Fine mapping and candidate gene analysis of qSRC3 controlling the silk color in maize (Zea mays L.).

KEY MESSAGE: Fine mapping of the maize QTL qSRC3, responsible for red silk, uncovered the candidate gene ZmMYB20, which encodes an R2R3-MYB transcription factor, has light-sensitive expression, and putatively regulates genes expression associated with anthocyanin biosynthesis. Colorless silk is a key characteristic contributing to the visual quality of fresh corn intended for market distribution. Nonetheless, the identification of Mendelian trait loci and associated genes that control silk color has been scarce. In this study, a F2 population arising from the hybridization of the single-segment substitution line qSRC3MT1 with red silk, carrying an introgressed allele from teosinte (Zea mays ssp. mexicana), and the recurrent maize inbred line Mo17, characterized by light green silk, was utilized for fine mapping. We found that the red silk trait is controlled by a semi-dominant genetic locus known as qSRC3, and its expression is susceptible to light-mediated inhibition. Moreover, qSRC3 explained 68.78% of the phenotypic variance and was delimited to a 133.2 kb region, which includes three genes. Subsequent expression analyses revealed that ZmMYB20 (Zm00001d039700), which encodes an R2R3-MYB transcription factor, was the key candidate gene within qSRC3. Yeast one-hybrid and dual-luciferase reporter assays provided evidence that ZmMYB20 suppresses the expression of two crucial anthocyanin biosynthesis genes, namely ZmF3H and ZmUFGT, by directly binding to their respective promoter regions. Our findings underscore the significance of light-inhibited ZmMYB20 in orchestrating the spatial and temporal regulation of anthocyanin biosynthesis. These results advance the production of colorless silk in fresh corn, responding to the misconception that fresh corn with withered colored silk is not fresh and providing valuable genetic resources for the improvement of sweet and waxy maize.

Deploying QTL-seq rapid identification and separation of the major QTLs of tassel branch number for fine-mapping in advanced maize populations.

The tassel competes with the ear for nutrients and shields the upper leaves, thereby reducing the yield of grain. The tassel branch number (TBN) is a pivotal determinant of tassel size, wherein the reduced TBN has the potential to enhance the transmission of light and reduce the consumption of nutrients, which should ultimately result in increased yield. Consequently, the TBN has emerged as a vital target trait in contemporary breeding programs that focus on compact maize varieties. In this study, QTL-seq technology and advanced population mapping were used to rapidly identify and dissect the major effects of the TBN on QTL. Advanced mapping populations (BC4F2 and BC4F3) were derived from the inbred lines 18-599 (8-11 TBN) and 3237 (0-1 TBN) through phenotypic recurrent selection. First, 13 genomic regions associated with the TBN were detected using quantitative trait locus (QTL)-seq and were located on chromosomes 2 and 5. Subsequently, validated loci within these regions were identified by QTL-seq. Three QTLs for TBN were identified in the BC4F2 populations by traditional QTL mapping, with each QTL explaining the phenotypic variation of 6.13-18.17%. In addition, for the major QTL (qTBN2-2 and qTBN5-1), residual heterozygous lines (RHLs) were developed from the BC4F2 population. These two major QTLs were verified in the RHLs by QTL mapping, with the phenotypic variation explained (PVE) of 21.57% and 30.75%, respectively. Near-isogenic lines (NILs) of qTBN2-2 and qTBN5-1 were constructed. There were significant differences between the NILs in TBN. These results will enhance our understanding of the genetic basis of TBN and provide a solid foundation for the fine-mapping of TBN. Supplementary Information: The online version contains supplementary material available at 10.1007/s11032-023-01431-y.

Identification of a major QTL and genome-wide epistatic interactions for single vs. paired spikelets in a maize-teosinte F2 population.

Maize ear carries paired spikelets, whereas the ear of its wild ancestor, teosinte, bears single spikelets. However, little is known about the genetic basis of the processes of transformation of single spikelets in teosinte ear to paired spikelets in maize ear. In this study, a two-ranked, paired-spikelets primitive maize and a two-ranked, single-spikelet teosinte were utilized to develop an F2 population, and quantitative trait locus (loci) (QTL) mapping for single vs. paired spikelets (PEDS) was performed. One major QTL (qPEDS3.1) for PEDS located on chromosome 3S was identified in the 162 F2 plants using the inclusive composite interval mapping of additive (ICIM-ADD) module, explaining 23.79% of the phenotypic variance. Out of the 409 F2 plants, 43 plants with PEDS = 0% and 43 plants with PEDS > 20% were selected for selective genotyping, and the QTL (qPEDS3.1) was detected again. Moreover, the QTL (qPEDS3.1) was validated in three environments, which explained 31.05%, 38.94%, and 23.16% of the phenotypic variance, respectively. In addition, 50 epistatic QTLs were detected in the 162 F2 plants using the two-locus epistatic QTL (ICIM-EPI) module; they were distributed on all 10 chromosomes and explained 94.40% of the total phenotypic variance. The results contribute to a better understanding of the genetic basis of domestication of paired spikelets and provide a genetic resource for future map-based cloning; in addition, the systematic dissection of epistatic interactions underlies a theoretical framework for overcoming epistatic effects on QTL fine mapping. Supplementary Information: The online version contains supplementary material available at 10.1007/s11032-022-01276-x.

Combining QTL-seq and linkage mapping to uncover the genetic basis of single vs. paired spikelets in the advanced populations of two-ranked maize×teosinte.

BACKGROUND: Teosinte ear bears single spikelet, whereas maize ear bears paired spikelets, doubling the number of grains in each cupulate during maize domestication. In the past 20 years, genetic analysis of single vs. paired spikelets (PEDS) has been stagnant. A better understanding of genetic basis of PEDS could help fine mapping of quantitative trait loci (QTL) and cloning of genes. RESULTS: In this study, the advanced mapping populations (BC3F2 and BC4F2) of maize × teosinte were developed by phenotypic recurrent selection. Four genomic regions associated with PEDS were detected using QTL-seq, located on 194.64-299.52 Mb, 0-162.80 Mb, 12.82-97.17 Mb, and 125.06-157.01 Mb of chromosomes 1, 3, 6, and 8, respectively. Five QTL for PEDS were identified in the regions of QTL-seq using traditional QTL mapping. Each QTL explained 1.12-38.05% of the phenotypic variance (PVE); notably, QTL qPEDS3.1 with the average PVE of 35.29% was identified in all tests. Moreover, 14 epistatic QTL were detected, with the total PVE of 47.57-66.81% in each test. The QTL qPEDS3.1 overlapped with, or was close to, one locus of 7 epistatic QTL. Near-isogenic lines (NILs) of QTL qPEDS1.1, qPEDS3.1, qPEDS6.1, and qPEDS8.1 were constructed. All individuals of NIL-qPEDS6.1(MT1) and NIL-qPEDS8.1(MT1) showed paired spikelets (PEDS = 0), but the flowering time was 7 days shorter in the NIL-qPEDS8.1(MT1). The ratio of plants with PEDS > 0 was low (1/18 to 3/18) in the NIL-qPEDS1.1(MT1) and NIL-qPEDS3.1(MT1), maybe due to the epistatic effect. CONCLUSION: Our results suggested that major QTL, minor QTL, epistasis and photoperiod were associated with the variation of PEDS, which help us better understand the genetic basis of PEDS and provide a genetic resource for fine mapping of QTL.

Development of genic KASP SNP markers from RNA-Seq data for map-based cloning and marker-assisted selection in maize.

BACKGROUND: Maize is one of the most important field crops in the world. Most of the key agronomic traits, including yield traits and plant architecture traits, are quantitative. Fine mapping of genes/ quantitative trait loci (QTL) influencing a key trait is essential for marker-assisted selection (MAS) in maize breeding. However, the SNP markers with high density and high polymorphism are lacking, especially kompetitive allele specific PCR (KASP) SNP markers that can be used for automatic genotyping. To date, a large volume of sequencing data has been produced by the next generation sequencing technology, which provides a good pool of SNP loci for development of SNP markers. In this study, we carried out a multi-step screening method to identify kompetitive allele specific PCR (KASP) SNP markers based on the RNA-Seq data sets of 368 maize inbred lines. RESULTS: A total of 2,948,985 SNPs were identified in the high-throughput RNA-Seq data sets with the average density of 1.4 SNP/kb. Of these, 71,311 KASP SNP markers (the average density of 34 KASP SNP/Mb) were developed based on the strict criteria: unique genomic region, bi-allelic, polymorphism information content (PIC) value ≥0.4, and conserved primer sequences, and were mapped on 16,161 genes. These 16,161 genes were annotated to 52 gene ontology (GO) terms, including most of primary and secondary metabolic pathways. Subsequently, the 50 KASP SNP markers with the PIC values ranging from 0.14 to 0.5 in 368 RNA-Seq data sets and with polymorphism between the maize inbred lines 1212 and B73 in in silico analysis were selected to experimentally validate the accuracy and polymorphism of SNPs, resulted in 46 SNPs (92.00%) showed polymorphism between the maize inbred lines 1212 and B73. Moreover, these 46 polymorphic SNPs were utilized to genotype the other 20 maize inbred lines, with all 46 SNPs showing polymorphism in the 20 maize inbred lines, and the PIC value of each SNP was 0.11 to 0.50 with an average of 0.35. The results suggested that the KASP SNP markers developed in this study were accurate and polymorphic. CONCLUSIONS: These high-density polymorphic KASP SNP markers will be a valuable resource for map-based cloning of QTL/genes and marker-assisted selection in maize. Furthermore, the method used to develop SNP markers in maize can also be applied in other species.

Fruit development and epigenetic modifications.

Fruit development is a complex process that is regulated not only by plant hormones and transcription factors, but also requires epigenetic modifications. Epigenetic modifications include DNA methylation, histone post-translational modifications, chromatin remodeling and noncoding RNAs. Together, these epigenetic modifications, which are controlled during development and in response to the environment, determine the chromatin state of genes and contribute to the transcriptomes of an organism. Recent studies have demonstrated that epigenetic regulation plays an important role in fleshy fruit ripening. Dysfunction of a DNA demethylase delayed ripening in tomato, and the application of a DNA methylation inhibitor altered ripening process in the fruits of several species. These studies indicated that manipulating the epigenome of fruit crops could open new ways for breeding in the future. In this review, we highlight recent progress and address remaining questions and challenges concerning the epigenetic regulation of fruit development and ripening.

Critical roles of DNA demethylation in the activation of ripening-induced genes and inhibition of ripening-repressed genes in tomato fruit.

DNA methylation is a conserved epigenetic mark important for genome integrity, development, and environmental responses in plants and mammals. Active DNA demethylation in plants is initiated by a family of 5-mC DNA glycosylases/lyases (i.e., DNA demethylases). Recent reports suggested a role of active DNA demethylation in fruit ripening in tomato. In this study, we generated loss-of-function mutant alleles of a tomato gene, SlDML2, which is a close homolog of the Arabidopsis DNA demethylase gene ROS1 In the fruits of the tomato mutants, increased DNA methylation was found in thousands of genes. These genes included not only hundreds of ripening-induced genes but also many ripening-repressed genes. Our results show that SlDML2 is critical for tomato fruit ripening and suggest that active DNA demethylation is required for both the activation of ripening-induced genes and the inhibition of ripening-repressed genes.

Genetic mapping of QTL for the sizes of eight consecutive leaves below the tassel in maize (Zea mays L.).

KEY MESSAGE: A set of RIL population was used to detect QTL associated with the sizes of eight consecutive leaves, across different environments, and ten QTL clusters were identified as main QTLs. One of the important parameters of the maize leaf architecture that affects light penetration into the canopy, leaf size, has long attracted breeders' attention for optimizing the plant type of maize and for maximizing the grain yield (GY). In this study, we used 253 RIL lines derived from a cross between B73 and SICAU1212 to investigate the leaf widths (LWs), leaf lengths (LLs), and leaf areas (LAs) of eight consecutive leaves of maize below the tassel and GY across different environments and to identify quantitative traits loci (QTLs) controlling the above-mentioned traits, using inclusive interval mapping for single-environment analysis plus a mixed-model-based composite interval mapping for joint analysis. A total of 171 and 159 putative QTLs were detected through these two mapping methods, respectively. Single-environment mapping revealed that 39 stable QTLs explained more than 10 % of the phenotypic variance, and 35 of the 39 QTLs were also detected by joint analysis. In addition, joint analysis showed that nine of the 159 QTLs exhibited significant QTL × environment interaction and 15 significant epistatic interactions were identified. Approximately 47.17 % of the QTLs for leaf architectural traits in joint analysis were concentrated in ten main chromosomal regions, namely, bins 1.07, 2.02, 3.06, 4.09, 5.01, 5.02, 5.03-5.04, 5.07, 6.07, and 8.05. This study should provide a basis for further fine-mapping of these main genetic regions and improvement of maize leaf architecture.

Development of genome-wide insertion and deletion markers for maize, based on next-generation sequencing data.

BACKGROUND: Insertions and deletions (indels) are the most abundant form of structural variation in all genomes. Indels have been increasingly recognized as an important source of molecular markers due to high-density occurrence, cost-effectiveness, and ease of genotyping. Coupled with developments in bioinformatics, next-generation sequencing (NGS) platforms enable the discovery of millions of indel polymorphisms by comparing the whole genome sequences of individuals within a species. RESULTS: A total of 1,973,746 unique indels were identified in 345 maize genomes, with an overall density of 958.79 indels/Mbp, and an average allele number of 2.76, ranging from 2 to 107. There were 264,214 indels with polymorphism information content (PIC) values greater than or equal to 0.5, accounting for 13.39% of overall indels. Of these highly polymorphic indels, we designed primer pairs for 83,481 and 29,403 indels with major allele differences (i.e. the size difference between the most and second most frequent alleles) greater than or equal to 3 and 8 bp, respectively, based on the differing resolution capabilities of gel electrophoresis. The accuracy of our indel markers was experimentally validated, and among 100 indel markers, average accuracy was approximately 90%. In addition, we also validated the polymorphism of the indel markers. Of 100 highly polymorphic indel markers, all had polymorphisms with average PIC values of 0.54. CONCLUSIONS: The maize genome is rich in indel polymorphisms. Intriguingly, the level of polymorphism in genic regions of the maize genome was higher than that in intergenic regions. The polymorphic indel markers developed from this study may enhance the efficiency of genetic research and marker-assisted breeding in maize.