Correlation between parental transcriptome and field data for the characterization of heterosis in Zea mays L

Correlation between Parental Transcriptome and Field Data for the Characterization of Heterosis in Chinese Cabbage

In Chinese cabbage breeding, hybrids have made a terrific contribution due to heterosis, the superior performance of offspring compared to their inbred parents. Since the development of new, top-performing hybrids requires a large scale of human and material resources, the prediction of hybrid performance is of utmost interest to plant breeders. In our research, leaf transcriptome data from eight parents were used to investigate if they might be employed as markers to predict hybrid performance and heterosis. In Chinese cabbage, heterosis of plant growth weight (PGW) and heterosis of head weight (HW) were more obvious than other traits. The number of differential expression genes (DEGs) between parents was related to the PGW, length of the biggest outer leaf (LOL), leaf head height (LHH), leaf head width (LHW), HW, leaf number of head (LNH) and plant height (PH) of hybrids, and up-regulated DEGs number was also associated with these traits. Euclidean and binary distances of parental gene expression levels were significantly correlated with the PGW, LOL, LHH, LHW, HW and PH of hybrids. Additionally, there was a significant correlation between the parental expression levels of multiple genes involved in the ribosomal metabolic pathway and hybrid observations and heterosis in PGW, with the BrRPL23A gene showing the highest correlation with the MPH of PGW(r = 0.75). Therefore, leaf transcriptome data can preliminarily predict the hybrid performance and select parents in Chinese cabbage.

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.

A Review of Integrative Omic Approaches for Understanding Rice Salt Response Mechanisms

Soil salinity is one of the most serious environmental challenges, posing a growing threat to agriculture across the world. Soil salinity has a significant impact on rice growth, development, and production. Hence, improving rice varieties’ resistance to salt stress is a viable solution for meeting global food demand. Adaptation to salt stress is a multifaceted process that involves interacting physiological traits, biochemical or metabolic pathways, and molecular mechanisms. The integration of multi-omics approaches contributes to a better understanding of molecular mechanisms as well as the improvement of salt-resistant and tolerant rice varieties. Firstly, we present a thorough review of current knowledge about salt stress effects on rice and mechanisms behind rice salt tolerance and salt stress signalling. This review focuses on the use of multi-omics approaches to improve next-generation rice breeding for salinity resistance and tolerance, including genomics, transcriptomics, proteomics, metabolomics and phenomics. Integrating multi-omics data effectively is critical to gaining a more comprehensive and in-depth understanding of the molecular pathways, enzyme activity and interacting networks of genes controlling salinity tolerance in rice. The key data mining strategies within the artificial intelligence to analyse big and complex data sets that will allow more accurate prediction of outcomes and modernise traditional breeding programmes and also expedite precision rice breeding such as genetic engineering and genome editing.

Transcriptome Reveals Allele Contribution to Heterosis in Maize

Heterosis, which has greatly increased maize yields, is associated with gene expression patterns during key developmental stages that enhance hybrid phenotypes relative to parental phenotypes. Before heterosis can be more effectively used for crop improvement, hybrid maize developmental gene expression patterns must be better understood. Here, six maize hybrids, including the popular hybrid Zhengdan958 (ZC) from China, were studied. Maize hybrids created in-house were generated using an incomplete diallel cross (NCII)-based strategy from four elite inbred parental lines. Differential gene expression (DEG) profiles corresponding to three developmental stages revealed that hybrid partial expression patterns exhibited complementarity of expression of certain parental genes, with parental allelic expression patterns varying both qualitatively and quantitatively in hybrids. Single-parent expression (SPE) and parent-specific expression (PSE) types of qualitative variation were most prevalent, 43.73 and 41.07% of variation, respectively. Meanwhile, negative super-dominance (NSD) and positive super-dominance (PSD) types of quantitative variation were most prevalent, 31.06 and 24.30% of variation, respectively. During the early reproductive growth stage, the gene expression pattern differed markedly from other developmental stage patterns, with allelic expression patterns during seed development skewed toward low-value parental alleles in hybrid seeds exhibiting significant quantitative variation-associated superiority. Comparisons of qualitative gene expression variation rates between ZC and other hybrids revealed proportions of SPE-DEGs (41.36%) in ZC seed DEGs that significantly exceeded the average proportion of SPE-DEGs found in seeds of other hybrids (28.36%). Importantly, quantitative gene expression variation rate comparisons between ZC and hybrids, except for transgressive expression, revealed that the ZC rate exceeded the average rate for other hybrids, highlighting the importance of partial gene expression in heterosis. Moreover, enriched ZC DEGs exhibiting distinct tissue-specific expression patterns belonged to four biological pathways, including photosynthesis, plant hormone signal transduction, biology metabolism and biosynthesis. These results provide valuable technical insights for creating hybrids exhibiting strong heterosis.

Overdominance at the Gene Expression Level Plays a Critical Role in the Hybrid Root Growth of Brassica napus

Despite heterosis contributing to genetic improvements in crops, root growth heterosis in rapeseed plants is poorly understood at the molecular level. The current study was performed to discover key differentially expressed genes (DEGs) related to heterosis in two hybrids with contrasting root growth performance (FO; high hybrid and FV; low hybrid) based on analysis of the root heterosis effect. Based on comparative transcriptomic analysis, we believe that the overdominance at the gene expression level plays a critical role in hybrid roots’ early biomass heterosis. Our findings imply that a considerable increase in up-regulation of gene expression underpins heterosis. In the FO hybrid, high expression of DEGs overdominant in the starch/sucrose and galactose metabolic pathways revealed a link between hybrid vigor and root growth. DEGs linked to auxin, cytokinin, brassinosteroids, ethylene, and abscisic acid were also specified, showing that these hormones may enhance mechanisms of root growth and the development in the FO hybrid. Moreover, transcription factors such as MYB, ERF, bHLH, NAC, bZIP, and WRKY are thought to control downstream genes involved in root growth. Overall, this is the first study to provide a better understanding related to the regulation of the molecular mechanism of heterosis, which assists in rapeseed growth and yield improvement.

Single-parent expression drives dynamic gene expression complementation in maize hybrids

Single-parent expression (SPE) is defined as gene expression in only one of the two parents. SPE can arise from differential expression between parental alleles, termed non-presence/absence (non-PAV) SPE, or from the physical absence of a gene in one parent, termed PAV SPE. We used transcriptome data of diverse Zea mays (maize) inbreds and hybrids, including 401 samples from five different tissues, to test for differences between these types of SPE genes. Although commonly observed, SPE is highly genotype and tissue specific. A positive correlation was observed between the genetic distance of the two inbred parents and the number of SPE genes identified. Regulatory analysis showed that PAV SPE and non-PAV SPE genes are mainly regulated by cis effects, with a small fraction under trans regulation. Polymorphic transposable element insertions in promoter sequences contributed to the high level of cis regulation for PAV SPE and non-PAV SPE genes. PAV SPE genes were more frequently expressed in hybrids than non-PAV SPE genes. The expression of parentally silent alleles in hybrids of non-PAV SPE genes was relatively rare but occurred in most hybrids. Non-PAV SPE genes with expression of the silent allele in hybrids are more likely to exhibit above high parent expression level than hybrids that do not express the silent allele, leading to non-additive expression. This study provides a comprehensive understanding of the nature of non-PAV SPE and PAV SPE genes and their roles in gene expression complementation in maize hybrids.

Single-Parent Expression of Anti-sense RNA Contributes to Transcriptome Complementation in Maize Hybrid

Anti-sense transcription is increasingly being recognized as an important regulator of gene expression. But the transcriptome complementation of anti-sense RNA in hybrid relative to their inbred parents was largely unknown. In this study, we profiled strand-specific RNA sequencing (RNA-seq) in a maize hybrid and its inbred parents (B73 and Mo17) in two tissues. More anti-sense transcripts were present in the hybrid compared with the parental lines. We detected 293 and 242 single-parent expression of anti-sense (SPEA) transcripts in maize immature ear and leaf tissues, respectively. There was little overlap of the SPEA transcripts between the two maize tissues. These results suggested that SPEA is a general mechanism that drives extensive complementation in maize hybrids. More importantly, extremely high-level expression of anti-sense transcripts was associated with low-level expression of the cognate sense transcript by reducing the level of histone H3 lysine 36 methylation (H3K36me3). In summary, these SPEA transcripts increased our knowledge about the transcriptomic complementation in hybrid.

Transcriptome analysis of biological pathways associated with heterosis in Chinese cabbage

Chinese cabbage is an important vegetable in Asia, and high-yielding hybrids are needed to cope with the growing demand. A comparative transcriptome profiling was conducted to reveal the differentially expressed genes (DEGs) associated with heterosis in two hybrids relative to their parents. Our data suggests that heterosis is underlined by a significant upregulation of gene expression. High expression of DEGs in glycolysis and photosynthesis pathways in hybrids depicted their relation with growth and hybrid vigor. Besides, DEGs related to auxin, abscisic acid, ethylene and gibberellin were identified, implying that these hormones may boost the mechanisms of growth and developmental processes in the hybrids. Furthermore, transcription factors, including bHLH, ERF, MYB and WRKY were predicted to regulate downstream genes linked to hybrid vigor. Collectively, the present study will be helpful for a better understanding of the regulation mechanisms of heterosis to aid cabbage yield improvement.

The Role of Transcriptional Regulation in Hybrid Vigor

The genetic basis of hybrid vigor in plants remains largely unsolved but strong evidence suggests that variation in transcriptional regulation can explain many aspects of this phenomenon. Natural variation in transcriptional regulation is highly abundant in virtually all species and thus a potential source of heterotic variability. Allele Specific Expression (ASE), which is tightly linked to parent of origin effects and modulated by complex interactions in cis and in trans, is generally considered to play a key role in explaining the differences between hybrids and parental lines. Here we discuss the recent developments in elucidating the role of transcriptional variation in a number of aspects of hybrid vigor, thereby bridging old paradigms and hypotheses with contemporary research in various species.

Small RNA-based prediction of hybrid performance in maize

BACKGROUND

Small RNA (sRNA) sequences are known to have a broad impact on gene regulation by various mechanisms. Their performance for the prediction of hybrid traits has not yet been analyzed. Our objective was to analyze the relation of parental sRNA expression with the performance of their hybrids, to develop a sRNA-based prediction approach, and to compare it to more common SNP and mRNA transcript based predictions using a factorial mating scheme of a maize hybrid breeding program.

RESULTS

Correlation of genomic differences and messenger RNA (mRNA) or sRNA expression differences between parental lines with hybrid performance of their hybrids revealed that sRNAs showed an inverse relationship in contrast to the other two data types. We associated differences for SNPs, mRNA and sRNA expression between parental inbred lines with the performance of their hybrid combinations and developed two prediction approaches using distance measures based on associated markers. Cross-validations revealed parental differences in sRNA expression to be strong predictors for hybrid performance for grain yield in maize, comparable to genomic and mRNA data. The integration of both positively and negatively associated markers in the prediction approaches enhanced the prediction accurary. The associated sRNAs belong predominantly to the canonical size classes of 22- and 24-nt that show specific genomic mapping characteristics.

CONCLUSION

Expression profiles of sRNA are a promising alternative to SNPs or mRNA expression profiles for hybrid prediction, especially for plant species without reference genome or transcriptome information. The characteristics of the sRNAs we identified suggest that association studies based on breeding populations facilitate the identification of sRNAs involved in hybrid performance.

Parental Expression Variation of Small RNAs Is Negatively Correlated with Grain Yield Heterosis in a Maize Breeding Population

Heterosis refers to a quantitative phenomenon in which F1 hybrid trait values exceed the mean of the parental values in a positive direction. Generally, it is dependent on a high degree of heterozygosity, which is maintained in hybrid breeding by developing parental lines in separate, genetically distinct heterotic groups. The mobility of small RNAs (sRNAs) that mediate epigenetic regulation of gene expression renders them promising candidates for modulating the action of combined diverse genomes in trans-and evidence already indicates their contribution to transgressive phenotypes. By sequencing small RNA libraries of a panel of 21 maize parental inbred lines we found a low overlap of 35% between the sRNA populations from both distinct heterotic groups. Surprisingly, in contrast to genetic or gene expression variation, parental sRNA expression variation is negatively correlated with grain yield (GY) heterosis. Among 0.595 million expressed sRNAs, we identified 9,767, predominantly 22- and 24-nt long sRNAs, which showed an association of their differential expression between parental lines and GY heterosis of the respective hybrids. Of these sRNAs, 3,485 or 6,282 showed an association with high or low GY heterosis, respectively, thus the low heterosis associated group prevailing at 64%. The heterosis associated sRNAs map more frequently to genes that show differential expression between parental lines than reference sets. Together these findings suggest that trans-chromosomal actions of sRNAs in hybrids might add up to a negative contribution in heterosis formation, mediated by unfavorable gene expression regulation. We further revealed an exclusive accumulation of 22-nt sRNAs that are associated with low GY heterosis in pericentromeric genomic regions. That recombinational suppression led to this enrichment is indicated by its close correlation with low recombination rates. The existence of this enrichment, which we hypothesize resulted from the separated breeding of inbred lines within heterotic groups, may have implications for hybrid breeding strategies addressing the recombinational constraints characteristic of complex crop genomes.

Transcriptomics and proteomics reveal genetic and biological basis of superior biomass crop Miscanthus

Miscanthus is a rhizomatous C4 grass which is considered as potential high-yielding energy crop with the low-nutrient requirements, high water-use efficiency, and capability of C mitigation. To better understand the genetic basis, an integrative analysis of the transcriptome and proteome was performed to identify important genes and pathways involved in Miscanthus leaves. At the transcript level, 64,663 transcripts in M. lutarioriparius, 97,043 in M. sacchariflorus, 97,043 in M. sinensis, 67,323 in M. floridulus and 70,021 in M. × giganteus were detected by an RNA sequencing approach. At the protein level, 1964 peptide-represented proteins were identified and 1933 proteins differed by 1.5-fold or more in their relative abundance, as indicated by iTRAQ (isobaric tags for relative and absolute quantitation) analysis. Phylogenies were constructed from the nearly taxa of Miscanthus. A large number of genes closely related to biomass production were found. And SSR markers and their corresponding primers were derived from Miscanthus transcripts and 90% of them were successfully detected by PCR amplification among Miacanthus species. These similarities and variations on the transcriptional and proteomic level between Miscanthus species will serve as a resource for research in Miscanthus and other lignocellulose crops.

Hybridization and emergence of virulence in opportunistic human yeast pathogens

Hybridization between different species can result in the emergence of new lineages and adaptive phenotypes. Occasionally, hybridization in fungal organisms can drive the appearance of opportunistic lifestyles or shifts to new hosts, resulting in the emergence of novel pathogens. In recent years, an increasing number of studies have documented the existence of hybrids in diverse yeast clades, including some comprising human pathogens. Comparative and population genomics studies performed on these clades are enabling us to understand what roles hybridization may play in the evolution and emergence of a virulence potential towards humans. Here we survey recent genomic studies on several yeast pathogenic clades where hybrids have been identified, and discuss the broader implications of hybridization in the evolution and emergence of pathogenic lineages. © 2017 The Authors. Yeast published by John Wiley & Sons, Ltd.

Omics-based hybrid prediction in maize

Complementing genomic data with other "omics" predictors can increase the probability of success for predicting the best hybrid combinations using complex agronomic traits. Accurate prediction of traits with complex genetic architecture is crucial for selecting superior candidates in animal and plant breeding and for guiding decisions in personalized medicine. Whole-genome prediction has revolutionized these areas but has inherent limitations in incorporating intricate epistatic interactions. Downstream "omics" data are expected to integrate interactions within and between different biological strata and provide the opportunity to improve trait prediction. Yet, predicting traits from parents to progeny has not been addressed by a combination of "omics" data. Here, we evaluate several "omics" predictors-genomic, transcriptomic and metabolic data-measured on parent lines at early developmental stages and demonstrate that the integration of transcriptomic with genomic data leads to higher success rates in the correct prediction of untested hybrid combinations in maize. Despite the high predictive ability of genomic data, transcriptomic data alone outperformed them and other predictors for the most complex heterotic trait, dry matter yield. An eQTL analysis revealed that transcriptomic data integrate genomic information from both, adjacent and distant sites relative to the expressed genes. Together, these findings suggest that downstream predictors capture physiological epistasis that is transmitted from parents to their hybrid offspring. We conclude that the use of downstream "omics" data in prediction can exploit important information beyond structural genomics for leveraging the efficiency of hybrid breeding.

Comparative transcriptome analysis of flower heterosis in two soybean F1 hybrids by RNA-seq

Heterosis has been widely exploited as an approach to enhance crop traits during breeding. However, its underlying molecular genetic mechanisms remain unclear. Recent advances in RNA sequencing technology (RNA-seq) have provided an opportunity to conduct transcriptome profiling for heterosis studies. We used RNA-seq to analyze the flower transcriptomes of two F1 hybrid soybeans (HYBSOY-1 and HYBSOY-5) and their parents. More than 385 million high-quality reads were generated and aligned against the soybean reference genome. A total of 681 and 899 genes were identified as being differentially expressed between HYBSOY-1 and HYBSOY-5 and their parents, respectively. These differentially expressed genes (DEGs) were categorized into four major expression categories with 12 expression patterns. Furthermore, gene ontology (GO) term analysis showed that the DEGs were enriched in the categories metabolic process and catalytic activity, while Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis found that metabolic pathway and biosynthesis of secondary metabolites were enriched in the two F1 hybrids. Comparing the DEGs of the two F1 hybrids by GO term and KEGG pathway analyses identified 26 common DEGs that showed transgressive up-regulation, and which could be considered potential candidate genes for heterosis in soybean F1 hybrids. This identification of an extensive transcriptome dataset gives a comprehensive overview of the flower transcriptomes in two F1 hybrids, and provides useful information for soybean hybrid breeding. These findings lay the foundation for future studies on molecular mechanisms underlying soybean heterosis.

Transcriptome Analysis of Salt Stress Responsiveness in the Seedlings of Dongxiang Wild Rice (Oryza rufipogon Griff.)

Dongxiang wild rice (Oryza rufipogon Griff.) is the progenitor of cultivated rice (Oryza sativa L.), and is well known for its superior level of tolerance against cold, drought and diseases. To date, however, little is known about the salt-tolerant character of Dongxiang wild rice. To elucidate the molecular genetic mechanisms of salt-stress tolerance in Dongxiang wild rice, the Illumina HiSeq 2000 platform was used to analyze the transcriptome profiles of the leaves and roots at the seedling stage under salt stress compared with those under normal conditions. The analysis results for the sequencing data showed that 6,867 transcripts were differentially expressed in the leaves (2,216 up-regulated and 4,651 down-regulated) and 4,988 transcripts in the roots (3,105 up-regulated and 1,883 down-regulated). Among these differentially expressed genes, the detection of many transcription factor genes demonstrated that multiple regulatory pathways were involved in salt stress tolerance. In addition, the differentially expressed genes were compared with the previous RNA-Seq analysis of salt-stress responses in cultivated rice Nipponbare, indicating the possible specific molecular mechanisms of salt-stress responses for Dongxiang wild rice. A large number of the salt-inducible genes identified in this study were co-localized onto fine-mapped salt-tolerance-related quantitative trait loci, providing candidates for gene cloning and elucidation of molecular mechanisms responsible for salt-stress tolerance in rice.

Genetic properties of the MAGIC maize population: a new platform for high definition QTL mapping in Zea mays

BACKGROUND

Maize (Zea mays) is a globally produced crop with broad genetic and phenotypic variation. New tools that improve our understanding of the genetic basis of quantitative traits are needed to guide predictive crop breeding. We have produced the first balanced multi-parental population in maize, a tool that provides high diversity and dense recombination events to allow routine quantitative trait loci (QTL) mapping in maize.

RESULTS

We produced 1,636 MAGIC maize recombinant inbred lines derived from eight genetically diverse founder lines. The characterization of 529 MAGIC maize lines shows that the population is a balanced, evenly differentiated mosaic of the eight founders, with mapping power and resolution strengthened by high minor allele frequencies and a fast decay of linkage disequilibrium. We show how MAGIC maize may find strong candidate genes by incorporating genome sequencing and transcriptomics data. We discuss three QTL for grain yield and three for flowering time, reporting candidate genes. Power simulations show that subsets of MAGIC maize might achieve high-power and high-definition QTL mapping.

CONCLUSIONS

We demonstrate MAGIC maize's value in identifying the genetic bases of complex traits of agronomic relevance. The design of MAGIC maize allows the accumulation of sequencing and transcriptomics layers to guide the identification of candidate genes for a number of maize traits at different developmental stages. The characterization of the full MAGIC maize population will lead to higher power and definition in QTL mapping, and lay the basis for improved understanding of maize phenotypes, heterosis included. MAGIC maize is available to researchers.

Transcriptome Analysis of Interspecific Hybrid between Brassica napus and B. rapa Reveals Heterosis for Oil Rape Improvement

The hybrid between Brassica napus and B. rapa displays obvious heterosis in both growth performance and stress tolerances. A comparative transcriptome analysis for B. napus (AⁿAⁿCC genome), B. rapa (A^rA^r genome), and its hybrid F1 (AⁿA^rC genome) was carried out to reveal the possible molecular mechanisms of heterosis at the gene expression level. A total of 40,320 nonredundant unigenes were identified using B. rapa (AA genome) and B. oleracea (CC genome) as reference genomes. A total of 6,816 differentially expressed genes (DEGs) were mapped in the A and C genomes with 4,946 DEGs displayed nonadditively by comparing the gene expression patterns among the three samples. The coexistence of nonadditive DEGs including high-parent dominance, low-parent dominance, overdominance, and underdominance was observed in the gene action modes of F1 hybrid, which were potentially related to the heterosis. The coexistence of multiple gene actions in the hybrid was observed and provided a list of candidate genes and pathways for heterosis. The expression bias of transposable element-associated genes was also observed in the hybrid compared to their parents. The present study could be helpful for the better understanding of the determination and regulation of mechanisms of heterosis to aid Brassica improvement.

Hierarchical additive effects on heterosis in rice (Oryza sativa L.)

Exploitation of heterosis in crops has contributed greatly to improvement in global food and energy production. In spite of the pervasive importance of heterosis, a complete understanding of its mechanisms has remained elusive. In this study, a small test-crossed rice population was constructed to investigate the formation mechanism of heterosis for 13 traits. The results of the relative mid-parent heterosis and modes of inheritance of all investigated traits demonstrated that additive effects were the foundation of heterosis for complex traits in a hierarchical structure, and multiplicative interactions among the component traits were the framework of heterosis in complex traits. Furthermore, new balances between unit traits and related component traits provided hybrids with the opportunity to achieve an optimal degree of heterosis for complex traits. This study dissected heterosis of both reproductive and vegetative traits from the perspective of hierarchical structure for the first time. Additive multiplicative interactions of component traits were proven to be the origin of heterosis in complex traits. Meanwhile, more attention should be paid to component traits, rather than complex traits, in the process of revealing the mechanism of heterosis.

What is crop heterosis: new insights into an old topic

Heterosis (or hybrid vigor) refers to a natural phenomenon whereby hybrid offspring of genetically diverse individuals out-perform their parents in multiple traits including yield, adaptability and resistances to biotic and abiotic stressors. Innovations in technology and research continue to clarify the mechanisms underlying crop heterosis, however the intrinsic relationship between the biological basis of heterosis remain unclear. In this review, we aim to provide insight into the molecular genetic basis of heterosis by presenting recent advances in the 'omics' of heterosis and the role of non-coding regions, particularly in relation to energy-use efficiency. We propose that future research should focus on integrating the expanding datasets from different species and hybrid combinations, to mine key heterotic genes and unravel interactive 'omics' networks associated with heterosis. Improved understanding of heterosis and the biological basis for its manipulation in agriculture should help to streamline its use in enhancing crop productivity.

Identification of a bioactive Bowman-Birk inhibitor from an insect-resistant early maize inbred

Breeding of maize, Zea mays, has improved insect resistance, but the genetic and biochemical basis of many of these improvements is unknown. Maize oligonucleotide microarrays were utilized to identify differentially expressed genes in leaves of three maize inbreds, parents Oh40B and W8 and progeny Oh43, developed in the 1940s. Oh43 had enhanced leaf resistance to corn earworm larvae, Helicoverpa zea, and fall armyworm larvae, Spodoptera frugiperda, compared to one or both parents. Among ca. 100 significantly differentially expressed genes, expression of a Bowman-Birk trypsin inhibitor (BBI) gene was at least ca. 8-fold higher in Oh43 than in either parent. The Oh43 BBI gene was expressed as a recombinant protein. Purified BBI inhibited trypsin and the growth of fall armyworm larvae when added to insect diet. These experiments indicate that comparative gene expression analysis combined with insect resistance measurements of early inbreds can identify previously unrecognized resistance genes.

Genome-wide meta-analysis of maize heterosis reveals the potential role of additive gene expression at pericentromeric loci

BACKGROUND

The identification of QTL involved in heterosis formation is one approach to unravel the not yet fully understood genetic basis of heterosis - the improved agronomic performance of hybrid F1 plants compared to their inbred parents. The identification of candidate genes underlying a QTL is important both for developing markers and determining the molecular genetic basis of a trait, but remains difficult owing to the large number of genes often contained within individual QTL. To address this problem in heterosis analysis, we applied a meta-analysis strategy for grain yield (GY) of Zea mays L. as example, incorporating QTL-, hybrid field-, and parental gene expression data.

RESULTS

For the identification of genes underlying known heterotic QTL, we made use of tight associations between gene expression pattern and the trait of interest, identified by correlation analyses. Using this approach genes strongly associated with heterosis for GY were discovered to be clustered in pericentromeric regions of the complex maize genome. This suggests that expression differences of sequences in recombination-suppressed regions are important in the establishment of heterosis for GY in F1 hybrids and also in the conservation of heterosis for GY across genotypes. Importantly functional analysis of heterosis-associated genes from these genomic regions revealed over-representation of a number of functional classes, identifying key processes contributing to heterosis for GY. Based on the finding that the majority of the analyzed heterosis-associated genes were addtitively expressed, we propose a model referring to the influence of cis-regulatory variation on heterosis for GY by the compensation of fixed detrimental expression levels in parents.

CONCLUSIONS

The study highlights the utility of a meta-analysis approach that integrates phenotypic and multi-level molecular data to unravel complex traits in plants. It provides prospects for the identification of genes relevant for QTL, and also suggests a model for the potential role of additive expression in the formation and conservation of heterosis for GY via dominant, multigenic quantitative trait loci. Our findings contribute to a deeper understanding of the multifactorial phenomenon of heterosis, and thus to the breeding of new high yielding varieties.

Ups and downs of a transcriptional landscape shape iron deficiency associated chlorosis of the maize inbreds B73 and Mo17

BACKGROUND

Improving nutrient homeostasis is a major challenge of a sustainable maize cultivation, and cornerstone to ensure food supply for a growing world population. Although, iron constitutes an important nutrient, iron availability is limited. In this respect, iron deficiency associated chlorosis causes severe yield losses every year. Natural variation of the latter trait has yet not been addressed in maize and was therefore studied in the present analysis.

RESULTS

In this study, we i) report about the contrasting chlorosis phenotypes of the inbreds B73 and Mo17 at 10 and 300 μM iron regime, ii) identified over 400 significantly regulated transcripts (FDR < 0.05) within both inbreds at these growth conditions by deep RNA-Sequencing, iii) linked the gained knowledge with QTL information about iron deficiency related traits within the maize intermated B73 by Mo17 (IBM) population, and iv) highlighted contributing molecular pathways. In this respect, several genes within methionine salvage pathway and phytosiderophore synthesis were found to present constitutively high expression in Mo17, even under sufficient iron supply. Moreover, the same expression pattern could be observed for two putative bHLH transcription factors. In addition, a number of differentially expressed genes showed a co-localisation with QTL confidence intervals for iron deficiency related traits within the IBM population.

CONCLUSIONS

Our study highlights differential iron deficiency associated chlorosis between B73 and Mo17 and represents a valuable resource for differentially expressed genes upon iron limitation and chlorosis response. Besides identifying two putative bHLH transcription factors, we propose that methionine salvage pathway and sterol metabolism amongst others; underlie the contrasting iron deficiency related chlorosis phenotype of both inbreds. Altogether, this study emphasizes a contribution of selected genes and pathways on natural trait variation within the IBM population.

Identification and characterization of a repertoire of genes differentially expressed in developing top ear shoots between a superior hybrid and its parental inbreds in Zea mays L

Heterosis has been widely used in crop breeding and production; however, little is known about the genes controlling trait heterosis. The shortage of genes known to function in heterosis significantly limits our understanding of the molecular basis underlying heterosis. Here, we report 748 genes differentially expressed (DG) in the developing top ear shoots between a maize heterotic F1 hybrid (Mo17 × B73) and its parental inbreds identified using maize microarrays containing 28,608 unigene features. Of the 748 DG, over 600 were new for the inbred and hybrid combination. The DG were enriched for 35 of the total 213 maize gene ontology (GO) terms, including those describing photosynthesis, respiration, DNA replication, metabolism, and hormone biosynthesis. From the DG, we identified six genes involved in glycolysis, three genes in the citrate cycle, and four genes in the C4-dicarboxylic acid cycle. We mapped 533 of the 748 DG to the maize B73 genome, 298 (55.9 %) of which mapped to the QTL intervals of 11 maize ear traits. Moreover, we compared the repertoire of the DG with that of 14-day seedlings of the same inbred and hybrid combination. Only approximately 5 % of the DG was shared between the two organs and developmental stages. Furthermore, we mapped 417 (55.7 %) of the 748 maize DG to the QTL intervals of 26 rice yield-related traits. Therefore, this study provides a repertoire of genes useful for identification of genes involved in maize ear trait heterosis and information for a better understanding of the molecular basis underlying heterosis in maize.

Transcriptome analysis of rice root heterosis by RNA-Seq

Background

Heterosis is a phenomenon in which hybrids exhibit superior performance relative to parental phenotypes. In addition to the heterosis of above-ground agronomic traits on which most existing studies have focused, root heterosis is also an indispensable component of heterosis in the entire plant and of major importance to plant breeding. Consequently, systematic investigations of root heterosis, particularly in reproductive-stage rice, are needed. The recent advent of RNA sequencing technology (RNA-Seq) provides an opportunity to conduct in-depth transcript profiling for heterosis studies.

Results

Using the Illumina HiSeq 2000 platform, the root transcriptomes of the super-hybrid rice variety Xieyou 9308 and its parents were analyzed at tillering and heading stages. Approximately 391 million high-quality paired-end reads (100-bp in size) were generated and aligned against the Nipponbare reference genome. We found that 38,872 of 42,081 (92.4%) annotated transcripts were represented by at least one sequence read. A total of 829 and 4186 transcripts that were differentially expressed between the hybrid and its parents (DG_HP) were identified at tillering and heading stages, respectively. Out of the DG_HP, 66.59% were down-regulated at the tillering stage and 64.41% were up-regulated at the heading stage. At the heading stage, the DG_HP were significantly enriched in pathways related to processes such as carbohydrate metabolism and plant hormone signal transduction, with most of the key genes that are involved in the two pathways being up-regulated in the hybrid. Several significant DG_HP that could be mapped to quantitative trait loci (QTLs) for yield and root traits are also involved in carbohydrate metabolism and plant hormone signal transduction pathways.

Conclusions

An extensive transcriptome dataset was obtained by RNA-Seq, giving a comprehensive overview of the root transcriptomes at tillering and heading stages in a heterotic rice cross and providing a useful resource for the rice research community. Using comparative transcriptome analysis, we detected DG_HP and identified a group of potential candidate transcripts. The changes in the expression of the candidate transcripts may lay a foundation for future studies on molecular mechanisms underlying root heterosis.

Complementation contributes to transcriptome complexity in maize (Zea mays L.) hybrids relative to their inbred parents

Typically, F₁-hybrids are more vigorous than their homozygous, genetically distinct parents, a phenomenon known as heterosis. In the present study, the transcriptomes of the reciprocal maize (Zea mays L.) hybrids B73×Mo17 and Mo17×B73 and their parental inbred lines B73 and Mo17 were surveyed in primary roots, early in the developmental manifestation of heterotic root traits. The application of statistical methods and a suitable experimental design established that 34,233 (i.e., 86%) of all high-confidence maize genes were expressed in at least one genotype. Nearly 70% of all expressed genes were differentially expressed between the two parents and 42%–55% of expressed genes were differentially expressed between one of the parents and one of the hybrids. In both hybrids, ∼10% of expressed genes exhibited nonadditive gene expression. Consistent with the dominance model (i.e., complementation) for heterosis, 1124 genes that were expressed in the hybrids were expressed in only one of the two parents. For 65 genes, it could be shown that this was a consequence of complementation of genomic presence/absence variation. For dozens of other genes, alleles from the inactive inbred were activated in the hybrid, presumably via interactions with regulatory factors from the active inbred. As a consequence of these types of complementation, both hybrids expressed more genes than did either parental inbred. Finally, in hybrids, ∼14% of expressed genes exhibited allele-specific expression (ASE) levels that differed significantly from the parental-inbred expression ratios, providing further evidence for interactions of regulatory factors from one parental genome with target genes from the other parental genome.

Comparative proteomic study reveals dynamic proteome changes between superhybrid rice LYP9 and its parents at different developmental stages

Heterosis is a common phenomenon in which the hybrids exhibit superior agronomic performance than either inbred parental lines. Although hybrid rice is one of the most successful apotheoses in crops utilizing heterosis, the molecular mechanisms underlying rice heterosis remain elusive. To gain a better understanding of the molecular mechanisms of rice heterosis, comparative leaf proteomic analysis between a superhybrid rice LYP9 and its parental cultivars 9311 and PA64s at tillering, flowering and grain-filling stages were carried out. A total of 384 differentially expressed proteins (DP) were detected and 297 DP were identified, corresponding to 222 unique proteins. As DP were divided into those between the parents (DP(PP)) and between the hybrid and its parents (DP(HP)), the comparative results demonstrate that proteins in the categories of photosynthesis, glycolysis, and disease/defense were mainly enriched in DP. Moreover, the number of identified DP(HP) involved in photosynthesis, glycolysis, and disease/defense increased at flowering and grain-filling stages as compared to that at the tillering stage. Most of the up-regulated DP(HP) involved in the three categories showed greater expression in LYP9 at flowering and grain-filling stages than at the tillering stage. In addition, CO(2) assimilation rate and apparent quantum yield of photosynthesis also showed a greater increase in LYP9 at flowering and grain-filling stages than at the tillering stage. These results suggest that the proteins involved in photosynthesis, glycolysis, and disease/defense as well as their dynamic regulation at different developmental stages may be responsible for heterosis in rice.

Partial least squares regression, support vector machine regression, and transcriptome-based distances for prediction of maize hybrid performance with gene expression data

The performance of hybrids can be predicted with gene expression data from their parental inbred lines. Implementing such prediction approaches in breeding programs promises to increase the efficiency of hybrid breeding. The objectives of our study were to compare the accuracy of prediction models employing multiple linear regression (MLR), partial least squares regression (PLS), support vector machine regression (SVM), and transcriptome-based distances (D(B)). For a factorial of 7 flint and 14 dent maize lines, the grain yield of the hybrids was assessed and the gene expression of the parental lines was profiled with a 56k microarray. The accuracy of the prediction models was measured by the correlation between predicted and observed yield employing two cross-validation schemes. The first modeled the prediction of hybrids when testcross data are available for both parental lines (type 2 hybrids), and the second modeled the prediction of hybrids when no testcross data for the parental lines were available (type 0 hybrids). MLR, SVM, and PLS resulted in a high correlation between predicted and observed yield for type 2 hybrids, whereas for type 0 hybrids D(B) had greater prediction accuracy. The regression methods were robust to the choice of the set of profiled genes and required only a few hundred genes. In contrast, for an accurate hybrid prediction with D(B), 1,000-1,500 genes were required, and the prediction accuracy depended strongly on the set of profiled genes. We conclude that for prediction within one set of genetic material MLR is a promising approach, and for transferring prediction models from one set of genetic material to a related one, the transcriptome-based distance D(B) is most promising.

Dissecting grain yield pathways and their interactions with grain dry matter content by a two-step correlation approach with maize seedling transcriptome

BACKGROUND

The importance of maize for human and animal nutrition, but also as a source for bio-energy is rapidly increasing. Maize yield is a quantitative trait controlled by many genes with small effects, spread throughout the genome. The precise location of the genes and the identity of the gene networks underlying maize grain yield is unknown. The objective of our study was to contribute to the knowledge of these genes and gene networks by transcription profiling with microarrays.

RESULTS

We assessed the grain yield and grain dry matter content (an indicator for early maturity) of 98 maize hybrids in multi-environment field trials. The gene expression in seedlings of the parental inbred lines, which have four different genetic backgrounds, was assessed with genome-scale oligonucleotide arrays. We identified genes associated with grain yield and grain dry matter content using a newly developed two-step correlation approach and found overlapping gene networks for both traits. The underlying metabolic pathways and biological processes were elucidated. Genes involved in sucrose degradation and glycolysis, as well as genes involved in cell expansion and endocycle were found to be associated with grain yield.

CONCLUSIONS

Our results indicate that the capability of providing energy and substrates, as well as expanding the cell at the seedling stage, highly influences the grain yield of hybrids. Knowledge of these genes underlying grain yield in maize can contribute to the development of new high yielding varieties.

Enriched partial correlations in genome-wide gene expression profiles of hybrids (A. thaliana): a systems biological approach towards the molecular basis of heterosis

Heterosis is a well-known phenomenon but the underlying molecular mechanisms are not yet established. To contribute to the understanding of heterosis at the molecular level, we analyzed genome-wide gene expression profile data of Arabidopsis thaliana in a systems biological approach. We used partial correlations to estimate the global interaction structure of regulatory networks. Our hypothesis states that heterosis comes with an increased number of partial correlations which we interpret as increased numbers of regulatory interactions leading to enlarged adaptability of the hybrids. This hypothesis is true for mid-parent heterosis for our dataset of gene expression in two homozygous parental lines and their reciprocal crosses. For the case of best-parent heterosis just one hybrid is significant regarding our hypothesis based on a resampling analysis. Summarizing, both metabolome and gene expression level of our illustrative dataset support our proposal of a systems biological approach towards a molecular basis of heterosis.

Variation of the parental genome contribution in segregating populations derived from biparental crosses and its relationship with heterosis of their Design III progenies

The variation of the parental genome contribution (PGC) and its relationship with the genetic architecture of heterosis have received little attention. Our objectives were to (1) derive formulas for the variance of PGC in selfing, backcross (BC) or intermated generations produced from biparental crosses of homozygous parents, (2) investigate the correlation [Formula: see text] of the PGC [Formula: see text] estimated by a set M of markers, with Z (2) (half the trait difference between each pair of BC progenies) in the Design III, and (3) interpret experimental results on this correlation with regard to the genetic basis of heterosis. Under all mating systems, the variance of PGC is smaller in species with a larger number and more uniform length of chromosomes. It decreases with intermating and backcrossing but increases under selfing. The ratio of variances of PGC in F(1)DH (double haploids), F(2) and BC(1) populations is 4:2:1, but it is smaller in advanced selfing generations than expected for quantitative traits. Thus, altering the PGC by marker-assisted selection for the genetic background is more promising (i) in species with a smaller number and/or shorter chromosomes and (ii) in F(2) than in progenies of later selfing generations. The correlation [Formula: see text] depends on the linkage relationships between M and the QTL influencing Z(2) as well as the augmented dominance effects [Formula: see text] of the QTL, which include dominance and additive x additive effects with the genetic background, and sum up to mid-parent heterosis. From estimates of [Formula: see text] as well as QTL studies, we conclude that heterosis for grain yield in maize is caused by the action of numerous QTL distributed across the entire genome with positive [Formula: see text] effects.

Background correction of two-colour cDNA microarray data using spatial smoothing methods

The analysis of two-colour cDNA microarray data usually involves subtracting background values from foreground values prior to normalization and further analysis. This approach has the advantage of reducing bias and the disadvantage of blowing up the variance of lower abundant spots. Whenever background subtraction is considered, it implicitly assumes locally constant background values. In practice, this assumption is often not met, which casts doubts on the usefulness of simple background subtraction. In order to improve background correction, we propose local background smoothing within the pre-processing pipeline of cDNA microarray data prior to background correction. For this purpose, we employ a geostatistical framework with ordinary kriging using both isotropic and anisotropic models of spatial correlation and 2-D locally weighted regression. We show that application of local background smoothing prior to background correction is beneficial in comparison to using raw background estimates. This is done using data of a self-versus-self experiment in Arabidopsis where subsets of differentially expressed genes were simulated. Using locally smoothed background values in conjunction with existing background correction methods increases the power, increases the accuracy and decreases the number of false positive results.

Transcriptome-based distance measures for grouping of germplasm and prediction of hybrid performance in maize

Grouping of germplasm and prediction of hybrid performance and heterosis are important applications in hybrid breeding programs. Gene expression analysis is a promising tool to achieve both tasks efficiently. Our objectives were to (1) investigate distance measures based on transcription profiles, (2) compare these with genetic distances based on AFLP markers, and (3) assess the suitability of transcriptome-based distances for grouping of germplasm and prediction of hybrid performance and heterosis in maize. We analyzed transcription profiles from seedlings of the 21 parental maize lines of a 7 x 14 factorial with a 46-k oligonucleotide array. The hybrid performance and heterosis of the 98 hybrids were assessed in field trials. In cluster and principal coordinate analyses for germplasm grouping, the transcriptome-based distances were as powerful as the genetic distances for separating flint from dent inbreds. Cross validation showed that prediction of hybrid performance with transcriptome-based distances using selected markers was more precise than earlier prediction models using DNA markers or general combining ability estimates using field data. Our results suggest that transcriptome-based prediction of hybrid performance and heterosis has a great potential to improve the efficiency of maize hybrid breeding programs.