Faculty Opinions recommendation of Global transcriptome and coexpression network analyses reveal cultivar-specific molecular signatures associated with seed development and seed size/weight determination in chickpea.

2019 ◽  
Author(s):  
Andy Pereira
Keyword(s):  
Seed Development ◽  
Seed Size ◽  
Coexpression Network ◽  
Molecular Signatures ◽  
Network Analyses ◽  
Global Transcriptome

scholarly journals Genome-wide analysis of autophagy-related genes in Medicago truncatula highlights their roles in seed development and response to drought stress

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Mingkang Yang ◽  
Liping Wang ◽  
Chumin Chen ◽  
Xu Guo ◽  
Chuanglie Lin ◽  
...  
Keyword(s):  
Drought Stress ◽  
Seed Development ◽  
Medicago Truncatula ◽  
Interaction Network ◽  
Abiotic Stress Response ◽  
Biotic And Abiotic Stress ◽  
Comprehensive Overview ◽  
Network Analyses ◽  
Atg Genes ◽  
Gene Structures

AbstractAutophagy is a highly conserved process of degradation of cytoplasmic constituents in eukaryotes. It is involved in the growth and development of plants, as well as in biotic and abiotic stress response. Although autophagy-related (ATG) genes have been identified and characterized in many plant species, little is known about this process in Medicago truncatula. In this study, 39 ATGs were identified, and their gene structures and conserved domains were systematically characterized in M. truncatula. Many cis-elements, related to hormone and stress responsiveness, were identified in the promoters of MtATGs. Phylogenetic and interaction network analyses suggested that the function of MtATGs is evolutionarily conserved in Arabidopsis and M. truncatula. The expression of MtATGs, at varied levels, was detected in all examined tissues. In addition, most of the MtATGs were highly induced during seed development and drought stress, which indicates that autophagy plays an important role in seed development and responses to drought stress in M. truncatula. In conclusion, this study gives a comprehensive overview of MtATGs and provides important clues for further functional analysis of autophagy in M. truncatula.

scholarly journals Comprehensive Transcriptome Analyses Reveal Candidate Genes for Variation in Seed Size/Weight During Peanut (Arachis hypogaea L.) Domestication

2021 ◽  
Vol 12 ◽  
Author(s):  
Zhongfeng Li ◽  
Xingguo Zhang ◽  
Kunkun Zhao ◽  
Kai Zhao ◽  
Chengxin Qu ◽  
...  
Keyword(s):  
Candidate Genes ◽  
Seed Development ◽  
Seed Size ◽  
Snp Markers ◽  
Pentatricopeptide Repeat ◽  
Significant Differential Expression ◽  
Ppr Protein ◽  
Cultivated Peanut ◽  
Transcriptome Analyses ◽  
Wild Peanut

Seed size/weight, a key domestication trait, is also an important selection target during peanut breeding. However, the mechanisms that regulate peanut seed development are unknown. We re-sequenced 12 RNA samples from developing seeds of two cultivated peanut accessions (Lines 8106 and 8107) and wild Arachis monticola at 15, 30, 45, and 60 days past flowering (DPF). Transcriptome analyses showed that ∼36,000 gene loci were expressed in each of the 12 RNA samples, with nearly half exhibiting moderate (2 ≤ FPKM < 10) expression levels. Of these genes, 12.2% (4,523) were specifically expressed during seed development, mainly at 15 DPF. Also, ∼12,000 genes showed significant differential expression at 30, 45, and/or 60 DPF within each of the three peanut accessions, accounting for 31.8–34.1% of the total expressed genes. Using a method that combined comprehensive transcriptome analysis and previously mapped QTLs, we identified several candidate genes that encode transcription factor TGA7, topless-related protein 2, IAA-amino acid hydrolase ILR1-like 5, and putative pentatricopeptide repeat-containing (PPR) protein. Based on sequence variations identified in these genes, SNP markers were developed and used to genotype both 30 peanut landraces and a genetic segregated population, implying that EVM0025654 encoding a PPR protein may be associated with the increased seed size/weight of the cultivated accessions in comparison with the allotetraploid wild peanut. Our results provide additional knowledge for the identification and functional research into candidate genes responsible for the seed size/weight phenotype in peanut.

scholarly journals Transcriptome Analysis Reveals Key Seed-Development Genes in Common Buckwheat (Fagopyrum esculentum)

2019 ◽  
Vol 20 (17) ◽  
pp. 4303 ◽  
Author(s):  
Hongyou Li ◽  
Qiuyu Lv ◽  
Jiao Deng ◽  
Juan Huang ◽  
Fang Cai ◽  
...  
Keyword(s):  
Signal Transduction ◽  
Seed Development ◽  
Seed Size ◽  
Molecular Mechanisms ◽  
Signal Transduction Pathway ◽  
Fagopyrum Esculentum ◽  
Rna Seq ◽  
Common Buckwheat ◽  
Size Change ◽  
Key Genes

Seed development is an essential and complex process, which is involved in seed size change and various nutrients accumulation, and determines crop yield and quality. Common buckwheat (Fagopyrum esculentum Moench) is a widely cultivated minor crop with excellent economic and nutritional value in temperate zones. However, little is known about the molecular mechanisms of seed development in common buckwheat (Fagopyrum esculentum). In this study, we performed RNA-Seq to investigate the transcriptional dynamics and identify the key genes involved in common buckwheat seed development at three different developmental stages. A total of 4619 differentially expressed genes (DEGs) were identified. Based on the results of Gene Ontology (GO) and KEGG analysis of DEGs, many key genes involved in the seed development, including the Ca2+ signal transduction pathway, the hormone signal transduction pathways, transcription factors (TFs), and starch biosynthesis-related genes, were identified. More importantly, 18 DEGs were identified as the key candidate genes for seed size through homologous query using the known seed size-related genes from different seed plants. Furthermore, 15 DEGs from these identified as the key genes of seed development were selected to confirm the validity of the data by using quantitative real-time PCR (qRT-PCR), and the results show high consistency with the RNA-Seq results. Taken together, our results revealed the underlying molecular mechanisms of common buckwheat seed development and could provide valuable information for further studies, especially for common buckwheat seed improvement.

Global transcriptome and weighted gene co-expression network analyses reveal hybrid-specific modules and candidate genes related to plant height development in maize

2018 ◽  
Vol 98 (3) ◽  
pp. 187-203 ◽  
Author(s):  
Hengsheng Wang ◽  
Longjiang Gu ◽  
Xingen Zhang ◽  
Mingli Liu ◽  
Haiyang Jiang ◽  
...  
Keyword(s):  
Candidate Genes ◽  
Plant Height ◽  
Network Analyses ◽  
Global Transcriptome

scholarly journals High-Resolution Mapping in Two RIL Populations Refines Major “QTL Hotspot” Regions for Seed Size and Shape in Soybean (Glycine max L.)

2020 ◽  
Vol 21 (3) ◽  
pp. 1040 ◽  
Author(s):  
Aiman Hina ◽  
Yongce Cao ◽  
Shiyu Song ◽  
Shuguang Li ◽  
Ripa Akter Sharmin ◽  
...  
Keyword(s):  
Seed Size ◽  
Composite Interval Mapping ◽  
Mixed Model ◽  
Gene Annotation ◽  
Soybean Seed ◽  
Interval Mapping ◽  
Epistatic Effect ◽  
Size And Shape ◽  
Network Analyses ◽  
Major Qtl

Seed size and shape are important traits determining yield and quality in soybean. However, the genetic mechanism and genes underlying these traits remain largely unexplored. In this regard, this study used two related recombinant inbred line (RIL) populations (ZY and K3N) evaluated in multiple environments to identify main and epistatic-effect quantitative trait loci (QTLs) for six seed size and shape traits in soybean. A total of 88 and 48 QTLs were detected through composite interval mapping (CIM) and mixed-model-based composite interval mapping (MCIM), respectively, and 15 QTLs were common among both methods; two of them were major (R2 > 10%) and novel QTLs (viz., qSW-1-1ZN and qSLT-20-1K3N). Additionally, 51 and 27 QTLs were identified for the first time through CIM and MCIM methods, respectively. Colocalization of QTLs occurred in four major QTL hotspots/clusters, viz., “QTL Hotspot A”, “QTL Hotspot B”, “QTL Hotspot C”, and “QTL Hotspot D” located on Chr06, Chr10, Chr13, and Chr20, respectively. Based on gene annotation, gene ontology (GO) enrichment, and RNA-Seq analysis, 23 genes within four “QTL Hotspots” were predicted as possible candidates, regulating soybean seed size and shape. Network analyses demonstrated that 15 QTLs showed significant additive x environment (AE) effects, and 16 pairs of QTLs showing epistatic effects were also detected. However, except three epistatic QTLs, viz., qSL-13-3ZY, qSL-13-4ZY, and qSW-13-4ZY, all the remaining QTLs depicted no main effects. Hence, the present study is a detailed and comprehensive investigation uncovering the genetic basis of seed size and shape in soybeans. The use of a high-density map identified new genomic regions providing valuable information and could be the primary target for further fine mapping, candidate gene identification, and marker-assisted breeding (MAB).

An analysis of seed development in Pisum sativum. XV. The influence of seed size on protein content

1991 ◽  
Vol 1 (4) ◽  
pp. 203-208 ◽  
Author(s):  
A. E. Arthur ◽  
H. Adams ◽  
K. Strouts ◽  
D. A. Jones ◽  
T. L. Wang ◽  
...  
Keyword(s):  
Pisum Sativum ◽  
Protein Content ◽  
Total Variation ◽  
Seed Development ◽  
Seed Size ◽  
Seed Weight ◽  
Genetic Component ◽  
Residual Variation ◽  
Percentage Protein

AbstractThe variation for protein content has been assessed in a series of pea (Pisum sativum L.) lines differing in mean seed size. The range of seed size within each genotype was manipulated by growing the plants in different environments and by altering the structure of the plant. The response of the lines in terms of seed weight to the environments and treatments was inconsistent, but 90% of the total variation was accounted for by differences between genotypes. In contrast, for percentage protein, the genetic component was much weaker with nearly half the variation being accounted for by within (residual) variation. The correlations between seed weight and percentage protein were highly genotype specific. For the largerseeded genotype, percentage protein increased with increasing seed size (r= +0.9, P < 0.01), while for the small-seeded genotype there was mid-range negative value (r = −0.5, P <0.01). It is suggested that any assessment of percentage protein in pea genotypes must take account of seed size.

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