Scholar] [CrossRef]
  23. Gauley, A.; Boden, S.A. Genetic pathways controlling inflorescence architecture and development in wheat and barley. J. Integr. Plant Biol. 2019, 61, 296–309. [Google Scholar] [CrossRef]
  24. Koppolu, R.; Schnurbusch, T. Developmental pathways for shaping spike inflorescence architecture in barley and wheat. J. Integr. Plant Biol. 2019, 61, 278–295. [Google Scholar] [CrossRef]
  25. Gao, X.Q.; Wang, N.; Wang, X.L.; Zhang, X.S. Architecture of Wheat Inflorescence: Insights from Rice. Trends Plant Sci. 2019, 24, 802–809. [Google Scholar] [CrossRef]
  26. Ikeda, K.; Sunohara, H.; Nagato, Y. Developmental Course of Inflorescence and Spikelet in Rice. Breed. Sci. 2004, 54, 147–156. [Google Scholar] [CrossRef]
  27. Vollbrecht, E.; Springer, P.S.; Goh, L.; Iv, E.S.B.; Martienssen, R. Architecture of floral branch systems in maize and related grasses. Nature 2005, 436, 1119–1126. [Google Scholar] [CrossRef]
  28. Guo, Z.; Zhao, Y.; Röder, M.S.; Reif, J.C.; Ganal, M.W.; Chen, D.; Schnurbusch, T. Manipulation and prediction of spike morphology traits for the improvement of grain yield in wheat. Sci. Rep. 2018, 8, 14435. [Google Scholar] [CrossRef] [PubMed]
  29. Hu, W.; Wu, H.; Lu, C.; Zheng, X.; Jia, J.; Xu, W. Genetic dissection of quantitative trait loci for spikelets compactness in two Yanzhan1-derived recombinant inbred line wheat populations. Plant Breed. 2022, 141, 719–732. [Google Scholar] [CrossRef]
  30. Li, T.; Deng, G.; Su, Y.; Yang, Z.; Tang, Y.; Wang, J.; Qiu, X.; Pu, X.; Li, J.; Liu, Z.; et al. Identification and validation of two major QTLs for spike compactness and length in bread wheat (Triticum aestivum L.) showing pleiotropic effects on yield-related traits. Theor. Appl. Genet. 2021, 134, 3625–3641. [Google Scholar] [CrossRef]
  31. You, J.; Liu, H.; Wang, S.; Luo, W.; Gou, L.; Tang, H.; Mu, Y.; Deng, M.; Jiang, Q.; Chen, G.; et al. Spike Density Quantitative Trait Loci Detection and Analysis in Tetraploid and Hexaploid Wheat Recombinant Inbred Line Populations. Front. Plant Sci. 2021, 12, 796397. [Google Scholar] [CrossRef]
  32. Chai, L.; Chen, Z.; Bian, R.; Zhai, H.; Cheng, X.; Peng, H.; Yao, Y.; Hu, Z.; Xin, M.; Guo, W.; et al. Dissection of two quantitative trait loci with pleiotropic effects on plant height and spike length linked in coupling phase on the short arm of chromosome 2D of common wheat (Triticum aestivum L.). Theor. Appl. Genet. 2019, 132, 1815–1831. [Google Scholar] [CrossRef]
  33. Heidari, B.; Sayed-Tabatabaei, B.E.; Saeidi, G.; Kearsey, M.; Suenaga, K. Mapping QTL for grain yield, yield components, and spike features in a doubled haploid population of bread wheat. Genome 2011, 54, 517–527. [Google Scholar] [CrossRef] [PubMed]
  34. Kumar, N.; Kulwal, P.L.; Balyan, H.S.; Gupta, P.K. QTL mapping for yield and yield contributing traits in two mapping populations of bread wheat. Mol. Breed. 2007, 19, 163–177. [Google Scholar] [CrossRef]
  35. Li, Y.; Gao, J.; Zhang, R.; Song, G.; Zhang, S.; Li, W.; Li, G. Identification of new QTL for yield-related traits in Chinese landrace and elite wheat varieties through a genome-wide linkage mapping. Euphytica 2020, 216. [Google Scholar] [CrossRef]
  36. Liu, Y.; Yu, R.; Shen, L.; Sun, M.; Peng, Y.; Zeng, Q.; Shen, K.; Yu, X.; Wu, H.; Ye, B.; et al. Genomic insights into the modifications of spike morphology traits during wheat breeding. Plant Cell Environ. 2024, 47, 5470–5482. [Google Scholar] [CrossRef]
  37. Sourdille, P.; Cadalen, T.; Guyomarc’h, H.; Snape, J.W.; Perretant, M.R.; Charmet, G.; Boeuf, C.; Bernard, S.; Bernard, M. An update of the Courtot x Chinese Spring intervarietal molecular marker linkage map for the QTL detection of agronomic traits in wheat. Theor. Appl. Genet. 2003, 106, 530–538. [Google Scholar] [CrossRef]
  38. Wu, X.; Cheng, R.; Xue, S.; Kong, Z.; Wan, H.; Li, G.; Huang, Y.; Jia, H.; Jia, J.; Zhang, L.; et al. Precise mapping of a quantitative trait locus interval for spike length and grain weight in bread wheat (Triticum aestivum L.). Mol. Breed. 2014, 33, 129–138. [Google Scholar] [CrossRef]
  39. Xu, X.; Li, X.; Zhang, D.; Zhao, J.; Jiang, X.; Sun, H.; Ru, Z. Identification and validation of QTLs for kernel number per spike and spike length in two founder genotypes of wheat. BMC Plant Biol. 2022, 22, 146. [Google Scholar] [CrossRef]
  40. Xiong, H.; Zhou, C.; Fu, M.; Guo, H.; Xie, Y.; Zhao, L.; Gu, J.; Zhao, S.; Ding, Y.; Li, Y.; et al. Cloning and functional characterization of Rht8, a “Green Revolution” replacement gene in wheat. Mol. Plant 2022, 15, 373–376. [Google Scholar] [CrossRef]
  41. Kong, X.; Wang, F.; Wang, Z.; Gao, X.; Geng, S.; Deng, Z.; Zhang, S.; Fu, M.; Cui, D.; Liu, S.; et al. Grain yield improvement by genome editing of TaARF12 that decoupled peduncle and rachis development trajectories via differential regulation of gibberellin signalling in wheat. Plant Biotechnol. J. 2023, 21, 1990–2001. [Google Scholar] [CrossRef]
  42. He, G.; Zhang, Y.; Liu, P.; Jing, Y.; Zhang, L.; Zhu, Y.; Kong, X.; Zhao, H.; Zhou, Y.; Sun, J. The transcription factor TaLAX1 interacts with Q to antagonistically regulate grain threshability and spike morphogenesis in bread wheat. New Phytol. 2021, 230, 988–1002. [Google Scholar] [CrossRef]
  43. Zhu, J.; Huang, F.; Zhai, H.; Zheng, Y.; Yu, J.; Chen, Z.; Fan, Y.; Zhao, H.; Sun, Q.; Liang, R.; et al. The Tetratricopeptide repeat protein TaTPR-B1 regulates spike compactness in bread wheat. Plant Physiol. 2024, 197, kiae546. [Google Scholar] [CrossRef]
  44. Yan, L.; Loukoianov, A.; Tranquilli, G.; Helguera, M.; Fahima, T.; Dubcovsky, J. Positional cloning of the wheat vernalization gene VRN1. Proc. Natl. Acad. Sci. USA 2003, 100, 6263–6268. [Google Scholar] [CrossRef]
  45. Yan, L.; Loukoianov, A.; Blechl, A.; Tranquilli, G.; Ramakrishna, W.; SanMiguel, P.; Bennetzen, J.L.; Echenique, V.; Dubcovsky, J. The wheat VRN2 gene is a flowering repressor down-regulated by vernalization. Science 2004, 303, 1640–1644. [Google Scholar] [CrossRef] [PubMed]
  46. Glenn, P.; Zhang, J.; Brown-Guedira, G.; DeWitt, N.; Cook, J.P.; Li, K.; Akhunov, E.; Dubcovsky, J. Identification and characterization of a natural polymorphism in FT-A2 associated with increased number of grains per spike in wheat. Theor. Appl. Genet. 2022, 135, 679–692. [Google Scholar] [CrossRef] [PubMed]
  47. Su, L.; Shan, J.X.; Gao, J.P.; Lin, H.X. OsHAL3, a Blue Light-Responsive Protein, Interacts with the Floral Regulator Hd1 to Activate Flowering in Rice. Mol. Plant 2016, 9, 233–244. [Google Scholar] [CrossRef] [PubMed]
  48. Wang, J.; Wen, W.; Hanif, M.; Xia, X.; Wang, H.; Liu, S.; Liu, J.; Yang, L.; Gao, S.; He, Z. TaELF3-1DL, a homolog of ELF3, is associated with heading date in bread wheat. Mol. Breed. 2016, 36, 161. [Google Scholar] [CrossRef]
  49. Zikhali, M.; Wingen, L.U.; Leverington-Waite, M.; Specel, S.; Griffiths, S. The identification of new candidate genes triticum aestivum flowering locus T3-B1 (TAFT3-B1) and target of EAT1 (TATOE1-B1) controlling the short-day photoperiod response in bread wheat. Plant Cell Environ. 2017, 40, 2678–2690. [Google Scholar] [CrossRef]
  50. Corsi, B.; Obinu, L.; Zanella, C.M.; Cutrupi, S.; Day, R.; Geyer, M.; Lillemo, M.; Lin, M.; Mazza, L.; Percival-Alwyn, L.; et al. Identification of eight QTL controlling multiple yield components in a German multi-parental wheat population, including Rht24, WAPO-A1, WAPO-B1 and genetic loci on chromosomes 5A and 6A. Theor. Appl. Genet. 2021, 134, 1435–1454. [Google Scholar] [CrossRef]
  51. Dobrovolskaya, O.; Pont, C.; Sibout, R.; Martinek, P.; Badaeva, E.; Murat, F.; Chosson, A.; Watanabe, N.; Prat, E.; Gautier, N.; et al. Frizzy panicle drives supernumerary spikelets in bread wheat. Plant Physiol. 2015, 167, 189–199. [Google Scholar] [CrossRef]
  52. Du, D.; Zhang, D.; Yuan, J.; Feng, M.; Li, Z.; Wang, Z.; Zhang, Z.; Li, X.; Ke, W.; Li, R.; et al. FRIZZY PANICLE defines a regulatory hub for simultaneously controlling spikelet formation and awn elongation in bread wheat. New Phytol. 2021, 231, 814–833. [Google Scholar] [CrossRef]
  53. Kuzay, S.; Lin, H.; Li, C.; Chen, S.; Woods, D.P.; Zhang, J.; Lan, T.; von Korff, M.; Dubcovsky, J. WAPO-A1 is the causal gene of the 7AL QTL for spikelet number per spike in wheat. PLoS Genet. 2022, 18, e1009747. [Google Scholar] [CrossRef] [PubMed]
  54. Li, Y.; Li, L.; Zhao, M.; Guo, L.; Guo, X.; Zhao, D.; Batool, A.; Dong, B.; Xu, H.; Cui, S.; et al. Wheat FRIZZY PANICLE activates VERNALIZATION1-A and HOMEOBOX4-A to regulate spike development in wheat. Plant Biotechnol. J. 2021, 19, 1141–1154. [Google Scholar] [CrossRef] [PubMed]
  55. Liu, Y.; Chen, J.; Yin, C.; Wang, Z.; Wu, H.; Shen, K.; Zhang, Z.; Kang, L.; Xu, S.; Bi, A.; et al. A high-resolution genotype–phenotype map identifies the TaSPL17 controlling grain number and size in wheat. Genome Biol. 2023, 24, 196. [Google Scholar] [CrossRef] [PubMed]
  56. Wittern, L.M.; Barrero, J.M.; Bovill, W.D.; Verbyla, K.L.; Hughes, T.; Swain, S.M.; Steed, G.; Webb, A.A.R.; Gardner, K.; Greenland, A.; et al. Overexpression of the WAPO-A1 gene increases the number of spikelets per spike in bread wheat. Sci. Rep. 2022, 12, 14229. [Google Scholar] [CrossRef]
  57. Chen, D.; Zhang, J.; Wang, J.; Yang, X.; Liu, W.; Gao, A.; Li, X.; Li, L. Inheritance and Availability of High Grain Number Per Spike in Two Wheat Germplasm Lines. J. Integr. Agric. 2012, 12, 1409–1416. [Google Scholar] [CrossRef]
  58. Fernandes, R.; Busanello, C.; Viana, V.; Venske, E.; de Oliveira, V.; Lopes, J.; da Maia, L.; Costa de Oliveira, A.; Pegoraro, C. Genetic variability and heritability of agronomic traits in a wheat collection used in southern Brazil. J. Crop Sci. Biotechnol. 2022, 25, 337–348. [Google Scholar] [CrossRef]
  59. Sakuma, S.; Golan, G.; Guo, Z.; Ogawa, T.; Tagiri, A.; Sugimoto, K.; Bernhardt, N.; Brassac, J.; Mascher, M.; Hensel, G.; et al. Unleashing floret fertility in wheat through the mutation of a homeobox gene. Proc. Natl. Acad. Sci. USA 2019, 116, 5182–5187. [Google Scholar] [CrossRef]
  60. Kong, X.; Wang, F.; Geng, S.; Guan, J.; Tao, S.; Jia, M.; Sun, G.; Wang, Z.; Wang, K.; Ye, X.; et al. The wheat AGL6-like MADS-box gene is a master regulator for floral organ identity and a target for spikelet meristem development manipulation. Plant Biotechnol. J. 2022, 20, 75–88. [Google Scholar] [CrossRef]
  61. Pearce, S.; Shaw, L.M.; Lin, H.; Cotter, J.D.; Li, C.; Dubcovsky, J. Night-break experiments shed light on the photoperiod1-mediated flowering. Plant Physiol. 2017, 174, 1139–1150. [Google Scholar] [CrossRef]
  62. Ream, T.S.; Woods, D.P.; Amasino, R.M. The molecular basis of vernalization in different plant groups. Cold Spring Harb. Symp. Quant. Biol. 2012, 77, 105–115. [Google Scholar] [CrossRef]
  63. Chouard, P. Vernalization and Its Relation to Dormancy. Annu. Rev. Plant Physiol. 1960, 11, 191–238. [Google Scholar] [CrossRef]
  64. Corbesier, L.; Vincent, C.; Jang, S.; Fornara, F.; Fan, Q.; Searle, I.; Giakountis, A.; Farrona, S.; Gissot, L.; Turnbull, C.; et al. FT protein movement contributes to long-distance signaling in floral induction of Arabidopsis. Science 2007, 316, 1030–1033. [Google Scholar] [CrossRef] [PubMed]
  65. Yan, L.; Fu, D.; Li, C.; Blechl, A.; Tranquilli, G.; Bonafede, M.; Sanchez, A.; Valarik, M.; Yasuda, S.; Dubcovsky, J. The wheat and barley vernalization gene VRN3 is an orthologue of FT. Proc. Natl. Acad. Sci. USA 2006, 103, 19581–19586. [Google Scholar] [CrossRef] [PubMed]
  66. Gauley, A.; Pasquariello, M.; Yoshikawa, G.V.; Alabdullah, A.K.; Hayta, S.; Smedley, M.A.; Dixon, L.E.; Boden, S.A. Photoperiod-1 regulates the wheat inflorescence transcriptome to influence spikelet architecture and flowering time. Curr. Biol. 2024, 34, 2330–2343. [Google Scholar] [CrossRef]
  67. Alvarez, M.A.; Li, C.; Lin, H.; Joe, A.; Padilla, M.; Woods, D.P.; Dubcovsky, J. EARLY FLOWERING 3 interactions with PHYTOCHROME B and PHOTOPERIOD1 are critical for the photoperiodic regulation of wheat heading time. PLoS Genet. 2023, 19, e1010655. [Google Scholar] [CrossRef]
  68. Chen, A.; Li, C.; Hu, W.; Lau, M.Y.; Lin, H.; Rockwell, N.C.; Martin, S.S.; Jernstedt, J.A.; Lagarias, J.C.; Dubcovsky, J. PHYTOCHROME C plays a major role in the acceleration of wheat flowering under long-day photoperiod. Proc. Natl. Acad. Sci. USA 2014, 111, 10037–10044. [Google Scholar] [CrossRef]
  69. Kippes, N.; VanGessel, C.; Hamilton, J.; Akpinar, A.; Budak, H.; Dubcovsky, J.; Pearce, S. Effect of phyB and phyC loss-of-function mutations on the wheat transcriptome under short and long day photoperiods. BMC Plant Biol. 2020, 20, 297. [Google Scholar] [CrossRef]
  70. Pearce, S.; Kippes, N.; Chen, A.; Debernardi, J.M.; Dubcovsky, J. RNA-seq studies using wheat PHYTOCHROME B and PHYTOCHROME C mutants reveal shared and specific functions in the regulation of flowering and shade-avoidance pathways. BMC Plant Biol. 2016, 16, 141. [Google Scholar] [CrossRef]
  71. Distelfeld, A.; Li, C.; Dubcovsky, J. Regulation of flowering in temperate cereals. Curr. Opin. Plant Biol. 2009, 12, 178–184. [Google Scholar] [CrossRef]
  72. Greenup, A.; Peacock, W.J.; Dennis, E.S.; Trevaskis, B. The molecular biology of seasonal flowering-responses in Arabidopsis and the cereals. Ann. Bot. 2009, 103, 1165–1172. [Google Scholar] [CrossRef]
  73. Xie, L.; Zhang, Y.; Wang, K.; Luo, X.; Xu, D.; Tian, X.; Li, L.; Ye, X.; Xia, X.; Li, W.; et al. TaVrt2, an SVP-like gene, cooperates with TaVrn1 to regulate vernalization-induced flowering in wheat. New Phytol. 2021, 23, 834–848. [Google Scholar] [CrossRef] [PubMed]
  74. Luo, X.; Liu, B.; Xie, L.; Wang, K.; Xu, D.; Tian, X.; Xie, L.; Li, L.; Ye, X.; He, Z.; et al. The TaSOC1-TaVRN1 module integrates photoperiod and vernalization signals to regulate wheat flowering. Plant Biotechnol. J. 2024, 22, 635–649. [Google Scholar] [CrossRef] [PubMed]
  75. Dixon, L.E.; Greenwood, J.R.; Bencivenga, S.; Zhang, P.; Cockram, J.; Mellers, G.; Ramm, K.; Cavanagh, C.; Swain, S.M.; Boden, S.A. TEOSINTE BRANCHED1 regulates inflorescence architecture and development in bread wheat (Triticum aestivum). Plant Cell 2018, 30, 563–581. [Google Scholar] [CrossRef] [PubMed]
  76. Shaw, L.M.; Lyu, B.; Turner, R.; Li, C.; Chen, F.; Han, X.; Fu, D.; Dubcovsky, J. FLOWERING LOCUS T2 regulates spike development and fertility in temperate cereals. J. Exp. Bot. 2019, 70, 193–204. [Google Scholar] [CrossRef]
  77. Li, C.; Lin, H.; Chen, A.; Lau, M.; Jernstedt, J.; Dubcovsky, J. Wheat VRN1, FUL2 and FUL3 play critical and redundant roles in spikelet development and spike determinacy. Development 2019, 146, dev175398. [Google Scholar] [CrossRef]
  78. Kobayashi, K.; Yasuno, N.; Sato, Y.; Yoda, M.; Yamazaki, R.; Kimizu, M.; Yoshida, H.; Nagamura, Y.; Kyozuka, J. Inflorescence meristem identity in rice is specified by overlapping functions of three AP1/FUL-Like MADS box genes and PAP2, a SEPALLATA MADS Box gene. Plant Cell 2012, 24, 1848–1859. [Google Scholar] [CrossRef]
  79. Wu, F.; Shi, X.; Lin, X.; Liu, Y.; Chong, K.; Theißen, G.; Meng, Z. The ABCs of flower development: Mutational analysis of AP1/FUL-like genes in rice provides evidence for a homeotic (A)-function in grasses. Plant J. 2017, 89, 310–324. [Google Scholar] [CrossRef]
  80. Li, K.; Debernardi, J.M.; Li, C.; Lin, H.; Zhang, C.; Jernstedt, J.; Korff, M.V.; Zhong, J.; Dubcovsky, J. Interactions between SQUAMOSA and SHORT VEGETATIVE PHASE MADS-box proteins regulate meristem transitions during wheat spike development. Plant Cell 2021, 33, 3621–3644. [Google Scholar] [CrossRef]
  81. Paraiso, F.; Lin, H.; Li, C.; Woods, D.P.; Lan, T.; Tumelty, C.; Debernardi, J.M.; Joe, A.; Dubcovsky, J. LEAFY and WAPO1 jointly regulate spikelet number per spike and floret development in wheat. Development 2024, 151, dev202803. [Google Scholar] [CrossRef] [PubMed]
  82. Zhang, J.; Burguener, G.F.; Paraiso, F.; Dubcovsky, J. Natural alleles of LEAFY and WAPO1 interact to regulate spikelet number per spike in wheat. Theor. Appl. Genet. 2024, 137, 257. [Google Scholar] [CrossRef] [PubMed]
  83. Lin, X.; Xu, Y.; Wang, D.; Yang, Y.; Zhang, X.; Bie, X.; Gui, L.; Chen, Z.; Ding, Y.; Mao, L.; et al. Systematic identification of wheat spike developmental regulators by integrated multi-omics, transcriptional network, GWAS, and genetic analyses. Mol. Plant 2024, 17, 438–459. [Google Scholar] [CrossRef] [PubMed]
  84. Liu, J.; Cheng, X.; Liu, P.; Sun, J. miR156-targeted SBP-box transcription factors interact with DWARF53 to regulate teosinte branched1 and barren STALK1 expression in bread wheat. Plant Physiol. 2017, 174, 1931–1948. [Google Scholar] [CrossRef]
  85. Dixon, L.E.; Pasquariello, M.; Badgami, R.; Levin, K.A.; Poschet, G.; Ng, P.Q.; Orford, S.; Chayut, N.; Adamski, N.M.; Brinton, J.; et al. MicroRNA-resistant alleles of HOMEOBOX DOMAIN-2 modify inflorescence branching and increase grain protein content of wheat. Sci. Adv. 2022, 8, eabn5907. [Google Scholar] [CrossRef]
  86. Jiang, D.; Hua, L.; Zhang, C.; Li, H.; Wang, Z.; Li, J.; Wang, G.; Song, R.; Shen, T.; Li, H.; et al. Mutations in the miRNA165/166 binding site of the HB2 gene result in pleiotropic effects on morphological traits in wheat. Crop J. 2023, 11, 9–20. [Google Scholar] [CrossRef]
  87. Zhang, X.; Meng, W.; Liu, D.; Pan, D.; Yang, Y.; Chen, Z.; Ma, X.; Yin, W.; Niu, M.; Dong, N.; et al. Enhancing rice panicle branching and grain yield through tissue-specific brassinosteroid inhibition. Science 2024, 383, eadk8838. [Google Scholar] [CrossRef]
  88. Boden, S.A.; Cavanagh, C.; Cullis, B.R.; Ramm, K.; Greenwood, J.; Jean Finnegan, E.; Trevaskis, B.; Swain, S.M. Ppd-1 is a key regulator of inflorescence architecture and paired spikelet development in wheat. Nat. Plants 2015, 1, 14016. [Google Scholar] [CrossRef]
  89. Wang, Y.; Du, F.; Wang, J.; Wang, K.; Tian, C.; Qi, X.; Lu, F.; Liu, X.; Ye, X.; Jiao, Y. Improving bread wheat yield through modulating an unselected AP2/ERF gene. Nat. Plants 2022, 8, 930–939. [Google Scholar] [CrossRef]
  90. Clark, R.M.; Wagler, T.N.; Quijada, P.; Doebley, J. A distant upstream enhancer at the maize domestication gene tb1 has pleiotropic effects on plant and inflorescent architecture. Nat. Genet. 2006, 38, 594–597. [Google Scholar] [CrossRef]
  91. Studer, A.J.; Wang, H.; Doebley, J.F. Selection during maize domestication targeted a gene network controlling plant and inflorescence architecture. Genetics 2017, 207, 755–765. [Google Scholar] [CrossRef]
  92. Studer, A.; Zhao, Q.; Ross-Ibarra, J.; Doebley, J. Identification of a functional transposon insertion in the maize domestication gene tb1. Nat. Genet. 2011, 43, 1160–1163. [Google Scholar] [CrossRef]
  93. Studer, A.J.; Doebley, J.F. Evidence for a Natural Allelic Series at the Maize Domestication Locus teosinte branched1. Genetics 2012, 191, 951–958. [Google Scholar] [CrossRef]
  94. Chuck, G.; Muszynski, M.; Kellogg, E.; Hake, S.; Schmidt, R.J. The control of spikelet meristem identity by the branched silkless1 gene in maize. Science 2002, 298, 1238–1241. [Google Scholar] [CrossRef] [PubMed]
  95. Komatsu, M.; Chujo, A.; Nagato, Y.; Shimamoto, K.; Kyozuka, J. Frizzy panicle is required to prevent the formation of axillary meristems and to establish floral meristem identity in rice spikelets. Development 2003, 130, 3841–3850. [Google Scholar] [CrossRef] [PubMed]
  96. Li, L.; Shi, F.; Wang, Y.; Yu, X.; Zhi, J.; Guan, Y.; Zhao, H.; Chang, J.; Chen, M.; Yang, G.; et al. TaSPL13 regulates inflorescence architecture and development in transgenic wheat (Triticum aestivum L.). Plant Sci. 2020, 296, 110516. [Google Scholar] [CrossRef] [PubMed]
  97. Gupta, A.; Hua, L.; Zhang, Z.; Yang, B.; Li, W. CRISPR-induced miRNA156-recognition element mutations in TaSPL13 improve multiple agronomic traits in wheat. Plant Biotechnol. J. 2023, 21, 536–548. [Google Scholar] [CrossRef]
  98. Feng, N.; Song, G.; Guan, J.; Chen, K.; Jia, M.; Huang, D.; Wu, J.; Zhang, L.; Kong, X.; Geng, S.; et al. Transcriptome profiling of wheat inflorescence development from spikelet initiation to floral patterning identified stage-specific regulatory Genes. Plant Physiol. 2017, 174, 1779–1794. [Google Scholar] [CrossRef]
  99. Su, Y.; Liu, J.; Liang, W.; Dou, Y.; Fu, R.; Li, W.; Feng, C.; Gao, C.; Zhang, D.; Kang, Z.; et al. Wheat AGAMOUS like 6 transcription factors function in stamen development by regulating the expression of Ta APETALA3. Development 2019, 146, dev177527. [Google Scholar] [CrossRef]
  100. Debernardi, J.M.; Greenwood, J.R.; Jean Finnegan, E.; Jernstedt, J.; Dubcovsky, J. APETALA 2-like genes AP2L2 and Q specify lemma identity and axillary floral meristem development in wheat. Plant J. 2020, 101, 171–187. [Google Scholar] [CrossRef]
  101. Zuo, J.; Li, J. Molecular dissection of complex agronomic traits of rice: A team effort by Chinese scientists in recent years. Natl. Sci. Rev. 2014, 1, 253–276. [Google Scholar] [CrossRef]
  102. Ai, G.; He, C.; Bi, S.; Zhou, Z.; Liu, A.; Hu, X.; Liu, Y.; Jin, L.; Zhou, J.; Zhang, H.; et al. Dissecting the molecular basis of spike traits by integrating gene regulatory networks and genetic variation in wheat. Plant Commun. 2024, 5, 100879. [Google Scholar] [CrossRef]
  103. Chen, Y.; Guo, Y.; Guan, P.; Wang, Y.; Wang, X.; Wang, Z.; Qin, Z.; Ma, S.; Xin, M.; Hu, Z.; et al. A wheat integrative regulatory network from large-scale complementary functional datasets enables trait-associated gene discovery for crop improvement. Mol. Plant 2023, 16, 393–414. [Google Scholar] [CrossRef] [PubMed]
  104. Wang, Y.; Abrouk, M.; Gourdoupis, S.; Koo, D.H.; Karafiátová, M.; Molnár, I.; Holušová, K.; Doležel, J.; Athiyannan, N.; Cavalet-Giorsa, E.; et al. An unusual tandem kinase fusion protein confers leaf rust resistance in wheat. Nat. Genet. 2023, 55, 914–920. [Google Scholar] [CrossRef] [PubMed]
  105. Li, B.; Liu, W.; Xu, J.; Huang, X.; Yang, L.; Xu, F. Decoding maize meristems maintenance and differentiation: Integrating single-cell and spatial omics. J. Genet. Genom. 2025, 52, 319–333. [Google Scholar] [CrossRef]
  106. Wang, Y.; Luo, Y.; Guo, X.; Li, Y.; Yan, J.; Shao, W.; Wei, W.; Wei, X.; Yang, T.; Chen, J.; et al. A spatial transcriptome map of the developing maize ear. Nat. Plants 2024, 10, 815–827. [Google Scholar] [CrossRef]
  107. Xu, X.; Crow, M.; Rice, B.R.; Li, F.; Harris, B.; Liu, L.; Demesa-Arevalo, E.; Lu, Z.; Wang, L.; Fox, N.; et al. Single-cell RNA sequencing of developing maize ears facilitates functional analysis and trait candidate gene discovery. Dev. Cell 2021, 56, 557–568. [Google Scholar] [CrossRef]
  108. Qin, X.; Zhang, F.; Liu, C.; Yu, H.; Cao, B.; Tian, S.; Liao, Y.; Siddique, K. Wheat yield improvements in China: Past trends and future directions. Field Crops Res. 2015, 177, 117–124. [Google Scholar] [CrossRef]
  109. Jian, C.; Pan, Y.; Liu, S.; Guo, M.; Huang, Y.; Cao, L.; Zhang, W.; Yan, L.; Zhang, X.; Hou, J.; et al. The TaGW2-TaSPL14 module regulates the trade-off between tiller number and grain weight in wheat. J. Integr. Plant Biol. 2024, 66, 1953–1965. [Google Scholar] [CrossRef]
  110. Xie, Q.; Sparkes, D.L. Dissecting the trade-off of grain number and size in wheat. Planta 2021, 254, 3. [Google Scholar] [CrossRef]
  111. Vicentin, L.; Canales, J.; Calderini, D.F. The trade-off between grain weight and grain number in wheat is explained by the overlapping of the key phases determining these major yield components. Front. Plant Sci. 2024, 15, 1380429. [Google Scholar] [CrossRef]
  112. Cell Editorial Team. Five decades of genetics and genomics. Cell 2024, 187, 1017–1018. [Google Scholar] [CrossRef]
  113. Wei, W.; Gao, C. Gene editing: From technologies to applications in research and beyond. Sci. China Life Sci. 2022, 65, 657–659. [Google Scholar] [CrossRef]
  114. Pacesa, M.; Pelea, O.; Jinek, M. Past, present, and future of CRISPR genome editing technologies. Cell 2024, 187, 1076–1100. [Google Scholar] [CrossRef] [PubMed]
  115. Bastos, L.M.; Carciochi, W.; Lollato, R.P.; Jaenisch, B.R.; Rezende, C.R.; Schwalbert, R.; Vara Prasad, P.V.; Zhang, G.; Fritz, A.K.; Foster, C.; et al. Winter Wheat Yield Response to Plant Density as a Function of Yield Environment and Tillering Potential: A Review and Field Studies. Front. Plant Sci. 2020, 11, 00054. [Google Scholar] [CrossRef] [PubMed]
  116. Gao, Y.; Wang, Q.; Liu, Y.; He, J.; Chen, W.; Xing, J.; Sun, M.; Gao, Z.; Wang, Z.; Zhang, M.; et al. Optimal water, nitrogen, and density management increased wheat yield by improving population uniformity. Agric. Water Manag. 2025, 310, 109362. [Google Scholar] [CrossRef]
  117. Yang, D.; Cai, T.; Luo, Y.; Wang, Z. Optimizing plant density and nitrogen application to manipulate tiller growth and increase grain yield and nitrogen-use efficiency in winter wheat. PeerJ 2019, 7, e6484. [Google Scholar] [CrossRef]
  118. Wyzińska, M.; Grabiński, J. The influence of autumn sowing date on the productivity of spring wheat (Triticum aestivum L.). Res. Rural. Dev. 2018, 2, 35–41. [Google Scholar] [CrossRef]
  119. Wyzińska, M.; Grabiński, J. The productivity of spring wheat (Triticum aestivum L.) on the autumn sowing date. Curr. Agron. 2020, 42, 51–56. [Google Scholar]
  120. Wen, P.; Wei, Q.; Zheng, L.; Rui, Z.; Niu, M.; Gao, C.; Guan, X.; Wang, T.; Xiong, S. Adaptability of wheat to future climate change: Effects of sowing date and sowing rate on wheat yield in three wheat production regions in the North China Plain. Sci. Total Environ. 2023, 901, 165906. [Google Scholar] [CrossRef]
Agriculture 15 01575 g001
Figure 1. The development process of young spikes in hexaploid wheat. (A) The developmental process and structural features of young spikes in hexaploid wheat. The shoot apical meristem (SAM), inflorescence meristem (IM), and spikelet meristem (SM) are highlighted with yellow dashed lines. Leafy organs, such as bracts and GP (Glume primordium), are marked with pink dashed lines. Florets and terminal spikelets (TS) are indicated with green and blue dashed lines, respectively. (B) Comparison of inflorescence structures in wheat, rice, and maize. SR, Single ridge; DR, Double ridge; FM, Floret meristem; FO, Floret organ.
Figure 1. The development process of young spikes in hexaploid wheat. (A) The developmental process and structural features of young spikes in hexaploid wheat. The shoot apical meristem (SAM), inflorescence meristem (IM), and spikelet meristem (SM) are highlighted with yellow dashed lines. Leafy organs, such as bracts and GP (Glume primordium), are marked with pink dashed lines. Florets and terminal spikelets (TS) are indicated with green and blue dashed lines, respectively. (B) Comparison of inflorescence structures in wheat, rice, and maize. SR, Single ridge; DR, Double ridge; FM, Floret meristem; FO, Floret organ.
Agriculture 15 01575 g001
Agriculture 15 01575 g002
Figure 2. The genetic basis of wheat spike morphology. (A). The three key architectures of spike: the number of spikelets (SNS) (indicated by red asterisks), spike length (SL), and spikelet compactness (SC). Spikelet compactness is the ratio of the number of spikelets to SL. There are two typical spike types of hexaploid wheat, namely the loose spike and the compact spike. (B). Distribution of QTLs and genes controlling wheat GNS, SNS, SL, and SC.
Figure 2. The genetic basis of wheat spike morphology. (A). The three key architectures of spike: the number of spikelets (SNS) (indicated by red asterisks), spike length (SL), and spikelet compactness (SC). Spikelet compactness is the ratio of the number of spikelets to SL. There are two typical spike types of hexaploid wheat, namely the loose spike and the compact spike. (B). Distribution of QTLs and genes controlling wheat GNS, SNS, SL, and SC.
Agriculture 15 01575 g002
Agriculture 15 01575 g003
Figure 3. Regulatory network controlling wheat spike architecture. (A) Photoperiod and vernalization are the main factors controlling floral transition in wheat. Photoperiod and temperature signals reach FT through the PHYB/PHYC-ELF3-Ppd1 and VRN1-VRN2 modules, respectively. FT then moves from the leaves to the shoot apical meristem (SAM), where it forms a florigen activation complex with 14-3-3 and FDL, activating floral identity genes and promoting the transition to the inflorescence meristem (IM). Additionally, VRT2 and SOC1 regulate the SAM to IM transition by interacting with VRN1. (B) Eight core pathways (marked with circled Arabic numbers) regulate wheat spikelet development. Pathway 1, Pathway 2, and Pathway 3 involve wheat SQUAMOSA and SVP clade genes, controlling the transition from the inflorescence meristem (IM) to the terminal spikelet (TS) and spikelet meristem (SM). Accelerating the IM-TS transition reduces spikelet number, while delaying SM formation increases spikelet number. Pathway 4 and Pathway 5 involve Tak4 and TaColB5 phosphorylation and the miRNA156-SPL3/17 influence spikelet number, respectively. Pathway 6, Pathway 7, and Pathway 8 specifically regulate supernumerary spikelet formation. Ppd1 represses ALOG1 (OsG1L1 in rice) and promotes FT expression to facilitate supernumerary spikelet formation, indicating that photoperiod is important in supernumerary spikelet regulation. WFZP, homologous to rice FZP and maize BD1, suppresses supernumerary spikelet formation, as does the miRNA165/166-HB-2 degradation pathway. (C) The specific expression pattern of genes controlling wheat spikelet development. FUL2, FUL3, and HB-2 are expressed in the apical region of the spikelet meristem. VRT2, SVP1, and TaBA1 accumulate on the abaxial side, while TaSPL17 is expressed at the abaxial boundary. SOC1 is found in the central part, and WAPO1 and ALOG1 are in the distal part of the spikelet. LFY is expressed in the leafy region, and WFZP in the floret meristem. The specific gene expression regions are highlighted in different colors on a longitudinal section of a young wheat spike. (D) Seven pathways regulate floret development. Pathway 5, Pathway 8, Pathway 9, and Pathway 10 control floret number per spikelet, with Pathway 5 and Pathway 8 linked to the miRNA156-SPL13 and WFZP-MYB30 module, partially overlapping with spikelet development. Pathway 9 involved in GNI1 promotes fertile florets, and Pathway 10 is for the unclear role of hormones in regulating floret number. Pathway 3, Pathway 11, and Pathway 12 regulate floret organ identity. AGL6 promotes AP3 for stamen identity, and AGL6 and LFY regulate other BCDE class genes in floret organ identity, while miRNA172-Q/AP2L2 controls lemma identity.
Figure 3. Regulatory network controlling wheat spike architecture. (A) Photoperiod and vernalization are the main factors controlling floral transition in wheat. Photoperiod and temperature signals reach FT through the PHYB/PHYC-ELF3-Ppd1 and VRN1-VRN2 modules, respectively. FT then moves from the leaves to the shoot apical meristem (SAM), where it forms a florigen activation complex with 14-3-3 and FDL, activating floral identity genes and promoting the transition to the inflorescence meristem (IM). Additionally, VRT2 and SOC1 regulate the SAM to IM transition by interacting with VRN1. (B) Eight core pathways (marked with circled Arabic numbers) regulate wheat spikelet development. Pathway 1, Pathway 2, and Pathway 3 involve wheat SQUAMOSA and SVP clade genes, controlling the transition from the inflorescence meristem (IM) to the terminal spikelet (TS) and spikelet meristem (SM). Accelerating the IM-TS transition reduces spikelet number, while delaying SM formation increases spikelet number. Pathway 4 and Pathway 5 involve Tak4 and TaColB5 phosphorylation and the miRNA156-SPL3/17 influence spikelet number, respectively. Pathway 6, Pathway 7, and Pathway 8 specifically regulate supernumerary spikelet formation. Ppd1 represses ALOG1 (OsG1L1 in rice) and promotes FT expression to facilitate supernumerary spikelet formation, indicating that photoperiod is important in supernumerary spikelet regulation. WFZP, homologous to rice FZP and maize BD1, suppresses supernumerary spikelet formation, as does the miRNA165/166-HB-2 degradation pathway. (C) The specific expression pattern of genes controlling wheat spikelet development. FUL2, FUL3, and HB-2 are expressed in the apical region of the spikelet meristem. VRT2, SVP1, and TaBA1 accumulate on the abaxial side, while TaSPL17 is expressed at the abaxial boundary. SOC1 is found in the central part, and WAPO1 and ALOG1 are in the distal part of the spikelet. LFY is expressed in the leafy region, and WFZP in the floret meristem. The specific gene expression regions are highlighted in different colors on a longitudinal section of a young wheat spike. (D) Seven pathways regulate floret development. Pathway 5, Pathway 8, Pathway 9, and Pathway 10 control floret number per spikelet, with Pathway 5 and Pathway 8 linked to the miRNA156-SPL13 and WFZP-MYB30 module, partially overlapping with spikelet development. Pathway 9 involved in GNI1 promotes fertile florets, and Pathway 10 is for the unclear role of hormones in regulating floret number. Pathway 3, Pathway 11, and Pathway 12 regulate floret organ identity. AGL6 promotes AP3 for stamen identity, and AGL6 and LFY regulate other BCDE class genes in floret organ identity, while miRNA172-Q/AP2L2 controls lemma identity.
Agriculture 15 01575 g003
Table 1. Summary of spike traits QTLs.
Table 1. Summary of spike traits QTLs.
TraitsNo. of QTLsNo. of ClustesChr Distribution
Spike length (SL)22512621
Spike compactness (SC)994917 (except chr1A/4D/6D/7D)
Grain number (GNS)52534721
Spikelet number (SNS)30922121
Table 2. Pairs of spike compactness and spike length clusters.
Table 2. Pairs of spike compactness and spike length clusters.
ChrSpike Length ClustersInterval (Mb)
(Ref V1.0)		PVE (%)Spike Compactness ClustersInterval (Mb)
(Ref V1.0)		PVE (%)Genes
1BSL-cluster1B.4634.2–634.3 SC-cluster1B.2638.14–656.96.04
2ASL-cluster2A.5747.6–753.1 SC-cluster2A.2754.17–755.94.42TaARF12-2A
2BSL-cluster2B.9739.12–776.5 SC-cluster2B.2/2B.3741.6–799.251.53–12.74TaARF12-2B
2DSL-cluster2D.117.61–32.913–37.5SC-cluster2D.114.36–35.0212.55–22.4Rht8/RNHL-D1
3ASL-cluster3A.3711.2 SC-cluster3A.2711.3–711.654.23
3BSL-cluster3B.225.4–26.5 SC-cluster3B.125.4–26.5
3BSL-cluster3B.7577.8–593.7 SC-cluster3B.2531.4–636.4413.21TaLAX1-3B
3DSL-cluster3D.11.11–4.49 SC-cluster3D.12.2–2.4
3DSL-cluster3D.230.3710.53SC-cluster3D.230.3711.12
4ASL-cluster4A.5698.74–745.95 SC-cluster4A.1713.52–719.314.21
4BSL-cluster4B.122.56–44.5310.39–14.54SC-cluster4B.131.89–37.172.44–11.23Rht-B1b, ZnF-B
5ASL-cluster5A.113.85–43.434.87–10.32SC-cluster5A.119.24–37.9810.42
5ASL-cluster5A.5468.03–540.111.8–26.6SC-cluster5A.3478.6–541.212.02–26.6
5ASL-cluster5A.7668.41–710.42 SC-cluster5A.5690.42–702.193.56–6.78TaVRN2, WSOC1-5A
5BSL-cluster5B.2388.5–406.911SC-cluster5B.2388.5–406.9
5BSL-cluster5B.5536.05–550.23 SC-cluster5B.4538.29–590.153.42–35.62
6ASL-cluster6A.350.28–63.587.13–9.37SC-cluster6A.150.28–77.511.89
6ASL-cluster6A.5548.08–554.0411.4SC-cluster6A.3533.24–616.9711.85–12.98SVP1-6A, TaPIN1-6A
6BSL-cluster6B.5654.19–702.319.1SC-cluster6B.2701.61–703.37.19–13.04TaTPR-B1
7ASL-cluster7A.268.9–85.6 SC-cluster7A.282.38–84.781.66–5.94
7ASL-cluster7A.4643.09–683.39 SC-cluster7A.5678.47–682.2923.14WAPO1-7A
7BSL-cluster7B.5686.16–711.117.11SC-cluster7B.1680.85–687.7412
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Ji, Z.; Liu, X.; Yan, F.; Wu, S.; Du, Y. The Genetic Basis of Wheat Spike Architecture. Agriculture 2025, 15, 1575. https://doi.org/10.3390/agriculture15151575

AMA Style

Ji Z, Liu X, Yan F, Wu S, Du Y. The Genetic Basis of Wheat Spike Architecture. Agriculture. 2025; 15(15):1575. https://doi.org/10.3390/agriculture15151575

Chicago/Turabian Style

Ji, Zhen, Xin Liu, Fei Yan, Shouqing Wu, and Yanfang Du. 2025. "The Genetic Basis of Wheat Spike Architecture" Agriculture 15, no. 15: 1575. https://doi.org/10.3390/agriculture15151575

APA Style

Ji, Z., Liu, X., Yan, F., Wu, S., & Du, Y. (2025). The Genetic Basis of Wheat Spike Architecture. Agriculture, 15(15), 1575. https://doi.org/10.3390/agriculture15151575

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop