Quantitative measurement of allele-specific protein expression in a diploid yeast hybrid by LC-MS

Normal Alpha-1-Antitrypsin Variants Display in Serum Allele-Specific Protein Levels

Alpha-1-antitrypsin (A1AT or SERPINA1) has been proposed as a putative biomarker distinguishing healthy from diseased donors throughout several proteomics studies. However, the SERPINA1 gene displays high variability of frequent occurring genotypes among the general population. These different genotypes may affect A1AT expression and serum protein concentrations, and this is often not known, ignored, and/or not reported in serum proteomics studies. Here, we address allele-specific protein serum levels of A1AT in donors carrying the normal M variants of A1AT by measuring the proteoform profiles of purified A1AT from 81 serum samples, originating from 52 donors. When focusing on heterozygous donors, our data clearly reveal a statistically relevant difference in allele-specific protein serum levels of A1AT. In donors with genotype PI*M1VM1A, the experimentally observed ratio was approximately 1:1 (M1V/M1A, 1.00:0.96 ± 0.07, n = 17). For individuals with genotype PI*M1VM2, this ratio was 1:1.28 (M1V/M2, 1.00:1.31, ±0.19, n = 7). For genotypes PI*M1VM3 and PI*M1AM3, a significant higher amount of M3 was observed compared to the M1-subtypes (M1V/M3, 1.00:1.84 ± 0.35, n = 8; M1A/M3, 1.00:1.61 ± 0.33, n = 5). We argue that these observations are important and should be considered when analyzing serum A1AT levels before proposing A1AT as a putative serum biomarker.

Gene age shapes the transcriptional landscape of sexual morphogenesis in mushroom forming fungi (Agaricomycetes)

Multicellularity has been one of the most important innovations in the history of life. The role of gene regulatory changes in driving transitions to multicellularity is being increasingly recognized; however, factors influencing gene expression patterns are poorly known in many clades. Here, we compared the developmental transcriptomes of complex multicellular fruiting bodies of eight Agaricomycetes and Cryptococcus neoformans, a closely related human pathogen with a simple morphology. In-depth analysis in Pleurotus ostreatus revealed that allele-specific expression, natural antisense transcripts, and developmental gene expression, but not RNA editing or a ‘developmental hourglass,’ act in concert to shape its transcriptome during fruiting body development. We found that transcriptional patterns of genes strongly depend on their evolutionary ages. Young genes showed more developmental and allele-specific expression variation, possibly because of weaker evolutionary constraint, suggestive of nonadaptive expression variance in fruiting bodies. These results prompted us to define a set of conserved genes specifically regulated only during complex morphogenesis by excluding young genes and accounting for deeply conserved ones shared with species showing simple sexual development. Analysis of the resulting gene set revealed evolutionary and functional associations with complex multicellularity, which allowed us to speculate they are involved in complex multicellular morphogenesis of mushroom fruiting bodies.

SMAP is a pipeline for sample matching in proteogenomics

The integration of genomics and proteomics data (proteogenomics) holds the promise of furthering the in-depth understanding of human disease. However, sample mix-up is a pervasive problem in proteogenomics because of the complexity of sample processing. Here, we present a pipeline for Sample Matching in Proteogenomics (SMAP) to verify sample identity and ensure data integrity. SMAP infers sample-dependent protein-coding variants from quantitative mass spectrometry (MS), and aligns the MS-based proteomic samples with genomic samples by two discriminant scores. Theoretical analysis with simulated data indicates that SMAP is capable of uniquely matching proteomic and genomic samples when ≥20% genotypes of individual samples are available. When SMAP was applied to a large-scale dataset generated by the PsychENCODE BrainGVEX project, 54 samples (19%) were corrected. The correction was further confirmed by ribosome profiling and chromatin sequencing (ATAC-seq) data from the same set of samples. Our results demonstrate that SMAP is an effective tool for sample verification in a large-scale MS-based proteogenomics study. SMAP is publicly available at https://github.com/UND-Wanglab/SMAP, and a web-based version can be accessed at https://smap.shinyapps.io/smap/.

Sample mix-up is a potential problem in large-scale omic studies due to the complexity of sample processing. Here, the authors present a pipeline for sample matching in proteogenomics to verify sample identity and ensure data integrity.

Genetic architecture of protein expression and its regulation in the mouse brain

BACKGROUND

Natural variation in protein expression is common in all organisms and contributes to phenotypic differences among individuals. While variation in gene expression at the transcript level has been extensively investigated, the genetic mechanisms underlying variation in protein expression have lagged considerably behind. Here we investigate genetic architecture of protein expression by profiling a deep mouse brain proteome of two inbred strains, C57BL/6 J (B6) and DBA/2 J (D2), and their reciprocal F1 hybrids using two-dimensional liquid chromatography coupled with tandem mass spectrometry (LC/LC-MS/MS) technology.

RESULTS

By comparing protein expression levels in the four mouse strains, we observed 329 statistically significant differentially expressed proteins between the two parental strains and characterized the genetic basis of protein expression. We further applied a proteogenomic approach to detect variant peptides and define protein allele-specific expression (pASE), identifying 33 variant peptides with cis-effects and 17 variant peptides showing trans-effects. Comparison of regulation at transcript and protein levels show a significant divergence.

CONCLUSIONS

The results provide a comprehensive analysis of genetic architecture of protein expression and the contribution of cis- and trans-acting regulatory differences to protein expression.

Genome and transcriptome evolve separately in recently hybridized Trichosporon fungi

Genome hybridization is an important evolutionary event that gives rise to species with novel capabilities. However, the merging of distinct genomes also brings together incompatible regulatory networks that must be resolved during the course of evolution. Understanding of the early stages of post-hybridization evolution is particularly important because changes in these stages have long-term evolutionary consequences. Here, via comparative transcriptomic analyses of two closely related, recently hybridized Trichosporon fungi, T. coremiiforme and T. ovoides, and three extant relatives, we show that early post-hybridization evolutionary processes occur separately at the gene sequence and gene expression levels but together contribute to the stabilization of hybrid genome and transcriptome. Our findings also highlight lineage-specific consequences of genome hybridization, revealing that the transcriptional regulatory dynamics in these hybrids responded completely differently to gene loss events: one involving both subgenomes and another that is strictly subgenome-specific.

Determining Allele-Specific Protein Expression (ASPE) Using a Novel Quantitative Concatamer Based Proteomics Method

Measuring allele-specific expression (ASE) is a powerful approach for identifying cis-regulatory genetic variants. Here, we developed a novel targeted proteomics method for the quantification of allele-specific protein expression (ASPE) based on scheduled parallel reaction monitoring (PRM) with a heavy stable isotope-labeled quantitative concatamer (QconCAT) internal protein standard. This strategy was applied to the determination of the ASPE of UGT2B15 in human livers using the common UGT2B15 nonsynonymous variant rs1902023 (i.e., Y85D) as the marker to differentiate expressions from the two alleles. The QconCAT standard contains both the wild-type tryptic peptide and the Y85D mutant peptide at a ratio of 1:1 to ensure accurate measurement of the ASPE of UGT2B15. The results from 18 UGT2B15 Y85D heterozygotes revealed that the ratios between the wild-type Y allele and the mutant D allele varied from 0.60 to 1.46, indicating the presence of cis-regulatory variants. In addition, we observed no significant correlations between the ASPE and mRNA ASE of UGT2B15, suggesting the involvement of different cis-acting variants in regulating the transcription and translation processes of the gene. This novel ASPE approach provides a powerful tool for capturing cis-genetic variants involved in post-transcription processes, an important yet understudied area of research.

Natural gene expression variation studies in yeast

The rise of sequence information across different yeast species and strains is driving an increasing number of studies in the emerging field of genomics to associate polymorphic variants, mRNA abundance and phenotypic differences between individuals. Here, we gathered evidence from recent studies covering several layers that define the genotype-phenotype gap, such as mRNA abundance, allele-specific expression and translation efficiency to demonstrate how genetic variants co-evolve and define an individual's genome. Moreover, we exposed several antecedents where inter- and intra-specific studies led to opposite conclusions, probably owing to genetic divergence. Future studies in this area will benefit from the access to a massive array of well-annotated genomes and new sequencing technologies, which will allow the fine breakdown of the complex layers that delineate the genotype-phenotype map. Copyright © 2016 John Wiley & Sons, Ltd.

Coordinated Evolution of Transcriptional and Post-Transcriptional Regulation for Mitochondrial Functions in Yeast Strains

Evolution of gene regulation has been proposed to play an important role in environmental adaptation. Exploring mechanisms underlying coordinated evolutionary changes at various levels of gene regulation could shed new light on how organism adapt in nature. In this study, we focused on regulatory differences between a laboratory Saccharomyces cerevisiae strain BY4742 and a pathogenic S. cerevisiae strain, YJM789. The two strains diverge in many features, including growth rate, morphology, high temperature tolerance, and pathogenicity. Our RNA-Seq and ribosomal footprint profiling data showed that gene expression differences are pervasive, and genes functioning in mitochondria are mostly divergent between the two strains at both transcriptional and translational levels. Combining functional genomics data from other yeast strains, we further demonstrated that significant divergence of expression for genes functioning in the electron transport chain (ETC) was likely caused by differential expression of a transcriptional factor, HAP4, and that post-transcriptional regulation mediated by an RNA-binding protein, PUF3, likely led to expression divergence for genes involved in mitochondrial translation. We also explored mito-nuclear interactions via mitochondrial DNA replacement between strains. Although the two mitochondrial genomes harbor substantial sequence divergence, neither growth nor gene expression were affected by mitochondrial DNA replacement in both fermentative and respiratory growth media, indicating compatible mitochondrial and nuclear genomes between these two strains in the tested conditions. Collectively, we used mitochondrial functions as an example to demonstrate for the first time that evolution at both transcriptional and post-transcriptional levels could lead to coordinated regulatory changes underlying strain specific functional variations.

Mitochondrial proteomics of the acetic acid - induced programmed cell death response in a highly tolerant Zygosaccharomyces bailii - derived hybrid strain

Very high concentrations of acetic acid at low pH induce programmed cell death (PCD) in both the experimental model Saccharomyces cerevisiae and in Zygosaccharomyces bailii, the latter being considered the most problematic acidic food spoilage yeast due to its remarkable intrinsic resistance to this food preservative. However, while the mechanisms underlying S. cerevisiae PCD induced by acetic acid have been previously examined, the corresponding molecular players remain largely unknown in Z. bailii. Also, the reason why acetic acid concentrations known to be necrotic for S. cerevisiae induce PCD with an apoptotic phenotype in Z. bailii remains to be elucidated. In this study, a 2-DE-based expression mitochondrial proteomic analysis was explored to obtain new insights into the mechanisms involved in PCD in the Z. bailii derived hybrid strain ISA1307. This allowed the quantitative assessment of expression of protein species derived from each of the parental strains, with special emphasis on the processes taking place in the mitochondria known to play a key role in acetic acid - induced PCD. A marked decrease in the content of proteins involved in mitochondrial metabolism, in particular, in respiratory metabolism (Cor1, Rip1, Lpd1, Lat1 and Pdb1), with a concomitant increase in the abundance of proteins involved in fermentation (Pdc1, Ald4, Dld3) was registered. Other differentially expressed identified proteins also suggest the involvement of the oxidative stress response, protein translation, amino acid and nucleotide metabolism, among other processes, in the PCD response. Overall, the results strengthen the emerging concept of the importance of metabolic regulation of yeast PCD.

Extensive allele-specific translational regulation in hybrid mice

Translational regulation is mediated through the interaction between diffusible trans-factors and cis-elements residing within mRNA transcripts. In contrast to extensively studied transcriptional regulation, cis-regulation on translation remains underexplored. Using deep sequencing-based transcriptome and polysome profiling, we globally profiled allele-specific translational efficiency for the first time in an F1 hybrid mouse. Out of 7,156 genes with reliable quantification of both alleles, we found 1,008 (14.1%) exhibiting significant allelic divergence in translational efficiency. Systematic analysis of sequence features of the genes with biased allelic translation revealed that local RNA secondary structure surrounding the start codon and proximal out-of-frame upstream AUGs could affect translational efficiency. Finally, we observed that the cis-effect was quantitatively comparable between transcriptional and translational regulation. Such effects in the two regulatory processes were more frequently compensatory, suggesting that the regulation at the two levels could be coordinated in maintaining robustness of protein expression.

A Systems Approach to Elucidate Heterosis of Protein Abundances in Yeast

Heterosis is a universal phenomenon that has major implications in evolution and is of tremendous agro-economic value. To study the molecular manifestations of heterosis and to find factors that maximize its strength, we implemented a large-scale proteomic experiment in yeast. We analyzed the inheritance of 1,396 proteins in 55 inter- and intraspecific hybrids obtained from Saccharomyces cerevisiae and S. uvarum that were grown in grape juice at two temperatures. We showed that the proportion of heterotic proteins was highly variable depending on the parental strain and on the temperature considered. For intraspecific hybrids, this proportion was higher at nonoptimal temperature. Unexpectedly, heterosis for protein abundance was strongly biased toward positive values in interspecific hybrids but not in intraspecific hybrids. Computer modeling showed that this observation could be accounted for by assuming concave relationships between protein abundances and their controlling factors, in line with the metabolic model of heterosis. These results point to nonlinear processes that could play a central role in heterosis.

Evolution of gene regulation during transcription and translation

Understanding how gene regulation evolves is a key area in the current evolutionary field. Gene regulation occurs at various levels. Previous work on the evolution of gene regulation has largely focused on gene transcription. In this study, we used a recently developed ribosomal footprint profiling method to investigate how gene regulation evolves at both the transcription (mRNA abundance) and translation (ribosomal density) levels. By constructing a hybrid between Saccharomyces cerevisiae (Scer) and Saccharomyces bayanus (Sbay), which diverged ∼20 Ma, and quantifying transcriptome and translatome in both parental strains and their hybrid, we showed that translation is much more conserved than transcription, mostly due to the buffering effect of translational regulation for the transcriptional divergence. More conservation in translation than transcription is also confirmed by the inheritance mode of transcription and translation between two species. Furthermore, cis and trans effects are widely involved in changes at both transcription and translation levels. Finally, our results showed that genes with certain functions and sequence features might employ specific modes for evolution at these two critical levels of gene regulation. Our results demonstrated that it is essential to investigate the evolution of gene regulation at various levels from different genetic backgrounds to obtain a complete picture of its evolutionary modes in nature.

Negative feedback buffers effects of regulatory variants

Mechanisms conferring robustness against regulatory variants have been controversial. Previous studies suggested widespread buffering of RNA misexpression on protein levels during translation. We do not find evidence that translational buffering is common. Instead, we find extensive buffering at the level of RNA expression, exerted through negative feedback regulation acting in trans, which reduces the effect of regulatory variants on gene expression. Our approach is based on a novel experimental design in which allelic differential expression in a yeast hybrid strain is compared to allelic differential expression in a pool of its spores. Allelic differential expression in the hybrid is due to cis-regulatory differences only. Instead, in the pool of spores allelic differential expression is not only due to cis-regulatory differences but also due to local trans effects that include negative feedback. We found that buffering through such local trans regulation is widespread, typically compensating for about 15% of cis-regulatory effects on individual genes. Negative feedback is stronger not only for essential genes, indicating its functional relevance, but also for genes with low to middle levels of expression, for which tight regulation matters most. We suggest that negative feedback is one mechanism of Waddington's canalization, facilitating the accumulation of genetic variants that might give selective advantage in different environments.

Methods of integrating data to uncover genotype-phenotype interactions

Recent technological advances have expanded the breadth of available omic data, from whole-genome sequencing data, to extensive transcriptomic, methylomic and metabolomic data. A key goal of analyses of these data is the identification of effective models that predict phenotypic traits and outcomes, elucidating important biomarkers and generating important insights into the genetic underpinnings of the heritability of complex traits. There is still a need for powerful and advanced analysis strategies to fully harness the utility of these comprehensive high-throughput data, identifying true associations and reducing the number of false associations. In this Review, we explore the emerging approaches for data integration - including meta-dimensional and multi-staged analyses - which aim to deepen our understanding of the role of genetics and genomics in complex outcomes. With the use and further development of these approaches, an improved understanding of the relationship between genomic variation and human phenotypes may be revealed.

Assembly of a phased diploid Candida albicans genome facilitates allele-specific measurements and provides a simple model for repeat and indel structure

Background

Candida albicans is a ubiquitous opportunistic fungal pathogen that afflicts immunocompromised human hosts. With rare and transient exceptions the yeast is diploid, yet despite its clinical relevance the respective sequences of its two homologous chromosomes have not been completely resolved.

Results

We construct a phased diploid genome assembly by deep sequencing a standard laboratory wild-type strain and a panel of strains homozygous for particular chromosomes. The assembly has 700-fold coverage on average, allowing extensive revision and expansion of the number of known SNPs and indels. This phased genome significantly enhances the sensitivity and specificity of allele-specific expression measurements by enabling pooling and cross-validation of signal across multiple polymorphic sites. Additionally, the diploid assembly reveals pervasive and unexpected patterns in allelic differences between homologous chromosomes. Firstly, we see striking clustering of indels, concentrated primarily in the repeat sequences in promoters. Secondly, both indels and their repeat-sequence substrate are enriched near replication origins. Finally, we reveal an intimate link between repeat sequences and indels, which argues that repeat length is under selective pressure for most eukaryotes. This connection is described by a concise one-parameter model that explains repeat-sequence abundance in C. albicans as a function of the indel rate, and provides a general framework to interpret repeat abundance in species ranging from bacteria to humans.

Conclusions

The phased genome assembly and insights into repeat plasticity will be valuable for better understanding allele-specific phenomena and genome evolution.

Genomic variation. Impact of regulatory variation from RNA to protein

The phenotypic consequences of expression quantitative trait loci (eQTLs) are presumably due to their effects on protein expression levels. Yet the impact of genetic variation, including eQTLs, on protein levels remains poorly understood. To address this, we mapped genetic variants that are associated with eQTLs, ribosome occupancy (rQTLs), or protein abundance (pQTLs). We found that most QTLs are associated with transcript expression levels, with consequent effects on ribosome and protein levels. However, eQTLs tend to have significantly reduced effect sizes on protein levels, which suggests that their potential impact on downstream phenotypes is often attenuated or buffered. Additionally, we identified a class of cis QTLs that affect protein abundance with little or no effect on messenger RNA or ribosome levels, which suggests that they may arise from differences in posttranslational regulation.

Decoding neuroproteomics: integrating the genome, translatome and functional anatomy

The immense intercellular and intracellular heterogeneity of the CNS presents major challenges for high-throughput omic analyses. Transcriptional, translational and post-translational regulatory events are localized to specific neuronal cell types or subcellular compartments, resulting in discrete patterns of protein expression and activity. A spatial and quantitative knowledge of the neuroproteome is therefore critical to understanding both normal and pathological aspects of the functional genomics and anatomy of the CNS. Improvements in mass spectrometry allow the profiling of proteins at a sufficient depth to complement results from high-throughput genomic and transcriptomic assays. However, there are challenges in integrating proteomic data with other data modalities and even greater challenges in obtaining comprehensive neuroproteomic data with cell-type specificity. Here we discuss how proteomics should be exploited to enhance high-throughput functional genomic analysis by tighter integration of data analyses. We also discuss experimental strategies to achieve finer cellular and subcellular resolution in transcriptomic and proteomic studies of neural tissues.

Extensive and coordinated control of allele-specific expression by both transcription and translation in Candida albicans

Though sequence differences between alleles are often limited to a few polymorphisms, these differences can cause large and widespread allelic variation at the expression level. Such allele-specific expression (ASE) has been extensively explored at the level of transcription but not translation. Here we measured ASE in the diploid yeast Candida albicans at both the transcriptional and translational levels using RNA-seq and ribosome profiling, respectively. Since C. albicans is an obligate diploid, our analysis isolates ASE arising from cis elements in a natural, nonhybrid organism, where allelic effects reflect evolutionary forces. Importantly, we find that ASE arising from translation is of a similar magnitude as transcriptional ASE, both in terms of the number of genes affected and the magnitude of the bias. We further observe coordination between ASE at the levels of transcription and translation for single genes. Specifically, reinforcing relationships—where transcription and translation favor the same allele—are more frequent than expected by chance, consistent with selective pressure tuning ASE at multiple regulatory steps. Finally, we parameterize alleles based on a range of properties and find that SNP location and predicted mRNA-structure stability are associated with translational ASE in cis. Since this analysis probes more than 4000 allelic pairs spanning a broad range of variations, our data provide a genome-wide view into the relative impact of cis elements that regulate translation.

Ribosome profiling reveals post-transcriptional buffering of divergent gene expression in yeast

Understanding the patterns and causes of phenotypic divergence is a central goal in evolutionary biology. Much work has shown that mRNA abundance is highly variable between closely related species. However, the extent and mechanisms of post-transcriptional gene regulatory evolution are largely unknown. Here we used ribosome profiling to compare transcript abundance and translation efficiency in two closely related yeast species (S. cerevisiae and S. paradoxus). By comparing translation regulatory divergence to interspecies differences in mRNA sequence features, we show that differences in transcript leaders and codon bias substantially contribute to divergent translation. Globally, we find that translation regulatory divergence often buffers species differences in mRNA abundance, such that ribosome occupancy is more conserved than transcript abundance. We used allele-specific ribosome profiling in interspecies hybrids to compare the relative contributions of cis- and trans-regulatory divergence to species differences in mRNA abundance and translation efficiency. The mode of gene regulatory divergence differs for these processes, as trans-regulatory changes play a greater role in divergent mRNA abundance than in divergent translation efficiency. Strikingly, most genes with aberrant transcript abundance in F1 hybrids (either over- or underexpressed compared to both parent species) did not exhibit aberrant ribosome occupancy. Our results show that interspecies differences in translation contribute substantially to the evolution of gene expression. Compensatory differences in transcript abundance and translation efficiency may increase the robustness of gene regulation.

Extensive translational regulation of gene expression in an allopolyploid (Glycine dolichocarpa)

All flowering plants have experienced repeated rounds of polyploidy (whole-genome duplication), which has in turn driven the evolution of novel phenotypes and ecological tolerances and been a major driver of speciation. The effects of polyploidy on gene expression have been studied extensively at the level of transcription and, to a much lesser extent, at the level of the steady state proteome, but not at the level of translation. We used polysome profiling by RNA-Seq to quantify translational regulation of gene expression in a recently formed (∼100,000 years ago) allotetraploid (Glycine dolichocarpa) closely related to the cultivated soybean (Glycine max). We show that there is a high level of concordance between the allopolyploid transcriptome and translatome overall but that at least one-quarter of the transcriptome is translationally regulated. We further show that translational regulation preferentially targets genes involved in transcription, translation, and photosynthesis, causes regional and possibly whole-chromosome shifts in expression bias between duplicated genes (homoeologs), and reduces transcriptional differences between the polyploid and its diploid progenitors, possibly attenuating misregulation resulting from genome merger and/or doubling. Finally, translational regulation correlates positively with long-term retention of homoeologs from a paleopolyploidy event, suggesting that it plays a significant role in polyploid evolution.

Evolution at two levels of gene expression in yeast

Despite the greater functional importance of protein levels, our knowledge of gene expression evolution is based almost entirely on studies of mRNA levels. In contrast, our understanding of how translational regulation evolves has lagged far behind. Here we have applied ribosome profiling—which measures both global mRNA levels and their translation rates—to two species of Saccharomyces yeast and their interspecific hybrid in order to assess the relative contributions of changes in mRNA abundance and translation to regulatory evolution. We report that both cis- and trans-acting regulatory divergence in translation are abundant, affecting at least 35% of genes. The majority of translational divergence acts to buffer changes in mRNA abundance, suggesting a widespread role for stabilizing selection acting across regulatory levels. Nevertheless, we observe evidence of lineage-specific selection acting on several yeast functional modules, including instances of reinforcing selection acting at both levels of regulation. Finally, we also uncover multiple instances of stop-codon readthrough that are conserved between species. Our analysis reveals the underappreciated complexity of post-transcriptional regulatory divergence and indicates that partitioning the search for the locus of selection into the binary categories of “coding” versus “regulatory” may overlook a significant source of selection, acting at multiple regulatory levels along the path from genotype to phenotype.

Large-scale mass spectrometric detection of variant peptides resulting from nonsynonymous nucleotide differences

Each individual carries thousands of nonsynonymous single nucleotide variants (nsSNVs) in their genome, each corresponding to a single amino acid polymorphism (SAP) in the encoded proteins. It is important to be able to directly detect and quantify these variations at the protein level to study post-transcriptional regulation, differential allelic expression, and other important biological processes. However, such variant peptides are not generally detected in standard proteomic analyses due to their absence from the generic databases that are employed for mass spectrometry searching. Here we extend previous work that demonstrated the use of customized SAP databases constructed from sample-matched RNA-Seq data. We collected deep-coverage RNA-Seq data from the Jurkat cell line, compiled the set of nsSNVs that are expressed, used this information to construct a customized SAP database, and searched it against deep-coverage shotgun MS data obtained from the same sample. This approach enabled the detection of 421 SAP peptides mapping to 395 nsSNVs. We compared these peptides to peptides identified from a large generic search database containing all known nsSNVs (dbSNP) and found that more than 70% of the SAP peptides from this dbSNP-derived search were not supported by the RNA-Seq data and thus are likely false positives. Next, we increased the SAP coverage from the RNA-Seq derived database by utilizing multiple protease digestions, thereby increasing variant detection to 695 SAP peptides mapping to 504 nsSNV sites. These detected SAP peptides corresponded to moderate to high abundance transcripts (30+ transcripts per million, TPM). The SAP peptides included 192 allelic pairs; the relative expression levels of the two alleles were evaluated for 51 of those pairs and were found to be comparable in all cases.

A new system for comparative functional genomics of Saccharomyces yeasts

Whole-genome sequencing, particularly in fungi, has progressed at a tremendous rate. More difficult, however, is experimental testing of the inferences about gene function that can be drawn from comparative sequence analysis alone. We present a genome-wide functional characterization of a sequenced but experimentally understudied budding yeast, Saccharomyces bayanus var. uvarum (henceforth referred to as S. bayanus), allowing us to map changes over the 20 million years that separate this organism from S. cerevisiae. We first created a suite of genetic tools to facilitate work in S. bayanus. Next, we measured the gene-expression response of S. bayanus to a diverse set of perturbations optimized using a computational approach to cover a diverse array of functionally relevant biological responses. The resulting data set reveals that gene-expression patterns are largely conserved, but significant changes may exist in regulatory networks such as carbohydrate utilization and meiosis. In addition to regulatory changes, our approach identified gene functions that have diverged. The functions of genes in core pathways are highly conserved, but we observed many changes in which genes are involved in osmotic stress, peroxisome biogenesis, and autophagy. A surprising number of genes specific to S. bayanus respond to oxidative stress, suggesting the organism may have evolved under different selection pressures than S. cerevisiae. This work expands the scope of genome-scale evolutionary studies from sequence-based analysis to rapid experimental characterization and could be adopted for functional mapping in any lineage of interest. Furthermore, our detailed characterization of S. bayanus provides a valuable resource for comparative functional genomics studies in yeast.

Inheritance of gene expression level and selective constraints on trans- and cis-regulatory changes in yeast

Gene expression evolution can be caused by changes in cis- or trans-regulatory elements or both. As cis and trans regulation operate through different molecular mechanisms, cis and trans mutations may show different inheritance patterns and may be subjected to different selective constraints. To investigate these issues, we obtained and analyzed gene expression data from two Saccharomyces cerevisiae strains and their hybrid, using high-throughput sequencing. Our data indicate that compared with other types of genes, those with antagonistic cis-trans interactions are more likely to exhibit over- or underdominant inheritance of expression level. Moreover, in accordance with previous studies, genes with trans variants tend to have a dominant inheritance pattern, whereas cis variants are enriched for additive inheritance. In addition, cis regulatory differences contribute more to expression differences between species than within species, whereas trans regulatory differences show a stronger association between divergence and polymorphism. Our data indicate that in the trans component of gene expression differences genes subjected to weaker selective constraints tend to have an excess of polymorphism over divergence compared with those subjected to stronger selective constraints. In contrast, in the cis component, this difference between genes under stronger and weaker selective constraint is mostly absent. To explain these observations, we propose that purifying selection more strongly shapes trans changes than cis changes and that positive selection may have significantly contributed to cis regulatory divergence.

Global properties and functional complexity of human gene regulatory variation

Identification and functional interpretation of gene regulatory variants is a major focus of modern genomics. The application of genetic mapping to molecular and cellular traits has enabled the detection of regulatory variation on genome-wide scales and revealed an enormous diversity of regulatory architecture in humans and other species. In this review I summarise the insights gained and questions raised by a decade of genetic mapping of gene expression variation. I discuss recent extensions of this approach using alternative molecular phenotypes that have revealed some of the biological mechanisms that drive gene expression variation between individuals. Finally, I highlight outstanding problems and future directions for development.

Research progress in allele-specific expression and its regulatory mechanisms

Although the majority of genes are expressed equally from both alleles, some genes are differentially expressed. Organisms possess characteristics to preferentially express a particular allele under regulatory factors, which is termed allele-specific expression (ASE). It is one of the important genetic factors that lead to phenotypic variation and can be used to identify the variance of gene regulation factors. ASE indicates mechanisms such as DNA methylation, histone modifications, and non-coding RNAs function. Here, we review a broad survey of progress in ASE studies, and what this simple yet very effective approach can offer in functional genomics, and possible implications toward our better understanding of the underlying mechanisms of complex traits.