Combined bulked segregant sequencing and traditional linkage analysis for identification of candidate gene for purple leaf sheath in maize

High-resolution mapping reveals a Ht3-like locus against northern corn leaf blight

Northern corn leaf blight (NCLB), caused by the fungal pathogen Exserohilum turcicum, poses a grave threat to maize production worldwide. The resistance gene in A619Ht3, discovered decades ago, is an important genetic resource for NCLB control. By using a pair of near-isogenic lines (NILs) A619Ht3 and A619, together with the resistant and susceptible bulks derived from the cross of A619Ht3 and L3162 lines, we initially detected a Ht3-like (Ht3L) locus in bin 8.06 that was closely associated with NCLB resistance. We then performed five rounds of fine-mapping, which ultimately delimited the Ht3L locus to a 577-kb interval flanked by SNP markers KA002081 and KA002084. Plants homozygous for the Ht3L/Ht3L genotype exhibited an average reduction in diseased leaf area (DLA) by 16.5% compared to plants lacking Ht3L locus. The Ht3L locus showed extensive variation in genomic architecture among different maize lines and did not appear to contain any genes encoding canonical cell wall-associated kinases against NCLB. Moreover, the Ht3L locus was located ∼2.7 Mb away from the known Htn1 locus. We speculate that the Ht3L locus may contain a bona fide Ht3 gene or a novel NCLB resistance gene closely linked to Ht3. In practice, the Ht3L locus is a valuable resource for improving maize resistance to NCLB.

A newly characterized allele of ZmR1 increases anthocyanin content in whole maize plant and the regulation mechanism of different ZmR1 alleles

The novel ZmR1^CQ01 allele for maize anthocyanin synthesis was identified, and the biological function and regulatory molecular mechanisms of three ZmR1 alleles were unveiled. Anthocyanins in maize are valuable to human health. The R1 gene family is one of the important regulatory genes for the tissue-specific distribution of anthocyanins. R1 gene allelic variations are abundant and its biological function and regulatory molecular mechanisms are not fully understood. By exploiting genetic mapping and transgenic verification, we found that anthocyanin pigmentation in maize leaf midrib was controlled by ZmR1 on chromosome 10. Allelism test of maize zmr1 EMS mutants confirmed that anthocyanin pigmentation in leaf sheath was also controlled by ZmR1. ZmR1^CQ01 was a novel ZmR1 allelic variation obtained from purple maize. Its overexpression caused the whole maize plant to turn purple. ZmR1^B73 allele confers anthocyanin accumulation in near ground leaf sheath rather than in leaf midribs. The mRNA expression level of ZmR1^B73 was low in leaf midribs, resulting in no anthocyanin accumulation. ZmR1^B73 overexpression promoted anthocyanin accumulation in leaf midribs. Loss of exon 5 resulted in ZmR1^ZN3 allele function destruction and no anthocyanin accumulation in leaf midrib and leaf sheath. DNA affinity purification sequencing revealed 1010 genes targeted by ZmR1^CQ01, including the bz2 in anthocyanin synthesis pathway. RNA-seq analysis showed 55 genes targeted by ZmR1^CQ01 changed the expression level significantly, and the expression of genes encoding key enzymes in flavonoid and phenylpropanoid biosynthesis pathways were significantly up-regulated. ZmR1 functional molecular marker was developed. These results revealed the effects of transcriptional regulation and sequence variation on ZmR1 function and identified the genes targeted by ZmR1^CQ01 at the genome-wide level.

Dissecting the Genetic Structure of Maize Leaf Sheaths at Seedling Stage by Image-Based High-Throughput Phenotypic Acquisition and Characterization

The rapid development of high-throughput phenotypic detection techniques makes it possible to obtain a large number of crop phenotypic information quickly, efficiently, and accurately. Among them, image-based phenotypic acquisition method has been widely used in crop phenotypic identification and characteristic research due to its characteristics of automation, non-invasive, non-destructive and high throughput. In this study, we proposed a method to define and analyze the traits related to leaf sheaths including morphology-related, color-related and biomass-related traits at V6 stage. Next, we analyzed the phenotypic variation of leaf sheaths of 418 maize inbred lines based on 87 leaf sheath-related phenotypic traits. In order to further analyze the mechanism of leaf sheath phenotype formation, 25 key traits (2 biomass-related, 19 morphology-related and 4 color-related traits) with heritability greater than 0.3 were analyzed by genome-wide association studies (GWAS). And 1816 candidate genes of 17 whole plant leaf sheath traits and 1,297 candidate genes of 8 sixth leaf sheath traits were obtained, respectively. Among them, 46 genes with clear functional descriptions were annotated by single nucleotide polymorphism (SNPs) that both Top1 and multi-method validated. Functional enrichment analysis results showed that candidate genes of leaf sheath traits were enriched into multiple pathways related to cellular component assembly and organization, cell proliferation and epidermal cell differentiation, and response to hunger, nutrition and extracellular stimulation. The results presented here are helpful to further understand phenotypic traits of maize leaf sheath and provide a reference for revealing the genetic mechanism of maize leaf sheath phenotype formation.

A combinatorial strategy to identify various types of QTLs for quantitative traits using extreme phenotype individuals in an F2 population

Theoretical and applied studies demonstrate the difficulty of detecting extremely over-dominant and small-effect genes for quantitative traits via bulked segregant analysis (BSA) in an F2 population. To address this issue, we proposed an integrated strategy for mapping various types of quantitative trait loci (QTLs) for quantitative traits via a combination of BSA and whole-genome sequencing. In this strategy, the numbers of read counts of marker alleles in two extreme pools were used to predict the numbers of read counts of marker genotypes. These observed and predicted numbers were used to construct a new statistic, Gw, for detecting quantitative trait genes (QTGs), and the method was named dQTG-seq1. This method was significantly better than existing BSA methods. If the goal was to identify extremely over-dominant and small-effect genes, another reserved DNA/RNA sample from each extreme phenotype F2 plant was sequenced, and the observed numbers of marker alleles and genotypes were used to calculate Gw to detect QTGs; this method was named dQTG-seq2. In simulated and real rice dataset analyses, dQTG-seq2 could identify many more extremely over-dominant and small-effect genes than BSA and QTL mapping methods. dQTG-seq2 may be extended to other heterogeneous mapping populations. The significance threshold of Gw in this study was determined by permutation experiments. In addition, a handbook for the R software dQTG.seq, which is available at https://cran.r-project.org/web/packages/dQTG.seq/index.html, has been provided in the supplemental materials for the users' convenience. This study provides a new strategy for identifying all types of QTLs for quantitative traits in an F2 population.

Fine mapping and gene cloning in the post-NGS era: advances and prospects

Improvement in traits of agronomic importance is the top breeding priority of crop improvement programs. Majority of these agronomic traits show complex quantitative inheritance. Identification of quantitative trait loci (QTLs) followed by fine mapping QTLs and cloning of candidate genes/QTLs is central to trait analysis. Advances in genomic technologies revolutionized our understanding of genetics of complex traits, and genomic regions associated with traits were employed in marker-assisted breeding or cloning of QTLs/genes. Next-generation sequencing (NGS) technologies have enabled genome-wide methodologies for the development of ultra-high-density genetic linkage maps in different crops, thus allowing placement of candidate loci within few kbs in genomes. In this review, we compare the marker systems used for fine mapping and QTL cloning in the pre- and post-NGS era. We then discuss how different NGS platforms in combination with advanced experimental designs have improved trait analysis and fine mapping. We opine that efficient genotyping/sequencing assays may circumvent the need for cumbersome procedures that were earlier used for fine mapping. A deeper understanding of the trait architectures of agricultural significance will be crucial to accelerate crop improvement.