Dual-Model GWAS Analysis and Genomic Selection of Maize Flowering Time-Related Traits.

An appropriate flowering period is an important selection criterion in maize breeding. It plays a crucial role in the ecological adaptability of maize varieties. To explore the genetic basis of flowering time, GWAS and GS analyses were conducted using an associating panel consisting of 379 multi-parent DH lines. The DH population was phenotyped for days to tasseling (DTT), days to pollen-shedding (DTP), and days to silking (DTS) in different environments. The heritability was 82.75%, 86.09%, and 85.26% for DTT, DTP, and DTS, respectively. The GWAS analysis with the FarmCPU model identified 10 single-nucleotide polymorphisms (SNPs) distributed on chromosomes 3, 8, 9, and 10 that were significantly associated with flowering time-related traits. The GWAS analysis with the BLINK model identified seven SNPs distributed on chromosomes 1, 3, 8, 9, and 10 that were significantly associated with flowering time-related traits. Three SNPs 3_198946071, 9_146646966, and 9_152140631 showed a pleiotropic effect, indicating a significant genetic correlation between DTT, DTP, and DTS. A total of 24 candidate genes were detected. A relatively high prediction accuracy was achieved with 100 significantly associated SNPs detected from GWAS, and the optimal training population size was 70%. This study provides a better understanding of the genetic architecture of flowering time-related traits and provides an optimal strategy for GS.

Effects of Laminaria japonica polysaccharide and coumaric acid on pasting, rheological, retrogradation and structural properties of corn starch.

The aim of this study was to investigate the effects of Laminaria japonica polysaccharide (LJP) and coumaric acid (CA) on pasting, rheological, retrogradation and structural properties of corn starch (CS). Rapid viscosity analysis (RVA) revealed that LJP significantly increased the peak viscosity, trough viscosity, final viscosity, and setback viscosity of CS gel (p < 0.05) in a concentration-dependent manner. The addition of LJP and CA simultaneously caused the pasting of CS to need a greater temperature (from 75.53 °C to 78.75 °C), suggesting that LJP and CA made CS pasting more difficult. Dynamic viscoelasticity measurements found that all gels exhibited typical characteristics of weak gel. When compared to CS gel, 4 % LJP increased the viscosity and fluidity of gel and the simultaneous addition of LJP and CA reduced the elasticity. The steady shear results showed that the all gels were pseudoplastic fluids with shear-thinning behavior. In the meanwhile, the addition of LJP and CA enhanced the pseudoplasticity of CS-LJP-CA gel and improved its shear thinning. Furthermore, thermodynamic results showed that 8 % LJP promoted the retrogradation of CS gel and 2.0 % CA delayed the retrogradation of CS gel. Notably, on the 7th day of retrogradation, 2.0 % CA significantly decreased the retrogradation rate of CS-LJP by 19.31 % as compared to CS + 8 % LJP. Microstructure observation revealed that LJP made the honeycomb network structure of CS gel partially collapsed, and the surface of CS-LJP gel developed venation. Nevertheless, the structure of CS-LJP gel was clearly enhanced by adding CA. FT-IR spectra demonstrated that the addition of LJP or CA to CS did not result in the formation of a new distinctive peak in the system, suggesting the absence of a new group. Moreover, LF-NMR findings showed that LJP and CA strengthened the gel structure of CS and enhanced its capacity to retain water. This study not only provided a new insight into using LJP and CA to regulate the gel properties of CS, but also provided scientific strategy for developing starchy foods.

HDGT: Heterogeneous Driving Graph Transformer for Multi-Agent Trajectory Prediction via Scene Encoding.

Encoding a driving scene into vector representations has been an essential task for autonomous driving that can benefit downstream tasks e.g., trajectory prediction. The driving scene often involves heterogeneous elements such as the different types of objects (agents, lanes, traffic signs) and the semantic relations between objects are rich and diverse. Meanwhile, there also exist relativity across elements, which means that the spatial relation is a relative concept and need be encoded in a ego-centric manner instead of in a global coordinate system. Based on these observations, we propose Heterogeneous Driving Graph Transformer (HDGT), a backbone modelling the driving scene as a heterogeneous graph with different types of nodes and edges. For heterogeneous graph construction, we connect different types of nodes according to diverse semantic relations. For spatial relation encoding, the coordinates of the node as well as its in-edges are in the local node-centric coordinate system. For the aggregation module in the graph neural network (GNN), we adopt the transformer structure in a hierarchical way to fit the heterogeneous nature of inputs. Experimental results show that HDGT achieves state-of-the-art performance for the task of trajectory prediction, on INTERACTION Prediction Challenge and Waymo Open Motion Challenge.

Identification and fine mapping of a major QTL (qRtsc8-1) conferring resistance to maize tar spot complex and validation of production markers in breeding lines.

KEY MESSAGE: A major QTL of qRtsc8-1 conferring TSC resistance was identified and fine mapped to a 721 kb region on chromosome 8 at 81 Mb, and production markers were validated in breeding lines. Tar spot complex (TSC) is a major foliar disease of maize in many Central and Latin American countries and leads to severe yield loss. To dissect the genetic architecture of TSC resistance, a genome-wide association study (GWAS) panel and a bi-parental doubled haploid population were used for GWAS and selective genotyping analysis, respectively. A total of 115 SNPs in bin 8.03 were detected by GWAS and three QTL in bins 6.05, 6.07, and 8.03 were detected by selective genotyping. The major QTL qRtsc8-1 located in bin 8.03 was detected by both analyses, and it explained 14.97% of the phenotypic variance. To fine map qRtsc8-1, the recombinant-derived progeny test was implemented. Recombinations in each generation were backcrossed, and the backcross progenies were genotyped with Kompetitive Allele Specific PCR (KASP) markers and phenotyped for TSC resistance individually. The significant tests for comparing the TSC resistance between the two classes of progenies with and without resistant alleles were used for fine mapping. In BC5 generation, qRtsc8-1 was fine mapped in an interval of ~ 721 kb flanked by markers of KASP81160138 and KASP81881276. In this interval, the candidate genes GRMZM2G063511 and GRMZM2G073884 were identified, which encode an integral membrane protein-like and a leucine-rich repeat receptor-like protein kinase, respectively. Both genes are involved in maize disease resistance responses. Two production markers KASP81160138 and KASP81160155 were verified in 471 breeding lines. This study provides valuable information for cloning the resistance gene, and it will also facilitate the routine implementation of marker-assisted selection in the breeding pipeline for improving TSC resistance.

Genetic Dissection of Quantitative Resistance to Common Rust (Puccinia sorghi) in Tropical Maize (Zea mays L.) by Combined Genome-Wide Association Study, Linkage Mapping, and Genomic Prediction.

Common rust is one of the major foliar diseases in maize, leading to significant grain yield losses and poor grain quality. To dissect the genetic architecture of common rust resistance, a genome-wide association study (GWAS) panel and a bi-parental doubled haploid (DH) population, DH1, were used to perform GWAS and linkage mapping analyses. The GWAS results revealed six single-nucleotide polymorphisms (SNPs) significantly associated with quantitative resistance of common rust at a very stringent threshold of P-value 3.70 × 10-6 at bins 1.05, 1.10, 3.04, 3.05, 4.08, and 10.04. Linkage mapping identified five quantitative trait loci (QTL) at bins 1.03, 2.06, 4.08, 7.03, and 9.00. The phenotypic variation explained (PVE) value of each QTL ranged from 5.40 to 12.45%, accounting for the total PVE value of 40.67%. Joint GWAS and linkage mapping analyses identified a stable genomic region located at bin 4.08. Five significant SNPs were only identified by GWAS, and four QTL were only detected by linkage mapping. The significantly associated SNP of S10_95231291 detected in the GWAS analysis was first reported. The linkage mapping analysis detected two new QTL on chromosomes 7 and 10. The major QTL on chromosome 7 in the region between 144,567,253 and 149,717,562 bp had the largest PVE value of 12.45%. Four candidate genes of GRMZM2G328500, GRMZM2G162250, GRMZM2G114893, and GRMZM2G138949 were identified, which played important roles in the response of stress resilience and the regulation of plant growth and development. Genomic prediction (GP) accuracies observed in the GWAS panel and DH1 population were 0.61 and 0.51, respectively. This study provided new insight into the genetic architecture of quantitative resistance of common rust. In tropical maize, common rust could be improved by pyramiding the new sources of quantitative resistance through marker-assisted selection (MAS) or genomic selection (GS), rather than the implementation of MAS for the single dominant race-specific resistance gene.

Mapping of QTL and identification of candidate genes conferring spontaneous haploid genome doubling in maize (Zea mays L.).

In vivo doubled haploid (DH) technology is widely used in commercial maize (Zea mays L.) breeding. Haploid genome doubling is a critical step in DH breeding. In this study, inbred lines GF1 (0.65), GF3(0.29), and GF5 (0) with high, moderate, and poor spontaneous haploid genome doubling (SHGD), respectively, were selected to develop mapping populations for SHGD. Three QTL, qshgd1, qshgd2, and qshgd3, related to SHGD were identified by selective genotyping. With the exception of qshgd3, the source of haploid genome doubling alleles were derived from GF1. Furthermore, RNA-Seq was conducted to identify putative candidate genes between GF1 and GF5 within the qshgd1 region. A differentially expressed formin-like protein 5 transcript was identified within the qshgd1 region.

Mapping of QTL for kernel abortion caused by in vivo haploid induction in maize (Zea mays L.).

Kernel abortion is common phenomenon in vivo haploid induction and closely linked with haploid induction rate, but little information of kernel abortion is available and its genetic basis still unclear. We used two mapping populations including 186 and 263 F2.3 family lines to analyze the different degree of kernel abortion and identify quantitative trait loci (QTL) responsible for kernel abortion during haploid induction. In total 62 putative QTL, accounting for 3.27-14.70% of the phenotypic variation in kernel abortion traits, were detected across all 10 chromosomes. Ten QTL with over 10% contribution to phenotypic variation were affecting the fifth level of endosperm abortion (EnA5th), endosperm abortion (EnA) and total abortion (TA). Co-localization among kernel abortion traits QTL was observed in both populations and among different kernel abortion types. Five overlaps were indentified in the QTL for kernel abortion traits and HIR traits. Maize chromosome bins 3.01-3.02, 3.04-3.06, 4.05-4.06, 5.03-5.04, 8.06 were QTL hotspots for three or four traits related to the kernel abortion during haploid induction. Total kernel abortion rate (TAR) and HIR showed highly significant positive correlation. These findings may help to reveal haploid induction mechanisms and improve haploid production efficiency.

Coregulation of ribosomal RNA with hundreds of genes contributes to phenotypic variation.

Ribosomal repeats occupy 5% of a plant genome, yet there has been little study of their diversity in the modern age of genomics. Ribosomal copy number and expression variation present an opportunity to tap a novel source of diversity. In the present study, we estimated the ribosomal DNA (rDNA) copy number and ribosomal RNA (rRNA) expression for a population of maize inbred lines and investigated the potential role of rDNA and rRNA dosage in regulating global gene expression. Extensive variation was found in both ribosomal DNA copy number and ribosomal RNA expression among maize inbred lines. However, rRNA abundance was not consistent with the copy number of the rDNA. We have not found that the rDNA gene dosage has a regulatory role in gene expression; however, thousands of genes are identified to be coregulated with rRNA expression, including genes participating in ribosome biogenesis and other functionally relevant pathways. We further investigated the potential roles of copy number and the expression level of rDNA on agronomic traits and found that both correlated with flowering time but through different regulatory mechanisms. This comprehensive analysis suggested that rRNA expression variation is a valuable source of functional diversity that affects gene expression variation and field-based phenotypic changes.

Novel technologies in doubled haploid line development.

haploid inducer line can be transferred (DH) technology can not only shorten the breeding process but also increase genetic gain. Haploid induction and subsequent genome doubling are the two main steps required for DH technology. Haploids have been generated through the culture of immature male and female gametophytes, and through inter- and intraspecific via chromosome elimination. Here, we focus on haploidization via chromosome elimination, especially the recent advances in centromere-mediated haploidization. Once haploids have been induced, genome doubling is needed to produce DH lines. This study has proposed a new strategy to improve haploid genome doubling by combing haploids and minichromosome technology. With the progress in haploid induction and genome doubling methods, DH technology can facilitate reverse breeding, cytoplasmic male sterile (CMS) line production, gene stacking and a variety of other genetic analysis.

QTL mapping for haploid male fertility by a segregation distortion method and fine mapping of a key QTL qhmf4 in maize.

KEY MESSAGE: Four QTL related to haploid male fertility were detected by a segregation distortion method and the key QTL qhmf4 was fine mapped to an interval of ~800 kb. Doubled haploid (DH) technology enables rapid development of homozygous lines in maize breeding programs. However, haploid genome doubling is a bottleneck for the commercialization of DH technology and is limited by haploid male fertility (HMF). This is the first study reporting the quantitative trait locus (QTL) analysis of HMF in maize. Four QTL, qhmf1, qhmf2, qhmf3, and qhmf4, controlling HMF have been identified by segregation distortion (SD) loci detection in the selected haploid population derived from 'Yu87-1/Zheng58'. Three loci, qhmf1, qhmf2, and qhmf4, were also detected in the selected haploid population derived from '4F1/Zheng58'. The QTL qhmf4 showed the strongest SD in both haploid populations. Based on the sequence information of 'Yu87-1' and 'Zheng58', thirteen markers being polymorphic between the two lines were developed to saturate the qhmf4 region. A total of 8168 H1BC2 (haploid backcross generation) plants produced from 'Yu87-1' and 'Zheng58' were screened for recombinants. All the 48 recombinants were backcrossed to 'Zheng58' to develop H1BC3 progeny. The heterozygous H1BC3 individuals were crossed with CAU5 to induce haploids. In each H1BC3 progeny, haploids were genotyped and evaluated for anther emergence score (AES). Significant (or no significant) difference (P < 0.05) between haploids with or without 'Yu87-1' donor segment indicated presence or absence of qhmf4 in the donor segment. The analysis of the 48 recombinants narrowed the qhmf4 locus down to an ~800 kb interval flanked by markers IND166 and IND1668.