136. PROGESTERONE RECEPTOR-REGULATED GENES IN THE PREOVULATORY OVARIAN FOLLICLE AND OVIDUCT

2010 ◽  
Vol 22 (9) ◽  
pp. 54 ◽  
Author(s):  
L. Akison ◽  
D. Russell ◽  
R. Robker
Keyword(s):  
Progesterone Receptor ◽  
Molecular Mechanisms ◽  
Ovarian Follicle ◽  
Normal Growth ◽  
Cellular Adhesion ◽  
Differentially Expressed ◽  
Reproductive Process ◽  
Molecular Control ◽  
Cancer Migration ◽  
Preovulatory Follicles

Ovulation is a highly regulated and precisely timed reproductive process but the underlying molecular mechanisms are not well understood. Progesterone receptor (PGR) is a transcription factor highly yet transiently expressed in granulosa cells (GCs) of preovulatory follicles; has low expression in cumulus-oocyte-complexes (COCs); and is abundantly expressed in the oviduct. PR–/– mice validate its essential role in ovulation as they are anovulatory, despite normal growth and development of ovarian follicles and oocytes. Our aim was to use microarray to identify differentially expressed genes in GCs, COCs and oviducts from PR–/– and PR+/– mice, specifically genes potentially involved in oocyte release and transport. GCs, COCs and oviducts were collected from 21d-old mice (n = 5; 3 mice/replicate) at 8h post-hCG/44h post-eCG. Extracted RNA samples were hybridized to Affymetrix Mouse Gene 1.0 ST Arrays and post-experiment processing/analysis performed using Partek Genomics Suite. Gene ontology analysis was performed using Ingenuity Pathway Analysis (IPA). In GCs, 296 genes were differentially expressed (P < 0.05); 78% down-regulated in PR–/–. IPA identified genes involved in cancer migration/invasion, chemotaxis, and adhesion; the chemokine receptor Cxcr4, was >3-fold down-regulated in PR–/–. Proteases were also decreased; Adam8 (3.5-fold) and Adamts1 (2.6-fold) in PR–/–. In oviducts, 1003 genes were differentially expressed at P < 0.05 and 266 genes at P < 0.01; 93% were down-regulated in PR–/–. IPA identified genes involved in cell adhesion, movement/migration, invasion and chemotaxis as well as muscle contraction and vasoconstriction. The most highly down-regulated was Itga8 (>9-fold), one of 11 integrins, well known cellular adhesion receptors, differentially expressed. In COCs, 44 genes were differentially expressed (P < 0.05); 52% down-regulated in PR–/–. IPA identified 18 genes (41%) involved in cancer invasion/migration or adhesion. Thus, this study has identified novel gene targets for PGR regulation, which may have essential roles in the molecular control of oocyte release into the oviduct at ovulation.

scholarly journals Integrated Analysis of lncRNA, miRNA and mRNA Reveals Novel Insights into the Fertility Regulation of Large White Sows

2019 ◽  
Author(s):  
Huiyan Hu ◽  
Qing Jia ◽  
Jianzhong Xi ◽  
Bo Zhou ◽  
Zhiqiang Li
Keyword(s):  
Molecular Mechanisms ◽  
Ovarian Tissue ◽  
Length Distribution ◽  
Differentially Expressed ◽  
Integrated Analysis ◽  
Rna Seq ◽  
Large White ◽  
Reproductive Process ◽  
Mrna Targets ◽  
Micro Rnas

Abstract Background: Improving sow fertility is extremely important as it can lead to increased reproductive efficiency and thus profitability for swine producers. There are considerable differences in fertility rates among individual animals, but the underlying molecular mechanisms remain unclear. In this study, by using different types of RNA libraries, we investigated the complete transcriptome of ovarian tissue during the luteal (L) and follicular phases (F) of the estrous cycle in Large White pigs with high (H) and low fecundity (L), and performed a comprehensive analysis of long noncoding RNAs (lncRNAs), mRNAs and micro RNAs (miRNAs) from 16 samples by combining RNA sequencing (RNA-seq) with bioinformatics. Results: In total, 24,447 lncRNAs, 27,370 mRNAs, and 216 known miRNAs were identified in ovarian tissues. The genomic features of lncRNAs, such as length distribution and number of exons, were further analyzed. We selected a threshold of P < 0.05 and |log2 (fold change)| ≥ 1to obtain the differentially expressed lncRNAs, miRNAs and mRNAs by pairwise comparison (LH vs. LL, FH vs. FL). Bioinformatics analysis of these differentially expressed RNAs revealed multiple significantly enriched pathways (P < 0.05) that were closely involved in the reproductive process, such as ovarian steroidogenesis, lysosome, steroid biosynthesis, and the estrogen and GnRH signaling pathways. Moreover, bioinformatics screening of differentially expressed miRNAs that share common miRNA response elements (MREs) with lncRNAs and their downstream mRNA targets were performed. Finally, we constructed lncRNA–miRNA–mRNA regulation networks. The key genes in these networks were verified by Reverse Transcription Real-time Quantitative PCR (RT-qRCR), which were consistent with the results from RNA-Seq data.Conclusions: These results provide further insights into the fertility of pigs and can contribute to further experimental investigation of the functions of these genes.

scholarly journals Integrated analysis of lncRNA, miRNA and mRNA reveals novel insights into the fertility regulation of large white sows

BMC Genomics ◽  
2020 ◽  
Vol 21 (1) ◽  
Author(s):  
Huiyan Hu ◽  
Qing Jia ◽  
Jianzhong Xi ◽  
Bo Zhou ◽  
Zhiqiang Li
Keyword(s):  
Molecular Mechanisms ◽  
Ovarian Tissue ◽  
Length Distribution ◽  
Differentially Expressed ◽  
Integrated Analysis ◽  
Rna Seq ◽  
Large White ◽  
Reproductive Process ◽  
Mrna Targets ◽  
Micro Rnas

Abstract Background Improving sow fertility is extremely important as it can lead to increased reproductive efficiency and thus profitability for swine producers. There are considerable differences in fertility rates among individual animals, but the underlying molecular mechanisms remain unclear. In this study, by using different types of RNA libraries, we investigated the complete transcriptome of ovarian tissue during the luteal (L) and follicular (F) phases of the estrous cycle in Large White pigs with high (H) and low (L) fecundity, and performed a comprehensive analysis of long noncoding RNAs (lncRNAs), mRNAs and micro RNAs (miRNAs) from 16 samples by combining RNA sequencing (RNA-seq) with bioinformatics. Results In total, 24,447 lncRNAs, 27,370 mRNAs, and 216 known miRNAs were identified in ovarian tissues. The genomic features of lncRNAs, such as length distribution and number of exons, were further analyzed. We selected a threshold of P < 0.05 and |log2 (fold change)| ≥ 1 to obtain the differentially expressed lncRNAs, miRNAs and mRNAs by pairwise comparison (LH vs. LL, FH vs. FL). Bioinformatics analysis of these differentially expressed RNAs revealed multiple significantly enriched pathways (P < 0.05) that were closely involved in the reproductive process, such as ovarian steroidogenesis, lysosome, steroid biosynthesis, and the estrogen and GnRH signaling pathways. Moreover, bioinformatics screening of differentially expressed miRNAs that share common miRNA response elements (MREs) with lncRNAs and their downstream mRNA targets were performed. Finally, we constructed lncRNA–miRNA–mRNA regulation networks. The key genes in these networks were verified by Reverse Transcription Real-time Quantitative PCR (RT-qRCR), which were consistent with the results from RNA-Seq data. Conclusions These results provide further insights into the fertility of pigs andcan contribute to further experimental investigation of the functions of these genes.

scholarly journals Integrated Analysis of lncRNA, miRNA and mRNA Reveals Novel Insights into the Fertility Regulation of Large White Sows

2020 ◽  
Author(s):  
Huiyan Hu ◽  
Qing Jia ◽  
Jianzhong Xi ◽  
Bo Zhou ◽  
Zhiqiang Li
Keyword(s):  
Molecular Mechanisms ◽  
Ovarian Tissue ◽  
Length Distribution ◽  
Differentially Expressed ◽  
Integrated Analysis ◽  
Rna Seq ◽  
Large White ◽  
Reproductive Process ◽  
Mrna Targets ◽  
Micro Rnas

Abstract Background: Improving sow fertility is extremely important as it can lead to increased reproductive efficiency and thus profitability for swine producers. There are considerable differences in fertility rates among individual animals, but the underlying molecular mechanisms remain unclear. In this study, by using different types of RNA libraries, we investigated the complete transcriptome of ovarian tissue during the luteal (L) and follicular (F) phases of the estrous cycle in Large White pigs with high (H) and low (L) fecundity, and performed a comprehensive analysis of long noncoding RNAs (lncRNAs), mRNAs and micro RNAs (miRNAs) from 16 samples by combining RNA sequencing (RNA-seq) with bioinformatics.Results: In total, 24,447 lncRNAs, 27,370 mRNAs, and 216 known miRNAs were identified in ovarian tissues. The genomic features of lncRNAs, such as length distribution and number of exons, were further analyzed. We selected a threshold of P <0.05 and |log2 (fold change)| ≥ 1 to obtain the differentially expressed lncRNAs, miRNAs and mRNAs by pairwise comparison (LH vs. LL, FH vs. FL). Bioinformatics analysis of these differentially expressed RNAs revealed multiple significantly enriched pathways (P <0.05) that were closely involved in the reproductive process, such as ovarian steroidogenesis, lysosome, steroid biosynthesis, and the estrogen and GnRH signaling pathways. Moreover, bioinformatics screening of differentially expressed miRNAs that share common miRNA response elements (MREs) with lncRNAs and their downstream mRNA targets were performed. Finally, we constructed lncRNA–miRNA–mRNA regulation networks. The key genes in these networks were verified by Reverse Transcription Real-time Quantitative PCR (RT-qRCR), which were consistent with the results from RNA-Seq data.Conclusions: These results provide further insights into the fertility of pigs andcan contribute to further experimental investigation of the functions of these genes.

scholarly journals Integrated Analysis of lncRNA, miRNA and mRNA Reveals Novel Insights into the Fertility Regulation of Large White Sows

2020 ◽  
Author(s):  
Huiyan Hu ◽  
Qing Jia ◽  
Jianzhong Xi ◽  
Bo Zhou ◽  
Zhiqiang Li
Keyword(s):  
Molecular Mechanisms ◽  
Ovarian Tissue ◽  
Length Distribution ◽  
Differentially Expressed ◽  
Integrated Analysis ◽  
Rna Seq ◽  
Large White ◽  
Reproductive Process ◽  
Mrna Targets ◽  
Micro Rnas

Abstract Background: Improving sow fertility is extremely important as it can lead to increased reproductive efficiency and thus profitability for swine producers. There are considerable differences in fertility rates among individual animals, but the underlying molecular mechanisms remain unclear. In this study, by using different types of RNA libraries, we investigated the complete transcriptome of ovarian tissue during the luteal (L) and follicular (F) phases of the estrous cycle in Large White pigs with high (H) and low (L) fecundity, and performed a comprehensive analysis of long noncoding RNAs (lncRNAs), mRNAs and micro RNAs (miRNAs) from 16 samples by combining RNA sequencing (RNA-seq) with bioinformatics.Results: In total, 24,447 lncRNAs, 27,370 mRNAs, and 216 known miRNAs were identified in ovarian tissues. The genomic features of lncRNAs, such as length distribution and number of exons, were further analyzed. We selected a threshold of P <0.05 and |log2 (fold change)| ≥ 1 to obtain the differentially expressed lncRNAs, miRNAs and mRNAs by pairwise comparison (LH vs. LL, FH vs. FL). Bioinformatics analysis of these differentially expressed RNAs revealed multiple significantly enriched pathways (P <0.05) that were closely involved in the reproductive process, such as ovarian steroidogenesis, lysosome, steroid biosynthesis, and the estrogen and GnRH signaling pathways. Moreover, bioinformatics screening of differentially expressed miRNAs that share common miRNA response elements (MREs) with lncRNAs and their downstream mRNA targets were performed. Finally, we constructed lncRNA–miRNA–mRNA regulation networks. The key genes in these networks were verified by Reverse Transcription Real-time Quantitative PCR (RT-qRCR), which were consistent with the results from RNA-Seq data.Conclusions: These results provide further insights into the fertility of pigs andcan contribute to further experimental investigation of the functions of these genes.

scholarly journals Integrated Analysis of lncRNA, miRNA and mRNA Reveals Novel Insights into the Fertility Regulation of Large White Sows

2020 ◽  
Author(s):  
Huiyan Hu ◽  
Qing Jia ◽  
Jianzhong Xi ◽  
Bo Zhou ◽  
Zhiqiang Li
Keyword(s):  
Molecular Mechanisms ◽  
Ovarian Tissue ◽  
Length Distribution ◽  
Differentially Expressed ◽  
Integrated Analysis ◽  
Rna Seq ◽  
Large White ◽  
Reproductive Process ◽  
Mrna Targets ◽  
Micro Rnas

Abstract Background: Improving sow fertility is extremely important as it can lead to increased reproductive efficiency and thus profitability for swine producers. There are considerable differences in fertility rates among individual animals, but the underlying molecular mechanisms remain unclear. In this study, by using different types of RNA libraries, we investigated the complete transcriptome of ovarian tissue during the luteal (L) and follicular (F) phases of the estrous cycle in Large White pigs withhigh (H) and low (L) fecundity, and performed a comprehensive analysis of long noncoding RNAs (lncRNAs), mRNAs and micro RNAs (miRNAs) from 16 samples by combining RNA sequencing (RNA-seq) with bioinformatics.Results: In total, 24,447 lncRNAs, 27,370 mRNAs, and 216 known miRNAs were identified in ovarian tissues. The genomic features of lncRNAs, such as length distribution and number of exons, were further analyzed. We selected a threshold of P<0.05 and |log2 (fold change)| ≥ 1 to obtain the differentially expressed lncRNAs, miRNAs and mRNAs by pairwise comparison (LH vs. LL, FH vs. FL).Bioinformatics analysis of these differentially expressed RNAs revealed multiple significantly enriched pathways (P< 0.05) that were closely involved in the reproductive process, such as ovarian steroidogenesis, lysosome, steroid biosynthesis, and the estrogen and GnRH signaling pathways. Moreover, bioinformatics screening of differentially expressed miRNAs that share common miRNA response elements (MREs) with lncRNAs and their downstream mRNA targets were performed. Finally, we constructed lncRNA–miRNA–mRNA regulation networks. The key genes in these networks were verified by Reverse Transcription Real-time Quantitative PCR (RT-qRCR), which were consistent with the results from RNA-Seq data.Conclusions: These results provide further insights into the fertility of pigs andcan contribute to further experimental investigation of the functions of these genes.

Identification of Differentially Expressed Genes Associated with Papillary Thyroid Carcinoma

2020 ◽  
Vol 23 (6) ◽  
pp. 546-553
Author(s):  
Hongyuan Cui ◽  
Mingwei Zhu ◽  
Junhua Zhang ◽  
Wenqin Li ◽  
Lihui Zou ◽  
...  
Keyword(s):  
Papillary Thyroid Carcinoma ◽  
Thyroid Carcinoma ◽  
Differentially Expressed Genes ◽  
Molecular Mechanisms ◽  
Cellular Proliferation ◽  
Mrna Level ◽  
Thyroid Tissue ◽  
Differentially Expressed ◽  
Thyroid Tumors ◽  
Papillary Thyroid

Objective: Next-generation sequencing (NGS) was performed to identify genes that were differentially expressed between normal thyroid tissue and papillary thyroid carcinoma (PTC). Materials & Methods: Six candidate genes were selected and further confirmed with quantitative real-time polymerase chain reaction (qRT-PCR), and immunohistochemistry in samples from 24 fresh thyroid tumors and adjacent normal tissues. The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis was used to investigate signal transduction pathways of the differentially expressed genes. Results: In total, 1690 genes were differentially expressed between samples from patients with PTC and the adjacent normal tissue. Among these, SFRP4, ZNF90, and DCN were the top three upregulated genes, whereas KIRREL3, TRIM36, and GABBR2 were downregulated with the smallest p values. Several pathways were associated with the differentially expressed genes and involved in cellular proliferation, cell migration, and endocrine system tumor progression, which may contribute to the pathogenesis of PTC. Upregulation of SFRP4, ZNF90, and DCN at the mRNA level was further validated with RT-PCR, and DCN expression was further confirmed with immunostaining of PTC samples. Conclusion: These results provide new insights into the molecular mechanisms of PTC. Identification of differentially expressed genes should not only improve the tumor signature for thyroid tumors as a diagnostic biomarker but also reveal potential targets for thyroid tumor treatment.

Systems Biology Approaches Reveal a Multi-stress Responsive WRKY Transcription Factor and Stress Associated Gene Co-expression Networks in Chickpea

2019 ◽  
Vol 14 (7) ◽  
pp. 591-601 ◽  
Author(s):  
Aravind K. Konda ◽  
Parasappa R. Sabale ◽  
Khela R. Soren ◽  
Shanmugavadivel P. Subramaniam ◽  
Pallavi Singh ◽  
...  
Keyword(s):  
Expression Pattern ◽  
Gene Networks ◽  
Molecular Mechanisms ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Wrky Transcription Factor ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Callose Deposition ◽  
Significant Probability

Background: Chickpea is a nutritional rich premier pulse crop but its production encounters setbacks due to various stresses and understanding of molecular mechanisms can be ascribed foremost importance. Objective: The investigation was carried out to identify the differentially expressed WRKY TFs in chickpea in response to herbicide stress and decipher their interacting partners. Methods: For this purpose, transcriptome wide identification of WRKY TFs in chickpea was done. Behavior of the differentially expressed TFs was compared between other stress conditions. Orthology based cofunctional gene networks were derived from Arabidopsis. Gene ontology and functional enrichment analysis was performed using Blast2GO and STRING software. Gene Coexpression Network (GCN) was constructed in chickpea using publicly available transcriptome data. Expression pattern of the identified gene network was studied in chickpea-Fusarium interactions. Results: A unique WRKY TF (Ca_08086) was found to be significantly (q value = 0.02) upregulated not only under herbicide stress but also in other stresses. Co-functional network of 14 genes, namely Ca_08086, Ca_19657, Ca_01317, Ca_20172, Ca_12226, Ca_15326, Ca_04218, Ca_07256, Ca_14620, Ca_12474, Ca_11595, Ca_15291, Ca_11762 and Ca_03543 were identified. GCN revealed 95 hub genes based on the significant probability scores. Functional annotation indicated role in callose deposition and response to chitin. Interestingly, contrasting expression pattern of the 14 network genes was observed in wilt resistant and susceptible chickpea genotypes, infected with Fusarium. Conclusion: This is the first report of identification of a multi-stress responsive WRKY TF and its associated GCN in chickpea.

scholarly journals Comparative transcriptomic and metabolomic analyses of carotenoid biosynthesis reveal the basis of white petal color in Brassica napus

Planta ◽  
2021 ◽  
Vol 253 (1) ◽  
Author(s):  
Ledong Jia ◽  
Junsheng Wang ◽  
Rui Wang ◽  
Mouzheng Duan ◽  
Cailin Qiao ◽  
...  
Keyword(s):  
Brassica Napus ◽  
Molecular Mechanisms ◽  
Flower Color ◽  
Carotenoid Biosynthesis ◽  
Differentially Expressed ◽  
Transcriptome Data ◽  
Oilseed Crops ◽  
Qrt Pcr ◽  
Carotenoid Metabolism ◽  
Rapeseed Cultivar

Abstract Main conclusion The molecular mechanism underlying white petal color in Brassica napus was revealed by transcriptomic and metabolomic analyses. Abstract Rapeseed (Brassica napus L.) is one of the most important oilseed crops worldwide, but the mechanisms underlying flower color in this crop are known less. Here, we performed metabolomic and transcriptomic analyses of the yellow-flowered rapeseed cultivar ‘Zhongshuang 11’ (ZS11) and the white-flowered inbred line ‘White Petal’ (WP). The total carotenoid contents were 1.778-fold and 1.969-fold higher in ZS11 vs. WP petals at stages S2 and S4, respectively. Our findings suggest that white petal color in WP flowers is primarily due to decreased lutein and zeaxanthin contents. Transcriptome analysis revealed 10,116 differentially expressed genes with a fourfold or greater change in expression (P-value less than 0.001) in WP vs. ZS11 petals, including 1,209 genes that were differentially expressed at four different stages and 20 genes in the carotenoid metabolism pathway. BnNCED4b, encoding a protein involved in carotenoid degradation, was expressed at abnormally high levels in WP petals, suggesting it might play a key role in white petal formation. The results of qRT-PCR were consistent with the transcriptome data. The results of this study provide important insights into the molecular mechanisms of the carotenoid metabolic pathway in rapeseed petals, and the candidate genes identified in this study provide a resource for the creation of new B. napus germplasms with different petal colors.

scholarly journals Genome-wide transcriptome profiling uncovers differential miRNAs and lncRNAs in ovaries of Hu sheep at different developmental stages

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Samina Shabbir ◽  
Prerona Boruah ◽  
Lingli Xie ◽  
Muhammad Fakhar-e-Alam Kulyar ◽  
Mohsin Nawaz ◽  
...  
Keyword(s):  
Target Genes ◽  
Expression Profiles ◽  
Ovarian Follicle ◽  
Follicular Development ◽  
Differentially Expressed ◽  
Ovary Development ◽  
Estrogen Metabolism ◽  
Genome Wide ◽  
Micro Rnas ◽  
Hu Sheep

AbstractOvary development is an important determinant of the procreative capacity of female animals. Here, we performed genome-wide sequencing of long non-coding RNAs (lncRNAs) and mRNAs on ovaries of 1, 3 and 8 months old Hu sheep to assess their expression profiles and roles in ovarian development. We identified 37,309 lncRNAs, 45,404 messenger RNAs (mRNAs) and 330 novel micro RNAs (miRNAs) from the transcriptomic analysis. Six thousand, seven hundred and sixteen (6716) mRNAs and 1972 lncRNAs were significantly and differentially expressed in ovaries of 1 month and 3 months old Hu sheep (H1 vs H3). These mRNAs and target genes of lncRNAs were primarily enriched in the TGF-β and PI3K-Akt signalling pathways which are closely associated with ovarian follicular development and steroid hormone biosynthesis regulation. We identified MSTRG.162061.1, MSTRG.222844.7, MSTRG.335777.1, MSTRG.334059.16, MSTRG.188947.6 and MSTRG.24344.3 as vital genes in ovary development by regulating CTNNB1, CCNA2, CDK2, CDC20, CDK1 and EGFR expressions. A total of 2903 mRNAs and 636 lncRNAs were differentially expressed in 3 and 8 months old ovaries of Hu sheep (H3 vs H8); and were predominantly enriched in PI3K-Akt, progesterone-mediated oocyte maturation, estrogen metabolism, ovulation from the ovarian follicle and oogenesis pathways. These lncRNAs were also found to regulate FGF7, PRLR, PTK2, AMH and INHBA expressions during follicular development. Our result indicates the identified genes participate in the development of the final stages of follicles and ovary development in Hu sheep.

scholarly journals Differential Morpho-Physiological and Transcriptomic Responses to Heat Stress in Two Blueberry Species

2021 ◽  
Vol 22 (5) ◽  
pp. 2481
Author(s):  
Jodi Callwood ◽  
Kalpalatha Melmaiee ◽  
Krishnanand P. Kulkarni ◽  
Amaranatha R. Vennapusa ◽  
Diarra Aicha ◽  
...  
Keyword(s):  
Heat Stress ◽  
Molecular Mechanisms ◽  
Stomatal Closure ◽  
Enrichment Analysis ◽  
Leaf Size ◽  
Vaccinium Corymbosum ◽  
Climatic Conditions ◽  
Differentially Expressed ◽  
Transcriptomic Changes ◽  
Go Terms

Blueberries (Vaccinium spp.) are highly vulnerable to changing climatic conditions, especially increasing temperatures. To gain insight into mechanisms underpinning the response to heat stress, two blueberry species were subjected to heat stress for 6 and 9 h at 45 °C, and leaf samples were used to study the morpho-physiological and transcriptomic changes. As compared with Vaccinium corymbosum, Vaccinium darrowii exhibited thermal stress adaptation features such as small leaf size, parallel leaf orientation, waxy leaf coating, increased stomatal surface area, and stomatal closure. RNAseq analysis yielded ~135 million reads and identified 8305 differentially expressed genes (DEGs) during heat stress against the control samples. In V. corymbosum, 2861 and 4565 genes were differentially expressed at 6 and 9 h of heat stress, whereas in V. darrowii, 2516 and 3072 DEGs were differentially expressed at 6 and 9 h, respectively. Among the pathways, the protein processing in the endoplasmic reticulum (ER) was the highly enriched pathway in both the species: however, certain metabolic, fatty acid, photosynthesis-related, peroxisomal, and circadian rhythm pathways were enriched differently among the species. KEGG enrichment analysis of the DEGs revealed important biosynthesis and metabolic pathways crucial in response to heat stress. The GO terms enriched in both the species under heat stress were similar, but more DEGs were enriched for GO terms in V. darrowii than the V. corymbosum. Together, these results elucidate the differential response of morpho-physiological and molecular mechanisms used by both the blueberry species under heat stress, and help in understanding the complex mechanisms involved in heat stress tolerance.

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