Abstract

Background

   Cross breeding is the most commonly used method in chrysanthemum
   (Chrysanthemum morifolium) breeding; however, cross barriers always
   exist in these combinations. Many studies have shown that paternal
   chromosome doubling can often overcome hybridization barriers during
   cross breeding, although the underlying mechanism has seldom been
   investigated.

Results

   In this study, we performed two crosses: C. morifolium (pollen
   receptor) × diploid C. nankingense (pollen donor) and C.
   morifolium × tetraploid C. nankingense. Seeds were obtained only from
   the latter cross. RNA-Seq and isobaric tags for relative and absolute
   quantitation (iTRAQ) were used to investigate differentially expressed
   genes and proteins during key embryo development stages in the latter
   cross. A previously performed cross, C. morifolium × diploid C.
   nankingense, was compared to our results and revealed that
   transcription factors (i.e., the agamous-like MADS-box protein AGL80
   and the leucine-rich repeat receptor protein kinase EXS),
   hormone-responsive genes (auxin-binding protein 1), genes and proteins
   related to metabolism (ATP-citrate synthase, citrate synthase and
   malate dehydrogenase) and other genes reported to contribute to embryo
   development (i.e., LEA, elongation factor and tubulin) had higher
   expression levels in the C. morifolium × tetraploid C. nankingense
   cross. In contrast, genes related to senescence and cell death were
   down-regulated in the C. morifolium × tetraploid C. nankingense cross.

Conclusions

   The data resources helped elucidate the gene and protein expression
   profiles and identify functional genes during different development
   stages. When the chromosomes from the male parent are doubled, the
   genes contributing to normal embryo developmentare more abundant.
   However, genes with negative functions were suppressed, suggesting that
   chromosome doubling may epigenetically inhibit the expression of these
   genes and allow the embryo to develop normally.

Electronic supplementary material

   The online version of this article (doi:10.1186/s12864-016-2939-0)
   contains supplementary material, which is available to authorized
   users.

   Keywords: Chromosome doubling, Chrysanthemum morifolium, Cross barrier,
   Interspecific hybridization, iTRAQ, RNA-Seq

Background

   Intergeneric/interspecific crosses between cultivars and their wild
   species are widely used to improve the tolerance of crop plants to
   biotic and abiotic stresses. The offspring of these crosses might have
   greater environmental adaptability and species diversity. The embryos
   develop normally, and seeds can be successfully obtained, which are the
   considerations when evaluating crossing efficiency. Many factors
   influence the efficiency of interspecific crosses. Differences in the
   ploidy levels of the parental plants were thought to be one major
   barrier causing endosperm malformation and the inhibition of
   germination [[40]1]. Indeed, hybrid embryos are often spontaneously
   aborted due to the absence of endosperm or retarded development after
   successful interspecific pollination, which is a typical
   post-fertilization barrier that strongly hampers embryo development
   [[41]2]. There is growing evidence that polyploid breeding has the
   potential to overcome this barrier and has emerged as one of the most
   efficient methods. The development of the major crop species common
   wheat (Triticum aestivum) is a universally acknowledged textbook
   example of an allohexaploid derived through hybridization between a
   domesticated forms of the tetraploid T. turgidum ssp. dicoccoides and
   the diploid Aegilops tauschii [[42]3, [43]4]. In 1988, Badger found
   that tetraploid azaleas could overcome interspecific barriers. The
   cross Rhododendron calendulaceum x tetraploid evergreen Obtusum was
   highly successful, and produced many viable seeds. However, the cross
   between R. calendulaceum and the diploid evergreen Obtusum was seldom
   successful [[44]5]. Although chromosome doubling can also overcome
   reproductive barriers during the cross breeding of many other plant
   species, the underlying mechanism remains unknown.

   C. morifolium is an important ornamental crop that is similar to the
   rose and lily with a high demand in the consumer market. To meet
   increasing consumer needs, breeders must search for novel traits,
   improve plant qualities and increase the resistance of existing species
   to biotic or abiotic stresses. Cross breeding is the conventional path
   to improve genetic variability and develop modified species. Successful
   intergeneric hybridization efforts have been reported between the
   chrysanthemum and related genera, such as C. lavandulifolium × Ajania
   remotipinna, A. remotipinna × C. chanetii [[45]6] and Opisthopappus
   taihangensis × C. lavandulifolium [[46]7]. However, interspecific
   crosses with the chrysanthemum are difficult because of its limited
   genetic diversity, especially between the hexaploid chrysanthemum and
   diploid wild species. In a cross between C. morifolium and diploid C.
   nankingense, six interspecific hybrids were generated but required
   ovary rescue [[47]8]. In a cross chrysanthemum cultivar
   ‘Zhongshanzixing’ × diploid C. nankingense, no seeds were obtained,
   whereas seeds were obtained in the cross between ‘Zhongshanzixing’ and
   tetraploid C. nankingense [[48]9]. These results suggest that
   polyploidization of the male parent can overcome cross barriers between
   incongruous groups. In these studies, the reason for interspecific
   cross inhibition was attentively examined. A pre- or post-fertilization
   barrier was confirmed to exist between different hybrids in a large
   number of morphological and cytological studies [[49]8, [50]10].
   However, the expression patterns of genes and proteins underlying the
   morphological and cytological traits remain unclear. The effects of
   polyploidization on interspecific chrysanthemum crosses have not been
   studied, and the mechanisms by which different ploidy levels regulate
   chrysanthemum embryonic development remain elusive.

   Currently, RNA-Seq is often used for gene discovery and transcript
   abundance measurements during a certain state in particular organs or
   tissues and has been successfully applied in different species
   [[51]11]. Recently, transcriptome and proteome methodologies were
   applied to developing Medicago truncatula seeds [[52]12] and
   Arabidopsis seed germination [[53]13]. Deep sequencing analysis was
   applied to the peanut pod transcriptome to identify candidate genes
   related to early embryo abortion [[54]14]; this approach was also used
   to study the early Arabidopsis embryo [[55]15]. In a previous study, we
   explored genes and proteins associated with chrysanthemum embryo
   abortion in the cross C. morifolium × diploid C. nankingense using
   RNA-Seq and isobaric tags for relative and absolute quantitation
   (iTRAQ), focusing on the perspective of embryo abortion [[56]16]. Here,
   we performed the cross C. morifolium × tetraploid C. nankingense, which
   decreased the embryo abortion rate and produced seeds, but the genes
   and proteins that aided normal embryo development were unclear.
   Therefore, the combination of transcriptomic and proteomic data is
   suitable to study chrysanthemum embryo development and explore the
   differential expression patterns in different interspecific crosses and
   samples. Our objectives were as follows: (i) to analyze gene and
   protein expression in the developing chrysanthemum embryo and
   characterize expression changes at different stages of embryonic
   development from the cross C. morifolium × tetraploid C. nankingense
   and to identify over-expressed genes and proteins that promote normal
   embryo development; (ii) to compare the expression of key genes and
   proteins related to chrysanthemum embryo abortion in the two different
   crosses using a previous study [[57]16] and point out the genes and
   proteins with positive roles promoting chrysanthemum embryo
   development. This study will also provide a better understanding of the
   mechanism underlying the different seed setting rates when the male
   parent has different ploidy levels.

Results

Ovule development and seed setting

   In the cross C. morifolium × tetraploid C. nankingense, many ovules
   were morphologically well developed with a full form at 12 days after
   pollination (DAP); a total of 93.5 ± 1.7 % of the ovules were normal.
   The percentage was 89.7 ± 3.1 % in the cross C. morifolium × diploid C.
   nankingense, similar to that of the C. morifolium × tetraploid C.
   nankingense cross. Based on continuous observations, many ovules were
   shriveled, and only 54.8 ± 0.9 % of the ovules appeared normal at 18
   DAP; however, this value was significantly higher than 43.3 ± 1.8 %,
   the corresponding rate in the C. morifolium × diploid C. nankingense
   cross. Eventually, a few seeds were obtained generating a seed set rate
   of 1.45 ± 0.03 % in this study. No seeds were obtained when the diploid
   C. nankingense was the male parent [[58]16] (Table [59]1). In this
   study, transmission electron microscopy (TEM) analysis showed that the
   normal cells at 12 DAP contained many organelles, mitochondria and
   plastids with normal shapes. Moreover, the cells exhibited an intact
   cell wall structure and rich edge information. In the normal embryos at
   18 DAP, although the cytoplasm contracted slightly as the embryos
   developed, the organelles were well developed and metabolism was robust
   in the mitochondria. However, abnormal embryos at 18 DAP showed
   significant differences, including clearly shrinking nuclei and a
   decrease in mitochondria and plastid. Additionally, the organelle
   structures were aberrant, with degradation and obvious variation and
   thickening of the cell wall (Fig. [60]1).

Table 1.

   Percentage of normal embryos at different stages after pollination in
   C. morifolium × C. nankingense
   Cross Percentage of normal embryos or seed set
   12 DAP 18 DAP 40 DAP
   C. morifolium × tetraploid C. nankingense 93.5 ± 1.7 % 54.8 ± 0.9 %
   1.45 ± 0.03 %
   C. morifolium × diploid C. nankingense [[61]16] 89.7 ± 3.1 %
   43.3 ± 1.8 %^* 0^*
   [62]Open in a new tab

   DAP means days after pollination.

   ‘*’ indicates the significant differences at P ≤ 0.05 according to
   t-test. Values are means ± standard error (n = 3).

Fig. 1.

   Fig. 1
   [63]Open in a new tab

   TEM of NE12, NE18 and AE18 in the cross C. morifolium × tetraploid C.
   nankingense. a, b NE12; c, d NE18; e, f AE18. Bar = 20 μm. NE12: normal
   embryos at 12 days after pollination; NE18: normal embryos at 18 days
   after pollination; AE18: abnormal embryos at 18 days after pollination.
   N: nucleus; CW: cell wall; M: mitochondria; V: vacuole; P: plastid; ER:
   endoplasmic reticulum

Transcriptome sequencing and read assembly

   Using Illumina high-throughput sequencing, we constructed three cDNA
   libraries from normal embryos at 12 DAP (NE12), normal embryos at 18
   DAP (NE18) and abnormal embryo at 18 DAP (AE18) from the C.
   morifolium × tetraploid C. nankingense cross. After cleaning the raw
   data, we obtained 52,206,996, 51,935,854 and 51,720,046 clean reads
   from NE12, NE18 and AE18, respectively, containing 4,698,629,640,
   4,674,226,860 and 4,654,804,140 clean nucleotides (Table [64]2). Based
   on these high-quality clean reads, a total of 99,119 unigenes were
   assembled with a mean length of 726 nt, including 45,770 clusters and
   53,349 singletons. The numbers of unigenes for NE12, NE18 and AE18 were
   88,909, 91,971 and 97,889, respectively, with a mean length of
   550-580 nt (Table [65]3).

Table 2.

   Output statistics of sequencing
   Sample Total raw reads Total clean reads Total clean nucleotides (nt)
   Q20 percentage N percentage GC percentage
   NE12 55,087,918 52,206,996 4,698,629,640 98.37 % 0.00 % 44.20 %
   NE18 56,564,364 51,935,854 4,674,226,860 98.40 % 0.00 % 44.49 %
   AE18 58,160,684 51,720,046 4,654,804,140 98.45 % 0.00 % 44.19 %
   [66]Open in a new tab

Table 3.

   Statistics of assembly quality
   Sample Total number of sequences Total Length (nt) Mean Length (nt)
   Distinct Clusters Distinct Singletons
   NE12 88,909 51,281,289 577 33,867 55,042
   NE18 91,971 52,587,899 572 34,581 57,390
   AE18 97,889 54,412,745 556 36,097 61,792
   All 99,119 71,965,184 726 45,770 53,349
   [67]Open in a new tab

Unigene functional annotation

   Annotation analysis of the chrysanthemum embryo provided information on
   gene expression and the function of all unigenes detected at different
   developmental stages. The annotation consisted of protein functional
   annotation, pathway annotation, Clusters of Orthologous Groups of
   proteins (COG) functional annotation and gene ontology (GO) functional
   annotation. As a result, 58,799 unigenes were annotated with the NR,
   NT, Swiss-Prot, KEGG, COG and GO databases; the numbers of annotations
   obtained from each database were 56,665, 39,101, 36,897, 33,594, 20,391
   and 43,526, respectively (Table [68]4). The largest number of annotated
   unigenes was obtained from the NR database.

Table 4.

   Annotation of unigenes in chrysanthemum embryo
   Sequence database Number of annotated unigenes Percentage of annotated
   unigenes
   NR 56,665 96.37
   NT 39,101 66.5
   Swiss-Prot 36,897 62.75
   KEGG 33,594 57.13
   COG 20,391 34.68
   GO 43,526 74.03
   All 58,799 100
   [69]Open in a new tab

   To investigate unigene function and evaluate the effectiveness of the
   annotation process, 20,391 sequences accounting for 34.68 % of the
   total annotated unigenes were assigned a COG functional annotation.
   Among the 25 COG categories, the clusters in the top three were
   ‘general function prediction only’ (6749); ‘transcription’ (3844); and
   ‘replication, and recombination and repair’ (3323). The number of
   unigenes in each cluster accounted for more than 15 % of all unigenes
   with a COG annotation. The two clusters with the fewest unigenes were
   ‘extracellular structures’ (14) and ‘nuclear structure’ (11); the
   percentage of unigenes in each category was less than 1 % (Additional
   file [70]1: Figure S1).

   Using NR annotation, we obtained GO functional annotations describing
   the properties of genes and their products in chrysanthemum. Based on
   sequence homology, 43,526 sequences could be categorized into 55
   functional groups, including the three main GO classifications
   (biological process, cellular component, and molecular function). There
   were 24, 15 and 16 functional subcategories in each main
   classification; ‘cellular process’, ‘cell’ and ‘cell part’ (equal), and
   ‘catalytic activity’ were the most common subcategories (Additional
   file [71]2: Figure S2). Additionally, the classes ‘organelle’ and
   ‘metabolic process’ contained many unigenes that might play important
   roles in the metabolic pathways involved in chrysanthemum embryo
   development.

   Next, the KEGG pathway database was applied to identify the biological
   pathways activated in the chrysanthemum embryo. A total of 33,594
   annotated unigenes were assigned to 128 KEGG pathways (Additional file
   [72]3: Table S1). The majority of these pathways were ‘metabolic
   pathways’ (22.67 %), ‘biosynthesis of secondary metabolites’ (11.27 %),
   ‘plant-pathogen interaction’ (5.67 %) and ‘plant hormone signal
   transduction’ (4.97 %).

Genes related to embryo development and differentially expressed genes at
three stages

   Using FPKM (Fragments Per kb per Million fragments), we explored the
   gene expression levels in normal and abnormal embryos. In three
   comparisons (NE12 vs NE18, NE18 vs AE18, and NE12 vs AE18), the number
   of differentially expressed genes (DEGs) was 6537 (4302 were
   up-regulated), 3276 (1119 were up-regulated), and 7794 (5082 were
   up-regulated). The first and third comparisons exhibited more
   up-regulated genes than down-regulated genes (Fig. [73]2). The details
   of the DEGs are presented in Additional file [74]4: Table S2. During
   the embryonic developmental stage from 12 DAP to 18 DAP (including both
   normal and abnormal embryos), the number of up-regulated genes at 18
   DAP was nearly twice as high as the number of down-regulated genes.
   Interestingly, the number of down-regulated genes in abnormal embryos
   was higher than the number of up-regulated genes during the later
   developmental stage (18 DAP) (Fig. [75]2).

Fig. 2.

   Fig. 2
   [76]Open in a new tab

   Differentially expressed genes among three libraries in the cross C.
   morifolium × tetraploid C. nankingense

   After deep analysis of these DEGs, we found that several categories of
   genes had similar expression patterns in normal and abnormal embryos.
   Then, we used the CDS sequences of these DEGs as a query to identify
   the same unigenes in the transcriptome library sequenced from
   chrysanthemum embryos in the C. morifolium × diploid C. nankingense
   cross [[77]16]. We analyzed the expression of some of the genes to
   obtain clues concerning their roles during chrysanthemum embryo
   development (i.e., CmLEA, CmLEC, CmEM, CmSSP, CmOLE, CmTUB and CmEXT).
   The expression patterns of these genes differed between the two crosses
   and various samples. For instance, CmTUB in NE18 had the highest
   expression level in the cross C. morifolium × tetraploid C.
   nankingense; however, in the cross C. morifolium × diploid C.
   nankingense, it was most highly expressed during NE12 (Fig. [78]3).

Fig. 3.

   Fig. 3
   [79]Open in a new tab

   The expression patterns of DEGs in two transcriptome libraries. Blue
   columns represent the cross C. morifolium  × tetraploid C. nankingense,
   and green columns represent the cross C. morifolium  × diploid C.
   nankingense

Pathway classification by KEGG

   KEGG is a database that analyzes gene products during metabolism and
   related gene functions involved in cellular processes. Using the KEGG
   database, we obtained two pathway annotations [energy metabolism
   (Fig. [80]4) and auxin signal transduction (Fig. [81]5)] between NE18
   and AE18 in the cross C. morifolium × tetraploid C. nankingense.
   Compared with NE18, many of the enzymes involved in the pyruvate,
   acetyl-CoA and tricarboxylic acid (TCA) cycle pathways in the
   mitochondria were down-regulated in AE18; only citrate synthase [EC:
   2.3.3.1] showed altered expression (Fig. [82]4). Auxin response factor
   (ARF) is the key factor in the auxin signal transduction pathway and
   receives auxin signals, leading to activation or repression of
   downstream genes. Two genes (AUX/IAA and GH3) involved in cell
   enlargement and plant growth reported to be regulated by ARF were
   down-regulated in the abnormal embryos when compared with the normal
   embryos (Fig. [83]5).

Fig. 4.

   Fig. 4
   [84]Open in a new tab

   Analysis of the tricarboxylic acid (TCA) cycle pathway in normal and
   abnormal embryos 18 DAP in the cross C. morifolium × tetraploid C.
   nankingense. The map displays selected steps from the KEGG pathway
   ko00020 ‘Citrate cycle (TCA cycle)’. Yellow indicates higher relative
   levels and blue indicates lower levels in AE18. Enzymes are given as EC
   numbers: 1.2.4.1, pyruvate dehydrogenase; 1.8.1.4, dihydrolipoamide
   dehydrogenase; 2.3.1.12, dihydrolipoamide acetyltransferase; 2.3.3.1,
   citrate synthase; 1.3.5.1, succinate dehydrogenase; and 1.1.1.37,
   malate dehydrogenase

Fig. 5.

   Fig. 5
   [85]Open in a new tab

   Analysis of the pathway related to auxin signal transduction in normal
   and abnormal embryos 18 DAP in the cross C. morifolium × tetraploid C.
   nankingense. The map displays selected steps from the KEGG pathway
   ko04075 ‘Plant hormone signal transduction’. Blue indicates the lower
   expression level of genes in AE18

qRT-PCR validation

   To validate the quality of the RNA-Seq data in this study, quantitative
   real-time RT-PCR (qRT-PCR) was performed on 29 randomly selected genes
   with differential expression levels. The differential expression
   patterns in the three samples, and the expression trend of almost all
   of the genes were consistent with the sequencing data (Fig. [86]6).
   Most of these genes were related to plant embryonic development (i.e.,
   globulin seed storage protein, ethylene-responsive transcription
   factor, auxin-induced protein, embryonic protein, leafy cotyledon
   1-like protein and senescence-related protein). Moreover, 40 DEGs (in
   Tables [87]5 and [88]6) in two crosses were validated, and 35 of 40
   DEGs (87.5 %) showed the same type of altered expression as RNA-Seq
   (Additional file [89]5: Figure S3 and Additional file [90]6: Figure
   S4).

Fig. 6.

   Fig. 6
   [91]Open in a new tab

   Validation of the RNA-Seq results by qRT-PCR. FPKM represents the gene
   abundance in the sequencing data of the transcriptome libraries

Table 5.

   Genes with same CDS sequences involved in embryo development at 12 DAP
   in two crosses
   Gene ID (numbered in cross I) FPKM in cross I FPKM in cross II UP/DOWN
   Annotation Acronym Function
   CL1478.Contig3 61.3065 6.9942 UP Agamous-like MADS-box protein AGL80
   AGL80 Affect female gametophyte and endosperm development in
   Arabidopsis [[92]23]
   Unigene25835 10.9284 0.509 UP Floral homeotic protein APETALA2 AP2
   Influence development of the zygotic embryo and endosperm [[93]50]
   CL4736.Contig1 15.3212 40.7673 DOWN AP2 domain class transcription
   factor AP2 Same as above
   CL5669.Contig8 2.2975 4.874 DOWN Receptor-like protein kinase HAIKU2
   Iku2 Regulate the early endosperm cellularization and seed size
   [[94]51]
   Unigene26041 74.7454 28.9534 UP Leucine-rich repeat extensin-like
   protein EXS Promote seed development and enhance cee size in
   Arabidopsis [[95]52]
   Unigene30982 39.5864 82.4367 DOWN Multicopy suppressor of Ira1 MSI1 Be
   required for seed development [[96]53]
   CL15981.Contig1 18.8318 3.0993 UP Auxin-binding protein 1 ABP1 Be
   required for cell elongation and division in Arabidopsis embryogenesis
   [[97]54]
   Unigene26808 54.5756 2.5485 UP Arabidopsis histidine kinase AHK Serve
   as cytokinin receptors and regulate the seed size [[98]55]
   CL1615.Contig2 8.5299 3.0442 UP Cytosolic phosphoglycerate kinase 2
   CPK2 Be involved in glycolysis pathway [[99]19]
   Unigene744 24.4165 6.4023 UP Citrate synthase N/A Be involved in the
   tricarboxylic acid (TCA) cycle pathway [[100]19]
   CL6259.Contig2 119.376 34.959 UP Aconitase protein N/A Same as above
   Unigene41988 8.1445 1.4722 UP NADP-isocitrate Dehydrogenase N/A Same as
   above
   CL5293.Contig2 22.4495 3.113 UP 2-succinylbenzoate-CoA ligase N/A Same
   as above
   CL16042.Contig2 4.6659 1.2739 UP Succinate dehydrogenase [ubiquinone]
   flavoprotein subunit 1 N/A Same as above
   CL12323.Contig3 46.8787 6.9274 UP Malate dehydrogenase N/A Same as
   above
   Unigene31171 1.0883 70.9733 DOWN Late embryogenesis abundant protein
   LEA Be associated with desiccation tolerance during embryo maturation
   [[101]29]
   Unigene14917 6.9638 21.5178 DOWN Senescence-related protein N/A Play
   essential roles of cell death during plant embryogenesis [[102]56]
   Unigene9288 48.7268 98.1867 DOWN Programmed cell death protein N/A Same
   as above
   [103]Open in a new tab

   Cross I: C. morifolium × tetraploid C. nankingense; Cross II: C.
   morifolium × diploid C. nankingense

   N/A not applicable

Table 6.

   Genes with same CDS sequences involved in embryo development at 18 DAP
   in two crosses
   Gene ID (numbered in cross I) FPKM in cross I FPKM in cross II UP/DOWN
   Annotation Acronym Function
   Unigene33530 3.9624 1.4042 UP Agamous-like MADS-box protein AGL80 AGL80
   Affect female gametophyte and endosperm development [[104]23]
   Unigene42751 6.6841 13.8857 DOWN Transcription factor APETALA2 AP2
   Influence development of the zygotic embryo and endosperm [[105]50]
   CL9156 118.0731 314.5676 DOWN AP2 domain class transcription factor AP2
   Same as above
   CL13570.Contig2 7.4684 24.1844 Down Receptor-like protein kinase HAIKU2
   Iku2 Regulate the early endosperm cellularization and seed size
   [[106]51]
   CL11805.Contig1 10.291 1.3491 UP Leucine-rich repeat receptor protein
   kinase EXS EXS Promote seed development in Arabidopsis [[107]52]
   CL1584.Contig1 1.7702 4.0557 DOWN Multicopy suppressor of Ira1 MSI1 Be
   required for seed development [[108]53]
   Unigene7908 97.3165 4.6421 UP Auxin-binding protein 1 ABP1 Be required
   for organized cell elongation and division in Arabidopsis embryogenesis
   [[109]54]
   Unigene7916 45.2634 11.3354 UP Arabidopsis histidine kinase AHK Serve
   as cytokinin receptors and regulate the seed size [[110]55]
   CL4474 88.4354 5.6919 UP Leafy cotyledon 1-like protein LEC1 Regulate
   the embryogenesis, morphogenesis and seed maturation [[111]25]
   CL8636.Contig2 37.1208 7.9805 UP Chloroplast phosphoglycerate kinase 3
   CPK Be involved in glycolysis pathway [[112]19]
   CL4864.Contig4 26.4753 2.0837 UP ATP-citrate synthase beta chain
   protein 1-like N/A Be involved in the tricarboxylic acid (TCA) cycle
   [[113]19]
   CL13319 104.2401 8.611 UP Citrate synthase N/A Same as above
   CL2895.Contig3 66.6572 6.0815 UP aconitase N/A Same as above
   CL9180 112.6106 25.6244 UP NADP-isocitrate dehydrogenase N/A Same as
   above
   CL954.Contig1 33.9533 1.0652 UP Succinyl-CoA ligase N/A Same as above
   Unigene24208 110.71 12.2391 UP succinate dehydrogenase [ubiquinone]
   iron-sulfur subunit 2 N/A Same as above
   Unigene30868 31.2681 5.6957 UP Fumarate hydratase 1 N/A Same as above
   CL2079.Contig6 182.8558 25.9528 UP Malate dehydrogenase N/A Same as
   above
   Unigene31171 445.1903 150.025 UP Late embryogenesis abundant protein
   LEA Be associated with desiccation tolerance during embryo maturation
   [[114]29]
   Unigene15940 0.9442 2.2972 DOWN Senescence-induced receptor N/A Play
   essential roles of cell death during plant embryogenesis [[115]56]
   CL3148.Contig1 17.8887 73.7542 DOWN Regulator of cell death N/A Same as
   above
   Unigene9484 47.3966 12.4093 UP Defender against cell death N/A Same as
   above
   [116]Open in a new tab

   Cross I: C. morifolium × tetraploid C. nankingense; Cross II: C.
   morifolium × diploid C. nankingense

   N/A not applicable

Comparative analysis of identical genes during the same developmental stage
between the two crosses

   Based on the CDS sequence comparison between the two NE12 libraries
   from the two crosses, we identified 18 candidate genes (Table [117]5)
   that had not been analyzed in the C. morifolium × diploid C.
   nankingense cross, that might enhance chrysanthemum embryo development,
   including transcription factors, energy metabolism-related genes and
   other genes that might function in embryo development. Then, the same
   comparative analysis was applied to the NE18 libraries. A total of 22
   candidates (Table [118]6) were found that facilitate the transformation
   from heart embryos to torpedo and cotyledonary embryos during seed
   development. These candidates were similar to NE12 except for
   unigene30868 (fumarate hydratase 1) and unigene9484 (defender against
   cell death), which were differentially expressed only at this stage.
   During both stages, we found that the auxin-binding protein, citrate
   synthase and other genes associated with energy metabolism were more
   highly expressed in cross I (C. morifolium × tetraploid C. nankingense)
   than in cross II (C. morifolium × diploid C. nankingense). Conversely,
   genes related to senescence and programmed cell death were
   down-regulated (Tables [119]5 and [120]6).

Differentially-expressed proteins during chrysanthemum embryo development

   In the embryos from cross I (C. morifolium × tetraploid C.
   nankingense), a total of 23 differentially expressed proteins (DEPs)
   (Table [121]7) were identified, 10 of which were considered predicted,
   hypothetical or unknown proteins, which was not useful for the
   elucidation of their functions. Thus, we aligned their peptides to the
   CDS sequences from the chrysanthemum embryo transcriptome library, and
   as a result, only two of the proteins remained unannotated, suggesting
   that studying the transcriptome was conducive to proteomics research
   for crops without genome sequences. Most of these DEPs were involved in
   energy metabolism (i.e., acetoacetyl CoA thiolase, pyruvate kinase,
   isopropylmalate synthase and malate dehydrogenase) and had high
   expression levels in normal embryos at 18 DAP.

Table 7.

   Differentially expressed proteins in normal and abnormal embryos in
   cross C. morifolium × tetraploid C. nankingense
   Gene ID in transcriptome Annotation in transcriptome Annotation in
   proteome Protein abundance Accession Peptides (95 %) Species
   NE18:NE12 AE18:NE12 NE18:AE18
   CL11142.Contig2 acetoacetyl CoA thiolase acetoacetyl CoA thiolase 1.54
   1.22 1.25 gi|34597334 4 Helianthus annuus
   CL12806.Contig2 GDP-mannose 3,5-epimerase 1 isoform 1 GDP-mannose
   3’,5’-epimerase 0.76 0.54 1.42 gi|240248436 3 Solanum pennellii
   CL12806.Contig2 GDP-mannose 3,5-epimerase 1 isoform 1 predicted protein
   0.63 0.66 0.95 gi|224130650 3 Populus trichocarpa
   CL13159.Contig2 ruBisCO large subunit-binding protein subunit alpha
   hypothetical protein 0.77 0.51 1.51 gi|242032147 4 Sorghum bicolor
   CL15574.Contig2 pyruvate kinase, cytosolic isozyme-like Pyruvate kinase
   1.57 0.69 2.26 gi|92870921 3 Medicago truncatula
   CL2359.Contig5 putative isopropylmalate synthase putative
   isopropylmalate synthase 1.26 1.52 0.82 gi|193290704 2 Capsicum annuum
   CL4538.Contig4 glyceraldehyde 3-phosphate dehydrogenase
   glyceraldehyde-3-phosphate dehydrogenase 1.48 1.64 0.90 gi|83701234 5
   Talipariti tiliaceum
   CL4750.Contig2 predicted protein hypothetical protein 1.86 0.91 2.04
   gi|242074456 2 Sorghum bicolor
   CL4761.Contig1 photosystem II cp47 protein photosystem II 47 kDa
   protein 1.53 1.38 1.11 gi|75755685 4 Acorus calamus
   CL480.Contig6 Transitional endoplasmic reticulum ATPase predicted
   protein 1.12 0.43 2.62 gi|326527541 6 Hordeum vulgare subsp. vulgare
   CL4814.Contig3 unknown unnamed protein product 0.65 0.87 0.75
   gi|257674447 4 Helianthus annuus
   CL5465.Contig4 elongation factor 1-gamma-like hypothetical protein 1.51
   1.56 0.97 gi|225465198 4 Vitis vinifera
   CL7034.Contig6 putative UDP-glucose dehydrogenase 1 hypothetical
   protein 0.81 1.54 0.53 gi|302779800 3 Selaginella moellendorffii
   CL8744.Contig1 14-3-3-like protein 14-3-3 protein 6 1.19 1.62 0.73
   gi|26454608 7 SOLLC
   Unigene11968 thiazole biosynthetic enzyme unknown 0.86 0.63 1.36
   gi|116784521 3 Picea sitchensis
   Unigene12985 thioredoxin peroxidase peroxiredoxin 1.53 1.04 1.47
   gi|300078580 2 Jatropha curcas
   Unigene15015 Nucleoside diphosphate kinase cytosolic nucleoside
   diphosphate kinase 1.52 0.81 1.87 gi|73808794 4 Solanum chacoense
   Unigene16290 calcium-dependent protein kinase 1 unnamed protein product
   0.58 0.57 1.02 gi|257734686 2 Solanum lycopersicum
   Unigene23495 serine carboxypeptidase precursor putative serine
   carboxypeptidase precursor 1.74 1.13 1.54 gi|18447763 5 Gossypium
   hirsutum
   Unigene30534 sucrose sucrose 1-fructosyltransferase sucrose:sucrose
   1-fructosyltransferase 0.59 0.64 0.92 gi|162424641 5 Lactuca sativa
   Unigene45009 tubulin beta chain, putative tubulin beta-9 chain 0.81
   0.61 1.32 gi|7268885 12 Arabidopsis thaliana
   Unigene7304 malate dehydrogenase, mitochondrial-like malate
   dehydrogenase 1.64 1.52 1.08 gi|7798706 5 Vitis vinifera
   Unigene8567 conserved hypothetical protein predicted protein 1.90 2.83
   0.67 gi|224138258 2 Populus trichocarpa
   [122]Open in a new tab

   To analyze the expression levels of these 23 DEPs in cross II (C.
   morifolium × diploid C. nankingense), peptides were searched in a
   proteomic library. As a result, 10 proteins were aligned with the same
   peptides, and their expression levels were variable. The proteins
   associated with energy metabolism, such as pyruvate kinase
   (gi|92870921), transitional endoplasmic reticulum ATPase (gi|326527541)
   and cytosolic nucleoside diphosphate kinase (gi|73808794), had
   significantly higher NE18/AE18 ratios in cross I compared with those of
   cross II (Table [123]8).

Table 8.

   Differentially expressed proteins with same peptides during
   chrysanthemum embryo development in two crosses
   Protein name Protein abundance in Cross I Protein abundance in Cross II
   Accession Species
   NE18:NE12 AE18:NE12 NE18:AE18 NE18:NE12 AE18:NE12 NE18:AE18
   acetoacetyl CoA thiolase 1.54 1.22 1.25 no hit gi|34597334 Helianthus
   annuus
   GDP-mannose 3’,5’-epimerase 0.76 0.54 1.42 no hit gi|240248436 Solanum
   pennellii
   predicted protein 0.63 0.66 0.95 no hit gi|224130650 Populus
   trichocarpa
   hypothetical protein 0.77 0.51 1.51 no hit gi|242032147 Sorghum bicolor
   pyruvate kinase 1.57 0.69 2.26 1.04 0.74 1.41 gi|92870921 Medicago
   truncatula
   putative isopropylmalate synthase 1.26 1.52 0.82 no hit gi|193290704
   Capsicum annuum
   glyceraldehyde-3-phosphate dehydrogenase 1.48 1.64 0.9 1.05 1.29 0.81
   gi|83701234 Talipariti tiliaceum
   hypothetical protein 1.86 0.91 2.04 no hit gi|242074456 Sorghum bicolor
   photosystem II 47 kDa protein 1.53 1.38 1.11 no hit gi|75755685 Acorus
   calamus
   predicted protein 1.12 0.43 2.62 1.12 1.07 1.05 gi|326527541 Hordeum
   vulgare subsp. vulgare
   unnamed protein product 0.65 0.87 0.75 0.68 1.11 0.61 gi|257674447
   Helianthus annuus
   hypothetical protein 1.51 1.56 0.97 no hit gi|225465198 Vitis vinifera
   hypothetical protein 0.81 1.54 0.53 1.03 0.89 1.16 gi|302779800
   Selaginella moellendorffii
   14-3-3 protein 6 1.19 1.62 0.73 0.91 1.06 0.86 gi|26454608 SOLLC
   unknown 0.86 0.63 1.36 no hit gi|116784521 Picea sitchensis
   peroxiredoxin 1.53 1.04 1.47 no hit gi|300078580 Jatropha curcas
   cytosolic nucleoside diphosphate kinase 1.52 0.81 1.87 0.77 1.12 0.68
   gi|73808794 Solanum chacoense
   unnamed protein product 0.58 0.57 1.02 no hit gi|257734686 Solanum
   lycopersicum
   putative serine carboxypeptidase precursor 1.74 1.13 1.54 no hit
   gi|18447763 Gossypium hirsutum
   sucrose:sucrose 1-fructosyltransferase 0.59 0.64 0.92 1.08 0.99 1.09
   gi|162424641 Lactuca sativa
   tubulin beta-9 chain 0.81 0.61 1.32 0.77 0.56 1.37 gi|7268885
   Arabidopsis thaliana
   malate dehydrogenase 1.64 1.52 1.08 1.02 0.99 1.03 gi|7798706 Vitis
   vinifera
   predicted protein 1.9 2.83 0.67 no hit gi|224138258 Populus trichocarpa
   [124]Open in a new tab

   Cross I: C. morifolium × tetraploid C. nankingense; Cross II: C.
   morifolium × diploid C. nankingense

   no hit: These proteins in cross II have not been retrieved in cross I
   by their peptide.

Discussion

   Polyploid breeding can improve breeding efficiency by adjusting the
   optimal chromosome number to successfully match in interspecific
   crosses [[125]17]. In this study, a few seeds were obtained following
   hybridization between a hexaploid maternal parent and a tetraploid male
   parent. Conversely, the cross with the diploid male failed to produce
   seeds [[126]16], suggesting that the ploidy of the male parent might
   affect the formation of hybrid plants. The closer the chromosome ploidy
   of the parents, the more likely the cross will be successful. The same
   phenomenon has been previously reported in chrysanthemum interspecific
   hybridization, in which the cross C. morifolium × C. nankingense
   failed, and cross ability was greatly affected by the pollen grains on
   stigmas and embryo abortion [[127]10]. In another cross, C.
   morifolium × diploid C. nankingense, six hybrids were created, but they
   required ovary rescue, suggesting that the post-fertilization barrier
   played an important role in embryo abortion [[128]8]. In the previous
   study in which C. morifolium ‘Zhongshanzixing’ was the female parent,
   the cross using diploid C. nankingense failed to produce seeds, whereas
   hybrids were obtained when the male parent was a tetraploid C.
   nankingense [[129]9]. Therefore, the doubled chromosome number of C.
   nankingense likely enabled a successful interspecific cross in the
   cultivated chrysanthemum.

   Currently, high-throughput sequencing technology has been used to study
   embryo abortion research [[130]14, [131]16] as well as for de novo
   genome assembly, molecular marker and genome diversity studies, the
   discovery of novel genes and investigations into gene expression
   patterns. Therefore, studying the genes or proteins related to embryo
   or endosperm development in various crosses is also helpful.

Transcriptome and proteome data analysis during chrysanthemum embryo
development

   In this study, COG and GO functional annotations were performed. In the
   COG functional annotation (Additional file [132]1: Figure S1) from the
   three transcriptomic libraries, the top five of the 25 obtained COG
   categories were same as cross II [[133]16]. Interestingly, the same
   situation was observed in the GO functional annotation (Additional file
   [134]2: Figure S2), suggesting that the genes involved in the
   regulation of these processes had widespread expression during
   chrysanthemum embryonic development. Next, we detected 3276 DEGs
   (Fig. [135]2) and 23 DEPs (Table [136]7) between the normal and
   abnormal embryos at 18 DAP that might be related to embryo and
   endosperm development in this cross. Finally, using KEGG annotation,
   two pathways were chosen in NE18 and AE18: ‘Citrate cycle (TCA cycle)’
   and ‘Plant hormone signal transduction’. Between two crosses, qRT-PCR
   confirmed the reliability of the 35 DEGs in Tables [137]5 and [138]6.
   Study has shown that the DEGs detection depended on the pooled samples
   or individual samples [[139]18]. Thus, pooled samples were used in this
   study, which might have caused the false positivity observed for the
   other 5 DEGs. RNA-Seq of the individual samples is a better way to
   detect DEGs. However, because of the difficulty collecting material and
   the limitation of florescence, pooled samples are also worthwhile when
   qRT-PCR verification is used as a complementary approach to exclude
   false positive of DEGs.

Expression of genes involved in energy metabolism pathways

   Energy metabolism is necessary for nearly all biological process,
   including plant embryo development. In our results, the KEGG pathway
   analysis between NE18 and AE18 in cross I demonstrated the importance
   of energy metabolism for normal embryo development. Most of the enzymes
   involved in the TCA cycle exhibited reduced expression levels in
   abnormal embryos at 18 DAP (Fig. [140]4), suggesting that decreased
   energy was not sufficient for continued embryo growth and resulted in
   abortion. The genes and proteins involved in energy metabolism
   (especially in cytosolic glycolysis and the mitochondrial TCA cycle)
   were identified as differentially expressed during embryogenesis
   (Fig. [141]4, Tables [142]5, [143]6, [144]7, [145]8). In normal embryos
   at 12 DAP in the two crosses, the genes related to citrate synthase,
   aconitase protein, NADP-isocitrate dehydrogenase and malate
   dehydrogenase were up-regulated in cross I (Table [146]5); moreover,
   normal embryos at 18 DAP exhibited the same expression pattern, whereas
   the genes associated with the TCA cycle and glycolysis pathway in cross
   I were also more highly expressed (Table [147]6). During maize embryo
   development, genes related to metabolism showed altered expression;
   these gene transcripts accumulated at higher levels between 10 and 20
   DAP during the active process of metabolism [[148]19]. Using
   comparative proteome analysis, we identified some proteins associated
   with energy metabolism, such as pyruvate kinase (the ratios of
   NE18/AE18 for cross I and II were 2.26 and 1.41, respectively) and the
   transitional endoplasmic reticulum ATPase (the ratios were 2.62 and
   1.65, respectively). In this study, the higher expression of these
   genes in NE12 and NE18 and the obviously higher ratios (NE18/AE18) of
   these proteins in cross I (Table [149]8) suggested that more active
   energy metabolism occurred in cross I during the development of
   chrysanthemum embryos, which would help provide sufficient energy for
   improved embryo development and reduced rates of abortion, which
   increased the production of seeds.

Expression of genes involved in hormonal signaling

   Plant hormones, such as auxins, cytokinins, and gibberellins are
   involved in the regulation of seed development [[150]20]. For example,
   in an auxin-binding protein 1 (abp1) mutant, the embryos develop
   abnormally after the globular embryo stage because of a failure of cell
   elongation [[151]21]. In NE12 and NE18 of the two crosses, the
   expression of ABP1 was significantly higher in cross I (Tables [152]5
   and [153]6), suggesting that ABP1 might facilitate normal embryo
   development in chrysanthemums by mediating auxin-induced cell
   elongation and cell division. In cross I, the KEGG pathway related to
   auxin signal transduction indicated down-regulated expression of the
   DNA binding ARF activators (Fig. [154]5), which were shown to regulate
   the expression of auxin-responsive genes. These auxin-responsive genes
   belong to three major groups: Aux/IAA, Small Auxin Up RNA (SAUR) and
   Gretchen Hagen 3 (GH3) [[155]22]. In abnormal embryos, the expression
   of Aux/IAA and GH3 were down-regulated, indicating that these genes
   play an important role during normal embryo development in
   chrysanthemum.

Expression of transcription factors

   Transcription factors (TFs) are critically important during plant
   flower and fruit development. Several types of TFs were differentially
   expressed during chrysanthemum embryo development in the two crosses.
   However, how these TFs are regulated from early embryogenesis to
   maturity is unknown. Transcriptome analysis revealed that some of the
   transcription factors were significantly up-regulated in cross I, such
   as AGAMOUS-LIKE62 (AGL62), AGL80, exs and LEAFY COTYLEDON1 (LEC1),
   which enhance important functions necessary for in plant embryonic
   development. In Arabidopsis, the AGL80 has been demonstrated to be
   involved in endosperm development. In fem111 plants, female
   gametophytes contain a T-DNA insertion in AGL80, resulting in the
   reduced size of the central cell’s nucleolus and vacuole and a failure
   to generate endosperm [[156]23]. In NE12, the expression level of AGL80
   (CL1478.Contig3) in cross I was far greater than in cross II
   (Table [157]5). In Arabidopsis, AGL80 was expressed exclusively in the
   endosperm at the stage from 8 to 72 h after pollination, and the
   expression level was strongest in young seeds, decreasing gradually as
   the seeds age [[158]23]. Similar gene expression was observed in this
   study, in which the expression of AGL80 (Unigene33530) decreased in
   NE18 compared to NE12 (Table [159]6). The globular-to-heart transition
   stage is essential for endosperm development and provides nutrient
   supplies for embryo development [[160]20]. Thus, the high expression of
   AGL80 at 12 DAP observed in our study might promote normal
   chrysanthemum endosperm development by ensuring the energy supply for
   embryo development at 18 DAP, suggesting that AGL80 in cross I was
   required for endosperm development and the improved success rate of the
   interspecific cross.

   Another indispensable transcription factor involved in embryogenesis is
   LEC1. LEC regulates embryo development and is required for normal
   development during the morphogenesis and maturation stages in
   Arabidopsis [[161]24, [162]25]. Studies on the functions of LEC
   demonstrated that LEC was required to specify the suspensor cell fate
   and cotyledon identity during early embryogenesis [[163]26, [164]27].
   However, during late embryogenesis, LEC was required for the
   acquisition of desiccation tolerance and the expression of many
   maturation-specific genes [[165]28]. Our findings showed that LEC1 was
   expressed mainly in cross I, especially in NE18 (Fig. [166]3 and
   Table [167]6), and was significantly reduced in cross II
   (Table [168]6). However, there was no significant difference in NE12
   between the two crosses. This LEC1 expression suggested it might be a
   transcriptional regulator of chrysanthemum seed development and
   required for normal early stage embryo development. Moreover, a
   deficiency in LEC1 during the late development stage might cause the
   seeds to lose their desiccation tolerance, resulting in abnormal
   development or abortion in the C. morifolium × diploid C. nankingense
   cross.

Expression of other genes related to embryo development

   Plant embryogenesis is a complicated process regulated by numerous
   genes and regulators. Moreover, various proteins are synthesized
   steadily, such as late embryogenesis abundant (LEA) protein, embryonic
   protein, oleosin and proteins related to senescence or cell death. In
   plants, the LEA protein is associated with desiccation tolerance during
   embryo maturation when seeds undergo a developmentally regulated
   dehydration period. A study found that an A. thaliana mutant with a
   T-DNA insertion allele of the AtEM6 gene belonging to the group 1 LEA
   family might be required for normal seed development. Studies on
   regulation and expression patterns indicated that the LEA genes in
   diverse species, such as rice, barley and soybean, were primarily
   expressed in developing or mature embryos [[169]29], whereas OsLEA1a
   transcripts accumulated to high levels in dried mature embryos
   [[170]30]. Here, LEA expression in NE18 from cross I was higher than
   that from cross II (Fig. [171]3), suggesting that the LEA proteins were
   required for normal seed development and expressed primarily at the
   late embryonic stage, when they might function as a buffer to protect
   from the water loss that occurs during embryo maturation. Therefore,
   more LEA proteins were expressed at NE18 when tetraploid C. nankingense
   was the male parent, which might be one reason that we were able to
   obtain seeds.

   In dicotyledons, seed storage proteins (SSPs) mainly accumulate in the
   endosperm [[172]31], including the 7S and 11S globulin classes
   [[173]32]. Arabidopsis lec mutants exhibit defective synthesis and the
   accumulation of specific storage molecules, including SSPs [[174]28].
   Additionally, oleosins, which are seed-specific lipid storage proteins,
   have specific functions in seed tissues controlling oil body structure
   and lipid accumulation [[175]33]. We showed that the expression levels
   of the embryonic protein (CmEM), 11S globulin seed storage protein
   (CmSSP) and oleosin (CmOLE) were all most abundant in NE18 in cross I,
   and their expression in both NE12 and NE18 was substantially higher
   than that in cross II (Fig. [176]3). This analysis provides evidence
   that more storage proteins accumulated quickly during the phase from 12
   – 18 DAP when the interspecific cross occurred between the hexaploid C.
   morifolium and tetraploid C. nankingense. Thus, these specific proteins
   might contribute to the completion of embryonic development and
   maturation.

   In contrast, particular genes and proteins related to senescence or
   cell death had different expression patterns and were down-regulated in
   cross I. Previous evidence indicated that programmed cell death
   occurred concomitantly with the development of the embryo and endosperm
   [[177]16, [178]34, [179]35]. In this study, genes related to programmed
   cell death in NE12 (Table [180]5) and the senescence-induced receptor
   and regulator of cell death in NE18 (Table [181]6) were down-regulated
   in the C. morifolium × tetraploid C. nankingense cross. However, the
   gene defender against cell death (Unigene9484) was up-regulated,
   suggesting that chromosome doubling of the male parent might
   epigenetically inhibit the expression of senescence-induced genes and
   cause normal embryo development.

Conclusions

   We sequenced and characterized the transcriptome and proteome of normal
   and abnormal chrysanthemum ovules and analyzed the differentially
   expressed genes and proteins associated with embryogenesis in two
   interspecific crosses in which the female was diploid or tetraploid.
   The comparative analysis of the two crosses demonstrated important
   roles for energy metabolism, auxin signal transduction, transcription
   factors and proteins related to cell death during chrysanthemum embryo
   development. The results provide valuable evidence at the molecular
   level that doubling the chromosome number in C. nankingense might
   overcome the distant hybridization barrier in the cultivated
   chrysanthemum.

Methods

Plant materials and artificial hybridization

   The chrysanthemum ‘Yuhualuoying’ (2n = 6X = 54) (Fig. [182]7a, b) is a
   ground-cover cultivar with desirable ornamental traits for landscape
   applications. The tetraploid C. nankingense (2n = 4X = 36)
   (Fig. [183]7c, d) has a stronger tolerance to both abiotic and biotic
   stresses and is an autopolyploid generated by colchicine doubling of
   the diploid C. nankingense (2n = 2X = 18) [[184]36] (Fig. [185]7e, f).
   The plants were grown in the Chrysanthemum Germplasm Resource
   Preserving Center, Nanjing Agricultural University, China. The
   interspecific cross C. morifolium × tetraploid C. nankingense was
   performed according to a previously reported method [[186]37]. For
   abundant and high quality samples, we planted a total of 60
   chrysanthemum plants in three areas to generate approximately 1500
   inflorescences (18-23 female ligulate florets or ray florets containing
   one ovule per inflorescence) for artificial hybridization. At the same
   time, the interspecific cross C. morifolium × diploid C. nankingense
   was performed with approximately 100 inflorescences to generate the
   seed setting rate statistics. Statistical analyses for the seed setting
   rate was performed with a one-way analysis of variance using SPSS
   version 20.0 (IBM SPSS Statistics, IBM Corporation, Chicago, IL), and
   the means were compared using Student’s t-test with alpha = 0.05.

Fig. 7.

   Fig. 7
   [187]Open in a new tab

   Flower morphology of C. morifolium ‘Yuhualuoying’ tetraploid C.
   nankingense and diploid C. nankingense. a, b C. morifolium
   ‘Yuhualuoying’. c, d Tetraploid C. nankingense. e, f Diploid C.
   nankingense. Bar = 1 cm

Sample preparation and RNA extraction

   We collected chrysanthemum ovules during two developmental stages. At
   12 DAP, almost all of the embryos were normal; therefore, we collected
   0.6 g of normal ovules from each of the three planted areas, (0.2 g was
   stored separately, and the remaining three 0.4 g samples were mixed for
   NE12). Thereafter, the proportion of normal embryos was gradually
   reduced concomitant with embryonic development. At 18 DAP, some embryos
   reached the heart-shaped embryo stage, whereas others underwent
   degeneration; therefore, we collected more than 1.0 g of normal and
   abnormal ovules identically to NE12. All of the samples were
   immediately frozen in liquid nitrogen and stored at -80 °C.

   Meanwhile, for TEM observation, we collected the ovules from NE12, NE18
   and AE18 from cross I, and immediately immersed them in 2.5 % (v/v)
   glutaraldehyde (in 0.1 mol/L phosphate buffer, pH 7.2), gently
   extracted the air using a syringe, and then stored the sample at 4 °C.
   Next, the ovules were washed five times in the same phosphate buffer
   and post-fixed in 1.5 % osmium tetroxide for 5 h. Then the ovules were
   treated in graded PHEM buffer (60 mmol/L pipes; 25 mmol/L Hepes;
   10 mmol/L EGTA; 2 mmol/L MgCl2; pH 7. 0) and 100 % ethanol, and then
   embedded in Epon 812. The sections were cut into 80 nm thickness using
   an LKB-V ultramicrotome (Bromma, Sweden) and stained with uranyl
   acetate and lead citrate. Finally, the sections were imaged under a
   transmission electron microscope (Hitachi H-7650) at 80 kV [[188]38].
   Total RNA was isolated using TRIzol reagent according to the
   manufacturer’s protocol (Takara Bio Inc., Otsu, Japan). The RNA
   quantity and quality were determined using an Agilent 2100 RNA 6000 Kit
   (Agilent Technologies, Santa Clara, CA, USA) and electrophoresis on a
   1 % agarose gel.

cDNA preparation and Illumina deep sequencing

   After RNA extraction and DNase I treatment, mRNA was isolated using
   magnetic beads with Oligo (dT) and fragmented in mixed fragmentation
   buffer. Then cDNA was synthesized using the mRNA fragments. Short
   fragments were purified and resolved with EB buffer for end repair and
   single nucleotide A (adenine) addition. Then, the short fragments were
   connected with adapters, and the suitable fragments were selected for
   PCR amplification. The Agilent 2100 Bioanalyses and ABI StepOnePlus
   Real-Time PCR System were used in quantification and qualification of
   the sample library [[189]14]. At last, the libraries were sequenced
   using Illumina HiSeq™ 2000 according to the manufacturer’s instructions
   (Illumina, San Diego, CA, USA) [[190]39] at the Beijing Genomics
   Institute [(BGI)-Shenzhen, Shenzhen, China;
   [191]http://www.genomics.cn/index.php].

Filtering raw reads and de novo assembly

   The raw reads produced from sequencing contain adapters and unknown or
   low-quality bases. Therefore, obtaining clean reads by removing the
   unqualified reads is necessary. Then, transcriptome de novo assembly
   was performed with Trinity software [[192]39]. The TGICL program
   (version 2.0; [193]http://sourceforge.net/projects/tgicl) was used for
   de novo assembly of the data by Trinity. This program can splice and
   remove redundant unigenes from each sample’s assembly to acquire
   non-redundant unigenes that are as long as possible. Then, the unigenes
   were divided into two classes by gene family clustering. The first
   clusters were denoted by the prefix CL and the suffix indicating the
   cluster number containing several similar unigenes (more than 70 %) in
   one cluster. The other cluster contained singletons with the prefix
   representing the unigene.

   In the final step, a BlastX alignment (E-value < 0.00001) was performed
   between databases such as NR, Swiss-Prot, KEGG and COG, and the
   directions of the unigenes were decided according to the best alignment
   results. If the results conflicted in the different libraries, the
   sequence direction was determined by the priority order of NR,
   Swiss-Prot, KEGG and COG. If a unigene was not aligned to any of the
   above databases, the software ESTScan [[194]40] was used to predict the
   sequence direction.

Unigene functional annotation

   First, unigene sequences were aligned to protein databases including
   NR, Swiss-Prot, KEGG and COG by BlastX and to the nucleotide database
   NT by BlastN. Then, the putative functional annotations of the unigenes
   were retrieved. Next, we used the Blast2GO program [[195]40] to obtain
   gene ontology (GO) ([196]http://www.geneontology.org) annotations of
   the unigenes based on the NR annotations. After GO annotations were
   obtained for each unigene, WEGO software [[197]41] was used to obtain
   GO functional classifications for all unigenes. GO has three
   ontologies: molecular function, cellular component and biological
   process. Finally, we used the KEGG database to study the genes’
   functions in cellular processes and obtain pathway annotation for the
   unigenes based on KEGG annotation.

Differential unigene expression analysis

   To predict unigene expression levels in different samples, we
   calculated the unigene expression levels using FPKM [[198]42]. After
   the calculation, rigorous algorithms were used to identify
   differentially expressed genes between the two samples by referring to
   the Audic and Claverie’s method [[199]43]. In our analysis, these DEGs
   met the criteria of an FDR ≤ 0.001 and ratio larger than 2. Then, GO
   functional analysis and KEGG pathway analysis were performed for the
   DEGs.

   In the GO functional analysis, all of the DEGs were mapped to each term
   of the GO database and the gene numbers associated with each GO term
   were calculated. After obtaining a gene list and gene numbers for each
   included GO term, we used the hypergeometric test to identify
   significantly enriched GO terms in the DEGs compared to the genome
   background. In KEGG pathway analysis, pathway enrichment analysis
   identifies significantly enriched metabolic pathways or signal
   transduction pathways that involve the DEGs compared with the whole
   genome background.

Quantitative real-time PCR analysis

   To ensure the libraries’ reliability, we randomly selected 29
   differentially expressed genes and validated the data by qRT-PCR using
   three biological replicate samples. The qRT-PCR assays were conducted
   as described by Song et al [[200]44] on a Mastercycler ep realplex
   device (Eppendorf, Hamburg, Germany). In addition, qRT-PCR also
   performed on the 40 DEGs shown in Tables [201]5 and [202]6 using three
   biological replicates from two crosses. Gene-specific primers
   (sequences shown in Additional file [203]7: Table S3) were designed
   using PRIMER3 RELEASE 2.3.4 [[204]45]; the reference sequence for the
   quantitative expression analysis was the Elongation Factor 1a (EF1a)
   gene, which is stably expressed in chrysanthemum [[205]16, [206]46].
   Relative transcript abundances were calculated using the 2^−ΔΔCt method
   [[207]47].

Protein preparation, sample labeling and iTRAQ analysis

   For each sample, approximately 0.5 g of ovules was used for protein
   extraction by the trichloroacetic acid/acetone method [[208]48]. The
   extracted proteins were acetone precipitated and redissolved in
   dissolution buffer [[209]16]. The protein concentration was determined
   according to the Bradford assay. Prior to digestion, 100 μg of protein
   from each sample was denatured and alkylated and the cysteines were
   blocked according to the 8-plex iTRAQ reagent kit instructions (Applied
   Biosystems, California, USA). Then, the protein was digested [[210]16].
   The NE12, NE18 and AE18 samples were labeled with 113, 119, and 121
   iTRAQ tags, respectively. The three labeled samples from each
   individual replicate experiment were combined and vacuum-dried. The
   pooled sample was resuspended in the SepPac™ C18 cartridge
   (1 cm^3/50 mg, Waters Corporation, Milford, MA, USA) to remove the salt
   buffer and re-dissolved in a low salt buffer [[211]16]. Then, the
   proteins were separated by Poly-LC strong cation exchange
   chromatography using a PolySULFOETHYL A (2.1 × 100 mmi.d.) HPLC column
   (PolyLC Inc, Columbia, MD, USA). The peptide mixture was collected
   using a high salt buffer [[212]16] for elution. After the acetonitrile
   was volatilized, excess KCl was removed by the SepPac™ C18 cartridge,
   and the sample was dried in a vacuum concentrator.

   Next, the peptide mixture was re-dissolved in buffer A [[213]16] and
   fractionated by high pH separation using a Shimazu UFLC system
   (Shimazu, Kyoto, Japan). The high-pH separation was performed using a
   four-step linear gradient (5 % B for 30 min, 35 % B for 30 min, 80 % B
   for 2 min, and 5 % B for 2 min; B, 20 mM NH[4]HCO[2] in 90 %
   acetonitrile, pH 10.0, adjusted with NH[4]OH). The peptides were eluted
   from the LC column at a flow rate of 200 μL/min. A total of 15
   fractions were collected and dried in a vacuum concentrator for the
   next step.

Mass spectrometry analysis

   Mass spectrometric analysis of the iTRAQ-labeled samples was performed
   on a Nano Aquity UPLC system (Waters Corporation, Milford, MA, USA)
   connected to an LTQ Orbitrap XL mass spectrometer (Thermo Electron
   Corp., Bremen, Germany) equipped with an online nanoelectrospray ion
   source (Michrom Bioresources, Auburn, CA, USA). The detailed steps were
   described previously [[214]16].

Database searches and analysis

   Protein identification and quantification for the iTRAQ experiment were
   performed with ProteinPilot software version 4.0 (Applied Biosystems)
   [[215]49]. The resulting dataset was auto-bias corrected to remove any
   variations caused by unequal mixing when combining differently labeled
   samples. For iTRAQ quantitation, the peptide for quantification was
   automatically selected by the Pro Group algorithm (at least two
   peptides with 99 % confidence) to calculate the reporter peak area,
   error factor (EF), and p-value. For the selection of differentially
   expressed proteins, we considered the following situations: (1) the
   proteins must contain at least two unique high-scoring peptides and (2)
   the proteins must have a p-value < 0.05, and the proteins identified
   with mass tag changes ratio must be ≥ 1.3 or ≤ 0.75.

Abbreviations

   AE18, abnormal embryo at 18 DAP; ARF, auxin response factor; COG,
   clusters of orthologous groups of proteins; DAP, days after
   pollination; DEGs, differentially expressed genes; DEPs, differentially
   expressed proteins; FPKM, fragments per kb per million fragments; GO,
   gene onotology; KEGG, Kyoto Encyclopedia of genes and genomes; NE12,
   normal embryo at 12 DAP; NE18, normal embryo at 18 DAP; qRT-PCR,
   quantitative real-time PCR; TCA, tricarboxylic acid cycle; TEM,
   transmission electron microscopy

Acknowledgements