BackgroundAcetic acid is one of the major inhibitors in lignocellulose hydrolysates used for the production of second-generation bioethanol. Although several genes have been identified in laboratory yeast strains that are required for tolerance to acetic acid, the genetic basis of the high acetic acid tolerance naturally present in some Saccharomyces cerevisiae strains is unknown. Identification of its polygenic basis may allow improvement of acetic acid tolerance in yeast strains used for second-generation bioethanol production by precise genome editing, minimizing the risk of negatively affecting other industrially important properties of the yeast.ResultsHaploid segregants of a strain with unusually high acetic acid tolerance and a reference industrial strain were used as superior and inferior parent strain, respectively. After crossing of the parent strains, QTL mapping using the SNP variant frequency determined by pooled-segregant whole-genome sequence analysis revealed two major QTLs. All F1 segregants were then submitted to multiple rounds of random inbreeding and the superior F7 segregants were submitted to the same analysis, further refined by sequencing of individual segregants and bioinformatics analysis taking into account the relative acetic acid tolerance of the segregants. This resulted in disappearance in the QTL mapping with the F7 segregants of a major F1 QTL, in which we identified HAA1, a known regulator of high acetic acid tolerance, as a true causative allele. Novel genes determining high acetic acid tolerance, GLO1, DOT5, CUP2, and a previously identified component, VMA7, were identified as causative alleles in the second major F1 QTL and in three newly appearing F7 QTLs, respectively. The superior HAA1 allele contained a unique single point mutation that significantly improved acetic acid tolerance under industrially relevant conditions when inserted into an industrial yeast strain for second-generation bioethanol production.ConclusionsThis work reveals the polygenic basis of high acetic acid tolerance in S. cerevisiae in unprecedented detail. It also shows for the first time that a single strain can harbor different sets of causative genes able to establish the same polygenic trait. The superior alleles identified can be used successfully for improvement of acetic acid tolerance in industrial yeast strains.

Molecular domestications of transposable elements have occurred repeatedly during the evolution of eukaryotes. Vertebrates, especially mammals, possess numerous single copy domesticated genes (DGs) that have originated from the intronless multicopy transposable elements. However, the origin and evolution of the retroelement-derived DGs (RDDGs) that originated from Metaviridae has been only partially elucidated, due to absence of genome data or to limited analysis of a single family of DGs. We traced the genesis and regulatory wiring of the Metaviridae-derived DGs through phylogenomic analysis, using whole-genome information from more than 90 chordate genomes. Phylogenomic analysis of these DGs in chordate genomes provided direct evidence that major diversification has occurred in the ancestor of placental mammals. Mammalian RDDGs have been shown to originate in several steps by independent domestication events and to diversify later by gene duplications. Analysis of syntenic loci has shown that diverse RDDGs and their chromosomal positions were fully established in the ancestor of placental mammals. By analysis of active Metaviridae lineages in amniotes, we have demonstrated that RDDGs originated from retroelement remains. The chromosomal gene movements of RDDGs were highly dynamic only in the ancestor of placental mammals. During the domestication process, de novo acquisition of regulatory regions is shown to be a prerequisite for the survival of the DGs. The origin and evolution of de novo acquired promoters and untranslated regions in diverse mammalian RDDGs have been explained by comparative analysis of orthologous gene loci. The origin of placental mammal-specific innovations and adaptations, such as placenta and newly evolved brain functions, was most probably connected to the regulatory wiring of DGs and their rapid fixation in the ancestor of placental mammals.

The yeast pathogen Candida glabrata is the second most frequent cause of Candida infections. However, from the phylogenetic point of view, C. glabrata is much closer to Saccharomyces cerevisiae than to Candida albicans. Apparently, this yeast has relatively recently changed its life style and become a successful opportunistic pathogen. Recently, several C. glabrata sister species, among them clinical and environmental isolates, have had their genomes characterized. Also, hundreds of C. glabrata clinical isolates have been characterized for their genomes. These isolates display enormous genomic plasticity. The number and size of chromosomes vary drastically, as well as intra- and interchromosomal segmental duplications occur frequently. The observed genome alterations could affect phenotypic properties and thus help to adapt to the highly variable and harsh habitats this yeast finds in different human patients and their tissues. Further genome sequencing of pathogenic isolates will provide a valuable tool to understand the mechanisms behind genome dynamics and help to elucidate the genes contributing to the virulence potential.

Background Dictyostelium discoideum, a soil-dwelling social amoeba, is a model for the study of numerous biological processes. Research in the field has benefited mightily from the adoption of next-generation sequencing for genomics and transcriptomics. Dictyostelium biologists now face the widespread challenges of analyzing and exploring high dimensional data sets to generate hypotheses and discovering novel insights.ResultsWe present dictyExpress (2.0), a web application designed for exploratory analysis of gene expression data, as well as data from related experiments such as Chromatin Immunoprecipitation sequencing (ChIP-Seq). The application features visualization modules that include time course expression profiles, clustering, gene ontology enrichment analysis, differential expression analysis and comparison of experiments. All visualizations are interactive and interconnected, such that the selection of genes in one module propagates instantly to visualizations in other modules. dictyExpress currently stores the data from over 800 Dictyostelium experiments and is embedded within a general-purpose software framework for management of next-generation sequencing data. dictyExpress allows users to explore their data in a broader context by reciprocal linking with dictyBase—a repository of Dictyostelium genomic data. In addition, we introduce a companion application called GenBoard, an intuitive graphic user interface for data management and bioinformatics analysis.ConclusionsdictyExpress and GenBoard enable broad adoption of next generation sequencing based inquiries by the Dictyostelium research community. Labs without the means to undertake deep sequencing projects can mine the data available to the public. The entire information flow, from raw sequence data to hypothesis testing, can be accomplished in an efficient workspace. The software framework is generalizable and represents a useful approach for any research community. To encourage more wide usage, the backend is open-source, available for extension and further development by bioinformaticians and data scientists.

Dictyostelium discoideum live in the soil as single cells, engulfing bacteria and growing vegetatively. Upon starvation, tens of thousands of amoebae enter a developmental program that includes aggregation, multicellular differentiation, and sporulation. Major shifts across the protein-coding transcriptome accompany these developmental changes. However, no study has presented a global survey of long noncoding RNAs (ncRNAs) in D. discoideum. To characterize the antisense and long intergenic noncoding RNA (lncRNA) transcriptome, we analyzed previously published developmental time course samples using an RNA-sequencing (RNA-seq) library preparation method that selectively depletes ribosomal RNAs (rRNAs). We detected the accumulation of transcripts for 9833 protein-coding messenger RNAs (mRNAs), 621 lncRNAs, and 162 putative antisense RNAs (asRNAs). The noncoding RNAs were interspersed throughout the genome, and were distinct in expression level, length, and nucleotide composition. The noncoding transcriptome displayed a temporal profile similar to the coding transcriptome, with stages of gradual change interspersed with larger leaps. The transcription profiles of some noncoding RNAs were strongly correlated with known differentially expressed coding RNAs, hinting at a functional role for these molecules during development. Examining the mitochondrial transcriptome, we modeled two novel antisense transcripts. We applied yet another ribosomal depletion method to a subset of the samples to better retain transfer RNA (tRNA) transcripts. We observed polymorphisms in tRNA anticodons that suggested a post-transcriptional means by which D. discoideum compensates for codons missing in the genomic complement of tRNAs. We concluded that the prevalence and characteristics of long ncRNAs indicate that these molecules are relevant to the progression of molecular and cellular phenotypes during development.