Gene expression is regulated both by cis elements, which are DNA segments closely linked to the genes they regulate, and by trans factors, which are usually proteins capable of diffusing to unlinked genes. Understanding the patterns and sources of regulatory variation is crucial for understanding phenotypic and genome evolution. Here, we measure genome-wide allele-specific expression by deep sequencing to investigate the patterns of cis and trans expression variation between two strains of Saccharomyces cerevisiae. We propose a statistical modeling framework based on the binomial distribution that simultaneously addresses normalization of read counts derived from different parents and estimating the cis and trans expression variation parameters. We find that expression polymorphism in yeast is common for both cis and trans, though trans variation is more common. Constraint in expression evolution is correlated with other hallmarks of constraint, including gene essentiality, number of protein interaction partners, and constraint in amino acid substitution, indicating that both cis and trans polymorphism are clearly under purifying selection, though trans variation appears to be more sensitive to selective constraint. Comparing interspecific expression divergence between S. cerevisiae and S. paradoxus to our intraspecific variation suggests a significant departure from a neutral model of molecular evolution. A further examination of correlation between polymorphism and divergence within each category suggests that cis divergence is more frequently mediated by positive Darwinian selection than is trans divergence.

To study the regulatory and functional differentiation between the mesophyll (M) and bundle sheath (BS) cells of maize (Zea mays), we isolated large quantities of highly homogeneous M and BS cells from newly matured second leaves for transcriptome profiling by RNA sequencing. A total of 52,421 annotated genes with at least one read were found in the two transcriptomes. Defining a gene with more than one read per kilobase per million mapped reads as expressed, we identified 18,482 expressed genes; 14,972 were expressed in M cells, including 53 M-enriched transcription factor (TF) genes, whereas 17,269 were expressed in BS cells, including 214 BS-enriched TF genes. Interestingly, many TF gene families show a conspicuous BS preference in expression. Pathway analyses reveal differentiation between the two cell types in various functional categories, with the M cells playing more important roles in light reaction, protein synthesis and folding, tetrapyrrole synthesis, and RNA binding, while the BS cells specialize in transport, signaling, protein degradation and posttranslational modification, major carbon, hydrogen, and oxygen metabolism, cell division and organization, and development. Genes coding for several transporters involved in the shuttle of C₄ metabolites and BS cell wall development have been identified, to our knowledge, for the first time. This comprehensive data set will be useful for studying M/BS differentiation in regulation and function.

Time-series transcriptomes of a biological process obtained under different conditions are useful for identifying the regulators of the process and their regulatory networks. However, such data are 3D (gene expression, time, and condition), and there is currently no method that can deal with their full complexity. Here, we developed a method that avoids time-point alignment and normalization between conditions. We applied it to analyze time-series transcriptomes of developing maize leaves under light–dark cycles and under total darkness and obtained eight time-ordered gene coexpression networks (TO-GCNs), which can be used to predict upstream regulators of any genes in the GCNs. One of the eight TO-GCNs is light-independent and likely includes all genes involved in the development of Kranz anatomy, which is a structure crucial for the high efficiency of photosynthesis in C₄plants. Using this TO-GCN, we predicted and experimentally validated a regulatory cascade upstream ofSHORTROOT1, a key Kranz anatomy regulator. Moreover, we applied the method to compare transcriptomes from maize and rice leaf segments and identified regulators of maize C₄enzyme genes andRUBISCO SMALL SUBUNIT2. Our study provides not only a powerful method but also novel insights into the regulatory networks underlying Kranz anatomy development and C₄photosynthesis.

Thermotolerance is a polygenic trait that contributes to cell survival and growth under unusually high temperatures. Although some genes associated with high temperature growth (Htg⁺) have been identified, how cells accumulate mutations to achieve prolonged thermotolerance is still mysterious. Here we conducted experimental evolution of a Saccharomyces cerevisiae laboratory strain with stepwise temperature increases for it to grow at 42 °C. Whole genome resequencing of 14 evolved strains and the parental strain revealed a total of 153 mutations in the evolved strains, including single nucleotide variants, small INDELs, and segmental duplication/deletion events. Some mutations persisted from an intermediate temperature to 42 °C, so they might be Htg⁺ mutations. Functional categorization of mutations revealed enrichment of exonic mutations in the SWI/SNF complex and F-type ATPase, pointing to their involvement in high temperature tolerance. In addition, multiple mutations were found in a general stress associated signal transduction network consisting of Hog1 mediated pathway, RAS-cAMP pathway, and Rho1-Pkc1 mediated cell wall integrity pathway, implying that cells can achieve Htg⁺ partly through modifying existing stress regulatory mechanisms. Using pooled segregant analysis of 5 Htg⁺ phenotype-orientated pools, we inferred causative mutations for growth at 42 °C and identified those mutations with stronger impacts on the phenotype. Finally, we experimentally validated a number of the candidate Htg⁺ mutations. This study increased our understanding of the genetic basis of yeast tolerance to high temperature.

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.

Gut dysbiosis plays a role in hepatic encephalopathy (HE), while its relationship at the acute episode of overt HE (AHE), the disease progression and clinical outcomes remains unclear. We aimed to identify AHE-specific microbiome and its association to patients' outcomes. We profiled fecal microbiome changes for a cohort of 62 patients with cirrhosis and AHE i) before treatment, ii) 2-3 days after medication and iii) 2-3 months after recovery, and three control cohorts i) healthy individuals, patients with ii) compensated or iii) decompensated cirrhosis. Comparison of the microbiome shift from compensated, decompensated cirrhosis, AHE to recovery revealed the AHE-specific gut-dysbiosis. The gut microbiome diversity was decreased during AHE, further reduced after medication, and only partially reversed during the recovery. The relative abundance of Bacteroidetes phylum in the microbiome decreased, whereas that of Firmicute, Proteobacteria and Actinobacteria increased in patients during AHE compared with those with compensated cirrhosis. A total of 70 operational taxonomic units (OTUs) were significantly different between AHE and decompensated cirrhosis abundances. Of them, the abundance of Veillonella parvula increased the most during AHE via a metagenomics recovery of the genomes. Moreover, the relative abundances of three (Alistipes, Bacteroides, Phascolarctobacterium) and five OTUs (Clostridium-XI, Bacteroides, Bacteroides, Lactobacillus, Clostridium-sedis) at AHE were respectively associated with HE recurrence and overall survival during the subsequent one-year follow-up. AHE-specific gut OTUs were identified that may be involved in HE development and able to predict clinical outcomes, providing new strategies for the prevention and treatment of HE recurrence in patients with cirrhosis.