Plant Molecular Biology Reporter

, Volume 32, Issue 2, pp 438–451 | Cite as

Differentially Expressed Genes during Flowering and Grain Filling in Common Bean (Phaseolus vulgaris) Grown under Drought Stress Conditions

  • Bárbara Salomão de Faria Müller
  • Tetsu Sakamoto
  • Ricardo Diógenes Dias Silveira
  • Patricia Fernanda Zambussi-Carvalho
  • Maristela Pereira
  • Georgios Joanis PappasJr
  • Marcos Mota do Carmo Costa
  • Cleber Moraes Guimarães
  • Wendell Jacinto Pereira
  • Claudio Brondani
  • Rosana Pereira Vianello-Brondani
Original Paper


Drought stress, particularly during the flowering and grain-filling stages of growth, contributes to serious yield loss in common bean (Phaseolus vulgaris L.). The aim of this study was to identify genes induced in response to drought stress using transcriptome analysis of contrasting genotypes. Using leaf tissues of tolerant (BAT 477) and susceptible common bean genotypes (Pérola), collected at the flowering and grain-filling stages, four complementary deoxyribonucleic acid representational difference analysis subtractive libraries were constructed and then sequenced. A total of 7,203 (77.6 %) sequences with an average sequence size of 570 bp were considered valid, for a combined 4 Mbp sequence. According to a differential display analysis, 802 expressed sequence tags, distributed across 67 contigs, were differentially expressed by the tolerant (37 contigs) and susceptible genotypes (30 contigs) after identification under drought conditions during the two investigated plant developmental stages. Of these differential contigs, the 13 most frequent genes were exclusive to the tolerant genotype. Based on BLAST2GO, 73 % of the gene sequences were annotated and 12 % showed mapping results, with the highest similarity rate corresponding to Glycine max (41 %). According to gene ontology functional analysis, 48 % of the sequences were attributed to cell metabolic processes. Overall, 8.3 % of the transcribed sequences exhibited similarity to transcription factors, predominantly those of the AP2-EREBP family (97.8 %). Of the target sequences validated by quantitative real-time polymerase chain reaction, most genes showed an expression level that agreed with that predicted by in silico analysis. Thus, the drought transcriptome dataset is a valuable resource on the variation in these gene sequences, offering the opportunity to identify robust molecular markers tightly linked to trait-controlling loci for use in marker-assisted breeding.


Legume crop Abiotic stress ESTs sequencing Drought stress 



We thank the National Council for Scientific and Technological Development (CNPq) for the grants to MP, GJPJr, CB, and RPV-B; the Coordination of Improvement of Higher-Education Personnel/Ministry of Education (CAPES/MEC) for the grants to BSFM, RDDS, and PFZC; the Minas Gerais State Research Foundation (Fapemig) for the grant to TS; and the Brazilian Enterprise for Agricultural Research (Embrapa MP2) for financial support for this research.

Supplementary material

11105_2013_651_MOESM1_ESM.doc (32 kb)
Additional File 1 TaqMan assay of the differentially expressed genes of common beans exposed to drought conditions. The library in which the sequence originated is indicated, as are the contig identification, TaqMan assay, and number of cluster copies (redundancy). (DOC 32 kb)
11105_2013_651_MOESM2_ESM.doc (40 kb)
Additional File 2 Data for the cDNA samples used in qPCR to validate genes that were identified as differentially expressed through in silico analysis. (DOC 40 kb)
11105_2013_651_MOESM3_ESM.doc (140 kb)
Additional File 3 Identification of the 67 contigs that were differentially expressed by the BAT 477 (37 contigs) and Pérola genotypes (30), which are tolerant and susceptible to water deficit, respectively, during both investigated developmental stages. Data include contig identification, derived gene products from the GenBank database, species with the highest similarity estimates and corresponding E-values, and the number of times the EST was sampled. (DOC 140 kb)
11105_2013_651_MOESM4_ESM.doc (109 kb)
Additional File 4 Distribution of sequences according to GO term categorization. (DOC 109 kb)
11105_2013_651_MOESM5_ESM.doc (34 kb)
Additional file 5 Statistical analysis based on values of the relative quantification (RQ) of four genes comparing the contrasting genotypes BAT477 (tolerant) and Pérola (susceptive) under different times of exposure to drought. The treatments were the control (T0) and two dehydration condition (T25 and T150). Letters shared in common between or among the groups would indicate no significant difference (95% IC, p < 0.05). (DOC 33 kb)
11105_2013_651_MOESM6_ESM.doc (68 kb)
Supplementary Figure 1 Representation of the distributions of EST sequence and plant species similarities from BLAST2GO and the NCBI database. (DOC 68.5 KB)
11105_2013_651_MOESM7_ESM.doc (64 kb)
Supplementary Figure 2 Annotation graph of the total sequences derived from the four P. vulgaris cDNA–RDA subtraction libraries. (DOC 63.5 KB)


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Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  • Bárbara Salomão de Faria Müller
    • 1
    • 3
  • Tetsu Sakamoto
    • 2
  • Ricardo Diógenes Dias Silveira
    • 3
  • Patricia Fernanda Zambussi-Carvalho
    • 4
  • Maristela Pereira
    • 4
  • Georgios Joanis PappasJr
    • 5
  • Marcos Mota do Carmo Costa
    • 6
  • Cleber Moraes Guimarães
    • 7
  • Wendell Jacinto Pereira
    • 3
  • Claudio Brondani
    • 3
  • Rosana Pereira Vianello-Brondani
    • 3
  1. 1.Plant Molecular Genetics Laboratory, Institute of Biotechnology Applied to Agriculture and Animal Science (BIOAGRO)Federal University of ViçosaViçosaBrazil
  2. 2.BioData Laboratory, Institute of Biological ScienceFederal University of Minas GeraisBelo HorizonteBrazil
  3. 3.Biotechnology LaboratoryEmbrapa Rice and BeansSanto Antônio de GoiásBrazil
  4. 4.Molecular Biology Laboratory, Department of Biochemistry and Molecular Biology, Institute of Biological ScienceFederal University of GoiásGoiâniaBrazil
  5. 5.Laboratory of Molecular Biology, Department of Cellular BiologyUniversity of BrasíliaBrasíliaBrazil
  6. 6.Bioinformatics LaboratoryEmbrapa Genetic Resources and BiotechnologyBrasíliaBrazil
  7. 7.Agrophysiology LaboratoryEmbrapa Rice and BeansSanto Antônio de GoiásBrazil

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