A mutation in LacDWARF1 results in a GA-deficient dwarf phenotype in sponge gourd (Luffa acutangula)

Abstract Key message A dwarfism gene LacDWARF1 was mapped by combined BSA-Seq and comparative genomics analyses to a 65.4 kb physical genomic region on chromosome 05. Abstract Dwarf architecture is one of the most important traits utilized in Cucurbitaceae breeding because it saves labor and increases the harvest index. To our knowledge, there has been no prior research about dwarfism in the sponge gourd. This study reports the first dwarf mutant WJ209 with a decrease in cell size and internodes. A genetic analysis revealed that the mutant phenotype was controlled by a single recessive gene, which is designated Lacdwarf1 (Lacd1). Combined with bulked segregate analysis and next-generation sequencing, we quickly mapped a 65.4 kb region on chromosome 5 using F2 segregation population with InDel and SNP polymorphism markers. Gene annotation revealed that Lac05g019500 encodes a gibberellin 3β-hydroxylase (GA3ox) that functions as the most likely candidate gene for Lacd1. DNA sequence analysis showed that there is an approximately 4 kb insertion in the first intron of Lac05g019500 in WJ209. Lac05g019500 is transcribed incorrectly in the dwarf mutant owing to the presence of the insertion. Moreover, the bioactive GAs decreased significantly in WJ209, and the dwarf phenotype could be restored by exogenous GA3 treatment, indicating that WJ209 is a GA-deficient mutant. All these results support the conclusion that Lac05g019500 is the Lacd1 gene. In addition, RNA-Seq revealed that many genes, including those related to plant hormones, cellular process, cell wall, membrane and response to stress, were significantly altered in WJ209 compared with the wild type. This study will aid in the use of molecular marker-assisted breeding in the dwarf sponge gourd.

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Identification of Bna.IAA7.C05 as allelic gene for dwarf mutant generated from tissue culture in oilseed rape

BMC Plant Biology ◽

10.1186/s12870-019-2094-2 ◽

2019 ◽

Vol 19 (1) ◽

Cited By ~ 3

Author(s):

Hongtao Cheng ◽

Fenwei Jin ◽

Qamar U. Zaman ◽

Bingli Ding ◽

Mengyu Hao ◽

...

Keyword(s):

Tissue Culture ◽

Plant Height ◽

High Throughput Sequencing ◽

Agronomic Traits ◽

Crop Improvement ◽

Dwarf Mutant ◽

Sequencing Analysis ◽

Rna Seq ◽

Dwarf Phenotype ◽

Lodging Resistance

Abstract Background Plant height is one of the most important agronomic traits in many crops due to its influence on lodging resistance and yield performance. Although progress has been made in the use of dwarfing genes in crop improvement, identification of new dwarf germplasm is still of significant interest for breeding varieties with increased yield. Results Here we describe a dominant, dwarf mutant G7 of Brassica napus with down-curved leaves derived from tissue culture. To explore the genetic variation responsible for the dwarf phenotype, the mutant was crossed to a conventional line to develop a segregating F2 population. Bulks were formed from plants with either dwarf or conventional plant height and subjected to high throughput sequencing analysis via mutation mapping (MutMap). The dwarf mutation was mapped to a 0.6 Mb interval of B. napus chromosome C05. Candidate gene analysis revealed that one SNP causing an amino acid change in the domain II of Bna.IAA7.C05 may contribute to the dwarf phenotype. This is consistent with the phenotype of a gain-of-function indole-3-acetic acid (iaa) mutant in Bna.IAA7.C05 reported recently. GO and KEGG analysis of RNA-seq data revealed the down-regulation of auxin related genes, including many other IAA and small up regulated response (SAUR) genes, in the dwarf mutant. Conclusion Our studies characterize a new allele of Bna.IAA7.C05 responsible for the dwarf mutant generated from tissue culture. This may provide a valuable genetic resource for breeding for lodging resistance and compact plant stature in B. napus.

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Transcriptomic Profiling of Skeletal Muscle Reveals Candidate Genes Influencing Muscle Growth and Associated Lipid Composition in Portuguese Local Pig Breeds

Animals ◽

10.3390/ani11051423 ◽

2021 ◽

Vol 11 (5) ◽

pp. 1423

Author(s):

André Albuquerque ◽

Cristina Óvilo ◽

Yolanda Núñez ◽

Rita Benítez ◽

Adrián López-Garcia ◽

...

Keyword(s):

Candidate Genes ◽

Muscle Growth ◽

Rna Seq ◽

Next Generation Sequencing Technology ◽

Pig Breeds ◽

Nfkb Activation ◽

Main Gene ◽

Slow Type ◽

Longissimus Lumborum ◽

Generation Sequencing

Gene expression is one of the main factors to influence meat quality by modulating fatty acid metabolism, composition, and deposition rates in muscle tissue. This study aimed to explore the transcriptomics of the Longissimus lumborum muscle in two local pig breeds with distinct genetic background using next-generation sequencing technology and Real-Time qPCR. RNA-seq yielded 49 differentially expressed genes between breeds, 34 overexpressed in the Alentejano (AL) and 15 in the Bísaro (BI) breed. Specific slow type myosin heavy chain components were associated with AL (MYH7) and BI (MYH3) pigs, while an overexpression of MAP3K14 in AL may be associated with their lower loin proportion, induced insulin resistance, and increased inflammatory response via NFkB activation. Overexpression of RUFY1 in AL pigs may explain the higher intramuscular (IMF) content via higher GLUT4 recruitment and consequently higher glucose uptake that can be stored as fat. Several candidate genes for lipid metabolism, excluded in the RNA-seq analysis due to low counts, such as ACLY, ADIPOQ, ELOVL6, LEP and ME1 were identified by qPCR as main gene factors defining the processes that influence meat composition and quality. These results agree with the fatter profile of the AL pig breed and adiponectin resistance can be postulated as responsible for the overexpression of MAP3K14′s coding product NIK, failing to restore insulin sensitivity.

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Advancing clinical genomics and precision medicine with GVViZ: FAIR bioinformatics platform for variable gene-disease annotation, visualization, and expression analysis

Human Genomics ◽

10.1186/s40246-021-00336-1 ◽

2021 ◽

Vol 15 (1) ◽

Author(s):

Zeeshan Ahmed ◽

Eduard Gibert Renart ◽

Saman Zeeshan ◽

XinQi Dong

Keyword(s):

Data Analysis ◽

Patient Care ◽

Expression Analysis ◽

High Throughput ◽

Gene Annotation ◽

Next Generation Sequencing Data ◽

Rna Seq ◽

Sequencing Data ◽

Complex Disorders ◽

Transcriptomics Data

Abstract Background Genetic disposition is considered critical for identifying subjects at high risk for disease development. Investigating disease-causing and high and low expressed genes can support finding the root causes of uncertainties in patient care. However, independent and timely high-throughput next-generation sequencing data analysis is still a challenge for non-computational biologists and geneticists. Results In this manuscript, we present a findable, accessible, interactive, and reusable (FAIR) bioinformatics platform, i.e., GVViZ (visualizing genes with disease-causing variants). GVViZ is a user-friendly, cross-platform, and database application for RNA-seq-driven variable and complex gene-disease data annotation and expression analysis with a dynamic heat map visualization. GVViZ has the potential to find patterns across millions of features and extract actionable information, which can support the early detection of complex disorders and the development of new therapies for personalized patient care. The execution of GVViZ is based on a set of simple instructions that users without a computational background can follow to design and perform customized data analysis. It can assimilate patients’ transcriptomics data with the public, proprietary, and our in-house developed gene-disease databases to query, easily explore, and access information on gene annotation and classified disease phenotypes with greater visibility and customization. To test its performance and understand the clinical and scientific impact of GVViZ, we present GVViZ analysis for different chronic diseases and conditions, including Alzheimer’s disease, arthritis, asthma, diabetes mellitus, heart failure, hypertension, obesity, osteoporosis, and multiple cancer disorders. The results are visualized using GVViZ and can be exported as image (PNF/TIFF) and text (CSV) files that include gene names, Ensembl (ENSG) IDs, quantified abundances, expressed transcript lengths, and annotated oncology and non-oncology diseases. Conclusions We emphasize that automated and interactive visualization should be an indispensable component of modern RNA-seq analysis, which is currently not the case. However, experts in clinics and researchers in life sciences can use GVViZ to visualize and interpret the transcriptomics data, making it a powerful tool to study the dynamics of gene expression and regulation. Furthermore, with successful deployment in clinical settings, GVViZ has the potential to enable high-throughput correlations between patient diagnoses based on clinical and transcriptomics data.

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Genetic Mapping and Identification of the Candidate Gene for White Seed Coat in Cucurbita maxima

International Journal of Molecular Sciences ◽

10.3390/ijms22062972 ◽

2021 ◽

Vol 22 (6) ◽

pp. 2972

Author(s):

Yuzi Shi ◽

Meng Zhang ◽

Qin Shu ◽

Wei Ma ◽

Tingzhen Sun ◽

...

Keyword(s):

Seed Coat ◽

Molecular Breeding ◽

Coat Color ◽

Recessive Gene ◽

Myb Transcription Factor ◽

Cucurbita Maxima ◽

Seed Coat Color ◽

Rna Seq ◽

Edible Seed ◽

Segregating Population

Seed coat color is an important agronomic trait of edible seed pumpkin in Cucurbita maxima. In this study, the development pattern of seed coat was detected in yellow and white seed coat accessions Wuminglv and Agol. Genetic analysis suggested that a single recessive gene white seed coat (wsc) is involved in seed coat color regulation in Cucurbita maxima. An F2 segregating population including 2798 plants was used for fine mapping and a candidate region containing nine genes was identified. Analysis of 54 inbred accessions revealed four main Insertion/Deletion sites in the promoter of CmaCh15G005270 encoding an MYB transcription factor were co-segregated with the phenotype of seed coat color. RNA-seq analysis and qRT-PCR revealed that some genes involved in phenylpropanoid/flavonoid metabolism pathway displayed remarkable distinction in Wuminglv and Agol during the seed coat development. The flanking InDel marker S1548 was developed to predict the seed coat color in the MAS breeding with an accuracy of 100%. The results may provide valuable information for further studies in seed coat color formation and structure development in Cucurbitaceae crops and help the molecular breeding of Cucurbita maxima.

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RcTGA1 and glucosinolate biosynthesis pathway involvement in the defence of rose against the necrotrophic fungus Botrytis cinerea

BMC Plant Biology ◽

10.1186/s12870-021-02973-z ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Penghua Gao ◽

Hao Zhang ◽

Huijun Yan ◽

Qigang Wang ◽

Bo Yan ◽

...

Keyword(s):

Disease Resistance ◽

Gene Annotation ◽

Infected Plant ◽

Grey Mould ◽

Cascade Reactions ◽

Postharvest Quality ◽

Rna Seq ◽

Protein Activity ◽

Phenylpropanoid Biosynthesis ◽

And Cluster Analysis

Abstract Background Rose is an important economic crop in horticulture. However, its field growth and postharvest quality are negatively affected by grey mould disease caused by Botrytis c. However, it is unclear how rose plants defend themselves against this fungal pathogen. Here, we used transcriptomic, metabolomic and VIGS analyses to explore the mechanism of resistance to Botrytis c. Result In this study, a protein activity analysis revealed a significant increase in defence enzyme activities in infected plants. RNA-Seq of plants infected for 0 h, 36 h, 60 h and 72 h produced a total of 54 GB of clean reads. Among these reads, 3990, 5995 and 8683 differentially expressed genes (DEGs) were found in CK vs. T36, CK vs. T60 and CK vs. T72, respectively. Gene annotation and cluster analysis of the DEGs revealed a variety of defence responses to Botrytis c. infection, including resistance (R) proteins, MAPK cascade reactions, plant hormone signal transduction pathways, plant-pathogen interaction pathways, Ca2+ and disease resistance-related genes. qPCR verification showed the reliability of the transcriptome data. The PTRV2-RcTGA1-infected plant material showed improved susceptibility of rose to Botrytis c. A total of 635 metabolites were detected in all samples, which could be divided into 29 groups. Metabonomic data showed that a total of 59, 78 and 74 DEMs were obtained for T36, T60 and T72 (T36: Botrytis c. inoculated rose flowers at 36 h; T60: Botrytis c. inoculated rose flowers at 60 h; T72: Botrytis c. inoculated rose flowers at 72 h) compared to CK, respectively. A variety of secondary metabolites are related to biological disease resistance, including tannins, amino acids and derivatives, and alkaloids, among others; they were significantly increased and enriched in phenylpropanoid biosynthesis, glucosinolates and other disease resistance pathways. This study provides a theoretical basis for breeding new cultivars that are resistant to Botrytis c. Conclusion Fifty-four GB of clean reads were generated through RNA-Seq. R proteins, ROS signalling, Ca2+ signalling, MAPK signalling, and SA signalling were activated in the Old Blush response to Botrytis c. RcTGA1 positively regulates rose resistance to Botrytis c. A total of 635 metabolites were detected in all samples. DEMs were enriched in phenylpropanoid biosynthesis, glucosinolates and other disease resistance pathways.

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Erratum: Multi-platform assessment of transcriptome profiling using RNA-seq in the ABRF next-generation sequencing study

Nature Biotechnology ◽

10.1038/nbt1114-1166a ◽

2014 ◽

Vol 32 (11) ◽

pp. 1166-1166 ◽

Cited By ~ 3

Author(s):

Sheng Li ◽

Scott W Tighe ◽

Charles M Nicolet ◽

Deborah Grove ◽

Shawn Levy ◽

...

Keyword(s):

Next Generation Sequencing ◽

Transcriptome Profiling ◽

Rna Seq ◽

Next Generation ◽

Generation Sequencing

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Phosphate transporter genes: genome-wide identification and characterization in Camelina sativa

10.1101/2021.02.28.433256 ◽

2021 ◽

Author(s):

Soosan Hasanzadeh ◽

Sahar Faraji ◽

Abdullah ◽

Parviz Heidari

Keyword(s):

Phosphate Transporter ◽

Rna Seq ◽

Specific Expression ◽

Cis Acting ◽

Genome Wide ◽

Sodium Dependent ◽

Intron Number ◽

Response To Stress ◽

Growth Energy ◽

Root Tissues

Phosphorus is known as a key element associated with growth, energy, and cell signaling. In plants, phosphate transporters (PHTs) are responsible for moving and distributing phosphorus in cells and organs. PHT genes have been genome-wide identified and characterized in various plant species, however, these genes have not been widely identified based on available genomic data in Camellia sativa, which is an important oil seed plant. In the present study, we found 66 PHT genes involved in phosphate transporter/translocate in C. sativa. The recognized genes belonged to PHTs1, PHTs2, PHTs4, PHOs1, PHO1 homologs, glycerol-3-PHTs, sodium dependent PHTs, inorganic PHTs, xylulose 5-PHTs, glucose-6-phosphate translocators, and phosphoenolpyruvate translocators. Our finding revealed that PHT proteins are divers based on their physicochemical properties such as Isoelectric point (pI), molecular weight, GRAVY value, and exon-intron number(s). Besides, the expression profile of PHT genes in C. sativa based on RNA-seq data indicate that PHTs are involved in response to abiotic stresses such as cold, drought, salt, and cadmium. The tissue specific expression high expression of PHO1 genes in root tissues of C. sativa. In additions, four PHTs, including a PHT4;5 gene, a sodium dependent PHT gene, and two PHO1 homolog 3 genes were found with an upregulation in response to aforementioned studied stresses. In the current study, we found that PHO1 proteins and their homologs have high potential to post-translation modifications such as N-glycosylation and phosphorylation. Besides, different cis-acting elements associated with response to stress and phytohormone were found in the promoter region of PHT genes. Overall, our results show that PHT genes play various functions in C. Sativa and regulate Camellia responses to external and intracellular stimuli. The results can be used in future studies related to the functional genomics of C. sativa.

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Maximizing prediction of orphan genes in assembled genomes

10.1101/2019.12.17.880294 ◽

2019 ◽

Cited By ~ 2

Author(s):

Arun Seetharam ◽

Urminder Singh ◽

Jing Li ◽

Priyanka Bhandary ◽

Zeb Arendsee ◽

...

Keyword(s):

Sequence Homology ◽

Evolutionary History ◽

Direct Evidence ◽

Gene Annotation ◽

Rna Seq ◽

Orphan Genes ◽

Orphan Gene ◽

New Genes ◽

Conserved Genes ◽

Rapid Emergence

ABSTRACTThe evolutionary rapid emergence of new genes gives rise to “orphan genes” that share no sequence homology to genes in closely related genomes. These genes provide organisms with a reservoir of genetic elements to quickly respond to changing selection pressures. Gene annotation pipelines that combine ab initio machine-learning with sequence homology-based searches are efficient in identifying basal genes with a long evolutionary history. However, their ability to identify orphan genes and other young genes has not been systematically evaluated. Here, we classify the phylostrata of curated Arabidopsis thaliana genes and use these to assess the ability of two of the most prevalent annotation pipelines, MAKER and BRAKER, to predict orphans and other young genes. MAKER predictions are highly dependent on the RNA-Seq evidence, predicting between 11% and 60% of the orphan-genes and 95% to 98% of basal-genes in the annotated genome of Arabidopsis. In contrast, BRAKER consistently predicts 33% of orphan-genes and 98% of basal-genes. A less used method to identify genes is by directly aligning RNA-Seq data to the genome sequence. We present a Findable, Accessible, Interoperable and Reusable (FAIR) approach, called BIND, that mitigates the under-prediction of orphan genes. BIND combines BRAKER predictions with direct evidence-based inference of transcripts based on RNA-Seq alignments to the genome. BIND increases the number and accuracy of orphan gene predictions, identifying 68% of Araport11-annotated orphan genes and 99% of the conserved genes.

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TrancriptomeReconstructoR, A Data-Driven Annotation of Complex Transcriptomes

10.21203/rs.3.rs-131404/v1 ◽

2020 ◽

Author(s):

Maxim Ivanov ◽

Albin Sandelin ◽

Sebastian Marquardt

Keyword(s):

De Novo ◽

Gene Annotation ◽

R Package ◽

Sequence Information ◽

Rna Seq ◽

Sequencing Data ◽

Gene Model ◽

Preparation Methods ◽

Downstream Analysis

Abstract Background: The quality of gene annotation determines the interpretation of results obtained in transcriptomic studies. The growing number of genome sequence information calls for experimental and computational pipelines for de novo transcriptome annotation. Ideally, gene and transcript models should be called from a limited set of key experimental data. Results: We developed TranscriptomeReconstructoR, an R package which implements a pipeline for automated transcriptome annotation. It relies on integrating features from independent and complementary datasets: i) full-length RNA-seq for detection of splicing patterns and ii) high-throughput 5' and 3' tag sequencing data for accurate definition of gene borders. The pipeline can also take a nascent RNA-seq dataset to supplement the called gene model with transient transcripts.We reconstructed de novo the transcriptional landscape of wild type Arabidopsis thaliana seedlings as a proof-of-principle. A comparison to the existing transcriptome annotations revealed that our gene model is more accurate and comprehensive than the two most commonly used community gene models, TAIR10 and Araport11. In particular, we identify thousands of transient transcripts missing from the existing annotations. Our new annotation promises to improve the quality of A.thaliana genome research.Conclusions: Our proof-of-concept data suggest a cost-efficient strategy for rapid and accurate annotation of complex eukaryotic transcriptomes. We combine the choice of library preparation methods and sequencing platforms with the dedicated computational pipeline implemented in the TranscriptomeReconstructoR package. The pipeline only requires prior knowledge on the reference genomic DNA sequence, but not the transcriptome. The package seamlessly integrates with Bioconductor packages for downstream analysis.

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SparK: A Publication-quality NGS Visualization Tool

10.1101/845529 ◽

2019 ◽

Author(s):

Stefan Kurtenbach ◽

J. William Harbour

Keyword(s):

Standard Deviation ◽

Ucsc Genome Browser ◽

Genomic Region ◽

Visualization Tool ◽

Command Line ◽

Integrative Genomics ◽

Rna Seq ◽

Vector Graphic ◽

Ngs Data ◽

Publication Quality

AbstractWhile there are sophisticated resources available for displaying NGS data, including the Integrative Genomics Viewer (IGV) and the UCSC genome browser, exporting regions and assembling figures for publication remains challenging. In particular, customizing track appearance and overlaying track replicates is a manual and time-consuming process. Here, we present SparK, a tool which auto-generates publication-ready, high-resolution, true vector graphic figures from any NGS-based tracks, including RNA-seq, ChIP-seq, and ATAC-seq. Novel functions of SparK include averaging of replicates, plotting standard deviation tracks, and highlighting significantly changed areas. SparK is written in Python 3, making it executable on any major OS platform. Using command line prompts to generate figures allows later changes to be made very easy. For instance, if the genomic region of the plot needs to be changed, or tracks need to be added or removed, the figure can easily be re-generated within seconds without the manual process of re-exporting and re-assembling everything. After plotting with SparK, changes to the output SVG vector graphic files are simple to make, including text, lines, and colors. SparK is publicly available on GitHub: https://github.com/harbourlab/SparK.

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