Coding region structural heterogeneity and turnover of transcription start sites contribute to divergence in expression between duplicate genes

Effects of Genetic Variation of the Sorting Nexin 29 (SNX29) Gene on Growth Traits of Xiangdong Black Goat

Previous studies have found that the copy number variation (CNV) and insertion/deletion (indels) located in the sorting nexin 29 (SNX29) gene, which is an important candidate gene related to meat production and quality, are associated with growth traits of African goats and Shaanbei white cashmere goats. However, the genetic effects of SNX29 genetic variation on growth traits of Xiangdong black (XDB) goat (a representative meat goat breed in China) are still unclear. The purpose of this study was to detect the mRNA expression level of SNX29 and to explore the genetic effects of CNV and indel within SNX29 on growth traits and gene expression in XDB goat. The SNX29 mRNA expression profile showed that the SNX29 was highly expressed in adipose tissues, indicating that the SNX29 gene could play a key role in subcutaneous adipose deposition of XDB goat. 17 bp indel (g.10559298-10559314), 21 bp indel (g.10918982-10919002) and CNV were detected in 516 individuals of XDB goat by PCR or qPCR. The association analysis of SNX29 CNV with growth traits in XDB goats showed that SNX29 CNV was significantly correlated with chest circumference and abdominal circumference (p < 0.01), and the normal type of SNX29 CNV goat individuals were more advantageous. For the mRNA expression of SNX29 gene, individuals with SNX29 copy number normal type had a higher trend than that of SNX29 gene with copy number gain type in longissimus dorsi muscle (p = 0.07), whereas individuals with SNX29 copy number gain type had a higher trend in abdominal adipose (p = 0.09). Overall, these results suggested that the SNX29 gene could play an important role in growth and development of XDB goats and could be used for marker-assisted selection (MAS) in XDB goats.

Spatio-temporal transcriptome profiling and subgenome analysis in Brassica napus

Brassica napus is an important oil crop and an allotetraploid species. However, the detailed analysis of gene function and homoeologous gene expression in all tissues at different developmental stages was not explored. In this study, we performed a global transcriptome analysis of 24 vegetative and reproductive tissues at six developmental stages (totally 111 tissues). These samples were clustered into eight groups. The gene functions of silique pericarp were similar to roots, stems and leaves. In particular, glucosinolate metabolic process was associated with root and silique pericarp. Genes involved in protein phosphorylation were often associated with stamen, anther and the early developmental stage of seeds. Transcription factor (TF) genes were more specific than structural genes. A total of 17 100 genes that were preferentially expressed in one tissue (tissue-preferred genes, TPGs), including 889 TFs (5.2%), were identified in the 24 tissues. Some TPGs were identified as hub genes in the co-expression network analysis, and some TPGs in different tissues were involved in different hormone pathways. About 67.0% of the homoeologs showed balanced expression, whereas biased expression of homoeologs was associated with structural divergence. In addition, the spatiotemporal expression of homoeologs was related to the presence of transposable elements (TEs) and regulatory elements (REs); more TEs and fewer REs in the promoters resulted in divergent expression in different tissues. This study provides a valuable transcriptional map for understanding the growth and development of B. napus, for identifying important genes for future crop improvement, and for exploring gene expression patterns in the B. napus.

Detection of InDel and CNV of SPAG17 gene and their associations with bovine growth traits

Sperm-associated antigen 17 (SPAG17) gene encodes a central pair protein, which is involved in flagellar motility, male fertility and skeletal growth in ruminants. The insertions/deletions (indels) and copy number variations (CNVs) influence phenotypic traits by altering the sequences and copy numbers of functional genes, respectively. This study identified a novel 8-bp indel of SPAG17 gene in 1520 individuals from eight different cattle breeds, as well as a novel CNV region in 355 animals. The correlation analysis of indel showed that the individuals of ID genotype had superior performance traits such as body height (p = 0.038) and body slanting length (p = 0.041) as compared to other genotypes in Xianan cattle. For the CNV, different copy numbers were closely related to the body height in Qinchuan (p = 0.045) and body weight in Xianan (p = 0.036) breeds. Importantly, significant difference was observed between the 8-bp indel and the copy number loss in Xianan breed (p < 0.01). These findings indicated that the variations within the bovine SPAG17 gene can be considered as an effective DNA molecular marker for beef cattle breeding.

PIC-Me: paralogs and isoforms classifier based on machine-learning approaches

Background

Paralogs formed through gene duplication and isoforms formed through alternative splicing have been important processes for increasing protein diversity and maintaining cellular homeostasis. Despite their recognized importance and the advent of large-scale genomic and transcriptomic analyses, paradoxically, accurate annotations of all gene loci to allow the identification of paralogs and isoforms remain surprisingly incomplete. In particular, the global analysis of the transcriptome of a non-model organism for which there is no reference genome is especially challenging.

Results

To reliably discriminate between the paralogs and isoforms in RNA-seq data, we redefined the pre-existing sequence features (sequence similarity, inverse count of consecutive identical or non-identical blocks, and match-mismatch fraction) previously derived from full-length cDNAs and EST sequences and described newly discovered genomic and transcriptomic features (twilight zone of protein sequence alignment and expression level difference). In addition, the effectiveness and relevance of the proposed features were verified with two widely used support vector machine (SVM) and random forest (RF) models. From nine RNA-seq datasets, all AUC (area under the curve) scores of ROC (receiver operating characteristic) curves were over 0.9 in the RF model and significantly higher than those in the SVM model.

Conclusions

In this study, using an RF model with five proposed RNA-seq features, we implemented our method called Paralogs and Isoforms Classifier based on Machine-learning approaches (PIC-Me) and showed that it outperformed an existing method. Finally, we envision that our tool will be a valuable computational resource for the genomics community to help with gene annotation and will aid in comparative transcriptomics and evolutionary genomics studies, especially those on non-model organisms.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-021-04229-x.

ERCC5 quantification for age estimation of peripheral blood in a Chinese Han population

Age estimation is an important topic of human identification in forensic practice, especially coming to biological samples in crime scene, such as blood, saliva, semen. As rate-limiting enzyme in Nucleotide excision repair (NER) that was associated with aging, Excision repair cross-complementation group 5 (ERCC5) was considered to be a candidate biomarker for individual age estimation. The ERCC5 mRNA and protein expression levels association with age have been demonstrated in our previous study. However, very little is known about relationship DNA-based quantification of ERCC5 with age. In this study, we detected ERCC5 level in peripheral blood from a Chinese Han population by SYBR qPCR assay to gain better insight into the quantitative relationship with age. The results showed ERCC5 level declined with individual age with a negative correlation(r = -0.8, R² = 0.63, P < 0.001). The data model for age estimation based on ERCC5 level was Y = -31.352X + 14.436 ± 10.28 (Y: age, year; X: Cq_TBP-Cq_ERCC5; standard error: year). The accuracy about the data model for age estimation was about 73.33%. The mean absolute difference (MAD) values were 8.22, 8.09 and 8.38 in total, male and female, respectively. Furthermore, ERCC5 quantification for age estimation was also applicable for stored blood samples under low temperature up to 6 months. It was suggested that the ERCC5 quantification was expected to be a valuable additional method for individual age estimation, especially in cases where traditional morphologic method is absent or inefficient in forensic practice.

Primed histone demethylation regulates shoot regenerative competency

Acquisition of pluripotency by somatic cells is a striking process that enables multicellular organisms to regenerate organs. This process includes silencing of genes to erase original tissue memory and priming of additional cell type specification genes, which are then poised for activation by external signal inputs. Here, through analysis of genome-wide histone modifications and gene expression profiles, we show that a gene priming mechanism involving LYSINE-SPECIFIC DEMETHYLASE 1-LIKE 3 (LDL3) specifically eliminates H3K4me2 during formation of the intermediate pluripotent cell mass known as callus derived from Arabidopsis root cells. While LDL3-mediated H3K4me2 removal does not immediately affect gene expression, it does facilitate the later activation of genes that act to form shoot progenitors when external cues lead to shoot induction. These results give insights into the role of H3K4 methylation in plants, and into the primed state that provides plant cells with high regenerative competency.

Plant regeneration can occur via formation of a mass of pluripotent cells known as callus. Here, Ishihara et al. show that acquisition of regenerative capacity of callus-forming cells requires a lysine-specific demethylase that removes H3K4me2 to prime gene expression in response to regenerative cues.

Survival, gene and metabolite responses of Litoria verreauxii alpina frogs to fungal disease chytridiomycosis

The fungal skin disease chytridiomycosis has caused the devastating decline and extinction of hundreds of amphibian species globally, yet the potential for evolving resistance, and the underlying pathophysiological mechanisms remain poorly understood. We exposed 406 naïve, captive-raised alpine tree frogs (Litoria verreauxii alpina) from multiple populations (one evolutionarily naïve to chytridiomycosis) to the aetiological agent Batrachochytrium dendrobatidis in two concurrent and controlled infection experiments. We investigated (A) survival outcomes and clinical pathogen burdens between populations and clutches, and (B) individual host tissue responses to chytridiomycosis. Here we present multiple interrelated datasets associated with these exposure experiments, including animal signalment, survival and pathogen burden of 355 animals from Experiment A, and the following datasets related to 61 animals from Experiment B: animal signalment and pathogen burden; raw RNA-Seq reads from skin, liver and spleen tissues; de novo assembled transcriptomes for each tissue type; raw gene expression data; annotation data for each gene; and raw metabolite expression data from skin and liver tissues. These data provide an extensive baseline for future analyses.

Feed in summer, rest in winter: microbial carbon utilization in forest topsoil

BACKGROUND

Evergreen coniferous forests contain high stocks of organic matter. Significant carbon transformations occur in litter and soil of these ecosystems, making them important for the global carbon cycle. Due to seasonal allocation of photosynthates to roots, carbon availability changes seasonally in the topsoil. The aim of this paper was to describe the seasonal differences in C source utilization and the involvement of various members of soil microbiome in this process.

RESULTS

Here, we show that microorganisms in topsoil encode a diverse set of carbohydrate-active enzymes, including glycoside hydrolases and auxiliary enzymes. While the transcription of genes encoding enzymes degrading reserve compounds, such as starch or trehalose, was high in soil in winter, summer was characterized by high transcription of ligninolytic and cellulolytic enzymes produced mainly by fungi. Fungi strongly dominated the transcription in litter and an equal contribution of bacteria and fungi was found in soil. The turnover of fungal biomass appeared to be faster in summer than in winter, due to high activity of enzymes targeting its degradation, indicating fast growth in both litter and soil. In each enzyme family, hundreds to thousands of genes were typically transcribed simultaneously.

CONCLUSIONS

Seasonal differences in the transcription of glycoside hydrolases and auxiliary enzyme genes are more pronounced in soil than in litter. Our results suggest that mainly fungi are involved in decomposition of recalcitrant biopolymers in summer, while bacteria replace them in this role in winter. Transcripts of genes encoding enzymes targeting plant biomass biopolymers, reserve compounds and fungal cell walls were especially abundant in the coniferous forest topsoil.

Gene expression patterns of chicken neuregulin 3 in association with copy number variation and frameshift deletion

Background

Neuregulin 3 (NRG3) plays a key role in central nervous system development and is a strong candidate for human mental disorders. Thus, genetic variation in NRG3 may have some impact on a variety of phenotypes in non-mammalian vertebrates. Recently, genome-wide screening for short insertions and deletions in chicken (Gallus gallus) genomes has provided useful information about structural variation in functionally important genes. NRG3 is one such gene that has a putative frameshift deletion in exon 2, resulting in premature termination of translation. Our aims were to characterize the structure of chicken NRG3 and to compare expression patterns between NRG3 isoforms.

Results

Depending on the presence or absence of the 2-bp deletion in chicken NRG3, 3 breeds (red junglefowl [RJF], Boris Brown [BB], and Hinai-jidori [HJ]) were genotyped using flanking primers. In the commercial breeds (BB and HJ), approximately 45% of individuals had at least one exon 2 allele with the 2-bp deletion, whereas there was no deletion allele in RJF. The lack of a homozygous mutant indicated the existence of duplicated NRG3 segments in the chicken genome. Indeed, highly conserved elements consisting of exon 1, intron 1, exon 2, and part of intron 2 were found in the reference RJF genome, and quantitative PCR detected copy number variation (CNV) between breeds as well as between individuals. The copy number of conserved elements was significantly higher in chicks harboring the 2-bp deletion in exon 2. We identified 7 novel transcript variants using total mRNA isolated from the amygdala. Novel isoforms were found to lack the exon 2 cassette, which probably harbored the premature termination codon. The relative transcription levels of the newly identified isoforms were almost the same between chick groups with and without the 2-bp deletion, while chicks with the deletion showed significant suppression of the expression of previously reported isoforms.

Conclusions

A putative frameshift deletion and CNV in chicken NRG3 are structural mutations that occurred before the establishment of commercial chicken lines. Our results further suggest that the putative frameshift deletion in exon 2 may potentially affect the expression level of particular isoforms of chicken NRG3.

Electronic supplementary material

The online version of this article (doi:10.1186/s12863-017-0537-z) contains supplementary material, which is available to authorized users.

Accurate detection for a wide range of mutation and editing sites of microRNAs from small RNA high-throughput sequencing profiles

Various types of mutation and editing (M/E) events in microRNAs (miRNAs) can change the stabilities of pre-miRNAs and/or complementarities between miRNAs and their targets. Small RNA (sRNA) high-throughput sequencing (HTS) profiles can contain many mutated and edited miRNAs. Systematic detection of miRNA mutation and editing sites from the huge volume of sRNA HTS profiles is computationally difficult, as high sensitivity and low false positive rate (FPR) are both required. We propose a novel method (named MiRME) for an accurate and fast detection of miRNA M/E sites using a progressive sequence alignment approach which refines sensitivity and improves FPR step-by-step. From 70 sRNA HTS profiles with over 1.3 billion reads, MiRME has detected thousands of statistically significant M/E sites, including 3'-editing sites, 57 A-to-I editing sites (of which 32 are novel), as well as some putative non-canonical editing sites. We demonstrated that a few non-canonical editing sites were not resulted from mutations in genome by integrating the analysis of genome HTS profiles of two human cell lines, suggesting the existence of new editing types to further diversify the functions of miRNAs. Compared with six existing studies or methods, MiRME has shown much superior performance for the identification and visualization of the M/E sites of miRNAs from the ever-increasing sRNA HTS profiles.

A simple metric of promoter architecture robustly predicts expression breadth of human genes suggesting that most transcription factors are positive regulators

BACKGROUND

Conventional wisdom holds that, owing to the dominance of features such as chromatin level control, the expression of a gene cannot be readily predicted from knowledge of promoter architecture. This is reflected, for example, in a weak or absent correlation between promoter divergence and expression divergence between paralogs. However, an inability to predict may reflect an inability to accurately measure or employment of the wrong parameters. Here we address this issue through integration of two exceptional resources: ENCODE data on transcription factor binding and the FANTOM5 high-resolution expression atlas.

RESULTS

Consistent with the notion that in eukaryotes most transcription factors are activating, the number of transcription factors binding a promoter is a strong predictor of expression breadth. In addition, evolutionarily young duplicates have fewer transcription factor binders and narrower expression. Nonetheless, we find several binders and cooperative sets that are disproportionately associated with broad expression, indicating that models more complex than simple correlations should hold more predictive power. Indeed, a machine learning approach improves fit to the data compared with a simple correlation. Machine learning could at best moderately predict tissue of expression of tissue specific genes.

CONCLUSIONS

We find robust evidence that some expression parameters and paralog expression divergence are strongly predictable with knowledge of transcription factor binding repertoire. While some cooperative complexes can be identified, consistent with the notion that most eukaryotic transcription factors are activating, a simple predictor, the number of binding transcription factors found on a promoter, is a robust predictor of expression breadth.

DNA methylation and evolution of duplicate genes

The evolutionary mechanisms underlying duplicate gene maintenance and divergence remain highly debated. Epigenetic modifications, such as DNA methylation, may contribute to duplicate gene evolution by facilitating tissue-specific regulation. However, the role of epigenetic divergence on duplicate gene evolution remains little understood. Here we show, using comprehensive data across 10 diverse human tissues, that DNA methylation plays critical roles in several aspects of duplicate gene evolution. We first demonstrate that duplicate genes are initially heavily methylated, before gradually losing DNA methylation as they age. Within each pair, DNA methylation divergence between duplicate partners increases with evolutionary age. Importantly, tissue-specific DNA methylation of duplicates correlates with tissue-specific expression, implicating DNA methylation as a causative factor for functional divergence of duplicate genes. These patterns are apparent in promoters but not in gene bodies, in accord with the complex relationship between gene-body DNA methylation and transcription. Remarkably, many duplicate gene pairs exhibit consistent division of DNA methylation across multiple, divergent tissues: For the majority (73%) of duplicate gene pairs, one partner is always hypermethylated compared with the other. This is indicative of a common underlying determinant of DNA methylation. The division of DNA methylation is also consistent with their chromatin accessibility profiles. Moreover, at least two sequence motifs known to interact with the Sp1 transcription factor mark promoters of more hypomethylated duplicate partners. These results demonstrate critical roles of DNA methylation, as well as complex interaction between genome and epigenome, on duplicate gene evolution.

Transcription start site evolution in Drosophila

Transcription start site (TSS) evolution remains largely undescribed in Drosophila, likely due to limited annotations in non-melanogaster species. In this study, we introduce a concise new method that selectively sequences from the 5′-end of mRNA and used it to identify TSS in four Drosophila species, including Drosophila melanogaster, D. simulans, D. sechellia, and D. pseudoobscura. For verification, we compared our results in D. melanogaster with known annotations, published 5′-rapid amplification of cDNA ends data, and with RNAseq from the same mRNA pool. Then, we paired 2,849 D. melanogaster TSS with its closest equivalent TSS in each species (likely to be its true ortholog) using the available multiple sequence alignments. Most of the D. melanogaster TSSs were successfully paired with an ortholog in each species (83%, 86%, and 55% for D. simulans, D. sechellia, and D. pseudoobscura, respectively). On the basis of the number and distribution of reads mapped at each TSS, we also estimated promoter-specific expression (PSE) and TSS peak shape, respectively. Among paired TSS orthologs, the location and promoter activity were largely conserved. TSS location appears important as PSE, and TSS peak shape was more frequently divergent among TSS that had moved. Unpaired TSS were surprisingly common in D. pseudoobscura. An increased mutation rate upstream of TSS might explain this pattern. We found an enrichment of ribosomal protein genes among diverged TSS, suggesting that TSS evolution is not uniform across the genome.

Asymmetric functional divergence of young, dispersed gene duplicates in Arabidopsis thaliana

One prediction of the classic Ohno model of gene duplication predicts that new genes form from the asymmetric functional divergence of a newly arisen, redundant duplicate locus. In order to understand the mechanisms which give rise to functional divergence of newly formed dispersed duplicates, we assessed the expression and molecular evolutionary divergence of a suite of 19 highly similar dispersed duplicates in Arabidopsis thaliana. These duplicates have a K sil equal to or less than 5 % and are specific to the A. thaliana lineage; thus, they predictably represent some of the youngest duplicates in the A. thaliana genome. We found that the majority of young duplicate loci exhibit asymmetric expression patterns, with the daughter locus exhibiting reduced expression across all tissues analyzed relative to the progenitor locus or simply not expressed. Furthermore, daughter loci, on the whole, have significantly more nonsynonymous substitutions than the progenitor loci. We also identified four pairs of loci which exhibit significant (P < 0.05) evolutionary rate asymmetry, three of which exhibit elevated dN/dS in the duplicate copy. We suggest, based on these data, that functional diversification initially takes the form of asymmetric regulatory divergence that can be a direct consequence of the mode of duplication. The reduced and/or absence of expression in the daughter copy relaxes functional constraint on its protein coding sequence leading to the asymmetric accumulation of nonsynonymous mutations. Thus, our data both affirm Ohno's prediction while explaining the mechanism by which functional divergence initially occurs following duplication for dispersed gene duplicates.

High expression hampers horizontal gene transfer

Horizontal gene transfer (HGT), the movement of genetic material from one species to another, is a common phenomenon in prokaryotic evolution. Although the rate of HGT is known to vary among genes, our understanding of the cause of this variation, currently summarized by two rules, is far from complete. The first rule states that informational genes, which are involved in DNA replication, transcription, and translation, have lower transferabilities than operational genes. The second rule asserts that protein interactivity negatively impacts gene transferability. Here, we hypothesize that high expression hampers HGT, because the fitness cost of an HGT to the recipient, arising from the 1) energy expenditure in transcription and translation, 2) cytotoxic protein misfolding, 3) reduction in cellular translational efficiency, 4) detrimental protein misinteraction, and 5) disturbance of the optimal protein concentration or cell physiology, increases with the expression level of the transferred gene. To test this hypothesis, we examined laboratory and natural HGTs to Escherichia coli. We observed lower transferabilities of more highly expressed genes, even after controlling the confounding factors from the two established rules and the genic GC content. Furthermore, expression level predicts gene transferability better than all other factors examined. We also confirmed the significant negative impact of gene expression on the rate of HGTs to 127 of 133 genomes of eubacteria and archaebacteria. Together, these findings establish the gene expression level as a major determinant of horizontal gene transferability. They also suggest that most successful HGTs are initially slightly deleterious, fixed because of their negligibly low costs rather than high benefits to the recipient.

Diversification at transcription factor binding sites within a species and the implications for environmental adaptation

Evolution of new cellular functions can be achieved both by changes in protein coding sequences and by alteration of expression patterns. Variation of expression may lead to changes in cellular function with relatively little change in genomic sequence. We therefore hypothesize that one of the first signals of functional divergence should be evolution of transcription factor-binding sites (TFBSs). This adaptation should be detectable as substantial variation in the TFBSs of alleles. New data sets allow the first analyses of intraspecies variation from large number of whole-genome sequences. Using data from the Saccharomyces Genome Resequencing Project, we have analyzed variation in TFBSs. We find a large degree of variation both between these closely related strains and between pairs of duplicated genes. There is a correlation between changes in promoter regions and changes in coding sequences, indicating a coupling of changes in expression and function. We show that 1) the types genes with diverged promoters vary between strains from different environments and 2) that patterns of divergence in promoters consistent with positive selection are detectable in alleles between strains and on duplicate promoters. This variation is likely to reflect adaptation to each strain's natural environment. We conclude that, even within a species, we detect signs of selection acting on promoter regions that may act to alter expression patterns. These changes may indicate functional innovation in multiple genes and across the whole genome. Change in function could represent adaptation to the environment and be a precursor to speciation.

A computational approach to candidate gene prioritization for X-linked mental retardation using annotation-based binary filtering and motif-based linear discriminatory analysis

Background

Several computational candidate gene selection and prioritization methods have recently been developed. These in silico selection and prioritization techniques are usually based on two central approaches - the examination of similarities to known disease genes and/or the evaluation of functional annotation of genes. Each of these approaches has its own caveats. Here we employ a previously described method of candidate gene prioritization based mainly on gene annotation, in accompaniment with a technique based on the evaluation of pertinent sequence motifs or signatures, in an attempt to refine the gene prioritization approach. We apply this approach to X-linked mental retardation (XLMR), a group of heterogeneous disorders for which some of the underlying genetics is known.

Results

The gene annotation-based binary filtering method yielded a ranked list of putative XLMR candidate genes with good plausibility of being associated with the development of mental retardation. In parallel, a motif finding approach based on linear discriminatory analysis (LDA) was employed to identify short sequence patterns that may discriminate XLMR from non-XLMR genes. High rates (>80%) of correct classification was achieved, suggesting that the identification of these motifs effectively captures genomic signals associated with XLMR vs. non-XLMR genes. The computational tools developed for the motif-based LDA is integrated into the freely available genomic analysis portal Galaxy (http://main.g2.bx.psu.edu/). Nine genes (APLN, ZC4H2, MAGED4, MAGED4B, RAP2C, FAM156A, FAM156B, TBL1X, and UXT) were highlighted as highly-ranked XLMR methods.

Conclusions

The combination of gene annotation information and sequence motif-orientated computational candidate gene prediction methods highlight an added benefit in generating a list of plausible candidate genes, as has been demonstrated for XLMR.

Reviewers: This article was reviewed by Dr Barbara Bardoni (nominated by Prof Juergen Brosius); Prof Neil Smalheiser and Dr Dustin Holloway (nominated by Prof Charles DeLisi).

Evidences for increased expression variation of duplicate genes in budding yeast: from cis- to trans-regulation effects

Duplicate genes tend to have a more variable expression program than singleton genes, which was thought to be an important way for the organism to respond and adapt to fluctuating environment. However, the underlying molecular mechanisms driving such expression variation remain largely unexplored. In this work, we first rigorously confirmed that duplicate genes indeed have higher gene expression variation than singleton genes in several aspects, i.e. responses to environmental perturbation, between-strain divergence, and expression noise. To investigate the underlying mechanism, we further analyzed a previously published expression dataset of yeast segregants produced from genetic crosses. We dissected the observed expression divergence between segregant strains into cis- and trans-variabilities, and demonstrated that trans-regulation effect can explain larger fraction of the expression variation than cis-regulation effect. This is true for both duplicate genes and singleton genes. In contrast, we found, between a pair of sister paralogs, cis-variability explains more of the expression divergence between the paralogs than trans-variability. We next investigated the presence of cis- and trans-features that are associated with elevated expression variations. For cis-acting regulation, duplicate genes have higher genetic diversity in their promoters and coding regions than singleton genes. For trans-acting regulation, duplicate and singleton genes are differentially regulated by chromatin regulators and transcription factors, and duplicate genes are more severely affected by the deletion of histone tails. These results showed that both cis-and trans-factors have great effect in causing the increased expression variation of duplicate genes, and explained the previously observed differences in transcription regulation between duplicate genes and singleton genes.

The impact of gene expression regulation on evolution of extracellular signaling pathways

Extracellular protein interactions are crucial to the development of multicellular organisms because they initiate signaling pathways and enable cellular recognition cues. Despite their importance, extracellular protein interactions are often under-represented in large scale protein interaction data sets because most high throughput assays are not designed to detect low affinity extracellular interactions. Due to the lack of a comprehensive data set, the evolution of extracellular signaling pathways has remained largely a mystery. We investigated this question using a combined data set of physical pairwise interactions between zebrafish extracellular proteins, mainly from the immunoglobulin superfamily and leucine-rich repeat families, and their spatiotemporal expression profiles. We took advantage of known homology between proteins to estimate the relative rates of changes of four parameters after gene duplication, namely extracellular protein interaction, expression pattern, and the divergence of extracellular and intracellular protein sequences. We showed that change in expression profile is a major contributor to the evolution of signaling pathways followed by divergence in intracellular protein sequence, whereas extracellular sequence and interaction profiles were relatively more conserved. Rapidly evolving expression profiles will eventually drive other parameters to diverge more quickly because differentially expressed proteins get exposed to different environments and potential binding partners. This allows homologous extracellular receptors to attain specialized functions and become specific to tissues and/or developmental stages.

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).

Noncoding sequences near duplicated genes evolve rapidly

Gene expression divergence and chromosomal rearrangements have been put forward as major contributors to phenotypic differences between closely related species. It has also been established that duplicated genes show enhanced rates of positive selection in their amino acid sequences. If functional divergence is largely due to changes in gene expression, it follows that regulatory sequences in duplicated loci should also evolve rapidly. To investigate this hypothesis, we performed likelihood ratio tests (LRTs) on all noncoding loci within 5 kb of every transcript in the human genome and identified sequences with increased substitution rates in the human lineage since divergence from Old World Monkeys. The fraction of rapidly evolving loci is significantly higher nearby genes that duplicated in the common ancestor of humans and chimps compared with nonduplicated genes. We also conducted a genome-wide scan for nucleotide substitutions predicted to affect transcription factor binding. Rates of binding site divergence are elevated in noncoding sequences of duplicated loci with accelerated substitution rates. Many of the genes associated with these fast-evolving genomic elements belong to functional categories identified in previous studies of positive selection on amino acid sequences. In addition, we find enrichment for accelerated evolution nearby genes involved in establishment and maintenance of pregnancy, processes that differ significantly between humans and monkeys. Our findings support the hypothesis that adaptive evolution of the regulation of duplicated genes has played a significant role in human evolution.

Why does binding of proteins to DNA or proteins to proteins not necessarily spell function?

Studies of binding are often question: first, is the observed binding functional, and second, if it is, which function? Is it activation or repression? The first question relates to binding at different sites; the second relates to binding at similar sites. These questions apply to transcription factors binding to genomic DNA and to protein interaction domains binding to their partners. Here, we explain that both can be understood in terms of allostery and the cellular (or in vitro) environment. The idea is simple yet powerful; it emphasizes the role of allostery in defining whether binding between transcription factors and (cognate or noncognate) DNA sequences will lead to function and to the type of function. Allosteric effects are the outcome of dynamically shifting populations; thus binding to even slightly different DNA sequences will lead to different transcription factor conformations that can be reflected in the binding sites to their co-regulators. Currently, allostery is not considered when trying to understand how binding phenomena determine the functional outcome. Allosteric effects can enhance the binding specificity in a function-oriented manner. Here we provide a biological rationale that considers cellular crowding effects.

Translog, a web browser for studying the expression divergence of homologous genes

Background

Increasing amount of data from comparative genomics, and newly developed technologies producing accurate gene expression data facilitate the study of the expression divergence of homologous genes. Previous studies have individually highlighted factors that contribute to the expression divergence of duplicate genes, e.g. promoter changes, exon structure heterogeneity, asymmetric histone modifications and genomic neighborhood conservation. However, there is a lack of a tool to integrate multiple factors and visualize their variety among homologous genes in a straightforward way.

Results

We introduce Translog (a web-based tool for Transcriptome comparison of homologous genes) that assists in the comparison of homologous genes by displaying the loci in three different views: promoter view for studying the sharing/turnover of transcription initiations, exon structure for displaying the exon-intron structure changes, and genomic neighborhood to show the macro-synteny conservation in a larger scale. CAGE data for transcription initiation are mapped for each transcript and can be used to study transcription turnover and expression changes. Alignment anchors between homologous loci can be used to define the precise homologous transcripts. We demonstrate how these views can be used to visualize the changes of homologous genes during evolution, particularly after the 2R and 3R whole genome duplication.

Conclusion

We have developed a web-based tool for assisting in the transcriptome comparison of homologous genes, facilitating the study of expression divergence.

Protein-protein interaction networks: how can a hub protein bind so many different partners?

How can a single hub protein bind so many different partners? Numerous studies have sought differences between hubs and non-hubs to explain what makes a protein a hub and how a shared hub-binding site can be promiscuous, yet at the same time be specific. Here, we suggest that the problem is largely non-existent and resides in the popular representation of protein interaction networks: protein products derived from a single gene, even if different, are clustered in maps into a single node. This leads to the impression that a single protein binds to a very large number of partners. In reality, it does not; rather, protein networks reflect the combination of multiple proteins, each with a distinct conformation.

Evolution and survival on eutherian sex chromosomes

Since the two eutherian sex chromosomes diverged from an ancestral autosomal pair, the X has remained relatively gene-rich, while the Y has lost most of its genes through the accumulation of deleterious mutations in nonrecombining regions. Presently, it is unclear what is distinctive about genes that remain on the Y chromosome, when the sex chromosomes acquired their unique evolutionary rates, and whether X-Y gene divergence paralleled that of paralogs located on autosomes. To tackle these questions, here we juxtaposed the evolution of X and Y homologous genes (gametologs) in eutherian mammals with their autosomal orthologs in marsupial and monotreme mammals. We discovered that genes on the X and Y acquired distinct evolutionary rates immediately following the suppression of recombination between the two sex chromosomes. The Y-linked genes evolved at higher rates, while the X-linked genes maintained the lower evolutionary rates of the ancestral autosomal genes. These distinct rates have been maintained throughout the evolution of X and Y. Specifically, in humans, most X gametologs and, curiously, also most Y gametologs evolved under stronger purifying selection than similarly aged autosomal paralogs. Finally, after evaluating the current experimental data from the literature, we concluded that unique mRNA/protein expression patterns and functions acquired by Y (versus X) gametologs likely contributed to their retention. Our results also suggest that either the boundary between sex chromosome strata 3 and 4 should be shifted or that stratum 3 should be divided into two strata.

Using recently available marsupial and monotreme genomes, we investigated nascent sex chromosome evolution in mammals. We show that, in eutherian mammals, X and Y genes acquired distinct evolutionary rates and functional constraints immediately after recombination suppression; X-linked genes maintained lower, ancestral (autosomal), rates, whereas the evolutionary rates of Y-linked genes increased. Most X and, unexpectedly, Y genes evolved under stronger purifying selection than similarly aged autosomal paralogs. However, we also observed that the divergence of gametologs and paralogs shared similar features. In addition, many Y-linked copies evolved unique functions and expression patterns compared to their counterparts on the X chromosome. Therefore, our results suggest that to be retained on the Y chromosome, genes need to acquire separately valuable expression and/or functions to be safeguarded by purifying selection.

A comprehensive analysis of gene expression evolution between humans and mice

Evolutionary changes in gene expression account for most phenotypic differences between species. Advances in microarray technology have made the systematic study of gene expression evolution possible. In this study, gene expression patterns were compared between human and mouse genomes using two published methods. Specifically, we studied how gene expression evolution was related to GO terms and tried to decode the relationship between promoter evolution and gene expression evolution. The results showed that (1) the significant enrichment of biological processes in orthologs of expression conservation reveals functional significance of gene expression conservation. The more conserved gene expression in some biological processes than is expected in a purely neutral model reveals negative selection on gene expression. However, fast evolving genes mainly support the neutrality of gene expression evolution, and (2) gene expression conservation is positively but only slightly correlated with promoter conservation based on a motif-count score of the promoter alignment. Our results suggest a neutral model with negative selection for gene expression evolution between humans and mice, and promoter evolution could have some effects on gene expression evolution.