Dissecting the epigenomic differences between smoking and nicotine dependence in a veteran cohort

Smoking is a serious public health issue linked to more than 8 million deaths per year worldwide and may lead to nicotine dependence (ND). Although the epigenomic literature on smoking is well established, studies evaluating the role of epigenetics in ND are limited. In this study, we examined the epigenomic signatures of ND and how these differ from smoking exposure to identify biomarkers specific to ND. We investigated the peripheral epigenetic profile of smoking status (SS) and ND in a US male veteran cohort. DNA from saliva was collected from 1135 European American (EA) male US military veterans. DNAm was assessed using the Illumina Infinium Human MethylationEPIC BeadChip array. SS was evaluated as current smokers (n = 137; 12.1%) and non-current smokers (never and former; n = 998; 87.9%). NDFTND was assessed as a continuous variable using the Fagerström Test for ND (FTND; n = 1135; mean = 2.54 ± 2.29). Epigenome-wide association studies (EWAS) and co-methylation analyses were conducted for SS and NDFTND . A total of 450 and 22 genome-wide significant differentially methylated sites (DMS) were associated with SS and NDFTND , respectively (15 overlapped DMS). We identified 97 DMS (43 genes) in SS-EWAS previously reported in the literature, including AHRR and F2RL3 genes (p-value: 1.95 × 10-83 to 4.55 × 10-33 ). NDFTND novel DMS mapped to NEUROG1, ANPEP, and SLC29A1. Co-methylation analysis identified 386 modules (11 SS-related and 19 NDFTND -related). SS-related modules showed enrichment for alcoholism, while NDFTND -related modules were enriched for nicotine addiction. This study confirms previous findings associated with SS and identifies novel and-potentially specific-epigenetic biomarkers of ND that may inform prognosis and novel treatment strategies.

Cross-Species Convergence of Brain Transcriptomic and Epigenomic Findings in Posttraumatic Stress Disorder: A Systematic Review

Introduction

Posttraumatic stress disorder (PTSD) is a complex multifactorial disorder influenced by the interaction of genetic and environmental factors. Analyses of epigenomic and transcriptomic modifications may help to dissect the biological factors underlying the gene-environment interplay in PTSD. To date, most human PTSD epigenetics studies have used peripheral tissue, and these findings have complex and poorly understood relationships to brain alterations. Studies examining brain tissue may help characterize the brain-specific transcriptomic and epigenomic profiles of PTSD. In this review, we compiled and integrated brain-specific molecular findings of PTSD from humans and animals.

Methods

A systematic literature search according to the PRISMA criteria was performed to identify transcriptomic and epigenomic studies of PTSD, focusing on brain tissue from human postmortem samples or animal-stress paradigms.

Results

Gene- and pathway-level convergence analyses revealed PTSD-dysregulated genes and biological pathways across brain regions and species. A total of 243 genes converged across species, with 17 of them significantly enriched for PTSD. Chemical synaptic transmission and signaling by G-protein-coupled receptors were consistently enriched across omics and species.

Discussion

Our findings point out dysregulated genes highly replicated across PTSD studies in humans and animal models and suggest a potential role for the corticotropin-releasing hormone/orexin pathway in PTSD's pathophysiology. Further, we highlight current knowledge gaps and limitations and recommend future directions to address them.

Genetic variation in symbiotic islands of natural variant strains of soybean Bradyrhizobium japonicum and Bradyrhizobium diazoefficiens differing in competitiveness and in the efficiency of nitrogen fixation

Soybean is the most important legume cropped worldwide and can highly benefit from the biological nitrogen fixation (BNF) process. Brazil is recognized for its leadership in the use of inoculants and two strains, Bradyrhizobium japonicum CPAC 15 (=SEMIA 5079) and Bradyrhizobium diazoefficiens CPAC 7 (=SEMIA 5080) compose the majority of the 70 million doses of soybean inoculants commercialized yearly in the country. We studied a collection of natural variants of these two strains, differing in properties of competitiveness and efficiency of BNF. We sequenced the genomes of the parental strain SEMIA 566 of B. japonicum, of three natural variants of this strain (S 204, S 340 and S 370), and compared with another variant of this group, strain CPAC 15. We also sequenced the genome of the parental strain SEMIA 586 of B. diazoefficiens, of three natural variants of this strain (CPAC 390, CPAC 392 and CPAC 394) and compared with the genome of another natural variant, strain CPAC 7. As the main genes responsible for nodulation (nod, noe, nol) and BNF (nif, fix) in soybean Bradyrhizobium are located in symbiotic islands, our objective was to identify genetic variations located in this region, including single nucleotide polymorphisms (SNPs) and insertions and deletions (indels), that could be potentially related to their different symbiotic phenotypes. We detected 44 genetic variations in the B. japonicum strains and three in B. diazoefficiens. As the B. japonicum strains have gone through a longer period of adaptation to the soil, the higher number of genetic variations could be explained by survival strategies under the harsh environmental conditions of the Brazilian Cerrado biome. Genetic variations were detected in genes enconding proteins such as a dephospho-CoA kinase, related to the CoA biosynthesis; a glucosamine-fructose-6-phosphate aminotransferase, key regulator of the hexosamine biosynthetic pathway; a LysR family transcriptional regulator related to nodulation genes; and NifE and NifS proteins, directly related to the BNF process. We suggest potential genetic variations related to differences in the symbiotic phenotypes.

Ethanol production process driving changes on industrial strains

Ethanol production has key differences between the two largest producing countries of this biofuel, Brazil and the USA, such as feedstock source, sugar concentration and ethanol titers in industrial fermentation. Therefore, it is highly probable that these specificities have led to genome adaptation of the Saccharomyces cerevisiae strains employed in each process to tolerate different environments. In order to identify particular adaptations, in this work, we have compared the genomes of industrial yeast strains widely used to produce ethanol from sugarcane, corn and sweet sorghum, and also two laboratory strains as reference. The genes were predicted and then 4524 single-copy orthologous were selected to build the phylogenetic tree. We found that the geographic location and industrial process were shown as the main evolutionary drivers: for sugarcane fermentation, positive selection was identified for metal homeostasis and stress response genes, whereas genes involved in membrane modeling have been connected with corn fermentation. In addition, the corn specialized strain Ethanol Red showed an increased number of copies of MAL31, a gene encoding a maltose transporter. In summary, our work can help to guide new strain chassis selection for engineering strategies, to produce more robust strains for biofuel production and other industrial applications.

Expected Genotype Quality and Diploidized Marker Data from Genotyping-by-Sequencing of Urochloa spp. Tetraploids

Introduced concept of expected genotype quality (EGQ) and software to calculate it Provided read depth guidelines for GBS in tetraploids Developed software to generate diploidized genotype calls from VCF files Demonstrated value of aligning GBS reads to a mock reference genome for SNP discovery Recommend filtering based on GQ and read depth to prevent genotype bias Although genotyping-by-sequencing (GBS) is a well-established marker technology in diploids, the development of best practices for tetraploid species is a topic of current research. We determined the theoretical relationship between read depth and the phred-scaled probability of genotype misclassification conditioned on the true genotype, which we call expected genotype quality (EGQ). If the GBS method has 0.5% allelic error, then 17 reads are needed to classify simplex tetraploids as heterozygous with 95% accuracy (EGQ = 13) vs. 61 reads to determine allele dosage. We developed an R script to convert tetraploid GBS data in variant call format (VCF) into diploidized genotype calls and applied it to 267 interspecific hybrids of the tetraploid forage grass Urochloa. When reads were aligned to a mock reference genome created from GBS data of the Urochloa brizantha (Hochst. ex A. Rich.) R. D. Webster cultivar Marandu, 25,678 biallelic single nucleotide polymorphism (SNPs) were discovered, compared with ∼3000 SNPs when aligning to the closest true reference genomes, Setaria viridis (L.) P. Beauv. and S. italica (L.) P. Beauv. Cross-validation revealed that missing genotypes were imputed by the random forest method with a median accuracy of 0.85 regardless of heterozygote frequency. Using the Urochloa spp. hybrids, we illustrated how filtering samples based only on genotype quality (GQ) creates genotype bias; a depth threshold based on EGQ is also needed regardless of whether genotypes are called using a diploidized or allele dosage model.

Unraveling the genetic basis of xylose consumption in engineered Saccharomyces cerevisiae strains

The development of biocatalysts capable of fermenting xylose, a five-carbon sugar abundant in lignocellulosic biomass, is a key step to achieve a viable production of second-generation ethanol. In this work, a robust industrial strain of Saccharomyces cerevisiae was modified by the addition of essential genes for pentose metabolism. Subsequently, taken through cycles of adaptive evolution with selection for optimal xylose utilization, strains could efficiently convert xylose to ethanol with a yield of about 0.46 g ethanol/g xylose. Though evolved independently, two strains carried shared mutations: amplification of the xylose isomerase gene and inactivation of ISU1, a gene encoding a scaffold protein involved in the assembly of iron-sulfur clusters. In addition, one of evolved strains carried a mutation in SSK2, a member of MAPKKK signaling pathway. In validation experiments, mutating ISU1 or SSK2 improved the ability to metabolize xylose of yeast cells without adaptive evolution, suggesting that these genes are key players in a regulatory network for xylose fermentation. Furthermore, addition of iron ion to the growth media improved xylose fermentation even by non-evolved cells. Our results provide promising new targets for metabolic engineering of C5-yeasts and point to iron as a potential new additive for improvement of second-generation ethanol production.