Small RNAs and Karma methylation in Elaeis guineensis mother palms are linked to high clonal mantling.

The mantled phenotype is an abnormal somaclonal variant arising from the oil palm cloning process and severe phenotypes lead to oil yield losses. Hypomethylation of the Karma retrotransposon within the B-type MADS-box EgDEF1 gene has been associated with this phenotype. While abnormal Karma-EgDEF1 hypomethylation was detected in mantled clones, we examined the methylation state of Karma in ortets that gave rise to high mantling rates in their clones. Small RNAs (sRNAs) were proposed to play a role in Karma hypomethylation as part of the RNA-directed DNA methylation process, hence differential expression analysis of sRNAs between the ortet groups was conducted. While no sRNA was differentially expressed at the Karma-EgDEF1 region, three sRNA clusters were differentially regulated in high-mantling ortets. The first two down-regulated clusters were possibly derived from long non-coding RNAs while the third up-regulated cluster was derived from the intron of a DnaJ chaperone gene. Several predicted mRNA targets for the first two sRNA clusters conversely displayed increased expression in high-mantling relative to low-mantling ortets. These predicted mRNA targets may be associated with defense or pathogenesis response. In addition, several differentially methylated regions (DMRs) were identified in Karma and its surrounding regions, mainly comprising subtle CHH hypomethylation in high-mantling ortets. Four of the 12 DMRs were located in a region corresponding to hypomethylated areas at the 3'end of Karma previously reported in mantled clones. Further investigations on these sRNAs and DMRs may indicate the predisposition of certain ortets towards mantled somaclonal variation.

Genome-Wide Prediction of Transcription Start Sites in Conifers.

The identification of promoters is an essential step in the genome annotation process, providing a framework for gene regulatory networks and their role in transcription regulation. Despite considerable advances in the high-throughput determination of transcription start sites (TSSs) and transcription factor binding sites (TFBSs), experimental methods are still time-consuming and expensive. Instead, several computational approaches have been developed to provide fast and reliable means for predicting the location of TSSs and regulatory motifs on a genome-wide scale. Numerous studies have been carried out on the regulatory elements of mammalian genomes, but plant promoters, especially in gymnosperms, have been left out of the limelight and, therefore, have been poorly investigated. The aim of this study was to enhance and expand the existing genome annotations using computational approaches for genome-wide prediction of TSSs in the four conifer species: loblolly pine, white spruce, Norway spruce, and Siberian larch. Our pipeline will be useful for TSS predictions in other genomes, especially for draft assemblies, where reliable TSS predictions are not usually available. We also explored some of the features of the nucleotide composition of the predicted promoters and compared the GC properties of conifer genes with model monocot and dicot plants. Here, we demonstrate that even incomplete genome assemblies and partial annotations can be a reliable starting point for TSS annotation. The results of the TSS prediction in four conifer species have been deposited in the Persephone genome browser, which allows smooth visualization and is optimized for large data sets. This work provides the initial basis for future experimental validation and the study of the regulatory regions to understand gene regulation in gymnosperms.

Bioinformatics Applications to Reveal Molecular Mechanisms of Gene Expression Regulation in Model Organisms.

Gene expression regulation at the transcriptome, genome, cell, and tissue levels is a complex phenomenon demanding the development of bioinformatics tools [...].

Changes in Biological Pathways During 6,000 Years of Civilization in Europe.

The beginning of civilization was a turning point in human evolution. With increasing separation from the natural environment, mankind stimulated new adaptive reactions in response to new environmental factors. In this paper, we describe direct signs of these reactions in the European population during the past 6,000 years. By comparing whole-genome data between Late Neolithic/Bronze Age individuals and modern Europeans, we revealed biological pathways that are significantly differently enriched in nonsynonymous single nucleotide polymorphisms in these two groups and which therefore could be shaped by cultural practices during the past six millennia. They include metabolic transformations, immune response, signal transduction, physical activity, sensory perception, reproduction, and cognitive functions. We demonstrated that these processes were influenced by different types of natural selection. We believe that our study opens new perspectives for more detailed investigations about when and how civilization has been modifying human genomes.

DNA methylation changes in clonally propagated oil palm.

KEY MESSAGE: Several hypomethylated sites within the Karma region of EgDEF1 and hotspot regions in chromosomes 1, 2, 3, and 5 may be associated with mantling. One of the main challenges faced by the oil palm industry is fruit abnormalities, such as the "mantled" phenotype that can lead to reduced yields. This clonal abnormality is an epigenetic phenomenon and has been linked to the hypomethylation of a transposable element within the EgDEF1 gene. To understand the epigenome changes in clones, methylomes of clonal oil palms were compared to methylomes of seedling-derived oil palms. Whole-genome bisulfite sequencing data from seedlings, normal, and mantled clones were analyzed to determine and compare the context-specific DNA methylomes. In seedlings, coding and regulatory regions are generally hypomethylated while introns and repeats are extensively methylated. Genes with a low number of guanines and cytosines in the third position of codons (GC3-poor genes) were increasingly methylated towards their 3' region, while GC3-rich genes remain demethylated, similar to patterns in other eukaryotic species. Predicted promoter regions were generally hypomethylated in seedlings. In clones, CG, CHG, and CHH methylation levels generally decreased in functionally important regions, such as promoters, 5' UTRs, and coding regions. Although random regions were found to be hypomethylated in clonal genomes, hypomethylation of certain hotspot regions may be associated with the clonal mantling phenotype. Our findings, therefore, suggest other hypomethylated CHG sites within the Karma of EgDEF1 and hypomethylated hotspot regions in chromosomes 1, 2, 3 and 5, are associated with mantling.

Bioinformatics Methods in Medical Genetics and Genomics.

Medical genomics relies on next-gen sequencing methods to decipher underlying molecular mechanisms of gene expression. This special issue collects materials originally presented at the "Centenary of Human Population Genetics" Conference-2019, in Moscow. Here we present some recent developments in computational methods tested on actual medical genetics problems dissected through genomics, transcriptomics and proteomics data analysis, gene networks, protein-protein interactions and biomedical literature mining. We have selected materials based on systems biology approaches, database mining. These methods and algorithms were discussed at the Digital Medical Forum-2019, organized by I.M. Sechenov First Moscow State Medical University presenting bioinformatics approaches for the drug targets discovery in cancer, its computational support, and digitalization of medical research, as well as at "Systems Biology and Bioinformatics"-2019 (SBB-2019) Young Scientists School in Novosibirsk, Russia. Selected recent advancements discussed at these events in the medical genomics and genetics areas are based on novel bioinformatics tools.

The Impact of MNRI Therapy on the Levels of Neurotransmitters Associated with Inflammatory Processes.

The neurotransmitter levels of representatives from five different diagnosis groups were tested before and after participation in the MNRI®-Masgutova Neurosensorimotor Reflex Intervention. The purpose of this study was to ascertain neurological impact on (1) Developmental disorders, (2) Anxiety disorders/OCD (Obsessive Compulsive Disorder), PTSD (Post-Traumatic Stress disorder), (3) Palsy/Seizure disorders, (4) ADD/ADHD (Attention Deficit Disorder/Attention Deficit Disorder Hyperactive Disorder), and (5) ASD (Autism Spectrum Disorder) disorders. Each participant had a form of neurological dysregulation and typical symptoms respective to their diagnosis. These diagnoses have a severe negative impact on the quality of life, immunity, stress coping, cognitive skills, and social assimilation. This study showed a trend towards optimization and normalization of neurological and immunological functioning, thus supporting the claim that the MNRI method is an effective non-pharmacological neuromodulation treatment of neurological disorders. The effects of MNRI on inflammation have not yet been assessed. The resulting post-MNRI changes in participants' neurotransmitters show significant adjustments in the regulation of the neurotransmitter resulting in being calmer, a decrease of hypervigilance, an increase in stress resilience, behavioral and emotional regulation improvements, a more positive emotional state, and greater control of cognitive processes. In this paper, we demonstrate that the MNRI approach is an intervention that reduces inflammation. It is also likely to reduce oxidative stress and encourage homeostasis of excitatory neurotransmitters. MNRI may facilitate neurodevelopment, build stress resiliency, neuroplasticity, and optimal learning opportunity. There have been no reported side effects of MNRI treatments.

Characterization of the mitochondrial genome of the MAX1 type of cytoplasmic male-sterile sunflower.

BACKGROUND: More than 70 cytoplasmic male sterility (CMS) types have been identified in Helianthus, but only for less than half of them, research of mitochondrial organization has been conducted. Moreover, complete mitochondrion sequences have only been published for two CMS sources - PET1 and PET2. It has been demonstrated that other sunflower CMS sources like MAX1, significantly differ from the PET1 and PET2 types. However, possible molecular causes for the CMS induction by MAX1 have not yet been proposed. In the present study, we have investigated structural changes in the mitochondrial genome of HA89 (MAX1) CMS sunflower line in comparison to the fertile mitochondrial genome. RESULTS: Eight significant major reorganization events have been determined in HA89 (MAX1) mtDNA: one 110 kb inverted region, four deletions of 439 bp, 978 bp, 3183 bp and 14,296 bp, respectively, and three insertions of 1999 bp, 5272 bp and 6583 bp. The rearrangements have led to functional changes in the mitochondrial genome of HA89 (MAX1) resulting in the complete elimination of orf777 and the appearance of new ORFs - orf306, orf480, orf645 and orf1287. Aligning the mtDNA of the CMS sources PET1 and PET2 with MAX1 we found some common reorganization features in their mitochondrial genome sequences. CONCLUSION: The new open reading frame orf1287, representing a chimeric atp6 gene, may play a key role in MAX1 CMS phenotype formation in sunflower, while the contribution of other mitochondrial reorganizations seems to appear negligible for the CMS development.

Seqping: gene prediction pipeline for plant genomes using self-training gene models and transcriptomic data.

BACKGROUND: Gene prediction is one of the most important steps in the genome annotation process. A large number of software tools and pipelines developed by various computing techniques are available for gene prediction. However, these systems have yet to accurately predict all or even most of the protein-coding regions. Furthermore, none of the currently available gene-finders has a universal Hidden Markov Model (HMM) that can perform gene prediction for all organisms equally well in an automatic fashion. RESULTS: We present an automated gene prediction pipeline, Seqping that uses self-training HMM models and transcriptomic data. The pipeline processes the genome and transcriptome sequences of the target species using GlimmerHMM, SNAP, and AUGUSTUS pipelines, followed by MAKER2 program to combine predictions from the three tools in association with the transcriptomic evidence. Seqping generates species-specific HMMs that are able to offer unbiased gene predictions. The pipeline was evaluated using the Oryza sativa and Arabidopsis thaliana genomes. Benchmarking Universal Single-Copy Orthologs (BUSCO) analysis showed that the pipeline was able to identify at least 95% of BUSCO's plantae dataset. Our evaluation shows that Seqping was able to generate better gene predictions compared to three HMM-based programs (MAKER2, GlimmerHMM and AUGUSTUS) using their respective available HMMs. Seqping had the highest accuracy in rice (0.5648 for CDS, 0.4468 for exon, and 0.6695 nucleotide structure) and A. thaliana (0.5808 for CDS, 0.5955 for exon, and 0.8839 nucleotide structure). CONCLUSIONS: Seqping provides researchers a seamless pipeline to train species-specific HMMs and predict genes in newly sequenced or less-studied genomes. We conclude that the Seqping pipeline predictions are more accurate than gene predictions using the other three approaches with the default or available HMMs.

Between Lake Baikal and the Baltic Sea: genomic history of the gateway to Europe.

BACKGROUND: The history of human populations occupying the plains and mountain ridges separating Europe from Asia has been eventful, as these natural obstacles were crossed westward by multiple waves of Turkic and Uralic-speaking migrants as well as eastward by Europeans. Unfortunately, the material records of history of this region are not dense enough to reconstruct details of population history. These considerations stimulate growing interest to obtain a genetic picture of the demographic history of migrations and admixture in Northern Eurasia. RESULTS: We genotyped and analyzed 1076 individuals from 30 populations with geographical coverage spanning from Baltic Sea to Baikal Lake. Our dense sampling allowed us to describe in detail the population structure, provide insight into genomic history of numerous European and Asian populations, and significantly increase quantity of genetic data available for modern populations in region of North Eurasia. Our study doubles the amount of genome-wide profiles available for this region. We detected unusually high amount of shared identical-by-descent (IBD) genomic segments between several Siberian populations, such as Khanty and Ket, providing evidence of genetic relatedness across vast geographic distances and between speakers of different language families. Additionally, we observed excessive IBD sharing between Khanty and Bashkir, a group of Turkic speakers from Southern Urals region. While adding some weight to the "Finno-Ugric" origin of Bashkir, our studies highlighted that the Bashkir genepool lacks the main "core", being a multi-layered amalgamation of Turkic, Ugric, Finnish and Indo-European contributions, which points at intricacy of genetic interface between Turkic and Uralic populations. Comparison of the genetic structure of Siberian ethnicities and the geography of the region they inhabit point at existence of the "Great Siberian Vortex" directing genetic exchanges in populations across the Siberian part of Asia. Slavic speakers of Eastern Europe are, in general, very similar in their genetic composition. Ukrainians, Belarusians and Russians have almost identical proportions of Caucasus and Northern European components and have virtually no Asian influence. We capitalized on wide geographic span of our sampling to address intriguing question about the place of origin of Russian Starovers, an enigmatic Eastern Orthodox Old Believers religious group relocated to Siberia in seventeenth century. A comparative reAdmix analysis, complemented by IBD sharing, placed their roots in the region of the Northern European Plain, occupied by North Russians and Finno-Ugric Komi and Karelian people. Russians from Novosibirsk and Russian Starover exhibit ancestral proportions close to that of European Eastern Slavs, however, they also include between five to 10 % of Central Siberian ancestry, not present at this level in their European counterparts. CONCLUSIONS: Our project has patched the hole in the genetic map of Eurasia: we demonstrated complexity of genetic structure of Northern Eurasians, existence of East-West and North-South genetic gradients, and assessed different inputs of ancient populations into modern populations.

Differential Evolution approach to detect recent admixture.

The genetic structure of human populations is extraordinarily complex and of fundamental importance to studies of anthropology, evolution, and medicine. As increasingly many individuals are of mixed origin, there is an unmet need for tools that can infer multiple origins. Misclassification of such individuals can lead to incorrect and costly misinterpretations of genomic data, primarily in disease studies and drug trials. We present an advanced tool to infer ancestry that can identify the biogeographic origins of highly mixed individuals. reAdmix can incorporate individual's knowledge of ancestors (e.g. having some ancestors from Turkey or a Scottish grandmother). reAdmix is an online tool available at http://chcb.saban-chla.usc.edu/reAdmix/.

Genome-wide signatures of male-mediated migration shaping the Indian gene pool.

Multiple questions relating to contributions of cultural and demographical factors in the process of human geographical dispersal remain largely unanswered. India, a land of early human settlement and the resulting diversity is a good place to look for some of the answers. In this study, we explored the genetic structure of India using a diverse panel of 78 males genotyped using the GenoChip. Their genome-wide single-nucleotide polymorphism (SNP) diversity was examined in the context of various covariates that influence Indian gene pool. Admixture analysis of genome-wide SNP data showed high proportion of the Southwest Asian component in all of the Indian samples. Hierarchical clustering based on admixture proportions revealed seven distinct clusters correlating to geographical and linguistic affiliations. Convex hull overlay of Y-chromosomal haplogroups on the genome-wide SNP principal component analysis brought out distinct non-overlapping polygons of F*-M89, H*-M69, L1-M27, O2a-M95 and O3a3c1-M117, suggesting a male-mediated migration and expansion of the Indian gene pool. Lack of similar correlation with mitochondrial DNA clades indicated a shared genetic ancestry of females. We suggest that ancient male-mediated migratory events and settlement in various regional niches led to the present day scenario and peopling of India.

Gene expression and nucleotide composition are associated with genic methylation level in Oryza sativa.

BACKGROUND: The methylation of cytosines at CpG dinucleotides, which plays an important role in gene expression regulation, is one of the most studied epigenetic modifications. Thus far, the detection of DNA methylation has been determined mostly by experimental methods, which are not only prone to bench effects and artifacts but are also time-consuming, expensive, and cannot be easily scaled up to many samples. It is therefore useful to develop computational prediction methods for DNA methylation. Our previous studies highlighted the existence of correlations between the GC content of the third codon position (GC3), methylation, and gene expression. We thus designed a model to predict methylation in Oryza sativa based on genomic sequence features and gene expression data. RESULTS: We first derive equations to describe the relationship between gene methylation levels, GC3, expression, length, and other gene compositional features. We next assess gene compositional features involving sixmers and their association with methylation levels and other gene level properties. By applying our sixmer-based approach on rice gene expression data we show that it can accurately predict methylation (Pearson's correlation coefficient r = 0.79) for the majority (79%) of the genes. Matlab code with our model is included. CONCLUSIONS: Gene expression variation can be used as predictors of gene methylation levels.

Chromosome-scale Elaeis guineensis and E. oleifera assemblies: comparative genomics of oil palm and other Arecaceae.

Elaeis guineensis and E. oleifera are the two species of oil palm. E. guineensis is the most widely cultivated commercial species, and introgression of desirable traits from E. oleifera is ongoing. We report an improved E. guineensis genome assembly with substantially increased continuity and completeness, as well as the first chromosome-scale E. oleifera genome assembly. Each assembly was obtained by integration of long-read sequencing, proximity ligation sequencing, optical mapping, and genetic mapping. High interspecific genome conservation is observed between the two species. The study provides the most extensive gene annotation to date, including 46,697 E. guineensis and 38,658 E. oleifera gene predictions. Analyses of repetitive element families further resolve the DNA repeat architecture of both genomes. Comparative genomic analyses identified experimentally validated small structural variants between the oil palm species and resolved the mechanism of chromosomal fusions responsible for the evolutionary descending dysploidy from 18 to 16 chromosomes.