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Genomic hybridization intensities (gDNA intensity) of XL, XB, and XM vary with respect to the non-target to target ratio of these intensities (gDNA ratio). This graph depicts the median gDNA intensities of all probes on the chip ranked by their gDNA ratio into 25 bins; each bin contains 10,000 probes except the 25th bin, which contains 7852 probes. The area in gray corresponds with the range of gDNA ratios of probes that are retained using the method of Malone et al. (2007). XL gDNA ratios are represented by filled symbols and non-target gDNA ratios are represented by unfilled symbols. Shown are relationships between the median gDNA intensity of each bin and the median gDNA ratio of each bin for (A) our XM and XL gDNA hybridizations, (B) the XM and XL gDNA hybridizations of Malone et al. (2007), and (C) our XB and XL gDNA hybridizations.
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Prefabricated expression microarrays are currently available for only a few species but methods have been proposed to extend their application to comparisons between divergent genomes.
Here we demonstrate that the hybridization intensity of genomic DNA is a poor basis on which to select unbiased probes on Affymetrix expression arrays for studies of...
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... Most of the annotated genes expressed in any one species were detected in all three species (Additional file 3: Figure S2B). However, to confirm species differences in expression profiles, qPCR was used to validate hybridization results [36] by using primers with approximately equal efficiency for all three species (Additional file 4: Table S2). ...
Salmon species vary in susceptibility to infections with the salmon louse (Lepeophtheirus salmonis). Comparing mechanisms underlying responses in susceptible and resistant species is important for estimating impacts of infections on wild salmon, selective breeding of farmed salmon, and expanding our knowledge of fish immune responses to ectoparasites. Herein we report three L. salmonis experimental infection trials of co-habited Atlantic Salmo salar, chum Oncorhynchus keta and pink salmon O. gorbuscha, profiling hematocrit, blood cortisol concentrations, and transcriptomic responses of the anterior kidney and skin to the infection.
In all trials, infection densities (lice per host weight (g)) were consistently highest on chum salmon, followed by Atlantic salmon, and lowest in pink salmon. At 43 days post-exposure, all lice had developed to motile stages, and infection density was uniformly low among species. Hematocrit was reduced in infected Atlantic and chum salmon, and cortisol was elevated in infected chum salmon. Systemic transcriptomic responses were profiled in all species and large differences in response functions were identified between Atlantic and Pacific (chum and pink) salmon. Pink and chum salmon up-regulated acute phase response genes, including complement and coagulation components, and down-regulated antiviral immune genes. The pink salmon response involved the largest and most diverse iron sequestration and homeostasis mechanisms. Pattern recognition receptors were up-regulated in all species but the active components were often species-specific. C-type lectin domain family 4 member M and acidic mammalian chitinase were specifically up-regulated in the resistant pink salmon.
Experimental exposures consistently indicated increased susceptibility in chum and Atlantic salmon, and resistance in pink salmon, with differences in infection density occurring within the first three days of infection. Transcriptomic analysis suggested candidate resistance functions including local inflammation with cytokines, specific innate pattern recognition receptors, and iron homeostasis. Suppressed antiviral immunity in both susceptible and resistant species indicates the importance of future work investigating co-infections of viral pathogens and lice.
... Early in the diversification of Xenopus tetraploids, an ancestor split into two descendant lineages that eventually evolved into Xenopus laevis and the common ancestor of Xenopus borealis and Xenopus muelleri. It is estimated that X. laevis and X. borealis, which are the focus of this study, diverged from one another million years ago [9][10][11]. The question as to how many allopolyploidization events occurred to generate the extant Xenopus species remains an open one and has implications for the level of divergence between the "subgenomes" of each tetraploid lineage [5]. ...
... In such interspecies crosses, the F1 males are sterile and the F1 females are fully or partially fertile [24]. The generation of F1 hybrids between X. laevis and the Marsabit clawed frog X. borealis (Parker, 1936) in laboratory has been described and microarray analyses combined with comparative transcriptomics have been used to study gene expression in the testis and brain tissue from hybrid males [10]. The aim of the present study was to use peptidomic analysis (reversed-phase HLPC coupled with mass spectrometry) to compare the AMPs, and the caerulein-related and xenopsin-related peptides in norepinephrine-stimulated skin secretions from X. laevis female × X. borealis male hybrids (hereafter X LB ) with hybrids from the reciprocal cross from X. borealis female and X. laevis male (hereafter X BL ). ...
... University (Protocol No. A21-09) and were carried out by authorized investigators. Both types of F1 hybrids (X LB and X BL ) between X. laevis (from the Cape region of South Africa) and X. borealis (from Kenya) were generated via in vitro fertilization as previously described [10]. Female X LB hybrids (n = 2; 5-6 years old; weights 26.1 g and 27.8 g) and female X BL hybrids (n = 2; 5-6 years old; weight 31.1 g and 31.5 g) were injected via the dorsal lymph sac with norepinephrine hydrochloride (40 nmol/g body weight) and placed in water (100 ml) for 15 min. ...
... Microarrays developed for a specific species have been used for transcript profiling of closely related species. Cross-species RNA hybridization (CSH) to DNA microarrays has been used successfully in both animal and plant when a representative microarray platform is not available1516171819202122232425262728293031323334. The assumption that underlies the validity of CSH on a gene chip of a closely related species is that the level of sequence homology among genes conserved between closely related species is significant enough to enable the detection of messages by probes originally designed for their orthologs. ...
... Several CSH studies have utilized this approach [20,29,32]. However, a recent study questioned the reliability of the DNA hybridization-based method for selecting unbiased probes in CSH studies [34]. Wang et al. [27] took a different approach to identify inter-species conserved (ISC) probe sets based on the expressed sequence tag (EST) homology between target and non-target species. ...
... However, this method was limited by an inability to distinguish between technical variation due to faulty hybridization and gene expression divergence across species. Consequently, single-species microarrays have been called into question in comparative transcriptomics (Chain et al., 2008). In contrast to the previous studies, this study compared two allotetraploid species (X. ...
The availability of both the Xenopus tropicalis genome and the soon to be released Xenopus laevis genome provides a solid foundation for Xenopus developmental biologists. The Xenopus community has presently amassed expression data for ∼2,300 genes in the form of published images collected in the Xenbase, the principal Xenopus research database. A few of these genes have been examined in both X. tropicalis and X. laevis and the cross-species comparison has been proven invaluable for studying gene function. A recently published work has yielded developmental expression profiles for the majority of Xenopus genes across fourteen developmental stages spanning the blastula, gastrula, neurula, and the tail-bud. While this data was originally queried for global evolutionary and developmental principles, here we demonstrate its general use for gene-level analyses. In particular, we present the accessibility of this dataset through Xenbase and describe biases in the characterized genes in terms of sequence and expression conservation across the two species. We further indicate the advantage of examining coexpression for gene function discovery relating to developmental processes conserved across species. We suggest that the integration of additional large-scale datasets--comprising diverse functional data--into Xenbase promises to provide a strong foundation for researchers in elucidating biological processes including the gene regulatory programs encoding development.
... Several studies have reported that genes with specific attributes change expression more quickly4567, though it is not known whether the expression of such subsets of genes also diverges linearly with time. RNA-Seq offers a methodological improvement over microarrays for measuring expression divergence because it does not suffer from the probe-based biases that confound cross-species microarray measurements891011 . Technical replication studies, in which expression values are assayed more than once from the same sample, have shown that RNA-Seq quantifies relative gene expression accurately [12,13]. ...
The evolution of gene expression is a challenging problem in evolutionary biology, for which accurate, well-calibrated measurements and methods are crucial.
We quantified gene expression with whole-transcriptome sequencing in four diploid, prototrophic strains of Saccharomyces species grown under the same condition to investigate the evolution of gene expression. We found that variation in expression is gene-dependent with large variations in each gene's expression between replicates of the same species. This confounds the identification of genes differentially expressed across species. To address this, we developed a statistical approach to establish significance bounds for inter-species differential expression in RNA-Seq data based on the variance measured across biological replicates. This metric estimates the combined effects of technical and environmental variance, as well as Poisson sampling noise by isolating each component. Despite a paucity of large expression changes, we found a strong correlation between the variance of gene expression change and species divergence (R² = 0.90).
We provide an improved methodology for measuring gene expression changes in evolutionary diverged species using RNA Seq, where experimental artifacts can mimic evolutionary effects.GEO Accession Number: GSE32679.
... The former method, which is used primarily when commercial microarrays are not available for both species, depends on the assumption that transcripts from closely related species (e.g., human and rhesus macaque) hybridize equally well to a homologous probe. In practice, this assumption is not always correct, which clearly confounds the experimental results (Gilad et al., 2005;Sartor et al., 2006;Chain et al., 2008). Furthermore, because many interspecies comparisons involve evolutionarily distant organisms with substantial sequence divergence, this approach has somewhat limited usefulness. ...
Introduction Use for Chemical Risk Assessment Issues to Consider Transcriptome Level Comparisons Tools and Approaches for Data Analysis Conclusions References
... This approach contrasts to what has been reported before for S. pennellii, where total trichomes, including stalks, were aggregately (trichome types were not distinguishable) analyzed for gene expression level by hybridization to the S. lycopersicum TOM2 microarray, an array containing sequences from a different Solanum species than what was used in the hybridization analysis (Slocombe et al., 2008). Such cross-species microarray experiments, while capable of differentiating rough relative expression levels between tissues within the same species for many (but not all) genes in the target species, are not capable of providing absolute expression levels or of being useful when comparing expression for any particular gene between species ( Chain et al., 2008;Gilad et al., 2009). Thus, it is unfortunately practically impossible to draw comparisons between our approach and what has been previously published with regard to observed levels of expression for any particular gene, as our approach was fundamentally different from what has been described before. ...
Glandular trichomes play important roles in protecting plants from biotic attack by producing defensive compounds. We investigated the metabolic profiles and transcriptomes to characterize the differences between different glandular trichome types in several domesticated and wild Solanum species: Solanum lycopersicum (glandular trichome types 1, 6, and 7), Solanum habrochaites (types 1, 4, and 6), Solanum pennellii (types 4 and 6), Solanum arcanum (type 6), and Solanum pimpinellifolium (type 6). Substantial chemical differences in and between Solanum species and glandular trichome types are likely determined by the regulation of metabolism at several levels. Comparison of S. habrochaites type 1 and 4 glandular trichomes revealed few differences in chemical content or transcript abundance, leading to the conclusion that these two glandular trichome types are the same and differ perhaps only in stalk length. The observation that all of the other species examined here contain either type 1 or 4 trichomes (not both) supports the conclusion that these two trichome types are the same. Most differences in metabolites between type 1 and 4 glands on the one hand and type 6 glands on the other hand are quantitative but not qualitative. Several glandular trichome types express genes associated with photosynthesis and carbon fixation, indicating that some carbon destined for specialized metabolism is likely fixed within the trichome secretory cells. Finally, Solanum type 7 glandular trichomes do not appear to be involved in the biosynthesis and storage of specialized metabolites and thus likely serve another unknown function, perhaps as the site of the synthesis of protease inhibitors.
... Similarly, comparative transcriptomics are experiencing a growing interest for a wide range of studies including abiotic stress response (Campoli et al. 2009), regulation of developmental processes (Gil-Humanes et al. 2009) or differential regulation between polyploid species (He et al. 2003; Poole et al. 2007; Salentijn et al. 2009). In this context, microarrays designed for one species are being used to determine expression divergence among species (Becher et al. 2004; Weber et al. 2004; Chain et al. 2008). However, sequence mismatches could cause bias when expression divergence of two species are compared using an array designed for only one of them (Chain et al. 2008). ...
... In this context, microarrays designed for one species are being used to determine expression divergence among species (Becher et al. 2004; Weber et al. 2004; Chain et al. 2008). However, sequence mismatches could cause bias when expression divergence of two species are compared using an array designed for only one of them (Chain et al. 2008). As a consequence these studies should validate their results using microarray-independent approaches such as quantitative real-time PCR (qPCR). ...
Comparative transcriptomics are useful to determine the role of orthologous genes among Triticeae species. Thus they constitute an interesting tool to improve the use of wild relatives for crop breeding. Reverse transcription quantitative real-time PCR (qPCR) is the most accurate measure of gene expression but efficient normalization is required. The choice and optimal number of reference genes must be experimentally determined and the primers optimized for cross-species amplification. Our goal was to test the utility of wheat-reference genes for qPCR normalization when species carrying the following genomes (A, B, D, R, H
v
and H
ch
) are compared either simultaneously or in smaller subsets of samples. Wheat/barley/rye consensus primers outperformed wheat-specific ones which indicate that consensus primers should be considered for data normalization in comparative transcriptomics. All genes tested were stable but their ranking in terms of stability differed among subsets of samples. CDC (cell division control protein, AAA-superfamily of ATPases, Ta54227) and RLI (68 kDa protein HP68 similar to Arabidopsis thaliana RNase L inhibitor protein, Ta2776) were always among the three most stable genes. The optimal number of reference genes varied between 2 and 3 depending on the subset of samples and the method used (geNorm vs. coefficient of determination between sequential normalization factors). In any case a maximum number of three reference genes would provide adequate normalization independent of the subset of samples considered. This work constitutes a substantial advance towards comparative transcriptomics using qPCR since it provides useful primers/reference genes.
... In addition to their utility in measuring gene expression levels, whole-genome DNA hybridization to expression arrays has various applications in small genome species; mutant mapping in yeast (genome size: ~12 Mb) and Arabidopsis (genome size: ~125 Mb) by bulk segregant analysis234567; quantitative trait loci extreme array mapping in Arabidopsis [4,8,9]; and comparative genomics in yeast [10], Arabidopsis [11], malaria mosquitoes (genome size: ~278 Mb) [12], in the human malarial parasite (genome size: ~23 Mb) [13], and in Mycobacterium tuberculosis (genome size: ~4.4 Mb) [14]. However, in large genome species, such as barley (genome size: ~5.2 Gb) [15], Xenopus (genome size: ~3.1 Gb) [16], and maize (genome size: ~2.5 Gb) [17], whole-genome DNA hybridization to expression arrays has not worked out well because of cross-hybridization . Although applications of oligonucleotide expression arrays were limited in large genome species, complementary RNA (cRNA) from their transcripts was used to detect SFPs in barley [15,18,19], maize [17], wheat (genome size: ~17 Gb) [20], and cowpea (genome size: ~600 Mb) [21]. ...
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.
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.
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.
... Microarrays developed for a specific species have been used for transcript profiling of closely related species. Cross-species RNA hybridization (CSH) to DNA microarrays has been used successfully in both animal and plant when a representative microarray platform is not available1516171819202122232425262728293031323334. The assumption that underlies the validity of CSH on a gene chip of a closely related species is that the level of sequence homology among genes conserved between closely related species is significant enough to enable the detection of messages by probes originally designed for their orthologs. ...
... Several CSH studies have utilized this approach [20,29,32]. However, a recent study questioned the reliability of the DNA hybridization-based method for selecting unbiased probes in CSH studies [34]. Wang et al. [27] took a different approach to identify inter-species conserved (ISC) probe sets based on the expressed sequence tag (EST) homology between target and non-target species. ...
Common bean (Phaseolus vulgaris L.) and soybean (Glycine max) both belong to the Phaseoleae tribe and share significant coding sequence homology. This suggests that the GeneChip(R) Soybean Genome Array (soybean GeneChip) may be used for gene expression studies using common bean.
To evaluate the utility of the soybean GeneChip for transcript profiling of common bean, we hybridized cRNAs purified from nodule, leaf, and root of common bean and soybean in triplicate to the soybean GeneChip. Initial data analysis showed a decreased sensitivity and accuracy of measuring differential gene expression in common bean cross-species hybridization (CSH) GeneChip data compared to that of soybean. We employed a method that masked putative probes targeting inter-species variable (ISV) regions between common bean and soybean. A masking signal intensity threshold was selected that optimized both sensitivity and accuracy of measuring differential gene expression. After masking for ISV regions, the number of differentially-expressed genes identified in common bean was increased by 2.8-fold reflecting increased sensitivity. Quantitative RT-PCR (qRT-PCR) analysis of 20 randomly selected genes and purine-ureide pathway genes demonstrated an increased accuracy of measuring differential gene expression after masking for ISV regions. We also evaluated masked probe frequency per probe set to gain insight into the sequence divergence pattern between common bean and soybean. The sequence divergence pattern analysis suggested that the genes for basic cellular functions and metabolism were highly conserved between soybean and common bean. Additionally, our results show that some classes of genes, particularly those associated with environmental adaptation, are highly divergent.
The soybean GeneChip is a suitable cross-species platform for transcript profiling in common bean when used in combination with the masking protocol described. In addition to transcript profiling, CSH of the GeneChip in combination with masking probes in the ISV regions can be used for comparative ecological and/or evolutionary genomics studies.
