A comprehensive analysis of gene expression evolution between humans and mice

Cross-Species Meta-Analysis of Transcriptomic Data in Combination With Supervised Machine Learning Models Identifies the Common Gene Signature of Lactation Process

Lactation, a physiologically complex process, takes place in mammary gland after parturition. The expression profile of the effective genes in lactation has not comprehensively been elucidated. Herein, meta-analysis, using publicly available microarray data, was conducted identify the differentially expressed genes (DEGs) between pre- and post-peak milk production. Three microarray datasets of Rat, Bos Taurus, and Tammar wallaby were used. Samples related to pre-peak (n = 85) and post-peak (n = 24) milk production were selected. Meta-analysis revealed 31 DEGs across the studied species. Interestingly, 10 genes, including MRPS18B, SF1, UQCRC1, NUCB1, RNF126, ADSL, TNNC1, FIS1, HES5 and THTPA, were not detected in original studies that highlights meta-analysis power in biosignature discovery. Common target and regulator analysis highlighted the high connectivity of CTNNB1, CDD4 and LPL as gene network hubs. As data originally came from three different species, to check the effects of heterogeneous data sources on DEGs, 10 attribute weighting (machine learning) algorithms were applied. Attribute weighting results showed that the type of organism had no or little effect on the selected gene list. Systems biology analysis suggested that these DEGs affect the milk production by improving the immune system performance and mammary cell growth. This is the first study employing both meta-analysis and machine learning approaches for comparative analysis of gene expression pattern of mammary glands in two important time points of lactation process. The finding may pave the way to use of publically available to elucidate the underlying molecular mechanisms of physiologically complex traits such as lactation in mammals.

Comparative transcriptomics in human and mouse

Cross-species comparisons of genomes, transcriptomes and gene regulation are now feasible at unprecedented resolution and throughput, enabling the comparison of human and mouse biology at the molecular level. Insights have been gained into the degree of conservation between human and mouse at the level of not only gene expression but also epigenetics and inter-individual variation. However, a number of limitations exist, including incomplete transcriptome characterization and difficulties in identifying orthologous phenotypes and cell types, which are beginning to be addressed by emerging technologies. Ultimately, these comparisons will help to identify the conditions under which the mouse is a suitable model of human physiology and disease, and optimize the use of animal models.

Neighboring Genes Show Correlated Evolution in Gene Expression

When considering the evolution of a gene’s expression profile, we commonly assume that this is unaffected by its genomic neighborhood. This is, however, in contrast to what we know about the lack of autonomy between neighboring genes in gene expression profiles in extant taxa. Indeed, in all eukaryotic genomes genes of similar expression-profile tend to cluster, reflecting chromatin level dynamics. Does it follow that if a gene increases expression in a particular lineage then the genomic neighbors will also increase in their expression or is gene expression evolution autonomous? To address this here we consider evolution of human gene expression since the human-chimp common ancestor, allowing for both variation in estimation of current expression level and error in Bayesian estimation of the ancestral state. We find that in all tissues and both sexes, the change in gene expression of a focal gene on average predicts the change in gene expression of neighbors. The effect is highly pronounced in the immediate vicinity (<100 kb) but extends much further. Sex-specific expression change is also genomically clustered. As genes increasing their expression in humans tend to avoid nuclear lamina domains and be enriched for the gene activator 5-hydroxymethylcytosine, we conclude that, most probably owing to chromatin level control of gene expression, a change in gene expression of one gene likely affects the expression evolution of neighbors, what we term expression piggybacking, an analog of hitchhiking.

Enhanced transcriptome maps from multiple mouse tissues reveal evolutionary constraint in gene expression

Mice have been a long-standing model for human biology and disease. Here we characterize, by RNA sequencing, the transcriptional profiles of a large and heterogeneous collection of mouse tissues, augmenting the mouse transcriptome with thousands of novel transcript candidates. Comparison with transcriptome profiles in human cell lines reveals substantial conservation of transcriptional programmes, and uncovers a distinct class of genes with levels of expression that have been constrained early in vertebrate evolution. This core set of genes captures a substantial fraction of the transcriptional output of mammalian cells, and participates in basic functional and structural housekeeping processes common to all cell types. Perturbation of these constrained genes is associated with significant phenotypes including embryonic lethality and cancer. Evolutionary constraint in gene expression levels is not reflected in the conservation of the genomic sequences, but is associated with conserved epigenetic marking, as well as with characteristic post-transcriptional regulatory programme, in which sub-cellular localization and alternative splicing play comparatively large roles.

The analysis of mammalian transcriptomes could provide new insights into human biology. Here the authors carry out RNA sequencing in a large collection of mouse tissues and compare these data to human transcriptome profiles, identifying a set of constrained genes that carry out basic cellular functions with remarkably constant expression levels across tissues and species.

The relationship between gene isoform multiplicity, number of exons and protein divergence

At present we know that phenotypic differences between organisms arise from a variety of sources, like protein sequence divergence, regulatory sequence divergence, alternative splicing, etc. However, we do not have yet a complete view of how these sources are related. Here we address this problem, studying the relationship between protein divergence and the ability of genes to express multiple isoforms. We used three genome-wide datasets of human-mouse orthologs to study the relationship between isoform multiplicity co-occurrence between orthologs (the fact that two orthologs have more than one isoform) and protein divergence. In all cases our results showed that there was a monotonic dependence between these two properties. We could explain this relationship in terms of a more fundamental one, between exon number of the largest isoform and protein divergence. We found that this last relationship was present, although with variations, in other species (chimpanzee, cow, rat, chicken, zebrafish and fruit fly). In summary, we have identified a relationship between protein divergence and isoform multiplicity co-occurrence and explained its origin in terms of a simple gene-level property. Finally, we discuss the biological implications of these findings for our understanding of inter-species phenotypic differences.

Underlying functional genomics of fat deposition in adipose tissue

The objective of this study was to gain insight into the underlying mechanisms of fat deposition. Two sheep breeds with large fat-tail (Lori-Bakhtiari) and with thin-tail (Zel) were used as models. To determine important and key candidate lipid metabolism related genes, comparative genomic approaches were employed. Gene expression profiles of adipose tissues were analyzed in human, pig, and cattle by express sequence tag (EST) analysis. EST analysis determined 65, 102 and 125 transcripts in human, pig and cattle respectively with at least 10 fold over-expression in the adipose tissue. Based on our comparative functional genomic analysis, seven genes were more abundant and common in investigated mammalian adipose tissues promising a conserved novel gene network in mammalian lipid metabolism. The candidate genes including fatty acid binding protein 4 (FABP4), fatty acid synthase (FASN), Stearoyl-CoA desaturase (SCD) and Lipoprotein lipase (LPL) were selected for further gene expression investigation within two sheep breeds. The real time PCR results showed that among the genes tested, FABP4 was expressed at higher levels than the others. The expression of FABP4 was significantly higher in the fat-tail of Lori-Bakhtiari than in the fat-tail and visceral adipose tissues of Zel (P<0.05). The findings suggest that the FABP4 gene expression in the fat-tail is an important index of fat deposition.

Comparative modular analysis of gene expression in vertebrate organs

Background

The degree of conservation of gene expression between homologous organs largely remains an open question. Several recent studies reported some evidence in favor of such conservation. Most studies compute organs' similarity across all orthologous genes, whereas the expression level of many genes are not informative about organ specificity.

Results

Here, we use a modularization algorithm to overcome this limitation through the identification of inter-species co-modules of organs and genes. We identify such co-modules using mouse and human microarray expression data. They are functionally coherent both in terms of genes and of organs from both organisms. We show that a large proportion of genes belonging to the same co-module are orthologous between mouse and human. Moreover, their zebrafish orthologs also tend to be expressed in the corresponding homologous organs. Notable exceptions to the general pattern of conservation are the testis and the olfactory bulb. Interestingly, some co-modules consist of single organs, while others combine several functionally related organs. For instance, amygdala, cerebral cortex, hypothalamus and spinal cord form a clearly discernible unit of expression, both in mouse and human.

Conclusions

Our study provides a new framework for comparative analysis which will be applicable also to other sets of large-scale phenotypic data collected across different species.

Modes of gene duplication contribute differently to genetic novelty and redundancy, but show parallels across divergent angiosperms

Background

Both single gene and whole genome duplications (WGD) have recurred in angiosperm evolution. However, the evolutionary effects of different modes of gene duplication, especially regarding their contributions to genetic novelty or redundancy, have been inadequately explored.

Results

In Arabidopsis thaliana and Oryza sativa (rice), species that deeply sample botanical diversity and for which expression data are available from a wide range of tissues and physiological conditions, we have compared expression divergence between genes duplicated by six different mechanisms (WGD, tandem, proximal, DNA based transposed, retrotransposed and dispersed), and between positional orthologs. Both neo-functionalization and genetic redundancy appear to contribute to retention of duplicate genes. Genes resulting from WGD and tandem duplications diverge slowest in both coding sequences and gene expression, and contribute most to genetic redundancy, while other duplication modes contribute more to evolutionary novelty. WGD duplicates may more frequently be retained due to dosage amplification, while inferred transposon mediated gene duplications tend to reduce gene expression levels. The extent of expression divergence between duplicates is discernibly related to duplication modes, different WGD events, amino acid divergence, and putatively neutral divergence (time), but the contribution of each factor is heterogeneous among duplication modes. Gene loss may retard inter-species expression divergence. Members of different gene families may have non-random patterns of origin that are similar in Arabidopsis and rice, suggesting the action of pan-taxon principles of molecular evolution.

Conclusion

Gene duplication modes differ in contribution to genetic novelty and redundancy, but show some parallels in taxa separated by hundreds of millions of years of evolution.

Integrative transcriptional analysis between human and mouse cancer cells provides a common set of transformation associated genes

Mouse functional genomics is largely used to investigate relevant aspects of mammalian physiology and pathology. To which degree mouse models may offer accurate representations of molecular events underlining human diseases such as cancer is not yet fully established. Herein we compare gene expression signatures between a set of human cancer cell lines (NCI-60 cell collection) and a mouse cellular model of oncogenic K-ras dependent transformation in order to identify their closeness at the transcriptional level. The results of our integrative and comparative analysis show that in both species as compared to normal cells or tissues the transformation process involves the activation of a transcriptional response. Furthermore, the cellular mouse model of K-ras dependent transformation has a good degree of similarity with several human cancer cell lines and in particular with cell lines containing oncogenic Ras mutations. Moreover both species have similar genetic signatures that are associated to the same altered cellular pathways (e.g. Spliceosome and Proteasome) or to deregulation of the same genes (e.g. cyclin D1, AHSA1 and HNRNPD) detected in the comparison between cancer cells versus normal cells or tissues. In summary, we report one of the first in-depth analysis of global gene expression profiles of a K-ras dependent mouse cell model of transformation and a large collection of human cancer cells as compared to their normal counterparts. Taken together our findings show a strong correlation in the transcriptional and pathway alteration responses between the two species, therefore validating the use of the mouse model as an appropriate tool to investigate human cancer, and indicating that the comparative analysis, as described here, offers a useful approach to identify cancer-specific gene signatures.

Positive selection at high temperature reduces gene transcription in the bacteriophage ϕX174

Background

Gene regulation plays a central role in the adaptation of organisms to their environments. There are many molecular components to gene regulation, and it is often difficult to determine both the genetic basis of adaptation and the evolutionary forces that influence regulation. In multiple evolution experiments with the bacteriophage ϕX174, adaptive substitutions in cis-acting regulatory sequences sweep through the phage population as the result of strong positive selection at high temperatures that are non-permissive for laboratory-adapted phage. For one cis-regulatory region, we investigate the individual effects of four adaptive substitutions on transcript levels and fitness for phage growing on three hosts at two temperatures.

Results

The effect of the four individual substitutions on transcript levels is to down-regulate gene expression, regardless of temperature or host. To ascertain the conditions under which these substitutions are adaptive, fitness was measured by a variety of methods for several bacterial hosts growing at two temperatures, the control temperature of 37°C and the selective temperature of 42°C. Time to lysis and doublings per hour indicate that the four substitutions individually improve fitness over the ancestral strain at high temperature independent of the bacterial host in which the fitness was measured. Competition assays between the ancestral strain and either of two mutant strains indicate that both mutants out-compete the ancestor at high temperature, but the relative frequencies of each phage remain the same at the control temperature.

Conclusions

Our results strongly suggest that gene transcription plays an important role in influencing fitness in the bacteriophage ϕX174, and different point mutations in a single cis-regulatory region provided the genetic basis for this role in adaptation to high temperature. We speculate that the adaptive nature of these substitutions is due to the physiology of the host at high temperature or the need to maintain particular ratios of phage proteins during capsid assembly. Our investigation of regulatory evolution contributes to interpreting genome-level assessments of regulatory variation, as well as to understanding the molecular basis of adaptation.

Comparison of computational models for assessing conservation of gene expression across species

Assessing conservation/divergence of gene expression across species is important for the understanding of gene regulation evolution. Although advances in microarray technology have provided massive high-dimensional gene expression data, the analysis of such data is still challenging. To date, assessing cross-species conservation of gene expression using microarray data has been mainly based on comparison of expression patterns across corresponding tissues, or comparison of co-expression of a gene with a reference set of genes. Because direct and reliable high-throughput experimental data on conservation of gene expression are often unavailable, the assessment of these two computational models is very challenging and has not been reported yet. In this study, we compared one corresponding tissue based method and three co-expression based methods for assessing conservation of gene expression, in terms of their pair-wise agreements, using a frequently used human-mouse tissue expression dataset. We find that 1) the co-expression based methods are only moderately correlated with the corresponding tissue based methods, 2) the reliability of co-expression based methods is affected by the size of the reference ortholog set, and 3) the corresponding tissue based methods may lose some information for assessing conservation of gene expression. We suggest that the use of either of these two computational models to study the evolution of a gene's expression may be subject to great uncertainty, and the investigation of changes in both gene expression patterns over corresponding tissues and co-expression of the gene with other genes is necessary.

Measuring gene expression divergence: the distance to keep

Background

Gene expression divergence is a phenotypic trait reflecting evolution of gene regulation and characterizing dissimilarity between species and between cells and tissues within the same species. Several distance measures, such as Euclidean and correlation-based distances have been proposed for measuring expression divergence.

Results

We show that different distance measures identify different trends in gene expression patterns. When comparing orthologous genes in eight rat and human tissues, the Euclidean distance identified genes uniformly expressed in all tissues near the expression background as genes with the most conserved expression pattern. In contrast, correlation-based distance and generalized-average distance identified genes with concerted changes among homologous tissues as those most conserved. On the other hand, correlation-based distance, Euclidean distance and generalized-average distance highlight quite well the relatively high similarity of gene expression patterns in homologous tissues between species, compared to non-homologous tissues within species.

Conclusions

Different trends exist in the high-dimensional numeric data, and to highlight a particular trend an appropriate distance measure needs to be chosen. The choice of the distance measure for measuring expression divergence can be dictated by the expression patterns that are of interest in a particular study.

Reviewers

This article was reviewed by Mikhail Gelfand, Eugene Koonin and Subhajyoti De (nominated by Sarah Teichmann).

Microarray data analysis of gene expression evolution

Microarrays are becoming a widely used tool to study gene expression evolution. A recent paper by Wang and Rekaya describes a comprehensive study of gene expression evolution by microarray. The work provides a perspective to study gene expression evolution in terms of functional enrichment and promoter conservation. It was found that gene expression patterns are highly conserved in some biological processes, but the correlation between promoter and gene expression is insignificant. This scope of this work and future improvement to study gene expression evolution will be discussed in this article.