Linkage mapping combined with association analysis reveals QTL and candidate genes for three husk traits in maize

A combination of QTL mapping and genome-wide association study revealed the key gene for husk number in maize

KEY MESSAGE

Two key genes Zm00001d021232 and Zm00001d048138 were identified by QTL mapping and GWAS. Additionally, they were verified to be significantly associated with maize husk number (HN) using gene-based association study. As a by-product of maize production, maize husk is an important industrial raw material. Husk layer number (HN) is an important trait that affects the yield of maize husk. However, the genetic mechanism underlying HN remains unclear. Herein, a total of 13 quantitative trait loci (QTL) controlling HN were identified in an IBM Syn 10 DH population across different locations. Among these, three QTL were individually repeatedly detected in at least two environments. Meanwhile, 26 unique single nucleotide polymorphisms (SNPs) were detected to be significantly (p < 2.15 × 10-6) associated with HN in an association pool. Of these SNPs, three were simultaneously detected across multiple environments or environments and best linear unbiased prediction (BLUP). We focused on these environment-stable and population-common genetic loci for excavating the candidate genes responsible for maize HN. Finally, 173 initial candidate genes were identified, of which 22 were involved in both multicellular organism development and single-multicellular organism process and thus confirmed as the candidate genes for HN. Gene-based association analyses revealed that the variants in four genes were significantly (p < 0.01/N) correlated with HN, of which Zm00001d021232 and Zm00001d048138 were highly expressed in husks and early developing ears among different maize tissues. Our study contributes to the understanding of genetic and molecular mechanisms of maize husk yield and industrial development in the future.

The RHW1-ZCN4 regulatory pathway confers natural variation of husk leaf width in maize

Maize husk leaf - the outer leafy layers covering the ear - modulates kernel yield and quality. Despite its importance, however, the genetic controls underlying husk leaf development remain elusive. Our previous genome-wide association study identified a single nucleotide polymorphism located in the gene RHW1 (Regulator of Husk leaf Width) that is significantly associated with husk leaf-width diversity in maize. Here, we further demonstrate that a polymorphic 18-bp InDel (insertion/deletion) variant in the 3' untranslated region of RHW1 alters its protein abundance and accounts for husk leaf width variation. RHW1 encodes a putative MYB-like transcriptional repressor. Disruption of RHW1 altered cell proliferation and resulted in a narrower husk leaf, whereas RHW1 overexpression yielded a wider husk leaf. RHW1 positively regulated the expression of ZCN4, a well-known TFL1-like protein involved in maize ear development. Dysfunction of ZCN4 reduced husk leaf width even in the context of RHW1 overexpression. The InDel variant in RHW1 is subject to selection and is associated with maize husk leaf adaption from tropical to temperate regions. Overall, our results identify that RHW1-ZCN4 regulates a pathway conferring husk leaf width variation at a very early stage of husk leaf development in maize.

Combined linkage mapping and association analysis uncovers candidate genes for 25 leaf-related traits across three environments in maize

Combined linkage and association analysis revealed five co-localized genetic loci across multiple environments. The key gene Zm00001d026491 was further verified to influence leaf length by candidate gene association analysis. Leaf morphology and number determine the canopy structure and thus affect crop yield. Herein, the genetic basis and key genes for 25 leaf-related traits, including leaf lengths (LL), leaf widths (LW), and leaf areas (LA) of eight continuous leaves under the tassel, and the number of leaves above the primary ear (LAE), were dissected by using an association panel and a biparental population. Using an intermated B73 × Mo17 (IBM) Syn10 doubled haploid (DH) population, 290 quantitative trait loci (QTL) controlling these traits were detected across different locations, among which 115 QTL were individually repeatedly identified in at least two environments. Using the association panel, 165 unique significant single-nucleotide polymorphisms (SNPs) were associated with target traits (P < 2.15E-06), of which 35 were separately detected across multiple environments. In total, 42 pleiotropic QTL/SNPs (pQTL/SNPs) were responsible for at least two of the LL, LW, LA, and LAE traits across multiple environments. Combining the QTL mapping and association study, five unique SNPs were located within the confidence intervals of seven QTL, and 77 genes were identified based on the linkage disequilibrium regions of co-localized SNP loci. Gene-based association studies verified that the intragenic variants in the candidate gene Zm00001d026491 influenced LL of the third leaf counted from the top node. These findings will provide vital information to understanding the genetic basis of leaf-related traits and help to cultivate maize varieties with ideal plant architecture.

An Integration of Linkage Mapping and GWAS Reveals the Key Genes for Ear Shank Length in Maize

Ear shank length (ESL) has significant effects on grain yield and kernel dehydration rate in maize. Herein, linkage mapping and genome-wide association study were combined to reveal the genetic architecture of maize ESL. Sixteen quantitative trait loci (QTL) were identified in the segregation population, among which five were repeatedly detected across multiple environments. Meanwhile, 23 single nucleotide polymorphisms were associated with the ESL in the association panel, of which four were located in the QTL identified by linkage mapping and were designated as the population-common loci. A total of 42 genes residing in the linkage disequilibrium regions of these common variants and 12 of them were responsive to ear shank elongation. Of the 12 genes, five encode leucine-rich repeat receptor-like protein kinases, proline-rich proteins, and cyclin11, respectively, which were previously shown to regulate cell division, expansion, and elongation. Gene-based association analyses revealed that the variant located in Cyclin11 promoter affected the ESL among different lines. Cyclin11 showed the highest expression in the ear shank 15 days after silking among diverse tissues of maize, suggesting its role in modulating ESL. Our study contributes to the understanding of the genetic mechanism underlying maize ESL and genetic modification of maize dehydration rate and kernel yield.

Genome-wide association study reveals the genetic basis of brace root angle and diameter in maize

Brace roots are the main organ to support the above-ground part of maize plant. It involves in plant growth and development by water absorption and lodging resistance. The bracing root angle (BRA) and diameter (BRD) are important components of brace root traits. Illuminating the genetic basis of BRA and BRD will contribute the improvement for mechanized harvest and increasing production. A GWAS of BRA and BRD was conducted using an associated panel composed of 508 inbred lines of maize. The broad-sense heritability of BRA and BRD was estimated to be respectively 71% ± 0.19 and 52% ± 0.14. The phenotypic variation of BRA and BRD in the non-stiff stalk subgroup (NSS) and the stiff stalk subgroup (SS) subgroups are significantly higher than that in the tropical/subtropical subgroup (TST) subgroups. In addition, BRA and BRD are significantly positive with plant height (PH), ear length (EL), and kernel number per row (KNPR). GWAS revealed 27 candidate genes within the threshold of p < 1.84 × 10⁻⁶ by both MLM and BLINK models. Among them, three genes, GRMZM2G174736, GRMZM2G445169 and GRMZM2G479243 were involved in cell wall function, and GRMZM2G038073 encoded the NAC transcription factor family proteins. These results provide theoretical support for clarifying the genetic basis of brace roots traits.

Selection Signatures in Chinese Sorghum Reveals Its Unique Liquor-Making Properties

Chinese sorghum (S. bicolor) has been a historically critical ingredient for brewing famous distilled liquors ever since Yuan Dynasty (749 ∼ 652 years BP). Incomplete understanding of the population genetics and domestication history limits its broad applications, especially that the lack of genetics knowledge underlying liquor-brewing properties makes it difficult to establish scientific standards for sorghum breeding. To unravel the domestic history of Chinese sorghum, we re-sequenced 244 Chinese sorghum lines selected from 16 provinces. We found that Chinese sorghums formed three distinct genetic sub-structures, referred as the Northern, the Southern, and the Chishui groups, following an obviously geographic pattern. These sorghum accessions were further characterized in liquor brewing traits and identified selection footprints associated with liquor brewing efficiency. An importantly selective sweep region identified includes several homologous genes involving in grain size, pericarp thickness, and architecture of inflorescence. Our result also demonstrated that pericarp strength rather than grain size determines the ability of the grains to resist repeated cooking during brewing process. New insight into the traits beneficial to the liquor-brewing process provides both a better understanding on Chinese sorghum domestication and a guidance on breeding sorghum as a multiple use crop in China.

Genetic analysis of three maize husk traits by QTL mapping in a maize-teosinte population

BACKGROUND

The maize husk consists of numerous leafy layers and plays vital roles in protecting the ear from pathogen infection and dehydration. Teosinte, the wild ancestor of maize, has about three layers of small husk outer covering the ear. Although several quantitative trait loci (QTL) underlying husk morphology variation have been reported, the genetic basis of husk traits between teosinte and maize remains unclear.

RESULTS

A linkage population including 191 BC₂F₈ inbred lines generated from the maize line Mo17 and the teosinte line X26-4 was used to identify QTL associated with three husk traits: i.e., husk length (HL), husk width (HW) and the number of husk layers (HN). The best linear unbiased predictor (BLUP) depicted wide phenotypic variation and high heritability of all three traits. The HL exhibited greater correlation with HW than HN. A total of 4 QTLs were identified including 1, 1, 2, which are associated with HL, HW and HN, respectively. The proportion of phenotypic variation explained by these QTLs was 9.6, 8.9 and 8.1% for HL, HN and HW, respectively.

CONCLUSIONS

The QTLs identified in this study will pave a path to explore candidate genes regulating husk growth and development, and benefit the molecular breeding program based on molecular marker-assisted selection to cultivate maize varieties with an ideal husk morphology.

Genetic analysis of maize shank length by QTL mapping in three recombinant inbred line populations

In maize, the shank is a unique tissue linking the stem to the ear. Shank length (SL) mainly affects the transport of photosynthetic products to the ear and the dehydration of kernels via regulated husk morphology. The limited studies on SL revealed it is a highly heritable quantitative trait controlled by significant additive and additive-dominance effects. However, the genetic basis of SL remains unclear. In this study, we analyzed three maize recombinant inbred line (RIL) populations to elucidate the molecular mechanism underlying the SL. The data indicated the SL varied among the three RIL populations and was highly heritable. Additionally, the SL was positively correlated with the husk length (HL), husk number (HN), ear length (EL), and ear weight (EW) in the BY815/K22 (BYK) and CI7/K22 (CIK) RIL populations, but was negatively correlated with the husk width (HW) in the BYK RIL population. Moreover, 10 quantitative trait loci (QTL) for SL were identified in the three RIL populations, five of which were large-effect QTL. The percentage of the total phenotypic variation explained by the QTL for SL was 13.67 %, 20.45 %, and 30.81 % in the BY815/DE3 (BYD), BYK, and CIK RIL populations, respectively. Further analyses uncovered some genetic overlap between SL and EL, SL and ear row number (ERN), SL and cob weight (CW), and SL and HN. Unlike the large-effect QTL qSL BYK-2-2, which spanned the centromere, the other four large-effect QTL were delimited to a single peak bin via bin map. Furthermore, 2, 5, 6, and 12 genes associated with SL were identified for qSL BYK-2-1, qSL CIK-2-1, qSL CIK-9-1, and qSL CIK-9-2, respectively. Five of the candidate genes for SL may contribute to the hormone metabolism and sphingolipid biosynthesis regulating cell elongation, division, differentiation, and expansion. These results may be relevant for future studies on the genetic basis of SL and for the molecular breeding of maize based on marker-assisted selection to develop new varieties with an ideal SL.

Genetic Analysis of Walnut (Juglans regia L.) Pellicle Pigment Variation Through a Novel, High-Throughput Phenotyping Platform

Walnut pellicle color is a key quality attribute that drives consumer preference and walnut sales. For the first time a high-throughput, computer vision-based phenotyping platform using a custom algorithm to quantitatively score each walnut pellicle in L* a* b* color space was deployed at large-scale. This was compared to traditional qualitative scoring by eye and was used to dissect the genetics of pellicle pigmentation. Progeny from both a bi-parental population of 168 trees (‘Chandler’ × ‘Idaho’) and a genome-wide association (GWAS) with 528 trees of the UC Davis Walnut Improvement Program were analyzed. Color phenotypes were found to have overlapping regions in the ‘Chandler’ genetic map on Chr01 suggesting complex genetic control. In the GWAS population, multiple, small effect QTL across Chr01, Chr07, Chr08, Chr09, Chr10, Chr12 and Chr13 were discovered. Marker trait associations were co-localized with QTL mapping on Chr01, Chr10, Chr14, and Chr16. Putative candidate genes controlling walnut pellicle pigmentation were postulated.

Assessment of the Potential for Genomic Selection To Improve Husk Traits in Maize

Husk has multiple functions such as protecting ears from diseases, infection, and dehydration during development. Additionally, husks comprised of fewer, shorter, thinner, and narrower layers allow faster moisture evaporation of kernels prior to harvest. Intensive studies have been conducted to identify appropriate husk architecture by understanding the genetic basis of related traits, including husk length, husk layer number, husk thickness, and husk width. However, marker-assisted selection is inefficient because the identified quantitative trait loci and associated genetic loci could only explain a small proportion of total phenotypic variation. Genomic selection (GS) has been used successfully on many species including maize on other traits. Thus, the potential of using GS for husk traits to directly identify superior inbred lines, without knowing the specific underlying genetic loci, is well worth exploring. In this study, we compared four GS models on a maize association population with 498 inbred lines belonging to four subpopulations, including 27 lines in stiff stalk, 67 lines in non-stiff stalk, 193 lines in tropical-subtropical, and 211 lines in mixture subpopulations. Genomic Best Linear Unbiased Prediction with principal components as cofactor, performed the best and was selected to examine the impact of interaction between sampling proportions and subpopulations. We found that predictions on inbred lines in a subpopulation were benefited from excluding individuals from other subpopulations for training if the training population within the subpopulation was large enough. Husk thickness exhibited the highest prediction accuracy among all husk traits. These results gave strategic insight to improve husk architecture.

A combination of linkage mapping and GWAS brings new elements on the genetic basis of yield-related traits in maize across multiple environments

Using GWAS and QTL mapping identified 100 QTL and 138 SNPs, which control yield-related traits in maize. The candidate gene GRMZM2G098557 was further validated to regulate ear row number by using a segregation population. Understanding the genetic basis of yield-related traits contributes to the improvement of grain yield in maize. This study used an inter-mated B73 × Mo17 (IBM) Syn10 doubled-haploid (DH) population and an association panel to identify the genetic loci responsible for nine yield-related traits in maize. Using quantitative trait loci (QTL) mapping, 100 QTL influencing these traits were detected across different environments in the IBM Syn10 DH population, with 25 co-detected in multiple environments. Using a genome-wide association study (GWAS), 138 single-nucleotide polymorphisms (SNPs) were identified as correlated with these traits (P < 2.04E-06) in the association panel. Twenty-one pleiotropic QTL/SNPs were identified to control different traits in both populations. A combination of QTL mapping and GWAS uncovered eight significant SNPs (PZE-101097575, PZE-103169263, ZM011204-0763, PZE-104044017, PZE-104123110, SYN8062, PZE-108060911, and PZE-102043341) that were co-located within seven QTL confidence intervals. According to the eight co-localized SNPs by the two populations, 52 candidate genes were identified, among which the ear row number (ERN)-associated SNP SYN8062 was closely linked to SBP-transcription factor 7 (GRMZM2G098557). Several SBP-transcription factors were previously demonstrated to modulate maize ERN. We then validated the phenotypic effects of SYN8062 in the IBM Syn10 DH population, indicating that the ERN of the lines with the A-allele in SYN8062 was significantly (P < 0.05) larger than that of the lines with the G-allele in SYN8062 in each environment. These findings provide valuable information for understanding the genetic mechanisms of maize grain yield formation and for improving molecular marker-assisted selection for the high-yield breeding of maize.

Genome-Wide Association Study Dissects the Genetic Architecture of Maize Husk Tightness

The husk is a leafy outer tissue that encloses a maize ear. Previously, we identified the optimum husk structure by measuring the husk length, husk layer number, husk thickness and husk width. Husk tightness (HTI) is a combined trait based on the above four husk measurements. Unveiling the genetic basis of HTI will aid in guiding the genetic improvement of maize for mechanical harvesting and for protecting the ear from pest damage and pathogen infection. Here, we used a maize associate population of 508 inbred lines with tropical, subtropical and temperate backgrounds to analyze the genetic architecture of HTI. Evaluating the phenotypic diversity in three different environments showed that HTI exhibited broad natural variations and a moderate heritability level of 0.41. A diversity analysis indicated that the inbred lines having a temperate background were more loosely related than those having a tropical or subtropical background. HTI showed significant negative correlations with husk thickness and width, which indicates that thicker and wider husks wrapped the ear tighter than thinner and slimmer husks. Combining husk traits with ∼1.25 million single nucleotide polymorphisms in a genome-wide association study revealed 27 variants that were significantly associated with HTI above the threshold of P < 7.26 × 10^-6. We found 27 candidate genes for HTI that may participate in (1) husk senescence involving lipid peroxidation (GRMZM2G017616) and programmed cell death (GRMZM2G168898 and GRMZM2G035045); (2) husk morphogenesis involving cell division (GRMZM5G869246) and cell wall architecture (GRMZM2G319798); and (3) cell signal transduction involving protein phosphorylation (GRMZM2G149277 and GRMZM2G004207) and the ABSISIC ACID INSENSITIVE3/VIVIPAROUS1 transcription factor (GRMZM2G088427). These results provide useful information for understanding the genetic basis of husk development. Further studies of identified candidate genes will help elucidate the molecular pathways that regulate HTI in maize.

Denser Markers and Advanced Statistical Method Identified More Genetic Loci Associated with Husk Traits in Maize

The husk—the leaf-like outer covering of maize ear—has multiple functions, including protecting the ear from diseases infection and dehydration. In previous studies, we genotyped an association panel of 508 inbred lines genotyped with a total of ~550,000 SNPs (Illumina 50 K SNP Chip and RNA-seq). Genome-Wide Association Studies (GWAS) were conducted on four husk traits: husk length (HL), husk layer number (HN), husk thickness (HT), and husk width (HW). Minimal associations were identified and none of them passed the P-value threshold after a Bonferroni multiple-test correction using a single locus test in framework of mixed linear model. In this study, we doubled the number of SNPs (~1,250,000 in total) by adding GBS and 600 K SNP Chip. GWAS, performed with the recently developed multiple loci model (BLINK), revealed six genetic loci associated with HN and HT above the Bonferroni multiple-test threshold. Five candidate genes were identified based on the linkage disequilibrium with these loci, including GRMZM2G381691 and GRMZM2G012416. These two genes were up-regulation and down-regulation in all husk related tissues, respectively. GRMZM2G381691 associated with HT encoded a CCT domain protein, which expressed higher in tropical than temperate maize. GRMZM2G012416 associated with HN encoded an Armadillo (ARM) repeat protein, which regulated GA signal pathway. These associated SNPs and candidate genes paved a path to understand the genetic architecture of husk in maize.

QTL mapping and transcriptome analysis identify candidate genes regulating pericarp thickness in sweet corn

BACKGROUND

In recent years, the planting area of sweet corn in China has expanded rapidly. Some new varieties with high yields and good adaptabilities have emerged. However, the improvement of edible quality traits, especially through the development of varieties with thin pericarp thickness, has not been achieved to date. Pericarp thickness is a complex trait that is the key factor determining the edible quality of sweet corn. Genetic mapping combined with transcriptome analysis was used to identify candidate genes controlling pericarp thickness.

RESULTS

To identify novel quantitative trait loci (QTLs) for pericarp thickness, a sweet corn BC₄F₃ population of 148 lines was developed using the two sweet corn lines M03 (recurrent parent) and M08 (donor parent). Additionally, a high-density genetic linkage map containing 3876 specific length amplified fragment (SLAF) tags was constructed and used for mapping QTLs for pericarp thickness. Interestingly, 14 QTLs for pericarp thickness were detected, and one stable QTL (qPT10-5) was detected across multiple years, which explained 7.78-35.38% of the phenotypic variation located on chromosome 10 (144,631,242-145,532,401). Forty-two candidate genes were found within the target region of qPT10-5. Moreover, of these 42 genes, five genes (GRMZM2G143402, GRMZM2G143389, GRMZM2G143352, GRMZM6G287947, and AC234202.1_FG004) were differentially expressed between the two parents, as revealed by transcriptome analysis. According to the gene annotation information, three genes might be considered candidates for pericarp thickness. GRMZM2G143352 and GRMZM2G143402 have been annotated as AUX/IAA transcription factor and ZIM transcription factor, respectively, while GRMZM2G143389 has been annotated as FATTY ACID EXPORT 2, chloroplastic.

CONCLUSIONS

This study identified a major QTL and candidate genes that could accelerate breeding for the thin pericarp thickness variety of sweet corn, and these results established the basis for map-based cloning and further functional research.