Identification of favorable SNP alleles and candidate genes responsible for inflorescence-related traits via GWAS in chrysanthemum

Multi-locus genome-wide association studies reveal the dynamic genetic architecture of flowering time in chrysanthemum

KEY MESSAGE

The dynamic genetic architecture of flowering time in chrysanthemum was elucidated by GWAS. Thirty-six known genes and 14 candidate genes were identified around the stable QTNs and QEIs, among which ERF-1 was highlighted. Flowering time (FT) adaptation is one of the major breeding goals in chrysanthemum, a multipurpose ornamental plant. In order to reveal the dynamic genetic architecture of FT in chrysanthemum, phenotype investigation of ten FT-related traits was conducted on 169 entries in 2 environments. The broad-sense heritability of five non-conditional FT traits, i.e., budding (FBD), visible coloring (VC), early opening (EO), full-bloom (OF) and decay period (DP), ranged from 56.93 to 84.26%, which were higher than that of the five derived conditional FT traits (38.51-75.13%). The phenotypic variation coefficients of OF_EO and DP_OF were relatively large ranging from 30.59 to 36.17%. Based on 375,865 SNPs, the compressed variance component mixed linear model 3VmrMLM was applied for a multi-locus genome-wide association study (GWAS). As a result, 313 quantitative trait nucleotides (QTNs) were identified for the non-conditional FT traits in single-environment analysis, while 119 QTNs and 67 QTN-by-environment interactions (QEIs) were identified in multi-environment analysis. As for the conditional traits, 343 QTNs were detected in single-environment analysis, and 119 QTNs and 83 QEIs were identified in multi- environment analysis. Among the genes around stable QTNs and QEIs, 36 were orthologs of known FT genes in Arabidopsis and other plants; 14 candidates were mined by combining the transcriptomics data and functional annotation, including ERF-1, ACA10, and FOP1. Furthermore, the haplotype analysis of ERF-1 revealed six elite accessions with extreme FBD. Our findings contribute to the understanding of dynamic genetic architecture of FT and provide valuable resources for future chrysanthemum molecular breeding programs.

Genetic architecture and genomic prediction of plant height-related traits in chrysanthemum

Plant height (PH) is a crucial trait determining plant architecture in chrysanthemum. To better understand the genetic basis of PH, we investigated the variations of PH, internode number (IN), internode length (IL), and stem diameter (SD) in a panel of 200 cut chrysanthemum accessions. Based on 330 710 high-quality SNPs generated by genotyping by sequencing, a total of 42 associations were identified via a genome-wide association study (GWAS), and 16 genomic regions covering 2.57 Mb of the whole genome were detected through selective sweep analysis. In addition, two SNPs, Chr1_339370594 and Chr18_230810045, respectively associated with PH and SD, overlapped with the selective sweep regions from FST and π ratios. Moreover, candidate genes involved in hormones, growth, transcriptional regulation, and metabolic processes were highlighted based on the annotation of homologous genes in Arabidopsis and transcriptomes in chrysanthemum. Finally, genomic selection for four PH-related traits was performed using a ridge regression best linear unbiased predictor model (rrBLUP) and six marker sets. The marker set constituting the top 1000 most significant SNPs identified via GWAS showed higher predictabilities for the four PH-related traits, ranging from 0.94 to 0.97. These findings improve our knowledge of the genetic basis of PH and provide valuable markers that could be applied in chrysanthemum genomic selection breeding programs.

Multi-locus genome-wide association study and genomic prediction for flowering time in chrysanthemum

MAIN CONCLUSION

Multi-locus GWAS detected several known and candidate genes responsible for flowering time in chrysanthemum. The associations could greatly increase the predictive ability of genome selection that accelerates the possible application of GS in chrysanthemum breeding. Timely flowering is critical for successful reproduction and determines the economic value for ornamental plants. To investigate the genetic architecture of flowering time in chrysanthemum, a multi-locus genome-wide association study (GWAS) was performed using a collection of 200 accessions and 330,710 single-nucleotide polymorphisms (SNPs) via 3VmrMLM method. Five flowering time traits including budding (FBD), visible colouring (VC), early opening (EO), full-bloom (OF) and senescing (SF) stages, plus five derived conditional traits were recorded in two environments. Extensive phenotypic variations were observed for these flowering time traits with coefficients of variation ranging from 6.42 to 38.27%, and their broad-sense heritability ranged from 71.47 to 96.78%. GWAS revealed 88 stable quantitative trait nucleotides (QTNs) and 93 QTN-by-environment interactions (QEIs) associated with flowering time traits, accounting for 0.50-8.01% and 0.30-10.42% of the phenotypic variation, respectively. Amongst the genes around these stable QTNs and QEIs, 21 and 10 were homologous to known flowering genes in Arabidopsis; 20 and 11 candidate genes were mined by combining the functional annotation and transcriptomics data, respectively, such as MYB55, FRIGIDA-like, WRKY75 and ANT. Furthermore, genomic selection (GS) was assessed using three models and seven unique marker datasets. We found the prediction accuracy (PA) using significant SNPs identified by GWAS under SVM model exhibited the best performance with PA ranging from 0.90 to 0.95. Our findings provide new insights into the dynamic genetic architecture of flowering time and the identified significant SNPs and candidate genes will accelerate the future molecular improvement of chrysanthemum.

Recent advances and future perspectives in early-maturing cotton research

Cotton's fundamental requirements for long periods of growth and specific seasonal temperatures limit the global arable areas that can be utilized to cultivate cotton. This constraint can be alleviated by breeding for early-maturing varieties. By delaying the sowing dates without impacting the boll-opening time, early-maturing varieties not only mitigate the yield losses brought on by unfavorable weathers in early spring and late autumn but also help reducing the competition between cotton and other crops for arable land, thereby optimizing the cropping system. This review presents studies and breeding efforts for early-maturing cotton, which efficiently pyramid early maturity, high-quality, multiresistance traits, and suitable plant architecture by leveraging pleiotropic genes. Attempts are also made to summarize our current understanding of the molecular mechanisms underlying early maturation, which involves many pathways such as epigenetic, circadian clock, and hormone signaling pathways. Moreover, new avenues and effective measures are proposed for fine-scale breeding of early-maturing crops to ensure the healthy development of the agricultural industry.

Bioinformatics in Plant Breeding and Research on Disease Resistance

In the context of plant breeding, bioinformatics can empower genetic and genomic selection to determine the optimal combination of genotypes that will produce a desired phenotype and help expedite the isolation of these new varieties. Bioinformatics is also instrumental in collecting and processing plant phenotypes, which facilitates plant breeding. Robots that use automated and digital technologies to collect and analyze different types of information to monitor the environment in which plants grow, analyze the environmental stresses they face, and promptly optimize suboptimal and adverse growth conditions accordingly, have helped plant research and saved human resources. In this paper, we describe the use of various bioinformatics databases and algorithms and explore their potential applications in plant breeding and for research on plant disease resistance.

Towards the Improvement of Ornamental Attributes in Chrysanthemum: Recent Progress in Biotechnological Advances

Incessant development and introduction of novel cultivars with improved floral attributes are vital in the dynamic ornamental industry. Chrysanthemum (Chrysanthemum morifolium) is a highly favored ornamental plant, ranking second globally in the cut flower trade, after rose. Development of new chrysanthemum cultivars with improved and innovative modifications in ornamental attributes, including floral color, shape, plant architecture, flowering time, enhanced shelf life, and biotic and abiotic stress tolerance, is a major goal in chrysanthemum breeding. Despite being an economically important ornamental plant, the application of conventional and molecular breeding approaches to various key traits of chrysanthemum is hindered owing to its genomic complexity, heterozygosity, and limited gene pool availability. Although classical breeding of chrysanthemum has resulted in the development of several hundreds of cultivars with various morphological variations, the genetic and transcriptional control of various important ornamental traits remains unclear. The coveted blue colored flowers of chrysanthemums cannot be achieved through conventional breeding and mutation breeding due to technical limitations. However, blue-hued flower has been developed by genetic engineering, and transgenic molecular breeding has been successfully employed, leading to substantial progress in improving various traits. The recent availability of whole-genome sequences of chrysanthemum offers a platform to extensively employ MAS to identify a large number of markers for QTL mapping, and GWAS to dissect the genetic control of complex traits. The combination of NGS, multi-omic platforms, and genome editing technologies has provided a tremendous scope to decipher the molecular and regulatory mechanisms. However, the application and integration of these technologies remain inadequate for chrysanthemum. This review, therefore, details the significance of floral attributes, describes the efforts of recent advancements, and highlights the possibilities for future application towards the improvement of crucial ornamental traits in the globally popular chrysanthemum plant.

Association Mapping of Drought Tolerance Indices in Ethiopian Durum Wheat (Triticum turgidum ssp. durum)

Ethiopia is a major producer of durum wheat in sub-Saharan Africa. However, its production is prone to drought stress as it is fully dependent on rain, which is erratic and unpredictable. This study aimed to detect marker-trait associations (MTAs) and quantitative trait loci (QTLs) related to indices. Six drought tolerance indices, i.e., drought susceptibility index (DSI), geometric mean productivity (GMP), relative drought index (RDI), stress tolerance index (STI), tolerance index (TOL), and yield stability index (YSI) were calculated from least-square means (lsmeans) of grain yield (GY) and traits significantly (p < 0.001) correlated with grain yield (GY) under field drought stress (FDS) and field non-stress (FNS) conditions. GY, days to grain filling (DGF), soil plant analysis development (SPAD) chlorophyll meter, seeds per spike (SPS), harvest index (HI), and thousand kernel weight (TKW) were used to calculate DSI, GMP, RDI, STI, TOL, and YSI drought indices. Accessions, DW084, DW082, DZ004, C037, and DW092 were selected as the top five drought-tolerant based on DSI, RDI, TOL, and YSI combined ranking. Similarly, C010, DW033, DW080, DW124-2, and C011 were selected as stable accessions based on GMP and STI combined ranking. A total of 184 MTAs were detected linked with drought indices at -log₁₀p ≥ 4.0,79 of which were significant at a false discovery rate (FDR) of 5%. Based on the linkage disequilibrium (LD, r ² ≥ 0.2), six of the MTAs with a positive effect on GY-GMP were detected on chromosomes 2B, 3B, 4A, 5B, and 6B, explaining 14.72, 10.07, 26.61, 21.16, 21.91, and 22.21% of the phenotypic variance, respectively. The 184 MTAs were clustered into 102 QTLs. Chromosomes 1A, 2B, and 7A are QTL hotspots with 11 QTLs each. These chromosomes play a key role in drought tolerance and respective QTL may be exploited by marker-assisted selection for improving drought stress tolerance in wheat.

Identification of Chilling Accumulation-Associated Genes for Litchi Flowering by Transcriptome-Based Genome-Wide Association Studies

Litchi is an important Sapindaceae fruit tree. Flowering in litchi is triggered by low temperatures in autumn and winter. It can be divided into early-, medium-, and late-flowering phenotypes according to the time for floral induction. Early-flowering varieties need low chilling accumulation level for floral induction, whereas the late-flowering varieties require high chilling accumulation level. In the present study, RNA-Seq of 87 accessions was performed and transcriptome-based genome-wide association studies (GWAS) was used to identify candidate genes involved in chilling accumulation underlying the time for floral induction. A total of 98,155 high-quality single-nucleotide polymorphism (SNP) sites were obtained. A total of 1,411 significantly associated SNPs and 1,115 associated genes (AGs) were identified, of which 31 were flowering-related, 23 were hormone synthesis-related, and 27 were hormone signal transduction-related. Association analysis between the gene expression of the AGs and the flowering phenotypic data was carried out, and differentially expressed genes (DEGs) in a temperature-controlled experiment were obtained. As a result, 15 flowering-related candidate AGs (CAGs), 13 hormone synthesis-related CAGs, and 11 hormone signal transduction-related CAGs were further screened. The expression levels of the CAGs in the early-flowering accessions were different from those in the late-flowering ones, and also between the flowering trees and non-flowering trees. In a gradient chilling treatment, flowering rates of the trees and the CAGs expression were affected by the treatment. Our present work for the first time provided candidate genes for genetic regulation of flowering in litchi using transcriptome-based GWAS.

Transcriptome Analysis Reveals Genes Respond to Chlorophyll Deficiency in Green and Yellow Leaves of Chrysanthemum morifolium Ramat

Chlorophyll is vital for photosynthesis to produce sugars and other useful biochemical products in green plants. However, the molecular effects of chlorophyll deficiency in Chrysanthemum are largely unknown. In this study, we identified a bud sport mutant chrysanthemum belonging to the variety ‘Nannong Binyun’, which has yellow branches. Plant physiological studies have shown that the yellow color is revealed due to chlorophyll loss. RNA extracts of yellow and green tissues were analyzed using high-throughput RNA-sequencing, and a total of 11,649 tissue enriched unigenes that respond to chlorophyll deficiency were identified, including 4803 unigenes upregulated in yellow tissues and 6846 unigenes in green tissues. GO analysis revealed that these tissue-enriched genes may involve in the physiological processes of chlorophyll accumulation and photosynthesis. In addition, many DEGs from the families of AP2-EREBP, bHLH, MYB, and FAR1 that are associated with plant development and stress response were detected. Our study found that most of the genes from the GRAS family were downregulated in yellow leaves, indicating their putative roles in stem cell maintenance and possible contribution to leaf size determination.

Genotyping by Sequencing-Based Discovery of SNP Markers and Construction of Linkage Map from F5 Population of Pepper with Contrasting Powdery Mildew Resistance Trait

Powdery mildew (PM) is a common fungal disease infecting pepper plants worldwide. Molecular breeding of pepper cultivars with powdery mildew resistance is desirable for the economic improvement of pepper cultivation. In the present study, 188 F5 population derived from AR1 (PM resistant) and TF68 (PM sensitive) parents were subjected to high-throughput genotyping by sequencing (GBS) for the identification of single nucleotide polymorphism (SNP) markers. Further, the identified SNP markers were utilized for the construction of genetic linkage map and QTL analysis. Overall read mapping percentage of 87.29% was achieved in this study with the total length of mapped region ranging from 2,956,730 to 25,537,525 bp. A total of 41,111 polymorphic SNPs were identified, and a final of 1,841 SNPs were filtered for the construction of a linkage map. A total of 12 linkage groups were constructed corresponding to each chromosome with 1,308 SNP markers with the map length of 2506.8 cM. Further, two QTLs such as Pm-2.1 and Pm-5.1 were identified in chromosomes 2 and 5, respectively, for the PM resistance. Overall, the outcomes of the present endeavor can be utilized for the marker-assisted selection of pepper with powdery mildew-resistant trait.

Genetic Architecture Underlying the Metabolites of Chlorogenic Acid Biosynthesis in Populus tomentosa

Chlorogenic acid (CGA) plays a crucial role in defense response, immune regulation, and the response to abiotic stress in plants. However, the genetic regulatory network of CGA biosynthesis pathways in perennial plants remains unclear. Here, we investigated the genetic architecture for CGA biosynthesis using a metabolite-based genome-wide association study (mGWAS) and expression quantitative trait nucleotide (eQTN) mapping in a population of 300 accessions of Populus tomentosa. In total, we investigated 204 SNPs which were significantly associated with 11 metabolic traits, corresponding to 206 genes, and were mainly involved in metabolism and cell growth processes of P. tomentosa. We identified 874 eQTNs representing 1066 genes, in which the expression and interaction of causal genes affected phenotypic variation. Of these, 102 genes showed significant signatures of selection in three geographical populations, which provided insights into the adaptation of CGA biosynthesis to the local environment. Finally, we constructed a genetic network of six causal genes that coordinately regulate CGA biosynthesis, revealing the multiple regulatory patterns affecting CGA accumulation in P. tomentosa. Our study provides a multiomics strategy for understanding the genetic basis underlying the natural variation in the CGA biosynthetic metabolites of Populus, which will enhance the genetic development of abiotic-resistance varieties in forest trees.

Association mapping for yield traits in Paeonia rockii based on SSR markers within transcription factors of comparative transcriptome

BACKGROUND

Allelic variation underlying the quantitative traits in plants is caused by the extremely complex regulation process. Tree peony originated in China is a peculiar ornamental, medicinal and oil woody plant. Paeonia rockii, one of tree peony species, is a precious emerging woody oil crop. However, in this valuable plant, the study of functional loci associated with yield traits has rarely been identified. Therefore, to explore the genetic architecture of 24 yield quantitative traits, the association mapping was first reported in 420 unrelated cultivated P. rockii individuals based on the next-generation sequencing (NGS) and single-molecule long-read sequencing (SMLRS).

RESULTS

The developed 58 pairs of polymorphic expressed sequence tag-simple sequence repeat (EST-SSR) markers from 959 candidate transcription factors (TFs) associated with yield were used for genotyping the 420 P. rockii accessions. We observed a high level of genetic diversity (polymorphic information content, PIC = 0.514) and low linkage disequilibrium (LD) between EST-SSRs. Moreover, four subpopulations in the association population were revealed by STRUCTURE analyses. Further, single-marker association analysis identified 141 significant associations, involving 17 quantitative traits and 41 EST-SSRs. These loci were mainly from AP2, TCP, MYB, HSF, bHLH, GATA, and B3 gene families and showed a small proportion of the phenotypic variance (3.79 to 37.45%).

CONCLUSIONS

Our results summarize a valuable collection of functional loci associated with yield traits in P. rockii, and provide a precious resource that reveals allelic variation underlying quantitative traits in Paeonia and other woody oil crops.

Current achievements and future prospects in the genetic breeding of chrysanthemum: a review

Chrysanthemum (Chrysanthemum morifolium Ramat.) is a leading flower with applied value worldwide. Developing new chrysanthemum cultivars with novel characteristics such as new flower colors and shapes, plant architectures, flowering times, postharvest quality, and biotic and abiotic stress tolerance in a time- and cost-efficient manner is the ultimate goal for breeders. Various breeding strategies have been employed to improve the aforementioned traits, ranging from conventional techniques, including crossbreeding and mutation breeding, to a series of molecular breeding methods, including transgenic technology, genome editing, and marker-assisted selection (MAS). In addition, the recent extensive advances in high-throughput technologies, especially genomics, transcriptomics, proteomics, metabolomics, and microbiomics, which are collectively referred to as omics platforms, have led to the collection of substantial amounts of data. Integration of these omics data with phenotypic information will enable the identification of genes/pathways responsible for important traits. Several attempts have been made to use emerging molecular and omics methods with the aim of accelerating the breeding of chrysanthemum. However, applying the findings of such studies to practical chrysanthemum breeding remains a considerable challenge, primarily due to the high heterozygosity and polyploidy of the species. This review summarizes the recent achievements in conventional and modern molecular breeding methods and emerging omics technologies and discusses their future applications for improving the agronomic and horticultural characteristics of chrysanthemum.