Funct Integr Genomics (2011) 11:651–657 and INDELs) for 75 (75.7%) out of 99 primer pairs (Electronic Supplementary Material Table 2). Among all the sequence variations identified within 99 probe regions, 363 were SNPs and 44 INDELs. A representative align- ment of genomic amplicon sequences examined for a putative SFP between ICP 28 and ICPW 94 genotypes for probe #3 of probe set Gma.12798.1.S1_at, revealed occurrence of four SNPs in the genotypes (Electronic Supplementary Material Figure 1). In addition, as compared to the pigeonpea TUS (TUS ID127906_2368_0221), there was a single base deletion in the two genotypes investigat- ed. On the other hand, as compared to soybean gene (Gma.12798.1.S1_at), an insertion of 2 bp was observed in the both pigeonpea genotypes. Based on SFP prediction, in aforementioned sequence data for 99 genes, the parental genotypes for cross 1 should have sequence polymorphisms for 38 genes, the parental genotypes for cross 2 should have sequence polymorphisms for 58 genes and 43 genes should have sequence poly- morphisms for the parents for the cross 3. Sequence analysis for 75 polymorphic genes, however, confirmed SNPs or INDELs for 31 (81.58%), 20 (34.48%), and 18 (41.86%) genes for the parental genotypes of the cross 1, 2, and 3 respectively (Table 1). Across all the six genotypes, the accuracy of the array to predict the presence of a sequence variant based on SFP was 52.6%. In summary, 52.6% predicted SFPs were found true, while the remaining 47.4% SFPs predicted were found false. The false discovery rate (FDR) of SFPs predicted in this study is relatively higher than FDRs reported in other studies using cRNA for SFP detection (Rostoks et al. 2005; Cui et al. 2005; Das et al. 2008; Yang et al. 2009). For instance, by using barley Affymetrix genome arrays to detect SFPs in barley genotypes, the FDR was 10–20% (Cui et al. 2005) and 40% (Rostoks et al. 2005). It is, however, noted that the present study deployed soybean genome arrays for SFP discovery in pigeonpea genotypes. Previously also, the soybean genome arrays were used to detect SFPs in cowpea (Das et al. 2008) and the barrel medic (Medicago truncatula) genome arrays were used for SFP discovery in alfalfa (Medicago sativa) (Yang et al. 2009). In these species, however, lower FDR (32% in cowpea and 17% in alfalfa) was observed. Higher (47.4%) FDR observed in the present study can be attributed to several factors. The phylogenetic distance between soybean and pigeonpea is higher than the phylogenetic distances between soybean–cowpea and Medicago–alfalfa. Owing to the relatively low level of sequence similarity between probes and transcripts in cross-species hybridization, more probes might be considered to cross-hybridize in cross- species hybridization as compared to self species hybrid- ization (Bar-or et al. 2006). Some false positive cases may occur due to paralogs being sequenced in the tested 655 genotypes which do not exhibit polymorphism. Variation in post-transcriptional modification such as alternative splicing in some genes may also have contributed to the FDR observed (Rostoks et al. 2005; Das et al. 2008). In addition to checking the SFPs specific to the given cross, analysis was also done to validate the SFPs that were common to parents of cross 1 and 2 (17), cross 1 and 3 (14), cross 2 and 3 (19), and cross 1, 2, and 3 (10). While a higher proportion of SFPs were confirmed for the parents of cross 1 and 2 (14, 82.35%), the least proportion of SFPs were confirmed for the parents of cross 2 and 3 (9, 47.36%). While 50% of SFPs (5) that were common to all the parents were confirmed at the sequence level, 64.28% (9) SFPs were confirmed for the parents of cross 1 and 3. Such polymorphisms generally represent haplotypes, which will be very useful in mapping of these genes especially for construction of consensus genetic maps. Moreover, these sequence variations represent expressed portion of the genomes and hence can directly be associated with some important phenotypic traits. Gene ontology descriptions Functional analysis was done for the 922 pigeonpea TUSs for the corresponding soybean transcripts that detected SFPs (soybean transcripts) between the parents of the mapping populations (ICPL 8755 × ICPL 227 and ICPL 151 ×ICPL 87) segregating for drought tolerance. Analysis of these sequences against UniProt database (Uniref50) showed that 752 TUSs (81.56%) had similarity to the proteins available in the database at a stringent criterion of e-value≤10−5. Subsequently, these TUSs were analyzed for gene ontology descriptions based on their BLASTX functions. As a result, 724 (78.52%) TUSs could be assigned into three principal categories: molecular function (599), biological process (559), and cellular component (570). While distributing these TUSs into various subcate- gories of three main categories, the highest number of TUSs fell into cell part (555) followed by cellular process (453), nucleotide binding (426), and metabolic process (409) subcategories (Electronic Supplementary Material Figure 2). Gene ontology analysis was also extended to identify the genes related to stress responses. As a result, a total of 139 TUSs were found under “response to stimulus” subcategory which includes both abiotic and biotic responses. This provides an indication of the involvement of these genes for drought tolerance. Some functional genomics approaches like qRT-PCR may validate the function of these genes (Hu et al. 2009). Furthermore, the linkage mapping of these SFPs using aforementioned mapping populations may provide association of these genes for QTLs for drought tolerance that can be used as “functional markers” in marker-assisted selection approaches in pigeonpea breeding.