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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.

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.

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.

Leaf angle (LA) is one of the most important canopy architecture related traits in maize (Zea mays L.). However, the genetic basis of LA at canopy-wide levels is still not completely understood. In this study, one RIL population derived from two parent lines with distinct plant architecture was used for QTL mapping of LA at eight leaves below the tassel across three environments. Fifty-six QTL for LA of eight leaves were identified in single environment analysis and 44 QTL for LA of eight leaves were detected in joint analysis. Among them, nine common QTL were identified because they were detected for LA more than 1 leaves or in 2 or 3 environments. The single QTL could explain 1.29–20.14% of the phenotypic variation with affecting LA of 1–8 leaves, included qLA5.1 affected LA of all eight leaves, qLA3.1 affected LA of the upper leaves (1stLA–4thLA), and qLA9.1 affected LA of the lower leaves (5thLA–8thLA). Furthermore, the 8thLA was mainly affected by major and minor QTL; the 1stLA, 4thLA and 5thLA were affected by major QTL, minor QTL and epistatic interactions; the other four LAs were simultaneously affected by major QTL, minor QTL, epistatic interactions and environments, inferred that the genetic architecture of LA of eight leaves was different. These results provide a comprehensive understanding of genetic basis of LA at canopy-wide levels, which will be helpful to design the ideal plant architecture in maize.

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 F 2 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 F 2 plants using the inclusive composite interval mapping of additive (ICIM-ADD) module, explaining 23.79% of the phenotypic variance. Out of the 409 F 2 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 F 2 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.

Ear row number (ERN) is not only a key trait involved in maize ( Zea mays L.) evolution but also an important component directly related to grain yield. In this report, 325 recombinant inbred lines (RILs, F 6:7 ) derived from a cross between B73 with 16 rows and SICAU1212 with four rows (two-ranked with two rows per rank) were utilized to detect quantitative trait loci (QTL) associated with ERN and two-ranked versus many-ranked ears (TR). Compared to modern maize that formed approximately 8–20 rows, SICAU1212 with four rows was the extreme case. A total of 12 and 8 QTLs were associated with ERN and TR across four environments through single-environment mapping, respectively. Each QTL responsible for ERN explained 2.33–21.28 % of the phenotypic variation. And the TR variation contributed by individual TR QTL ranged from 2.09 to 12.99 %. Notably, only three QTLs, qERN2 - 1 (bin 2.02), qERN8 - 1 (bin 8.02) and qERN8 - 2 (bin 8.04), were consistently detected in each environment and by joint analysis among all environments, which simultaneously influenced ERN and TR. One of the three QTLs, qERN8 - 1 was also identified as interacting with environment. In addition, nine pairs of significant epistatic interactions (two for ERN and seven for TR) were detected among all QTLs. The epistasis between qTR2 - 1 and qTR8 - 1 was consistent in most environments. This present study may provide the understanding of the genetic basis of ERN and TR and a foundation for further fine-mapping of these common QTLs.

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 (BC 3 F 2 and BC 4 F 2 ) 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.

Key message Two closely linked novel loci, qKRN2-1 and qKRN2-2 , associated with kernel row number were fine-mapped on chromosome 2, and a key candidate gene for qKRN2-1 was identified through expression analysis. Kernel row number (KRN) is a crucial factor influencing maize yield and serves as a significant target for maize breeding. The use of wild progenitor species can aid in identifying the essential traits for domestication and breeding. In this study, teosinte (MT1) served as the donor parent, the inbred maize line of Mo17 was used as the recurrent parent, we identified a major quantitative trait locus (QTL) for KRN, designated qKRN2 , into two closely linked loci, qKRN2-1 and qKRN2-2 . Here, fine mapping was performed to investigate two QTLs, qKRN2-1 and qKRN2-2 , within a genomic range of 272 kb and 775 kb, respectively. This was achieved using a progeny test strategy in an advanced backcross population, with the two QTLs explaining 33.49% and 35.30% of the phenotypic variance. Molecular marker-assisted selection resulted in the development of two nearly isogenic lines (NILs), qKRN2-1 and qKRN2-2 , which differed only in the segment containing the QTL. Notably, the maize (Mo17) alleles increased the KRN relative to teosinte by approximately 1.4 and 1.2 rows for qKRN2-1 and qKRN2-2 , respectively. Zm00001d002989 encodes a cytokinin oxidase/dehydrogenase and its expression in the immature ears exhibited significant differences among the qKRN2-1 NILs. In situ hybridization localized Zm00001d002989 to the primordia of the inflorescence meristem and spikelet pair meristems, is predicted to be the causal gene of qKRN2-1. The findings of this study deepen our understanding of the genetic basis of KRN and hold significant potential for improving maize grain yields.

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.

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 (BC 4 F 2 and BC 4 F 3 ) 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 BC 4 F 2 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 BC 4 F 2 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.