Global expression differences and tissue specific expression differences in rice evolution result in two contrasting types of differentially expressed genes.

BACKGROUND: Since the development of transcriptome analysis systems, many expression evolution studies characterized evolutionary forces acting on gene expression, without explicit discrimination between global expression differences and tissue specific expression differences. However, different types of gene expression alteration should have different effects on an organism, the evolutionary forces that act on them might be different, and different types of genes might show different types of differential expression between species. To confirm this, we studied differentially expressed (DE) genes among closely related groups that have extensive gene expression atlases, and clarified characteristics of different types of DE genes including the identification of regulating loci for differential expression using expression quantitative loci (eQTL) analysis data. RESULTS: We detected differentially expressed (DE) genes between rice subspecies in five homologous tissues that were verified using japonica and indica transcriptome atlases in public databases. Using the transcriptome atlases, we classified DE genes into two types, global DE genes and changed-tissues DE genes. Global type DE genes were not expressed in any tissues in the atlas of one subspecies, however changed-tissues type DE genes were expressed in both subspecies with different tissue specificity. For the five tissues in the two japonica-indica combinations, 4.6 ± 0.8 and 5.9 ± 1.5 % of highly expressed genes were global and changed-tissues DE genes, respectively. Changed-tissues DE genes varied in number between tissues, increasing linearly with the abundance of tissue specifically expressed genes in the tissue. Molecular evolution of global DE genes was rapid, unlike that of changed-tissues DE genes. Based on gene ontology, global and changed-tissues DE genes were different, having no common GO terms. Expression differences of most global DE genes were regulated by cis-eQTLs. Expression evolution of changed-tissues DE genes was rapid in tissue specifically expressed genes and those rapidly evolved changed-tissues DE genes were regulated not by cis-eQTLs, but by complicated trans-eQTLs. CONCLUSIONS: Global DE genes and changed-tissues DE genes had contrasting characteristics. The two contrasting types of DE genes provide possible explanations for the previous controversial conclusions about the relationships between molecular evolution and expression evolution of genes in different species, and the relationship between expression breadth and expression conservation in evolution.

Rice pollen hybrid incompatibility caused by reciprocal gene loss of duplicated genes.

Genetic incompatibility is a barrier contributing to species isolation and is caused by genetic interactions. We made a whole genome survey of two-way interacting loci acting within the gametophyte or zygote using independence tests of marker segregations in an F(2) population from an intersubspecific cross between O. sativa subspecies indica and japonica. We detected only one reproducible interaction, and identified paralogous hybrid incompatibility genes, DOPPELGANGER1 (DPL1) and DOPPELGANGER2 (DPL2), by positional cloning. Independent disruptions of DPL1 and DPL2 occurred in indica and japonica, respectively. DPLs encode highly conserved, plant-specific small proteins (∼10 kDa) and are highly expressed in mature anther. Pollen carrying two defective DPL alleles became nonfunctional and did not germinate, suggesting an essential role for DPLs in pollen germination. Although rice has many duplicated genes resulting from ancient whole genome duplication, the origin of this gene duplication was in recent small-scale gene duplication, occurring after Oryza-Brachypodium differentiation. Comparative analyses suggested the geographic and phylogenetic distribution of these two defective alleles, showing that loss-of-function mutations of DPL1 genes emerged multiple times in indica and its wild ancestor, O. rufipogon, and that the DPL2 gene defect is specific to japonica cultivars.

A simple optimization can improve the performance of single feature polymorphism detection by Affymetrix expression arrays.

BACKGROUND: High-density oligonucleotide arrays are effective tools for genotyping numerous loci simultaneously. In small genome species (genome size: < approximately 300 Mb), whole-genome DNA hybridization to expression arrays has been used for various applications. In large genome species, transcript hybridization to expression arrays has been used for genotyping. Although rice is a fully sequenced model plant of medium genome size (approximately 400 Mb), there are a few examples of the use of rice oligonucleotide array as a genotyping tool. RESULTS: We compared the single feature polymorphism (SFP) detection performance of whole-genome and transcript hybridizations using the Affymetrix GeneChip Rice Genome Array, using the rice cultivars with full genome sequence, japonica cultivar Nipponbare and indica cultivar 93-11. Both genomes were surveyed for all probe target sequences. Only completely matched 25-mer single copy probes of the Nipponbare genome were extracted, and SFPs between them and 93-11 sequences were predicted. We investigated optimum conditions for SFP detection in both whole genome and transcript hybridization using differences between perfect match and mismatch probe intensities of non-polymorphic targets, assuming that these differences are representative of those between mismatch and perfect targets. Several statistical methods of SFP detection by whole-genome hybridization were compared under the optimized conditions. Causes of false positives and negatives in SFP detection in both types of hybridization were investigated. CONCLUSIONS: The optimizations allowed a more than 20% increase in true SFP detection in whole-genome hybridization and a large improvement of SFP detection performance in transcript hybridization. Significance analysis of the microarray for log-transformed raw intensities of PM probes gave the best performance in whole genome hybridization, and 22,936 true SFPs were detected with 23.58% false positives by whole genome hybridization. For transcript hybridization, stable SFP detection was achieved for highly expressed genes, and about 3,500 SFPs were detected at a high sensitivity (> 50%) in both shoot and young panicle transcripts. High SFP detection performances of both genome and transcript hybridizations indicated that microarrays of a complex genome (e.g., of Oryza sativa) can be effectively utilized for whole genome genotyping to conduct mutant mapping and analysis of quantitative traits such as gene expression levels.

SNEP: Simultaneous detection of nucleotide and expression polymorphisms using Affymetrix GeneChip.

BACKGROUND: High-density short oligonucleotide microarrays are useful tools for studying biodiversity, because they can be used to investigate both nucleotide and expression polymorphisms. However, when different strains (or species) produce different signal intensities after mRNA hybridization, it is not easy to determine whether the signal intensities were affected by nucleotide or expression polymorphisms. To overcome this difficulty, nucleotide and expression polymorphisms are currently examined separately. RESULTS: We have developed SNEP, a new method that allows simultaneous detection of both nucleotide and expression polymorphisms. SNEP involves a robust statistical procedure based on the idea that a nucleotide polymorphism observed at the probe level can be regarded as an outlier, because the nucleotide polymorphism can reduce the hybridization signal intensity. To investigate the performance of SNEP, we used three species: barley, rice and mice. In addition to the publicly available barley data, we obtained new rice and mouse data from the strains with available genome sequences. The sensitivity and false positive rate of nucleotide polymorphism detection were estimated based on the sequence information. The robustness of expression polymorphism detection against nucleotide polymorphisms was also investigated. CONCLUSION: SNEP performed well regardless of the genome size and showed a better performance for nucleotide polymorphism detection, when compared with other previously proposed methods. The R-software 'SNEP' is available at http://www.ism.ac.jp/~fujisawa/SNEP/.

Rice genome organization: the centromere and genome interactions.

Over the last decade, many varied resources have become available for genome studies in rice. These resources include over 4000 DNA markers, several bacterial artificial chromosome (BAC) libraries, P-1 derived artificial chromosome (PAC) libraries and yeast artificial chromosome (YAC) libraries (genomic DNA clones, filters and end-sequences), retrotransposon tagged lines, and many chemical and irradiated mutant lines. Based on these, high-density genetic maps, cereal comparative maps, YAC and BAC physical maps, and quantitative trait loci (QTL) maps have been constructed, and 93 % of the genome has also been sequenced. These data have revealed key features of the genetic and physical structure of the rice genome and of the evolution of cereal chromosomes. This Botanical Briefing examines aspects of how the rice genome is organized structurally, functionally and evolutionarily. Emphasis is placed on the rice centromere, which is composed of long arrays of centromere-specific repetitive sequences. Differences and similarities amongst various cereal centromeres are detailed. These indicate essential features of centromere function. Another view of various kinds of interactive relationships within and between genomes, which could play crucial roles in genome organization and evolution, is also introduced. Constructed genetic and physical maps indicate duplication of chromosomal segments and spatial association between specific chromosome regions. A genome-wide survey of interactive genetic loci has identified various reproductive barriers that may drive speciation of the rice genome. The significance of these findings in genome organization and evolution is discussed.

Diverse variation of reproductive barriers in three intraspecific rice crosses.

Reproductive barriers are thought to play an important role in the processes of speciation and differentiation. Asian rice cultivars, Oryza sativa, can be classified into two main types, Japonica and Indica, on the basis of several characteristics. The fertility of Japonica-Indica hybrids differs from one cross to another. Many genes involved in reproductive barriers (hybrid sterility, hybrid weakness, and gametophytic competition genes) have been reported in different Japonica-Indica crosses. To clarify the state of Japonica-Indica differentiation, all reproductive barriers causing deviation from Mendelian segregation ratios in F(2) populations were mapped and compared among three different Japonica-Indica crosses: Nipponbare/Kasalath (NK), Fl1084/Dao Ren Qiao (FD), and Fl1007/Kinandang puti (FK). Mapping of reproductive barriers was performed by regression analysis of allele frequencies of DNA markers covering the entire genome. Allele frequencies were explained by 33 reproductive barriers (15 gametophytic and 18 zygotic) in NK, 32 barriers (15 gametophytic and 17 zygotic) in FD, and 37 barriers (19 gametophytic and 18 zygotic) in FK. The number of reproductive barriers in the three crosses was similar; however, most of the barriers were mapped at different loci. Therefore, these reproductive barriers formed after Japonica-Indica differentiation. Considering the high genetic similarity within Japonica and Indica cultivars, the differences in the reproductive barriers of each cross were unexpectedly numerous. The reproductive barriers of Japonica-Indica hybrids likely evolved more rapidly than other genetic elements. One possible force responsible for such rapid evolution of the barriers may have been the domestication of rice.