Genome-wide association mapping and genomic prediction of stalk rot in two mid-altitude tropical maize populations

Maize stalk rot reduces grain yield and quality.Information about the genetics of resistance to maize stalk rot could help breeders design effective breeding strategies for the trait.Genomic prediction may be a more effective breeding strategy for stalk-rot resistance than marker-assisted selection.We performed a genome-wide association study(GWAS)and genomic prediction of resistance in testcross hybrids of 677 inbred lines from the Tuxpe?o and non-Tuxpe?o heterotic pools grown in three environments and genotyped with 200,681 single-nucleotide polymorphisms(SNPs).Eighteen SNPs associated with stalk rot shared genomic regions with gene families previously associated with plant biotic and abiotic responses.More favorable SNP haplotypes traced to tropical than to temperate progenitors of the inbred lines.Incorporating genotype-by-environment(G×E)interaction increased genomic prediction accuracy.

Natural variation in maize gene ZmSBR1 confers seedling resistance to Fusarium verticillioides

Maize seedling blight caused by Fusarium verticillioides is a widely occurring maize disease,but the genetics and mechanisms of resistance are not well understood.In this study,GWAS performed by MLM and 3VmrMLM identified 40 and 20 QTNs,associated with seedling blight resistance.These methods identified 49 and 36 genes,respectively.Functional verification of candidate gene ZmSBR1 identified by both methods showed that the resistance of a mutant line to seedling blight decreased by 0.37 grade points after inoculation with F.verticillioides,compared with the WT.The length of the stem rot lesion caused by F.verticillioides increased by 86%in mutant seedlings,and the relative length of the adult plant stalk rot increased by 35%in mutant plants compared to the wild type after inoculation with Fusarium graminearum.Transcriptome analysis showed that expression of defense-related genes after inoculation was down-regulated in the mutant compared to the wild type,synthesis of secondary metabolites associated with resistance was reduced,and the immune response triggered by PAMP decreased,resulting in decreased resistance of mutant maize seedlings.Candidate gene association analysis showed that most maize inbred lines carried the susceptible haplotype.A functional PCR marker was developed.The results demonstrated that ZmSBR1 conferred resistance to multiple Fusarium diseases at the seedling and adult growth stages and had important application value in breeding.

Genome-wide association study and genomic prediction of Fusarium ear rot resistance in tropical maize germplasm

Fusarium ear rot(FER)is a destructive maize fungal disease worldwide.In this study,three tropical maize populations consisting of 874 inbred lines were used to perform genomewide association study(GWAS)and genomic prediction(GP)analyses of FER resistance.Broad phenotypic variation and high heritability for FER were observed,although it was highly influenced by large genotype-by-environment interactions.In the 874 inbred lines,GWAS with general linear model(GLM)identified 3034 single-nucleotide polymorphisms(SNPs)significantly associated with FER resistance at the P-value threshold of 1×10^(-5),the average phenotypic variation explained(PVE)by these associations was 3%with a range from 2.33%to 6.92%,and 49 of these associations had PVE values greater than 5%.The GWAS analysis with mixed linear model(MLM)identified 19 significantly associated SNPs at the P-value threshold of 1×10^(-4),the average PVE of these associations was 1.60%with a range from 1.39%to 2.04%.Within each of the three populations,the number of significantly associated SNPs identified by GLM and MLM ranged from 25 to 41,and from 5 to 22,respectively.Overlapping SNP associations across populations were rare.A few stable genomic regions conferring FER resistance were identified,which located in bins 3.04/05,7.02/04,9.00/01,9.04,9.06/07,and 10.03/04.The genomic regions in bins 9.00/01 and 9.04 are new.GP produced moderate accuracies with genome-wide markers,and relatively high accuracies with SNP associations detected from GWAS.Moderate prediction accuracies were observed when the training and validation sets were closely related.These results implied that FER resistance in maize is controlled by minor QTL with small effects,and highly influenced by the genetic background of the populations studied.Genomic selection(GS)by incorporating SNP associations detected from GWAS is a promising tool for improving FER resistance in maize.

Using genomic data to improve the estimation of general combining ability based on sparse partial diallel cross designs in maize

Evaluation of general combining ability(GCA)is crucial to hybrid breeding in maize.Although the complete diallel cross design can provide an efficient estimation,sparse partial diallel cross(SPDC)is more flexible in breeding practice.Using real and simulated data sets of partial diallel crosses between 266 maize inbred lines,this study investigated the performance of SPDC designs for estimating the GCA.With different distributions of parental lines involved in crossing(called random,balanced and unbalanced samplings),different numbers of hybrids were sampled as the training sets to estimate the GCA of the 266 inbred lines.In this process,three statistical approaches were applied.One obtained estimations through the ordinary least square(OLS)method,and the other two utilized genomic prediction(GP)to estimate the GCA.It was found that the coefficient of determination of each approach was always higher than the heritability of a target trait,showing that the GCA for maize inbred lines could be accurately predicted with SPDC designs.Both the GP approaches were more accurate than the OLS,particularly in the scenario for a low-heritability trait with a small sample size.Additionally,prediction results demonstrated that a big sample of hybrids could greatly help improve the accuracy.The random sampling of parental lines had little influence on the average accuracy.However,the prediction for lines that never or seldom involved in crossing might suffer from much lower accuracy.

Genomic prediction of the performance of hybrids and the combining abilities for line by tester trials in maize

The two most important activities in maize breeding are the development of inbred lines with high values of general combining ability(GCA)and specific combining ability(SCA),and the identification of hybrids with high yield potentials.Genomic selection(GS)is a promising genomic tool to perform selection on the untested breeding material based on the genomic estimated breeding values estimated from the genomic prediction(GP).In this study,GP analyses were carried out to estimate the performance of hybrids,GCA,and SCA for grain yield(GY)in three maize line-by-tester trials,where all the material was phenotyped in 10 to 11 multiple-location trials and genotyped with a mid-density molecular marker platform.Results showed that the prediction abilities for the performance of hybrids ranged from 0.59 to0.81 across all trials in the model including the additive effect of lines and testers.In the model including both additive and non-additive effects,the prediction abilities for the performance of hybrids were improved and ranged from 0.64 to 0.86 across all trials.The prediction abilities of the GCA for GY were low,ranging between-0.14 and 0.13 across all trials in the model including only inbred lines;the prediction abilities of the GCA for GY were improved and ranged from 0.49 to 0.55 across all trials in the model including both inbred lines and testers,while the prediction abilities of the SCA for GY were negative across all trials.The prediction abilities for GY between testers varied from-0.66 to 0.82;the performance of hybrids between testers is difficult to predict.GS offers the opportunity to predict the performance of new hybrids and the GCA of new inbred lines based on the molecular marker information,the total breeding cost could be reduced dramatically by phenotyping fewer multiple-location trials.

Comparison of sequencing-based and array-based genotyping platforms for genomic prediction of maize hybrid performance

Genomic selection(GS)is a powerful tool for improving genetic gain in maize breeding.However,its routine application in large-scale breeding pipelines is limited by the high cost of genotyping platforms.Although sequencing-based and array-based genotyping platforms have been used for GS,few studies have compared prediction performance among platforms.In this study,we evaluated the predictabilities of four agronomic traits in 305 maize hybrids derived from 149 parental lines subjected to genotyping by sequencing(GBS),a 40K SNP array,and target sequence capture(TSC)using eight GS models.The GBS marker dataset yielded the highest predictabilities for all traits,followed by TSC and SNP array datasets.We investigated the effect of marker density and statistical models on predictability among genotyping platforms and found that 1K SNPs were sufficient to achieve comparable predictabilities to 10K and all SNPs,and BayesB,GBLUP,and RKHS performed well,while XGBoost performed poorly in most cases.We also selected significant SNP subsets using genome-wide association study(GWAS)analyses in three panels to predict hybrid performance.GWAS facilitated selecting effective SNP subsets for GS and thus reduced genotyping cost,but depended heavily on the GWAS panel.We conclude that there is still room for optimization of the existing SNP array,and using genotyping by target sequencing(GBTS)techniques to integrate a few functional markers identified by GWAS into the 1K SNP array holds great promise of being an effective strategy for developing desirable GS breeding arrays.

Kernel metabolites depict the diversity of relationship between maize hybrids and their parental lines

As the end products of cellular regulatory processes,metabolites provide the link between genotypes and phenotypes.Althoughmetabolites have been widely applied for functional gene detection and phenotype prediction in maize,there is little research focusing on the genetic information of metabolites per se.Here,we performed genetic analyses for the kernel metabolites of 11 parental inbred lines of six representative maize varieties,including Zhongdan 2,Danyu 13,Yedan 13,Zhengdan 958,Xianyu 355,and Suyu 16,as well as their 26 reciprocal hybrids.We identified a total of 208 metabolites in maize kernels using untargeted metabolite profiling technology.Both cluster analysis and principal component analysis indicated that kernel metabolites could distinguish hybrids from their parents.Analysis of variance further revealed that 163 metabolites exhibited significant differences between parents and hybrids,and 40 metabolites showed significant differences between reciprocal crosses.We also investigated the genetic effects and heterosis for each metabolite.By taking all hybrids into consideration,about two-thirds of all metabolites displayed overdominant with 36.8%and 31%of them displaying positive overdominant and negative overdominant,respectively.Besides,27.5%and 20.4%of all hybrid combinations showed significant mid-parent heterosis and over-parent heterosis,respectively.Our findings revealed that kernel metabolites exhibited the diversity of relationship between maize hybrids and their parental lines.Additionally,we identified 25 significant metabolicmarkers related to 11 agronomic traits using the LASSO method.Seven metabolic markers were associated with more than one trait simultaneously.These results provide a genetic basis for further utilization of metabolites in the genetic improvement of maize.

Genomic prediction of yield performance among single-cross maize hybrids using a partial diallel cross design

Genomic prediction(GP)in plant breeding has the potential to predict and identify the best-performing hybrids based on the genotypes of their parental lines.In a GP experiment,34 elite inbred lines were selected to make 285 single-cross hybrids in a partial-diallel cross design.These lines represented a mini-core collection of Chinese maize germplasm and comprised 18 inbred lines from the Stiff Stalk heterotic group and 16 inbred lines from the Non-Stiff Stalk heterotic group.The parents were genotyped by sequencing and the 285 hybrids were phenotyped for nine yield and yield-related traits at two locations in the summer sowing area(SUS)and three locations in the spring sowing area(SPS)in the main maizeproducing regions of China.Multiple GP models were employed to assess the accuracy of trait prediction in the hybrids.By ten-fold cross-validation,the prediction accuracies of yield performance of the hybrids estimated by the genomic best linear unbiased prediction(GBLUP)model in SUS and SPS were 0.51 and 0.46,respectively.The prediction accuracies of the remaining yield-related traits estimated with GBLUP ranged from 0.49 to 0.86 and from 0.53 to 0.89 in SUS and SPS,respectively.When additive,dominance,epistasis effects,genotype-by-environment interaction,and multi-trait effects were incorporated into the prediction model,the prediction accuracy of hybrid yield performance was improved.The ratio of training to testing population and size of training population optimal for yield prediction were determined.Multiple prediction models can improve prediction accuracy in hybrid breeding.

Astronomical forcing and sedimentary noise modeling of lake-level changes in the Middle Eocene Chezhen Sag,Bohai Bay Basin,eastern China

The accurate determination of geological age is a key to understanding the history and process of paleolake evolution and oil and gas exploration in continental lake basin.However,improving the accuracy of geological age has always been a difficult scientific problem.A 609-m-thick,continuous lacustrine mudstone and sandstone succession in Chezhen Sag(eastern China)provides an ideal middle Eocene sedimentary record for establishing a high-resolution stratigraphic chronology framework.Based on spectrum analysis and sliding window spectrum analysis of the natural gamma(GR)logging data of well Che 271(C271)in Chezhen Sag,the periods of 405 kyr and 40.1 kyr were filtered by a Gaussian bandpass filter,and a“floating”astrochronological time scale(ATS)was established.The total number of 405 kyr eccentricity cycles were 13.6 and 40.1 kyr obliquity cycles were 138 which recorded from the upper member 4(Es4U)to the member 3(Es3)of the Eocene Shahejie Formation,and the depositional duration was 5.53 Myr.Correlation Coefficient(COCO)analysis and evolutionary Correlation Coefficient(eCoCo)analysis found that the optimal sedimentary rate of different strata.Sedimentary noise simulation revealed the history of paleolake water changes in the Middle Eocene in the Chezhen Sag,according to which four sequences are divided.The study shows that the lake level change of Chezhen Sag in the middle Eocene shows prominent 1.2 Myr cycles and an antiphase well-coupled relationship with obliquity modulation.Finally,we propose a model to explain the relationship between the orbital cycle and lake level change in the continental lake basin.When the obliquity of the earth increases,the middle and high latitudes of the earth will be closer to the sun,the direct sunlight will be higher,and the meridional sunshine will increase,thus accelerating the evaporation process of lake basin water.When the seasonal changes are obvious(maximum period of 1.2 Myr ultra-long obliquity),this effect is more significant.The relative lake level change based on the restoration of high-precision ATS has significant scientific and economic value for understanding the vertical evolution of continental stratigraphic sequences and the formation and distribution of oil and gas resources.

The RppC-AvrRppC NLR-effector interaction mediates the resistance to southern corn rust in maize

Southern corn rust(SCR),caused by the fungal pathogen Puccinia polysora,is a major threat to maize pro-duction worldwide.Efficient breeding and deployment of resistant hybrids are key to achieving durable control of SCR.Here,we report the molecular cloning and characterization of RppC,which encodes an NLR-type immune receptor and is responsible for a major SCR resistance quantitative trait locus.Further-more,we identified the corresponding avirulence effector,AvrRppC,which is secreted by P.polysora and triggers RppC-mediated resistance.Allelic variation of AvrRppC directly determines the effectiveness of RppC-mediated resistance,indicating that monitoring of AvrRppC variants in the field can guide the rational deployment of RppC-containing hybrids in maize production.Currently,RppC is the most frequently deployed SCR resistance gene in China,and a better understanding of its mode of action is crit-ical for extending its durability.

A Teosinte-derived Allele of a MYB Transcription Repressor Confers Multiple Disease Resistance in Maize.

Natural alleles controlling multiple disease resistances (MDR) are valuable for crop breeding. However, only one MDR gene have been cloned in maize, and molecular mechanisms of MDR are not clear. By map-based cloning, we have cloned a teosinte-derived allele of a resistance gene, Mexicana lesion mimic 1 (ZmMM1), which has a lesion mimic phenotype and confers resistance to northern leaf blight (NLB), gray leaf spot (GLS) and southern corn rust (SCR). Strong MDR conferred by the teosinte allele is linked with the polymorphisms in the 3' untranslated region of the ZmMM1 gene that cause increased accumulation of ZmMM1 protein. ZmMM1 acts as a transcription repressor and negatively regulates transcription of specific target genes including ZmMM1-target gene 3 (ZmMT3), which functions as a negative regulator of plant immunity and associated cell death. The successful isolation of the ZmMM1 resistance gene will help not only in developing broad-spectrum and durable disease resistance but also in understanding the molecular mechanisms underlying MDR.

Paleosalinity and lake level fluctuations of the 3rd Member of Paleogene Shahejie Formation,Chezhen Sag,Bohai Bay Basin

The Chezhen Sag,located in the north-western Jiyang Depression,is one of the most important oil-bearing sags in the Bohai Bay Basin.Due to the low degree of exploration in the sag,paleosalinity and sedimentary environment of the sag in the 3rd Member of Paleogene Shahejie Formation(Es3)is not clear.Recovering the paleosalinity and lake level fluctuations is helpful for understanding organic matter rich rocks sedimentation.Therefore,a detailed geochemical,mineralogical and paleontological analysis of the Es3 in the Chezhen Sag was conducted.Index like Sr/Ba ratios,B/Ga ratios,equivalent boron content and methods concluding Adams'formula and Couch's method were adopted to reveal the paleo-salinity and lake level variations.The results indicate that the lower submember(Lower Es3)was deposited in a salt water with high salinity,accompanied by dry climate and transgression event.The middle submember(Middle Es3)and upper submember(Upper Es3)record a freshwater to brackish environment.The paleosalinity and paleoclimate changes are consistent with the global sea level variations.The type and content of sporopollen indicate a dry climate in Lower Es3,which further confirms the reliability of the reconstruction results of paleosalinity.Combined with the paleoclimate and previous marine paleontological evidence,we proposed that the high salinity period is associated with a high lake level and a large-scale transgression event in Lower Es3.According to salinities and corresponding Lake depths,we established a sedimentary environment variation model of the Es3 Member in Chezhen Sag.

Giant enhancement of second-harmonic generation from a nanocavity metasurface

Nonlinear plasmonic metasurfaces are compatible with complementary metal oxide semiconductor technology and highly promising for on-chip optical switching and modulations and nanoscale frequency conversions.However,the low nonlinearoptical response of metasurface devices limits their practical applications.To circumvent this constraint,we propose the design of a nanocavity plasmonic metasurface,in which the strong light localization in the nanocavity can be used to boost the efficiency of second-harmonic generation.Compared with the single-layer counterpart,experimental results show that the intensity of the second-harmonic waves in the nanocavity metasurface is enhanced by~790 times.The proposed nanocavity plasmonic metasurfaces in this work may open new routes for developing highly efficient nonlinear metacrystals for on-chip nonlinear sources,nonlinear image encryption,information processing,and so on.

Enhancing maize's nitrogen-fixing potential through ZmSBT3, a gene suppressing mucilage secretion∞

Maize(Zea mays)requires substantial amounts of nitrogen,posing a challenge for its cultivation.Recent work discovered that some ancient Mexican maize landraces harbored diazotrophic bacteria in mucilage secreted by their aerial roots.To see if this trait is retained in modern maize,we conducted a field study of aerial root mucilage(ARM)in 258 inbred lines.We observed that ARM secretion is common in modern maize,but the amount significantly varies,and only a few lines have retained the nitrogen‐fixing traits found in ancient landraces.The mucilage of the high‐ARM inbred line HN5‐724 had high nitrogen‐fixing enzyme activity and abundant diazotrophic bacteria.Our genome‐wide association study identified 17 candidate genes associated with ARM across three environments.Knockouts of one candidate gene,the subtilase family gene ZmSBT3,confirmed that it negatively regulates ARM secretion.Notably,the ZmSBT3 knockout lines had increased biomass and total nitrogen accumulation under nitrogen‐free culture conditions.High ARM was associated with three ZmSBT3 haplotypes that were gradually lost during maize domestication,being retained in only a few modern inbred lines such as HN5‐724.In summary,our results identify ZmSBT3 as a potential tool for enhancing ARM,and thus nitrogen fixation,in maize.

Sedimentary characteristics of lacustrine deep-water gravity flow in the third member of Paleogene Shahejie Formation in Dongying Sag,Bohai Bay Basin,China

Many types of sedimentary systems occur in the middle of the third member of the Shahejie Formation(E_(2)S_(3)^(2))of the Paleogene in the Dongying Sag east of the Bohai Bay Basin.Due to the topography and material supply,traction and gravity flow depositions are intertwined in this area,and the sand body types are complex and diverse,making it challenging to improve the accuracy of their description and prediction and restricting oil reservoir exploration and development.Therefore,this paper documents our systematic study of the sedimentary characteristics of the southern slope of Dongying Depression,the formation mechanism of different sand body types,and the prediction of sand body distribution.First,according to the coring well’s single-well facies and vertical rock sequence,nine single lithofacies types and five lithofacies association types were identified.Combined with the well logging facies marks of all wells,the depositional models of delta and gravity flow depositional systems were established in the study area.Then,the gravity flow was divided into slip,collapse,debris flow,and turbidity flow according to its development mechanism.Finally,the distribution law of the gravity flow sedimentary facies type was predicted.Gravity flow sliding deposits are primarily distributed near the delta front,slump and clastic flow deposits are distributed near the far slope,and turbidity current deposits are distributed at the far slope.With the gradual shrinkage of the water body in the north-west direction and the continuous advancement of the river delta,the gravity flow sand body gradually disappears in the late E_(2)S_(3)^(2) and transits to delta plain deposition.

Pollen self-elimination CRISPR–Cas genome editing prevents transgenic pollen dispersal in maize

Dear Editor,Genome editing with clustered regularly interspaced short palindromic repeats(CRISPR)–CRISPR-associated nuclease(Cas)-mediated technologies have revolutionized basic plant science and crop genetic improvement(Chen et al.,2019).Stable genetic transformation of CRISPR–Cas cassette(s)is the main approach to genome editing in planta.In many sexually reproducing plants,a major concern is the dispersal of genetically modified elements through pollen(Devos et al.,2005).Maize(Zea mays L.).