QTL analysis for eating quality-related traits in an F2:3 population derived from waxy corn × sweet corn cross

Association Mapping of Seed Coat Color Characteristics for Near-Isogenic Lines of Colored Waxy Maize Using Simple Sequence Repeat Markers

Waxy maize is mainly cultivated in South Korea for the production of food and snacks, and colored maize with increased anthocyanin content is used in the production of functional foods and medicinal products. Association mapping analysis (AMA) is supported as the preferred method for identifying genetic markers associated with complex traits. Our study aimed to identify molecular markers associated with two anthocyanin content and six seed coat color traits in near-isogenic lines (NILs) of colored waxy maize assessed through AMA. We performed AMA for 285 SSR loci and two anthocyanin content and six seed coat color traits in 10 NILs of colored waxy maize. In the analysis of population structure and cluster formation, the two parental lines (HW3, HW9) of "Mibaek 2ho" variety waxy maize and the 10 NILs were clearly divided into two groups, with each group containing one of the two parental inbred lines. In the AMA, 62 SSR markers were associated with two seed anthocyanin content and six seed coat color traits in the 10 NILs. All the anthocyanin content and seed coat color traits were associated with SSR markers, ranging from 2 to 12 SSR markers per characteristic. The 12 SSR markers were together associated with both of the two anthocyanin content (kuromanin and peonidin) traits. Our current results demonstrate the effectiveness of SSR analysis for the examination of genetic diversity, relationships, and population structure and AMA in 10 NILs of colored waxy maize and the two parental lines of the "Mibaek 2ho" variety waxy maize.

Combining genome-wide association study and linkage mapping in the genetic dissection of amylose content in maize (Zea mays L.)

KEY MESSAGE

Integrated linkage and association analysis revealed genetic basis across multiple environments. The genes Zm00001d003102 and Zm00001d015905 were further verified to influence amylose content using gene-based association study. Maize kernel amylose is an important source of human food and industrial raw material. However, the genetic basis underlying maize amylose content is still obscure. Herein, we used an intermated B73 × Mo17 (IBM) Syn10 doubled haploid population composed of 222 lines and a germplasm set including 305 inbred lines to uncover the genetic control for amylose content under four environments. Linkage mapping detected 16 unique QTL, among which four were individually repeatedly identified across multiple environments. Genome-wide association study revealed 17 significant (P = 2.24E-06) single-nucleotide polymorphisms, of which two (SYN19568 and PZE-105090500) were located in the intervals of the mapped QTL (qAC2 and qAC5-3), respectively. According to the two population co-localized loci, 20 genes were confirmed as the candidate genes for amylose content. Gene-based association analysis indicated that the variants in Zm00001d003102 (Beta-16-galactosyltransferase GALT29A) and Zm00001d015905 (Sugar transporter 4a) affected amylose content across multi-environment. Tissue expression analysis showed that the two genes were specifically highly expressed in the ear and stem, respectively, suggesting that they might participate in sugar transport from source to sink organs. Our study provides valuable genetic information for breeding maize varieties with high amylose.

Genetic analysis and QTL mapping for pericarp thickness in maize (Zea mays L.)

Proper pericarp thickness protects the maize kernel against pests and diseases, moreover, thinner pericarp improves the eating quality in fresh corn. In this study, we aimed to investigate the dynamic changes in maize pericarp during kernel development and identified the major quantitative trait loci (QTLs) for maize pericarp thickness. It was observed that maize pericarp thickness first increased and then decreased. During the growth and formation stages, the pericarp thickness gradually increased and reached the maximum, after which it gradually decreased and reached the minimum during maturity. To identify the QTLs for pericarp thickness, a BC4F4 population was constructed using maize inbred lines B73 (recurrent parent with thick pericarp) and Baimaya (donor parent with thin pericarp). In addition, a high-density genetic map was constructed using maize 10 K SNP microarray. A total of 17 QTLs related to pericarp thickness were identified in combination with the phenotypic data. The results revealed that the heritability of the thickness of upper germinal side of pericarp (UG) was 0.63. The major QTL controlling UG was qPT1-1, which was located on chromosome 1 (212,215,145-212,948,882). The heritability of the thickness of upper abgerminal side of pericarp (UA) was 0.70. The major QTL controlling UA was qPT2-1, which was located on chromosome 2 (2,550,197-14,732,993). In addition, a combination of functional annotation, DNA sequencing analysis and quantitative real-time PCR (qPCR) screened two candidate genes, Zm00001d001964 and Zm00001d002283, that could potentially control maize pericarp thickness. This study provides valuable insights into the improvement of maize pericarp thickness during breeding.

Integrated metabolomics and transcriptomics analysis during seed germination of waxy corn under low temperature stress

BACKGROUND

Waxy corn has a short growth cycle and high multiple cropping index. However, after being planted in early spring, late autumn and winter, it is susceptible to low temperature (LT), which reduces the emergence rate and yield. Therefore, it is important to analyze the response mechanism of waxy corn under LT stress.

RESULTS

All phenotype indexes of waxy corn inbred lines N28 were significantly higher than waxy corn inbred lines N67 under LT. With the increase of LT stress time, all physiological indexes showed an upward trend in N28 and N67. Differentially expressed genes (DEGs) 16,017 and 14,435 were identified in N28 and N67 compared with nongerminated control under LT germination, respectively, and differential metabolites 127 and 93 were detected in N28 and N67, respectively. In addition, the expression level of some genes involved in plant hormones and mitogen activated protein kinase (MAPK) signaling pathways was significantly up-regulated in N28. Compared with N67, flavonoid metabolites were also significantly enriched in N28 under LT germination.

CONCLUSION

Under LT stress, the inbred lines N28 was significantly higher than the inbred lines N67 in the phenotypic and physiological indices of cold resistance. Compared with N67, the expression levels of some genes involved in the plant hormones and MAPK pathways were significantly up-regulated in N28, and flavonoid metabolites were also significantly enriched in N28 under LT stress. These genes and metabolites may help N28 to improve cold resistance and may be as potential target genes for cold resistance breeding in waxy corn.

Integrative analysis of transcriptome and miRNAome reveals molecular mechanisms regulating pericarp thickness in sweet corn during kernel development

Pericarp thickness affects the edible quality of sweet corn (Zea mays L. saccharata Sturt.). Therefore, breeding varieties with a thin pericarp is important for the quality breeding of sweet corn. However, the molecular mechanisms underlying the pericarp development remain largely unclear. We performed an integrative analysis of mRNA and miRNA sequencing to elucidate the genetic mechanism regulating pericarp thickness during kernel development (at 15 days, 19 days, and 23 days after pollination) of two sweet corn inbred lines with different pericarp thicknesses (M03, with a thinner pericarp and M08, with a thicker pericarp). A total of 2,443 and 1,409 differentially expressed genes (DEGs) were identified in M03 and M08, respectively. Our results indicate that phytohormone-mediated programmed cell death (PCD) may play a critical role in determining pericarp thickness in sweet corn. Auxin (AUX), gibberellin (GA), and brassinosteroid (BR) signal transduction may indirectly mediate PCD to regulate pericarp thickness in M03 (the thin pericarp variety). In contrast, abscisic acid (ABA), cytokinin (CK), and ethylene (ETH) signaling may be the key regulators of pericarp PCD in M08 (the thick pericarp variety). Furthermore, 110 differentially expressed microRNAs (DEMIs) and 478 differentially expressed target genes were identified. miRNA164-, miRNA167-, and miRNA156-mediated miRNA-mRNA pairs may participate in regulating pericarp thickness. The expression results of DEGs were validated by quantitative real-time PCR. These findings provide insights into the molecular mechanisms regulating pericarp thickness and propose the objective of breeding sweet corn varieties with a thin pericarp.

Mapping of QTL for agronomic traits using high-density SNPs with an RIL population in maize

BACKGROUND

Genome wide association studies (GWAS) have been widely used to identify QTLs underlying quantitative traits in humans and animals, and they have also become a popular method of mapping QTLs in many crops, including maize. Advances in high-throughput genotyping technologies enable construction of high-density linkage maps using SNP markers.

OBJECTIVES

High-density genetic mapping must precede to find molecular markers associated with a particular trait. The objectives of this study were to (1) construct a high-density linkage map using SNP markers and (2) detect the QTLs for grain yield and quality related traits of the Mo17/KW7 RIL population.

METHODS

In this study, two parental lines, Mo17 (normal maize inbred line) and KW7 (waxy inbred line) and 80 F_7:8 lines in the Mo17/KW7 RIL population were genotyped using the MaizeSNP50 BeadChip, an Illumina BeadChip array of 56,110 maize SNPs. Marker integration and detection of QTLs was performed using the inclusive composite interval mapping (ICIM) method within the QTL IciMapping software.

RESULTS

This study was genotyped using the Illumina MaizeSNP50 BeadChip for maize Mo17/KW7 recombinant inbred line (RIL) population. The 2904 SNP markers were distributed along all 10 maize chromosomes. The total length of the linkage map was 3553.7 cm, with an average interval of 1.22 cm between SNPs. A total of 18 QTLs controlling eight traits were detected in the Mo17/KW7 RIL population. Three QTLs for plant height (PH) were detected on chromosomes 4 and 8 and showed from 16.01% (qPH8) to 19.85% (qPH4a) of phenotypic variance. Five QTLs related to ear height (EH) were identified on chromosomes 3, 4, and 6 and accounted for 3.79% (qEH6) to 27.57% (qEH4b) of phenotypic variance. Five QTLs related to water content (WC) on chromosomes 1, 4, 8, and 9 accounted for 9.55% (qWC8b) to 23.30% (qWC4) of phenotypic variance. One QTL (qAC9) relating to amylose content (AC) on chromosome 9 showed 82.10% of phenotypic variance.

CONCLUSIONS

The high-density linkage map and putative QTLs of the maize RIL population detected in this study can be effectively utilized in waxy and normal maize breeding programs to facilitate the selection process through marker-assisted selection (MAS) breeding programs.

QTL Analysis of Five Morpho-Physiological Traits in Bread Wheat Using Two Mapping Populations Derived from Common Parents

Traits such as plant height (PH), juvenile growth habit (GH), heading date (HD), and tiller number are important for both increasing yield potential and improving crop adaptation to climate change. In the present study, these traits were investigated by using the same bi-parental population at early (F₂ and F₂-derived F₃ families) and late (F₆ and F₇, recombinant inbred lines, RILs) generations to detect quantitative trait loci (QTLs) and search for candidate genes. A total of 176 and 178 lines were genotyped by the wheat Illumina 25K Infinium SNP array. The two genetic maps spanned 2486.97 cM and 3732.84 cM in length, for the F₂ and RILs, respectively. QTLs explaining the highest phenotypic variation were found on chromosomes 2B, 2D, 5A, and 7D for HD and GH, whereas those for PH were found on chromosomes 4B and 4D. Several QTL detected in the early generations (i.e., PH and tiller number) were not detected in the late generations as they were due to dominance effects. Some of the identified QTLs co-mapped to well-known adaptive genes (i.e., Ppd-1, Vrn-1, and Rht-1). Other putative candidate genes were identified for each trait, of which PINE1 and PIF4 may be considered new for GH and TTN in wheat. The use of a large F₂ mapping population combined with NGS-based genotyping techniques could improve map resolution and allow closer QTL tagging.

QTL Mapping and Identification of Candidate Genes for Heat Tolerance at the Flowering Stage in Rice

High-temperature stress can cause serious abiotic damage that limits the yield and quality of rice. Heat tolerance (HT) during the flowering stage of rice is a key trait that can guarantee a high and stable yield under heat stress. HT is a complex trait that is regulated by multiple quantitative trait loci (QTLs); however, few underlying genes have been fine mapped and cloned. In this study, the F_2:3 population derived from a cross between Huanghuazhan (HHZ), a heat-tolerant cultivar, and 9311, a heat-sensitive variety, was used to map HT QTLs during the flowering stage in rice. A new major QTL, qHTT8, controlling HT was identified on chromosome 8 using the bulked-segregant analysis (BSA)-seq method. The QTL qHTT8 was mapped into the 3,555,000–4,520,000 bp, which had a size of 0.965 Mb. The candidate region of qHTT8 on chromosome 8 contained 65 predicted genes, and 10 putative predicted genes were found to be associated with abiotic stress tolerance. Furthermore, qRT-PCR was performed to analyze the differential expression of these 10 genes between HHZ and 9311 under high temperature conditions. LOC_Os08g07010 and LOC_Os08g07440 were highly induced in HHZ compared with 9311 under heat stress. Orthologous genes of LOC_Os08g07010 and LOC_Os08g07440 in plants played a role in abiotic stress, suggesting that they may be the candidate genes of qHTT8. Generally, the results of this study will prove useful for future efforts to clone qHTT8 and breed heat-tolerant varieties of rice using marker-assisted selection.

Genetic characterization and association mapping in near-isogenic lines of waxy maize using seed characteristics and SSR markers

BACKGROUND

Association mapping has been advocated as the method of choice for identifying loci involved in the inheritance of complex traits in crop species. This method involves identifying markers with significant differences in allele frequency between individuals with a phenotype of interest and a set of unrelated control individuals.

OBJECTIVE

The purpose of our study is not only to investigate the genetic diversity and relationships of the basic molecular markers of near-isogenic lines (NILs) of waxy maize, but it is also to identify molecular markers related to interesting seed characteristics including 4 seed quantity traits and 4 seed phenotypic traits using association analysis with population structure.

METHODS

We performed association mapping of 200 SSR markers and 8 seed characteristics among 10 NILs of waxy maize and two parental lines (HW3, HW9) (recurrent parent) of "Mibaek 2" variety.

RESULTS

In population structure and cluster analysis, the 10 NILs and two parental lines were divided into two groups. Seven inbred lines, including HW3, were assigned to Group I. Group II contained 5 inbred lines, including HW9. In addition, we found that 32 SSR markers associate with 8 seed characteristics in 10 NILs. In particular, five SSR markers (umc1986, umc1747, umc2275, phi078, umc1366) were together associated with more than one seed characteristics such as EL, 100 KW, SCC, R, L*, and V.

CONCLUSION

This study demonstrated the utility of SSR analysis for studying GD, population structure, and association mapping in 10 NILs and two parental lines (HW3, HW9) of "Mibaek 2" variety.

Genetic differentiation of Mutator insertion polymorphisms and association with agronomic traits in waxy and common maize

BACKGROUND

As waxy maize is considered a key economic crop in Korea, an understanding of its genetic variation and differentiation is fundamental for the selective plant breeding. The maize genome is primarily composed of transposable elements, for which large and stable insertions generate variations that reflect selection during evolution.

OBJECTIVES

This study was to elucidate the genetic diversity based on the contribution of TEs and to investigate the effect of Mu transposition on the genetic divergence of waxy and common maize. We also performed an association analysis on these inbred lines to determine the Mu insertions associated with agronomic traits.

METHODS

In this study, we utilized a Mutator-based transposon display method to study the genetic diversity and population structure of 40 waxy and 40 common inbred lines of maize in the Gangwon Agricultural Research and Extension Services collection at the Maize Research Institute.

RESULTS

We detected polymorphisms in 86.33% of 278 Mutator (Mu) anchored loci, reflecting the activity of the Mu element and its contribution to genetic variation. Common maize showed a substantial amount of genetic diversity, which was greater than that observed in waxy maize. Principal-coordinate and neighbor-joining cluster analyzes consistently supported the presence of two genetically distinct groups. However, the distribution of genetic variation within the populations was much higher than the genetic differentiation among the populations. To explore the contribution of the Mu element to phenotypic variation, we analyzed the associations with ten important agronomical traits. On the basis of the combined results from two models (QGLM and Q + KLM), we found significant associations between seven Mu loci and four different traits.

CONCLUSIONS

These results will assist waxy maize breeders in choosing parental lines and be useful for marker-assisted selection.

Construction of genetic linkage map and identification of QTLs related to agronomic traits in maize using DNA transposon-based markers

Transposable elements (TEs), are a rich source for molecular marker development as they constitute a significant fraction of the eukaryotic genome and impact the overall genome structure. Here, we utilize Mutator-based transposon display (Mu-TD), and CACTA-derived sequence-characterized amplified regions (SCAR) anchored by simple sequence repeats and single nucleotide polymorphisms to locate quantitative trait loci (QTLs) linked to agriculturally important traits on a genetic map. Specifically, we studied recombinant inbred line populations derived from a cross between dent corn and waxy corn. The resulting linkage map included 259 Mu-anchored fragments, 34 SCARs, and 614 SSR markers distributed throughout the ten maize chromosomes. Linkage analysis revealed three SNP loci associated with kernel starch synthesis genes (sh2, su1, wx1) linked to either Mu-TD loci or SSR markers, which may be useful for maize breeding programs. In addition, we used QTL analysis to determine the chromosomal location of traits related to grain yield and kernel quality. We identified 24 QTLs associated with nine traits located on nine out of ten maize chromosomes. Among these, 13 QTLs involved Mu loci and two involved SCARs. This study demonstrates the potential use of DNA transposon-based markers to construct linkage maps and identify QTLs linked to agronomic traits.

Genetic diversity of sweet corn inbreds using agro-morphological traits and microsatellite markers

Assessment of genetic diversity is a pre-requisite to broaden the genetic background of cultivated base of sweet corn, an endosperm mutant of field corn that alters starch biosynthesis pathway in endosperm. In the current investigation, genetic divergence among 39 inbred lines was assessed on the basis of 14 agro-morphological traits, two quality parameters and 63 microsatellite markers, selected on the basis of their association with QTLs affecting kernel quality. The cluster analysis based on unweighted pair-group method using arithmetic averages for agro-morphological and quality traits grouped the 39 inbreds into three clusters with 5, 14 and 20 genotypes, respectively. The unweighted neighbor-joining method for microsatellite markers also categorized the inbred lines into three major clusters grouping 10, 9 and 20 genotypes in cluster I, II and III, respectively. The two cluster distribution patterns showed approximately 36 percent similarity. The assay of 30 microsatellite repeats identified 82 alleles with allele size ranging from 80 to 400 bp. The major allele frequency and PIC value of the markers ranged from 0.42 to 0.79 and 0.27 to 0.63, respectively, which suggested the presence of high amount of polymorphism among the inbreds. The average heterozygosity was recorded to be 0.19 which signifies proper maintenance of inbred population. Principle co-ordinate analysis also depicted diverse nature of inbred lines and agreed well with the previously determined clustering pattern. This study has identified several inbreds, having good yield and high sugar content which will not only enhance the genetic background of sweet corn germplasm but will also lead to development of high-yielding hybrids with improved quality.