Next Article in Journal
Comprehensive Analysis of Subcellular Localization, Immune Function and Role in Bacterial wilt Disease Resistance of Solanum lycopersicum Linn. ROP Family Small GTPases
Next Article in Special Issue
Genome-Wide Association Study in Bread Wheat Identifies Genomic Regions Associated with Grain Yield and Quality under Contrasting Water Availability
Previous Article in Journal
Comparative Study on Selected Properties of Modified Polyurethane Foam with Fly Ash
Previous Article in Special Issue
Transcriptional Analysis on Resistant and Susceptible Kiwifruit Genotypes Activating Different Plant-Immunity Processes against Pseudomonas syringae pv. actinidiae
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
IJMS
Volume 23
Issue 17
10.3390/ijms23179726
ijms-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Transcriptome Analysis and Gene Expression Profiling of the Peanut Small Seed Mutant Identified Genes Involved in Seed Size Control

by
Fengdan Guo
1,2,
Xiujin Zhu
1,3,
Chuanzhi Zhao
1,
Shuzhen Zhao
1,
Jiaowen Pan
1,
Yanxiu Zhao
3,
Xingjun Wang
1 and
Lei Hou
1,3,*
1
Institute of Crop Germplasm Resources, Shandong Academy of Agricultural Sciences, Shandong Provincial Key Laboratory of Crop Genetic Improvement, Ecology and Physiology, Jinan 250100, China
2
Institute of Chinese Medicine Resources, Shandong Academy of Chinese Medicine, Jinan 250014, China
3
College of Life Sciences, Shandong Normal University, Jinan 250014, China
*
Author to whom correspondence should be addressed.
Int. J. Mol. Sci. 2022, 23(17), 9726; https://doi.org/10.3390/ijms23179726
Submission received: 12 July 2022 / Revised: 23 August 2022 / Accepted: 24 August 2022 / Published: 27 August 2022
(This article belongs to the Special Issue Plant Genetics and Breeding Research Progress in Genomics to Post-genomics Era)
Browse Figures
Versions Notes

Abstract

:
Seed size is a key factor affecting crop yield and a major agronomic trait concerned in peanut (Arachis hypogaea L.) breeding. However, little is known about the regulation mechanism of peanut seed size. In the present study, a peanut small seed mutant1 (ssm1) was identified through irradiating peanut cultivar Luhua11 (LH11) using 60Coγ ray. Since the globular embryo stage, the embryo size of ssm1 was significantly smaller than that of LH11. The dry seed weight of ssm1 was only 39.69% of the wild type LH14. The seeds were wrinkled with darker seed coat. The oil content of ssm1 seeds were also decreased significantly. Seeds of ssm1 and LH11 were sampled 10, 20, and 40 days after pegging (DAP) and were used for RNA-seq. The results revealed that genes involved in plant hormones and several transcription factors related to seed development were differentially expressed at all three stages, especially at DAP10 and DAP20. Genes of fatty acid biosynthesis and late embryogenesis abundant protein were significantly decreased to compare with LH11. Interestingly, the gene profiling data suggested that PKp2 and/or LEC1 could be the key candidate genes leading to the small seed phenotype of the mutant. Our results provide valuable clues for further understanding the mechanisms underlying seed size control in peanut.

1. Introduction

Peanut (Arachis hypogaea L.), an important oil crop, is widely grown around the world. Peanut seeds are rich in oil, protein, and many other nutritional components, such as resveratrol, isoflavones, vitamin, and biotin [1]. Seed size is a key factor affecting peanut yield and quality. Studies in Arabidopsis (Arabidopsis thaliana), rice (Oryza sativa L.), and other species have identified several signaling pathways and key genes that control seed size [2,3,4,5,6]. In peanut, there are studies that reported the identification of QTLs related to seed size through different approaches [4,5,6]. However, the molecular mechanism and regulatory networks underlying peanut seed size is still unclear.
Seed size is determined by coordinated growth of maternal integument, endosperm, and embryo. Several signaling pathways, such as the G-protein signaling pathway, mitogen-activated protein kinase (MAPK) signaling pathway, ubiquitin-proteasome signaling pathway, and HAIKU (IKU) pathway, have been identified to regulate seed size [7]. IKU1, IKU2, MINI3, and the upstream regulator Short Hypocotyl under Blue 1 (SHB1) play positive roles and increase seed size through promoting the growth of endosperm [8,9,10]. The legume seed development includes three typical stages: embryo morphogenesis phase, storage phase, and desiccation phase [11,12]. ABA play vital roles in seed development. During early embryo development, ABA promotes embryo growth [13]. The mutation of key genes in ABA biosynthesis and signaling transduction pathways led to defect of early embryogenesis in Arabidopsis [14]. During the seed maturation, ABA appear to promote accumulation of storage reserves [15]. Auxin and cytokinin also play critical roles in plant embryogenesis. Auxin responsive factor 2 (ARF2) plays negative roles in seed development and the mutant arf2 seeds are larger than the wild type control [16]. The mutation of cytokinin receptor genes could also generate larger seeds in Arabidopsis [17]. However, mutation of genes in brassinosteroid (BR) signaling pathway led to dwarf plant and small seeds [18,19,20,21,22].
Several transcriptional regulators are also involved in the regulation of seed size, such as ABI3, FUS3, LEC1, and LEC2 [15,23]. LEC1 could regulate gene expression during seed maturation by affecting the expression levels of ABI3, FUS3, and WRI1 [24,25]. WRI1 encodes a putative AP2/EREBP transcription factor. The mutant wri1-1 in Arabidopsis and the knockout line of TaWRI1L2 in wheat both produced small, wrinkled seeds with reduced oil accumulation [26,27]. Plastidial pyruvate kinase (PKp) is the key rate-limiting enzyme in glycolysis and provides acetyl-CoA for de novo synthesis of fatty acids [28]. The expression of PKp was directly or indirectly regulated by LEC1 and WRI1 [25,29]. The mutation of pkp1 and pkp2 in Arabidopsis led to defect in embryo elongation and produced small, wrinkled seeds with only 30%~50% fatty acid content of the WT seeds [30]. AP2/EREBP is a major transcription factor family that determines floral organ characteristics. Loss of function or suppression of AP2 gene expression in Arabidopsis resulted in enlarged integument cells and seeds [31]. The mutation of ANT, an AP2-like gene, resulted in small seeds [32]. WRKY transcription factors play important roles during seed development and eventually affect seed size. In Arabidopsis, the mutation of MINI3 which encodes a WRKY10 produced seeds with significantly reduced size [9]. The mutation of TTG2, another WRKY family member, resulted in small seed due to the restricted endosperm growth and integument cell elongation [33]. Previous studies demonstrated that B-class MADS-box transcription factors are negative regulators on seed size. The loss of function of these genes led to large seeds in Arabidopsis or long grains in rice [34,35,36,37].
To date, no gene that regulates seed size has been identified in peanut yet. To understand the molecular regulation mechanism of peanut seed size and search for the gene controlling peanut yield and quality, we identified a small seed mutant1 (ssm1) through irradiating peanut cultivar Luhua11 (LH11) using 60Coγ ray. In the present study, the phenotypic characteristics, endogenous hormone levels, and seed transcriptome of ssm1 were investigated. The results provided valuable information for candidate genes identification and understanding the molecular mechanism underlying seed size regulation in peanut.

2. Results

2.1. SSM1 Mutant Acquisition, Genetic and Phenotypic Analyses

A peanut mutant with small pod and small seed was named ssm1. It was identified from a mutant population induced by 60Co γ-ray radiation using cultivar Luhua 11 (LH11). Compared with LH11, the pod and seed of ssm1 were significantly smaller, and the seed coat was wrinkled with darker color. At maturity, the length, width, and weight of the pod of ssm1 decreased significantly. The pod and seed dry weight of ssm1 were only 35.04% and 39.69% of the control LH11, respectively (Figure 1a,b). At different development stages, the pod and seed weight of ssm1 were all much smaller than that of LH11. For example, the fresh weight of ssm1 seeds was reduced by 57.01%, 76.20%, 72.71%, 62.58%, and 55.67% compared with LH11 at DAP10 to DAP50 stages, respectively (Figure 1c–f). The oil content of dry seeds of ssm1 was 46.7%, which was 13.53% less than that of LH11. The protein content of ssm1 was 22.60%, which was similar to that of LH11.
The germination rate and germination potential of ssm1 were only 86.44% and 77.97% of LH11. The peanut seed development is not synchronized and that makes it difficult for investigate the phenotype of the seed in F2 population. To overcome this difficulty, we modified the phenotyping method in this study. We planted each F2 plant and harvested a number of F3 seeds, then the seed size of F3 seeds was investigated. If the F3 seeds in one plant are all small in size, we considered the genotype of the corresponding F2 seed/plant as a small seed homozygote mutant. In generation of Tif × ssm1 cross, the F2 large seeds to small seeds ratio (L/S) is 4.52:1 (1212 large seed plants and 268 small seed plants). The low germination rate of the small seeds (77.97%) could be the major reason that caused the deviation of L/S from 3:1. The mutant is inherited stably, and we speculated that small seed trait is controlled by a single gene.

2.2. Comparison of Early Embryo Development

In order to investigate the difference between the embryo development of ssm1 and LH11, embryos at different developmental stages were observed (Figure 2). Tissue sections showed that the trend of embryo development of ssm1 was consistent with LH11, but the size of embryo was smaller than LH11 significantly. The embryo at DAP0 was in the rod-like pro-embryo stage, and there was no significant difference between ssm1 and LH11. At DAP3, the embryo size was similar to that of DAP0 embryo in both ssm1 and LH11. At DAP6, the embryo of ssm1 and LH11 were both at the globular stage, but the embryo size of ssm1 was much smaller than LH11. At DAP10 and DAP20, the embryos of ssm1 were significantly smaller than that of LH11. A space between the ovule and ovary wall was observed in ssm1 due to the inconsistent development of the ovule and ovary, which was not occurred in LH11. The results indicated that ssm1 was different from LH11 during early embryo development from the globular stage, and the embryo was smaller than LH11.

2.3. Changes of Endogenous Hormone Content in SSM1

Endogenous auxin, cytokinin, and abscisic acid (ABA) concentrations were determined in ssm1 and LH11 seeds of DAP20 (Figure 3). Indole-3-acetic acid (IAA) in ssm1 was only 40.57% of that in LH11, while the content of a storage form of 1-O-indole-3-yl acetyl glucose (IAA-Glc) in ssm1 was much higher than that in LH11. Trans-zeatin (tZ) and trans-zeatin riboside (tZR) are the main active cytokinins, and their content in ssm1 were about 47.01% and 54.80% of that in LH11, respectively. The content of ABA and ABA-glucosylester (ABA-GE) in ssm1 seeds were significantly reduced at only 43.43% and 20.16% of that in LH11, respectively.

2.4. Transcriptome Differences between SSM1 and LH11 during Seed Development

In order to understand the changes at the transcription level, RNA-seq of seeds in different developmental stages were carried out. A total of 390.36 million raw reads were generated in this study (Supplementary Table S1). From each sample, we got 21.63 million clean reads on average. The average mapping ratio of clean reads to the reference genome and reference genes were 95.87% and 81.75%, respectively. The results showed that the reads were evenly distributed in each region of the transcripts, indicating that the sequencing data could accurately reflect the gene expression level. In total, 8192, 3677, and 2372 differentially expressed genes (DEGs) were identified in DAP10, DAP20, and DAP40 seeds between ssm1 and LH11, respectively (Figure 4; Supplementary Table S2). At DAP10, the number of DEGs was the largest, with 3209 and 4983 up-regulated and down-regulated genes in ssm1, respectively.
To gain insights into the functional categories of the DEGs between ssm1 and LH11, Gene Ontology (GO) enrichment analysis were conducted. The DEGs were classified into three main categories: biological process, cellular component, and molecular function (Figure 5). Cellular process and metabolic process were the top two terms in the biological process. In the cellular component category, DEGs were mainly distributed in terms of cell, membrane, membrane part, and organelle. The most abundant terms in the molecular function were catalytic activity and binding, which indicated that the mutants had a high degree of gene changes involved in binding and catalytic processes. At DAP10, 505 and 329 genes were annotated as the nucleus and DNA binding terms, respectively, most of which were transcription factors. At DAP20, the DEGs were enriched significantly in the synthesis and metabolism of nutriments, including fatty acid, carboxylic acid, lipid, and organic acid, etc. At DAP40, the enriched terms included carbohydrate, polysaccharide metabolic process, monolayer-surrounded lipid storage body, and nutrient reservoir activity, which were involved in nutrient accumulation.
Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis classified the DEGs into 132, 132, and 127 metabolic pathways at DAP10, DAP20, and DAP40, respectively (Supplementary Table S3). At DAP10, plant hormone signal transduction pathway was the most abundant pathway. Diterpenoid biosynthesis, tryptophan metabolism, and brassinosteroid biosynthesis were observed in the top 20 enriched pathways (Figure 6), which indicated that hormones were changed significantly in ssm1. At DAP20, fatty acid synthesis and metabolism was the most abundant pathway, and sugar metabolism related pathways such as glycolysis/gluconeogenesis and some amino acids metabolism were also enriched. These results suggested that the pathways related to nutrient accumulation were the main difference between ssm1 and LH11. At DAP40, flavonoid biosynthesis was the most enriched pathway, and metabolism pathways of starch, sucrose, and some amino acids were also enriched. In addition, plant hormone signal transduction and mitogen-activated protein kinase (MAPK) signaling pathway were also enriched at DAP20 and DAP40.

2.5. Genes Expression Changes in Hormone Biosynthesis and Signal Transduction

Plant hormones play important roles in the regulation of seed development. RNA-seq results showed that the expression of auxin synthesis-related genes was significantly different in ssm1 (Supplementary Table S4). Tryptophan aminotransferase of Arabidopsis 1/tryptophan aminotransferase related (TAA1/TARs) and YUCCA are the key enzymes in the indole-3-pyruvic acid pathway of auxin biosynthesis. One TAA1/TAR gene showed decreased expression at DAP10 in ssm1, which was 41% of the expression level of LH11. The expression of six YUCCA family genes were up-regulated at DAP10 and DAP20. Amidase (AMI) catalyzed indole-3-acetamide (IAM) to generate IAA, and the expression levels of two AMI1 genes were significantly reduced. ALDH is the key enzyme catalyzing indole-3-acetaldehyde (IAAld) to IAA. The expression level of six ALDH genes in DAP10 and DAP20 of ssm1 seeds were down-regulated to compare with LH11, which was consistent with the decreased IAA content in ssm1 seeds. UDP-glycosyltransferases (UGTs) are responsible for catalyzing auxin glycosylation. At DAP10, the expression of four UGTs decreased in ssm1, while the expression of four other UGTs increased significantly at DAP20, which was consistent with the high content of IAA-Glc in ssm1 seeds at DAP20. All five SAUR genes were down-regulated in ssm1 seeds at DAP10 and DAP20. The expression levels of the majority auxin response factors (ARF) genes were decreased more than one-fold in DAP10 and DAP20. Two auxin receptors TIR1 genes were also down-regulated in ssm1. Except for YUCCAs, the expression changes of these genes were consistent with the decreased IAA content in ssm1 seeds at DAP20, while these auxin synthesis and response genes were not changed obviously at DAP40.
DEGs in ABA synthesis and signal transduction pathways between ssm1 and LH11 seeds at DAP10, DAP20, and DAP40 showed an overall trend of down-regulation. Most ABA biosynthesis genes were significantly decreased in ssm1 seeds to compare with LH11, for example, beta-carotene 3-hydroxylase (BCH1), 9-cis-epoxycarotenoid dioxygenase (NCED), and ABA deficient 2/short-chain dehydrogenase reductase 1(ABA2/SDR). The CYP707A2 genes involved in ABA degradation were down-regulated at DAP10 and DAP40, but up-regulated in DAP20. ABA glucosyltransferase is responsible for catalyzing ABA glycosylation, and the expression level of four coding genes in ssm1 were all down-regulated at DAP10 and DAP20. The expression trends of these genes were consistent with the reduced trends of ABA-GE content at DAP20. The expression levels of the important transcription factor ABI5 in ABA signaling pathway were lower in ssm1 seeds than those in LH11, indicating that ABA signal transduction was also affected in ssm1 seeds.
Cytokinins (CKs) play key roles in plant growth and development. The levels of endogenous CKs in plants are influenced by isopentenyl transferases (IPT), cytochrome P450 monooxygenase (CYP735A), cytokinin oxidase/dehydrogenase (CKX), and other biosynthetic and degrading enzymes. The expression levels of three CYP735A genes up-regulated in ssm1; however, the expression level of most of the CKX genes, which degraded CKs, were increased in ssm1 seeds at three developmental stages. The increased expression of CKX genes in ssm1 presumably was the cause of the decrease of CKs in ssm1. Meanwhile, the expression of receptor CRE1 genes in CKs signal transduction were down-regulated in ssm1 seeds.
The expression levels of biosynthesis and signal transduction genes of brassinolide (BR) and gibberellin (GA) also changed in ssm1 seeds. The expression levels of most genes that catalyze BRs biosynthesis in ssm1 seeds at DAP10 and DAP20 were significantly lower than those of LH11, including DWF4/CYP90B1, CPD/CYP90A1, CYP90C1/D1, and Dwarf/CYP85A1. The expression of BES1/BZR1, a key transcription factor in BRs signal transduction, was decreased in ssm1 seeds at all three developmental stages. The key enzyme genes KAO and KO that catalyze GAs biosynthesis were down-regulated in ssm1 seeds at DAP10 and DAP20, and the expression of some GA20ox were down-regulated; however, the expressions of other GA20ox genes with low expression background were up-regulated. DELLA protein and GA receptor GID1 genes were down-regulated in ssm1 seeds at DAP10 and DAP20. These results indicated that BR and GA biosynthesis and signaling were affected in ssm1 seeds.

2.6. Genes Expression Changes of Storage Materials

The genes encoding key enzymes involved in fatty acid synthesis and metabolism including acetyl-CoA carboxylase (ACCase), acyl carrier protein 1 (ACP1), beta-ketoacyl-ACP synthase (KAS), and diacylglycerol acyltransferase (DGAT) were significantly down-regulated in ssm1 seeds to compare with LH11 at three developmental stages (Figure 7a,b). Plastic pyruvate kinase (PKp) and fructose-1,6-bisphosphatase (FBP) are the key enzymes in the glycolysis pathway, which provides the substrate acetyl-coA for the de novo synthesis of fatty acids. The expression of all PKp and FBP genes were significantly decreased in ssm1 seeds (Figure 7a). Late embryogenesis abundant proteins (LEA) are abundantly accumulated in seeds during late embryonic development. Arachin, vicilin, legumin, and dormancy-associated proteins are also important storage proteins in seeds. The expression of all these genes encoding these proteins in ssm1 seeds at DAP10, DAP20, and DAP40 were significantly decreased compared to LH11 (Figure 7d).

2.7. The Expression Changes of Transcription Factor Genes

RNA-seq analysis showed that the expression level of LEC1, AP2/EREBP, FUS3, ABI3, and GRF transcription factors encoding genes were significantly down-regulated in ssm1 of at DAP10 and DAP20 to compare with those of LH11, while the expression level of SPL and MADS-Box transcription factor genes were up-regulated in ssm1 (Supplementary Table S5). The IKU pathway positively regulates seed development by regulating endosperm growth. The expression level of IKU1 and IKU2 genes in ssm1 seeds at DAP10 were significantly lower than those of LH11, while the expression of some IKU2 genes were up-regulated in ssm1 seeds at DAP40. The expression of RAV1, which negatively control IKU2 expression in Arabidopsis, were up-regulated at DAP10 and DAP20 and down-regulated at DAP40 in ssm1 seeds.

2.8. Verification of DEGs Using qRT-PCR

To validate the RNA-seq results, 12 DEGs were randomly selected for qRT-PCR analysis. These genes include transcription factor genes, storage protein genes, and genes related to hormone biosynthesis and signal transduction. The qRT-PCR results of these genes were found in accordance with the relative expression levels obtained from RNA-seq. The correlation coefficients between qRT-PCR and RNA-seq data at DAP10, DAP 20, and DAP40 were 0.9059, 0.9253, and 0.9068, respectively (Figure 8 and Supplementary Table S6).

3. Discussion

The mechanism of seed size regulation has been extensively studied in Arabidopsis and many crops. However, little is known about the regulation mechanism of peanut seed size. In this study, ssm1 had decreased oil content and the seed size was significantly smaller than that of LH11. The differences of ovule and embryo size between ssm1 and LH11 become more obvious at DAP10 and DAP20 periods, and the development of seed integument was restricted.
Phytohormones play essential roles in seed development. The RNA-seq data presented in this study showed that genes involved in hormone signaling pathway in ssm1 seeds changed greatly compared with LH11. Most of the catalyzing enzyme genes in ABA or BRs biosynthesis pathways and the regulatory transcription factor genes were down-regulated in ssm1 seeds at three developmental stages, especially in DAP10 and DAP20. These results suggested that ABA and BRs biosynthesis and signaling might decrease in ssm1 seeds at early developmental stage. Our results showed that ABA and ABA-GE content in ssm1 seeds of DAP20 was significantly lower than LH11. Previous studies demonstrated that ABA play critical roles during early seed development through regulating embryonic cell division and endosperm cellularization. ABA-deficient mutant aba2-1 exhibited delayed embryogenesis compared with the wild type [14]. BRs regulate seed size and shape in Arabidopsis. BR-deficient affect seed cavity and endosperm development and eventually the seed size. The embryos of BR deficient mutant det2 were smaller than the wild type control due to the reduced cell size and cell number [20]. SHB1-MINI3-IKU2 cascade was a critical regulator promoting endosperm and embryo development and in Arabidopsis. The mutation of each gene of this cascade resulted in small seeds [9,10,38]. RAV1 is the negative player during early seed development by repressing IKU2 expression. IKU2 expression was significantly inhibited in overexpressing RAV1 transgenic plant which produced small seeds [39]. Both ABA and BR inhibited the expression of RAV1 [40,41]. Consistent with these results, in ssm1, the expression of RAV1 was up-regulated at DAP10 and DAP20, then decreased sharply at DAP40 compared with LH11. The expression profile of IKU2 was opposite to RAV1. Therefore, the reduced levels of ABA and BRs and the elevated expression of RAV1 might have affected the expression of the core components that regulate embryo and endosperm development during the early stage of seed development in ssm1.
Auxin plays key roles during seed development, including embryo pattern formation, cell division, cell expansion, and embryo structure determination and seed size [42,43,44]. Ovule fertilization triggered auxin production, and then functioning in both the maternal tissue and the embryo to drive seed development [44]. In this study, IAA decreased in ssm1 seeds while IAA-Glc increased. IAA sugar conjugates is an inactive form of auxin; UDP-glycosyltransferases (UGTs) catalyze the conjugation of sugar moieties and IAA [45,46,47]. Correspondingly, the expression of four UGT genes up-regulated in ssm1 seeds at DAP20. Small auxin up RNA (SAUR) genes are the largest auxin responsive gene family, regulating auxin mediated cell elongation [48]. All SAUR genes, most ARFs, and the auxin receptor TIR1 were down-regulated in ssm1 seeds at DAP10 and DAP20. It was deduced that the weak IAA biosynthesis and signaling might affect the development of ssm1 embryo and integuments, which results in small seed.
PKp2 catalyzes phosphoenolpyruvate to pyruvate in glycolysis and provides substrate for de novo fatty acid biosynthesis. The PKp2 loss of function affected seed development and seed size. In Arabidopsis pkp2, pkp1pkp2 mutants, the seed oil content reduced 50%~70% [30]. In wri1 mutant with low PKp2 expression, seed oil content decreased 80% [49].
The oil content of ssm1 dry seeds reduced 13.53%. The oleic acid (C18:1) and linoleic acid (C18:2) contents decreased, while the linolenic acid (C18:3) and erucic acid (C22:1) contents increased in ssm1 seed. The variation trend of fatty acid compositions is similar to that in pkp2, pkp1pkp2 mutants. The expression of PKp2 was hardly detected in ssm1 at DAP10 and DAP20. In the promoter of AhPKp2 gene, several hormone response elements including ABA, MeJA, GA, and auxin were identified. The reduced level of ABA and auxin in ssm1 seeds may be the key reason for the reduced expression of PKp2. On the other hand, the functional defects of PKp2 may affect the synthesis of plant hormones. Previous studies showed that loss of function of some enzymes involved in seed development usually affected multiple pathways, including the biosynthesis of plant hormones, overall metabolism, and composition of the storage materials [50,51,52]. Besides entering the fatty acid and starch synthesis pathways, the substrate phosphoenolpyruvate and the product pyruvate of PKp could also enter a variety of metabolic pathways, such as amino acid metabolism, terpene metabolism, and sterol metabolism. These pathways could provide precursors for the biosynthesis of IAA, cytokinins, gibberellin, brassinosteroids, and abscisic acid [53].
Several transcription factors have been proved playing key roles in seed size control. ABA play a key role in embryo maturation by inducing the expression of storage-related genes. Studies have shown that de-regulation of ABA impaired accumulation of storage materials in seed, which is closely related to the transcription factors LEC1, WRI1, ABI3, and FUS3 [24,54,55]. LEC1 act as key regulators to coordinate the expression of fatty acid biosynthetic genes; overexpression of LEC1 increased expression of over 58% of genes in fatty acid biosynthesis pathway. Moreover, genes of Sucrose Synthase 2 (SUS2) and PKp2 were also up-regulated upon LEC1 overexpression. Genetic analysis indicates that the LEC1 function is partially dependent on WRI1, ABI3, and FUS3 in the regulation of fatty acid biosynthesis [55]. Consistent with these results, our RNA-seq results showed that the expression of LEC1, FUS3, ABI3, and many genes involved in fatty acid biosynthesis and metabolism were significantly decreased in DAP10 and DAP20 seeds of ssm1.
Based on these results, we speculated that PKp2 and LEC1 could be the key candidate genes leading to the small seed phenotype of the mutant. Together, we hypothesized that the hormone signaling pathways and transcription factors cooperatively modulate seed development and storage accumulation (Figure 9). How hormones regulate expression of transcription factors and what role LEC1 plays in ssm1 small seed formation are still to be elucidated. To build up the interaction network of LEC1, WRI1, AhPKp2, and the plant hormones would provide useful information for us to understand the regulatory mechanism of peanut seed development.

4. Materials and Methods

4.1. Phenotypic Characteristics of SSM1 Mutant

The peanut mutant library was derived from cultivar Luahua 11 (LH11) through irradiation by 60Co γ-ray. In M2 generation of the library plants, a line with all of the seeds were smaller than LH11 and was screened, which in M3 generation, the small seed phenotypic can be stably inherited. After self-crossing for another two generations, the stable small seed peanut line was obtained and named small seed mutant 1 (ssm1). The peanut seeds were planted in Jiyang Experimental Farm, Shandong Academy of Agricultural Sciences. The pod and seed size and seed weight of ssm1 and LH11 in the same development stage was compared. The seeds were dried in an oven and powdered in a pestle and mortar. The dry seed powder was used to determine the crude protein and oil content by using micro-Kjeldahl method and Soxhlet extraction method, respectively, according to the method described in previous studies [56,57].
The plump peanut seeds of ssm1 and LH11 were selected for germination. Twenty seeds were germinated as one group, and five replicates were used in this study. The seeds were placed into 15 cm petri dish with a layer of filter paper on top and bottom, cultured in an incubator at 25 ± 2 °C under dark condition. The germination rate was calculated every 24 h, and the emergence of radicle was used as the germination standard. Germination potential = (number of germinated seeds at day 3/total number of tested seeds) × 100%; Germination rate = (number of final germinated seeds at day 7/total number of tested seeds) × 100%.

4.2. Paraffin Sectioning

The developing pods at DAP0 (0 day after gynophore penetrated the soil, gynophore above ground, not touching the soil), DAP3 (3 days after gynophore penetrated the soil), and DAP6 (6 days after gynophore penetrated the soil) were collected, respectively. The 0.5~1 cm gynophore tips were collected and approximately 20 gynophores from each stage were used for paraffin sectioning. Samples were fixed immediately in formalin-acetic acid-alcohol (FAA) for 24 h at 4 °C, then washed and dehydrated with a gradient ethanol series (70, 85, 95, and 100%). After dehydration, the tissues were cleared with xylol, embedded in paraffin, and sectioned into 8~10 μm sections. After drying at 37 °C, sections were de-paraffinized and hydrated in an ethanol gradient series (100, 95, 85, 70, 50, 30%, and distilled water) before being stained with toluidine blue O (TBO) reagent. After clearing and mounting, sections were observed under a microscope. Early pods (DAP10 and DAP20) were sliced freehand with double-sided blades and photographed under a stereoscope.

4.3. Determination of Endogenous Plant Hormones

The contents of IAA, cytokinin and ABA were measured with the seed tissues of DAP20 from ssm1 and LH11. Approximately 1.0 g of each sample was rapidly frozen in liquid nitrogen and ground into a powder, then extracted with 1 mL methanol/water/formic acid (15:4:1, V/V/V). The quantification of endogenous phytohormones were conducted according to the manufacturer’s instructions (Wuhan Metware Biotechnology Co., Ltd., Wuhan, China) and using the external standard method. The sample extracts were analyzed using an LC-ESI-MS/MS system (UHPLC, ExionLC™ AD; MS, Applied Biosystems 6500 Triple Quadrupole). The analytical conditions were as follows, HPLC: column, Waters ACQUITY UPLC HSS T3 C18 (100 mm × 2.1 mm i.d., 1.8 µm); solvent system, water with 0.04% acetic acid (A), acetonitrile with 0.04% acetic acid (B); gradient program, started at 5% B (0–1 min), increased to 95% B (1–8 min), 95% B (8–9 min), finaly ramped back to 5% B (9.1–12 min); flow rate, 0.35 mL/min; temperature, 40 °C; injection volume: 2 μL. Three biological replications were performed.

4.4. RNA Extraction, RNA-Seq and Bioinformatic Analyses

The ssm1 and LH11 immature seeds of DAP10 (10 days after gynophore penetrated the soil), DAP20 (20 days after gynophore penetrated the soil), and DAP40 (40 days after gynophore penetrated the soil) were collected for RNA extraction and sequencing. The samples were frozen immediately in liquid nitrogen and stored at −80 °C for RNA extraction using Trizol Reagent Kit (TaKaRa, Inc., Dalian, China). Three biological replicates were used for each sample. Total RNA was used to enrich mRNA with Oligo (dT) and sequenced using BGISEQ-500 platform (BGISEQ-500) at Beijing Genomics Institute (BGI; Shenzhen, China).
After removing the adaptor sequences and low-quality reads by SOAPunke and trimmomatic software, we obtained the clean reads. The sequences were uploaded to Short Read Archive of NCBI. The clean reads were aligned to peanut reference genome (https://www.peanutbase.org/data/public/Arachis_hypogaea/) using HISAT2 program and to reference gene by Bowtie2 [58,59]. The gene expression level was represented with FPKM (Fragments Per Kilobase per Million reads) calculated by RSEM method [60]. Relative gene expression level between ssm1 and LH11 was represented by log2 ratio. The differentially expressed genes (DEGs) were identified using DEseq2 method with fold change ≥ 2 and Q-value (adjusted p-value) ≤ 0.05 [61].
Gene function was annotated by different databases including NCBI non-redundant protein sequences (Nr), gene ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) database. The GO and KEGG enrichment analyses were performed using R software and hypergeometric test. MeV software (version 4.9.0, The Institute for Genomic Research, Rockville, MA, USA, http://mev.tm4.org/) was used to generate the heatmaps.

4.5. Verification of RNA-Seq Data by qRT-PCR

qRT-PCR was used to validate the expression levels of selected genes. RNA samples were those used for RNA-seq, and the reverse transcription was performed using PrimeScript II 1st Strand cDNA Synthesis Kit (TaKaRa). The gene-specific primers were designed using PerlPrimer software (version 1.1.19, Owen Marshall, Parkville, Australia, http://perlprimer.sourceforge.net. Supplementary Table S6). qRT-PCR reaction was performed on ABI7500 Real Time System (Applied Biosystems) using TB Green™ Premix Ex Taq™ II (TaKaRa). The parameters of thermal cycle were 94 °C for 10 min, followed by 40 cycles of 94 °C for 15 s and 60 °C for 1 min. Three biological replications were performed for each reaction with actin gene as internal reference. The relative expression level of each gene between ssm1 and LH11 was calculated by 2−ΔΔCt method.

5. Conclusions

In the present study, a peanut small seed mutant ssm1 was identified through irradiating peanut cultivar LH11 using 60Coγ ray. RNA-seq analysis identified DEGs involved in different pathways, a model for hormone signaling pathways and transcription factors cooperatively modulated seed development in ssm1 was proposed, and the candidate genes leading to small seed size of the mutant was predicted. These results provided information for further understanding the mechanisms regulating seed size in peanut.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/ijms23179726/s1.

Author Contributions

L.H., Y.Z. and X.W. conceived and designed the experiments: L.H., F.G. and X.Z. performed the experiments: L.H. and F.G. analyzed the data; C.Z., J.P. and S.Z. contributed reagents/materials/analysis tools; L.H. and F.G. wrote the manuscript; and X.W. revised. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by grants from the Natural Science Foundation of Shandong Province (ZR2020MC104, ZR2020MC105); National Natural Science Foundation of China (31861143009; 32072090); Key Research and Development Project of Shandong Province (2020LZGC001; 2021LZGC025); Agricultural scientific and technological innovation project of Shandong Academy of Agricultural Sciences (CXGC2022A07; CXGC2022F10); and Taishan Scholar Foundation of Shandong Province (ts20190964).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The RNA-seq data in this study were available at NCBI Short Read Archive with the accession number of PRJNA841457 (https://www.ncbi.nlm.nih.gov/bioproject/PRJNA841457, accessed on 23 May 2022).

Conflicts of Interest

The authors declare no conflict of interest.

Abbreviations

DEGs, Differentially expressed genes; KEGG, Kyoto encyclopedia of genes and genomes; GO, Gene ontology; MAPK, Mitogen-activated protein kinase; Glc-6P, D-Glucose 1-phosphate; PEP, Phosphoenol pyruvate; TAG, Triglyceride; Phe, Phenylalanine; Trp, Tyrosine; MVA, Mevalonic acid; DMAPP, Dimethylallyl diphosphate; GGPP, Geranylgeranyl diphosphate; IAA, Indoleacetic acid; BRs, Brassinolides; CKs, Cytokinins ; ABA, Abscisic acid; GAs, Gibberellic acidS; PKp2, Plastidial pyruvate kinase 2; TAA, Tryptophan aminotransferase; YUC, Indole-3-pyruvate monooxygenase YUCCA; AMI, Amidase; ALDH, Aldehyde dehydrogenase; TIR1, Transport inhibitor response 1; ARF, Auxin response factor; SAUR, Small auxin up RNA; DWF4, 22a-hydroxylase/Cytochrome P450 90B1; CPD, Constitutive photomorphogenic dwarf/Cytochrome P450 90A1; CYP90C1, Cytochrome P450 90C1; 3-epi-6-deoxocathasterone 23-monooxygenase; Dwarf, cytochrome P450 85A; BAK1, BRI1-associated receptor kinase 1; BZR1, Brassinazole resistant 1; CYP735A, cytokinin hydroxylase/Cytochrome P450 735A; CKX, cytokinin dehydrogenase; CRE1, Cytokinin response 1; AHP, Histidine phosphotransfer proteins; ARR, A-type response Regulator; BCH1, beta-Carotene 3-hydroxylase 1; NCED, 9-cis-Epoxycarotenoid dioxygenase; ABA2, ABA deficient 2; ABA3, ABA deficient 3; ABI5, Abscisic acid-insensitive 5; PYL, Pyrabactin resistance 1-Llke; KAO, Ent-kaurenoic acid oxidase; KO, Ent-kaurene oxidase; GA20ox, GA 20-oxidases; GA2ox, GA 2-oxidases; GID1, GA-insensitive dwarf 1; DELLA, Proteins containing conserved DELLA domains in the N terminus; LEC1, Leafy cotyledon 1; WRI1, WRINKLED 1; ABI3, Abscisic acid-insensitive 3; FUS3, FUSC A3; RAV1, Related to ABI3/VP1 1; IKU2, HAIKU2; AP2, APETALA 2.

References

  1. Zhao, X.; Chen, J.; Du, F. Technology: Potential use of peanut by-products in food processing: A review. J. Food Sci. Technol. 2012, 49, 521–529. [Google Scholar] [CrossRef]
  2. Wang, S.; Liu, S.; Wang, J.; Yokosho, K.; Zhou, B.; Yu, Y.C.; Liu, Z.; Frommer, W.B.; Ma, J.F.; Chen, L.Q.; et al. Simultaneous changes in seed size, oil content and protein content driven by selection of SWEET homologues during soybean domestication. Natl. Sci. Rev. 2020, 7, 1776–1786. [Google Scholar] [CrossRef] [PubMed]
  3. Li, N.; Xu, R.; Duan, P.; Li, Y. Control of grain size in rice. Plant Reprod. 2018, 31, 237–251. [Google Scholar] [CrossRef] [PubMed]
  4. Mondal, S.; Badigannavar, A.M. Identification of major consensus QTLs for seed size and minor QTLs for pod traits in cultivated groundnut (Arachis hypogaea L.). 3 Biotech. 2019, 9, 347. [Google Scholar] [CrossRef] [PubMed]
  5. Zhang, S.; Hu, X.; Miao, H.; Chu, Y.; Cui, F.; Yang, W.; Wang, C.; Shen, Y.; Xu, T.; Zhao, L.; et al. QTL identification for seed weight and size based on a high-density SLAF-seq genetic map in peanut (Arachis hypogaea L.). BMC Plant Biol. 2019, 19, 537. [Google Scholar] [CrossRef]
  6. Li, Z.; Zhang, X.; Zhao, K.; Zhao, K.; Qu, C.; Gao, G.; Gong, F.; Ma, X.; Yin, D. Comprehensive transcriptome analyses reveal candidate genes for variation in seed size/weight during peanut (Arachis hypogaea L.) domestication. Front. Plant Sci. 2021, 19, 666483. [Google Scholar] [CrossRef]
  7. Li, S.; Liu, Y.; Zheng, L.; Chen, L.; Li, N.; Corke, F.; Lu, Y.; Fu, X.; Zhu, Z.; Bevan, M.W.; et al. The plant-specific G protein gamma subunit AGG3 influences organ size and shape in Arabidopsis thaliana. New Phytol. 2012, 194, 690–703. [Google Scholar] [CrossRef]
  8. Sun, X.; Shantharaj, D.; Kang, X.; Ni, M. Transcriptional and hormonal signaling control of Arabidopsis seed development. Curr. Opin. Plant Biol. 2010, 13, 611–620. [Google Scholar] [CrossRef]
  9. Luo, M.; Dennis, E.S.; Berger, F.; Peacock, W.J.; Chaudhury, A. MINISEED3 (MINI3), a WRKY family gene, and HAIKU2 (IKU2), a leucine-rich repeat (LRR) KINASE gene, are regulators of seed size in Arabidopsis. Proc. Natl. Acad. Sci. USA 2005, 102, 17531–17536. [Google Scholar] [CrossRef]
  10. Zhou, Y.; Zhang, X.; Kang, X.; Zhao, X.; Zhang, X.; Ni, M. SHORT HYPOCOTYL UNDER BLUE1 associates with MINISEED3 and HAIKU2 promoters in vivo to regulate Arabidopsis seed development. Plant Cell 2009, 21, 106–117. [Google Scholar] [CrossRef] [Green Version]
  11. Weber, H.; Borisjuk, L.; Wobus, U. Molecular physiology of legume seed development. Annu. Rev. Plant Biol. 2005, 56, 253–279. [Google Scholar] [CrossRef] [PubMed]
  12. Borisjuk, L.; Rolletschek, H.; Radchuk, R.; Weschke, W.; Wobus, U.; Weber, H. Seed development and differentiation: A role for metabolic regulation. Plant Biol. 2004, 6, 375–386. [Google Scholar] [CrossRef] [PubMed]
  13. Frey, A.; Godin, B.; Bonnet, M.; Sotta, B.; Marion-Poll, A. Maternal synthesis of abscisic acid controls seed development and yield in Nicotiana plumbaginifolia. Planta 2004, 218, 958–964. [Google Scholar] [CrossRef] [PubMed]
  14. Cheng, Z.J.; Zhao, X.Y.; Shao, X.X.; Wang, F.; Zhou, C.; Liu, Y.G.; Zhang, Y.; Zhang, X.S. Abscisic acid regulates early seed development in Arabidopsis by ABI5-mediated transcription of SHORT HYPOCOTYL UNDER BLUE1. Plant Cell. 2014, 26, 1053–1068. [Google Scholar] [CrossRef]
  15. Finkelstein, R.R.; Gibson, S.I. ABA and sugar interactions regulating development: Cross-talk or voices in a crowd? Curr. Opin. Plant Biol. 2002, 5, 26–32. [Google Scholar] [CrossRef]
  16. Schruff, M.C.; Spielman, M.; Tiwari, S.; Adams, S.; Fenby, N.; Scott, R.J. The gene of links auxin signalling, cell division, and the size of seeds and other organs. Development 2006, 133, 251–261. [Google Scholar] [CrossRef]
  17. Riefler, M.; Novak, O.; Strnad, M.; Schmülling, T. Arabidopsis cytokinin receptor mutants reveal functions in shoot growth, leaf senescence, seed size, germination, root development, and cytokinin metabolism. Plant Cell. 2006, 18, 40–54. [Google Scholar] [CrossRef]
  18. Choe, S.; Tanaka, A.; Noguchi, T.; Fujioka, S.; Takatsuto, S.; Ross, A.S.; Tax, F.E.; Yoshida, S.; Feldmann, K.A. Lesions in the sterol delta 7 reductase gene of Arabidopsis cause dwarfism due to a block in brassinosteroid biosynthesis. Plant J. 2000, 21, 431–443. [Google Scholar] [CrossRef]
  19. Chory, J.; Nagpal, P.; Peto, C.A. Phenotypic and genetic analysis of det2, a new mutant that affects light-regulated seedling development in Arabidopsis. Plant Cell 1991, 3, 445–459. [Google Scholar] [CrossRef]
  20. Jiang, W.B.; Lin, W.H. Brassinosteroid functions in Arabidopsis seed development. Plant Signal Behav. 2013, 8, e25928. [Google Scholar] [CrossRef] [Green Version]
  21. Takahashi, N.; Nakazawa, M.; Shibata, K.; Yokota, T.; Ishikawa, A.; Suzuki, K.; Kawashima, M.; Ichikawa, T.; Shimada, H.; Matsui, M. shk1-D, a dwarf Arabidopsis mutant caused by activation of the CYP72C1 gene, has altered brassinosteroid levels. Plant J. 2005, 42, 13–22. [Google Scholar] [CrossRef] [PubMed]
  22. Tanabe, S.; Ashikari, M.; Fujioka, S.; Takatsuto, S.; Yoshida, S.; Yano, M.; Yoshimura, A.; Kitano, H.; Matsuoka, M.; Fujisawa, Y.; et al. A novel cytochrome P450 is implicated in brassinosteroid biosynthesis via the characterization of a rice dwarf mutant, dwarf11, with reduced seed length. Plant Cell. 2005, 17, 776–790. [Google Scholar] [CrossRef] [PubMed]
  23. Nambara, E.; Marion-Poll, A. ABA action and interactions in seeds. Trends Plant Sci. 2003, 8, 213–217. [Google Scholar] [CrossRef]
  24. Kagaya, Y.; Toyoshima, R.; Okuda, R.; Usui, H.; Yamamoto, A.; Hattori, T. LEAFY COTYLEDON1 controls seed storage protein genes through its regulation of FUSCA3 and ABSCISIC ACID INSENSITIVE3. Plant Cell Physiol. 2005, 46, 399–406. [Google Scholar] [CrossRef] [PubMed]
  25. Pelletier, J.M.; Kwong, R.W.; Park, S.; Le, B.H.; Baden, R.; Cagliari, A.; Hashimoto, M.; Munoz, M.D.; Fischer, R.L.; Goldberg, R.B.; et al. LEC1 sequentially regulates the transcription of genes involved in diverse developmental processes during seed development. Proc. Natl. Acad. Sci. USA 2017, 114, E6710–E6719. [Google Scholar] [CrossRef] [PubMed]
  26. Cernac, A.; Benning, C. WRINKLED1 encodes an AP2/EREB domain protein involved in the control of storage compound biosynthesis in Arabidopsis. Plant J. 2004, 40, 575–585. [Google Scholar] [CrossRef]
  27. Yang, F.; Liu, G.; Wu, Z.; Zhang, D.; Zhang, Y.; You, M.; Li, B.; Zhang, X.; Liang, R. Cloning and functional analysis of TaWRI1Ls, the key genes for grain fatty acid synthesis in bread wheat. Int. J. Mol. Sci. 2022, 23, 5293. [Google Scholar] [CrossRef]
  28. Schwender, J.; Ohlrogge, J.B.; Shachar-Hill, Y. A flux model of glycolysis and the oxidative pentosephosphate pathway in developing Brassica napus embryos. J. Biol. Chem. 2003, 278, 29442–29453. [Google Scholar] [CrossRef]
  29. Baud, S.; Mendoza, M.S.; To, A.; Harscoet, E.; Lepiniec, L.; Dubreucq, B. WRINKLED1 specifies the regulatory action of LEAFY COTYLEDON2 towards fatty acid metabolism during seed maturation in Arabidopsis. Plant J. 2007, 50, 825–838. [Google Scholar] [CrossRef]
  30. Baud, S.; Wuilleme, S.; Dubreucq, B.; de Almeida, A.; Vuagnat, C.; Lepiniec, L.; Miquel, M.; Rochat, C. Function of plastidial pyruvate kinases in seeds of Arabidopsis thaliana. Plant J. 2007, 52, 405–419. [Google Scholar] [CrossRef]
  31. Jofuku, K.D.; Omidyar, P.K.; Gee, Z.; Okamuro, J.K. Control of seed mass and seed yield by the floral homeotic gene APETALA2. Proc. Natl. Acad. Sci. USA 2005, 102, 3117–3122. [Google Scholar] [CrossRef] [PubMed]
  32. Mizukami, Y.; Fischer, R.L. Plant organ size control: AINTEGUMENTA regulates growth and cell numbers during organogenesis. Proc. Natl. Acad. Sci. USA 2000, 97, 942–947. [Google Scholar] [CrossRef]
  33. Johnson, C.S.; Kolevski, B.; Smyth, D.R. TRANSPARENT TESTA GLABRA2, a trichome and seed coat development gene of Arabidopsis, encodes a WRKY transcription factor. Plant Cell. 2002, 14, 1359–1375. [Google Scholar] [CrossRef]
  34. Nesi, N.; Debeaujon, I.; Jond, C.; Stewart, A.J.; Jenkins, G.I.; Caboche, M.; Lepiniec, L. The TRANSPARENT TESTA16 locus encodes the Arabidopsis BSISTER MADS domain protein and is required for proper development and pigmentation of the seed coat. Plant Cell. 2002, 14, 2463–2479. [Google Scholar] [CrossRef] [PubMed]
  35. Erdmann, R.; Gramzow, L.; Melzer, R.; Theissen, G.; Becker, A. GORDITA (AGL63) is a young paralog of the Arabidopsis thaliana Bsister MADS box gene ABS (TT16) that has undergone neofunctionalization. Plant J. 2010, 63, 914–924. [Google Scholar] [CrossRef] [PubMed]
  36. Nayar, S.; Sharma, R.; Tyagi, A.K.; Kapoor, S. Functional delineation of rice MADS29 reveals its role in embryo and endosperm development by affecting hormone homeostasis. J. Exp. Bot. 2013, 64, 4239–4253. [Google Scholar] [CrossRef]
  37. Liu, Q.; Han, R.; Wu, K.; Zhang, J.; Ye, Y.; Wang, S.; Chen, J.; Pan, Y.; Li, Q.; Xu, X.; et al. G-protein betagamma subunits determine grain size through interaction with MADS-domain transcription factors in rice. Nat Commun. 2018, 9, 852. [Google Scholar] [CrossRef]
  38. Garcia, D.; Saingery, V.; Chambrier, P.; Mayer, U.; Jurgens, G.; Berger, F. Arabidopsis haiku mutants reveal new controls of seed size by endosperm. Plant Physiol. 2003, 131, 1661–1670. [Google Scholar] [CrossRef]
  39. Shin, H.Y.; Nam, K.H. RAV1 Negatively Regulates Seed Development by Directly Repressing MINI3 and IKU2 in Arabidopsis. Mol. Cells 2018, 41, 1072–1080. [Google Scholar] [CrossRef]
  40. Fu, M.; Kang, H.Y.; Son, H.Y.; Kim, S.K.; Nam, K.H. A subset of Arabidopsis RAV transcription factors modulates drought and salt stress responses independent of ABA. Plant Cell Physiol. 2014, 55, 1892–1904. [Google Scholar] [CrossRef] [Green Version]
  41. Sun, Y.; Fan, X.Y.; Cao, D.M.; Tang, W.; He, K.; Zhu, J.Y.; He, J.X.; Bai, M.Y.; Zhu, S.; Oh, E.; et al. Integration of brassinosteroid signal transduction with the transcription network for plant growth regulation in Arabidopsis. Dev. Cell. 2010, 19, 765–777. [Google Scholar] [CrossRef] [PubMed]
  42. Jenik, P.D.; Barton, M.K. Surge and destroy: The role of auxin in plant embryogenesis. Development 2005, 132, 3577–3585. [Google Scholar] [CrossRef] [PubMed]
  43. Wabnik, K.; Robert, H.S.; Smith, R.S.; Friml, J. Modeling framework for the establishment of the apical-basal embryonic axis in plants. Curr. Biol. 2013, 23, 2513–2518. [Google Scholar] [CrossRef] [PubMed]
  44. Figueiredo, D.D.; Batista, R.A.; Roszak, P.J.; Hennig, L.; Köhler, C. Auxin production in the endosperm drives seed coat development in Arabidopsis. ELife 2016, 5, e20542. [Google Scholar] [CrossRef] [PubMed]
  45. Jackson, R.G.; Lim, E.K.; Li, Y.; Kowalczyk, M.; Sandberg, G.; Hoggett, J.; Ashford, D.A.; Bowles, D.J. Identification and biochemical characterization of an Arabidopsis indole-3-acetic acid glucosyltransferase. J. Biol. Chem. 2001, 276, 4350–4356. [Google Scholar] [CrossRef] [PubMed]
  46. Tognetti, V.B.; Van Aken, O.; Morreel, K.; Vandenbroucke, K.; van de Cotte, B.; De Clercq, I.; Chiwocha, S.; Fenske, R.; Prinsen, E.; Boerjan, W.; et al. Perturbation of indole-3-butyric acid homeostasis by the UDP-glucosyltransferase UGT74E2 modulates Arabidopsis architecture and water stress tolerance. Plant Cell 2010, 22, 2660–2679. [Google Scholar] [CrossRef] [PubMed]
  47. Jin, S.H.; Ma, X.M.; Han, P.; Wang, B.; Sun, Y.G.; Zhang, G.Z.; Li, Y.J.; Hou, B.K. UGT74D1 is a novel auxin glycosyltransferase from Arabidopsis thaliana. PLoS ONE 2013, 8, e61705. [Google Scholar] [CrossRef]
  48. Stortenbeker, N.; Bemer, M. The SAUR gene family: The plant's toolbox for adaptation of growth and development. J. Exp. Bot. 2019, 70, 17–27. [Google Scholar] [CrossRef]
  49. Focks, N.; Benning, C. wrinkled1: A novel, low-seed-oil mutant of Arabidopsis with a deficiency in the seed-specific regulation of carbohydrate metabolism. Plant Physiol. 1998, 118, 91–101. [Google Scholar] [CrossRef]
  50. Le-Clere, S.; Schmelz, E.A.; Chourey, P.S. Sugar levels regulate tryptophan-dependent auxin biosynthesis in developing maize kernels. Plant Physiol. 2010, 153, 306–318. [Google Scholar] [CrossRef] [Green Version]
  51. Faix, B.; Radchuk, V.; Nerlich, A.; Hümmer, C.; Radchuk, R.; Emery, R.J.; Keller, H.; Götz, K.P.; Weschke, W.; Geigenberger, P.; et al. Barley grains, deficient in cytosolic small subunit of ADP-glucose pyrophosphorylase, reveal coordinate adjustment of C:N metabolism mediated by an overlapping metabolic-hormonal control. Plant J. 2012, 69, 1077–1093. [Google Scholar] [CrossRef] [PubMed]
  52. Cheng, W.H.; Endo, A.; Zhou, L.; Penney, J.; Chen, H.C.; Arroyo, A.; Leon, P.; Nambara, E.; Asami, T.; Seo, M.; et al. A unique short-chain dehydrogenase/reductase in Arabidopsis glucose signaling and abscisic acid biosynthesis and functions. Plant Cell 2002, 14, 2723–2743. [Google Scholar] [CrossRef] [PubMed]
  53. Mattevi, A.; Bolognesi, M.; Valentini, G. The allosteric regulation of pyruvate kinase. FEBS Lett. 1996, 389, 15–19. [Google Scholar] [CrossRef]
  54. Kagaya, Y.; Okuda, R.; Ban, A.; Toyoshima, R.; Tsutsumida, K.; Usui, H.; Yamamoto, A.; Hattori, T. Indirect ABA-dependent regulation of seed storage protein genes by FUSCA3 transcription factor in Arabidopsis. Plant Cell Physiol. 2005, 46, 300–311. [Google Scholar] [CrossRef] [PubMed]
  55. Mu, J.; Tan, H.; Zheng, Q.; Fu, F.; Liang, Y.; Zhang, J.; Yang, X.; Wang, T.; Chong, K.; Wang, X.J.; et al. LEAFY COTYLEDON1 is a key regulator of fatty acid biosynthesis in Arabidopsis. Plant Physiol. 2008, 148, 1042–1054. [Google Scholar] [CrossRef] [PubMed]
  56. Nayak, S.N.; Hebbal, V.; Bharati, P.; Nadaf, H.L.; Naidu, G.K.; Bhat, R.S. Profiling of nutraceuticals and proximates in peanut genotypes differing for seed coat color and seed size. Front. Nutr. 2020, 7, 45. [Google Scholar] [CrossRef]
  57. Tang, G.; Xu, P.; Ma, W.; Wang, F.; Liu, Z.; Wan, S.; Shan, L. Seed-specific expression of AtLEC1 increased oil content and altered fatty acid composition in seeds of peanut (Arachis hypogaea L.). Front. Plant Sci. 2018, 6, 260. [Google Scholar] [CrossRef]
  58. Langmead, B.; Salzberg, S.L. Fast gapped-read alignment with Bowtie 2. Nat. Methods 2012, 9, 357–359. [Google Scholar] [CrossRef]
  59. Kim, D.; Langmead, B.; Salzberg, S.L. HISAT: A fast spliced aligner with low memory requirements. Nat. Methods 2015, 12, 357–360. [Google Scholar] [CrossRef]
  60. Li, B.; Dewey, C.N. RSEM: Accurate transcript quantification from RNA-Seq data with or without a reference genome. BMC Bioinformatics 2011, 12, 323. [Google Scholar] [CrossRef] [Green Version]
  61. Love, M.I.; Huber, W.; Anders, S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 2014, 15, 550. [Google Scholar] [CrossRef] [PubMed] [Green Version]
Ijms 23 09726 g001 550
Figure 1. Comparison of pods and seeds between mutant ssm1 and LH11. (a) Mature pods and seeds of ssm1 and LH11; (b) Mature pod and seed length, width, and weight of ssm1 and LH11; (c) The pods of ssm1 and LH11 at different developmental stages; (d) Seeds of ssm1 and LH11 at different developmental stages; (e) Pod weight of ssm1 and LH11 at different developmental stages; (f) Seed weight of ssm1 and LH11 at different developmental stages. DAP10, 10 days after pegging; DAP20, 20 days after pegging; DAP30, 30 days after pegging; DAP40, 40 days after pegging; DAP50, 50 days after pegging. Three biological replicates were used for statistical analysis (t-test; * p < 0.05, ** p < 0.01). Values in (b,e,f) represent means ± SE (n = 3).
Figure 1. Comparison of pods and seeds between mutant ssm1 and LH11. (a) Mature pods and seeds of ssm1 and LH11; (b) Mature pod and seed length, width, and weight of ssm1 and LH11; (c) The pods of ssm1 and LH11 at different developmental stages; (d) Seeds of ssm1 and LH11 at different developmental stages; (e) Pod weight of ssm1 and LH11 at different developmental stages; (f) Seed weight of ssm1 and LH11 at different developmental stages. DAP10, 10 days after pegging; DAP20, 20 days after pegging; DAP30, 30 days after pegging; DAP40, 40 days after pegging; DAP50, 50 days after pegging. Three biological replicates were used for statistical analysis (t-test; * p < 0.05, ** p < 0.01). Values in (b,e,f) represent means ± SE (n = 3).
Ijms 23 09726 g001
Ijms 23 09726 g002 550
Figure 2. Early embryonic development differences between ssm1 and LH11. DAP0, 0 day after pegging; DAP3, 3 days after pegging; DAP6, 6 days after pegging; DAP10, 10 days after pegging; DAP20, 20 days after pegging. Red arrows represent embryos.
Figure 2. Early embryonic development differences between ssm1 and LH11. DAP0, 0 day after pegging; DAP3, 3 days after pegging; DAP6, 6 days after pegging; DAP10, 10 days after pegging; DAP20, 20 days after pegging. Red arrows represent embryos.
Ijms 23 09726 g002
Ijms 23 09726 g003 550
Figure 3. Hormone content in seeds of ssm1 and LH11 at DAP20. IAA: Indole-3-acetic acid; IAA-Glc: 1-O-indol-3-ylacetylglucose; tZ: trans-Zeatin; tZR: trans-Zeatin Riboside; ABA: Abscisic acid; ABA-GE: ABA-glucosylester. Three biological replicates were used for statistical analysis (t-test; * p < 0.05, ** p < 0.01). Values represent means ± SE (n = 3).
Figure 3. Hormone content in seeds of ssm1 and LH11 at DAP20. IAA: Indole-3-acetic acid; IAA-Glc: 1-O-indol-3-ylacetylglucose; tZ: trans-Zeatin; tZR: trans-Zeatin Riboside; ABA: Abscisic acid; ABA-GE: ABA-glucosylester. Three biological replicates were used for statistical analysis (t-test; * p < 0.05, ** p < 0.01). Values represent means ± SE (n = 3).
Ijms 23 09726 g003
Ijms 23 09726 g004 550
Figure 4. Comparison of DGEs between ssm1 and LH11 seeds. (a) Numbers of DGEs in seeds between ssm1 and LH11 at DAP10, DAP20, and DAP40 three stages; (b) Scatter diagram of DEGs in seeds at DAP10 between ssm1 and LH11; (c) Scatter diagram of DEGs in seeds at DAP20 between ssm1 and LH11; (d) Scatter diagram of DEGs in seeds at DAP40 between ssm1 and LH11. Both the X and Y axes represent log10 values of gene expression.
Figure 4. Comparison of DGEs between ssm1 and LH11 seeds. (a) Numbers of DGEs in seeds between ssm1 and LH11 at DAP10, DAP20, and DAP40 three stages; (b) Scatter diagram of DEGs in seeds at DAP10 between ssm1 and LH11; (c) Scatter diagram of DEGs in seeds at DAP20 between ssm1 and LH11; (d) Scatter diagram of DEGs in seeds at DAP40 between ssm1 and LH11. Both the X and Y axes represent log10 values of gene expression.
Ijms 23 09726 g004
Ijms 23 09726 g005 550
Figure 5. GO classification analysis of DEGs in seeds of ssm1 and LH11. The X-axis represents the number of genes annotated into the GO terms, and the Y-axis represents the functional classification of GO.
Figure 5. GO classification analysis of DEGs in seeds of ssm1 and LH11. The X-axis represents the number of genes annotated into the GO terms, and the Y-axis represents the functional classification of GO.
Ijms 23 09726 g005
Ijms 23 09726 g006 550
Figure 6. Bubble diagram of top 20 enriched KEGG pathways of DEGs in seeds of ssm1 and LH11 at three stages. (a) DAP10; (b) DAP20; (c) DAP40. X-axis represents the rich ratio, which means the ratio of selected gene number annotated to a particular item to the total number of genes in this item in one species. The calculating formula is Rich Ratio = Term Candidate Gene Num/Term Gene Num. Y-axis represents KEGG Pathway. The size of the bubbles indicates the number of genes annotated to a KEGG Pathway. The color represents Q-value of enrichment. The deeper the color, the smaller the Q-value.
Figure 6. Bubble diagram of top 20 enriched KEGG pathways of DEGs in seeds of ssm1 and LH11 at three stages. (a) DAP10; (b) DAP20; (c) DAP40. X-axis represents the rich ratio, which means the ratio of selected gene number annotated to a particular item to the total number of genes in this item in one species. The calculating formula is Rich Ratio = Term Candidate Gene Num/Term Gene Num. Y-axis represents KEGG Pathway. The size of the bubbles indicates the number of genes annotated to a KEGG Pathway. The color represents Q-value of enrichment. The deeper the color, the smaller the Q-value.
Ijms 23 09726 g006
Ijms 23 09726 g007 550
Figure 7. The expression pattern of storage reserves-related genes in seeds between ssm1 and LH11. Different expressions of the related genes of fatty acid biosynthesis (a), fatty acid metabolism (b), starch synthesis (c), and late embryogenesis abundant proteins (d) in seeds between ssm1 and LH11. Scale bar is located at upside with log2 ratio value varying from green to red.
Figure 7. The expression pattern of storage reserves-related genes in seeds between ssm1 and LH11. Different expressions of the related genes of fatty acid biosynthesis (a), fatty acid metabolism (b), starch synthesis (c), and late embryogenesis abundant proteins (d) in seeds between ssm1 and LH11. Scale bar is located at upside with log2 ratio value varying from green to red.
Ijms 23 09726 g007
Ijms 23 09726 g008 550
Figure 8. Verification of DEGs by qRT-PCR in seeds. (a) Verification of 12 DEGs by qRT-PCR in seedss. DAP10, DAP20, and DAP40 were the relative gene expression levels of ssm1 and LH11 seeds at DAP10, DAP20, and DAP40, respectively. (b) Pearson’s correlation of gene expression ratios between RNA-seq and qRT-PCR results.
Figure 8. Verification of DEGs by qRT-PCR in seeds. (a) Verification of 12 DEGs by qRT-PCR in seedss. DAP10, DAP20, and DAP40 were the relative gene expression levels of ssm1 and LH11 seeds at DAP10, DAP20, and DAP40, respectively. (b) Pearson’s correlation of gene expression ratios between RNA-seq and qRT-PCR results.
Ijms 23 09726 g008
Ijms 23 09726 g009 550
Figure 9. The regulatory model underlying small-seed phenotype in ssm1 mutant. Glc-6P, D-Glucose 1-phosphate; PEP, Phosphoenol pyruvate; TAG, Triglyceride; Phe, Phenylalanine; Trp, Tyrosine; MVA, Mevalonic acid; DMAPP, Dimethylallyl diphosphate; GGPP, Geranylgeranyl diphosphate. Genes, metabolites, or arrows with green color indicate down-regulated expressions or reduced contents; those with red color indicate up-regulated expressions or increased contents.
Figure 9. The regulatory model underlying small-seed phenotype in ssm1 mutant. Glc-6P, D-Glucose 1-phosphate; PEP, Phosphoenol pyruvate; TAG, Triglyceride; Phe, Phenylalanine; Trp, Tyrosine; MVA, Mevalonic acid; DMAPP, Dimethylallyl diphosphate; GGPP, Geranylgeranyl diphosphate. Genes, metabolites, or arrows with green color indicate down-regulated expressions or reduced contents; those with red color indicate up-regulated expressions or increased contents.
Ijms 23 09726 g009
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Guo, F.; Zhu, X.; Zhao, C.; Zhao, S.; Pan, J.; Zhao, Y.; Wang, X.; Hou, L. Transcriptome Analysis and Gene Expression Profiling of the Peanut Small Seed Mutant Identified Genes Involved in Seed Size Control. Int. J. Mol. Sci. 2022, 23, 9726. https://doi.org/10.3390/ijms23179726

AMA Style

Guo F, Zhu X, Zhao C, Zhao S, Pan J, Zhao Y, Wang X, Hou L. Transcriptome Analysis and Gene Expression Profiling of the Peanut Small Seed Mutant Identified Genes Involved in Seed Size Control. International Journal of Molecular Sciences. 2022; 23(17):9726. https://doi.org/10.3390/ijms23179726

Chicago/Turabian Style

Guo, Fengdan, Xiujin Zhu, Chuanzhi Zhao, Shuzhen Zhao, Jiaowen Pan, Yanxiu Zhao, Xingjun Wang, and Lei Hou. 2022. "Transcriptome Analysis and Gene Expression Profiling of the Peanut Small Seed Mutant Identified Genes Involved in Seed Size Control" International Journal of Molecular Sciences 23, no. 17: 9726. https://doi.org/10.3390/ijms23179726

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop