scholarly journals The seasonal development dynamics of the yak hair cycle transcriptome

2019 ◽  
Author(s):  
Pengjia Bao ◽  
Jiayu Luo ◽  
Yanbin Liu ◽  
Min Chu ◽  
Qingmiao Ren ◽  
...  
Keyword(s):  
Hormonal Regulation ◽  
Regulatory Networks ◽  
Molecular Mechanisms ◽  
Time Series Data ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Seasonal Development ◽  
Series Data ◽  
Hair Cycle ◽  
Adaptation Mechanism

Abstract Background: Mammalian hair play an important role in mammals' ability to adapt to changing climatic environments. The seasonal circulation of yak hair helps them adapt to high altitude but the regulation mechanisms of the proliferation and differentiation of hair follicle (HF) cells during development are still unknown. Here, using time series data for whole genome expression profiles and hormone contents, we systematically analyzed the mechanism regulating the periodic expression of hair development in the yak and reviewed how different combinations of genetic pathways regulate HF development and cycling. Results: This study used high-throughput RNA sequencing to provide a detailed description of global gene expression in 15 samples from five developmental time points during the yak hair cycle. A total of 11,666 genes were found to be involved in the hair cycle. According to clustering analysis and the morphological features we observed, we found that these 15 samples could be significantly grouped into three phases, which represent different developmental periods in the hair cycle. A total of 2,316 genes were identified in these three consecutive developmental periods and their expression patterns could be divided into 9 clusters; GO annotation and KEGG pathway enrichment were performed on these differentially expressed genes (DEGs), showing that the three periods have distinctive functions in the seasonal hair cycle. The regulatory network of related signaling factors highlighted the interaction and dynamic expression of key DEGs during the seasonal hair cycle. Through co-expression analysis, we revealed a number of modular hub genes highly associated with hormones that may play unique roles in hormonal regulation of events associated with the hair cycle. Conclusions: Our results revealed the molecular mechanisms and developmental regulatory networks of the seasonal hair cycle in the yak and filled a gap in the current research field. The findings will be valuable in further understanding the alpine adaptation mechanism in the yak, which is important in order to make full use of yak hair resources and promote the economic development of pastoral plateau areas. Keywords: Hair cycle, Seasonal development, Transcriptome, Yak

scholarly journals The seasonal development dynamics of the yak hair cycle transcriptome

2020 ◽  
Author(s):  
Pengjia Bao ◽  
Jiayu Luo ◽  
Yanbin Liu ◽  
Min Chu ◽  
Qingmiao Ren ◽  
...  
Keyword(s):  
Hair Follicle ◽  
Hormonal Regulation ◽  
Molecular Mechanisms ◽  
Time Series Data ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Hair Follicles ◽  
Seasonal Development ◽  
Series Data ◽  
Hair Cycle

Abstract Background : Mammalian hair play an important role in mammals' ability to adapt to changing climatic environments. The seasonal circulation of yak hair helps them adapt to high altitude but the regulation mechanisms of the proliferation and differentiation of hair follicles (HFs) cells during development are still unknown. Here, using time series data for whole genome expression profiles and hormone contents, we systematically analyzed the mechanism regulating the periodic expression of hair development in the yak and reviewed how different combinations of genetic pathways regulate HFs development and cycling. Results : This study used high-throughput RNA sequencing to provide a detailed description of global gene expression in 15 samples from five developmental time points during the yak hair cycle. According to clustering analysis, we found that these 15 samples could be significantly grouped into three phases, which represent different developmental periods in the hair cycle. A total of 2,316 genes were identified in these three consecutive developmental periods and their expression patterns could be divided into 9 clusters. In the anagen, genes involved in activating hair follicle growth are highly expressed, such as the WNT pathway, FGF pathway, and some genes related to hair follicle differentiation. In the catagen, genes that inhibit differentiation and promote hair follicle cell apoptosis are highly expressed, such as FABP4 , BMP4 , and Wise . In the telogen, genes that inhibit hair follicle activity are highly expressed, such as DKK1 and BMP1 . Through co-expression analysis, we revealed a number of modular hub genes highly associated with hormones, such as SLF2 , BOP1 , DPP8 . They may play unique roles in hormonal regulation of events associated with the hair cycle. Conclusions : Our results revealed the expression pattern and molecular mechanisms of the seasonal hair cycle in the yak. The findings will be valuable in further understanding the alpine adaptation mechanism in the yak, which is important in order to make full use of yak hair resources and promote the economic development of pastoral plateau areas.

scholarly journals Study on cyanidin metabolism in petals of pink-flowered strawberry based on transcriptome sequencing and metabolite analysis

2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Li Xue ◽  
Jian Wang ◽  
Jun Zhao ◽  
Yang Zheng ◽  
Hai-Feng Wang ◽  
...  
Keyword(s):  
Regulatory Networks ◽  
Molecular Mechanisms ◽  
Target Genes ◽  
Anthocyanin Biosynthesis ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Anthocyanin Synthesis ◽  
Integrated Analysis ◽  
Intergeneric Hybridization ◽  
Significant Differential Expression

Abstract Background Pink-flowered strawberry is a promising new ornamental flower derived from intergeneric hybridization (Fragaria × Potentilla) with bright color, a prolonged flowering period and edible fruits. Its flower color ranges from light pink to red. Pigment compounds accumulated in its fruits were the same as in cultivated strawberry fruits, but different from that in its flowers. However, the transcriptional events underlying the anthocyanin biosynthetic pathway have not been fully characterized in petal coloration. To gain insights into the regulatory networks related to anthocyanin biosynthesis and identify the key genes, we performed an integrated analysis of the transcriptome and metabolome in petals of pink-flowered strawberry. Results The main pigments of red and dark pink petals were anthocyanins, among which cyanidins were the main compound. There were no anthocyanins detected in the white-flowered hybrids. A total of 50,285 non-redundant unigenes were obtained from the transcriptome databases involved in red petals of pink-flowered strawberry cultivar Sijihong at three development stages. Amongst the unigenes found to show significant differential expression, 57 were associated with anthocyanin or other flavonoid biosynthesis, in which they were regulated by 241 differentially expressed members of transcription factor families, such as 40 MYBs, 47 bHLHs, and 41 NACs. Based on a comprehensive analysis relating pigment compounds to gene expression profiles, the mechanism of flower coloration was examined in pink-flowered strawberry. A new hypothesis was proposed to explain the lack of color phenotype of the white-flowered strawberry hybrids based on the transcriptome analysis. The expression patterns of FpDFR and FpANS genes corresponded to the accumulation patterns of cyanidin contents in pink-flowered strawberry hybrids with different shades of pink. Moreover, FpANS, FpBZ1 and FpUGT75C1 genes were the major factors that led to the absence of anthocyanins in the white petals of pink-flowered strawberry hybrids. Meanwhile, the competitive effect of FpFLS and FpDFR genes might further inhibit anthocyanin synthesis. Conclusions The data presented herein are important for understanding the molecular mechanisms underlying the petal pigmentation and will be powerful for integrating novel potential target genes to breed valuable pink-flowered strawberry cultivars.

scholarly journals Modeling thePseudomonasSulfur Regulome by Quantifying the Storage and Communication of Information

mSystems ◽  
2018 ◽  
Vol 3 (3) ◽  
Author(s):  
Peter E. Larsen ◽  
Sarah Zerbs ◽  
Philip D. Laible ◽  
Frank R. Collart ◽  
Peter Korajczyk ◽  
...  
Keyword(s):  
Gene Expression ◽  
Information Theory ◽  
Information Transfer ◽  
Regulatory Networks ◽  
Molecular Mechanisms ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Gene Expression Profiles ◽  
Transcriptional Responses ◽  
Content Type

ABSTRACTBacteria are not simply passive consumers of nutrients or merely steady-state systems. Rather, bacteria are active participants in their environments, collecting information from their surroundings and processing and using that information to adapt their behavior and optimize survival. The bacterial regulome is the set of physical interactions that link environmental information to the expression of genes by way of networks of sensors, transporters, signal cascades, and transcription factors. As bacteria cannot have one dedicated sensor and regulatory response system for every possible condition that they may encounter, the sensor systems must respond to a variety of overlapping stimuli and collate multiple forms of information to make “decisions” about the most appropriate response to a specific set of environmental conditions. Here, we analyzePseudomonas fluorescenstranscriptional responses to multiple sulfur nutrient sources to generate a predictive, computational model of the sulfur regulome. To model the regulome, we utilize a transmitter-channel-receiver scheme of information transfer and utilize principles from information theory to portrayP. fluorescensas an informatics system. This approach enables us to exploit the well-established metrics associated with information theory to model the sulfur regulome. Our computational modeling analysis results in the accurate prediction of gene expression patterns in response to the specific sulfur nutrient environments and provides insights into the molecular mechanisms ofPseudomonassensory capabilities and gene regulatory networks. In addition, modeling the bacterial regulome using the tools of information theory is a powerful and generalizable approach that will have multiple future applications to other bacterial regulomes.IMPORTANCEBacteria sense and respond to their environments using a sophisticated array of sensors and regulatory networks to optimize their fitness and survival in a constantly changing environment. Understanding how these regulatory and sensory networks work will provide the capacity to predict bacterial behaviors and, potentially, to manipulate their interactions with an environment or host. Leveraging the information theory provides useful quantitative metrics for modeling the information processing capacity of bacterial regulatory networks. As our model accurately predicted gene expression profiles in a bacterial model system, we posit that the information theory-based approaches will be important to enhance our understanding of a wide variety of bacterial regulomes and our ability to engineer bacterial sensory and regulatory networks.

scholarly journals Jonckheere–Terpstra–Kendall-based non-parametric analysis of temporal differential gene expression

2021 ◽  
Vol 3 (1) ◽  
Author(s):  
Hitoshi Iuchi ◽  
Michiaki Hamada
Keyword(s):  
Gene Expression ◽  
Time Series ◽  
Time Course ◽  
Time Series Data ◽  
Expression Patterns ◽  
Detection Methods ◽  
Series Data ◽  
Expression Levels ◽  
Over Time ◽  
Non Parametric

Abstract Time-course experiments using parallel sequencers have the potential to uncover gradual changes in cells over time that cannot be observed in a two-point comparison. An essential step in time-series data analysis is the identification of temporal differentially expressed genes (TEGs) under two conditions (e.g. control versus case). Model-based approaches, which are typical TEG detection methods, often set one parameter (e.g. degree or degree of freedom) for one dataset. This approach risks modeling of linearly increasing genes with higher-order functions, or fitting of cyclic gene expression with linear functions, thereby leading to false positives/negatives. Here, we present a Jonckheere–Terpstra–Kendall (JTK)-based non-parametric algorithm for TEG detection. Benchmarks, using simulation data, show that the JTK-based approach outperforms existing methods, especially in long time-series experiments. Additionally, application of JTK in the analysis of time-series RNA-seq data from seven tissue types, across developmental stages in mouse and rat, suggested that the wave pattern contributes to the TEG identification of JTK, not the difference in expression levels. This result suggests that JTK is a suitable algorithm when focusing on expression patterns over time rather than expression levels, such as comparisons between different species. These results show that JTK is an excellent candidate for TEG detection.

scholarly journals Comparative transcriptomics identifies differences in the regulation of the floral transition between Arabidopsis and Brassica rapa cultivars

2020 ◽  
Author(s):  
Alexander Calderwood ◽  
Jo Hepworth ◽  
Shannon Woodhouse ◽  
Lorelei Bilham ◽  
D. Marc Jones ◽  
...  
Keyword(s):  
Gene Expression ◽  
Brassica Rapa ◽  
Regulatory Networks ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Gene Expression Profiles ◽  
Detailed Comparison ◽  
Developmental Time ◽  
Floral Transition ◽  
Gene Regulatory

AbstractThe timing of the floral transition affects reproduction and yield, however its regulation in crops remains poorly understood. Here, we use RNA-Seq to determine and compare gene expression dynamics through the floral transition in the model species Arabidopsis thaliana and the closely related crop Brassica rapa. A direct comparison of gene expression over time between species shows little similarity, which could lead to the inference that different gene regulatory networks are at play. However, these differences can be largely resolved by synchronisation, through curve registration, of gene expression profiles. We find that different registration functions are required for different genes, indicating that there is no common ‘developmental time’ to which Arabidopsis and B. rapa can be mapped through gene expression. Instead, the expression patterns of different genes progress at different rates. We find that co-regulated genes show similar changes in synchronisation between species, suggesting that similar gene regulatory sub-network structures may be active with different wiring between them. A detailed comparison of the regulation of the floral transition between Arabidopsis and B. rapa, and between two B. rapa accessions reveals different modes of regulation of the key floral integrator SOC1, and that the floral transition in the B. rapa accessions is triggered by different pathways, even when grown under the same environmental conditions. Our study adds to the mechanistic understanding of the regulatory network of flowering time in rapid cycling B. rapa under long days and highlights the importance of registration methods for the comparison of developmental gene expression data.

scholarly journals Convergent evolution of venom gland transcriptomes across Metazoa

2021 ◽  
Author(s):  
Giulia Zancolli ◽  
Maarten Reijnders ◽  
Robert Waterhouse ◽  
Marc Robinson-Rechavi
Keyword(s):  
Gene Expression ◽  
Regulatory Networks ◽  
Molecular Mechanisms ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Venom Gland ◽  
Bioactive Molecules ◽  
Specific Gene ◽  
Animal Kingdom ◽  
Venom Glands

Animals have repeatedly evolved specialized organs and anatomical structures to produce and deliver a cocktail of potent bioactive molecules to subdue prey or predators: venom. This makes it one of the most widespread convergent functions in the animal kingdom. Whether animals have adopted the same genetic toolkit to evolved venom systems is a fascinating question that still eludes us. Here, we performed the first comparative analysis of venom gland transcriptomes from 20 venomous species spanning the main Metazoan lineages, to test whether different animals have independently adopted similar molecular mechanisms to perform the same function. We found a strong convergence in gene expression profiles, with venom glands being more similar to each other than to any other tissue from the same species, and their differences closely mirroring the species phylogeny. Although venom glands secrete some of the fastest evolving molecules (toxins), their gene expression does not evolve faster than evolutionarily older tissues. We found 15 venom gland specific gene modules enriched in endoplasmic reticulum stress and unfolded protein response pathways, indicating that animals have independently adopted stress response mechanisms to cope with mass production of toxins. This, in turns, activates regulatory networks for epithelial development, cell turnover and maintenance which seem composed of both convergent and lineage-specific factors, possibly reflecting the different developmental origins of venom glands. This study represents the first step towards an understanding of the molecular mechanisms underlying the repeated evolution of one of the most successful adaptive traits in the animal kingdom.

scholarly journals Bivalent genes that undergo transcriptional switching identify networks of key regulators of embryonic stem cell differentiation

BMC Genomics ◽  
2020 ◽  
Vol 21 (S10) ◽  
Author(s):  
Ah-Jung Jeon ◽  
Greg Tucker-Kellogg
Keyword(s):  
Cell Differentiation ◽  
Time Series Data ◽  
Es Cells ◽  
Expression Patterns ◽  
Embryonic Stem ◽  
Stem Cell Differentiation ◽  
Chromatin State ◽  
Series Data ◽  
Embryonic Stem Cell Differentiation ◽  
Gene Promoters

Abstract Background Bivalent promoters marked with both H3K27me3 and H3K4me3 histone modifications are characteristic of poised promoters in embryonic stem (ES) cells. The model of poised promoters postulates that bivalent chromatin in ES cells is resolved to monovalency upon differntiation. With the availability of single-cell RNA sequencing (scRNA-seq) data, subsequent switches in transcriptional state at bivalent promoters can be studied more closely. Results We develop an approach for capturing genes undergoing transcriptional switching by detecting ‘bimodal’ gene expression patterns from scRNA-seq data. We integrate the identification of bimodal genes in ES cell differentiation with analysis of chromatin state, and identify clear cell-state dependent patterns of bimodal, bivalent genes. We show that binarization of bimodal genes can be used to identify differentially expressed genes from fractional ON/OFF proportions. In time series data from differentiating cells, we build a pseudotime approximation and use a hidden Markov model to infer gene activity switching pseudotimes, which we use to infer a regulatory network. We identify pathways of switching during differentiation, novel details of those pathway, and transcription factor coordination with downstream targets. Conclusions Genes with expression levels too low to be informative in conventional scRNA analysis can be used to infer transcriptional switching networks that connect transcriptional activity to chromatin state. Since chromatin bivalency is a hallmark of gene promoters poised for activity, this approach provides an alternative that complements conventional scRNA-seq analysis while focusing on genes near the ON/OFF boundary of activity. This offers a novel and productive means of inferring regulatory networks from scRNA-seq data.

Inference of gene regulatory networks based on nonlinear ordinary differential equations

2020 ◽  
Vol 36 (19) ◽  
pp. 4885-4893 ◽  
Author(s):  
Baoshan Ma ◽  
Mingkun Fang ◽  
Xiangtian Jiao
Keyword(s):  
Gene Expression ◽  
Time Series ◽  
Steady State ◽  
Differential Equations ◽  
Gene Regulatory Networks ◽  
Regulatory Networks ◽  
Time Series Data ◽  
Series Data ◽  
State Data ◽  
Gene Regulatory

Abstract Motivation Gene regulatory networks (GRNs) capture the regulatory interactions between genes, resulting from the fundamental biological process of transcription and translation. In some cases, the topology of GRNs is not known, and has to be inferred from gene expression data. Most of the existing GRNs reconstruction algorithms are either applied to time-series data or steady-state data. Although time-series data include more information about the system dynamics, steady-state data imply stability of the underlying regulatory networks. Results In this article, we propose a method for inferring GRNs from time-series and steady-state data jointly. We make use of a non-linear ordinary differential equations framework to model dynamic gene regulation and an importance measurement strategy to infer all putative regulatory links efficiently. The proposed method is evaluated extensively on the artificial DREAM4 dataset and two real gene expression datasets of yeast and Escherichia coli. Based on public benchmark datasets, the proposed method outperforms other popular inference algorithms in terms of overall score. By comparing the performance on the datasets with different scales, the results show that our method still keeps good robustness and accuracy at a low computational complexity. Availability and implementation The proposed method is written in the Python language, and is available at: https://github.com/lab319/GRNs_nonlinear_ODEs Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Insecticide Exposure Triggers a Modulated Expression of ABC Transporter Genes in Larvae of Anopheles gambiae s.s.

Insects ◽  
2019 ◽  
Vol 10 (3) ◽  
pp. 66 ◽  
Author(s):  
Valentina Mastrantonio ◽  
Marco Ferrari ◽  
Agata Negri ◽  
Tommaso Sturmo ◽  
Guido Favia ◽  
...  
Keyword(s):  
Anopheles Gambiae ◽  
Abc Transporter ◽  
Abc Transporters ◽  
Molecular Mechanisms ◽  
Expression Profiles ◽  
Larval Mortality ◽  
Expression Patterns ◽  
Main Tool ◽  
Gene Expression Response ◽  
Abc Transporter Genes

Insecticides remain a main tool for the control of arthropod vectors. The urgency to prevent the insurgence of insecticide resistance and the perspective to find new target sites, for the development of novel molecules, are fuelling the study of the molecular mechanisms involved in insect defence against xenobiotic compounds. In this study, we have investigated if ATP-binding cassette (ABC) transporters, a major component of the defensome machinery, are involved in defence against the insecticide permethrin, in susceptible larvae of the malaria vector Anopheles gambiae sensu stricto. Bioassays were performed with permethrin alone, or in combination with an ABC transporter inhibitor. Then we have investigated the expression profiles of five ABC transporter genes at different time points following permethrin exposure, to assess their expression patterns across time. The inhibition of ABC transporters increased the larval mortality by about 15-fold. Likewise, three genes were up-regulated after exposure to permethrin, showing different patterns of expression across the 48 h. Our results provide the first evidences of ABC transporters involvement in defence against a toxic in larvae of An. gambiae s.s. and show that the gene expression response is modulated across time, being continuous, but stronger at the earliest and latest times after exposure.

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