Transcriptional Profiling of Gene Expression During Malting in Barley

Abstract

Malt is a major raw material for the production of beer, and during the malting process barley grains are germinated under strictly-controlled conditions. Malting is a complex process that involves many enzymes. Four enzymes known to be important in malting are α-amylase, β-amylase, α-glucosidase, and limit dextrinase. The goal of this project is to isolate specific gene sequences and allelic variants of genes involved with the malting process. This includes known genes as well as undiscovered genes. To investigate the determining factors of malting quality, RNA expression patterns in different stages of micromalting (i.e, steeping, germination, kilning) in the 6-row cultivar ‘Morex’ was studied through hybridization of RNA against the 22K Barley1 Affymetrix GeneChip probe array. A subset of candidate genes that appear to be important in malting was identified. Expression patterns of these genes were then compared among the 6-row cultivars, ‘Morex’ and ‘Legacy’, and the 2-row cultivars, ‘Harrington’ and ‘Merit.’ Genes that were differentially expressed between 2-row and 6-row cultivars, as well as among individual cultivars were identified.

Introduction

DNA arrays have been successfully utilized in plants to help decipher biochemical pathways involved in complex traits. Two recent studies investigated pathways involved in the responses of Arabidopsis thaliana against infection by cucumber mosaic virus strain Y (1) and barley against attack by Blumeria graminis f. sp hordei (2). Both studies identified genes of unkown function which appear to be important in the plant’s defense response against the pathogens.

Malting quality of barley involves several traits that show quantitative variation (3). The number of QTLs (>150) that have been associated with malting quality phenotypes indicate the involvement of many more genes than the four major genes known to be important in seed germination and malting. Based on the hypothesis that the observed differences at the trait level are due to differences in the expression of the underlying genes, cDNA array technologies could be deployed to monitor gene expression in different genotypes and to identify genes contributing to complex traits such as malting (4). Based on an analysis of 1400 ESTs, between 17 and 30 candidate genes were identified for each of six malting quality parameters analyzed (4). These genes include well known malting related genes, as well as others with unknown function. This study was conducted to identify candidate genes that may be important determinants of malting quality in barley using the Barley 1 GeneChip probe array containing 22,792 barley genes (5). There were two specific objectives: 1) to identify genes that are highly regulated during malting in the cultivar ‘Morex’, and; 2) identify genes that show expression level polymorphisms among four malting cultivars.

Materials and Methods

Plant Material and Micromalting
Four barley cultivars were used: ‘Harrington’, ‘Legacy’, ‘Merit’, and ‘Morex’. One hundred grams of seed from each cultivar were micro-malted at Busch Agricultural Resources, Inc., Fort Collins, CO. Three sets of all cultivars were separately germinated. Samples for ‘Morex’ were collected at 4 stages: 1) steeping (14^oC for 48h), 2) Day-2 (48h germination, 20^oC) malting; 3) Day-4 malting (96 h germination, 20^oC) and 4) after kilning (22 hrs). For the other three cultivars, samples were collected at Day-2 and Day-4. Dry seed was used as control.

RNA Extraction and Hybridization
Total RNA was prepared from a bulk of 5 seeds per sample using TRIzol Reagent (Gibco BRL Life Technologies, Rockville, MD) and tested for quality by denaturing gradient gel electrophoresis. Isolated total RNA samples were processed as recommended by Affymetrix, Inc. (Affymetrix GeneChip Expression Analysis Technical Manual, Affymetrix, Inc., Santa Clara, CA). All starting total RNA samples were quality assessed prior to beginning target preparation/processing steps by running out a small amount of each sample (typically 25-250 ng/well) onto a RNA Lab-On-A-Chip (Caliper Technologies Corp., Mountain View, CA) that was evaluated on an Agilent Bioanalyzer 2100 (Agilent Technologies, Palo Alto, CA). Single-stranded, then double-stranded cDNA was synthesized from the poly(A)+ mRNA present in the isolated total RNA (10 ug total RNA starting material each sample reaction) using the SuperScript Double-Stranded cDNA Synthesis Kit (Invitrogen Corp., Carlsbad, CA ) and poly (T)-nucleotide primers that contained a sequence recognized by T7 RNA polymerase.A portion of the resulting ds cDNA was used as a template to generate biotin-tagged cRNA from an in vitro transcription reaction (IVT), using the BioArray High-Yield RNA Transcript Labeling Kit (T7) (Enzo Diagnostics, Inc., Farmingdale, NY). Fifteen µg of the resulting biotin-tagged cRNA was fragmented to strands of 35-200 bases in length following prescribed protocols (Affymetrix GeneChip Expression Analysis Technical Manual). Subsequently, 10 µg of this fragmented target cRNA was hybridized at 45°C with rotation for 16 hours (Affymetrix GeneChip Hybridization Oven 640) to probe sets present on the Barley1 GeneChip probe array. The GeneChip arrays were washed and then stained (SAPE, streptavidin-phycoerythrin) on an Affymetrix Fluidics Station 450, followed by scanning on a GeneChip Scanner 3000.

Experimental Design and Data analysis
To identify genes that are highly regulated during malting (Objective 1), RNA from 4 different stages of micro-malted ‘Morex’ and dry seed were hybridized onto the Barley 1 GeneChip probe array. Three replications per time point were conducted. For comparison of gene expression profiles among cultivars, RNA from Day-2 and Day-4 from ‘Legacy’, ‘Harrington’ and ‘Merit’ was hybridized to Barley 1 GeneChip array. Two replications per genotype/time point were performed. The data were quantified and analyzed using GCOS 1.1.1 software (Affymetrix, Inc.) and/or ArrayAssist’s gcRMA (Iobion Informatics, Inc.) using default values (Scaling, Target Signal Intensity = 500; Normalization, All Probe Sets, and Parameters, were set at default values). Statistical analysis was done using limma (Linear models for microarray data) (Smythe et al., 2005, http://bioinf.wehi.edu.au/limma) and hierarchical clustering and Bioconductor software (6)

Quantitative RT-PCR
Quantitative RT-PCR was done using the QuantiTect® SYBR® Green RT-PCR system (Qiagen Inc., Valencia, CA, USA) and the Cepheid Smart Cycler (Cepheid, Sunnyvale CA, USA). Primers were designed using the specific barley sequences on the Barley1 GeneChip probe array.

Results and Discussion

Transcript profiling of genes expressed during different stages of malting in barley
In order to better understand malting and possibly discover novel genes involved in this process, we employed the Affymetrix Barley 1 GeneChip probe array for transcriptional profiling of gene expression during malting. We began by looking at the main stages of malting using ‘Morex’ as a model and then compared the gene expression in these different malting stages to dry seed as control. The malting stages included steeping, Day-2 and Day-4 germination, and after kilning.

To evaluate technical and biological variability, we analyzed replication clusters for both the control and the different malting stages. The scatter plots showed that the same genes clustered in similar orders indicating that the replications gave highly reproducible results.

Gene expression at each of the four malting stages examined was compared against dry seed expression profiles. Four hundred eighty seven genes were identified which showed 5000-fold greater signal intensity than dry seed at a significance level of P<0.0005. Majority of the genes were up-regulated during steeping or imbibition compared to dry seed. Less than half of the genes were down-regulated. However, almost all of the genes increased in expression level from steeping to Day-2 and Day-4 germination.

Genes for enzymes known to be important in malting, including α-amylase, β-amylase, and isoamylase-like proteins, are among the highly expressed genes (Table 1). The highly expressed genes include genes that function in starch degradation, sucrose metabolism/energy production, cell wall degradation, hydrolytic enzyme inhibition, senescence, cell division and growth, lipid metabolism, amino acid metabolism, and protein synthesis. Furthermore, genes that are involved in stress/defense response as well as temperature response were also included in this list. Interestingly, 26% of highly expressed genes were of unknown function. This suggests that there are other genes involved in malting which have not been identified. Similar results were recently reported in a study to identify genes that are highly expressed during malting among 1400 ESTs (4).

Expression of genes that were co-regulated with α-amylase were investigated further by RT-PCR for two reasons. First, is to validate the gene expression profiles observed in the GeneChip array and second, to investigate expression at additional time points (i.e., 24 h steeping, 48 h steeping, days 1, 2, 3, and 4 malting). The results of RT-PCR were consistent with the results of the microrray (not shown). Sixteen genes that were co-regulated with genes coding for α-amylase and limit dextrinase and are involved in starch and cell wall degradation are being analyzed further by RT-PCR.

Table 1. Partial list of genes significantly expressed in Morex after 24 h (steeping) and 96 h (day 4) of micromalting compared to dry seed (P < 0.0001) grouped according to function

Starch degradation alpha-amylase [Hordeum vulgare subsp. vulgare]; Alpha-amylase type a isozyme precursor (1,4-alpha-d-glucan glucanohydrolase) (amy1) (low pi alpha amylase); Beta-amylase (1,4-alpha-D-glucan maltohydrolase); Iso-amylase-like protein Sucrose metabolism/energy production 2-oxoglutarate/malate translocator (clones OMT134 and OMT106), mitochondrial membrane - proso millet; Phosphoglycerate kinase, cytosolic pir||TVWTGY; phosphoglycerate kinase (EC 2.7.2.3), cytosolic – wheat; Glyceraldehyde 3-phosphate dehydrogenase (GAPDH) Inhibitors of hydrolytic enzymes Alpha-amylase/subtilisin inhibitor precursor (BASI) pir||S04860 alpha-amylase/subtilisin inhibitor precursor – barley; bowman-birk type trypsin inhibitor pir||TIBHB trypsin inhibitor (Bowman-Birk) - two-rowed barley Temperature stress response cold acclimation protein WCOR413 - wheat gb|AAB18207.1| cold acclimation protein WCOR413 [Triticum aestivum]; heat shock protein HSC70-1, cytosolic [imported] - spinach gb|AAA62445.1| heat shock protein Stress response/defense 23 kd jasmonate-induced protein pir||S22514 jasmonate-induced protein 1 – barley; chitinase (EC 3.2.1.14) CH11, acidic - maize (fragment) gb|AAA62420.1| (L16798) class I acidic chitinase [Zea mays]; (1->3,1->4)-beta-glucanase isoenzyme II (EC 3.2.1.73) [Hordeum vulgare] Senescence Ethylene-inducible protein [Oryza sativa] Putative pyridoxine/pyridoxal 5-phosphate S-adenosylmethionine synthetase 1 (Methionine adenosyltransferase 1) (AdoMet synthetase 1 Cell division and growth Tubulin beta-2 chain (Beta-2 tubulin) gb|AAD20179.1| beta-tubulin 2 [Eleusine indica]; ubiquitin / ribosomal protein CEP52 - rice dbj|BAA02154.1| ubiquitin/ribosomal polyprotein [Oryza sativa] Cell division and growth Tubulin beta-2 chain (Beta-2 tubulin) gb|AAD20179.1| beta-tubulin 2 [Eleusine indica] ubiquitin / ribosomal protein CEP52 - rice dbj|BAA02154.1| ubiquitin/ribosomal polyprotein [Oryza sativa] Lipid metabolism glyoxalase I [Oryza sativa (japonica cultivar-group)]; lipid transfer protein precursor 1 - barley (fragment) emb|CAA42832.1| LTP 1 [Hordeum vulgare]; omega-6 fatty acid desaturase [Sesamum indicum] Oxygen reactive enzymes CAD11966.1 2e-34 glutathione-S-transferase, I subunit [Hordeum vulgaresubsp. vulgare] ascorbate peroxidase [Hordeum vulgaresubsp. Vulgare Amino acid metabolism phosphoethanolamine methyltransferase [Triticum aestivum]; serine acetyltransferase [Oryza sativa (japonica cultivar-group)] Protein destination Adenosylhomocysteinase (S-adenosyl-L-homocysteine hydrolase) (AdoHcyase); cathepsin B-like cysteine proteinase (EC 3.4.22.-) - wheat (fragment); Cysteine proteinase EP-B 1 precursor pir||JQ1111; cysteine proteinase (EC 3.4.22.-) EP-B 1 precursor –barley Protein synthesis 40s ribosomal protein s11 gb|aac14469.1| ribosomal protein s11 [glycine max]; ribosomal protein s30 homolog; protein id: at4g29390.1 [arabidopsis thaliana]; 60s acidic ribosomal protein p0 pir||t04309 acidic ribosomal protein p0 – rice; ef-1 alpha [oryza sativa] dbj|baa23659.1| ef-1 alpha [oryza sativa Cell wall degradation (1->3,1->4)-beta-glucanase isoenzyme II (EC 3.2.1.73) [Hordeum vulgare]; arabinoxylan arabinofuranohydrolase isoenzyme AXAH-I [Hordeum vulgare] Signal transduction adenosine kinase [Zea mays]; small Ran-related GTP-binding protein [Triticum aestivum] Unknown or unclear

Comparative expression profiles among four malting barley cultivars
The expression profiles of three other cultivars at Day-2 and Day-4 malting were investigated and compared with the same stages in ‘Morex’. Expression patterns of the subset of genes (identified in the study above) that appeared to be important in malting were analyzed in these cultivars. Other genes showing significant levels of expression but were not highly expressed in ‘Morex’ were identified in the three cultivars. Among the highly expressed genes, 8.4% had at least a two-fold greater level of expression in ‘Morex’ and ‘Legacy’ than in the 2-row cutivars ‘Harrington’ and ‘Merit’. Fructokinase and peptidylprolyl isomerase are examples of genes in this category. Conversely, 11.9% of the genes had at least 2-fold greater level of expression in the 2-row cultivars than in the 6-row cultivars. Acid phosphatase, and defensin are examples of genes in the latter group. There were also some genes that were significantly expressed in one cultivar only. These genes may be involved in determining malting quality differences between 2-row and 6-row cultivars or among the cultivars.

In summary, candidate genes that appear to be important in malting or malting quality differences between cultivars were identified using the Barley 1 GeneChip probe array. Validation of these candidate genes will be important. Association with malting quality phenotypes is one approach. Genetic mapping and co-localization of candidate genes with QTLs for malting quality phenotypes will provide further evidence for their possible roles in malting.

Acknowledgments

This work was partially funded by Anheuser Busch and the US Barley Genome Project. We thank the following collaborators: Dr. Blake Cooper for providing genetic materials and for valuable discussions on strategies and malting quality phenotypes; Dr. Jolanta Menert for providing malted tissues and input on experimental design; Drs. Hari Iyer and Ann Hess for support with the statistical analyses; J.T. Svensson, and E.M. Rodriguez from Dr. Close’s lab for technical support with RNA quality assessments.

References
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Nora Lapitan (1), Anna-Maria Botha-Oberholster (1), Timothy J. Close (2), and Christopher Lawrence (3)
(1) Department of Soil and Crop Sciences, Colorado State University, Fort Collins, CO 80523;
(2) University of California, Riverside, CA 92521;
(3) Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA, 24061

Presented at the 18th North American Barley Researchers Workshop, July 17-20, 2005