The genetic mechanism of heterosis utilization in maize improvement

Validation of SNP Markers for Diversity Analysis, Quality Control, and Trait Selection in a Biofortified Cassava Population

A validated marker system is crucial to running an effective genomics-assisted breeding program. We used 36 Kompetitive Allele-Specific PCR (KASP) markers to genotype 376 clones from the biofortified cassava pipeline, and fingerprinted 93 of these clones with DArTseq markers to characterize breeding materials and evaluate their relationships. The discriminating ability of the 36-quality control (QC) KASP and 6602 DArTseq markers was assessed using 92 clones genotyped in both assays. In addition, trait-specific markers were used to determine the presence or absence of target genomic regions. Hierarchical clustering identified two major groups, and the clusters were consistent with the breeding program origins. There was moderate genetic differentiation and a low degree of variation between the identified groups. The general structure of the population was similar using both assays. Nevertheless, KASP markers had poor resolution when it came to differentiating the genotypes by seed sources and overestimated the prevalence of duplicates. The trait-linked markers did not achieve optimal performance as all markers displayed variable levels of false positive and/or false negative. These findings represent the initial step in the application of genomics-assisted breeding for the biofortified cassava pipeline, and will guide the use of genomic selection in the future.

Natural variations of heterosis-related allele-specific expression genes in promoter regions lead to allele-specific expression in maize

BACKGROUND

Heterosis has successfully enhanced maize productivity and quality. Although significant progress has been made in delineating the genetic basis of heterosis, the molecular mechanisms underlying its genetic components remain less explored. Allele-specific expression (ASE), the imbalanced expression between two parental alleles in hybrids, is increasingly being recognized as a factor contributing to heterosis. ASE is a complex process regulated by both epigenetic and genetic variations in response to developmental and environmental conditions.

RESULTS

In this study, we explored the differential characteristics of ASE by analyzing the transcriptome data of two maize hybrids and their parents under four light conditions. On the basis of allele expression patterns in different hybrids under various conditions, ASE genes were divided into three categories: bias-consistent genes involved in basal metabolic processes in a functionally complementary manner, bias-reversal genes adapting to the light environment, and bias-specific genes maintaining cell homeostasis. We observed that 758 ASE genes (ASEGs) were significantly overlapped with heterosis quantitative trait loci (QTLs), and high-frequency variations in the promoter regions of heterosis-related ASEGs were identified between parents. In addition, 10 heterosis-related ASEGs participating in yield heterosis were selected during domestication.

CONCLUSIONS

The comprehensive analysis of ASEGs offers a distinctive perspective on how light quality influences gene expression patterns and gene-environment interactions, with implications for the identification of heterosis-related ASEGs to enhance maize yield.

High-quality genome assembly enables prediction of allele-specific gene expression in hybrid poplar

Poplar (Populus) is a well-established model system for tree genomics and molecular breeding, and hybrid poplar is widely used in forest plantations. However, distinguishing its diploid homologous chromosomes is difficult, complicating advanced functional studies on specific alleles. In this study, we applied a trio-binning design and PacBio high-fidelity long-read sequencing to obtain haplotype-phased telomere-to-telomere genome assemblies for the 2 parents of the well-studied F1 hybrid "84K" (Populus alba × Populus tremula var. glandulosa). Almost all chromosomes, including the telomeres and centromeres, were completely assembled for each haplotype subgenome apart from 2 small gaps on one chromosome. By incorporating information from these haplotype assemblies and extensive RNA-seq data, we analyzed gene expression patterns between the 2 subgenomes and alleles. Transcription bias at the subgenome level was not uncovered, but extensive-expression differences were detected between alleles. We developed machine-learning (ML) models to predict allele-specific expression (ASE) with high accuracy and identified underlying genome features most highly influencing ASE. One of our models with 15 predictor variables achieved 77% accuracy on the training set and 74% accuracy on the testing set. ML models identified gene body CHG methylation, sequence divergence, and transposon occupancy both upstream and downstream of alleles as important factors for ASE. Our haplotype-phased genome assemblies and ML strategy highlight an avenue for functional studies in Populus and provide additional tools for studying ASE and heterosis in hybrids.

QTL mapping for plant height and ear height using bi-parental immortalized heterozygous populations in maize

Introduction

Plant height (PH) and ear height (EH) are key plant architectural traits in maize, which will affect the photosynthetic efficiency, high plant density tolerance, suitability for mechanical harvesting.

Methods

QTL mapping were conducted for PH and EH using a recombinant inbred line (RIL) population and two corresponding immortalized backcross (IB) populations obtained from crosses between the RIL population and the two parental lines.

Results

A total of 17 and 15 QTL were detected in the RIL and IB populations, respectively. Two QTL, qPH1-1 (qEH1-1) and qPH1-2 (qEH1-4) in the RIL, were simultaneously identified for PH and EH. Combing reported genome-wide association and cloned PH-related genes, co-expression network analyses were constructed, then five candidate genes with high confidence in major QTL were identified including Zm00001d011117 and Zm00001d011108, whose homologs have been confirmed to play a role in determining PH in maize and soybean.

Discussion

QTL mapping used a immortalized backcross population is a new strategy. These identified genes in this study can provide new insights for improving the plant architecture in maize.

Striking a growth-defense balance: Stress regulators that function in maize development

Maize (Zea mays) cultivation is strongly affected by both abiotic and biotic stress, leading to reduced growth and productivity. It has recently become clear that regulators of plant stress responses, including the phytohormones abscisic acid (ABA), ethylene (ET), and jasmonic acid (JA), together with reactive oxygen species (ROS), shape plant growth and development. Beyond their well established functions in stress responses, these molecules play crucial roles in balancing growth and defense, which must be finely tuned to achieve high yields in crops while maintaining some level of defense. In this review, we provide an in-depth analysis of recent research on the developmental functions of stress regulators, focusing specifically on maize. By unraveling the contributions of these regulators to maize development, we present new avenues for enhancing maize cultivation and growth while highlighting the potential risks associated with manipulating stress regulators to enhance grain yields in the face of environmental challenges.

Toward understanding and utilizing crop heterosis in the age of biotechnology

Heterosis, a universal phenomenon in nature, mainly reflected in the superior productivity, quality, and fitness of F1 hybrids compared with their inbred parents, has been exploited in agriculture and greatly benefited human society in terms of food security. However, the flexible and efficient utilization of heterosis has remained a challenge in hybrid breeding systems because of the limitations of "three-line" and "two-line" methods. In the past two decades, rapidly developed biotechnologies have provided unprecedented conveniences for both understanding and utilizing heterosis. Notably, "third-generation" (3G) hybrid breeding technology together with high-throughput sequencing and gene editing greatly promoted the efficiency of hybrid breeding. Here, we review emerging ideas about the genetic or molecular mechanisms of heterosis and the development of 3G hybrid breeding system in the age of biotechnology. In addition, we summarized opportunities and challenges for optimal heterosis utilization in the future.

Genome-Wide Association Study for Maize Hybrid Performance in a Typical Breeder Population

Maize is one of the major crops that has demonstrated success in the utilization of heterosis. Developing high-yield hybrids is a crucial part of plant breeding to secure global food demand. In this study, we conducted a genome-wide association study (GWAS) for 10 agronomic traits using a typical breeder population comprised 442 single-cross hybrids by evaluating additive, dominance, and epistatic effects. A total of 49 significant single nucleotide polymorphisms (SNPs) and 69 significant pairs of epistasis were identified, explaining 26.2% to 64.3% of the phenotypic variation across the 10 traits. The enrichment of favorable genotypes is significantly correlated to the corresponding phenotype. In the confident region of the associated site, 532 protein-coding genes were discovered. Among these genes, the Zm00001d044211 candidate gene was found to negatively regulate starch synthesis and potentially impact yield. This typical breeding population provided a valuable resource for dissecting the genetic architecture of yield-related traits. We proposed a novel mating strategy to increase the GWAS efficiency without utilizing more resources. Finally, we analyzed the enrichment of favorable alleles in the Shaan A and Shaan B groups, as well as in each inbred line. Our breeding practice led to consistent results. Not only does this study demonstrate the feasibility of GWAS in F1 hybrid populations, it also provides a valuable basis for further molecular biology and breeding research.

CropGS-Hub: a comprehensive database of genotype and phenotype resources for genomic prediction in major crops

The explosive amount of multi-omics data has brought a paradigm shift both in academic research and further application in life science. However, managing and reusing the growing resources of genomic and phenotype data points presents considerable challenges for the research community. There is an urgent need for an integrated database that combines genome-wide association studies (GWAS) with genomic selection (GS). Here, we present CropGS-Hub, a comprehensive database comprising genotype, phenotype, and GWAS signals, as well as a one-stop platform with built-in algorithms for genomic prediction and crossing design. This database encompasses a comprehensive collection of over 224 billion genotype data and 434 thousand phenotype data generated from >30 000 individuals in 14 representative populations belonging to 7 major crop species. Moreover, the platform implemented three complete functional genomic selection related modules including phenotype prediction, user model training and crossing design, as well as a fast SNP genotyper plugin-in called SNPGT specifically built for CropGS-Hub, aiming to assist crop scientists and breeders without necessitating coding skills. CropGS-Hub can be accessed at https://iagr.genomics.cn/CropGS/.

Genetic interrogation of phenotypic plasticity informs genome-enabled breeding in cotton

Phenotypic plasticity, or the ability to adapt to and thrive in changing climates and variable environments, is essential for developmental programs in plants. Despite its importance, the genetic underpinnings of phenotypic plasticity for key agronomic traits remain poorly understood in many crops. In this study, we aim to fill this gap by using genome-wide association studies to identify genetic variations associated with phenotypic plasticity in upland cotton (Gossypium hirsutum L.). We identified 73 additive quantitative trait loci (QTLs), 32 dominant QTLs, and 6799 epistatic QTLs associated with 20 traits. We also identified 117 additive QTLs, 28 dominant QTLs, and 4691 epistatic QTLs associated with phenotypic plasticity in 19 traits. Our findings reveal new genetic factors, including additive, dominant, and epistatic QTLs, that are linked to phenotypic plasticity and agronomic traits. Meanwhile, we find that the genetic factors controlling the mean phenotype and phenotypic plasticity are largely independent in upland cotton, indicating the potential for simultaneous improvement. Additionally, we envision a genomic design strategy by utilizing the identified QTLs to facilitate cotton breeding. Taken together, our study provides new insights into the genetic basis of phenotypic plasticity in cotton, which should be valuable for future breeding.

A potential candidate gene associated with the angles of the ear leaf and the second leaf above the ear leaf in maize

BACKGROUND

Leaf angle is a key trait for maize plant architecture that plays a significant role in its morphological development, and ultimately impacting maize grain yield. Although many studies have been conducted on the association and localization of genes regulating leaf angle in maize, most of the candidate genes identified are associated with the regulation of ligule-ear development and phytohormone pathways, and only a few candidate genes have been reported to enhance the mechanical strength of leaf midrib and vascular tissues.

RESULTS

To address this gap, we conducted a genome-wide association study (GWAS) using the leaf angle phenotype and genotyping-by-sequencing data generated from three recombinant inbred line (RIL) populations of maize. Through GWAS analysis, we identified 156 SNPs significantly associated with the leaf angle trait and detected a total of 68 candidate genes located within 10 kb upstream and downstream of these individual SNPs. Among these candidate genes, Zm00001d045408, located on chromosome 9 emerged as a key gene controlling the angles of both the ear leaf and the second leaf above the ear leaf. Notably, this new gene's homolog in Arabidopsis promotes cell division and vascular tissue development. Further analysis revealed that a SNP transversion (G/T) at 7.536 kb downstream of the candidate gene Zm00001d045408 may have caused a reduction in leaf angles of the ear and the second leaf above the ear leaf. Our analysis of the 10 kb region downstream of this candidate gene revealed a 4.337 kb solo long-terminal reverse transcription transposon (solo LTR), located 3.112 kb downstream of Zm00001d045408, with the SNP located 87 bp upstream of the solo LTR.

CONCLUSIONS

In summary, we have identified a novel candidate gene, Zm00001d045408 and a solo LTR that are associated with the angles of both the ear leaf and the second leaf above the ear leaf. The future research holds great potential in exploring the precise role of newly identified candidate gene in leaf angle regulation. Functional characterization of this gene can help in gaining deeper insights into the complex genetic pathways underlying maize plant architecture.

A dimensionality-reduction genomic prediction method without direct inverse of the genomic relationship matrix for large genomic data

KEY MESSAGE

A new genomic prediction method (RHPP) was developed via combining randomized Haseman-Elston regression (RHE-reg), PCR based on genomic information of core population, and preconditioned conjugate gradient (PCG) algorithm. Computational efficiency is becoming a hot issue in the practical application of genomic prediction due to the large number of data generated by the high-throughput genotyping technology. In this study, we developed a fast genomic prediction method RHPP via combining randomized Haseman-Elston regression (RHE-reg), PCR based on genomic information of core population, and preconditioned conjugate gradient (PCG) algorithm. The simulation results demonstrated similar prediction accuracy between RHPP and GBLUP, and significantly higher computational efficiency of the former with the increase of individuals. The results of real datasets of both bread wheat and loblolly pine demonstrated that RHPP had a similar or better predictive accuracy in most cases compared with GBLUP. In the future, RHPP may be an attractive choice for analyzing large-scale and high-dimensional data.

Genome-wide artificial introgressions of Gossypium barbadense into G. hirsutum reveal superior loci for simultaneous improvement of cotton fiber quality and yield traits

INTRODUCTION

The simultaneous improvement of fiber quality and yield for cotton is strongly limited by the narrow genetic backgrounds of Gossypium hirsutum (Gh) and the negative genetic correlations among traits. An effective way to overcome the bottlenecks is to introgress the favorable alleles of Gossypium barbadense (Gb) for fiber quality into Gh with high yield.

OBJECTIVES

This study was to identify superior loci for the improvement of fiber quality and yield.

METHODS

Two sets of chromosome segment substitution lines (CSSLs) were generated by crossing Hai1 (Gb, donor-parent) with cultivar CCRI36 (Gh) and CCRI45 (Gh) as genetic backgrounds, and cultivated in 6 and 8 environments, respectively. The kmer genotyping strategy was improved and applied to the population genetic analysis of 743 genomic sequencing data. A progeny segregating population was constructed to validate genetic effects of the candidate loci.

RESULTS

A total of 68,912 and 83,352 genome-wide introgressed kmers were identified in the CCRI36 and CCRI45 populations, respectively. Over 90 % introgressions were homologous exchanges and about 21 % were reverse insertions. In total, 291 major introgressed segments were identified with stable genetic effects, of which 66(22.98 %), 64(21.99 %), 35(12.03 %), 31(10.65 %) and 18(6.19 %) were beneficial for the improvement of fiber length (FL), strength (FS), micronaire, lint-percentage (LP) and boll-weight, respectively. Thirty-nine introgression segments were detected with stable favorable additive effects for simultaneous improvement of 2 or more traits in Gh genetic background, including 6 could increase FL/FS and LP. The pyramiding effects of 3 pleiotropic segments (A07:C45Clu-081, D06:C45Clu-218, D02:C45Clu-193) were further validated in the segregating population.

CONCLUSION

The combining of genome-wide introgressions and kmer genotyping strategy showed significant advantages in exploring genetic resources. Through the genome-wide comprehensive mining, a total of 11 clusters (segments) were discovered for the stable simultaneous improvement of FL/FS and LP, which should be paid more attention in the future.

Decoupling subgenomes within hybrid lavandin provide new insights into speciation and monoterpenoid diversification of Lavandula

Polyploidization and transposon elements contribute to shape plant genome diversity and secondary metabolic variation in some edible crops. However, the specific contribution of these variations to the chemo-diversity of Lamiaceae, particularly in economic shrubs, is still poorly documented. The rich essential oils (EOs) of Lavandula plants are distinguished by monoterpenoids among the main EO-producing species, L. angustifolia (LA), L. × intermedia (LX) and L. latifolia (LL). Herein, the first allele-aware chromosome-level genome was assembled using a lavandin cultivar 'Super' and its hybrid origin was verified by two complete subgenomes (LX-LA and LX-LL). Genome-wide phylogenetics confirmed that LL, like LA, underwent two lineage-specific WGDs after the γ triplication event, and their speciation occurred after the last WGD. Chloroplast phylogenetic analysis indicated LA was the maternal source of 'Super', which produced premium EO (higher linalyl/lavandulyl acetate and lower 1,8-cineole and camphor) close to LA. Gene expression, especially the monoterpenoid biosynthetic genes, showed bias to LX-LA alleles. Asymmetric transposon insertions in two decoupling 'Super' subgenomes were responsible for speciation and monoterpenoid divergence of the progenitors. Both hybrid and parental evolutionary analysis revealed that LTR (long terminal repeat) retrotransposon associated with AAT gene loss cause no linalyl/lavandulyl acetate production in LL, and multi-BDH copies retained by tandem duplication and DNA transposon resulted in higher camphor accumulation of LL. Advances in allelic variations of monoterpenoids have the potential to revolutionize future lavandin breeding and EO production.

Dominance is common in mammals and is associated with trans-acting gene expression and alternative splicing

BACKGROUND

Dominance and other non-additive genetic effects arise from the interaction between alleles, and historically these phenomena play a major role in quantitative genetics. However, most genome-wide association studies (GWAS) assume alleles act additively.

RESULTS

We systematically investigate both dominance-here representing any non-additive within-locus interaction-and additivity across 574 physiological and gene expression traits in three mammalian stocks: F2 intercross pigs, rat heterogeneous stock, and mice heterogeneous stock. Dominance accounts for about one quarter of heritable variance across all physiological traits in all species. Hematological and immunological traits exhibit the highest dominance variance, possibly reflecting balancing selection in response to pathogens. Although most quantitative trait loci (QTLs) are detectable as additive QTLs, we identify 154, 64, and 62 novel dominance QTLs in pigs, rats, and mice respectively that are undetectable as additive QTLs. Similarly, even though most cis-acting expression QTLs are additive, gene expression exhibits a large fraction of dominance variance, and trans-acting eQTLs are enriched for dominance. Genes causal for dominance physiological QTLs are less likely to be physically linked to their QTLs but instead act via trans-acting dominance eQTLs. In addition, thousands of eQTLs are associated with alternatively spliced isoforms with complex additive and dominant architectures in heterogeneous stock rats, suggesting a possible mechanism for dominance.

CONCLUSIONS

Although heritability is predominantly additive, many mammalian genetic effects are dominant and likely arise through distinct mechanisms. It is therefore advantageous to consider both additive and dominance effects in GWAS to improve power and uncover causality.

Unraveling Prevalence and Effects of Deleterious Mutations in Maize Elite Lines across Decades of Modern Breeding

Future breeding is likely to involve the detection and removal of deleterious alleles, which are mutations that negatively affect crop fitness. However, little is known about the prevalence of such mutations and their effects on phenotypic traits in the context of modern crop breeding. To address this, we examined the number and frequency of deleterious mutations in 350 elite maize inbred lines developed over the past few decades in China and the United States. Our findings reveal an accumulation of weakly deleterious mutations and a decrease in strongly deleterious mutations, indicating the dominant effects of genetic drift and purifying selection for the two types of mutations, respectively. We also discovered that slightly deleterious mutations, when at lower frequencies, were more likely to be heterozygous in the developed hybrids. This is consistent with complementation as a potential explanation for heterosis. Subsequently, we found that deleterious mutations accounted for more of the variation in phenotypic traits than nondeleterious mutations with matched minor allele frequencies, especially for traits related to leaf angle and flowering time. Moreover, we detected fewer deleterious mutations in the promoter and gene body regions of differentially expressed genes across breeding eras than in nondifferentially expressed genes. Overall, our results provide a comprehensive assessment of the prevalence and impact of deleterious mutations in modern maize breeding and establish a useful baseline for future maize improvement efforts.

Triticeae crop genome biology: an endless frontier

Triticeae, the wheatgrass tribe, includes several major cereal crops and their wild relatives. Major crops within the Triticeae are wheat, barley, rye, and oat, which are important for human consumption, animal feed, and rangeland protection. Species within this tribe are known for their large genomes and complex genetic histories. Powered by recent advances in sequencing technology, researchers worldwide have made progress in elucidating the genomes of Triticeae crops. In addition to assemblies of high-quality reference genomes, pan-genome studies have just started to capture the genomic diversities of these species, shedding light on our understanding of the genetic basis of domestication and environmental adaptation of Triticeae crops. In this review, we focus on recent signs of progress in genome sequencing, pan-genome analyses, and resequencing analysis of Triticeae crops. We also propose future research avenues in Triticeae crop genomes, including identifying genome structure variations, the association of genomic regions with desired traits, mining functions of the non-coding area, introgression of high-quality genes from wild Triticeae resources, genome editing, and integration of genomic resources.

Joint analysis of phenotype-effect-generation identifies loci associated with grain quality traits in rice hybrids

Genetic improvement of grain quality is more challenging in hybrid rice than in inbred rice due to additional nonadditive effects such as dominance. Here, we describe a pipeline developed for joint analysis of phenotypes, effects, and generations (JPEG). As a demonstration, we analyze 12 grain quality traits of 113 inbred lines (male parents), five tester lines (female parents), and 565 (113×5) of their hybrids. We sequence the parents for single nucleotide polymorphisms calling and infer the genotypes of the hybrids. Genome-wide association studies with JPEG identify 128 loci associated with at least one of the 12 traits, including 44, 97, and 13 loci with additive effects, dominant effects, and both additive and dominant effects, respectively. These loci together explain more than 30% of the genetic variation in hybrid performance for each of the traits. The JEPG statistical pipeline can help to identify superior crosses for breeding rice hybrids with improved grain quality.

Integrated IBD Analysis, GWAS Analysis and Transcriptome Analysis to Identify the Candidate Genes for White Spot Disease in Maize

Foundation parents (FPs) play an irreplaceable role in maize breeding practices. Maize white spot (MWS) is an important disease in Southwest China that always seriously reduces production. However, knowledge about the genetic mechanism of MWS resistance is limited. In this paper, a panel of 143 elite lines were collected and genotyped by using the MaizeSNP50 chip with approximately 60,000 single nucleotide polymorphisms (SNPs) and evaluated for resistance to MWS among 3 environments, and a genome-wide association study (GWAS) and transcriptome analysis were integrated to reveal the function of the identity-by-descent (IBD) segments for MWS. The results showed that (1) 225 IBD segments were identified only in the FP QB512, 192 were found only in the FP QR273 and 197 were found only in the FP HCL645. (2) The GWAS results showed that 15 common quantitative trait nucleotides (QTNs) were associated with MWS. Interestingly, SYN10137 and PZA00131.14 were in the IBD segments of QB512, and the SYN10137-PZA00131.14 region existed in more than 58% of QR273's descendants. (3) By integrating the GWAS and transcriptome analysis, Zm00001d031875 was found to located in the region of SYN10137-PZA00131.14. These results provide some new insights for the detection of MWS's genetic variation mechanisms.

Modeling the influence of phenotypic plasticity on maize hybrid performance

Phenotypic plasticity, the ability of an individual to alter its phenotype in response to changes in the environment, has been proposed as a target for breeding crop varieties with high environmental fitness. Here, we used phenotypic and genotypic data from multiple maize (Zea mays L.) populations to mathematically model phenotypic plasticity in response to the environment (PPRE) in inbred and hybrid lines. PPRE can be simply described by a linear model in which the two main parameters, intercept a and slope b, reflect two classes of genes responsive to endogenous (class A) and exogenous (class B) signals that coordinate plant development. Together, class A and class B genes contribute to the phenotypic plasticity of an individual in response to the environment. We also made connections between phenotypic plasticity and hybrid performance or general combining ability (GCA) of yield using 30 F₁ hybrid populations generated by crossing the same maternal line with 30 paternal lines from different maize heterotic groups. We show that the parameters a and b from two given parental lines must be concordant to reach an ideal GCA of F₁ yield. We hypothesize that coordinated regulation of the two classes of genes in the F₁ hybrid genome is the basis for high GCA. Based on this theory, we built a series of predictive models to evaluate GCA in silico between parental lines of different heterotic groups.

Performances of three-way cross hybrids over their respective single crosses and related heterosis of maize (Zea mays L.) hybrids evaluated in Ethiopia

Less attention had been given to the performances of three-way crosses and its comparative advantages of these hybrids over single crosses. This study was carried out to evaluate the performances of three-way crosses in comparison to single crosses for yield and related agronomic traits and to estimate the magnitude of heterosis. The trial was laid out in a simple alpha lattice design of 10 × 6 for lines, 6 × 5 for single crosses (SC), and 9 × 5 for three way-crosses and planted in adjacent plots in the 2019 cropping season in three locations namely Ambo, Abala-Farcha and Melkassa. Single cross hybrids showed a highly significant (P<1%) variation for grain yield, plant height, ear height, and ear length at three locations. These single cross hybrids had showed also a highly significant genotype by environment interaction (P < 1%) for grain yield, plant height, ear height and kernel per ear. Regarding three-way crosses, there was a significant variation (P<5%) on grain yield in Ambo and Melkassa but on ear height and rows per ear in Abala-Faracho. The genotype × environment interaction was significantly varied for grain yield, ear height and ear length. In the comparison, 80% crosses in Ambo, 73% in Abala-Faracho and 67% in Melkassa showed that three-way crosses were better in their performance than that of their respective single crosses. On the other hand, the single crosses that out-performed their respective three-way crosses were higher in Melkassa than Abala-Faracho and the least were reported from Ambo. Similarly, the maximum better and mid-parent heterosis was from single cross 1(769%) in Ambo and single cross 7 (104%) in Melkassa whereas TWC 14 (52%) and TWC 24 (78%) were the highest better and mid-parent heterosis, respectively in Ambo, TWC1 (56%), and TWC30 (25%) were the highest BPH, and MPH, respectively in Melkassa.

Combining GS-assisted GWAS and transcriptome analysis to mine candidate genes for nitrogen utilization efficiency in Populus cathayana

BACKGROUND

Forest trees such as poplar, shrub willow, et al. are essential natural resources for sustainable and renewable energy production, and their wood can reduce dependence on fossil fuels and reduce environmental pollution. However, the productivity of forest trees is often limited by the availability of nitrogen (N), improving nitrogen use efficiency (NUE) is an important way to address it. Currently, NUE genetic resources are scarce in forest tree research, and more genetic resources are urgently needed.

RESULTS

Here, we performed genome-wide association studies (GWAS) using the mixed linear model (MLM) to identify genetic loci regulating growth traits in Populus cathayana at two N levels, and attempted to enhance the signal strength of single nucleotide polymorphism (SNP) detection by performing genome selection (GS) assistance GWAS. The results of the two GWAS analyses identified 55 and 40 SNPs that were respectively associated with plant height (PH) and ground diameter (GD), and 92 and 69 candidate genes, including 30 overlapping genes. The prediction accuracy of the GS model (rrBLUP) for phenotype exceeds 0.9. Transcriptome analysis of 13 genotypes under two N levels showed that genes related to carbon and N metabolism, amino acid metabolism, energy metabolism, and signal transduction were differentially expressed in the xylem of P. cathayana under N treatment. Furthermore, we observed strong regional patterns in gene expression levels of P. cathayana, with significant differences between different regions. Among them, P. cathayana in Longquan region exhibited the highest response to N. Finally, through weighted gene co-expression network analysis (WGCNA), we identified a module closely related to the N metabolic process and eight hub genes.

CONCLUSIONS

Integrating the GWAS, RNA-seq and WGCNA data, we ultimately identified four key regulatory genes (PtrNAC123, PtrNAC025, Potri.002G233100, and Potri.006G236200) involved in the wood formation process, and they may affect P. cathayana growth and wood formation by regulating nitrogen metabolism. This study will provide strong evidence for N regulation mechanisms, and reliable genetic resources for growth and NUE genetic improvement in poplar.

The Use of DArTseq Technology to Identify Markers Related to the Heterosis Effects in Selected Traits in Maize

Spectacular scientific advances in the area of molecular biology and the development of modern biotechnological tools have had a significant impact on the development of maize heterosis breeding. One technology based on next-generation sequencing is DArTseq. The plant material used for the research consisted of 13 hybrids resulting from the crossing of inbred maize lines. A two-year field experiment was established at two Polish breeding stations: Smolice and Łagiewniki. Nine quantitative traits were observed: cob length, cob diameter, core length, core diameter, number of rows of grain, number of grains in a row, mass of grain from the cob, weight of one thousand grains, and yield. The isolated DNA was subjected to DArTseq genotyping. Association mapping was performed using a method based on the mixed linear model. A total of 81602 molecular markers (28571 SNPs and 53031 SilicoDArTs) were obtained as a result of next-generation sequencing. Out of 81602, 15409 (13850 SNPs and 1559 SilicoDArTs) were selected for association analysis. The 105 molecular markers (8 SNPs and 97 SilicoDArTs) were associated with the heterosis effect of at least one trait in at least one environment. A total of 186 effects were observed. The number of statistically significant relationships between the molecular marker and heterosis effect varied from 8 (for cob length) and 9 (for yield) to 42 (for the number of rows of grain). Of particular note were three markers (2490222, 2548691 and 7058267), which were significant in 17, 8 and 6 cases, respectively. Two of them (2490222 and 7058267) were associated with the heterosis effects of yield in three of the four environments.

IP4GS: Bringing genomic selection analysis to breeders

Genomic selection (GS), a strategy to use genotypes to predict phenotypes via statistical or machine learning models, has become a routine practice in plant breeding programs. GS can speed up the genetic gain by reducing phenotyping costs and/or shortening the breeding cycles. GS analysis is complicated involving data clean up and formatting, training and test population analysis, model selection and evaluation, and parameter optimization. In addition, GS analysis also requires some programming skills and knowledge of statistical modeling. Thus, we need a more practical GS tools for breeders. To alleviate this difficulty, we developed the web-based platform IP4GS (https://ngdc.cncb.ac.cn/ip4gs/), which offers a user-friendly interface to perform GS analysis simply through point-and-click actions. IP4GS currently includes seven commonly used models, eleven evaluation metrics, and visualization modules, offering great convenience for plant breeders with limited bioinformatics knowledge to apply GS analysis.

Recurrent Interpopulation Selection in Popcorn: From Heterosis to Genetic Gains

In view of the need to develop new popcorn cultivars and considering the uncertainties in choosing the most appropriate breeding methods to ensure consistent genetic progress, simultaneously for both popping expansion and grain yield, this study addressed the efficiency of interpopulation recurrent selection regarding genetic gains, the study of the response in genetic parameters as well as heterotic effects on the control of the main agronomic traits of popcorn. Two populations were established, Pop₁ and Pop₂. A total of 324 treatments were evaluated, which consisted of 200 half-sib families (100 from Pop₁ and 100 from Pop₂), 100 full-sib families from the two populations and 24 controls. The field experiment was arranged in a lattice design with three replications in two environments, in the north and northwest regions of the State of Rio de Janeiro, Brazil. The genotype × environment interaction was partitioned and the genetic parameters, heterosis and predicted gains were estimated by the Mulamba and Mock index, based on selection results in both environments. The genetic parameters detected variability that can be explored in successive interpopulation recurrent selection cycles. Exploring heterosis for GY, PE and yield components is a promising option to increase grain yield and quality. The Mulamba and Mock index was efficient in predicting the genetic gains in GY and PE. Interpopulation recurrent selection proved effective to provide genetic gains for traits with predominantly additive and dominance inheritance.

Integration of high-throughput phenotyping, GWAS, and predictive models reveals the genetic architecture of plant height in maize

Plant height (PH) is an essential trait in maize (Zea mays) that is tightly associated with planting density, biomass, lodging resistance, and grain yield in the field. Dissecting the dynamics of maize plant architecture will be beneficial for ideotype-based maize breeding and prediction, as the genetic basis controlling PH in maize remains largely unknown. In this study, we developed an automated high-throughput phenotyping platform (HTP) to systematically and noninvasively quantify 77 image-based traits (i-traits) and 20 field traits (f-traits) for 228 maize inbred lines across all developmental stages. Time-resolved i-traits with novel digital phenotypes and complex correlations with agronomic traits were characterized to reveal the dynamics of maize growth. An i-trait-based genome-wide association study identified 4945 trait-associated SNPs, 2603 genetic loci, and 1974 corresponding candidate genes. We found that rapid growth of maize plants occurs mainly at two developmental stages, stage 2 (S2) to S3 and S5 to S6, accounting for the final PH indicators. By integrating the PH-association network with the transcriptome profiles of specific internodes, we revealed 13 hub genes that may play vital roles during rapid growth. The candidate genes and novel i-traits identified at multiple growth stages may be used as potential indicators for final PH in maize. One candidate gene, ZmVATE, was functionally validated and shown to regulate PH-related traits in maize using genetic mutation. Furthermore, machine learning was used to build predictive models for final PH based on i-traits, and their performance was assessed across developmental stages. Moderate, strong, and very strong correlations between predictions and experimental datasets were achieved from the early S4 (tenth-leaf) stage. Colletively, our study provides a valuable tool for dissecting the spatiotemporal formation of specific internodes and the genetic architecture of PH, as well as resources and predictive models that are useful for molecular design breeding and predicting maize varieties with ideal plant architectures.

Evaluation of a Sugarcane (Saccharum spp.) Hybrid F1 Population Phenotypic Diversity and Construction of a Rapid Sucrose Yield Estimation Model for Breeding

Sugarcane is the major sugar-producing crop worldwide, and hybrid F₁ populations are the primary populations used in breeding. Challenged by the sugarcane genome's complexity and the sucrose yield's quantitative nature, phenotypic selection is still the most commonly used approach for high-sucrose yield sugarcane breeding. In this study, a hybrid F₁ population containing 135 hybrids was constructed and evaluated for 11 traits (sucrose yield (SY) and its related traits) in a randomized complete-block design during two consecutive growing seasons. The results revealed that all the traits exhibited distinct variation, with the coefficient of variation (CV) ranging from 0.09 to 0.35, the Shannon-Wiener diversity index (H') ranging between 2.64 and 2.98, and the broad-sense heritability ranging from 0.75 to 0.84. Correlation analysis revealed complex correlations between the traits, with 30 trait pairs being significantly correlated. Eight traits, including stalk number (SN), stalk diameter (SD), internode length (IL), stalk height (SH), stalk weight (SW), Brix (B), sucrose content (SC), and yield (Y), were significantly positively correlated with sucrose yield (SY). Cluster analysis based on the 11 traits divided the 135 F₁ hybrids into three groups, with 55 hybrids in Group I, 69 hybrids in Group II, and 11 hybrids in Group III. The principal component analysis indicated that the values of the first four major components' vectors were greater than 1 and the cumulative contribution rate reached 80.93%. Based on the main component values of all samples, 24 F₁ genotypes had greater values than the high-yielding parent 'ROC22' and were selected for the next breeding stage. A rapid sucrose yield estimation equation was established using four easily measured sucrose yield-related traits through multivariable linear stepwise regression. The model was subsequently confirmed using 26 sugarcane cultivars and 24 F₁ hybrids. This study concludes that the sugarcane F₁ population holds great genetic diversity in sucrose yield-related traits. The sucrose yield estimation model, ySY=2.01xSN+8.32xSD+0.79xB+3.44xSH-47.64, can aid to breed sugarcane varieties with high sucrose yield.

Machine learning bridges omics sciences and plant breeding

Some of the biological knowledge obtained from fundamental research will be implemented in applied plant breeding. To bridge basic research and breeding practice, machine learning (ML) holds great promise to translate biological knowledge and omics data into precision-designed plant breeding. Here, we review ML for multi-omics analysis in plants, including data dimensionality reduction, inference of gene-regulation networks, and gene discovery and prioritization. These applications will facilitate understanding trait regulation mechanisms and identifying target genes potentially applicable to knowledge-driven molecular design breeding. We also highlight applications of deep learning in plant phenomics and ML in genomic selection-assisted breeding, such as various ML algorithms that model the correlations among genotypes (genes), phenotypes (traits), and environments, to ultimately achieve data-driven genomic design breeding.

Genome-wide analysis of transcriptome and histone modifications in Brassica napus hybrid

Although utilization of heterosis has largely improved the yield of many crops worldwide, the underlying molecular mechanism of heterosis, particularly for allopolyploids, remains unclear. Here, we compared epigenome and transcriptome data of an elite hybrid and its parental lines in three assessed tissues (seedling, flower bud, and silique) to explore their contribution to heterosis in allopolyploid B. napus. Transcriptome analysis illustrated that a small proportion of non-additive genes in the hybrid compared with its parents, as well as parental expression level dominance, might have a significant effect on heterosis. We identified histone modification (H3K4me3 and H3K27me3) variation between the parents and hybrid, most of which resulted from the differences between parents. H3K4me3 variations were positively correlated with gene expression differences among the hybrid and its parents. Furthermore, H3K4me3 and H3K27me3 were rather stable in hybridization and were mainly inherited additively in the B. napus hybrid. Together, our data revealed that transcriptome reprogramming and histone modification remodeling in the hybrid could serve as valuable resources for better understanding heterosis in allopolyploid crops.

Genome-wide association analysis for grain moisture content and dehydration rate on maize hybrids

For mechanized maize production, a low grain water content (GWC) at harvest is necessary. However, as a complex quantitative trait, understand the genetic mechanism of GWC remains a large gap, especially in hybrids. In this study, a hybrid population through two environments including 442 F1 was used for genome-wide association analysis of GWC and the grain dehydration rate (GDR), using the area under the dry down curve (AUDDC) as the index. Then, we identified 19 and 17 associated SNPs for GWC and AUDDC, including 10 co-localized SNPs, along with 64 and 77 pairs of epistatic SNPs for GWC and AUDDC, respectively. These loci could explain 11.39-68.2% of the total phenotypic variation for GWC and 41.07-67.02% for AUDDC at different stages, whose major effect was the additive and epistatic effect. By exploring the candidate genes around the significant sites, a total of 398 and 457 possible protein-coding genes were screened, including autophagy pathway and auxin regulation-related genes, and five inbred lines with the potential to reduce GWC in the combined F1 hybrid were identified. Our research not only provides a certain reference for the genetic mechanism analysis of GWC in hybrids but also provides an added reference for breeding low-GWC materials.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-022-01349-x.

Large-scale genomic and transcriptomic profiles of rice hybrids reveal a core mechanism underlying heterosis

BACKGROUND

Heterosis is widely used in agriculture. However, its molecular mechanisms are still unclear in plants. Here, we develop, sequence, and record the phenotypes of 418 hybrids from crosses between two testers and 265 rice varieties from a mini-core collection.

RESULTS

Phenotypic analysis shows that heterosis is dependent on genetic backgrounds and environments. By genome-wide association study of 418 hybrids and their parents, we find that nonadditive QTLs are the main genetic contributors to heterosis. We show that nonadditive QTLs are more sensitive to the genetic background and environment than additive ones. Further simulations and experimental analysis support a novel mechanism, homo-insufficiency under insufficient background (HoIIB), underlying heterosis. We propose heterosis in most cases is not due to heterozygote advantage but homozygote disadvantage under the insufficient genetic background.

CONCLUSION

The HoIIB model elucidates that genetic background insufficiency is the intrinsic mechanism of background dependence, and also the core mechanism of nonadditive effects and heterosis. This model can explain most known hypotheses and phenomena about heterosis, and thus provides a novel theory for hybrid rice breeding in future.

ZmDREB2.9 Gene in Maize (Zea mays L.): Genome-Wide Identification, Characterization, Expression, and Stress Response

Dehydration-responsive element-binding (DREB) transcription factors of the A2 subfamily play key roles in plant stress responses. In this study, we identified and characterized a new A2-type DREB gene, ZmDREB2.9, in the Zea mays cv. B73 genome and compared its expression profile with those of the known A2-type maize genes ZmDREB2.1-2.8. ZmDREB2.9 was mapped to chromosome 8, contained 18 predicted hormone- and stress-responsive cis-elements in the promoter, and had two splice isoforms: short ZmDREB2.9-S preferentially expressed in the leaves, embryos, and endosperm and long ZmDREB2.9-L expressed mostly in the male flowers, stamens, and ovaries. Phylogenetically, ZmDREB2.9 was closer to A. thaliana DREB2A than the other ZmDREB2 factors. ZmDREB2.9-S, ZmDREB2.2, and ZmDREB2.1/2A were upregulated in response to cold, drought, and abscisic acid and may play redundant roles in maize stress resistance. ZmDREB2.3, ZmDREB2.4, and ZmDREB2.6 were not expressed in seedlings and could be pseudogenes. ZmDREB2.7 and ZmDREB2.8 showed similar transcript accumulation in response to cold and abscisic acid and could be functionally redundant. Our results provide new data on Z. mays DREB2 factors, which can be used for further functional studies as well as in breeding programs to improve maize stress tolerance.

Dominant complementation of biological pathways in maize hybrid lines is associated with heterosis

Allele-specific expressed genes (ASEGs) are widespread in maize hybrid lines and play important roles of complementation of biological pathways in heterosis. Heterosis (hybrid vigor) is an important phenomenon with both theoretical and practical value. However, our understanding of the genetic and molecular mechanisms behind heterosis is still limited. Here, we analyzed a comprehensive dataset of maize (Zea mays L.), including RNA-seq data from three hybrid-parent triplets (HPTs) and acetylated protein data from one HPT. The gene expression patterns exhibited extensive variation between the hybrids and their parents, and a substantial number of allele-specific expressed genes (ASEGs) were identified in the hybrids. Notably, ASEGs from different HPTs were significantly enriched in various conserved pathways. The parental alleles of ASEGs with fewer deleterious single-nucleotide polymorphisms were more likely to be expressed in hybrid lines than other parental alleles. ASEGs were mainly enriched in the functional gene ontology terms protein biosynthesis, photosynthesis, and metabolism. In addition, the ASEGs across the three HPTs were involved in key photosynthetic pathways and might enhance the photosynthetic efficiency of the hybrids. These findings suggest that ASEGs involved in complementary biological pathways in maize hybrids contribute to heterosis, shedding new light on the molecular mechanism of heterosis.

An Exploration of Pepino (Solanum muricatum) Flavor Compounds Using Machine Learning Combined with Metabolomics and Sensory Evaluation

Flavor is one of the most important characteristics that directly determines the popularity of a food. Moreover, the flavor of fruits is determined by the interaction of multiple metabolic components. Pepino, an emerging horticultural crop, is popular for its unique melon-like flavor. We analyzed metabolomics data from three different pepino growing regions in Haidong, Wuwei, and Jiuquan and counted the status of sweetness, acidity, flavor, and overall liking ratings of pepino fruit in these three regions by sensory panels. The metabolomics and flavor ratings were also integrated and analyzed using statistical and machine learning models, which in turn predicted the sensory panel ratings of consumers based on the chemical composition of the fruit. The results showed that pepino fruit produced in the Jiuquan region received the highest ratings in sweetness, flavor intensity, and liking, and the results with the highest contribution based on sensory evaluation showed that nucleotides and derivatives, phenolic acids, amino acids and derivatives, saccharides, and alcohols were rated in sweetness (74.40%), acidity (51.57%), flavor (56.41%), and likability (33.73%) dominated. We employed 14 machine learning strategies trained on the discovery samples to accurately predict the outcome of sweetness, sourness, flavor, and liking in the replication samples. The Radial Sigma SVM model predicted with better accuracy than the other machine learning models. Then we used the machine learning models to determine which metabolites influenced both pepino flavor and consumer preference. A total of 27 metabolites most important for pepino flavor attributes to distinguish pepino originating from three regions were screened. Substances such as N-acetylhistamine, arginine, and caffeic acid can enhance pepino‘s flavor intensity, and metabolites such as glycerol 3-phosphate, aconitic acid, and sucrose all acted as important variables in explaining the liking preference. While glycolic acid and orthophosphate inhibit sweetness and enhance sourness, sucrose has the opposite effect. Machine learning can identify the types of metabolites that influence fruit flavor by linking metabolomics of fruit with sensory evaluation among consumers, which conduces breeders to incorporate fruit flavor as a trait earlier in the breeding process, making it possible to select and release fruit with more flavor.

A Ghd7-centered regulatory network provides a mechanistic approximation to optimal heterosis in an elite rice hybrid

Heterosis refers to the superior performance of hybrids over their parents, which is a general phenomenon occurring in diverse organisms. Many commercial hybrids produce high yield without delayed flowering, which we refer to as optimal heterosis and is desired in hybrid breeding. Here, we attempted to illustrate the genomic basis of optimal heterosis by reinvestigating the single-locus quantitative trait loci and digenic interactions of two traits, the number of spikelets per panicle (SP) and heading date (HD), using recombinant inbred lines and 'immortalized F₂ s' derived from the elite rice (Oryza sativa) hybrid Shanyou 63. Our analysis revealed a regulatory network that may provide an approximation to the genetic constitution of the optimal heterosis observed in this hybrid. In this network, Ghd7 works as the core element, and three other genes, Ghd7.1, Hd1, and Hd3a/RFT1, also have major roles. The effects of positive dominance by Ghd7 and Ghd7.1 and negative dominance by Hd1 and Hd3a/RFT1 in the hybrid background contribute the major part to the high SP without delaying HD; numerous epistatic interactions, most of which involve Ghd7, also play important roles collectively. The results expand our understanding of the genic interaction networks underlying hybrid rice breeding programs, which may be very useful in future crop genetic improvement.

Genomic analyses of wild argali, domestic sheep, and their hybrids provide insights into chromosome evolution, phenotypic variation, and germplasm innovation

Understanding the genetic mechanisms of phenotypic variation in hybrids between domestic animals and their wild relatives may aid germplasm innovation. Here, we report the high-quality genome assemblies of a male Pamir argali (O ammon polii, 2n = 56), a female Tibetan sheep (O aries, 2n = 54), and a male hybrid of Pamir argali and domestic sheep, and the high-throughput sequencing of 425 ovine animals, including the hybrids of argali and domestic sheep. We detected genomic synteny between Chromosome 2 of sheep and two acrocentric chromosomes of argali. We revealed consistent satellite repeats around the chromosome breakpoints, which could have resulted in chromosome fusion. We observed many more hybrids with karyotype 2n = 54 than with 2n = 55, which could be explained by the selfish centromeres, the possible decreased rate of normal/balanced sperm, and the increased incidence of early pregnancy loss in the aneuploid ewes or rams. We identified genes and variants associated with important morphological and production traits (e.g., body weight, cannon circumference, hip height, and tail length) that show significant variations. We revealed a strong selective signature at the mutation (c.334C > A, p.G112W) in TBXT and confirmed its association with tail length among sheep populations of wide geographic and genetic origins. We produced an intercross population of 110 F2 offspring with varied number of vertebrae and validated the causal mutation by whole-genome association analysis. We verified its function using CRISPR-Cas9 genome editing. Our results provide insights into chromosomal speciation and phenotypic evolution and a foundation of genetic variants for the breeding of sheep and other animals.

Photosynthetic Efficiency and Glyco-Metabolism Changes in Artificial Triploid Loquats Contribute to Heterosis Manifestation

Previous studies indicated that extensive genetic variations could be generated due to polyploidy, which is considered to be closely associated with the manifestation of polyploid heterosis. Our previous studies confirmed that triploid loquats demonstrated significant heterosis, other than the ploidy effect, but the underlying mechanisms are largely unknown. This study aimed to overcome the narrow genetic distance of loquats, increase the genetic variation level of triploid loquats, and systematically illuminate the heterosis mechanisms of triploid loquats derived from two cross combinations. Here, inter-simple sequence repeats (ISSRs) and simple sequence repeats (SSRs) were adopted for evaluating the genetic diversity, and transcriptome sequencing (RNA-Seq) was performed to investigate gene expression as well as pathway changes in the triploids. We found that extensive genetic variations were produced during the formation of triploid loquats. The polymorphism ratios of ISSRs and SSRs were 43.75% and 19.32%, respectively, and almost all their markers had a PIC value higher than 0.5, suggesting that both ISSRs and SSRs could work well in loquat assisted breeding. Furthermore, our results revealed that by broadening the genetic distance between the parents, genetic variations in triploids could be promoted. Additionally, RNA-Seq results suggested that numerous genes differentially expressed between the triploids and parents were screened out. Moreover, KEGG analyses revealed that “photosynthetic efficiency” and “glyco-metabolism” were significantly changed in triploid loquats compared with the parents, which was consistent with the results of physiological indicator analyses, leaf micro-structure observations, and qRT-PCR validation. Collectively, our results suggested that extensive genetic variations occurred in the triploids and that the changes in the “photosynthetic efficiency” as well as “glyco-metabolism” of triploids might have further resulted in heterosis manifestation in the triploid loquats.

ZmCCT haplotype H5 improves yield, stalk-rot resistance, and drought tolerance in maize

The ZmCCT locus underlies both stalk-rot resistance and photoperiod sensitivity in maize (Zea mays L.). We previously introduced nine resistant ZmCCT haplotypes into seven elite but susceptible maize inbred lines (containing the haplotype H1) to generate 63 backcross families. Here, we continued backcrossing, followed by selfing, to develop 63 near-isogenic lines (NILs). We evaluated 22 of these NILs for stalk-rot resistance and flowering time under long-day conditions. Lines harboring the haplotype H5 outperformed the others, steadily reducing disease severity, while showing less photoperiod sensitivity. To demonstrate the value of haplotype H5 for maize production, we selected two pairs of NILs, 83B28 ^H1 /83B28 ^H5 and A5302 ^H1 /A5302 ^H5 , and generated F₁ hybrids with the same genetic backgrounds but different ZmCCT alleles: 83B28 ^H1 × A5302 ^H1 , 83B28 ^H1 × A5302 ^H5 , 83B28 ^H5 × A5302 ^H1 , and 83B28 ^H5 × A5302 ^H5 . We performed field trials to investigate yield/yield-related traits, stalk-rot resistance, flowering time, and drought/salt tolerance in these four hybrids. 83B28 ^H5 × A5302 ^H1 performed the best, with significantly improved yield, stalk-rot resistance, and drought tolerance compared to the control (83B28 ^H1 × A5302 ^H1 ). Therefore, the ZmCCT haplotype H5 has great value for breeding maize varieties with high yield potential, stalk-rot resistance, and drought tolerance.

Fine mapping of candidate quantitative trait loci for plant and ear height in a maize nested-association mapping population

Plant height (PH) and ear height (EH) are two important traits in maize (Zea mays L.), as they are closely related to lodging resistance and planting density. Our objectives were to (1) investigate single-nucleotide polymorphisms (SNPs) that are associated with PH and EH for detecting quantitative trait loci (QTL) and new gene that determines PH and EH, (2) explore the value of the QTL in maize breeding, and (3) investigate whether the "triangle heterotic group" theory is applicable for lowering PH and EH to increase yield. Seven inbred female parents were crossed with a common founder male parent Ye 107 to create a nested association mapping (NAM) population. The analysis of phenotypic data on PH and EH revealed wide variation among the parents of the NAM population. Genome-wide association study (GWAS) and high-resolution linkage mapping were conducted using the NAM population, which generated 264,694 SNPs by genotyping-by-sequencing. A total of 105 SNPs and 22 QTL were identified by GWAS and found to be significantly associated with PH and EH. A high-confidence QTL for PH, Qtl-chr1-EP, was identified on chromosome 1 via GWAS and confirmed by linkage analysis in two recombinant inbred line (RIL) populations. Results revealed that the SNP variation in the promoter region of the candidate gene Zm00001d031938, located at Qtl-chr1-EP, which encoded UDP-N-acetylglucosamine-peptide N-acetyl-glucosaminyl-transferase, might decrease PH and EH. Furthermore, the triangle heterotic pattern adopted in maize breeding programs by our team is practicable in selecting high-yield crosses based on the low ratio of EH/PH (EP).

Epistasis Activation Contributes Substantially to Heterosis in Temperate by Tropical Maize Hybrids

Epistasis strongly affects the performance of superior maize hybrids. In this study, a multiple-hybrid population, consisting of three hybrid maize sets with varied interparental divergence, was generated by crossing 28 temperate and 23 tropical inbred lines with diverse genetic backgrounds. We obtained 1,154 tested hybrids. Among these tested hybrids, heterosis increased steadily as the heterotic genetic distance increased. Mid-parent heterosis was significantly higher in the temperate by tropical hybrids than in the temperate by temperate hybrids. Genome-wide prediction and association mapping was performed for grain weight per plant (GWPP) and days to silking (DTS) using 20K high-quality SNPs, showing that epistatic effects played a more prominent role than dominance effects in temperate by tropical maize hybrids. A total of 33 and 420 epistatic QTL were identified for GWPP and DTS, respectively, in the temperate by tropical hybrids. Protein-protein interaction network and gene-set enrichment analyses showed that epistatic genes were involved in protein interactions, which play an important role in photosynthesis, biological transcription pathways, and protein synthesis. We showed that the interaction of many minor-effect genes in the hybrids could activate the transcription activators of epistatic genes, resulting in a cascade of amplified yield heterosis. The multiple-hybrid population design enhanced our understanding of heterosis in maize, providing an insight into the acceleration of hybrid maize breeding by activating epistatic effects.

Genetic Parameters for Selected Traits of Inbred Lines of Maize (Zea mays L.)

This paper presents an estimation of the parameters connected with the additive (a) effect, additive by additive (aa) epistatic effect, and additive by additive by additive (aaa) interaction gene effect for nine quantitative traits of maize (Zea mays L.) inbred lines. To our knowledge, this is the first report about aaa interaction of maize inbred lines. An analysis was performed on 252 lines derived from Plant Breeding Smolice Ltd. (Smolice, Poland)—Plant Breeding and Acclimatization Institute-National Research Institute Group (151 lines) and Małopolska Plant Breeding Ltd. (Kobierzyce, Poland) (101 lines). The total additive effects were significant for all studied cases. Two-way and three-way significant interactions were found in most analyzed cases with a considerable impact on phenotype. Omitting the inclusion of higher-order interactions effect in quantitative genetics may result in a substantial underestimation of additive QTL effects. Expanding models with that information may also be helpful in future homozygous line crossing projects.

Expression Patterns Divergence of Reciprocal F1 Hybrids Between Gossypium hirsutum and Gossypium barbadense Reveals Overdominance Mediating Interspecific Biomass Heterosis

Hybrid breeding has provided an impetus to the process and achievement of a higher yield and quality of crops. Interspecific hybridization is critical for resolving parental genetic diversity bottleneck problems. The reciprocal interspecific hybrids and their parents (Gossypium hirsutum and Gossypium barbadense) have been applied in this study to elucidate the transcription regulatory mechanism of early biomass heterosis. Phenotypically, the seed biomass, plant height over parent heterosis, leaf area over parent heterosis, and fresh and dry biomass were found to be significantly higher in hybrids than in parents. Analysis of leaf areas revealed that the one-leaf stage exhibits the most significant performance in initial vegetative growth vigor and larger leaves in hybrids, increasing the synthesis of photosynthesis compounds and enhancing photosynthesis compound synthesis. Comparative transcriptome analysis showed that transgressive down-regulation (TDR) is the main gene expression pattern in the hybrids (G. hirsutum × G. barbadense, HB), and it was found that the genes of photosystem I and Adenosine triphosphate (ATP)-binding may promote early growth vigor. Transgressive up-regulation (TUR) is the major primary gene expression pattern in the hybrids (G. barbadense × G. hirsutum, BH), and photosystem II-related genes mediated the performance of early biomass heterosis. The above results demonstrated that overdominance mediates biomass heterosis in interspecific hybrid cotton and the supervisory mechanism divergence of hybrids with different females. Photosynthesis and other metabolic process are jointly involved in controlling early biomass heterosis in interspecific hybrid cotton. The expression pattern data of transcriptome sequencing were supported using the qRT-PCR analysis. Our findings could be useful in theoretical and practical studies of early interspecific biomass heterosis, and the results provide potential resources for the theoretical and applied research on early interspecific biomass heterosis.

Dissection of the Genetic Basis of Yield Traits in Line per se and Testcross Populations and Identification of Candidate Genes for Hybrid Performance in Maize

Dissecting the genetic basis of yield traits in hybrid populations and identifying the candidate genes are important for molecular crop breeding. In this study, a BC1F3:4 population, the line per se (LPS) population, was constructed by using elite inbred lines Zheng58 and PH4CV as the parental lines. The population was genotyped with 55,000 SNPs and testcrossed to Chang7-2 and PH6WC (two testers) to construct two testcross (TC) populations. The three populations were evaluated for hundred kernel weight (HKW) and yield per plant (YPP) in multiple environments. Marker-trait association analysis (MTA) identified 24 to 151 significant SNPs in the three populations. Comparison of the significant SNPs identified common and specific quantitative trait locus/loci (QTL) in the LPS and TC populations. Genetic feature analysis of these significant SNPs proved that these SNPs were associated with the tested traits and could be used to predict trait performance of both LPS and TC populations. RNA-seq analysis was performed using maize hybrid varieties and their parental lines, and differentially expressed genes (DEGs) between hybrid varieties and parental lines were identified. Comparison of the chromosome positions of DEGs with those of significant SNPs detected in the TC population identified potential candidate genes that might be related to hybrid performance. Combining RNA-seq analysis and MTA results identified candidate genes for hybrid performance, providing information that could be useful for maize hybrid breeding.

From hybrid genomes to heterotic trait output: Challenges and opportunities

Heterosis (or hybrid vigor) has been widely used in crop seed breeding to improve many key economic traits. Nevertheless, the genetic and molecular basis of this important phenomenon has long remained elusive, constraining its flexible and effective exploitation. Advanced genomic approaches are efficient in characterizing the mechanism of heterosis. Here, we review how the omics approaches, including genomic, transcriptomic, and population genetics methods such as genome-wide association studies, can reveal how hybrid genomes outperform parental genomes in plants. This information opens up opportunities for genomic exploration and manipulation of heterosis in crop breeding.

Target-oriented prioritization: targeted selection strategy by integrating organismal and molecular traits through predictive analytics in breeding

Genomic prediction in crop breeding is hindered by modeling on limited phenotypic traits. We propose an integrative multi-trait breeding strategy via machine learning algorithm, target-oriented prioritization (TOP). Using a large hybrid maize population, we demonstrate that the accuracy for identifying a candidate that is phenotypically closest to an ideotype, or target variety, achieves up to 91%. The strength of TOP is enhanced when omics level traits are included. We show that TOP enables selection of inbreds or hybrids that outperform existing commercial varieties. It improves multiple traits and accurately identifies improved candidates for new varieties, which will greatly influence breeding.

Enhancing crop diversity for food security in the face of climate uncertainty

Global agriculture is dominated by a handful of species that currently supply a huge proportion of our food and feed. It additionally faces the massive challenge of providing food for 10 billion people by 2050, despite increasing environmental deterioration. One way to better plan production in the face of current and continuing climate change is to better understand how our domestication of these crops included their adaptation to environments that were highly distinct from those of their centre of origin. There are many prominent examples of this, including the development of temperate Zea mays (maize) and the alteration of day-length requirements in Solanum tuberosum (potato). Despite the pre-eminence of some 15 crops, more than 50 000 species are edible, with 7000 of these considered semi-cultivated. Opportunities afforded by next-generation sequencing technologies alongside other methods, including metabolomics and high-throughput phenotyping, are starting to contribute to a better characterization of a handful of these species. Moreover, the first examples of de novo domestication have appeared, whereby key target genes are modified in a wild species in order to confer predictable traits of agronomic value. Here, we review the scale of the challenge, drawing extensively on the characterization of past agriculture to suggest informed strategies upon which the breeding of future climate-resilient crops can be based.

Genome optimization via virtual simulation to accelerate maize hybrid breeding

The employment of doubled-haploid (DH) technology in maize has vastly accelerated the efficiency of developing inbred lines. The selection of superior lines has to rely on genotypes with genomic selection (GS) model, rather than phenotypes due to the high expense of field phenotyping. In this work, we implemented 'genome optimization via virtual simulation (GOVS)' using the genotype and phenotype data of 1404 maize lines and their F1 progeny. GOVS simulates a virtual genome encompassing the most abundant 'optimal genotypes' or 'advantageous alleles' in a genetic pool. Such a virtually optimized genome, although can never be developed in reality, may help plot the optimal route to direct breeding decisions. GOVS assists in the selection of superior lines based on the genomic fragments that a line contributes to the simulated genome. The assumption is that the more fragments of optimal genotypes a line contributes to the assembly, the higher the likelihood of the line favored in the F1 phenotype, e.g. grain yield. Compared to traditional GS method, GOVS-assisted selection may avoid using an arbitrary threshold for the predicted F1 yield to assist selection. Additionally, the selected lines contributed complementary sets of advantageous alleles to the virtual genome. This feature facilitates plotting the optimal route for DH production, whereby the fewest lines and F1 combinations are needed to pyramid a maximum number of advantageous alleles in the new DH lines. In summary, incorporation of DH production, GS and genome optimization will ultimately improve genomically designed breeding in maize. Short abstract: Doubled-haploid (DH) technology has been widely applied in maize breeding industry, as it greatly shortens the period of developing homozygous inbred lines via bypassing several rounds of self-crossing. The current challenge is how to efficiently screen the large volume of inbred lines based on genotypes. We present the toolbox of genome optimization via virtual simulation (GOVS), which complements the traditional genomic selection model. GOVS simulates a virtual genome encompassing the most abundant 'optimal genotypes' in a breeding population, and then assists in selection of superior lines based on the genomic fragments that a line contributes to the simulated genome. Availability of GOVS (https://govs-pack.github.io/) to the public may ultimately facilitate genomically designed breeding in maize.

Heterosis goes underground

This article comments on:

Dafna A, Halperin I, Oren E, Isaacson T, Tzuri G, Meir A, Schaffer AA, Burger J, Tadmor Y, Buckler ES, Gur A. 2021. Underground heterosis for yield improvement in melon. Journal of Experimental Botany 72, 6205–6218.

Advances in Research on the Mechanism of Heterosis in Plants

Heterosis is a common biological phenomenon in nature. It substantially contributes to the biomass yield and grain yield of plants. Moreover, this phenomenon results in high economic returns in agricultural production. However, the utilization of heterosis far exceeds the level of theoretical research on this phenomenon. In this review, the recent progress in research on heterosis in plants was reviewed from the aspects of classical genetics, parental genetic distance, quantitative trait loci, transcriptomes, proteomes, epigenetics (DNA methylation, histone modification, and small RNA), and hormone regulation. A regulatory network of various heterosis-related genes under the action of different regulatory factors was summarized. This review lays a foundation for the in-depth study of the molecular and physiological aspects of this phenomenon to promote its effects on increasing the yield of agricultural production.

LightGBM: accelerated genomically designed crop breeding through ensemble learning

LightGBM is an ensemble model of decision trees for classification and regression prediction. We demonstrate its utility in genomic selection-assisted breeding with a large dataset of inbred and hybrid maize lines. LightGBM exhibits superior performance in terms of prediction precision, model stability, and computing efficiency through a series of benchmark tests. We also assess the factors that are essential to ensure the best performance of genomic selection prediction by taking complex scenarios in crop hybrid breeding into account. LightGBM has been implemented as a toolbox, CropGBM, encompassing multiple novel functions and analytical modules to facilitate genomically designed breeding in crops.