Two near-isogenic lines (NIL) differing in presence or absence of gene Rk were used. The two parents used to develop the NIL were M. incognita race 3 resistant cowpea genotype 'CB46' (homozygous resistant, RkRk) and a highly susceptible genotype 'Chinese Red' (homozygous susceptible, rkrk). The F1 was backcrossed to recurrent parent CB46 (BC1), homozygous Rk plants were discarded in BC1F2, and non-segregating rkrk plants were advanced to the next back-cross (BC2). Repeated backcrossing and selection was used to recover the rkrk line in the CB46 background. BC6F4 progenies were used for all the experiments described here. The rkrk line is referred to as the null- Rk line from here on.
Eggs of M. incognita race 3 (isolate Beltran) cultured on susceptible tomato host plants were extracted from roots using 10% bleach solution . This isolate is avirulent to gene Rk in CB46. Eggs were hatched in an incubator at 28°C and J2 were collected in fresh deionized water. The J2 inoculum was prepared according to the experimental requirements.
Root infections for microarray analysis
Seeds of CB46 and null- Rk cowpea lines were surface-sterilized using 10% (v/v) bleach solution and planted singly in seedling growth pouches. Plants were grown under controlled environmental conditions of 26.7°C ± 0.5°C constant temperature and daily light/dark cycles of 16/8 hours. This temperature was used because it lies within the optimum temperature range of 26 - 28°C for development and reproduction of M. incognita on cowpea in growth pouches . Each of 100 pouches (50 pouches for each genotype) was inoculated with 3000 J2 in 5 ml of deionized water 12 days after planting (dap). This inoculum level was found to be optimum in a previous study (Das and Roberts, unpublished data) and it generated uniform infection throughout the root system. As a result the amount of infected tissue was maximized. An equal number of pouches were mock-inoculated with 5 ml of deionized water to use as non-infected controls. Infected and non-infected plants were arranged in a completely randomized design. Nematode infected root tissue was excised using a sterile scalpel at 3 days post-inoculation (dpi) and 9 dpi, respectively, under a magnifying glass and flash frozen immediately in liquid nitrogen. In previous studies (Das and Roberts, unpublished) the infected root regions showed swelling at 3 dpi which is indicative of initiation of giant cell formation, and at 9 dpi prominent galling was visible on infected roots. The infected tissue was collected based on these visual indicators. For each biological replicate infected tissue was collected from 7 plants picked randomly and pooled together. This was done in order to obtain enough biological material for RNA isolation. Similarly root tissue was collected from equivalent root regions of the control plants (tissue near root tips of secondary and tertiary roots) and flash frozen. Galled tissue was excised by cutting immediately adjacent to the root-gall in order to minimize the amount of non-infected tissue included in the assays. The harvested tissue was stored at -80°C until RNA isolation. A few infected root pieces were stained in acid fuchsin  to confirm the nematode infection.
RNA from nematode infected and non-infected root tissue was isolated using RNeasy plant mini kit (QIAGEN Inc., Valencia, CA, USA) according to the manufacturer's protocol. One volume of Plant RNA Isolation Aid (Ambion, Austin, TX, USA) per unit mass of frozen tissue (ml/g) was added before the tissue homogenization step for removal of common contaminants such as polysaccharides and polyphenolics. RNA was treated with RNase-Free DNase set (QIAGEN Inc., Valencia, CA, USA) to digest any genomic DNA which might be present. RNA was quantified using a UV-spectrophotometer. RNA quality and integrity was examined using RNA Lab-On-A-Chip (Caliper Technologies Corp., Mountain View, CA, USA) evaluated on an Agilent Bioanalyzer 2100 (Agilent Technologies, Palo Alto, CA, USA).
Soybean genome array
Phylogenetic relationships based on the conserved sequences within Papilionoideae legumes imply that Vigna (cowpea) is closely related to soybean . Since a commercial cowpea genome array was not available, a soybean genome array (Affymetrix Inc., Santa Clara, CA, USA) was used for transcriptome profiling in cowpea. The soybean genome array contains 37,500 probe sets derived from soybean (Glycine max L.) unigenes. This represents 61% of the total probe sets on the chip, with the remainder targeting two pathogens important for soybean research, of which 15,800 (26%) probe sets target Phytophthora sojae (a water mold) and 7,500 (12%) probe sets target Heterodera glycines (soybean cyst nematode). This array uses probe sets composed of 11 probe pairs to measure the expression of each gene. Each probe pair consists of a perfect match (PM) probe and a mismatch (MM) probe (see also http://www.affymetrix.com/products_services/arrays/specific/soybean.affx).
Double-stranded complementary deoxyribonucleic acid (cDNA) was synthesized using SuperScript Double-Stranded cDNA Synthesis Kit (Invitrogen) and T7-oligo (dT) promoter primers. The IVT Labeling Kit (Affymetrix) was then used to synthesize biotin-labeled complementary RNA (cRNA) from template cDNA by in vitro transcription. Twelve to 16 μg labeled cRNA was fragmented by metal-induced hydrolysis to 35-200 base fragments following Affymetrix protocols. 10 μg labeled, fragmented cRNA was then hybridized at 45°C with rotation for 16 h in an Affymetrix microarray Hybridization Oven 320 on Affymetrix soybean genome arrays. The arrays were washed and stained using streptavidin phycoerythrin on an Affymetrix Fluidics Station 450. The arrays were scanned on a Hewlett-Packard GeneArray scanner. cRNA synthesis and array hybridizations were performed in the Genomics Core Facility http://www.genomics.ucr.edu at the University of California, Riverside.
For 9-dpi samples three biological replicates were used for each of the four treatments (Rk infected and non-infected, and Rk -null infected and non-infected), requiring 12 soybean GeneChips. For the 3-dpi samples two biological replicates were used for each treatment requiring 8 GeneChips. The data from all 20 chips (CEL and CHP files) are publicly available in Gene Expression Omnibus (http://www.ncbi.nlm.nih.gov/geo/, platform GPL 4592, series GS13631). Expression signals were first analyzed in GeneChip operating software 1.3 (GCOS, Affymetrix Inc.) to determine the "present" probe set list. To detect "present" calls using GCOS software we used all the probe pairs in the probe set as "stat pairs". The definition of the term "stat pairs" is the number of probe pairs per probe set used in the analysis. During data analysis a specified subset of probe pairs can be selected by a probe mask file, but if the default settings are used no probe mask file will be applied and all the probe pairs will be used as "stat pairs" (11 probe pairs in the case of the soybean GeneChip). The detection algorithm uses probe pair intensities to generate a detection p-value and assign a "present", "marginal", or "absent" call. Each probe pair in a probe set has a potential vote in determining whether the measured transcript is or is not "present". The vote is described by the discrimination score (R), which is calculated for each probe pair and compared to a predefined threshold, Tau. Probe pairs with R higher than Tau vote "present" and the voting result is summarized as a p-value. The greater the number of discrimination scores (R) that are above Tau, the smaller the p-value and the more likely the given transcript is truly present in the sample. Only probe sets with a "present" call in all three replicates of at least one treatment were considered to be "expressed".
Data normalization and further analysis was carried out in GeneSpring GX 7.3 (Agilent Technologies, Palo Alto, CA, USA). Robust Multiarray Average (RMA, [47, 48]) normalization was performed. Each chip was normalized to the 50th percentile and each gene was normalized to the median. As we were only interested in plant response to nematode infection, all the probe set data from P. sojae and H. glycines were excluded from any further analysis.
Principal component analysis (PCA) is often used to reduce multidimensional data sets to lower dimensions for summarizing the most important part of the data while simultaneously filtering out the background errors. PCA involves the calculation of the eigenvalue decomposition of a data covariance matrix or singular value decomposition of a data matrix, usually after mean centering the data for each attribute. The results of PCA are usually discussed in terms of component scores and loadings . PCA on conditions (treatments) based on all genes which were present in at least one chip in the 9-dpi and 3-dpi samples were carried out to visualize the overall genome response to nematode infection in the resistant and susceptible cowpea genotypes.
For the 3-dpi samples, with only two biological replicates available, a Pearson correlation coefficient was calculated for normalized values of all probe sets between the two replicates of each treatment to determine the robustness of the data. This analysis was carried out in dChip software .
Differentially expressed genes were identified using a one-way analysis of variance (ANOVA) with a p-value cut-off of 0.05. A multiple testing correction was performed using the Bonferroni error correction model . False discovery rate (FDR) was set at 5.0%. Subsequently, differentially expressed genes were filtered for 1.5-fold change in expression level between the control and nematode infected treatment for both genotypes and also between the nematode infected treatments of the resistant and susceptible genotypes.
Validation of the use of Affymetrix soybean genome array for cowpea transcriptional profiling
In our recent related work  the Affymetrix soybean genome array was used successfully to identify single feature polymorphisms in cowpea and the statistical data were validated using PCR amplicon sequencing. Thus, we were able to correctly identify polymorphisms between two cowpea genotypes at a resolution as high as the single nucleotide level. Also, we conducted a small analysis to look at the sequence homology between sequence information files (SIF) of 30 probe sets selected to carry out PCR validation of predicted SFPs and their corresponding cowpea sequences. The homology ranged from 87% to as high as 94.5%. Though this analysis is not exhaustive, it provided a good indication that the homology between cowpea and soybean genomes is quite high at least in the SIF regions from where the probe sets were designed. For this work RNA was used as surrogate for genomic DNA. These data established that the soybean probe sets faithfully measure cowpea transcripts, validating the general reliability of the soybean-based platform for cowpea.
Annotations and functional classification of genes
The soybean genome array unigene sequences were used to query (using blastx) Arabidopsis translated gene models (version 7.0) from The Arabidopsis Information Resource (TAIR, http://www.arabidopsis.org) and Medicago truncatula 2.0 assembly release http://www.medicago.org. Annotations for the Affymetrix soybean probe sets were compiled into a browser called HarvEST:SoyChip which can be accessed online http://www.harvest-web.org or downloaded for Windows installation http://harvest.ucr.edu/. The E value cut-off for the gene annotations was equal to or less than E-10, E0 being a near perfect match.
Gene ontology based classification was obtained by transferring the corresponding Arabidopsis gene models to Munich Information Center for Protein Sequences Arabidopsis thaliana FunCat database (MIPS, http://mips.gsf.de/proj/funcatDB/search_main_frame.html). Arabidopsis gene models were taken from HarvEST:SoyChip.