Transcriptional Analysis of Total CD8+ T Cells and CD8+CD45RA- Memory T Cells From Young and Old Healthy Blood Donors.

Memory CD8+ T cells accumulate with aging, while the naïve T cell compartment decreases, leading to an increased susceptibility to infections and a decreased vaccine efficiency. To get deeper insights into the underlying mechanisms, this study aims to determine the age-dependent expression profile of total versus memory CD8+ T cells from young and old donors. Total CD8+ and CD8+CD45RA- memory T cells isolated from young (<30 years) and old (>60 years) donors were stimulated with anti-CD3 and anti-CD28 antibodies for 48h before analyzing the cytokine secretion and activation markers by flow cytometry and changes in the expression profiles using RNA sequencing. Gene ontology (GO) term enrichment analyses were performed for up-regulated and uniquely expressed transcripts identified in the T cell populations of both age groups. Total and memory CD8+ T cells from old donors expressed significantly higher CD25 levels and have an increased cytokine secretion. While approximately 1,500 up-regulated transcripts were identified in all groups, CD8+CD45RA- memory T cells of old donors had approximately 500 more uniquely expressed transcripts. Four GO terms related to the JAK-STAT pathway were identified for up-regulated transcripts in the total CD8+ T cells of old donors, whereas CD8+CD45RA- memory T cells GO terms related to adjacent pathways, like JNK and MAPK/ERK, were found. Additionally, the unique transcripts of CD8+CD45RA- memory T cells of old donors were related to the JNK, MAPK and IL-12 pathways. For both T cell populations of the old donors, cytokine and JAK-STAT pathway transcripts were up-regulated. Thus, an age-dependent effect was observed on the transcriptomes of total and memory CD8+ T cells. The CD8+ CD45RA- memory T cells from old donors maintained the increased cytokine secretion of the total CD8+ T cell population and the increased JAK-STAT pathway transcripts, which have an impact on inflammation and senescence.

Performance of Mapping Approaches for Whole-Genome Bisulfite Sequencing Data in Crop Plants.

DNA methylation is involved in many different biological processes in the development and well-being of crop plants such as transposon activation, heterosis, environment-dependent transcriptome plasticity, aging, and many diseases. Whole-genome bisulfite sequencing is an excellent technology for detecting and quantifying DNA methylation patterns in a wide variety of species, but optimized data analysis pipelines exist only for a small number of species and are missing for many important crop plants. This is especially important as most existing benchmark studies have been performed on mammals with hardly any repetitive elements and without CHG and CHH methylation. Pipelines for the analysis of whole-genome bisulfite sequencing data usually consists of four steps: read trimming, read mapping, quantification of methylation levels, and prediction of differentially methylated regions (DMRs). Here we focus on read mapping, which is challenging because un-methylated cytosines are transformed to uracil during bisulfite treatment and to thymine during the subsequent polymerase chain reaction, and read mappers must be capable of dealing with this cytosine/thymine polymorphism. Several read mappers have been developed over the last years, with different strengths and weaknesses, but their performances have not been critically evaluated. Here, we compare eight read mappers: Bismark, BismarkBwt2, BSMAP, BS-Seeker2, Bwameth, GEM3, Segemehl, and GSNAP to assess the impact of the read-mapping results on the prediction of DMRs. We used simulated data generated from the genomes of Arabidopsis thaliana, Brassica napus, Glycine max, Solanum tuberosum, and Zea mays, monitored the effects of the bisulfite conversion rate, the sequencing error rate, the maximum number of allowed mismatches, as well as the genome structure and size, and calculated precision, number of uniquely mapped reads, distribution of the mapped reads, run time, and memory consumption as features for benchmarking the eight read mappers mentioned above. Furthermore, we validated our findings using real-world data of Glycine max and showed the influence of the mapping step on DMR calling in WGBS pipelines. We found that the conversion rate had only a minor impact on the mapping quality and the number of uniquely mapped reads, whereas the error rate and the maximum number of allowed mismatches had a strong impact and leads to differences of the performance of the eight read mappers. In conclusion, we recommend BSMAP which needs the shortest run time and yields the highest precision, and Bismark which requires the smallest amount of memory and yields precision and high numbers of uniquely mapped reads.

Allele specific chromatin signals, 3D interactions, and motif predictions for immune and B cell related diseases.

Several Genome Wide Association Studies (GWAS) have reported variants associated to immune diseases. However, the identified variants are rarely the drivers of the associations and the molecular mechanisms behind the genetic contributions remain poorly understood. ChIP-seq data for TFs and histone modifications provide snapshots of protein-DNA interactions allowing the identification of heterozygous SNPs showing significant allele specific signals (AS-SNPs). AS-SNPs can change a TF binding site resulting in altered gene regulation and are primary candidates to explain associations observed in GWAS and expression studies. We identified 17,293 unique AS-SNPs across 7 lymphoblastoid cell lines. In this set of cell lines we interrogated 85% of common genetic variants in the population for potential regulatory effect and we identified 237 AS-SNPs associated to immune GWAS traits and 714 to gene expression in B cells. To elucidate possible regulatory mechanisms we integrated long-range 3D interactions data to identify putative target genes and motif predictions to identify TFs whose binding may be affected by AS-SNPs yielding a collection of 173 AS-SNPs associated to gene expression and 60 to B cell related traits. We present a systems strategy to find functional gene regulatory variants, the TFs that bind differentially between alleles and novel strategies to detect the regulated genes.

Optimal Block-Based Trimming for Next Generation Sequencing.

Read trimming is a fundamental first step of the analysis of next generation sequencing (NGS) data. Traditionally, it is performed heuristically, and algorithmic work in this area has been neglected. Here, we address this topic and formulate three optimization problems for block-based trimming (truncating the same low-quality positions at both ends for all reads and removing low-quality truncated reads). We find that all problems are NP-hard. Hence, we investigate the approximability of the problems. Two of them are NP-hard to approximate. However, the non-random distribution of quality scores in NGS data sets makes it tempting to speculate that quality constraints for read positions are typically satisfied by fulfilling quality constraints for reads. Thus, we propose three relaxed problems and develop efficient polynomial-time algorithms for them including heuristic speed-up techniques and parallelizations. We apply these optimized block trimming algorithms to 12 data sets from three species, four sequencers, and read lengths ranging from 36 to 101 bp and find that (i) the omitted constraints are indeed almost always satisfied, (ii) the optimized read trimming algorithms typically yield a higher number of untrimmed bases than traditional heuristics, and (iii) these results can be generalized to alternative objective functions beyond counting the number of untrimmed bases.

A Detailed Analysis of the BR1 Locus Suggests a New Mechanism for Bolting after Winter in Sugar Beet (Beta vulgaris L.).

Sugar beet (Beta vulgaris ssp. vulgaris) is a biennial, sucrose-storing plant, which is mainly cultivated as a spring crop and harvested in the vegetative stage before winter. For increasing beet yield, over-winter cultivation would be advantageous. However, bolting is induced after winter and drastically reduces yield. Thus, post-winter bolting control is essential for winter beet cultivation. To identify genetic factors controlling bolting after winter, a F2 population was previously developed by crossing the sugar beet accessions BETA 1773 with reduced bolting tendency and 93161P with complete bolting after winter. For a mapping-by-sequencing analysis, pools of 26 bolting-resistant and 297 bolting F2 plants were used. Thereby, a single continuous homozygous region of 103 kb was co-localized to the previously published BR1 QTL for post-winter bolting resistance (Pfeiffer et al., 2014). The BR1 locus was narrowed down to 11 candidate genes from which a homolog of the Arabidopsis CLEAVAGE AND POLYADENYLATION SPECIFICITY FACTOR 73-I (CPSF73-I) was identified as the most promising candidate. A 2 bp deletion within the BETA 1773 allele of BvCPSF73-Ia results in a truncated protein. However, the null allele of BvCPSF73-Ia might partially be compensated by a second BvCPSF73-Ib gene. This gene is located 954 bp upstream of BvCPSF73-Ia and could be responsible for the incomplete penetrance of the post-winter bolting resistance allele of BETA 1773. This result is an important milestone for breeding winter beets with complete bolting resistance after winter.

Divergent Evolution of the Transcriptional Network Controlled by Snf1-Interacting Protein Sip4 in Budding Yeasts.

Cellular responses to starvation are of ancient origin since nutrient limitation has always been a common challenge to the stability of living systems. Hence, signaling molecules involved in sensing or transducing information about limiting metabolites are highly conserved, whereas transcription factors and the genes they regulate have diverged. In eukaryotes the AMP-activated protein kinase (AMPK) functions as a central regulator of cellular energy homeostasis. The yeast AMPK ortholog SNF1 controls the transcriptional network that counteracts carbon starvation conditions by regulating a set of transcription factors. Among those Cat8 and Sip4 have overlapping DNA-binding specificity for so-called carbon source responsive elements and induce target genes upon SNF1 activation. To analyze the evolution of the Cat8-Sip4 controlled transcriptional network we have compared the response to carbon limitation of Saccharomyces cerevisiae to that of Kluyveromyces lactis. In high glucose, S. cerevisiae displays tumor cell-like aerobic fermentation and repression of respiration (Crabtree-positive) while K. lactis has a respiratory-fermentative life-style, respiration being regulated by oxygen availability (Crabtree-negative), which is typical for many yeasts and for differentiated higher cells. We demonstrate divergent evolution of the Cat8-Sip4 network and present evidence that a role of Sip4 in controlling anabolic metabolism has been lost in the Saccharomyces lineage. We find that in K. lactis, but not in S. cerevisiae, the Sip4 protein plays an essential role in C2 carbon assimilation including induction of the glyoxylate cycle and the carnitine shuttle genes. Induction of KlSIP4 gene expression by KlCat8 is essential under these growth conditions and a primary function of KlCat8. Both KlCat8 and KlSip4 are involved in the regulation of lactose metabolism in K. lactis. In chromatin-immunoprecipitation experiments we demonstrate binding of both, KlSip4 and KlCat8, to selected CSREs and provide evidence that KlSip4 counteracts KlCat8-mediated transcription activation by competing for binding to some but not all CSREs. The finding that the hierarchical relationship of these transcription factors differs between K. lactis and S. cerevisiae and that the sets of target genes have diverged contributes to explaining the phenotypic differences in metabolic life-style.

Genetic analysis of bolting after winter in sugar beet (Beta vulgaris L.).

KEY MESSAGE: This study reveals for the first time a major QTL for post-winter bolting resistance in sugar beet ( Beta vulgaris L.). The knowledge of this QTL is a major contribution towards the development of a winter sugar beet with controlled bolting behavior. In cool temperate climates, sugar beets are currently grown as a spring crop. They are sown in spring and harvested in autumn. Growing sugar beet as a winter crop with an extended vegetation period fails due to bolting after winter. Bolting after winter might be controlled by accumulating genes for post-winter bolting resistance. Previously, we had observed in field experiments a low post-winter bolting rate of 0.5 for sugar beet accession BETA 1773. This accession was crossed with a biennial sugar beet with regular bolting behavior to develop a F3 mapping population. The population was grown in the greenhouse, exposed to artificial cold treatment for 16 weeks and transplanted to the field. Bolting was recorded twice a week from May until October. Post-winter bolting behavior was assessed by two different factors, bolting delay (determined as days to bolt after cold treatment) and post-winter bolting resistance (bolting rate after winter). For days to bolt, means of F3 families ranged from 25 to 164 days while for bolting rate F3 families ranged from 0 to 1. For each factor one QTL explaining about 65% of the phenotypic variation was mapped to the same region on linkage group 9 with a partially recessive allele increasing bolting delay and post-winter bolting resistance. The results are discussed in relation to the potential use of marker-assisted breeding of winter sugar beets with controlled bolting.