PHOTOPERIOD1 (PPD1) gene. Tetraploid wheat plants carrying the Ppd-A1a allele with a large deletion in the promoter head earlier under SD than plants carrying the wildtype Ppd-A1b allele with an intact promoter. Phytochromes PHYB and PHYC are necessary for the light activation of PPD1, and mutations in either of these genes result in the downregulation of PPD1 and very late heading time. We show here that both effects are reverted when the phyB mutant is combined with loss-of-function mutations in EARLY FLOWERING 3 (ELF3), a component of the Evening Complex (EC) in the circadian clock. We also show that the wheat ELF3 protein interacts with PHYB and PHYC, is rapidly modified by light, and binds to the PPD1 promoter in planta (likely as part of the EC). Deletion of the ELF3 binding region in the Ppd-A1a promoter results in PPD1 upregulation at dawn, similar to PPD1 alleles with intact promoters in the elf3 mutant background. The upregulation of PPD1 is correlated with the upregulation of the florigen gene FLOWERING LOCUS T1 (FT1) and early heading time. Loss-of-function mutations in PPD1 result in the downregulation of FT1 and delayed heading, even when combined with the elf3 mutation. Taken together, these results indicate that ELF3 operates downstream of PHYB as a direct transcriptional repressor of PPD1, and that this repression is relaxed both by light and by the deletion of the ELF3 binding region in the Ppd-A1a promoter. In summary, the regulation of the light mediated activation of PPD1 by ELF3 is critical for the photoperiodic regulation of wheat heading time.The photoperiodic response is critical for plants to adjust their reproductive phase to the most favorable season. Wheat heads earlier under long days (LD) than under short days (SD) and this difference is mainly regulated by the  CONSTANS plays a central role in the perception of photoperiod, but in wheat the main photoperiod gene is PHOTOPERIOD1 (PPD1). In this study, we show that the clock gene EARLY FLOWERING 3 (ELF3) regulates the phytochrome-mediated light activation of PPD1. Loss-of-function mutations in ELF3 result in the upregulation of PPD1 at dawn, and in early heading under both long and short days, even in the absence of PHYB. A deletion in the PPD1 promoter including an ELF3 binding region also results in earlier heading under short days, indicating that ELF3 acts as a direct transcriptional repressor of PPD1. This study shows that ELF3 plays a critical role in the wheat photoperiod pathway by regulating the light signal between the phytochromes and PPD1. ELF3 provides an additional entry point to engineer heading time in wheat, an important trait for the development of better adapted varieties to a changing environment.The coordination of reproductive development with the optimal season for seed production is critical to maximize grain yield in crop species. Plants can perceive the length of the day or night (photoperiod) and use this information to anticipate seasonal changes. In most eudicot plants,  Crop productivity depends on the precise alignment of flowering with the most favorable season for seed production and grain filling. For that to happen, plants need to anticipate the proximity of the favorable season to initiate the reproductive phase in a timely manner. The duration of days and nights (photoperiod) provides seasonal information that plants have evolved to sense and use to this end .CONSTANS (CO) is the main photoperiodic gene .0–130 d)  and NB (.0–130 d)PPD1 by light results in the induction of FLOWERING LOCUS T1 (FT1) expression in the leaves [FT1 encodes a protein (florigen) that is thought to migrate through the phloem to the shoot apical meristem in wheat as shown in Arabidopsis and rice [VERNALIZATION1 (VRN1), which is critical to trigger the transition of the shoot apical meristem from the vegetative to the reproductive phase [VRN1 results in the downregulation of the flowering repressor VERNALIZATION2 (VRN2), generating a positive feedback loop that accelerates heading time [The transcriptional activation of e leaves ,17. FT1 and rice ,20. FT1 ve phase ,22. The ing time –25PPD1 and EARLY FLOWERING 3 (ELF3) in the regulation of heading time in both wheat and barley [ELF3 [LUX [ELF3 has also been associated with differences in heading time in diploid Triticum monococcum and in hexaploid wheat [Significant genetic interactions have been detected between d barley –28. In Ad barley . ELF3 fud barley . In barley [ELF3 ,27,30 orLF3 [LUX –33 resulid wheat ,34,35.ELF3, ELF4, and LUX overlaps and peaks at dusk, maximizing their repressive effect early in the night [PSEUDORESPONSE REGULATOR 7 (PRR7) and PRR9 in Arabidopsis [PRR37, PRR73, PRR95, GI, and GHD7 in rice [GHD7 is the rice ortholog of the wheat LD flowering repressor VRN2 [PRR7/PRR3 are the closest homologs of wheat and barley PPD1, and elf3 mutants in barley and Brachypodium show altered PPD1 expression profiles [PPD1 by ELF3 may contribute to their observed epistatic interactions on heading time in the temperate cereals.In Arabidopsis, the expression of he night . Chromatbidopsis ,38 and P in rice  . Sinprofiles ,42, we hPPD1. We also show that the repressed expression of PPD1 in the phyB mutant is restored in the elf3 phyB combined mutant, which flowers almost as early as the elf3 mutant. By contrast, the combined elf3 ppd1 mutant heads significantly later than elf3. Based on our results, we propose that ELF3 acts as a direct repressor of PPD1 and plays a critical role in the regulation of the light signals between the phytochromes and PPD1.In this study, we show that the wheat ELF3 protein interacts with PHYB and PHYC, is modified by light, and binds to the promoter of Arabidopsis [phyB mutant in previous studies [ELF3. To test this, we generated loss-of-function mutants phyB, elf3 and elf3 phyB  and LD .Given the documented interactions between ELF3 and PHYB in bidopsis ,43,44, w studies ,13 couldFig A in  in two dFig A in  and the ELF3 and PHYB were detected in both PS and PI plants . Interestingly, when the elf3 mutation was present, the phyB loss-of-function mutation was associated with a non-significant 2 d delay in heading time in PI  and PS (3.9 d). However, in the combined elf3 phyB mutant, SD was associated with a significant delay in heading time in PI (5.9 d), but a significant acceleration in PS  the large delays in heading time caused by the phyB mutation are mediated in large part by ELF3, ii) the elf3 mutant is still able to respond to photoperiod, and iii) the elf3 phyB mutant heads earlier under LD than under SD in the PI background, but later in the PS background.In summary, the heading time results indicate that ELF3 and PHYB on heading time, we explored the expression of PPD-A1, PPD-B1, and FT1 in phyB and elf3 phyB mutants grown under LD  and CO2 (ZT4-ZT8)  and shows similar transcriptional profiles under SD and LD  between ZT12 and ZT20 relative to the wildtype  assays. The full-length coding region of the ELF3 gene was fused to the GAL4 DNA-binding domain and used as bait. The phytochrome genes PHYC and PHYB were each divided into two parts encoding the N-terminal photosensory and C-terminal regulatory regions, respectively. The N-terminal region included 625 amino acids in PHYB (N-PHYB) and 600 amino acids in PHYC (N-PHYC). The C-terminal region encoded amino acids 626–1166 in PHYB (C-PHYB) and amino acids 601 to 1139 in PHYC (C-PHYC).Since the transcriptional regulation of ELF3 showed strong interactions with both C-PHYB and C-PHYC. However, its interaction with the N-PHYB was much stronger than with N-PHYC . AutoactUBIQUITIN promoter (UBI::ELF3-HA). The transgene was expressed at high levels in the leaves of both Kronos PS and the elf3 mutant, and was associated with the downregulation of PPD1 and FT1 and delayed heading, including in plants carrying the elf3 mutation , PPD1 (wildtype and ppd1) and photoperiod (SD and LD) revealed highly significant effects for these three factors and also for all two-way and three-way interactions  there are strong genetic interactions between ELF3, PPD1, and photoperiod, ii) the Ppd-A1a allele can accelerate heading time in the absence of ELF3 under both LD and SD, iii) ELF3 can delay heading time in a PPD1-independent manner, and iv) there is a residual photoperiodic response that is independent of PPD1 and ELF3.A factorial ANOVA including elf3 mutations on heading time at the molecular level, we analyzed the transcript levels of PPD1 and FT1 in the youngest leaves of five-week-old Kronos PI and PS plants grown under LD   . By contZT20-ZT8 , which w ZT0-ZT4 .PPD1 homoeologs at dawn was associated with the presence of the 1,027 bp deletion in the promoter of Ppd-A1a [Ppd-A1b allele with an intact promoter. Indeed, we found that the ZT0 peak was absent in PPD-A1b , hyB Figs  than in lf3 Figs  and 7, sPPD1 in the elf3 mutant suggest that ELF3 acts as a transcriptional repressor of this gene. To test the binding of ELF3 to the PPD1 promoter in vivo, we performed replicated chromatin immunoprecipitation (ChIP) experiments using PS plants carrying the UBI::ELF3-HA transgene combined with the elf3 mutation and non-transgenic elf3 plants as a control. Samples were collected from the aerial part of plants grown under SD at ZT10 in the dark, when ELF3 levels are elevated  promoter (-1933 to -1750), which does not have any putative LUX binding site and was included as a negative control. Taken together, these experiments confirm that ELF3 acts as a direct transcriptional repressor of PPD1 in planta (We did not observe enrichment of ELF3 for a region between -142 to -21 bp (close to another putative LUX binding site), a region in the coding region of rt codon . Lastly,n planta , likely ELF3 on the regulation of flowering time has been extensively studied given the importance of this trait in the adaptation of crop species to different latitudes [elf3 Kronos mutants in LD and SD and the delayed heading time of the UBI::ELF3-HA transgenic plants indicate that ELF3 functions as a heading time repressor in wheat. Early flowering of elf3 mutants has also been reported in barley [Brachypodium [ELF3 as a flowering repressor in the temperate grasses. A similar function has been observed in Arabidopsis, where elf3 mutants flower early under both SD and LD [The role of atitudes ,30,47–51n barley ,30 and Bhypodium , suggestD and LD ,52.elf3-1 and elf3-2 mutants flower later than the wildtype under both SD and LD conditions [elf3-1 elf3-2 fails to flower in both photoperiods [elf3 mutants show some similarities between wheat and rice. In both species, elf3 shows increased mRNA levels of the LD flowering repressor GHD7/VRN2 [phyC and phyB mutants have opposite effects on heading time in wheat and rice, those are mostly cancelled when combined with the elf3 mutant in both species [ELF3 in both wheat and rice [ELF3 and the phytochromes in wheat and rice flowering time are likely associated with the reverse role of their downstream target PPD1/PRR37, which acts as a LD flowering promoter in wheat and as a LD flowering repressor in rice [The opposite effect has been observed in rice, where the individual nditions ,54 and toperiods . In spitHD7/VRN2 . In addi species . This inand rice . The rev in rice .elf3 ppd1 combined mutant headed earlier than the ppd1 mutant both in LD (37 d) and SD (>48 d) indicating that ELF3 can delay wheat heading time independently of PPD1. The same result was reported for Brachypodium plants grown under 20 h light / 4 h darkness, where elf3 ppd1 headed 16 d earlier than ppd1 [Brachypodium genotypes were grown under SD (8 h light) or LD (16 h light), the elf3 ppd1 plants headed significantly later (24.4 and 13.7 d) than the ppd1 plants [Brachypodium and wheat in the PPD1-independent effect of ELF3.The han ppd1 . However1 plants . These relf3 mutants showed a significant reduction in spikelet number per spike  at ZT0 in the absence of ELF3 , PRR9, GIGANTEA, and LUX itself [The ELF3 repression of n barley , diploidnococcum ,76, and moeologs . LUX is moeologs ,38,77,78X itself ,38,77,78PRR3 –PRR7 paralogs in Arabidopsis and the PRR37 (PPD1)–PRR73 paralogs in the grass lineage belong to the same clade, suggesting a common history [PRR3 and PRR7 in Arabidopsis is independent of the duplication that originated PPD1—PRR73 in the grasses, the potential sub-functionalization of these two pairs of paralogs is also independent [PRR7 is an important component of the circadian clock with no major effects on the photoperiodic regulation of flowering, whereas natural mutations in PPD1 selected during wheat [prr7-11 mutant with the barley photoperiod sensitive (Ppd-H1) and insensitive (ppd-H1) alleles driven by the Arabidopsis PRR7 promoter complements circadian leaf movements in Arabidopsis [PPD1 mutations with limited effects on the clock that minimize negative pleiotropic effects. Taken together, these results suggest that grasses may have repurposed an ancient interaction between clock genes (EC and PRR7) to develop a photoperiod pathway that can operate independently of CO.The  history ,80. Howeependent . In Arabng wheat ,8,18,81 ng wheat  domesticng wheat ,79. Howebidopsis , suggestco1 co2 headed 3 d earlier than the wildtype under LD and 13.5 d under SD, suggesting that CO1 and CO2 function as weak heading time repressors in the presence of functional PPD1 alleles [ppd1 mutant headed more than 60 d earlier than the ppd1 co1 plants, which failed to head before the experiment was terminated at 180 d [CO1 locus, but only among accessions carrying the ppd-H1 photoperiod insensitive allele [CO1 can accelerate heading time under LD in the absence of PPD1, and may explain the residual photoperiodic response observed in the elf3 ppd1 mutant, which headed earlier under LD than under SD , which has not yet been functionally characterized in wheat. Loss-of-function mutants in GI have a reduced photoperiodic response in both rice [in vivo to promote GI protein degradation [A limitation of the model presented in oth rice  and Araboth rice . In Arabradation . In addiradation . TherefoPPD1-mediated photoperiod pathway, this study clearly shows that the ELF3 protein operates downstream of PHYB and PHYC, is regulated by light and acts as a direct repressor of PPD1. This information provides additional entry points to engineer heading time in wheat, an important trait for the development of better adapted varieties to a changing environment.Although much remains to be learned on the wheat Triticum turgidum ssp. durum, 2n = 28, genomes AABB) [Vrn-A1 allele for spring growth habit  [Vrn-B2 long day repressor locus (ZCCT-B2a and ZCCT-B2b) [Ppd-A1a allele for reduced photoperiodic response [ELF3 [PHYB [PPD1 [Plant materials used in this study were derived from a sequenced EMS-mutagenized TILLING population of the tetraploid wheat variety Kronos (es AABB) ,90. Kron allele) ,91, a fuCCT-B2b) , and these [ELF3 , PHYB [1F3 [PHYB , and PPDYB [PPD1  were desppd-A1 and ppd-B1) whereas the double mutants without any functional copy of the gene are indicated without any genome letter (e.g. ppd1). We intercrossed these different mutants and selected different mutant combinations using marker-assisted selection. All lines had at least two backcrosses to parental line Kronos to reduce the number of background mutations. The elf3 phyB combined mutant was also crossed with a Kronos near-isogenic line carrying the photoperiod sensitive Ppd-A1b allele [Mutants for the individual homoeologs are indicated with the capital letter of the genome  markers   were deveviously .− 1, 5 μl of 2x KASP Master Mix, and 0.14 μl of KASP primer mix. For every 100 μl, the primer mix included 12 μl of the VIC primer (100 μM), 12 μl of the FAM primer (100 μM), 30 μl of the genome-specific common primer (100 μM), and 46 μl of distilled water. A two-step touchdown PCR program was used, with an initial denaturalization step of 94°C for 15 min, followed by ten cycles of touchdown of 94°C for 20 s and annealing/extension at 61–55°C for 1 min (dropping 0.6°C per cycle), followed by 36 cycles of 94°C for 20 s and annealing/extension at 55°C for 1 min. KASP results were analyzed with a FLUOstar Omega F plate reader  using the software KlusterCaller .KASP reactions were carried out using 5 μl of genomic DNA diluted to a concentration of 5–50 ng μl2F3 plants homozygous for the different allelic combinations were stratified for 3 days at 4°C in the dark and then planted in PGR15 growth chambers . Lights were set to 350 μmol m−2 s−1 at canopy level and were kept on for 16 h in the LD experiments and for 8 h in the SD experiments. Temperature was set to 22°C during light periods and 17°C during dark periods. Heading time was recorded as the number of calendar days from planting in the soil to full emergence of the spike from the sheath.After the two backcrosses to Kronos, BCppd1 and ppd1 elf3; leaf five in wildtype and phyB, and leaf seven in elf3 and elf3 phyB. Five plants per genotype were analyzed at each time point. Different plants were sampled for each time point.The transcriptional profiles of genes regulating wheat flowering time were analyzed during a 24-hour period in PI and PS plants with different mutant combinations. Plants were grown in a Conviron growth chamber under LD conditions and tissue samples from the last fully-expanded leaf were collected simultaneously from five-week-old plants every 4 h, starting at Zeitgeber time 0 . Because of variation in leaf developmental rates of the different mutants, the last fully-expanded leaf at week five was leaf four in ACTIN was used as an endogenous control. Transcript levels for all genes are expressed as linearized fold-ACTIN levels calculated by the formula 2ACTIN CT–TARGET CT)( ± standard error (SE) of the mean (s.e.m.).Harvested tissue was grounded to a fine powder in liquid nitrogen and RNA was extracted using the Spectrum Plant Total RNA Kit  following the manufacturer’s recommendations. First-strand cDNAs were synthesized from 500 ng of total RNA using the High Capacity Reverse Transcription kit . The qRT-PCR experiments were performed using 2X USB VeriQuest Fast SYBR Green qPCR Master Mix  in a 7500 Fast Real-Time PCR system. Primers used for quantitative qRT-PCR are listed in Table B in ELF3 full-length coding region was first cloned into the pDONR-Zeo vector by BP reaction  using primers ELF3-GW-F and ELF3-GW-R (Table C in http://www.thermofisher) and used as bait. The cloning of the N-PHYC (1–600 AA) and C-PHYC (601-1139AA) was described previously [EcoRI and XmaI restriction sites using primers N-PHYB-F and N-PHYB-R, and the C-PHYB (626-1166AA) was cloned into pGADT7 between EcoRI and ClaI sites using primers C-PHYB- F and C-PHYB-R .Tissue from newly fully-expanded leaves was harvested from UBI::ELF3-HA transgenic plants. Protein extraction was performed as described previously . Whole lelf3 mutation or a combination of this mutation and the UBI::ELF3-HA transgene were grown to the fourth-leaf stage under SD (8h light). Eight grams of above-ground seedling tissue  were harvested at ZT10 and fixed in formaldehyde. Plants were harvested in the dark prior to fixation to avoid degradation of the ELF3 protein in the light. To aid in fixation penetration, harvested tissue was cut into 2–4 mm pieces and placed into metal tea infusers. Tissue was immediately cross linked under vacuum for 10 minutes in buffer containing 400 mM sucrose, 10 mM Tris (pH 8), 1% formaldehyde, then the vacuum was turned off and the tissue sat for an additional 5 minutes. To quench the cross-linking reaction 0.25 M glycine was used and the vacuum re-applied for an additional 5 minutes. Tissue was rinsed with milli-q water three times. After fixation, tissue was frozen in liquid nitrogen and stored at −80°C until performing the chromatin immunoprecipitation as described before [http://www.thermofisher) were used for the immunoprecipitation.Kronos PS plants carrying the d before . Anti-HAS1 TextPHYB, ELF3, and PPD1 mutants.Fig A. Schematic representations of  Mutations introducing premature stop codons are indicated with red triangles and deletions with dotted red lines. Exons are shown as gray rectangles and introns as black lines. (A) The phyB line combines a premature stop codon on the A-genome homoeolog that truncates the last 641 amino acids of the protein, spanning the entire regulatory module, and a premature stop codon in the B-genome copy that eliminates the distal 140 amino acids, including the histidine kinase domain [B) The elf3 line carries premature stop codons that eliminate the last 241 (A-genome) and 244 (B-genome) amino acids of the C-terminal region, including the third and fourth conserved blocks of the ELF3 protein [C) The ppd1 line carries a premature stop codon in ppd-A1 that eliminates 514 amino acids of the PPD-A1 protein, including the highly conserved CCT domain, and ppd-B1 is a gamma ray-induced deletion the eliminates the complete gene [D) Natural deletions in the promoter of the Ppd-A1a [Ppd-D1a [elf3 and elf3 phyB mutations on spikelet number per spike (SNS).Fig B. Effect of  (A) Kronos photoperiod insensitive (PI). (B) Kronos photoperiod sensitive (PS). In both experiment plants were grown under LD (16h light). Different letters above the bars indicate significant differences in pair-wise non-parametric Kruskal-Wallis tests (P < 0.05). The non-parametric test was used because no transformation was able to restore normality of residuals and homogeneity of variances simultaneously. The reduced SNS in the elf3 mutant was restored in the phyB elf3 combined mutant. Raw data is available in Data H in VRN1, VRN2, CO1, and CO2 in Kronos PI, phyB and elf3 phyB.Fig C. Transcript levels of flowering genes  (A-B) VRN1, (C-D) VRN2, (E-F) CO1, and (G-H) CO2.  Wildtype vs. phyB.  Wildtype vs. elf3 phyB. Primers used for qRT-PCR amplify both homoeologs of each gene. The WT data is the same within each row but can be at different scales. Error bars are s.e.m based on 5 biological replications. ns = not significant, * = P < 0.05, ** = P < 0.01, *** = P < 0.001 based on t-tests between mutants and wildtype at the different time points. Raw data and statistics are available in Data I in ELF3 transcript levels in leaves in the presence of phyB and phyC mutants under different photoperiods.Fig D.  (A) Transcript levels of Elf3 during the day in PS under SD. (B) Elf-A3 and Elf-B3 transcripts per million (TPM) in PI WT, phyB and phyC in leaves collected at ZT4 from 4-w old plants grown under LD and 8-w old plants grown under SD. Data are from previously published RNA-seq [C) Transcript levels during the day in PI and phyC under LD (D) Transcript levels during the day in PI and phyB under LD. Transcript levels were determined by qRT-PCR using ACTIN as endogenous control. NS = P > 0.05. Raw data and statistics are in Data J in ELF3 under the maize UBIQUITIN promoter (UBI::ELF3-HA).Fig E. Effect of the constitutive expression of  (A-C) Transcription profiles in the 7th leaf collected at ZT0, ZT4, ZT12 and ZT20 from five-week-old Kronos PS plants grown under LD. ACTIN was used as endogenous control. (A) ELF3, (B) PPD1 (conserved primers that amplify both Ppd-A1b and Ppd-B1b) and (C) FT1. Different letters indicate significant differences in Tukey tests (P < 0.05). The colors of the letters match the color of the respective treatment. OE = UBI::ELF3-HA and NT = non-transgenic sister line. (D) Complementation of the elf3 mutant by UBI::ELF3-HA. A factorial ANOVA showed highly significant effects on days to heading (DTH) for both the mutant and transgenic genotypes and for their interaction. Simple effects were tested by contrasts: ns = not significant, ** = P < 0.01, *** = P < 0.001. Raw data and statistics are available in Data K in Fig F. ELF3-HA protein size in western blots. (A-B) Samples extracted from leaves of Kronos-PS transgenic plants over-expressing ELF3 and a C-terminal 3xHA tag under the maize UBIQUITIN promoter (UBI::ELF3-HA). The ELF3-HA protein was detected by immunoblotting using an anti-HA antibody. Leaf samples were collected from plants grown under short day either 10 minutes before the lights were turned off (ZT8 -10m) or four hours after the lights were turned off (ZT12). (A) The expected size of the ELF3-HA protein is 88.5 kDa but the estimated size of the lowest band detected with the HA antibody was ~110 kDa based on both pre-stained and unstained protein markers. No bands were detected in the negative untransformed controls confirming the identity of the ELF3-HA protein. An additional and more diffuse band was detected at ZT8 -10m between 110 and 130 kDa. (B) Replicated experiment showing the complete blot. The lower strong band is rubisco (Rub). Top: Chemiluminescence, middle: CBB stained color-matrix, and bottom: merged images obtained by ChemiDoc imaging system (BioRad). (C) Wheat protoplasts transformed with UBI::ELF3:HA grown under both light and dark conditions. The unstained molecular marker was used to estimate band size. Table A. EMS-induced nucleotide changes that resulted in premature stop codon mutations in ELF3, PHYB, and PPD-A1. The ID of each of the mutant lines, the position of the loss-of-function mutations in the CDS and protein, and the primers used in the diagnostic KASP assays are listed. Capital letters in the primer sequences indicate the VIC and FAM tails. The 3′ allele-specific nucleotides are underlined. Table B. Primers used for qRT-PCR analysis. Table C. Primers used for cloning ELF3 and PHYB in yeast-two-hybrid assays. Table D. Primers used for chromatin immunoprecipitation.e domain . (B) The protein . (C) Theete gene . (D) Nat Ppd-A1a  and Ppd- RNA-seq . (C) Tra(DOCX)Click here for additional data file.S1 DataData A. Supporting data for Data B. Supporting data for Data C. Supporting data for Data D. Supporting data for Data E. Supporting data for Data F. Supporting data for Data G. Supporting data for Data H. Supporting data for Fig B in Data I. Supporting data for Fig C in Data J. Supporting data for Fig D in Data K. Supporting data for Fig E in (XLSX)Click here for additional data file. 10 Dec 2022Dear Dr Dubcovsky,Thank you very much for submitting your Research Article entitled 'EARLY FLOWERING 3 interactions with PHYTOCHROME B and PHOTOPERIOD1 are critical for the photoperiodic regulation of wheat heading time' to PLOS Genetics.The manuscript was fully evaluated at the editorial level and by independent peer reviewers. The reviewers appreciated the attention to an important topic but identified some concerns that we ask you address in a revised manuscript.We therefore ask you to modify the manuscript according to the review recommendations. Your revisions should address the specific points made by each reviewer.In addition we ask that you:1) Provide a detailed list of your responses to the review comments and a description of the changes you have made in the manuscript.archive. 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You will be contacted if needed following the screening process.PLOS has incorporated To resubmit, you will need to go to the link below and 'Revise Submission' in the 'Submissions Needing Revision' folder.Please let us know if you have any questions while making these revisions.Yours sincerely,Claudia KöhlerSection EditorPLOS GeneticsReviewer's Responses to QuestionsComments to the Authors:Please note here if the review is uploaded as an attachment.Reviewer #1: This is a very interesting and clear manuscript that demonstrates that ELF3 plays a critical role in the wheat photoperiod pathway by regulating the light signal between the phytochromes and PPD1.Loss-of-function mutations in ELF3 result in the upregulation of PPD1 at and dawn, and in early heading under both long and short days, even in the absence of PHYB. A deletion in the PPD1 promoter including an ELF3 binding region also results in earlier heading under short days, indicating that ELF3 acts as a direct transcriptional repressor of PPD1. The authors generated a large number of mutants and double mutants in different Kronos backgrounds . The paper is clearly written and well structured.I only have a few minor comments on the manuscript.1. Fig 1: It was surprising that Ppd1-A and Ppd1-B have a 4h shift in peak expression in the WT. Also how do you explain the very different diurnal pattern of Ppd1-B in KPI and KPS?2. Fig 4. How do you explain that in the night break experiment (C) the second Elf3 band starts appearing only 10min after lights on, whereas in LD  after lights on no elf3 can be seen (the gel at ZT0+10min looks different from the rest of the gel background?). Would this not suggest that not only the light but also the time of the day  would matter for elf3 protein abundance and form? Is your idea that the lower band elf3 in the night is the active one?3. Since you have the elf3-HA would it not be possible to really show binding of elf3 to phys in vivo?4. Fig. 5 Please, explain in the M&M part what exactly is ppd1-null is and how this line was generated.5. On page 17 you write: The notable exception is the downregulation of VRN2, CO1, and CO2 at dawn in elf3 phyB  relative to elf3 , suggesting the PHYB is required for the upregulation of these genes in the elf3 mutant background at dawn.6. In S3D VRN is upregulated in elf3 phyb, actually in all mutants VRN2 is upregulated, also in the phyb mutant and this is somewhat puzzling. It might also be indirect effects through feedback loops between flowering time genes  as is actually indicated in your flowering model.7. As the authors provide a model for a barley flowering time pathway with ELF3 in a central position, but also discuss the possible role of LUX, it might be nice to add LUX to the model in Fig. 9Reviewer #2: The authors provide a concise genetic analysis of photoperiodic flowering in the temperate cereal wheat. Through the phenotypic and molecular analysis of single and double mutants they show that ELF3 acts downstream of PHYB in the induction of the flowering activator PPD1, with ELF3 being a negative regulator of PPD1 expression. They further show that PHYB does not affect ELF3 gene expression but rather interacts with the PHYB photoreceptor (and PHYC) (in yeast two-hybrid), suggesting that PHYB regulates ELF3 activity, possibly by light-mediated post-translational modification of the ELF3 protein. They further show by ChIP that ELF3 directly binds the promoter of PPD1.This is a very thoughtful study. The data support the conclusions drawn. The manuscript is well-written. This manuscript stands out because it not only genetically analyzes ELF3 function but also addresses a possible mechanism of ELF3 regulation by studying the ELF3 protein.I only have a few minor comments:Fig. 4A. In this Western blot, the ELF3-HA protein runs at about 130 kDa. However, ELF3 is predicted to be only approx. 75 kDa in size. That is quite a discrepancy. I ask the authors to show a control blot with a protein extract of a non-transgenic plant as a control in order to confirm that the detected band(s) are indeed ELF3-HA. In the supplement, please also show a complete blot including the region of the gel where 75 kDa proteins are expected.I wonder if the authors have confirmed the PHYB-ELF3 interaction using additional methods? E.g. split luciferase, BiFC. This would strengthen the manuscript. However, since this interaction is described for Arabidopsis, I do not require these experiments.Fig. 4: The authors speculate that the upper ELF3 band might reflect PIF3 phosphorylation or ELF3 ubiquitination. A treatment of the extract with phosphatase could easily test for phosphorylation and would strengthen the manuscript.**********Have all data underlying the figures and results presented in the manuscript been provided?PLOS Geneticsdata availability policy, and numerical data that underlies graphs or summary statistics should be provided in spreadsheet form as supporting information.Large-scale datasets should be made available via a public repository as described in the Reviewer #1: YesReviewer #2: Yes**********what does this mean?). 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Productivity indices of ewes were calculated. Location and season of lambing had a significant impact on annual ewe productivity, while the ewe genotype showed no significant influence on productivity indices, except for the weight of lambs produced per kilogram of metabolic weight , where local ewes outperformed Dorper crossbred ewes. The difference in annual-productivity indices between local and Dorper crossbred ewes was more evident when considering the postpartum weight, as the ewes exhibited higher postpartum weights. However, both ewe genotypes produced comparable lamb weights per year . In summary, under low-input conditions, Dorper crossbred ewes demonstrated comparable reproductive performances and productivity traits to local ewes. Nevertheless, breed and environmental factors identified in this study should be taken into account to enhance sheep productivity in both local and Dorper crossbred ewes.This study evaluated the reproductive and productivity of local and Dorper crossbred ewes in a community-based management system. We analyzed data collected from 2013 to 2021, taking into account different factors such as dam-breed, location, type of birth, season, and year of lambing. Lambing was observed all year-round, but the majority (35%) occurred in September, October, and December. This suggests that pasture availability, which is influenced by climatic-factors, may play a role in the seasonality of lambing. Litter-size at birth and weaning did not show any significant difference. Age at first lambing varied between breeds (P < 0.001), while lambing-interval and annual reproductive rates were unaffected by dam-breed (P > 0.05). The annual number of lambing per year significantly varied based on location and lambing seasons (P < 0.001), with a higher frequency during the major rainy-season compared to the dry-season (1.58 According to Ref. , EthiopiIn Ethiopia there is no specialized sheep breed maintained for specific use only; sheep in Ethiopia are mainly kept for fulfilling multiple roles, such as cash income, meat, milk, skin, wool, manure, security, gifts, and religious rituals . Due to Basona Werana, Efratana Gidm, Kewet, Merhabete, and Kobo, to enhance sheep productivity. These initiatives involve the introduction of exotic Dorper sheep to facilitate the improvement of local sheep breeds. In his review work [Despite their adaptability, sheep productivity in Ethiopia is low due to no targeted improvements for specialized purposes, resulting in dismal productivity levels of local sheep . For insiew work , emphasiEvaluating the performance of crossbred ewes at different stages of the crossbreeding work becomes crucial to enhance the productivity and profitability of sheep farms managed under community-based management systems. This study aims to evaluate the reproductive performances and productivity of local and Dorper crossbred ewes managed under farmers' conditions, which will provide insights into optimizing the reproductive efficiency of sheep and positively impact the overall productivity and profitability of sheep farms.22.1This study was conducted on farmers' flocks in the Basona-Worana, Kewet, Efratana-Gidim, Merhabete, and Kobo areas, organized by the Debre-Birhan and Sirinka Agricultural Research Centers .Fig. 1MaOc, and the area receives an average annual rainfall of 758 mm.The Basona-Werana (Milky) site has a crop-livestock production system, with natural pasture grazing serving as the primary feed resource accounting for 75% of the livestock's feed resources . However0 0′ 0.12″ in the North and 39° 53′ 52.37″ in the east. The average temperature in this area is approximately 23.19 Oc and receives an annual rainfall of 1062.4 mm.The Kewet site has a Sorghum producing farming system, with native pasture grazing serving as the primary feed resource for sheep . Sheep aOc and receives an annual rainfall of 1048 mm [The Efratana-Gidim site is situated within a thriving farming system that cultivates major crops such as Sorghum, Teff, and Mung bean. Sheep mainly graze on natural pastures, with Sorghum stubble serving as an alternative feed resource. During the dry season, sheep are provided with Sorghum Stover and Mung bean haulm. The site is located at an altitude of 1448 m. a.s.l, with coordinates of approximately 10° 20′ 22.5″ north and 39° 57′ 38.28″ in the east. The region has an average temperature of 21.3  1048 mm .Oc and follows a crop-livestock mixed farming approach. Finger millet, Teff, and Maze are the primary crops in the midland area [Merhabete/Alemketema is located in the Northern region at coordinates 10° 3′ 25.39″ in the north, and 38° 59′ 34.58″ in the east, with an altitude of 2225 m. a.s.l. and an average rainfall of 934 mm. The area has a mean temperature of 19.3 and area , while Sand area . Land alThe Kobo (Raya-Kobo) site can be found at coordinates 12° 14′ 60.00″ in the North, and 39° 29′ 59.99″ in the East. The site sits at an altitude of 1470 m. a.s.l. and an average temperature of 23.1° Celsius. The area receives 630 mm of rainfall and is well-known for growing crops like Sorghum, Mung bean, and Teff. Livestock in the area relies on natural pastures and stubble grazing from Sorghum and Mung bean haulms for dry season feed sources.This study focuses on several local ewe breeds: Menz in Basona-Werana, Afar in Kewet and Efratana-Gidim, local Merhabete in Merhabete, and Tumelie in Kobo areas. The crossbred ewes produced in this study had a blood level of Dorper ranging from 25% to 50%. In 2013, a community-Based (CBBP) Dorper crossbreeding program was initiated, involving volunteer farmers in the respective study areas. The number of households participating in the study was as follows: Basona-Werana (48), Merhabete (46), Efratana-Gidim (40), Kewet (42), and Kobo (45). On average, these households held 15, 9, 7, 8, and 11 sheep, respectively.The crossbred ewes in the study have a blood level of Dorper ranging from 25% to 50%. In 2013, a community-based Dorper crossbreeding program was introduced, involving volunteer farmers in the respective study areas. The farmers received hands-on training covering various aspects of Dorper crossbreeding, lamb management, ram circulation, improved feeding systems, improved healthcare, and the concept of the community-based program. Once the farmers were aware of the utilization of Dorper rams, the distribution of Dorper rams from research centers took place. Farmers were grouped together based on proximity and their use of common grazing land and watering points. Each farmer group was allocated one sire to serve 20–25 breeding ewes, owned collectively by four to five households. The birth weight of the lambs and the postpartum body weight of the ewes were recorded within 24 h of lambing, along with lambing details. Rams were allowed to serve within the same breeding group for approximately one year before being transferred to another group within the same site to minimize inbreeding. The mating/crossbreeding system that followed was documented in a Dorper sheep strategy document ,19. The 2.2A team of researchers from the Debre-Birhan and Sirinka research centers collaborated to train a group of enumerators. The training focused on community-based crossbreeding practices, and the enumerators were responsible for collecting comprehensive data on reproductive performances from 2013 to 2021. The enumerators recorded the information in a master data-recording book prepared by the research team, with great attention to detail. To ensure the success of crossbreeding practices, diligent researchers made monthly visits to their respective flocks. This enabled them to address any challenges that arose and ensured the smooth execution of crossbreeding work. The collaborative approach between researchers, enumerators, and flock owners fostered an environment of continuous sheep crossbreeding practices.Throughout the research project, various traits were evaluated to determine the flock's reproductive performance and productivity. These traits included litter size at birth and weaning, which shows the number of lambs successfully born and weaned per ewe. This data helped assess the breeding efficiency and overall reproductive success of the flock. Age at first parturition was also considered, which indicates the age at which ewes gave birth for the first time. This parameter served as an indicator of the flock's development and young ewes' ability to reproduce efficiently. The research also looked at the lambing interval, which indicates the duration between successive lambing events. This information helped assess the reproductive efficiency and breeding management practices employed within the flock. Annual reproductive rates were calculated to provide insight into the overall reproductive performance of the flock, including the percentage of ewes that successfully conceived and delivered lambs within a year. Additionally, two indexes were used to evaluate the productivity of individual ewes. The first index, Kilograms of lamb produced per ewe per year, quantified each ewe's productivity in terms of the weight of lambs produced within a year. It helped evaluate the genetic potential, feeding management, and overall performance of individual ewes. The second index, Kilograms of lambs produced per post-Partum weight of ewe per year, considered the weight of the ewe after lambing as a factor in assessing lamb productivity. It provided insights into the efficiency of utilizing the ewe's body condition and resources for lamb production. Finally, the third index, the Kilogram of lambs produced per metabolic post-partum weight of ewe per year, took into account the metabolic weight of the ewe after lambing, considering factors such as body condition and energy requirement. It provided a comprehensive assessment of lamb production efficiency based on the ewe's metabolic state.0.73) demands of the dams, providing insights into the efficiency of the breeding program [•Index I: litter weight (kg) at 90 days of age × 365 days/subsequent lambing interval (days)•Index II: index I/post-partum body weight of ewe.•Index III: index I/metabolic post-partum body weight of ewe (kg)The study analyzed a large dataset consisting of 3585 records for litter size at birth (LSB) and 2904 records for litter size at weaning (LSW). Additionally, 1493 records were used to evaluate the reproductive indices of ewes for Index-I, while Index-II and Index-III were based on 1181 records each. Index-I is a comprehensive measure of overall productivity that considers various factors such as lambing intervals and the weight of lambs at weaning (90 days of age). It is calculated by multiplying litter weight (kg) at 90 days of age by 365 days and dividing it by the subsequent lambing interval (days). Index-II is a refined version of Index-I that normalizes productivity against the live weight of the dam, allowing for a fair comparison across dams of different sizes. On the other hand, Index-III takes into account the metabolic weight of the dams, which is crucial in determining their specific energy requirements. It relates productivity to the metabolic .Li = Fixed effect of ithdam genotype .Dj = Fixed effects of jseason .Sk = Fixed effects of kth lambing year .Yl = Fixed effects of lth lambing parity .Pm = Fixed effects of mth dam lambing Gender .Gn = Fixed effects of nth lamb eijklmn = effect of random error.Model 2Analysis of variance of Age at first lambing, Lambing interval, and Annual reproductive rate.ijklm, Where;Yijklm = μ + Li + Dj + Sk + Yl + Pm + Yijklm = the observation on Age at first lambing, Lambing interval, annual reproductive rate, and annual productivity indices of a ewe .μ = Overall Least squares mean.thLocation of the study Flock .Li = Fixed effect of ithdam genotype .Dj = Fixed effects of jseason .Sk = Fixed effects of kth lambing year .Yl = Fixed effects of lth lambing parity .Pm = Fixed effects of mth dam lambing eijklm = effect of random error.The statistical model employed for reproductive performances traits was.33.13.1.1It is important to understand the lambing pattern and distribution of lamb birth weight in sheep for assessing their reproductive efficiency and overall productivity. Sheep in temperate regions usually have a seasonal breeding pattern, while the presence of rams in tropical flocks often results in lambing occurring throughout the year ,23. Our The study showed that both local and Dorper crossbred ewes had similar seasonal lambing patterns, with 39% of the ewes giving birth during the Dry season while 33% gave birth during the main rainy season. This suggests that a larger number of ewes in both breeds entered estrus during the rainy season . These f3.1.23.1.2.1The litter size at birth (LSB) is a crucial factor in measuring the reproductive performance of sheep. Our study found an overall birth litter size of 1.09 ± 0.03 3585) . We obse85 . We oThere are several factors that can affect the size of a litter when sheep give birth. These include ovulation rate, uterine capacity, age at first lambing, parity, and the body condition of the ewe ,37. By i3.1.2.2P > 0.05, respectively), indicating that introducing Dorper genetics did not have a major impact on the number of lambs weaned compared to the local breed. When compared to previous studies, our litter size at weaning values was slightly lower than those reported by Ref. [The number of lambs in a litter at weaning (LSW) is an important factor in determining the success of reproduction and survival rates. In our research, the average litter size at weaning was found to be 0.95 ± 0.30 . Interes by Ref.  for Aber by Ref.  for hairOur study found that birth year and location significantly impact litter size at weaning (LSW) (P < 0.001), indicating that temporal and spatial factors are crucial in determining LSW. The differences in LSW across various birth years and locations can be attributed to the varying environmental conditions, management practices, and other location-specific factors. However, our study did not find a significant effect of dam genotype, parity of the dam, and lambing seasons on LSW (P > 0.05), suggesting that their influence on LSW may be relatively limited in our specific context. Our findings provide valuable insights into litter size at weaning in both local and Dorper crossbred sheep. Interestingly, there were no significant differences in LSW between the two breeds, indicating that the introduction of Dorper genetics did not have a substantial impact on LSW. Our results emphasize the importance of considering birth year and location when assessing reproductive performance. Further investigation into the underlying causes and potential management strategies can help improve LSW and enhance overall productivity in sheep farming.3.1.3The age at which sheep give birth for the first time, known as Age at First Lambing (AFL), is an important reproductive factor that reflects how efficient sheep production systems are. Our study found that the overall AFL was 15.51 months . InteresWe did not observe any significant effects of lambing year or season on the AFL (P > 0.05), indicating that these factors did not substantially influence the age at which the ewes gave birth to their first lamb in our population. Our findings align with previous reports from tropical regions by various authors ,41, whicOur study found that indigenous local sheep have an average age at first lambing (AFL) of 14.69 months, which is slightly higher than what other authors have reported for local sheep breeds in different regions of Ethiopia. For example, Gumuz sheep have an AFL of 13.67 months; , Afar sh3.1.4In the study we conducted, we examined the lambing interval (LI) of local and Dorper crossbred sheep. LI is an important factor in determining the reproductive effectiveness of a ewe flock. Our findings showed that the overall LI was 9.36 ± 2.11 months . Local e•AFL , LI •Lambing season: Dry-Period (October–January), Long-Rain (June–September), Short-Rain (February–May)•ARR , Index-I After analyzing values over different seasons, we discovered slight variations. During the dry, major rainy, and minor rainy seasons, the lambing intervals were 9.56 ± 0.28, 8.98 ± 0.28, and 9.47 ± 0.28 months, respectively. Although these differences were not statistically significant, our findings suggest that seasonal variations may have some influence on the lambing interval. Our study offers valuable insights into the lambing interval of local and Dorper crossbred sheep in the study area. These findings emphasize the significance of considering genetic factors, environmental conditions, and management practices when striving to improve reproductive efficiency and lambing intervals in sheep flocks. Further research is necessary to explore additional factors that may impact the lambing interval, such as nutrition, health status, and hormonal regulation, in order to develop targeted strategies for enhancing reproductive performance in various sheep production systems.3.23.2.1In the study, it was found that the average number of lambs per ewe per year was 1.47 . During The ARR values obtained for local and Dorper crossbred sheep  were lower than the reported number of lambing per ewe per year for Abera sheep (1.9) by Ref. . However3.2.2This study evaluated the productivity of ewes in terms of lamb rearing using three annual production indices: Index-I, which measured the kilogram of lambs reared to 90 days; Index-II, which measured the kilograms of lambs reared per kilogram of ewe postpartum weight; and Index-III, which measured the kilograms of lambs reared per kilogram of ewe metabolic weight. The study found that the overall productivity indices were: Index-I: 19.55 kg, Index-II: 0.76 kg, and Index-III: 1.82 kg .Table 3LThe body weight of lambs weaned was similar between the local and Dorper crossbred ewes, with weights of 20.91 kg and 20.16 kg, respectively. Although not statistically significant, the local ewes showed slightly better performance, which could be attributed to their slight advantages in LSB (litter size at birth) and LI . In another study conducted by Ref.  on Karak4In this study, it was discovered that both local and Dorper crossbred ewes are capable of lambing throughout the year. The distribution of lambing was found to range from 6% in July to 13% in October. While the majority of lambing occurred during the dry season (39%), there was no clear seasonality in lambing for either breed. It was noted that Dorper crossbred ewes performed well under a smallholder low-input production system, which is a great advantage of the breed. In contrast, other exotic breeds may not survive under such conditions. Environmental factors were found to have a significant impact on litter size and other productivity indices, but the ewe genotype did not. The results suggest that local ewes exhibited slightly higher productivity than the Dorper crossbred ewes, possibly due to their smaller size and more favorable lambing. However, it was noted that further improvements in management practices for Dorper crossbred ewes could enhance productivity.Ayele Abebe: Conceived and designed the experiment; performed the experiment; acquisition of data; analyzed and interpreted the data; contributed materials; wrote the paper; critically revised the paper; final approval of the version to be published. Gebreyohannes Berhane and Aynalem Haile: Designed the experiment; analyzed and interpreted the data; contributed materials; guided the project; wrote the paper, and final approval of the version to be published. Solomon Gizaw and Tesfaye Getachew: Conceived and designed the project, performed the experiment, analyzed and interpreted the data; and wrote the paper; critically revised the paper; final approval of the version to be published. All authors have read and agreed to the published version of the manuscript.10.13039/501100013249Agricultural Research Institute), 10.13039/501100004535EIAR , 10.13039/501100007941Addis Ababa University10.13039/100011523College of Veterinary Medicine and Agriculture (CVMA), and, International 10.13039/501100013249Agricultural Research Institute in Dry Areas (ICARDA).This work was supported by the Ethiopia Sheep and Goat Productivity Improvement Program (ESGPIP), ARARI (Amhara All data generated or analyzed during this study can be available on request to the corresponding author.The manuscript does not contain clinical studies or patient data.No additional information is available for this paper.Not applicable.The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.


It is essential to sustain global wheat production by utilizing accessions in wheat breeding. Among the traits associated with awn color and ear color that showed a high positive correlation, a SNP located on chr1B was significantly associated with both traits. Next, GS evaluated the prediction accuracy using six predictive models , and random forest) and various training populations (TPs). With the exception of the SVM, all statistical models demonstrated a prediction accuracy of 0.4 or better. For the optimization of the TP, the number of TPs was randomly selected  or divided into three subgroups  based on the subpopulation structure. Based on subgroup-based TPs, better prediction accuracy was found for awn color, culm color, culm length, ear color, ear length, and leaf width. A variety of Korean wheat cultivars were used for validation to evaluate the prediction ability of populations. Seven out of ten cultivars showed phenotype-consistent results based on genomics-evaluated breeding values (GEBVs) calculated by the reproducing kernel Hilbert space (RKHS) predictive model. Our research provides a basis for improving complex traits in wheat breeding programs through genomics assisted breeding. The results of our research can be used as a basis for improving wheat breeding programs by using genomics-assisted breeding.The agricultural traits that constitute basic plant breeding information are usually quantitative or complex in nature. This quantitative and complex combination of traits complicates the process of selection in breeding. This study examined the potential of genome-wide association studies (GWAS) and genomewide selection (GS) for breeding ten agricultural traits by using genome-wide SNPs. As a first step, a trait-associated candidate marker was identified by GWAS using a genetically diverse 567 Korean (K)-wheat core collection. The accessions were genotyped using an Axiom Genetic improvements are urgently required in wheat in order to achieve better quality, higher yields, better adaptation to diverse environments, tolerance to biotic stresses and to meet the needs of a growing population as well as the effects of global climate change  with the K-wheat core collection (CC) with genetic diversity for ten agricultural traits. In the first step, a mini core collection (miniCC) was constructed based on SNP markers across the Kwheat genome. We then used the miniCC to identify trait-associated markers using the fixed and random model circulating probability unification (FarmCPU). The third step involved evaluating the prediction accuracy with the CC using various compartmentalized training sets and statistical models. This study will serve as a foundation for the development of improved wheat varieties that are more efficient than conventional breeding methods.22.1http://genebank.rda.go.kr/). Based on 37 simple-sequence repeat (SSR) markers, this CC includes 567 accessions from 49 countries. (The K-wheat core collection (CC) reported in previous studies was used as a training population for this study . The CC 2.2® 35k breeders SNP array  . SNP callings were performed using modified versions of Affymetrix Power Tools (APT) and SNPolisher™ to account for the wheat genome’s specificity. Genotype scoring was performed in Affymetrix Genotyping Console using recommended QC metrics    to screell rate) . Among 3Genocore  and Core2.3STRUCTURE 3.4.0 software  was used2.4Agricultural traits of 567 accessions were measured at the National Institute of Crop Science research field . Ten agricultural traits were measured from 2018 to 2019, and the accumulated data was quantified for each trait. Agricultural traits were: awn color (AC), awn length (AL), culm color (CCL), culm length (CL), ear color (EC), ear length (EL), leaf length (LL), leaf width (LW), days to heading (HD), and days to maturity (MD).The bar plot depicts the phenotypic data distribution for all ten traits. Correlation analyses between phenotypes were performed using Pearson correlation coefficients of mini-tab 16.2.4 software . The phe2.5P > 3 was used to state significant marker-trait associations. Significant SNPs were annotated using Variant Effect Predictor of Ensembl-plants.Association analysis was performed using the FarmCPU method in the Genome Association and Prediction Integrated Tool (GAPIT) R package . A falsehttps://www.ncbi.nlm.nih.gov/genbank/).In order to find each trait-associated candidate gene, a gene region of up- and down-stream of 500 kb flanking sequences was secured in a significant SNP. For the flanking sequences of significant SNPs, the Basic Local Alignment Search Tool (BLASTx) analysis was performed using the National Center for Biotechnology Information’s (NCBI) nr protein database (confined to Viridiplantae) as a subject , least absolute shrinkage and selection operator (LASSO), random forest regression (RF), support vector machine (SVM), and reproducing kernel Hilbert space (RKHS) models widely used in various crops were evaluated and comparatively analyzed. All models are embedded in the R package Breed Wheat Genomic Selection Pipeline (BWGS) . Bayes AIn order to confirm the prediction ability according to the TP, the accessions included in the CC were divided into randomly selected subgroups or subgroups based on genetic backgrounds. First, the randomly selected subgroups were repeated ten times by selecting as many individuals as 10% (56 accessions), 30% (170 accessions), 50% (284 accessions), 70% (397 accessions), and 100% (567 accessions) of the CC. In order to see the differences according to the genetic backgrounds, three subgroups divided based on the results of the population structure analysis were used as training populations.2.7® 35k breeders SNP array. The phenotype data were measured by the NICS  from 2018 to 2019. The prediction ability was verified through correlation analysis between the GEBV and the measured values of the breeding population. The bwgs.predict, the function of the R package BWGS, was used for verification.Thirty-five Korean wheat cultivars were used to verify the estimated prediction accuracy. The genotype data of the breeding population was obtained with an Axiom33.1® 35k breeders SNP array  to construct the K-wheat mini CC and to re-analyze subpopulation structures. Since the original CC was constructed based on 37 SSR markers, the ability to scan the entire genome would be weak. Instead, the mini CC may enhance the power of predictive breeding because the 35k SNP array may efficiently cover the whole genome of bread wheat. Since SNP calling was not made in nine out of 576 accessions, the SNP data of 567 accessions was used for downstream analyses. A total of 35,153 SNPs were obtained through a 35K wheat DNA array. Across all the wheat chromosomes, an average of approximately 1,597 SNPs were identified in each chromosome. In terms of SNP distribution by chromosome, the 4D chromosome had the smallest number (828), and the 2D chromosome had the largest number . When filtering based on the MAF of 0.05, 27,598 SNPs were determined. Even after filtering, the 4D chromosome had the smallest number of SNPs, and the 2D chromosome had the largest  of ten traits was conducted using FarmCPU models Figure 53.5kat2 gene was annotated, and in the culm length, the amp gene and glb3 gene were annotated. As for the leaf width, the NAC domain-containing protein involved in growth and development was identified. For significant SNPs related to the days to maturity trait, the pp1 gene and the tet gene were annotated. All the genes were somehow related to traits, which will be discussed further in the next section.Candidate genes were identified for the significant SNPs associated with eight traits Table 1.3.62) of ten agricultural traits used for genomic selection are shown in The narrow-sense heritabilities . The prediction ability was determined by correlating GEBVs with phenotypic data, which is an actual observed value. For the TP for verification, the case where the whole CC was used as a TP and three subgroups based on the subpopulation structure were used. The prediction ability of CC-sub 3 was the highest. A comparison between the models confirmed the prediction ability of 0.49, 0.52, and 0.47 in GBLUP, RKHS, and RF, respectively Figure 8The GEBV of the RKHS model to CC-sub 3, with the highest prediction accuracy, and BLUP of the actual phenotype were compared Table 3.4Wheat is a major crop, and various varieties are grown in many countries. Breeding requires the development of varieties with characteristics that breeders value as necessary, such as increased grain yield, adaptation to climate change, and disease resistance. The first step in developing these breeds is to secure diverse individuals. Wheat diversity panels, such as core collections, were developed to understand populations’ genetics and structure. A variety of phenotypic variations offered by those panels could be used as breeding resources to develop markers or be directly applied for conventional selective breeding. Recently, various populations with phenotypic variations have been used for predictive breeding with advanced statistical models and computational resources to deal with big genomic data.® 35k breeders SNP array  for the SNPs to cover the entire wheat chromosomes, building the K-wheat mini CC with 247 accessions. A CC corresponds to about 30% of the total, and a mini CC to about 12% of the total. When the CC and the mini CC were divided by geographic origins, it was confirmed that they were composed of a certain percentage (According to the Balfourier et al. , a core To obtain useful information about the genetic diversity and population structure of the CC and mini CC, we divided them into three and six subgroups based on the population structure analysis Figure 3-8.However, candidate SNPs estimated to be significant in our study require additional validation (amp gene, a disease resistance-related gene that plays an important role in the immune system, and the glb gene, which is involved in growth development and stress response by participating in plant oxygen supply. In days to maturity, the pp1 gene (tet gene (NAC gene family, one of the strongest transcription factor families involved in various processes such as development, aging, and response to environmental stress (agc gene involved in response to environmental stress and immunoregulation (We obtained phenotypic data of ten agronomically important traits. First, association analysis using the FarmCPU model was conducted, resulting in 19 SNPs significantly associated with those traits. Significant SNPs associated with traits were selected based on -log 10 P > 3. The Bonferroni correction and FDR correction to avoid false positive or false negative results are very strict. Therefore, it is difficult to select complex traits and quantitative traits based on the existing P-value threshold of 5 × 10lidation . A high lidation . Culm lepp1 gene  and tet tet gene  involvedl stress . The siggulation . In mostSignificant differences in phenotypes according to alleles of SNPs were confirmed. Accessions with the A allele of SNP AX-94454667 had yellow-white to yellow in awn color and ear color. It was confirmed that accessions with the C allele ranged from brown to reddish-brown in both traits. In days to heading, it was confirmed that accessions with the A allele of SNP AX-94881841 were about nine days earlier. The awn length confirmed that the subjects with the T allele of SNP AX-94613491 were 2 cm longer on average. We identified significant SNPs associated with eight previously unknown agronomic traits. However, further studies are needed to validate the markers detected in this study using other populations and environments.Several researchers have reported genomic selection studies in wheat, but most have used advanced or preliminary breeding lines as a TP . HoweverNext, the prediction accuracy according to TPs was investigated. It is known that prediction accuracy increases with a large number of training populations. However, it was reported that the genetic diversity of the training population affects prediction accuracy . TherefoFinally, verification was conducted to determine whether the CC’s GS model applied to the validation population. Validation was performed only for the days to heading trait. As a result of applying the validation population consisting of 35 breeding lines to six models, it was possible to confirm the prediction ability of 0.4 or more in the CC-sub 3 training population. Based on the results from previous studies that a prediction accuracy greater than 0.3 would be sufficient to apply genomic selection , our stuhttps://www.ebi.ac.uk/ena/browser/view/PRJEB60428.The data presented in the study are deposited in the European Nucleotide Archive repository, accession number PRJEB60428 Conceptualization, YK and CK; methodology, YK, KM, JK, and C.K.; software, YK; validation, YK, CC, and CK; formal analysis, YK; investigation, KM, JK, and CC: resources, JK, KM,and CC; data curation, YK; writing—original draft preparation, YK; writing—review and editing, YK and CK; visualization, YK; project administration, CK. All authors contributed to the article and approved the submitted version.


Hevea brasiliensis) is grown in tropical regions and is the major source of natural rubber. Using traditional breeding approaches, the latex yield has increased by sixfold in the last century. However, the underlying genetic basis of rubber yield improvement is largely unknown. Here, we present a high‐quality, chromosome‐level genome sequence of the wild rubber tree, the first report on selection signatures and a genome‐wide association study (GWAS) of its yield traits. Population genomic analysis revealed a moderate population divergence between the Wickham clones and wild accessions. Interestingly, it is suggestive that H. brasiliensis and six relatives of the Hevea genus might belong to the same species. The selective sweep analysis found 361 obvious signatures in the domesticated clones associated with 245 genes. In a 15‐year field trial, GWAS identified 155 marker–trait associations with latex yield, in which 326 candidate genes were found. Notably, six genes related to sugar transport and metabolism, and four genes related to ethylene biosynthesis and signalling are associated with latex yield. The homozygote frequencies of the causal nonsynonymous SNPs have been greatly increased under selection, which may have contributed to the fast latex yield improvement during the short domestication history. Our study provides insights into the genetic basis of the latex yield trait and has implications for genomic‐assisted breeding by offering valuable resources in this new domesticated crop.The rubber tree ( Hevea brasiliensis Muell. Arg, 2 n = 36) is the most important source of natural rubber (NR), a widely used polyisoprene material. More than 90% of NR in the world is produced by rubber trees . Rubber trees are widely planted in Southeast Asia, West Africa and South America (approximately 13.3 million hectares). Rubber trees have become important sources of revenue for developing countries in these regions. Traditionally, the Hevea genus is believed to include 10 species . The original Wickham stock was collected in only one site . It was observed that, following one century of directional selection, a low level of genetic diversity might hinder yield improvement in the Wickham genotype. To overcome this limitation, several rounds of wild germplasm collections have been conducted. However, utilization is, thus far, restricted due to the significantly low average yield of wild germplasms  accounted for 71.05% of the whole genome, including 41.58% Gypsy and 6.53% Copia retro‐elements . Long terminal repeats  was 5  decay rate and nucleotide diversity (π) were determined in 34 wild accessions and 34 randomly selected Wickham clones. A short LD pairwise distance  and a low baseline were observed  was inferred to be 0.1918  and low nucleotide diversity (π). The top 5% threshold was set for FST and πwild/πWickham to screen the potential regions that had undergone a positive selection. A total of 361 loci were found in the regions that displayed positive selection in the Wickham clones (Z(FST) ≥ 1.92; log2 (πwild/πWickham) ≥1.59)  Figure . In tota) Figure , in whic) Figure . These nFST and π ratio (wild/Wickham) were carefully investigated, and a 120‐Kb fragment was identified on Chr4 (290001–410000) containing 51 nsSNPs  were inferred to be 3.1 and 2.27, respectively , suggesting that homozygous SNPs in this block constitute a haplotype with underlying functions that have contributed to the rubber tree domestication.The genomic regions with high s Figure . The reget al., P‐value of 1.60 × 10−7 was set as the significance threshold after a Bonferroni correction  were detected , HB8G00577  and HB10G01277  , indicating the close linkage of the SNPs to these alleles  with the significant latex yield associated SNP  biosynthesis and are transported from the source tissues (leaf) to the sinks (laticifer) and utilized through glycolysis  Figure . We furts Figure . The accs Figure . The HB1P Figure . The accP Figure .et al., et al., et al., et al., HB7G00777 gene, encoding the final enzyme of ethylene biosynthesis, 1‐aminocyclopropane‐1‐carboxylate oxidase (ACO), was found in proximity with Chr7‐13019105. An SNP (Chr7‐13019105) causing a missense mutation (Leu89 to Phe) at 267 nt of the cDNA sequence was found. Compared with wild accessions containing T/T (7), T/G (11) and GG (16) genotypes, all the Wickham clones harboured a G/G (107) genotype. Moreover, the latex yield in the accessions carrying the G/G genotype was significantly higher than in the accessions carrying a T/T and T/G genotypes , were found in proximity with to two other strong association signals . In HB4G01344, two missense SNPs were found, resulting in the change of Thr204 to Ile and Lys132 to Arg, respectively. The Wickham clones exhibited significantly higher frequencies of the A/A (93/107) and T/T (102/107) genotypes at these two alleles. Moreover, the latex yield in the accessions carrying the A/A or T/T genotypes was significantly higher than the accessions carrying other genotypes  between the significant SNPs and the missense alleles were evaluated and a very close linkage was found  were assessed by transactivation activity tests using dual‐luciferase assays in Nicotiana benthamiana leaves. Each gene contains nonsynonymous alleles resulting in two variants with amino acid changes of Lys132Arg (Hb4G01344) and Ala49Pro (Hb10G01564) respectively. A synthetic AP2/ERF responsive promoter  was used to drive firefly luciferase (FLUC) genes in the pGreenII 0800‐LUC plasmid. The reporter vector was co‐infiltrated into N. benthamiana leaves with effector vectors harbouring Hb4G01344 and Hb10G01564 gene variants  than their counterparts carrying Lys132. For Hb10G01564, the homozygous allele variant carrying Pro49 also exhibited significantly strong transactivation properties when compared to the Ala49 allele variant  was observed, and many hybrids were produced. This phenomenon raises a debate about whether the Hevea genus is a superspecies or whether these differentially taxonomically assigned species actually belong to the same species. Here, we provide molecular evidence to show that the six ‘relative species’ are highly likely the same species as Hevea brasiliensis.Traditionally, it was believed that the et al., Hevea , elucidates the genome evolution and population structure and provides a genetic variation map for 147 wild and cultivated clones. We identified 361 selection signatures and 155 loci associated with latex yield and revealed the contribution of the homozygosity of causal nonsynonymous SNPs on the latex yield trait improvement. Notably, six genes related to sugar transport and metabolism, and four genes related to ethylene biosynthesis and signalling were associated with latex yield. These findings provide insights into the genetic basis of the latex yield trait and offer valuable resources for improving the rubber tree and other newly domesticated crops.de novo genome sequencing. The accession was collected from the Vila Bela district, Moto Crosso States, Brazil. The accession is characterized by low heterozygosity. One hundred and seven Wickham clones, 34 IRRDB 1981’ wild germplasm accessions and six species of the Hevea genus were used for a population study. The wild germplasms were primarily collected from Acre (AC), Moto Crosso (MT) and Rondonia (RO) in Brazil (IRRDB 1981 expedition). We selected 11 RO, 10 MT, 11 AC and two other accessions to study the germplasm evolution. These accessions represent the genetic diversity in the regions of Hevea origin and the major rubber tree plantations. The rubber trees are planted in the National Rubber Tree Germplasm Repository .The rubber tree wild germplasm (IRRDB accession no.: MT/VB/25A 57/8) was used for et al., Illumina sequencing, nanopore sequencing and optical genome map construction were performed at Nextomics, China. High molecular weight DNA was extracted, and a nanopore sequencing library was constructed per the protocol instructions. Following this, the sequencing was conducted on the PromethION platform . Illumina Sequel sequencing was performed on the NovaSeq 6000 platform. The Bionano optical genome map was constructed by capturing the images using methods outlined by the NanoChannel Array technology . The Hi‐C library was prepared following a previously reported protocol  resequencing was conducted at Biomarker, China. The sequencing process was performed on a NovaSeq 6000 platform according to the standard protocol outlined by Illumina. The raw reads were filtered to eliminate the reads with adapters . The clean reads were then mapped to the compiled reference genome using BWA  was determined. The subgroup value (k) was preset for the SNPs selected using PLINK2 v2.00a3LM to construct the neighbour‐joining tree  tool was used to display the neighbour‐joining tree. PCA for all SNPs was conducted using EIGENSOFT  were calculated in 100‐Kb sliding windows with 10‐Kb steps using VCFtools v0.1.16  (Maere Agrobacterium strain GV3101 (pSoup‐P19). Co‐infiltration was performed by mixing equal volumes of Agrobacterium strains harbouring the effector and reporter vectors. FLUC and RLUC activities were measured after 48 h of infiltration using the dual‐luciferase assay kit  according to the manufacturer's instructions. The signal was recorded with Multimode Plate Reader . The transcriptional activity was calculated by the FLUC and RLUC ratios. Biological triplicates were performed for each assay.For transcriptional activity analysis of gene variants, the whole coding fragments of effector genes and the promoters of the reporter constructs were synthesized at Tsingke Biotechnology Co.  and subcloned into pCAMBIA2301 and pGreenII 0800‐LUC vectors, respectively. The reporter vector contains a firefly luciferase (FLUC) driven by three copies of the GCC and CRT binding elements (3 × GCC‐CRT) and a minimal TATA region of the CaMV 35S promoter. A renilla luciferase (RLUC) driven by the full CaMV 35S promoter in the pGreenII 0800‐LUC vector was used to normalize transient transformation efficiency. Each plasmid was transformed into the The authors declare that they have no competing interests.HC designed the project, conducted the population and the GWAS study, and coordinated the genome sequencing and evolution study. YH conducted the field trial and collected latex yield data. YH, MT, XZ and HH maintained the germplasm accessions. XS, QY, SF and XW performed the study of genome collinearity and gene family expansion. ZD, ZA and WW collected the samples. TW performed the biochemical analysis. HC wrote the manuscript. XW and XS read the manuscript.Table S1. The heterozygosity of the resequenced germplasms.Table S2. Nanopore sequencing libraries and data statistics.Table S3. The statistics of assembled contigs and scaffolds.Table S4. Statistics of Hi‐C Paired‐end Reads.Table S5. Characteristics of the wild rubber tree genome, and compared with the previous published rubber tree genomes.Table S6. Statistics of 18 pseudomolecules.Table S7. Statistics of CEGMA assessment.Table S8. Statistics of BUSCO assessment.Table S9. Statistics of NGS mapping results to the genome.Table S10. Statistics of single nucleotide accuracy of the genome.Table S11. Statistics of Nanopore reads mapping results to the genome.Table S12. The alignment results of the Hevea genome to NT (Nucleotide Sequence) Database.Table S13. Classification of TE in rubber tree genome.Table S14. The protein coding gene prediction results.Table S15. Comparison of the coding genes between other plants.Table 16. Non‐coding RNA in rubber tree genome.Table S17. Functional annotation of the rubber tree genes.Table S18. Number of homologous gene pairs within and between genomes.Table S19. Genes used for gene family analysis in each species.Table S20. The 75 single copy gene families among 9 species.Table S21. The origin of germplasms used for population study.Table S22. Germplasms used in population study and statistics of population resequencing data.Table S23. SNPs distribution on chromosomes.Table S24. SNP number of effects by regions.Table S25. Transitions and tranversions ratio.Table S26. Number of loci under positive selection on chromosomes.Table S27. The annotation of 245 genes under positive selection in cultivar clones.Table S28. 580 positive selected SNP sites that caused missense mutation in amino acid in 162 genes.Table S29. Genes with nsSNPs in Chr4:290001‐410000.Table S30. BLUP value of latex yield data collected from 2017‐2021 when the trees are at 10 years old.Table S31. Significant SNP signals for the latex yields (‐log10P >6.79).Table S32. Genes associated with latex yield and under artificial selection.Click here for additional data file.Note S1. Reference genome sequencing and assembly.Note S2. Reference genome annotation.Note S3. Comparative genomic analysis.Note S4. Gene family analysis.Note S5. Re‐sequencing and phylogenetic analysis.Figure S1. Heterozygosity estimation survey basing on kmer‐17 analysis. The kmer k‐mer occurrence plot of wild germplasm MT/VB/25A 57/8 indicated a very low heterozygosity rate about 0.462%.Figure S2. Kmer‐17 distribution curve of 50× Sequel WGS data.Figure S3. The ONT reads length distribution.Figure S4. The accumulative length distribution of assembled contigs.Figure S5. Hi‐C interaction heatmap of 18 clusters in Hevea brasiliensis genome.Figure S6. CEGMA assessment results.Figure S7. BUSCO assessment results.Figure S8. Distribution between GC content and sequencing depth.Figure S9. Distribution of divergence rate of each type of transposable element (TE) in the rubber tree genome assembly based on homology‐based prediction using RepeatModeler.Figure S10. Species distribution of NR annotation from the genes of Hevea brasiliensis.Figure S11. KEGG pathway classification of genes in Hevea brasiliensis genome.Figure S12. KOG functional classification of genes in Hevea brasiliensis genome.Figure S13. Gene ontology classification of genes in Hevea brasiliensis genome.Figure S14. Venn diagram of rubber tree genes annotation between NR, GO, KOG, KEGG, Swissprot databases.Figure S15. Cross‐species comparisons in the length distribution of genes, CDSs, exons, introns, and the numbers of exons and introns.Figure S16. Synteny plot of the rubber tree genome.Figure S17. Ks curve of Cassava (A), Rubber tree (B) and Poplar (C).Figure S18. Synteny plot between the rubber tree and M. esculenta genome.Figure S19. Genome collinearity and gene family analysis in rubber tree genome.Figure S21. Evolutionary tree of gene family expansion and contraction.Figure S22. Diagram showing the program for the rubber tree conventional breeding.Figure S23. Statistics of polymorphisms loci identified from the population.Figure S24. The distribution of SNP mutation types in the rubber tree accessions.Figure S25. The annotation of SNP mutations.Figure S26. The Percentage variance explained values of each component from PCA results.Figure S27. (CV) plot for K = 2 to K = 10 in rubber tree accessions using Admixture.Figure S28. Manhattan plot of genome‐wide nucleotide diversity (π) of Wickham accessions on each of the 18 chromosomes.Figure S29. Manhattan plot of genome‐wide nucleotide diversity (π) of Wild accessions on each of the 18 chromosomes.Figure S30. Manhattan plot of genome‐wide reduction of diversity (ROD) between wild and Wickham accessions on each of the 18 chromosomes. Dotted line, 1% threshold.Figure S31. Manhattan plot of genome‐wide Fst between wild and Wickham accessions on each of the 18 chromosomes. Dotted line, 1% threshold.Figure S32. Linkage disequilibrium of all SNPs in the selective region on Chr4 (290001–410000) corresponding the red dots on Figure 5B.Figure S33. Q‐Q plot displaying the GWAS results for latex yield using a SUPER model.Figure S34. Manhattan plot displaying the GWAS results for latex yield using a SUPER model. The threshold for significance is P‐value < 1.60e‐07 (‐log10P > 6.7).Figure S35. Q‐Q plot displaying the GWAS results for latex yield using: A, GLM; B, MLM; C, MLMLM; D, CMLM; E, ECMLM; F, Blink; G, FaST; H, EMMA; and I, EMMAx models respectively.Click here for additional data file.