Identification of regulatory networks and hub genes controlling soybean seed set and size using RNA sequencing analysis

Revolutionizing soybean genomics: How CRISPR and advanced sequencing are unlocking new potential

Soybean Glycine max L., paleopolyploid genome, poses challenges to its genetic improvement. However, the development of reference genome assemblies and genome sequencing has completely changed the field of soybean genomics, allowing for more accurate and successful breeding techniques as well as research. During the single-cell revolution, one of the most advanced sequencing tools for examining the transcriptome landscape is single-cell RNA sequencing (scRNA-seq). Comprehensive resources for genetic improvement of soybeans may be found in the SoyBase and other genomics databases. CRISPR-Cas9 genome editing technology provides promising prospects for precise genetic modifications in soybean. This method has enhanced several soybean traits, including as yield, nutritional value, and resistance to both biotic and abiotic stresses. With base editing techniques that allow for precise DNA modifications, the use of CRISPR-Cas9 is further increased. With the availability of the reference genome for soybeans and the following assembly of wild and cultivated soybeans, significant chromosomal rearrangements and gene duplication events have been identified, offering new perspectives on the complex genomic structure of soybeans. Furthermore, major single nucleotide polymorphisms (SNPs) linked to stachyose and sucrose content have been found through genome-wide association studies (GWAS), providing important tools for enhancing soybean carbohydrate profiles. In order to open up new avenues for soybean genetic improvement, future research approaches include investigating transcriptional divergence processes, enhancing genetic resources, and incorporating CRISPR-Cas9 technologies.

Transcriptome and metabolome analyses reveal regulatory networks associated with nutrition synthesis in sorghum seeds

Cereal seeds are vital for food, feed, and agricultural sustainability because they store and provide essential nutrients to human and animal food and feed systems. Unraveling molecular processes in seed development is crucial for enhancing cereal grain yield and quality. We analyze spatiotemporal transcriptome and metabolome profiles during sorghum seed development in the inbred line 'BTx623'. Morphological and molecular analyses identify the key stages of seed maturation, specifying starch biosynthesis onset at 5 days post-anthesis (dpa) and protein at 10 dpa. Transcriptome profiling from 1 to 25 dpa reveal dynamic gene expression pathways, shifting from cellular growth and embryo development (1-5 dpa) to cell division, fatty acid biosynthesis (5-25 dpa), and seed storage compounds synthesis in the endosperm (5-25 dpa). Network analysis identifies 361 and 207 hub genes linked to starch and protein synthesis in the endosperm, respectively, which will help breeders enhance sorghum grain quality. The availability of this data in the sorghum reference genome line establishes a baseline for future studies as new pangenomes emerge, which will consider copy number and presence-absence variation in functional food traits.

Transcriptomic analysis of hub genes regulating albinism in light- and temperature-sensitive albino tea cultivars 'Zhonghuang 1' and 'Zhonghuang 2'

Albino tea cultivars have high economic value because their young leaves contain enhanced free amino acids that improve the quality and properties of tea. Zhonghuang 1 (ZH1) and Zhonghuang 2 (ZH2) are two such cultivars widely planted in China; however, the environmental factors and molecular mechanisms regulating their yellow-leaf phenotype remain unclear. In this study, we demonstrated that both ZH1 and ZH2 are light- and temperature-sensitive. Under natural sunlight and low-temperature conditions, their young shoots were yellow with decreased chlorophyll and an abnormal chloroplast ultrastructure. Conversely, young shoots were green with increased chlorophyll and a normal chloroplast ultrastructure under shading and high-temperature conditions. RNA-seq analysis was performed for high light and low light conditions, and pairwise comparisons identified genes exhibiting different light responses between albino and green-leaf cultivars, including transcription factors, cytochrome P450 genes, and heat shock proteins. Weighted gene coexpression network analyses of RNA-seq data identified the modules related to chlorophyll differences between cultivars. Genes involved in chloroplast biogenesis and development, light signaling, and JA biosynthesis and signaling were typically downregulated in albino cultivars, accompanied by a decrease in JA-ILE content in ZH2 during the albino period. Furthermore, we identified the hub genes that may regulate the yellow-leaf phenotype of ZH1 and ZH2, including CsGDC1, CsALB4, CsGUN4, and a TPR gene (TEA010575.1), which were related to chloroplast biogenesis. This study provides new insights into the molecular mechanisms underlying leaf color formation in albino tea cultivars.

Genetic diversity of grain yield traits and identification of a grain weight gene SiTGW6 in foxtail millet

KEY MESSAGE

Agronomic traits were evaluated in 1250 foxtail millet accessions, and a crucial gene SiTGW6 governing grain yield was identified. Elite haplotypes and dCAPS markers developed for SiTGW6 facilitate molecular breeding. A comprehensive evaluation of phenotypic characteristics and genetic diversity in germplasm resources are important for gene discovery and breeding improvements. In this study, we conducted a comprehensive evaluation of 1250 foxtail millet varieties, assessing seven grain yield-related traits and fourteen common agronomic traits over two years. Principal component analysis, correlation analysis, and cluster analysis revealed a strong positive correlation between 1000-grain weight and grain width with grain yield, emphasizing their importance in foxtail millet breeding. Additionally, we found that panicle weight positively correlated with 1000-grain weight but negatively correlated with branch and tiller numbers, indicating selection factors during domestication and breeding. Using this information, we identified 27 germplasm resources suitable for high-yield foxtail millet breeding. Furthermore, through an integration of haplotype variations and phenotype association analysis, we pinpointed a crucial gene, SiTGW6, responsible for governing grain yield in foxtail millet. SiTGW6 encodes an IAA-glucose hydrolase, primarily localized in the cytoplasm and predominantly expressed in flowering panicles. Employing RNAseq analysis, we identified 1439 differentially expressed genes across various SiTGW6 haplotypes. Functional enrichment analysis indicating that SiTGW6 regulates grain yield through the orchestration of auxin and glucan metabolism, as well as plant hormone signaling pathways. Additionally, we have identified elite haplotypes and developed dCAPS markers for SiTGW6, providing valuable technical tools to facilitate molecular breeding efforts in foxtail millet.

Identification of the domestication gene GmCYP82C4 underlying the major quantitative trait locus for the seed weight in soybean

KEY MESSAGE

A major quantitative trait locus (QTL) for the hundred-seed weight (HSW) was identified and confirmed in the two distinct soybean populations, and the target gene GmCYP82C4 underlying this locus was identified that significantly associated with soybean seed weight, and it was selected during the soybean domestication and improvement process. Soybean is a major oil crop for human beings and the seed weight is a crucial goal of soybean breeding. However, only a limited number of target genes underlying the quantitative trait loci (QTLs) controlling seed weight in soybean are known so far. In the present study, six loci associated with hundred-seed weight (HSW) were detected in the first population of 573 soybean breeding lines by genome-wide association study (GWAS), and 64 gene models were predicted in these candidate QTL regions. The QTL qHSW_1 exhibits continuous association signals on chromosome four and was also validated by region association study (RAS) in the second soybean population (409 accessions) with wild, landrace, and cultivar soybean accessions. There were seven genes in qHSW_1 candidate region by linkage disequilibrium (LD) block analysis, and only Glyma.04G035500 (GmCYP82C4) showed specifically higher expression in flowers, pods, and seeds, indicating its crucial role in the soybean seed development. Significant differences in HSW trait were detected when the association panels are genotyped by single-nucleotide polymorphisms (SNPs) in putative GmCYP82C4 promoter region. Eight haplotypes were generated by six SNPs in GmCYP82C4 in the second soybean population, and two superior haplotypes (Hap2 and Hap4) of GmCYP82C4 were detected with average HSW of 18.27 g and 18.38 g, respectively. The genetic diversity of GmCYP82C4 was analyzed in the second soybean population, and GmCYP82C4 was most likely selected during the soybean domestication and improvement process, leading to the highest proportion of Hap2 of GmCYP82C4 both in landrace and cultivar subpopulations. The QTLs and GmCYP82C4 identified in this study provide novel genetic resources for soybean seed weight trait, and the GmCYP82C4 could be used for soybean molecular breeding to develop desirable seed weight in the future.

Regulation of seed traits in soybean

Soybean (Glycine max) is an essential economic crop that provides vegetative oil and protein for humans, worldwide. Increasing soybean yield as well as improving seed quality is of great importance. Seed weight/size, oil and protein content are the three major traits determining seed quality, and seed weight also influences soybean yield. In recent years, the availability of soybean omics data and the development of related techniques have paved the way for better research on soybean functional genomics, providing a comprehensive understanding of gene functions. This review summarizes the regulatory genes that influence seed size/weight, oil content and protein content in soybean. We also provided a general overview of the pleiotropic effect for the genes in controlling seed traits and environmental stresses. Ultimately, it is expected that this review will be beneficial in breeding improved traits in soybean.

ZjWRKY23 and ZjWRKY40 Promote Fruit Size Enlargement by Targeting and Downregulating Cytokinin Oxidase/Dehydrogenase 5 Expression in Chinese Jujube

Fruit size is crucial for fruit trees, as it contributes to both quality and yield. However, the underlying mechanism of fruit size regulation remains largely unknown. Taking advantage of using a fruit double-sized bud mutant of Chinese jujube, "Jinkuiwang" and its wild type, "Jinsixiaozao", we carried out a comprehensive study on the mechanism of fruit size development in jujube. Using weighted gene coexpression network analyses, a number of candidate regulators for fruit size including those involved in hormonal signaling pathways, transcription factors, and heat shock proteins were identified. A hub gene named cytokinin oxidase/dehydrogenase 5 (ZjCKX5), responsible for cytokinin degradation, was found to play a negative role in regulating fruit size development, and overexpressing ZjCKX5 in tomato and Arabidopsis resulted in much smaller fruits and dwarf plants. Furthermore, another two hub genes, ZjWRKY23 and ZjWRKY40 transcription factors, were found to participate in fruit size regulation by targeting and downregulating the ZjCKX5 expression. Overexpressing ZjWRKY23 or ZjWRKY40 in tomato led to much larger fruits and promoted plant architecture. Based on these results, a molecular framework for jujube fruit size regulation, namely, ZjWRKY-ZjCKX5 module, was proposed. This study provides a new insight into the molecular networks underlying fruit size regulation.

Genome-wide association study and RNA-seq identifies GmWRI1-like transcription factor related to the seed weight in soybean

The cultivated soybean (Glycine max (L.) Merrill) is domesticated from wild soybean (Glycine soja) and has heavier seeds with a higher oil content than the wild soybean. In this study, we identified a novel candidate gene associated with SW using a genome-wide association study (GWAS). The candidate gene GmWRI14-like was detected by GWAS analysis in three consecutive years. By constructing transgenic soybeans overexpressing the GmWRI14-like gene and gmwri14-like soybean mutants, we found that overexpression of GmWRI14-like increased the SW and increased total fatty acid content. We then used RNA-seq and qRT-PCR to identify the target genes directly or indirectly regulated by GmWRI14-like. Transgenic soyabeans overexpressing GmWRI14-like showed increased accumulation of GmCYP78A50 and GmCYP78A69 than non-transgenic soybean lines. Interestingly, we also found that GmWRI14-like proteins could interact with GmCYP78A69/GmCYP78A50 using yeast two-hybrid and bimolecular fluorescence complementation. Our results not only shed light on the genetic architecture of cultivated soybean SW, but also lays a theoretical foundation for improving the SW and oil content of soybeans.

Molecular, genetic, and genomic basis of seed size and yield characteristics in soybean

Soybean (Glycine max L. Merr.) is a crucial oilseed cash crop grown worldwide and consumed as oil, protein, and food by humans and feed by animals. Comparatively, soybean seed yield is lower than cereal crops, such as maize, rice, and wheat, and the demand for soybean production does not keep up with the increasing consumption level. Therefore, increasing soybean yield per unit area is the most crucial breeding objective and is challenging for the scientific community. Moreover, yield and associated traits are extensively researched in cereal crops, but little is known about soybeans' genetics, genomics, and molecular regulation of yield traits. Soybean seed yield is a complex quantitative trait governed by multiple genes. Understanding the genetic and molecular processes governing closely related attributes to seed yield is crucial to increasing soybean yield. Advances in sequencing technologies have made it possible to conduct functional genomic research to understand yield traits' genetic and molecular underpinnings. Here, we provide an overview of recent progress in the genetic regulation of seed size in soybean, molecular, genetics, and genomic bases of yield, and related key seed yield traits. In addition, phytohormones, such as auxin, gibberellins, cytokinins, and abscisic acid, regulate seed size and yield. Hence, we also highlight the implications of these factors, challenges in soybean yield, and seed trait improvement. The information reviewed in this study will help expand the knowledge base and may provide the way forward for developing high-yielding soybean cultivars for future food demands.

Identification of genes associated with abiotic stress tolerance in sweetpotato using weighted gene co-expression network analysis

Sweetpotato, Ipomoea batatas (L.), a key food security crop, is negatively impacted by heat, drought, and salinity stress. The orange-fleshed sweetpotato cultivar "Beauregard" was exposed to heat, salt, and drought treatments for 24 and 48 h to identify genes responding to each stress condition in leaves. Analysis revealed both common (35 up regulated, 259 down regulated genes in the three stress conditions) and unique sets of up regulated (1337 genes by drought, 516 genes by heat, and 97 genes by salt stress) and down regulated (2445 genes by drought, 678 genes by heat, and 204 genes by salt stress) differentially expressed genes (DEGs) suggesting common, yet stress-specific transcriptional responses to these three abiotic stressors. Gene Ontology analysis of down regulated DEGs common to both heat and salt stress revealed enrichment of terms associated with "cell population proliferation" suggestive of an impact on the cell cycle by the two stress conditions. To identify shared and unique gene co-expression networks under multiple abiotic stress conditions, weighted gene co-expression network analysis was performed using gene expression profiles from heat, salt, and drought stress treated 'Beauregard' leaves yielding 18 co-expression modules. One module was enriched for "response to water deprivation," "response to abscisic acid," and "nitrate transport" indicating synergetic crosstalk between nitrogen, water, and phytohormones with genes encoding osmotin, cell expansion, and cell wall modification proteins present as key hub genes in this drought-associated module. This research lays the groundwork for exploring to a further degree, mechanisms for abiotic stress tolerance in sweetpotato.

Fine mapping of the major gene BhHLS1 controlling seed size in wax gourd (Benincasa hispida)

Introduction/Background

The seed size of wax gourds is an important agronomic trait; however, the associated genes have not yet been reported.

Methods

In this study, we used a high-density genetic map constructed based on F8 recombinant inbred line populations derived from a cross between MY-1 (large seed) and GX-71 (small seed) strains to detect quantitative trait locis (QTLs) for seed-size-related traits in wax gourd over a two-year period.

Results

Two stable QTLs (qSL10 and qSW10) for seed length (SL) and seed width (SW) on chromosome 10 were repeatedly detected over two years (2021-2022). qSL10 had a phenotypic variation rate of 75.30% and 80.80% in 2021 and 2022, respectively. Whereas, qSW10 had a phenotypic variation rate of 66.60% and 73.80% in 2021 and 2022, respectively. Further, a single nucleotide polymorphism mutation was found to cause early termination of Bch10G006400 (BhHLS1) translation in GX-71 through sequencing analysis of candidate genes. Based on gene functional annotation and quantitative real-time PCR analyses, BhHLS1 encoded a probable N-acetyltransferase HLS1-like protein and its expression level was significantly different between parents. Therefore, BhHLS1 is a major candidate gene associated with a one-factor polymorphism regulating the SL and SW of wax gourds. Finally, based on variation in the BhHLS1 sequence, a cleaved amplified polymorphic sequence marker was developed for the molecular marker-assisted breeding of wax gourds.

Discussion

Overall, this study is of great significance for the genetic improvement of seed size, verification of gene functions, and cultivation of specific germplasm resources for wax gourds.

WGCNA and transcriptome profiling reveal hub genes for key development stage seed size/oil content between wild and cultivated soybean

BACKGROUND

Soybean is one of the most important oil crops in the world. The domestication of wild soybean has resulted in significant changes in the seed oil content and seed size of cultivated soybeans. To better understand the molecular mechanisms of seed formation and oil content accumulation, WDD01514 (E1), ZYD00463 (E2), and two extreme progenies (E23 and E171) derived from RILs were used for weighted gene coexpression network analysis (WGCNA) combined with transcriptome analysis.

RESULTS

In this study, both seed weight and oil content in E1 and E171 were significantly higher than those in E2 and E23, and 20 DAF and 30 DAF may be key stages of soybean seed oil content accumulation and weight increase. Pathways such as "Photosynthesis", "Carbon metabolism", and "Fatty acid metabolism", were involved in oil content accumulation and grain formation between wild and cultivated soybeans at 20 and 30 DAF according to RNA-seq analysis. A total of 121 oil content accumulation and 189 seed formation candidate genes were screened from differentially expressed genes. WGCNA identified six modules related to seed oil content and seed weight, and 76 candidate genes were screened from modules and network. Among them, 16 genes were used for qRT-PCR and tissue specific expression pattern analysis, and their expression-levels in 33-wild and 23-cultivated soybean varieties were subjected to correlation analysis; some key genes were verified as likely to be involved in oil content accumulation and grain formation.

CONCLUSIONS

Overall, these results contribute to an understanding of seed lipid metabolism and seed size during seed development, and identify potential functional genes for improving soybean yield and seed oil quantity.

Transcriptome and WGCNA reveal hub genes in sugarcane tiller seedlings in response to drought stress

Drought stress can severely affect sugarcane growth and yield. The objective of this research was to identify candidate genes in sugarcane tillering seedlings in response to drought stress. We performed a comparative phenotypic, physiological and transcriptomic analysis of tiller seedlings of drought-stressed and well-watered "Guire 2" sugarcane, in a time-course experiment (5 days, 9 days and 15 days). Physiological examination reviewed that SOD, proline, soluble sugars, and soluble proteins accumulated in large amounts in tiller seedlings under different intensities of drought stress, while MDA levels remained at a stable level, indicating that the accumulation of osmoregulatory substances and the enhancement of antioxidant enzyme activities helped to limit further damage caused by drought stress. RNA-seq and weighted gene co-expression network analysis (WGCNA) were performed to identify genes and modules associated with sugarcane tillering seedlings in response to drought stress. Drought stress induced huge down-regulated in gene expression profiles, most of down-regulated genes were mainly associated with photosynthesis, sugar metabolism and fatty acid synthesis. We obtained four gene co-expression modules significantly associated with the physiological changes under drought stress (three modules positively correlated, one module negatively correlated), and found that LSG1-2, ERF1-2, SHKA, TIL, HSP18.1, HSP24.1, HSP16.1 and HSFA6A may play essential regulatory roles as hub genes in increasing SOD, Pro, soluble sugar or soluble protein contents. In addition, one module was found mostly involved in tiller stem diameter, among which members of the BHLH148 were important nodes. These results provide new insights into the mechanisms by which sugarcane tillering seedlings respond to drought stress.

Major genetic locus with pleiotropism determined seed-related traits in cultivated and wild soybeans

KEY MESSAGE

Here, a novel pleiotropic QTL qSS14 simultaneously regulating four seed size traits and two consistently detected QTLs qSW17 and qSLW02 were identified across multiple years. Seed-related traits were the key agronomic traits that have been artificially selected during the domestication of wild soybean. Identifying the genetic loci and genes that regulate seed size could clarify the genetic variations in seed-related traits and provide novel insights into high-yield soybean breeding. In this study, we used a high-density genetic map constructed by F₁₀ RIL populations from a cross between Glycine max and Glycine soja to detect additive QTLs for seven seed-related traits over the last three years. As a result, we identified one novel pleiotropic QTL, qSS14, that simultaneously controlled four seed size traits (100-seed weight, seed length, seed width, and seed thickness) and two consistently detected QTLs, qSW17, and qSLW02, in multiple years of phenotypic data. Furthermore, we predicted two, two and three candidate genes within these three critical loci based on the parental resequencing data and gene function annotations. And the relative expression of four candidate genes GLYMA_14G155100, GLYMA_17G061000, GLYMA_02G273100, and GLYMA_02G273300 showed significant differences among parents and the extreme materials through qRT-PCR analysis. These findings could facilitate the determination of beneficial genes in wild soybean and contribute to our understanding of the soybean domestication process.

Genetic regulatory networks of soybean seed size, oil and protein contents

As a leading oilseed crop that supplies plant oil and protein for daily human life, increasing yield and improving nutritional quality (high oil or protein) are the top two fundamental goals of soybean breeding. Seed size is one of the most critical factors determining soybean yield. Seed size, oil and protein contents are complex quantitative traits governed by genetic and environmental factors during seed development. The composition and quantity of seed storage reserves directly affect seed size. In general, oil and protein make up almost 60% of the total storage of soybean seed. Therefore, soybean's seed size, oil, or protein content are highly correlated agronomical traits. Increasing seed size helps increase soybean yield and probably improves seed quality. Similarly, rising oil and protein contents improves the soybean's nutritional quality and will likely increase soybean yield. Due to the importance of these three seed traits in soybean breeding, extensive studies have been conducted on their underlying quantitative trait locus (QTLs) or genes and the dissection of their molecular regulatory pathways. This review summarized the progress in functional genome controlling soybean seed size, oil and protein contents in recent decades, and presented the challenges and prospects for developing high-yield soybean cultivars with high oil or protein content. In the end, we hope this review will be helpful to the improvement of soybean yield and quality in the future breeding process.

M. S, Aski MS, Mishra GP, Sinha SK, Vijay D, C. T. MP, Das S, Pawar PAM, Mishra DC, Singh AK, Kumar A, Tripathi K, Kumar RR, Gupta S, Kumar S, Dikshit HK. Morpho-biochemical characterization of a RIL population for seed parameters and identification of candidate genes regulating seed size trait in lentil (Lens culinaris Medik.)

The seed size and shape in lentil (Lens culinaris Medik.) are important quality traits as these influences the milled grain yield, cooking time, and market class of the grains. Linkage analysis was done for seed size in a RIL (F_5:6) population derived by crossing L830 (20.9 g/1000 seeds) with L4602 (42.13 g/1000 seeds) which consisted of 188 lines (15.0 to 40.5 g/1000 seeds). Parental polymorphism survey using 394 SSRs identified 31 polymorphic primers, which were used for the bulked segregant analysis (BSA). Marker PBALC449 differentiated the parents and small seed size bulk only, whereas large seeded bulk or the individual plants constituting the large-seeded bulk could not be differentiated. Single plant analysis identified only six recombinant and 13 heterozygotes, of 93 small-seeded RILs (<24.0 g/1000 seed). This clearly showed that the small seed size trait is very strongly regulated by the locus near PBLAC449; whereas, large seed size trait seems governed by more than one locus. The PCR amplified products from the PBLAC449 marker (149bp from L4602 and 131bp from L830) were cloned, sequenced and BLAST searched using the lentil reference genome and was found amplified from chromosome 03. Afterward, the nearby region on chromosome 3 was searched, and a few candidate genes like ubiquitin carboxyl-terminal hydrolase, E3 ubiquitin ligase, TIFY-like protein, and hexosyltransferase having a role in seed size determination were identified. Validation study in another RIL mapping population which is differing for seed size, showed a number of SNPs and InDels among these genes when studied using whole genome resequencing (WGRS) approach. Biochemical parameters like cellulose, lignin, and xylose content showed no significant differences between parents and the extreme RILs, at maturity. Various seed morphological traits like area, length, width, compactness, volume, perimeter, etc., when measured using VideometerLab 4.0 showed significant differences for the parents and RILs. The results have ultimately helped in better understanding the region regulating the seed size trait in genomically less explored crops like lentils.

Weighted gene co-expression network analysis identifies genes related to HG Type 0 resistance and verification of hub gene GmHg1

INTRODUCTION

The soybean cyst nematode (SCN) is a major disease in soybean production thatseriously affects soybean yield. At present, there are no studies on weighted geneco-expression network analysis (WGCNA) related to SCN resistance.

METHODS

Here, transcriptome data from 36 soybean roots under SCN HG Type 0 (race 3) stresswere used in WGCNA to identify significant modules.

RESULTS AND DISCUSSION

A total of 10,000 differentially expressed genes and 21 modules were identified, of which the module most related to SCN was turquoise. In addition, the hub gene GmHg1 with high connectivity was selected, and its function was verified. GmHg1 encodes serine/threonine protein kinase (PK), and the expression of GmHg1 in SCN-resistant cultivars ('Dongnong L-204') and SCN-susceptible cultivars ('Heinong 37') increased significantly after HG Type 0 stress. Soybean plants transformed with GmHg1-OX had significantly increased SCN resistance. In contrast, the GmHg1-RNAi transgenic soybean plants significantly reduced SCN resistance. In transgenic materials, the expression patterns of 11 genes with the same expression trend as the GmHg1 gene in the 'turquoise module' were analyzed. Analysis showed that 11genes were co-expressed with GmHg1, which may be involved in the process of soybean resistance to SCN. Our work provides a new direction for studying the Molecular mechanism of soybean resistance to SCN.

Identification of quantitative trait loci (QTLs) and candidate genes for seed shape and 100-seed weight in soybean [Glycine max (L.) Merr.]

Seed size and shape are important traits determining yield and quality in soybean. Seed size and shape are also desirable for specialty soy foods like tofu, natto, miso, and edamame. In order to find stable quantitative trait loci (QTLs) and candidate genes for seed shape and 100-seed weight, the current study used vegetable type and seed soybean-derived F₂ and F_2:3 mapping populations. A total of 42 QTLs were mapped, which were dispersed across 13 chromosomes. Of these, seven were determined to be stable QTLs and five of them were major QTLs, namely qSL-10-1, qSW-4-1, qSV-4-1, qSLW-10-1, and qSLH-10-1. Thirteen of the 42 QTLs detected in the current study were found at known loci, while the remaining 29 were discovered for the first time. Out of these 29 novel QTLs, 17 were major QTLs. Based on Protein Analysis Through Evolutionary Relationships (PANTHER), gene annotation information, and literature search, 66 genes within seven stable QTLs were predicted to be possible candidate genes that might regulate seed shape and seed weight in soybean. The current study identified the key candidate genes and quantitative trait loci (QTLs) controlling soybean seed shape and weight, and these results will be very helpful in marker-assisted breeding for developing soybean varieties with improved seed weight and desired seed shape.

Regeneration pattern and genome-wide transcription profile of rhizome axillary buds after perennial rice harvest

Perennial rice is a new type of rice that allows the harvest of rice for multiple years without growing new seedlings annually. This technology represents a green and sustainable agricultural production mode with many advantages for balancing agricultural ecology and food security. However, the differences in regeneration patterns between perennial and annual rice and the gene regulatory pathways of the apical dominance in axillary bud growth after harvest in perennial rice are still unclear. In this study, perennial rice (PR23) and annual rice (Chugeng28) were used to investigate axillary bud growth patterns before and after apical spike removal. After elimination of apical dominance at different development stages, perennial rice rhizome axillary buds at the compression nodes germinated more rapidly than others and developed into new seedlings. The axillary buds at the high-position nodes in annual rice grew faster than those at other nodes. Furthermore, the global gene expression patterns of PR23 rhizome buds at compression nodes grown for 1, 3, 4, and 5 days after apical spike removal were analyzed by transcriptome sequencing. Compared with the control buds without apical removal, 264, 3,484, 2,095, and 3,398 genes were up-regulated, and 674, 3,484, 1,594, and 1,824 genes were down-regulated in the buds grown for 1, 3, 4, and 5 days after apical spike removal, respectively. Trend analysis of the expressed genes at different time points was performed and co-expression network was constructed to identify key genes in rhizome axillary bud regrowth. The results showed that 85 hub genes involved in 12 co-regulatory networks were mainly enriched in the light system, photosynthesis-antenna protein, plant hormone signal transduction, ABC transporter and metabolic pathways, which suggested that hormone and photosynthetic signals might play important roles in the regulation of rhizome axillary bud regeneration in perennial rice. Overall, this study clarified the differences in the regeneration patterns of axillary buds between perennial and annual rice and provided insight into the complex regulatory networks during the regeneration of rhizome axillary buds in perennial rice.

Whole-transcriptome profiles of Chrysanthemum seticuspe improve genome annotation and shed new light on mRNA-miRNA-lncRNA networks in ray florets and disc florets

BACKGROUND

Chrysanthemum seticuspe has emerged as a model plant species of cultivated chrysanthemums, especially for studies involving diploid and self-compatible pure lines (Gojo-0). Its genome was sequenced and assembled into chromosomes. However, the genome annotation of C. seticuspe still needs to be improved to elucidate the complex regulatory networks in this species.

RESULTS

In addition to the 74,259 mRNAs annotated in the C. seticuspe genome, we identified 18,265 novel mRNAs, 51,425 novel lncRNAs, 501 novel miRNAs and 22,065 novel siRNAs. Two C-class genes and YABBY family genes were highly expressed in disc florets, while B-class genes were highly expressed in ray florets. A WGCNA was performed to identify the hub lncRNAs and mRNAs in ray floret- and disc floret-specific modules, and CDM19, BBX22, HTH, HSP70 and several lncRNAs were identified. ceRNA and lncNAT networks related to flower development were also constructed, and we found a latent functional lncNAT-mRNA combination, LXLOC_026470 and MIF2.

CONCLUSIONS

The annotations of mRNAs, lncRNAs and small RNAs in the C. seticuspe genome have been improved. The expression profiles of flower development-related genes, ceRNA networks and lncNAT networks were identified, laying a foundation for elucidating the regulatory mechanisms underlying disc floret and ray floret formation.

Weighted gene co-expression network analysis reveals key module and hub genes associated with the anthocyanin biosynthesis in maize pericarp

Anthocyanins are the visual pigments that present most of the colors in plants. Its biosynthesis requires the coordinated expression of structural genes and regulatory genes. Pericarps are the rich sources of anthocyanins in maize seeds. In the experiment, the transcriptomes of transparent and anthocyanins-enriched pericarps at 15, 20, and 25 DAP were obtained. The results output 110.007 million raw reads and 51407 genes' expression matrix. Using data filtration in R language, 2057 genes were eventually identified for weighted gene co-expression network analysis. The results showed that 2057 genes were classified into ten modules. The cyan module containing 183 genes was confirmed to be the key module with the highest correlation value of 0.98 to the anthocyanins trait. Among 183 genes, seven structural genes were mapped the flavonoid biosynthesis pathway, and a transcription factor Lc gene was annotated as an anthocyanin regulatory gene. Cluster heatmap and gene network analysis further demonstrated that Naringenin, 2-oxoglutarate 3-dioxygenase (Zm00001d001960), Dihydroflavonol 4-reductase (Zm00001d044122), Leucoanthocyanidin dioxygenase (Zm00001d014914), anthocyanin regulatory Lc gene (Zm00001d026147), and Chalcone synthase C2 (Zm00001d052673) participated in the anthocyanins biosynthesis. And the transcription factor anthocyanin regulatory Lc gene Zm00001d026147 may act on the genes Chalcone synthase C2 (Zm00001d052673) and Dihydroflavonol 4-reductase (Zm00001d044122). The yeast one-hybrid assays confirmed that the Lc protein could combine with the promoter region of C2 and directly regulate the anthocyanin biosynthesis in the pericarp. These results may provide a new sight to uncover the module and hub genes related to anthocyanins biosynthesis in plants.

Identification and Investigation of the Genetic Variations and Candidate Genes Responsible for Seed Weight via GWAS in Paper Mulberry

Seeds directly determine the survival and population size of woody plants, but the genetic basis of seed weight in woody plants remain poorly explored. To identify genetic variations and candidate genes responsible for seed weight in natural woody populations, we investigated the hundred-seed weight of 198 paper mulberry individuals from different areas. Our results showed that the hundred-seed weight of paper mulberry was significantly associated with the bioclimatic variables of sampling sites, which increased from south to north along the latitudinal-temperature gradient. Using 2,414,978 high-quality SNPs from re-sequencing data, the genome-wide association analysis of the hundred-seed weight was performed under three models, which identified 148, 19 and 12 associated genes, respectively. Among them, 25 candidate genes were directly hit by the significant SNPs, including the WRKY transcription factor, fatty acid desaturase, F-box protein, etc. Most importantly, we identified three crucial genetic variations in the coding regions of candidate genes (Bp02g2123, Bp01g3291 and Bp10g1642), and significant differences in the hundred-seed weight were detected among the individuals carrying different genotypes. Further analysis revealed that Bp02g2123 encoding a fatty acid desaturase (FAD) might be a key factor affecting the seed weight and local climate adaptation of woody plants. Furthermore, the genome-wide investigation and expression analysis of FAD genes were performed, and the results suggested that BpFADs widely expressed in various tissues and responded to multiple phytohormone and stress treatments. Overall, our study identifies valuable genetic variations and candidate genes, and provides a better understanding of the genetic basis of seed weight in woody plants.

Natural allelic variation of GmST05 controlling seed size and quality in soybean

Seed size is one of the most important agronomic traits determining the yield of crops. Cloning the key genes controlling seed size and pyramiding their elite alleles will facilitate yield improvement. To date, few genes controlling seed size have been identified in soybean, a major crop that provides half of the plant oil and one quarter of the plant protein globally. Here, through a genome-wide association study of over 1800 soybean accessions, we determined that natural allelic variation at GmST05 (Seed Thickness 05) predominantly controlled seed thickness and size in soybean germplasm. Further analyses suggested that the two major haplotypes of GmST05 differed significantly at the transcriptional level. Transgenic experiments demonstrated that GmST05 positively regulated seed size and influenced oil and protein contents, possibly by regulating the transcription of GmSWEET10a. Population genetic diversity analysis suggested that allelic variations of GmST05 were selected during geographical differentiation but have not been fixed. In summary, natural variation in GmST05 determines transcription levels and influences seed size and quality in soybean, making it an important gene resource for soybean molecular breeding.

Dynamic transcriptome analysis suggests the key genes regulating seed development and filling in Tartary buckwheat (Fagopyrum tataricum Garetn.)

Tartary buckwheat is highly attractive for the richness of nutrients and quality, yet post-embryonic seed abortion greatly halts the yield. Seed development is crucial for determining grain yield, whereas the molecular basis and regulatory network of Tartary buckwheat seed development and filling is not well understood at present. Here, we assessed the transcriptional dynamics of filling stage Tartary buckwheat seeds at three developmental stages by RNA sequencing. Among the 4249 differentially expressed genes (DEGs), genes related to seed development were identified. Specifically, 88 phytohormone biosynthesis signaling genes, 309 TFs, and 16 expansin genes participating in cell enlargement, 37 structural genes involved in starch biosynthesis represented significant variation and were candidate key seed development genes. Cis-element enrichment analysis indicated that the promoters of differentially expressed expansin genes and starch biosynthesis genes are rich of hormone-responsive (ABA-, AUX-, ET-, and JA-), and seed growth-related (MYB, MYC and WRKY) binding sites. The expansin DEGs showed strong correlations with DEGs in phytohormone pathways and transcription factors (TFs). In total, phytohormone ABA, AUX, ET, BR and CTK, and related TFs could substantially regulate seed development in Tartary buckwheat through targeting downstream expansin genes and structural starch biosynthetic genes. This transcriptome data could provide a theoretical basis for improving yield of Tartary buckwheat.

T. MP, Das S, Pawar PAM, Kumar A, Tripathi K, Kumar RR, Yadava DK, Kumar S, Dikshit HK. Comparative transcriptome analysis, unfolding the pathways regulating the seed-size trait in cultivated lentil (Lens culinaris Medik.)

Market class, cooking time, quality, and milled grain yield are largely influenced by the seed size and shape of the lentil (Lens culinaris Medik.); thus, they are considered to be important quality traits. To unfold the pathways regulating seed size in lentils, a transcriptomic approach was performed using large-seeded (L4602) and small-seeded (L830) genotypes. The study has generated nearly 375 million high-quality reads, of which 98.70% were properly aligned to the reference genome. Among biological replicates, very high similarity in fragments per kilobase of exon per million mapped fragments values (R > 0.9) showed the consistency of RNA-seq results. Various differentially expressed genes associated mainly with the hormone signaling and cell division pathways, transcription factors, kinases, etc. were identified as having a role in cell expansion and seed growth. A total of 106,996 unigenes were used for differential expression (DE) analysis. String analysis identified various modules having certain key proteins like Ser/Thr protein kinase, seed storage protein, DNA-binding protein, microtubule-associated protein, etc. In addition, some growth and cell division–related micro-RNAs like miR3457 (cell wall formation), miR1440 (cell proliferation and cell cycles), and miR1533 (biosynthesis of plant hormones) were identified as having a role in seed size determination. Using RNA-seq data, 5254 EST-SSR primers were generated as a source for future studies aiming for the identification of linked markers. In silico validation using Genevestigator^® was done for the Ser/Thr protein kinase, ethylene response factor, and Myb transcription factor genes. It is of interest that the xyloglucan endotransglucosylase gene was found differentially regulated, suggesting their role during seed development; however, at maturity, no significant differences were recorded for various cell wall parameters including cellulose, lignin, and xylose content. This is the first report on lentils that has unfolded the key seed size regulating pathways and unveiled a theoretical way for the development of lentil genotypes having customized seed sizes.

Integrated transcriptome and hormonal analysis of naphthalene acetic acid-induced adventitious root formation of tea cuttings (Camellia sinensis)

BACKGROUND

Tea plant breeding or cultivation mainly involves propagation via cuttings, which not only ensures the inheritance of the excellent characteristics of the mother plant but also facilitates mechanized management. The formation of adventitious root (AR) determines the success of cutting-based propagation, and auxin is an essential factor involved in this process. To understand the molecular mechanism underlying AR formation in nodal tea cuttings, transcriptome and endogenous hormone analysis was performed on the stem bases of red (mature)- and green (immature)-stem cuttings of 'Echa 1 hao' tea plant as affected by a pulse treatment with naphthalene acetic acid (NAA).

RESULTS

In this study, NAA significantly promoted AR formation in both red- and green-stem cuttings but slightly reduced callus formation. External application of NAA reduced the levels of endogenous indole-3-acetic acid (IAA) and cytokinin (TZR, trans-zeatin riboside). The number of DEGs (NAA vs. CK) identified in the green-stem cuttings was significantly higher than that in the red-stem cuttings, which corresponded to a higher rooting rate of green-stem cuttings under the NAA treatment. A total of 82 common DEGs were identified as being hormone-related and involved in the auxin, cytokinin, abscisic acid, ethylene, salicylic acid, brassinosteroid, and jasmonic acid pathways. The negative regulation of NAA-induced IAA and GH3 genes may explain the decrease of endogenous IAA. NAA reduced endogenous cytokinin levels and further downregulated the expression of cytokinin signalling-related genes. By the use of weighted gene co-expression network analysis (WGCNA), several hub genes, including three [cellulose synthase (CSLD2), SHAVEN3-like 1 (SVL1), SMALL AUXIN UP RNA (SAUR21)] that are highly related to root development in other crops, were identified that might play important roles in AR formation in tea cuttings.

CONCLUSIONS

NAA promotes the formation of AR of tea cuttings in coordination with endogenous hormones. The most important endogenous AR inductor, IAA, was reduced in response to NAA. DEGs potentially involved in NAA-mediated AR formation of tea plant stem cuttings were identified via comparative transcriptome analysis. Several hub genes, such as CSLD2, SVL1 and SAUR21, were identified that might play important roles in AR formation in tea cuttings.

Weighted Gene Correlation Network Analysis (WGCNA) of Arabidopsis Somatic Embryogenesis (SE) and Identification of Key Gene Modules to Uncover SE-Associated Hub Genes

Somatic embryogenesis (SE), which occurs naturally in many plant species, serves as a model to elucidate cellular and molecular mechanisms of embryo patterning in plants. Decoding the regulatory landscape of SE is essential for its further application. Hence, the present study was aimed at employing Weighted Gene Correlation Network Analysis (WGCNA) to construct a gene coexpression network (GCN) for Arabidopsis SE and then identifying highly correlated gene modules to uncover the hub genes associated with SE that may serve as potential molecular targets. A total of 17,059 genes were filtered from a microarray dataset comprising four stages of SE, i.e., stage I (zygotic embryos), stage II (proliferating tissues at 7 days of induction), stage III (proliferating tissues at 14 days of induction), and stage IV (mature somatic embryos). This included 1,711 transcription factors and 445 EMBRYO DEFECTIVE genes. GCN analysis identified a total of 26 gene modules with the module size ranging from 35 to 3,418 genes using a dynamic cut tree algorithm. The module-trait analysis revealed that four, four, seven, and four modules were associated with stages I, II, III, and IV, respectively. Further, we identified a total of 260 hub genes based on the degree of intramodular connectivity. Validation of the hub genes using publicly available expression datasets demonstrated that at least 78 hub genes are potentially associated with embryogenesis; of these, many genes remain functionally uncharacterized thus far. In silico promoter analysis of these genes revealed the presence of cis-acting regulatory elements, "soybean embryo factor 4 (SEF4) binding site," and "E-box" of the napA storage-protein gene of Brassica napus; this suggests that these genes may play important roles in plant embryo development. The present study successfully applied WGCNA to construct a GCN for SE in Arabidopsis and identified hub genes involved in the development of somatic embryos. These hub genes could be used as molecular targets to further elucidate the molecular mechanisms underlying SE in plants.

Identification of closely associated SNPs and candidate genes with seed size and shape via deep re-sequencing GWAS in soybean

KEY MESSAGE

A soybean natural population was genotyped by deep re-sequencing and phenotyped for six seed size- and shape-related traits under six environments to identify closely associated SNPs and candidate genes. Seed size and shape are important determining factors for soybean yield formation, while their genetic basis and molecular mechanism are still largely unknown, which seriously constrains the increasing of soybean yield at present. In view of this, a natural population was genotyped via the deep re-sequencing technique (~ 20 ×) and phenotyped for six related traits under six environments. In total, 154 SNPs were closely associated with seed length across diverse environments, and 323, 483, 565, 394 and 2038 SNPs were closely associated with seed width, seed diameter, seed circumference, seed area and ratio of length to width under multiple environments. Moreover, 98.70%, 96.28%, 48.24%, 85.13%, 97.21% and 98.58% of them were further demonstrated by the BLUP and mean values of the related traits. Furthermore, 218 genes flanking the associated SNPs on chromosomes 6 and 10 were analyzed for DNA mutations and RNA expressions through SNP alleles and transcriptome data, simultaneously. The candidate genes, Glyma.10G035200 (Sn1-specific diacylglycerol lipase), Glyma.10G035400 (transcription factor) and Glyma.10G058200 (phenylalanine ammonia-lyase), were discovered to relate with the seed size and shape for their different DNA sequences or differential RNA expressions among soybean varieties at five seed developmental stages. Thus, these closely associated SNPs and related genes provide novel insights and useful information for the seed size and shape genetic basis dissection and breeding improvement in soybean.

Gene Co-Expression Network Tools and Databases for Crop Improvement

Transcriptomics has significantly grown as a functional genomics tool for understanding the expression of biological systems. The generated transcriptomics data can be utilised to produce a gene co-expression network that is one of the essential downstream omics data analyses. To date, several gene co-expression network databases that store correlation values, expression profiles, gene names and gene descriptions have been developed. Although these resources remain scattered across the Internet, such databases complement each other and support efficient growth in the functional genomics area. This review presents the features and the most recent gene co-expression network databases in crops and summarises the present status of the tools that are widely used for constructing the gene co-expression network. The highlights of gene co-expression network databases and the tools presented here will pave the way for a robust interpretation of biologically relevant information. With this effort, the researcher would be able to explore and utilise gene co-expression network databases for crops improvement.

The Organ Size and Morphological Change During the Domestication Process of Soybean

Soybean is one of the most important legume crops that can provide the rich source of protein and oil for human beings and livestock. In the twenty-one century, the total production of soybean is seriously behind the needs of a growing world population. Cultivated soybean [Glycine max (L.) Merr.] was domesticated from wild soybean (G. soja Sieb. and Zucc.) with the significant morphology and organ size changes in China around 5,000 years ago, including twisted stems to erect stems, small seeds to large seeds. Then it was spread worldwide to become one of the most popular and important crops. The release of the reference soybean genome and omics data provides powerful tools for researchers and breeders to dissect the functional genes and apply the germplasm in their work. Here, we summarized the function genes related to yield traits and organ size in soybean, including stem growth habit, leaf size and shape, seed size and weight. In addition, we also summarized the selection of organ traits during soybean domestication. In the end, we also discussed the application of new technology including the gene editing on the basic research and breeding of soybean, and the challenges and research hotspots in the future.

Machine-Learning-Based Genome-Wide Association Studies for Uncovering QTL Underlying Soybean Yield and Its Components

A genome-wide association study (GWAS) is currently one of the most recommended approaches for discovering marker-trait associations (MTAs) for complex traits in plant species. Insufficient statistical power is a limiting factor, especially in narrow genetic basis species, that conventional GWAS methods are suffering from. Using sophisticated mathematical methods such as machine learning (ML) algorithms may address this issue and advance the implication of this valuable genetic method in applied plant-breeding programs. In this study, we evaluated the potential use of two ML algorithms, support-vector machine (SVR) and random forest (RF), in a GWAS and compared them with two conventional methods of mixed linear models (MLM) and fixed and random model circulating probability unification (FarmCPU), for identifying MTAs for soybean-yield components. In this study, important soybean-yield component traits, including the number of reproductive nodes (RNP), non-reproductive nodes (NRNP), total nodes (NP), and total pods (PP) per plant along with yield and maturity, were assessed using a panel of 227 soybean genotypes evaluated at two locations over two years (four environments). Using the SVR-mediated GWAS method, we were able to discover MTAs colocalized with previously reported quantitative trait loci (QTL) with potential causal effects on the target traits, supported by the functional annotation of candidate gene analyses. This study demonstrated the potential benefit of using sophisticated mathematical approaches, such as SVR, in a GWAS to complement conventional GWAS methods for identifying MTAs that can improve the efficiency of genomic-based soybean-breeding programs.

Transcriptomic Analysis Reveals the Regulatory Networks and Hub Genes Controlling the Unsaturated Fatty Acid Contents of Developing Seed in Soybean

Soybean [Glycine max (L.) Merr.] is one of the most important crops, which produces about 25% of the world's edible oil. The nutritional value of soybean oil depends mostly on the relative contents of three unsaturated fatty acids (UFAs), i.e., oleic acid, linoleic acid (LA), and linolenic acid. However, the biosynthetic mechanism of UFAs remains largely unknown, and there are few studies on RNA-seq analysis of developing seeds. To identify the candidate genes and related pathways involved in the regulation of UFA contents during seed development in soybean, two soybean lines with different UFA profiles were selected from 314 cultivars and landraces originated from Southern China, and RNA-seq analysis was performed in soybean seeds at three developmental stages. Using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis, a series of genes and pathways related to fatty acid metabolism were identified, and 40 days after flowering (DAF) was found to be the crucial period in the formation of UFA profiles. Further, weighted gene co-expression network analysis identified three modules with six genes whose functions were highly associated with the contents of oleic and LA. The detailed functional investigation of the networks and hub genes could further improve the understanding of the underlying molecular mechanism of UFA contents and might provide some ideas for the improvement in fatty acids profiles in soybean.

Transcriptome analysis of pod mutant reveals plant hormones are important regulators in controlling pod size in peanut (Arachis hypogaea L.)

Pod size is an important yield-influencing trait in peanuts. It is affected by plant hormones and identifying the genes related to these hormones may contribute to pod-related trait improvements in peanut breeding programs. However, there is limited information on the molecular mechanisms of plant hormones that regulate pod size in peanuts. We identified a mutant with an extremely small pod (spm) from Yuanza 9102 (WT) by ⁶⁰Co γ-radiation mutagenesis. The length and width of the natural mature pod in spm were only 71.34% and 73.36% of those in WT, respectively. We performed comparative analyses for morphological characteristics, anatomy, physiology, and global transcriptome between spm and WT pods. Samples were collected at 10, 20, and 30 days after peg elongation into the soil, representing stages S1, S2, and S3, respectively. The differences in pod size between WT and spm were seen at stage S1 and became even more striking at stages S2 and S3. The cell sizes of the pods were significantly smaller in spm than in WT at stages S1, S2, and S3. These results suggested that reduced cell size may be one of the important contributors for the small pod in spm. The contents of indole-3-acetic acid (IAA), gibberellin (GA), and brassinosteroid (BR) were also significantly lower in spm pods than those in WT pods at all three stages. RNA-Seq analyses showed that 1,373, 8,053, and 3,358 differently expressed genes (DEGs) were identified at stages S1, S2, and S3, respectively. Functional analyses revealed that a set of DEGs was related to plant hormone biosynthesis, plant hormone signal transduction pathway, and cell wall biosynthesis and metabolism. Furthermore, several hub genes associated with plant hormone biosynthesis and signal transduction pathways were identified through weighted gene co-expression network analysis. Our results revealed that IAA, GA, and BR may be important regulators in controlling pod size by regulating cell size in peanuts. This study provides helpful information for the understanding of the complex mechanisms of plant hormones in controlling pod size by regulating the cell size in peanuts and will facilitate the improvement of peanut breeding.

Comparative Analysis of Seed Transcriptome and Coexpression Analysis Reveal Candidate Genes for Enhancing Seed Size/Weight in Brassica juncea

Seed size/weight is a multigenic trait that is governed by complex transcriptional regulatory pathways. An understanding of the genetic basis of seed size is of great interest in the improvement of seed yield and quality in oilseed crops. A global transcriptome analysis was performed at the initial stages of seed development in two lines of Brassica juncea, small-seeded EH-2 and large-seeded PJ. The anatomical analyses revealed significant differences in cell number and cell size in the outer layer of the seed coat between EH-2 and PJ. Pairwise comparisons at each developmental stage identified 5,974 differentially expressed genes (DEGs) between the two lines, of which 954 genes belong to different families of transcription factors. Two modules were found to be significantly correlated with an increased seed size using weighted gene coexpression network analysis. The DEG and coexpression datasets were integrated with the thousand seed weight (Tsw) quantitative trait loci (QTL) mapped earlier in the EPJ (EH-2 × PJ) doubled haploid (DH) population, which identified forty potential key components controlling seed size. The candidate genes included genes regulating the cell cycle, cell wall biogenesis/modification, solute/sugar transport, and hormone signaling. The results provide a valuable resource to widen the current understanding of regulatory mechanisms underlying seed size in B. juncea.

Transcriptome and Coexpression Network Analyses Provide In-Sights into the Molecular Mechanisms of Hydrogen Cyanide Synthesis during Seed Development in Common Vetch (Vicia sativa L.)

The common vetch (Vicia sativa L.) seed is an ideal plant-based protein food for humans, but its edible value is mainly limited by the presence of cyanogenic glycosides that hydrolyze to produce toxic hydrogen cyanide (HCN), and the genes that regulate HCN synthesis in common vetch are unknown. In this study, seeds from common vetch at 5, 10, 15, 20, 25, 30, and 35 days after anthesis were sampled, and the seven stages were further divided into five developmental stages, S1, S2, S3, S4, and S5, based on morphological and transcriptome analyses. A total of 16,403 differentially expressed genes were identified in the five developmental stages. The HCN contents of seeds in these five stages were determined by alkaline titration, and weighted gene coexpression network analysis was used to explain the molecular regulatory mechanism of HCN synthesis in common vetch seeds. Eighteen key regulatory genes for HCN synthesis were identified, including the VsGT2, VsGT17 and CYP71A genes, as well as the VsGT1 gene family. VsGT1, VsGT2, VsGT17 and CYP71A jointly promoted HCN synthesis, from 5 to 25 days after anthesis, with VsGT1-1, VsGT1-4, VsGT1-11 and VsGT1-14 playing major roles. The HCN synthesis was mainly regulated by VsGT1, from 25 to 35 days after anthesis. As the expression level of VsGT1 decreased, the HCN content no longer increased. In-depth elucidation of seed HCN synthesis lays the foundations for breeding common vetch with low HCN content.

Progress in soybean functional genomics over the past decade

Soybean is one of the most important oilseed and fodder crops. Benefiting from the efforts of soybean breeders and the development of breeding technology, large number of germplasm has been generated over the last 100 years. Nevertheless, soybean breeding needs to be accelerated to meet the needs of a growing world population, to promote sustainable agriculture and to address future environmental changes. The acceleration is highly reliant on the discoveries in gene functional studies. The release of the reference soybean genome in 2010 has significantly facilitated the advance in soybean functional genomics. Here, we review the research progress in soybean omics (genomics, transcriptomics, epigenomics and proteomics), germplasm development (germplasm resources and databases), gene discovery (genes that are responsible for important soybean traits including yield, flowering and maturity, seed quality, stress resistance, nodulation and domestication) and transformation technology during the past decade. At the end, we also briefly discuss current challenges and future directions.

A ten-genes-based diagnostic signature for atherosclerosis

BACKGROUND

Atherosclerosis is the leading cause of cardiovascular disease with a high mortality worldwide. Understanding the atherosclerosis pathogenesis and identification of efficient diagnostic signatures remain major problems of modern medicine. This study aims to screen the potential diagnostic genes for atherosclerosis.

METHODS

We downloaded the gene chip data of 135 peripheral blood samples, including 57 samples with atherosclerosis and 78 healthy subjects from GEO database (Accession Number: GSE20129). The weighted gene co-expression network analysis was applied to identify atherosclerosis-related genes. Functional enrichment analysis was conducted by using the clusterProfiler R package. The interaction pairs of proteins encoded by atherosclerosis-related genes were screened using STRING database, and the interaction network was further optimized with the cytoHubba plug-in of Cytoscape software.

RESULTS

The logistic regression diagnostic model was constructed to predict normal and atherosclerosis samples. A gene module which included 532 genes related to the occurrence of atherosclerosis were screened. Functional enrichment analysis basing on the 532 genes identified 235 significantly enriched GO terms and 44 significantly enriched KEGG pathways. The top 50 hub genes of the protein-protein interaction network were identified. The final logistic regression diagnostic model was established by the optimal 10 key genes, which could distinguish atherosclerosis samples from normal samples.

CONCLUSIONS

A predictive model based on 10 potential atherosclerosis-related genes was obtained, which should shed light on the diagnostic research of atherosclerosis.

Analysis of Shared Genetic Regulatory Networks for Alzheimer's Disease and Epilepsy

Alzheimer's disease (AD) and epilepsy are neurological disorders that affect a large cohort of people worldwide. Although both of the two diseases could be influenced by genetic factors, the shared genetic mechanism underlying the pathogenesis of them is still unclear. In this study, we aimed to identify the shared genetic networks and corresponding hub genes for AD and epilepsy. Firstly, the gene coexpression modules (GCMs) were constructed by weighted gene coexpression network analysis (WGCNA), and 16 GCMs were identified. Through further integration of GCMs, genome-wide association studies (GWASs), and expression quantitative trait loci (eQTLs), 4 shared GCMs of AD and epilepsy were identified. Functional enrichment analysis was performed to analyze the shared biological processes of these GCMs and explore the functional overlaps between these two diseases. The results showed that the genes in shared GCMs were significantly enriched in nervous system-related pathways, such as Alzheimer's disease and neuroactive ligand-receptor interaction pathways. Furthermore, the hub genes of AD- and epilepsy-associated GCMs were captured by weighted key driver analysis (wKDA), including TRPC1, C2ORF40, NR3C1, KIAA0368, MMT00043109, STEAP1, MSX1, KL, and CLIC6. The shared GCMs and hub genes might provide novel therapeutic targets for AD and epilepsy.

Genome-Wide Association Study to Map Genomic Regions Related to the Initiation Time of Four Growth Stage Traits in Soybean

The time to flowering (DF), pod beginning (DPB), seed formation (DSF), and maturity initiation (DMI) in soybean (Glycine max [L.] Merr) are important characteristics of growth stage traits (GSTs) in Chinese summer-sowing soybean, and are influenced by genetic as well as environmental factors. To better understand the molecular mechanism underlying the initiation times of GSTs, we investigated four GSTs of 309 diverse soybean accessions in six different environments and Best Linear Unbiased Prediction values. Furthermore, the genome-wide association study was conducted by a Fixed and random model Circulating Probability Unification method using over 60,000 single nucleotide polymorphism (SNP) markers to identify the significant quantitative trait nucleotide (QTN) regions with phenotypic data. As a result, 212 SNPs within 102 QTN regions were associated with four GSTs. Of which, eight stable regions were repeatedly detected in least three datasets for one GST. Interestingly, half of the QTN regions overlapped with previously reported quantitative trait loci or well-known soybean growth period genes. The hotspots associated with all GSTs were concentrated on chromosome 10. E2 (Glyma10g36600), a gene with a known function in regulating flowering and maturity in soybean, is also found on this chromosome. Thus, this genomic region may account for the strong correlation among the four GSTs. All the significant SNPs in the remaining 7 QTN regions could cause the significant phenotypic variation with both the major and minor alleles. Two hundred and seventy-five genes in soybean and their homologs in Arabidopsis were screened within ± 500 kb of 7 peak SNPs in the corresponding QTN regions. Most of the genes are involved in flowering, response to auxin stimulus, or regulation of seed germination, among others. The findings reported here provide an insight for genetic improvement which will aid in breeding of soybean cultivars that can be adapted to the various summer sowing areas in China and beyond.

Transcriptome and Coexpression Network Analyses Reveal Hub Genes in Chinese Cabbage (Brassica rapa L. ssp. pekinensis) During Different Stages of Plasmodiophora brassicae Infection

Clubroot, caused by the soil-borne protist Plasmodiophora brassicae, is one of the most destructive diseases of Chinese cabbage worldwide. However, the clubroot resistance mechanisms remain unclear. In this study, in both clubroot-resistant (DH40R) and clubroot-susceptible (DH199S) Chinese cabbage lines, the primary (root hair infection) and secondary (cortical infection) infection stages started 2 and 5 days after inoculation (dai), respectively. With the extension of the infection time, cortical infection was blocked and complete P. brassica resistance was observed in DH40R, while disease scales of 1, 2, and 3 were observed at 8, 13, and 22 dai in DH199S. Transcriptome analysis at 0, 2, 5, 8, 13, and 22 dai identified 5,750 relative DEGs (rDEGs) between DH40R and DH199S. The results indicated that genes associated with auxin, PR, disease resistance proteins, oxidative stress, and WRKY and MYB transcription factors were involved in clubroot resistance regulation. In addition, weighted gene coexpression network analysis (WGCNA) identified three of the modules whose functions were highly associated with clubroot-resistant, including ten hub genes related to clubroot resistance (ARF2, EDR1, LOX4, NHL3, NHL13, NAC29, two AOP1, EARLI 1, and POD56). These results provide valuable information for better understanding the molecular regulatory mechanism of Chinese cabbage clubroot resistance.

Transcriptome profiling reveals the spatial-temporal dynamics of gene expression essential for soybean seed development

BACKGROUND

Seeds are the economic basis of oilseed crops, especially soybeans, the most widely cultivated oilseed crop worldwide. Seed development is accompanied by a multitude of diverse cellular processes, and revealing the underlying regulatory activities is critical for seed improvement.

RESULTS

In this study, we profiled the transcriptomes of developing seeds at 20, 25, 30, and 40 days after flowering (DAF), as these stages represent critical time points of seed development from early to full development. We identified a set of highly abundant genes and highlighted the importance of these genes in supporting nutrient accumulation and transcriptional regulation for seed development. We identified 8925 differentially expressed genes (DEGs) that exhibited temporal expression patterns over the course and expression specificities in distinct tissues, including seeds and nonseed tissues (roots, stems, and leaves). Genes specific to nonseed tissues might have tissue-associated roles, with relatively low transcript abundance in developing seeds, suggesting their spatially supportive roles in seed development. Coexpression network analysis identified several underexplored genes in soybeans that bridge tissue-specific gene modules.

CONCLUSIONS

Our study provides a global view of gene activities and biological processes critical for seed formation in soybeans and prioritizes a set of genes for further study. The results of this study help to elucidate the mechanism controlling seed development and storage reserves.

Machine learning analysis of gene expression profile reveals a novel diagnostic signature for osteoporosis

Background

Osteoporosis (OP) is increasingly prevalent with the aging of the world population. It is urgent to identify efficient diagnostic signatures for the clinical application.

Method

We downloaded the mRNA profile of 90 peripheral blood samples with or without OP from GEO database (Number: GSE152073). Weighted gene co-expression network analysis (WGCNA) was used to reveal the correlation among genes in all samples. GO term and KEGG pathway enrichment analysis was performed via the clusterProfiler R package. STRING database was applied to screen the interaction pairs among proteins. Protein–protein interaction (PPI) network was visualized based on Cytoscape, and the key genes were screened using the cytoHubba plug-in. The diagnostic model based on these key genes was constructed, and 5-fold cross validation method was applied to evaluate its reliability.

Results

A gene module consisted of 176 genes predicted to be associated with the occurrence of OP was identified. A total of 16 significantly enriched GO terms and 1 significantly enriched KEGG pathway were obtained based on the 176 genes. The top 50 key genes in the PPI network were identified. Then 22 genes were screened based on stepwise regression analysis from the 50 key genes. Of which, 9 genes were further screened out by multivariate regression analysis with the significant threshold of P value < 0.01. The diagnostic model was established based on the optimal 9 key genes, which efficiently separated the normal samples and OP samples.

Conclusion

A diagnostic model established based on nine key genes could reliably separate OP patients from healthy subjects, which provided novel lightings on the diagnostic research of OP.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13018-021-02329-1.

A four-genes based diagnostic signature for osteoarthritis

Osteoarthritis (OA) is a primary leading cause of pain and disability. However, some cases are diagnosed at the later stage which delayed the timely treatment. This study aims to identify effective diagnostic signature for OA. The mRNA profile GSE48566 including 106 blood samples of OA patients and 33 blood samples of healthy individuals was downloaded from Gene Expression Omnibus (GEO) database. The potential OA-related genes were screened by weighted gene co-expression network analysis (WGCNA). Gene ontology (GO) term and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed to reveal the functions or pathways of OA-related genes using the clusterProfiler function package of R software. Key genes significantly involved in OA progression were further screened by protein-protein interaction (PPI) network. The logistic regression model and the random forest model were conducted by bringing into optimal genes selected by stepwise regression analysis, and fivefold cross validation method was used to determine their reliability. A total of 146 genes, existed in three modules and might be associated with the occurrence of OA, were screened. 15 genes were screened from the PPI network and four genes, including CCR6, CLEC7A, IL18 and SRSF2, were further optimized. Finally, a logistic regression model and a random forest model were conducted by bringing into four optimal genes, and could reliably separate OA patients from healthy subjects. Our study established two effective diagnostic models based on CCR6, CLEC7A, IL18 and SRSF2, which could reliably separate OA patients from healthy subjects.

De novo transcriptome in roots of switchgrass (Panicum virgatum L.) reveals gene expression dynamic and act network under alkaline salt stress

Background

Soil salinization is a major limiting factor for crop cultivation. Switchgrass is a perennial rhizomatous bunchgrass that is considered an ideal plant for marginal lands, including sites with saline soil. Here we investigated the physiological responses and transcriptome changes in the roots of Alamo (alkaline-tolerant genotype) and AM-314/MS-155 (alkaline-sensitive genotype) under alkaline salt stress.

Results

Alkaline salt stress significantly affected the membrane, osmotic adjustment and antioxidant systems in switchgrass roots, and the ASTTI values between Alamo and AM-314/MS-155 were divergent at different time points. A total of 108,319 unigenes were obtained after reassembly, including 73,636 unigenes in AM-314/MS-155 and 65,492 unigenes in Alamo. A total of 10,219 DEGs were identified, and the number of upregulated genes in Alamo was much greater than that in AM-314/MS-155 in both the early and late stages of alkaline salt stress. The DEGs in AM-314/MS-155 were mainly concentrated in the early stage, while Alamo showed greater advantages in the late stage. These DEGs were mainly enriched in plant-pathogen interactions, ubiquitin-mediated proteolysis and glycolysis/gluconeogenesis pathways. We characterized 1480 TF genes into 64 TF families, and the most abundant TF family was the C2H2 family, followed by the bZIP and bHLH families. A total of 1718 PKs were predicted, including CaMK, CDPK, MAPK and RLK. WGCNA revealed that the DEGs in the blue, brown, dark magenta and light steel blue 1 modules were associated with the physiological changes in roots of switchgrass under alkaline salt stress. The consistency between the qRT-PCR and RNA-Seq results confirmed the reliability of the RNA-seq sequencing data. A molecular regulatory network of the switchgrass response to alkaline salt stress was preliminarily constructed on the basis of transcriptional regulation and functional genes.

Conclusions

Alkaline salt tolerance of switchgrass may be achieved by the regulation of ion homeostasis, transport proteins, detoxification, heat shock proteins, dehydration and sugar metabolism. These findings provide a comprehensive analysis of gene expression dynamic and act network induced by alkaline salt stress in two switchgrass genotypes and contribute to the understanding of the alkaline salt tolerance mechanism of switchgrass and the improvement of switchgrass germplasm.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-07368-w.

Transcriptome Analysis and RNA Interference Reveal GhGDH2 Regulating Cotton Resistance to Verticillium Wilt by JA and SA Signaling Pathways

Verticillium wilt, caused by Verticillium dahliae, is one of the most damaging and widespread soil-borne cotton diseases. The molecular mechanisms underlying the cotton defense against V. dahliae remain largely elusive. Here, we compared the transcriptional differences between Upland cotton cultivars: one highly resistant (HR; Shidalukang 1) and one highly susceptible (HS; Junmian 1). This was done at multiple time points after V. dahliae inoculation, which identified 2010 and 1275 differentially expressed genes (DEGs) in HR and HS, respectively. Plant hormone signal transduction-related genes were enriched in HR, whereas genes related to lignin biosynthesis were enriched in both HR and HS. Weighted gene co-expression network analysis (WGCNA) using the 2868 non-redundant genes differentially expressed between the V. dahliae infected and uninfected samples in HR or HS identified 10 different gene network modules and 22 hub genes with a potential role in regulating cotton defense against V. dahliae infection. GhGDH2, encoding glutamate dehydrogenase (GDH), was selected for functional characterization. Suppressing the expression level of GhGDH2 by virus-induced gene silencing (VIGS) in HS led to inhibition of the salicylic acid (SA) biosynthesis/signaling pathways and activation of the jasmonic acid (JA) biosynthesis/signaling pathways, which resulted in an increase of 42.1% JA content and a reduction of 78.9% SA content in cotton roots, and consequently enhanced V. dahliae resistance. Our finding provides new insights on the molecular mechanisms of cotton resistance to V. dahliae infection and candidate genes for breeding V. dahliae resistance cotton cultivars by genetic modification.

Weighted gene coexpression network analysis-based identification of key modules and hub genes associated with drought sensitivity in rice

BACKGROUND

Drought stress is an adverse factor with deleterious effects on several aspects of rice growth. However, the mechanism underlying drought resistance in rice remains unclear. To understand the molecular mechanism of the drought response in rice, drought-sensitive CSSL (Chromosome Single-substitution Segment Line) PY6 was used to map QTLs of sensitive phenotypes and to reveal the impact of the QTLs on transcriptional profiling.

RESULTS

The QTL dss-1 was mapped onto the short arm of chromosome 1 of rice. According to transcriptomic analysis, the identified differentially expressed genes (DEGs) exhibited a downregulated pattern and were mainly enriched in photosynthesis-related GO terms, indicating that photosynthesis was greatly inhibited under drought. Further, according to weighted gene coexpression network analysis (WGCNA), specific gene modules (designating a group of genes with a similar expression pattern) were strongly correlated with H₂O₂ (4 modules) and MDA (3 modules), respectively. Likewise, GO analysis revealed that the photosynthesis-related GO terms were consistently overrepresented in H₂O₂-correlated modules. Functional annotation of the differentially expressed hub genes (DEHGs) in the H₂O₂ and MDA-correlated modules revealed cross-talk between abiotic and biotic stress responses for these genes, which were annotated as encoding WRKYs and PR family proteins, were notably differentially expressed between PY6 and PR403.

CONCLUSIONS

We speculated that drought-induced photosynthetic inhibition leads to H₂O₂ and MDA accumulation, which can then trigger the reprogramming of the rice transcriptome, including the hub genes involved in ROS scavenging, to prevent oxidative stress damage. Our results shed light on and provide deep insight into the drought resistance mechanism in rice.

Overexpression of an ethylene-forming ACC oxidase (ACO) gene precedes the Minute Hilum seed coat phenotype in Glycine max

BACKGROUND

To elucidate features of seed development, we investigated the transcriptome of a soybean isoline from the germplasm collection that contained an introgressed allele known as minute hilum (mi) which confers a smaller hilum region where the seed attaches to the pod and also results in seed coat cracking surrounding the hilum region.

RESULTS

RNAs were extracted from immature seed from an extended hilum region (i.e., the hilum and a small ring of tissue surrounding the hilum in which the cracks form) at three different developmental stages:10-25, 25-50 and 50-100 mg seed fresh weight in two independent replicates for each stage. The transcriptomes of these samples from both the Clark isoline containing the mi allele (PI 547628, UC413, ii R t mi G), and its recurrent Clark 63 parent isoline (PI 548532, UC7, ii R T Mi g), which was used for six generations of backcrossing, were compared for differential expression of 88,648 Glyma models of the soybean genome Wm82.a2. The RNA sequence data obtained from the 12 cDNA libraries were subjected to padj value < 0.05 and at least two-fold expression differences to select with confidence genes differentially expressed in the hilum-containing tissue of the seed coat between the two lines. Glyma.09G008400 annotated as encoding an ethylene forming enzyme, ACC oxidase (ACO), was found to be highly overexpressed in the mi hilum region at 165 RPKMs (reads per kilobase per million mapped reads) compared to the standard line at just 0.03 RPKMs. Evidence of changes in expression of genes downstream of the ethylene pathway included those involved in auxin and gibberellin hormone action and extensive differences in expression of cell wall protein genes. These changes are postulated to determine the restricted hilum size and cracking phenotypes.

CONCLUSIONS

We present transcriptome and phenotypic evidence that substantially higher expression of an ethylene-forming ACO gene likely shifts hormone balance and sets in motion downstream changes resulting in a smaller hilum phenotype and the cracks observed in the minute hilum (mi) isoline as compared to its recurrent parent.

Analysis of Spatio-Temporal Transcriptome Profiles of Soybean (Glycine max) Tissues during Early Seed Development

Soybean (Glycine max) is an important crop providing oil and protein for both human and animal consumption. Knowing which biological processes take place in specific tissues in a temporal manner will enable directed breeding or synthetic approaches to improve seed quantity and quality. We analyzed a genome-wide transcriptome dataset from embryo, endosperm, endothelium, epidermis, hilum, outer and inner integument and suspensor at the global, heart and cotyledon stages of soybean seed development. The tissue specificity of gene expression was greater than stage specificity, and only three genes were differentially expressed in all seed tissues. Tissues had both unique and shared enriched functional categories of tissue-specifically expressed genes associated with them. Strong spatio-temporal correlation in gene expression was identified using weighted gene co-expression network analysis, with the most co-expression occurring in one seed tissue. Transcription factors with distinct spatiotemporal gene expression programs in each seed tissue were identified as candidate regulators of expression within those tissues. Gene ontology (GO) enrichment of orthogroup clusters revealed the conserved functions and unique roles of orthogroups with similar and contrasting expression patterns in transcript abundance between soybean and Arabidopsis during embryo proper and endosperm development. Key regulators in each seed tissue and hub genes connecting those networks were characterized by constructing gene regulatory networks. Our findings provide an important resource for describing the structure and function of individual soybean seed compartments during early seed development.

The core regulatory networks and hub genes regulating flower development in Chrysanthemum morifolium

The study has facilitated important insights into the regulatory networks involved in flower development in chrysanthemum (Asteraceae), and is informative with respect to the mechanism of flower shape determination. Chrysanthemum morifolium, valued as an ornamental species given the diversity of its inflorescence form, is viewed as a model for understanding flower development in the Asteraceae. Yet, the underlying regulatory networks remain largely unexplored. Here, a transcriptomic survey of the Chrysanthemum morifolium variety 'Jinba' was undertaken to uncover the global gene expression profiles and identify the modules of co-transcribed genes associated with flower development. The weighted gene coexpression network analysis revealed important networks and hub genes including ray floret petals-specific coexpression network, disc floret petals-specific network, B and E class genes involved network and CYC2 genes network. Three ray floret petal-specific hub genes were also strongly transcribed in the ray florets of a selection of six diverse varieties and especially so in those which form ligulate ray floret petals. CmCYC2c was strongly transcribed in the distal and lateral regions of the ray floret petals, and also, along with CmCYC2d, in the tubular ray florets. Furthermore, CmOFP, belonging to the family of ovate proteins, was identified in the CYC2 genes network. CmOFP can interact with CmCYC2d that physically interact with CmCYC2c. This work provides important insights into the regulatory networks involved in flower development in chrysanthemum, and is informative with respect to the mechanistic basis of the regulation of flower shape.

Multi-omics sequencing provides insight into floral transition in Catalpa bungei. C.A. Mey

BACKGROUND

Floral transition plays an important role in development, and proper time is necessary to improve the value of valuable ornamental trees. The molecular mechanisms of floral transition remain unknown in perennial woody plants. "Bairihua" is a type of C. bungei that can undergo floral transition in the first planting year.

RESULTS

Here, we combined short-read next-generation sequencing (NGS) and single-molecule real-time (SMRT) sequencing to provide a more complete view of transcriptome regulation during floral transition in C. bungei. The circadian rhythm-plant pathway may be the critical pathway during floral transition in early flowering (EF) C. bungei, according to horizontal and vertical analysis in EF and normal flowering (NF) C. bungei. SBP and MIKC-MADS-box were seemingly involved in EF during floral transition. A total of 61 hub genes were associated with floral transition in the MEturquoise model with Weighted Gene Co-expression Network Analysis (WGCNA). The results reveal that ten hub genes had a close connection with the GASA homologue gene (Cbu.gene.18280), and the ten co-expressed genes belong to five flowering-related pathways. Furthermore, our study provides new insights into the complexity and regulation of alternative splicing (AS). The ratio or number of isoforms of some floral transition-related genes is different in different periods or in different sub-genomes.

CONCLUSIONS

Our results will be a useful reference for the study of floral transition in other perennial woody plants. Further molecular investigations are needed to verify our sequencing data.