Zuxin Zhang

RNA sequencing reveals the complex regulatory network in the maize kernel

RNA sequencing can simultaneously identify exonic polymorphisms and quantitate gene expression. Here we report RNA sequencing of developing maize kernels from 368 inbred lines producing 25.8 billion reads and 3.6 million single-nucleotide polymorphisms. Both the MaizeSNP50 BeadChip and the Sequenom MassArray iPLEX platforms confirm a subset of high-quality SNPs. Of these SNPs, we have mapped 931,484 to gene regions with a mean density of 40.3 SNPs per gene. The genome-wide association study identifies 16,408 expression quantitative trait loci. A two-step approach defines 95.1% of the eQTLs to a 10-kb region, and 67.7% of them include a single gene. The establishment of relationships between eQTLs and their targets reveals a large-scale gene regulatory network, which include the regulation of 31 zein and 16 key kernel genes. These results contribute to our understanding of kernel development and to the improvement of maize yield and nutritional quality.

Genome-Wide Association Studies Identified Three Independent Polymorphisms Associated with α-Tocopherol Content in Maize Kernels

Tocopherols are a class of four natural compounds that can provide nutrition and function as antioxidant in both plants and animals. Maize kernels have low α-tocopherol content, the compound with the highest vitamin E activity, thus, raising the risk of vitamin E deficiency in human populations relying on maize as their primary vitamin E source. In this study, two insertion/deletions (InDels) within a gene encoding γ-tocopherol methyltransferase, Zea mays VTE4 (ZmVTE4), and a single nucleotide polymorphism (SNP) located ∼85 kb upstream of ZmVTE4 were identified to be significantly associated with α-tocopherol levels in maize kernels by conducting an association study with a panel of ∼500 diverse inbred lines. Linkage analysis in three populations that segregated at either one of these three polymorphisms but not at the other two suggested that the three polymorphisms could affect α-tocopherol content independently. Furthermore, we found that haplotypes of the two InDels could explain ∼33% of α-tocopherol variation in the association panel, suggesting ZmVTE4 is a major gene involved in natural phenotypic variation of α-tocopherol. One of the two InDels is located within the promoter region and associates with ZmVTE4 transcript level. This information can not only help in understanding the underlying mechanism of natural tocopherol variations in maize kernels, but also provide valuable markers for marker-assisted breeding of α-tocopherol content in maize kernels, which will then facilitate the improvement of maize as a better source of daily vitamin E nutrition.

Genome-wide identification and analysis of microRNA responding to long-term waterlogging in crown roots of maize seedlings

MicroRNAs (miRNAs) are critical post-transcriptional modulators of gene expression involving in plant responses to abiotic stress. However, the regulation of miRNA in the morphological response to waterlogging is poorly understood in maize. In this study, we detected miRNAs and their targets that expressed in waterlogged crown roots of maize seedlings in two inbred lines (Hz32 and Mo17) by RNA sequencing. A total of 61 mature miRNAs were found including 36 known maize (zma) miRNAs and 25 potential novel miRNA candidates. Comparison of miRNA expression in both waterlogged and control crown roots revealed 32 waterlogging-responsive miRNAs, most were consistently downregulated under waterlogging in the two inbred lines. We identified the miRNA targets through degradome sequencing. Many known miRNA targets involving in transcription regulation and reactive oxygen species elimination were found in the degradome libraries, and 17 targets of 10 newly detected miRNAs were identified as well. Moreover, the miRNA-mediated pathways that respond to waterlogging and regulate the induction of crown roots were discussed. This study is a comprehensive survey of responsive miRNAs in waterlogged maize crown roots. The results will help to understand the miRNA expression in response to waterlogging and miRNA-mediated regulation of morphological adaptation to waterlogging in maize.

Dynamic QTL Analysis and Candidate Gene Mapping for Waterlogging Tolerance at Maize Seedling Stage

Soil waterlogging is one of the major abiotic stresses adversely affecting maize growth and yield. To identify dynamic expression of genes or quantitative trait loci (QTL), QTL associated with plant height, root length, root dry weight, shoot dry weight and total dry weight were identified via conditional analysis in a mixed linear model and inclusive composite interval mapping method at three respective periods under waterlogging and control conditions. A total of 13, 19 and 23 QTL were detected at stages 3D|0D (the period during 0–3 d of waterlogging), 6D|3D and 9D|6D, respectively. The effects of each QTL were moderate and distributed over nine chromosomes, singly explaining 4.14–18.88% of the phenotypic variation. Six QTL (ph6-1, rl1-2, sdw4-1, sdw7-1, tdw4-1 and tdw7-1) were identified at two consistent stages of seedling development, which could reflect a continuous expression of genes; the remaining QTL were detected at only one stage. Thus, expression of most QTL was influenced by the developmental status. In order to provide additional evidence regarding the role of corresponding genes in waterlogging tolerance, mapping of Expressed Sequence Tags markers and microRNAs were conducted. Seven candidate genes were observed to co-localize with the identified QTL on chromosomes 1, 4, 6, 7 and 9, and may be important candidate genes for waterlogging tolerance. These results are a good starting point for understanding the genetic basis for selectively expressing of QTL in different stress periods and the common genetic control mechanism of the co-localized traits.

Identification of combining ability loci for five yield-related traits in maize using a set of testcrosses with introgression lines

Combining ability is essential for hybrid breeding in crops. However, the genetic basis of combining ability remains unclear and has been seldom investigated. Identifying molecular markers associated with this complex trait would help to understand its genetic basis and provide useful information for hybrid breeding in maize. In this study, we identified genetic loci of general combining ability (GCA) and specific combining ability (SCA) for five yield-related traits under three environments using a set of testcrosses with introgression lines (ILs). GCA or SCA of the five yield-related traits of the ILs was estimated by the performance of testcrosses with four testers from different heterotic groups. Genetic correlations between GCA of the traits and the corresponding traits per se were not significant or not strong, suggesting that the genetic basis between them is different. A total of 56 significant loci for GCA and 21 loci for SCA were commonly identified in at least two environments, and only 5 loci were simultaneously controlling GCA and SCA, indicating that the genetic basis of GCA and SCA is different. For all of the traits investigated, positive and significant correlations between the number of GCA loci in the ILs and the performance of the corresponding GCA of the ILs were detected, implying that pyramiding GCA loci would have positive effect on the performance of GCA. Results in this study would be useful for maize hybrid breeding.

Mining of Candidate Maize Genes for Nitrogen Use Efficiency by Integrating Gene Expression and QTL Data

Breeding maize varieties for high nitrogen (N) use efficiency (NUE) by marker-assisted selection using NUE quantitative trait locus (QTL) or by genetic transfer of NUE-associated genes is a viable approach for increasing grain yield in N-limited production areas. In this investigation, we evaluated a set of introgression line populations under N supply and N deficiency conditions. From 42 QTLs for grain yield and yield components, 23 were identified under N supply conditions and 33 from N limited conditions. Meta-analysis of published maize NUE QTLs revealed 37 “consensus” QTLs, of which, 18 was detected under low N conditions. In addition, 258 unique ESTs associated with low N stress response, N uptake, transport, and assimilation were aligned on the maize genome by in silico mapping. Integrating the EST map with the QTL map has resulted in the identification of candidate NUE-associated genes of the following functional categories: N uptake, transport, and assimilation; carbon (C) metabolism and assimilation; and cascades of stress response and signal transduction genes. Nine candidates that have been introgressed into Ye478 significantly altered grain yield/yield components. It is suggested that the dynamics of interactions between C and N metabolism are important for maize yield. A high NUE variety should have a highly efficient C assimilation per unit N and actively express CO2 assimilation-related genes under N-limited conditions.

Genetic bases of instability of male sterility and fertility reversibility in photoperiod-sensitive genic male-sterile rice

Abstract Photoperiod-sensitive genetic male-sterile (PSGMS) rice, with its male fertility regulated by photoperiod length, is very useful for hybrid rice development. However, breeding for new PSGMS lines has faced two major difficulties – the stability of male sterility and the reversibility of male fertility. In this study we assessed the genetic bases of stability of sterility and fertility reversibility using a molecular marker-based approach. A cross was made between two newly bred PSGMS lines: Peiai 64S, which has a stable sterility but is difficult to reverse to fertility, and 8902S, which has a unstable sterility but is easy to reverse to fertility. The fertility of the parents and of the F1 and F2 populations was repeatedly examined under 11 different long-day and short-day conditions. The genetic effects were assayed by interval mapping and two-way analyses of variance using the F2 data of 128 polymorphic loci representing all the 12 rice chromosomes. The analyses resolved a number of single-locus QTLs and two-locus interactions under both long-day and short day conditions. The interactions involved a large number of loci, most of which were not detectable on a single-locus basis. The results showed that the genetic bases of both stability of sterility and reversibility of fertility are the joint effects of the additive effects of the QTLs and additive-by-additive components of two-locus interactions. The implications of these findings in hybrid rice development are also discussed.

Fine Mapping and Candidate Gene Prediction of a Pleiotropic Quantitative Trait Locus for Yield-Related Trait in Zea mays

The yield of maize grain is a highly complex quantitative trait that is controlled by multiple quantitative trait loci (QTLs) with small effects, and is frequently influenced by multiple genetic and environmental factors. Thus, it is challenging to clone a QTL for grain yield in the maize genome. Previously, we identified a major QTL, qKNPR6, for kernel number per row (KNPR) across multiple environments, and developed two nearly isogenic lines, SL57-6 and Ye478, which differ only in the allelic constitution at the short segment harboring the QTL. Recently, qKNPR6 was re-evaluated in segregating populations derived from SL57-6×Ye478, and was narrowed down to a 2.8 cM interval, which explained 56.3% of the phenotypic variance of KNPR in 201 F2∶3 families. The QTL simultaneously affected ear length, kernel weight and grain yield. Furthermore, a large F2 population with more than 12,800 plants, 191 recombinant chromosomes and 10 overlapping recombinant lines placed qKNPR6 into a 0.91 cM interval corresponding to 198Kb of the B73 reference genome. In this region, six genes with expressed sequence tag (EST) evidence were annotated. The expression pattern and DNA diversity of the six genes were assayed in Ye478 and SL57-6. The possible candidate gene and the pathway involved in inflorescence development were discussed.

KRN4 Controls Quantitative Variation in Maize Kernel Row Number.

Kernel row number (KRN) is an important component of yield during the domestication and improvement of maize and controlled by quantitative trait loci (QTL). Here, we fine-mapped a major KRN QTL, KRN4, which can enhance grain productivity by increasing KRN per ear. We found that a ~3-Kb intergenic region about 60 Kb downstream from the SBP-box gene Unbranched3 (UB3) was responsible for quantitative variation in KRN by regulating the level of UB3 expression. Within the 3-Kb region, the 1.2-Kb Presence-Absence variant was found to be strongly associated with quantitative variation in KRN in diverse maize inbred lines, and our results suggest that this 1.2-Kb transposon-containing insertion is likely responsible for increased KRN. A previously identified A/G SNP (S35, also known as Ser220Asn) in UB3 was also found to be significantly associated with KRN in our association-mapping panel. Although no visible genetic effect of S35 alone could be detected in our linkage mapping population, it was found to genetically interact with the 1.2-Kb PAV to modulate KRN. The KRN4 was under strong selection during maize domestication and the favorable allele for the 1.2-Kb PAV and S35 has been significantly enriched in modern maize improvement process. The favorable haplotype (Hap1) of 1.2-Kb-PAV-S35 was selected during temperate maize improvement, but is still rare in tropical and subtropical maize germplasm. The dissection of the KRN4 locus improves our understanding of the genetic basis of quantitative variation in complex traits in maize.

Comparative transcriptomics uncovers alternative splicing changes and signatures of selection from maize improvement

BackgroundAlternative splicing (AS) is an important regulatory mechanism that greatly contributes to eukaryotic transcriptome diversity. A substantial amount of evidence has demonstrated that AS complexity is relevant to eukaryotic evolution, development, adaptation, and complexity. In this study, six teosinte and ten maize transcriptomes were sequenced to analyze AS changes and signatures of selection in maize domestication and improvement.ResultsIn maize and teosinte, 13,593 highly conserved genes, including 12,030 multiexonic genes, were detected. By identifying AS isoforms from mutliexonic genes, we found that AS types were not significantly different between maize and teosinte. In addition, the two main AS types (intron retention and alternative acceptor) contributed to more than 60% of the AS events in the two species, but the average unique AS events per each alternatively spliced gene in maize (4.12) was higher than that in teosinte (2.26). Moreover, 94 genes generating 98 retained introns with transposable element (TE) sequences were detected in maize, which is far more than 9 retained introns with TEs detected in teosinte. This indicates that TE insertion might be an important mechanism for intron retention in maize. Additionally, the AS levels of 3864 genes were significantly different between maize and teosinte. Of these, 151 AS level-altered genes that are involved in transcriptional regulation and in stress responses are located in regions that have been targets of selection during maize improvement. These genes were inferred to be putatively improved genes.ConclusionsWe suggest that both maize and teosinte share similar AS mechanisms, but more genes have increased AS complexity during domestication from teosinte to maize. Importantly, a subset of AS level-increased genes that encode transcription factors and stress-responsive proteins may have been selected during maize improvement.