Logo of geneticsGeneticsCurrent IssueInformation for AuthorsEditorial BoardSubscribeSubmit a Manuscript
Genetics. Jul 2006; 173(3): 1823–1827.
PMCID: PMC1526680

A Novel Approach for Characterizing Expression Levels of Genes Duplicated by Polyploidy

Abstract

Studying gene expression in polyploids is complicated by genomewide gene duplication and the problem of distinguishing transcript pools derived from each of the two homeologous genomes such as the A- and D-genomes of allotetraploid Gossypium. Short oligonucleotide probes designed to specifically target several hundred homeologous gene pairs of Gossypium were printed on custom NimbleGen microarrays. These results demonstrate that relative expression levels of homeologous genes may be measured by microarrays and that deviation from equal expression levels of homeologous loci may be common in the allotetraploid nucleus of Gossypium.

WHOLE-genome duplication, or polyploidy, has been a prominent force in angiosperm evolution (Grant 1981; Leitch and Bennett 1997). Recently formed allopolyploids, such as cotton, retain duplicated copies of most genes on homeologous chromosomes. These homeologous loci typically have sufficiently high sequence identity that their transcripts cross-hybridize on standard microarray platforms, thereby obscuring the genomic origin of expressed genes. Because of this technical limitation, the contribution of each homeolog from each constituent genome of a polyploid to the transcriptome has remained largely unexplored. Recent work indicates, however, that these contributions need not be equal and, in fact, that altered gene expression in allopolyploids is common (Kashkush et al. 2002; Adams et al. 2003; Osborn et al. 2003; Adams and Wendel 2005; Wang et al. 2006).

Domesticated cotton (Gossypium hirsutum) is an allotetraploid derived from two diploid genomes, “A” and “D.” Accumulated evidence indicates a relatively recent origin of the allopolyploid lineage, probably in the past 1–2 million years, from diploid parents similar to modern A- (G. arboreum or G. herbaceum) and D- (G. raimondii) genome species (Wendel and Cronn 2003). Most genes of A- and D-genome diploid Gossypium species are 98–99% similar in exon sequence, as are their homeologous counterparts in the allotetraploids (Senchina et al. 2003). Because of this high sequence identity, ESTs from diploid and allopolyploid species may be combined during contig assembly (Udall et al. 2006).

In this Note, we describe a novel bioinformatic and molecular methodology for simultaneously monitoring transcript accumulation for thousands of pairs of homeologous genes. The methodology involves custom short-oligonucleotide microarrays based on A- and D-genome-specific single nucleotide polymorphism (SNPs) or small insertion/deletions (indels), identified following assembly of ESTs of three different Gossypium species (Figure 1; Udall et al. 2006). Through comparisons of the progenitor diploid genomes, ortholog- and homeolog-specific polymorphisms were identified by scanning the 24,363 assembled contigs for polymorphisms between the A- and D-genome ESTs (Figure 1; supplemental Table S1 at http://www.genetics.org/supplemental/). A total of 2277 SNPs and 98 small indels from 701 genes were identified and probe pairs targeting these polymorphisms were included on a custom DNA microarray (supplemental Figure S1 at http://www.genetics.org/supplemental/; Nuwaysir et al. 2002; NimbleGen Systems).

Figure 1.
SNPs were identified between A- and D-genome ESTs, leading to assignment of genomic origin for ESTs from allopolyploid G. hirsutum. A portion (positions 811–1095) of the alignment for contig CL10115Contig1 is shown and a two-letter prefix of each ...

Diploid leaf complementary RNA (cRNA) was used to empirically identify probe pairs that would distinguish between the AT and DT homeologs (where AT and DT refer to the two genomes in the allopolyploid). For example, the A-genome-specific probes hybridized better to the A-genome cRNA than to the D-genome cRNA (Figure 2A; supplemental Figure S2 at http://www.genetics.org/supplemental/). Many A-genome-specific probes also hybridized equally well to the D-genome cRNA, but this was not entirely unexpected, as our probe pairs were developed in silico without prior testing, and some probes had weak support for the existence of the putative SNP (e.g., few ESTs from the diploids; supplemental Figure S3 at http://www.genetics.org/supplemental/). Thus, to identify diagnostic probes, we conducted a mixed linear model analysis for each probe pair to find probe pairs for which the A-genome cRNA gave significantly higher signal than the D-genome cRNA for the A-genome probe, while the D-genome cRNA gave significantly higher signal than the A-genome cRNA for the D-genome probe. Significance was determined using P-values conservatively adjusted to control the false discovery rate (FDR; Benjamini and Hochberg 1995). A total of 1210 probes (461 genes) were found be diagnostic [adjusted (adj.) P < 0.05] with respect to AT and DT transcript levels; therefore, probes that hybridized significantly better to their targeted cRNA than to the alternative cRNA were considered diagnostic (Figure 2, Table 1).

Figure 2.
Intensities of diagnostic probes on the custom Nimblegen microarray. (A) Many probes designed to target the A-genome had a genome-specific bias when hybridized with D-genome cRNA. While each microarray had both A- and D-genome-specific probes, only the ...
TABLE 1
Diagnostic oligonucleotide probes for diploid Gossypium and expression bias in their derived allopolyploid

When the microarray probe sets were challenged with cRNA from the G. hirsutum allotetraploid, which contains both AT- and DT-genomes, many diagnostic probes were found to have unequal expression levels (Table 1). Within the subset of 1210 diagnostic probe pairs, our null hypothesis for each gene was equal expression of the AT and DT homeologs in the allotetraploid transcript pool. The null hypothesis was rejected for 716 probe pairs, indicating unequal AT and DT expression levels (adj. P < 0.05) of many genes. Two hundred and seventy six of the 461 genes containing diagnostic probes had significantly different AT and DT expression levels. Ninety-nine of these loci were biased in a consistent direction when a gene was targeted by multiple probes while 77 other loci with multiple probes had ambiguous results (supplemental Figure S1 at http://www.genetics.org/supplemental/). This percentage (199 of 461; 43%) of biased expression in a polyploid genome is higher than that previously reported on much smaller scales (Adams et al. 2003; Mochida et al. 2003). Among the sampled genes reported here, the types of genes that had biased expression appeared to be random (supplemental Table S2 at http://www.genetics.org/supplemental/), much like transcription biases in wheat (Mochida et al. 2003). The data in Table 1 are suggestive, however, of a consistent preference for transcription of A-genome homeologs although χ2-tests indicated only the differences at the probe level to be significant.

A set of five genes was selected to verify the microarray results by single-strand conformational polymorphism (SSCP) analysis and by randomly sequencing cloned colonies (supplemental Table S2 at http://www.genetics.org/supplemental/). Primers were designed to amplify one or more targeted polymorphisms within contigs containing both A- and D-genome ESTs. Verification results for all of the genes agree with the microarray-based results in the direction of expression bias. CL15638Contig1 had a nonsignificant homeolog bias on the microarray, but was later found to have a bias via SSCP and sequencing (supplemental Table S2 at http://www.genetics.org/supplemental/). Four additional loci with ambiguous microarray results were further investigated for their expression bias (supplemental Table S3 at http://www.genetics.org/supplemental/). For two of the four, our verification results agreed with one of the two probes targeting these homeologous loci, suggesting that no expression bias existed. Another locus had several diagnostic probe sets in two different verification amplicons and significant biases were consistently supported by verification. For a fourth ambiguous locus, the correct direction of homeolog bias was determined by verification. Within these ambiguous results, perhaps cross-hybridization of probes to other family members could explain the inconsistent microarray results among the putatively diagnostic probe pairs. In summary, our microarray results suggest that homeologous expression level biases may be widespread in the allotetraploid nucleus; however, our investigation of ambiguous microarray results suggests that more probes per gene would be useful in future experiments.

We note that leaves, the only organ used in this study, consist of many different cell types including trichomes, epidermis, xylem, phloem, etc. Thus, homeologous transcript levels within a leaf RNA extract represent an average expression level of all these different cell types. In this light, perhaps it is not surprising that the largest biases between homeologous loci were found in differentiated tissues with fewer types of cells, such as petals (Adams et al. 2003). Because the methodology described here permits monitoring of homeolog-specific patterns of gene expression, custom microarrays may prove to be one of the tools necessary for the biotechnological improvement of cotton fiber. These and comparable arrays may also yield insights into fundamental processes of regulatory networks and transcriptional controls in cotton as well as other polyploid plants.

Acknowledgments

We gratefully acknowledge the National Science Foundation Plant Genome Program and the U. S. Department of Agriculture–National Research Initiative for financial support.

References

  • Adams, K. L., and J. F. Wendel, 2005. Polyploidy and genome evolution in plants. Curr. Opin. Plant Biol. 8: 135–141. [PubMed]
  • Adams, K. L., R. Cronn, R. Percifield and J. F. Wendel, 2003. Genes duplicated by polyploidy show unequal contributions to the transcriptome and organ-specific reciprocal silencing. Proc. Natl. Acad. Sci. USA 100: 4649–4654. [PMC free article] [PubMed]
  • Benjamini, Y., and Y. Hochberg, 1995. Controlling false discovery rate: a practical and powerful approach to multiple testing. J. R. Stat. Soc. 57: 289–300.
  • Eberwine, J., H. Yeh, K. Miyashiro, Y. Cao, S. Nair et al., 1992. Analysis of gene expression in single live neurons. Proc. Natl. Acad. Sci. USA 89: 3010–3014. [PMC free article] [PubMed]
  • Forman, J. E., I. D. Wilson, D. Stern, R. P. Rava and M. O. Trulson, 1997. Thermodynamics of duplex formation and mismatch discrimination on photolithographically synthesized oligonucleotide arrays in molecular modeling of nucleic acids, pp. 206–228 in Molecular Modeling of Nucleic Acids, edited by N. B. Leontis and J. Santa Lucia, Jr. ACS Publications, Oxford University Press, Oxford.
  • Grant, V., 1981. Plant Speciation. Columbia University Press, New York.
  • Kashkush, K., M. Feldman and A. A. Levy, 2002. Gene loss, silencing and activation in a newly synthesized wheat allotetraploid. Genetics 160: 1651–1659. [PMC free article] [PubMed]
  • Leitch, I. J., and M. D. Bennett, 1997. Polyploidy in angiosperms. Trends Plant Sci. 2: 470–476.
  • Mochida, K., Y. Yamazaki and Y. Ogihara, 2003. Discrimination of homoeologous gene expression in hexaploid wheat by SNP analysis of contigs grouped from a large number of expressed sequence tags. Mol. Gen. Genet. 270: 371–377. [PubMed]
  • Nuwaysir, E. F., W. Huang, T. J. Albert, J. Singh, K. Nuwaysir et al., 2002. Gene expression analysis using oligonucleotide arrays produced by maskless photolithography. Genome Res. 12: 1749–1755. [PMC free article] [PubMed]
  • Osborn, T. C., J. Chris Pires, J. A. Birchler, D. L. Auger, Z. Jeffery Chen et al., 2003. Understanding mechanisms of novel gene expression in polyploids. Trends Genet. 19: 141–147. [PubMed]
  • R Development Core Team, 2005. R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna.
  • Senchina, D. S., I. Alvarez, R. C. Cronn, B. Liu, J. Rong et al., 2003. Rate variation among nuclear genes and the age of polyploidy in Gossypium. Mol. Biol. Evol. 20: 633–643. [PubMed]
  • Stajich, J. E., D. Block, K. Boulez, S. E. Brenner, S. A. Chervitz et al., 2002. The Bioperl toolkit: perl modules for the life sciences. Genome Res. 12: 1611–1618. [PMC free article] [PubMed]
  • Udall, J. A., J. M. Swanson, K. Haller, R. A. Rapp, M. E. Sparks et al., 2006. A global assembly of cotton ESTs. Genome Res. 16: 441–450. [PMC free article] [PubMed]
  • Wang, J., L. Tian, H.-S. Lee, N. E. Wei, H. Jiang et al., 2006. Genomewide nonadditive gene regulation in Arabidopsis allotetraploids. Genetics 172: 507–517. [PMC free article] [PubMed]
  • Wendel, J. F., and R. C. Cronn, 2003. Polyploidy and the evolutionary history of cotton. Adv. Agron. 78: 139–186.
  • Wilkins, T. A., and L. B. Smart, 1996. Isolation of RNA from plant tissue, pp. 21–41 in A Laboratory Guide to RNA: Isolation, Analysis, and Synthesis, edited by P. A. Krieg. Wiley-Liss, New York.

Articles from Genetics are provided here courtesy of Genetics Society of America
PubReader format: click here to try

Formats:

Related citations in PubMed

See reviews...See all...

Cited by other articles in PMC

See all...

Links

Recent Activity

Your browsing activity is empty.

Activity recording is turned off.

Turn recording back on

See more...