@article{Kim2018,
abstract = {Hot pepper (Capsicum annuum) is one of the most consumed vegetable crops in the world and useful to human as it has many nutritional and medicinal values. Genomic resources of pepper are publically available since the pepper genomes have been completed and massive data such as transcriptomes have been deposited. Nevertheless, global transcriptome profiling is needed to identify molecular mechanisms related to agronomic traits in pepper, but limited analyses are published. Here, we report the comprehensive analysis of pepper transcriptomes during fruit ripening and pathogen infection. For the ripening, transcriptome data were obtained from placenta and pericarp at seven developmental stages. To reveal global transcriptomic landscapes during infection, leaves at six time points post-infection by one of three pathogens (Phytophthora infestans, Pepper mottle virus, and Tobacco mosaic virus P0 strain) were profiled. The massive parallel transcriptome profiling in this study will serve as a valuable resource for detection of molecular networks of fruit development and disease resistance in Capsicum annuum.},
author = {Kim, Myung Shin and Kim, Seungill and Jeon, Jongbum and Kim, Ki Tae and Lee, Hyun Ah and Lee, Hye Young and Park, Jieun and Seo, Eunyoung and Kim, Saet Byul and Yeom, Seon In and Lee, Yong Hwan and Choi, Doil},
doi = {10.1038/sdata.2018.103},
file = {:Users/almeidasilvaf/Documents/Papers/sdata2018103.pdf:pdf},
issn = {20524463},
journal = {Scientific Data},
pages = {1--6},
pmid = {29870035},
title = {{Global gene expression profiling for fruit organs and pathogen infections in the pepper, <i>Capsicum annuum</i> L.}},
volume = {5},
year = {2018}
}
@article{Siddique2019,
abstract = {Phytophthora capsici (Leon.) is a globally prevalent, devastating oomycete pathogen that causes root rot in pepper (Capsicum annuum). Several studies have identified quantitative trait loci (QTL) underlying resistance to P. capsici root rot (PcRR). However, breeding for pepper cultivars resistant to PcRR remains challenging due to the complexity of PcRR resistance. Here, we combined traditional QTL mapping with GWAS to broaden our understanding of PcRR resistance in pepper. Three major-effect loci (5.1, 5.2, and 5.3) conferring broad-spectrum resistance to three isolates of P. capsici were mapped to pepper chromosome P5. In addition, QTLs with epistatic interactions and minor effects specific to isolate and environment were detected on other chromosomes. GWAS detected 117 significant SNPs across the genome associated with PcRR resistance, including SNPs on chromosomes P5, P7, and P11 that colocalized with the QTLs identified here and in previous studies. Clusters of candidate nucleotide-binding site-leucine-rich repeat (NBS-LRR) and receptor-like kinase (RLK) genes were predicted within the QTL and GWAS regions; such genes often function in disease resistance. These candidate genes lay the foundation for the molecular dissection of PcRR resistance. SNP markers associated with QTLs for PcRR resistance will be useful for marker-assisted breeding and genomic selection in pepper breeding.},
author = {Siddique, Muhammad Irfan and Lee, Hea Young and Ro, Na Young and Han, Koeun and Venkatesh, Jelli and Solomon, Abate Mekonnen and Patil, Abhinandan Surgonda and Changkwian, Amornrat and Kwon, Jin Kyung and Kang, Byoung Cheorl},
doi = {10.1038/s41598-019-46342-1},
file = {:Users/almeidasilvaf/Documents/Papers/s41598-019-46342-1.pdf:pdf},
issn = {20452322},
journal = {Scientific Reports},
number = {1},
pages = {1--15},
pmid = {31292472},
publisher = {Springer US},
title = {{Identifying candidate genes for Phytophthora capsici resistance in pepper (Capsicum annuum) via genotyping-by-sequencing-based QTL mapping and genome-wide association study}},
url = {http://dx.doi.org/10.1038/s41598-019-46342-1},
volume = {9},
year = {2019}
}
@article{Proost2015,
abstract = {Comparative sequence analysis has significantly altered our view on the complexity of genome organization and gene functions in different kingdoms. PLAZA 3.0 is designed to make comparative genomics data for plants available through a user-friendly web interface. Structural and functional annotation, gene families, protein domains, phylogenetic trees and detailed information about genome organization can easily be queried and visualized. Compared with the first version released in 2009, which featured nine organisms, the number of integrated genomes is more than four times higher, and now covers 37 plant species. The new species provide a wider phylogenetic range as well as a more in-depth sampling of specific clades, and genomes of additional crop species are present. The functional annotation has been expanded and now comprises data from Gene Ontology, MapMan, UniProtKB/Swiss-Prot, PlnTFDB and PlantTFDB. Furthermore, we improved the algorithms to transfer functional annotation from well-characterized plant genomes to other species. The additional data and new features make PLAZA 3.0 (http://bioinformatics.psb.ugent.be/plaza/) a versatile and comprehensible resource for users wanting to explore genome information to study different aspects of plant biology, both in model and non-model organisms.},
author = {Proost, Sebastian and {Van Bel}, Michiel and Vaneechoutte, Dries and {Van de Peer}, Yves and Inz{\'{e}}, Dirk and Mueller-Roeber, Bernd and Vandepoele, Klaas},
doi = {10.1093/nar/gku986},
issn = {0305-1048},
journal = {Nucleic Acids Research},
month = {jan},
number = {D1},
pages = {D974--D981},
title = {{PLAZA 3.0: an access point for plant comparative genomics}},
url = {https://doi.org/10.1093/nar/gku986},
volume = {43},
year = {2015}
}
@article{Jin2017,
abstract = {With the goal of providing a comprehensive, high-quality resource for both plant transcription factors (TFs) and their regulatory interactions with target genes, we upgraded plant TF database PlantTFDB to version 4.0 (http://planttfdb.cbi.pku.edu.cn/). In the new version, we identified 320 370 TFs from 165 species, presenting a more comprehensive genomic TF repertoires of green plants. Besides updating the pre-existing abundant functional and evolutionary annotation for identified TFs, we generated three new types of annotation which provide more directly clues to investigate functional mechanisms underlying: (i) a set of high-quality, non-redundant TF binding motifs derived from experiments; (ii) multiple types of regulatory elements identified from high-throughput sequencing data; (iii) regulatory interactions curated from literature and inferred by combining TF binding motifs and regulatory elements. In addition, we upgraded previous TF prediction server, and set up four novel tools for regulation prediction and functional enrichment analyses. Finally, we set up a novel companion portal PlantRegMap (http://plantregmap.cbi.pku.edu.cn) for users to access the regulation resource and analysis tools conveniently.},
annote = {Jin, Jinpu
Tian, Feng
Yang, De-Chang
Meng, Yu-Qi
Kong, Lei
Luo, Jingchu
Gao, Ge
eng
Research Support, Non-U.S. Gov't
England
2016/12/08 06:00
Nucleic Acids Res. 2017 Jan 4;45(D1):D1040-D1045. doi: 10.1093/nar/gkw982. Epub 2016 Oct 24.},
author = {Jin, J and Tian, F and Yang, D C and Meng, Y Q and Kong, L and Luo, J and Gao, G},
doi = {10.1093/nar/gkw982},
file = {:Users/almeidasilvaf/Library/Application Support/Mendeley Desktop/Downloaded/Jin et al. - 2017 - PlantTFDB 4.0 toward a central hub for transcription factors and regulatory interactions in plants.pdf:pdf},
isbn = {1362-4962 (Electronic)
0305-1048 (Linking)},
journal = {Nucleic Acids Res},
keywords = {*Databases, Genetic,*Gene Expression Regulation, Plant,*Gene Regulatory Networks,Binding Sites,Computational Biology/methods,Evolution, Molecular,Genomics/methods,Molecular Sequence Annotation,Nucleotide Motifs,Plants/*genetics/*metabolism,Protein Binding,Transcription Factors/*metabolism,Web Browser,Workflow},
number = {D1},
pages = {D1040--D1045},
pmid = {27924042},
title = {{PlantTFDB 4.0: toward a central hub for transcription factors and regulatory interactions in plants}},
url = {http://www.ncbi.nlm.nih.gov/pubmed/27924042},
volume = {45},
year = {2017}
}

@Manual{R-BioNERO,
  title = {BioNERO: Biological Network Reconstruction Omnibus},
  author = {Fabricio Almeida-Silva and Thiago Venancio},
  year = {2021},
  note = {R package version 1.0.0},
  url = {https://github.com/almeidasilvaf/BioNERO},
}

@Article{rtracklayer2009,
  title = {rtracklayer: an R package for interfacing with
                  genome browsers},
  author = {Michael Lawrence and Robert Gentleman and Vincent Carey},
  year = {2009},
  journal = {Bioinformatics},
  volume = {25},
  pages = {1841-1842},
  doi = {10.1093/bioinformatics/btp328},
  url = {http://bioinformatics.oxfordjournals.org/content/25/14/1841.abstract},
}

