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.

Linguistic correlates of societal variation: A quantitative analysis.

Traditionally, many researchers have supported a uniformitarian view whereby all languages are of roughly equal complexity, facilitated by internal trade-offs between complexity at different levels, such as morphology and syntax. The extent to which the speakers' societies influence the trade-offs has not been well studied. In this paper, we focus on morphology and syntax, and report significant correlations between specific linguistic and societal features, in particular those relating to exoteric (open) vs. esoteric (close-knit) society types, characterizable in terms of population size, mobility, communication across distances, etc. We conduct an exhaustive quantitative analysis drawing upon WALS, D-Place, Ethnologue and Glottolog, finding some support for our hypothesis that languages spoken by exoteric societies tend towards more complex syntaxes, while languages spoken by esoteric societies tend towards more complex morphologies.

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.

Mitochondrial DNA haplogroup, genetic ancestry, and susceptibility to Ewing sarcoma.

Based on current studies, the incidence of Ewing sarcoma (ES) varies significantly by race and ethnicity, with the disease being most common in patients of European ancestry. However, race/ethnicity has generally been self-reported rather than formally evaluated at a population level using DNA evidence. Additionally, mitochondrial dysfunction is a hallmark of ES, yet there have been no reported studies of mitochondrial genetics in ES. Thus, we evaluated both the mitochondrial and nuclear ancestries of 420 pediatric ES patients in the United States using whole-genome sequencing. We found that the mitochondrial DNA (mtDNA) genomes of only six (1.4 %) patients belonged to African L haplogroups, while those of 90 % of the patients belonged to macrohaplogroup R, which includes haplogroup H, the most common maternal lineage in Europe. Compared to the general US population, European haplogroups were significantly enriched in ES patients (p < 2.2e-16) and the African haplogroups are significantly impoverished (p < 4.6e-16). Using the ancestry informative markers defined in a National Genographic study, the vast majority of patients exhibited significant nuclear ancestry originating from the Mediterranean, Northern Europe, and Southwest Asia, including all six patients with African L mtDNAs. Very few had primarily African nuclear ancestry. This is the first genomic epidemiology study to simultaneously interrogate the mitochondrial and nuclear ancestries of ES patients. While supporting previous findings of enriched European ancestry in ES patients, these results also suggest alternative hypotheses for the significant contribution of mitochondrial ancestry in ES patients, as well as the protective role of African ancestry.

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 [...].

Cervical cancer testing among women aged 30-49 years in the WHO European Region.

BACKGROUND: Screening programs play an important role in a comprehensive strategy to prevent cervical cancer, a leading cause of death among women of reproductive age. Unfortunately, there is a dearth of information about rates of cervical cancer testing, particularly in Eastern Europe and Central Asia where levels of cervical cancer are among the highest in the WHO European Region. The purpose of this article is to report on the lifetime prevalence of cervical cancer testing among females aged 30-49 years from across the WHO European region, and to describe high-level geographic and socioeconomic differences. METHODS: We used data from the European Health Information Survey and the WHO STEPwise approach to Surveillance survey to calculate the proportions of women who were tested for cervical cancer. RESULTS: The percentage of tested women ranged from 11.7% in Azerbaijan to 98.4% in Finland, with the lowest percentages observed in Azerbaijan, Tajikistan and Uzbekistan. Testing was lower in Eastern Europe (compared to Western Europe), among low-income countries and among women with lower levels of education. CONCLUSION: Effective cervical cancer screening programs are one part of a larger strategy, which must also include national scale-up of human papilloma virus vaccination, screening and treatment.

Genome-wide analysis of genetic diversity and artificial selection in Large White pigs in Russia.

Breeding practices adopted at different farms are aimed at maximizing the profitability of pig farming. In this work, we have analyzed the genetic diversity of Large White pigs in Russia. We compared genomes of historic and modern Large White Russian breeds using 271 pig samples. We have identified 120 candidate regions associated with the differentiation of modern and historic pigs and analyzed genomic differences between the modern farms. The identified genes were associated with height, fitness, conformation, reproductive performance, and meat quality.

Recent selection of candidate genes for mammal domestication in Europeans and language change in Europe: a hypothesis.

BACKGROUND AND AIM: Human evolution resulted from changes in our biology, behaviour, and culture. One source of these changes has been hypothesised to be our self-domestication (that is, the development in humans of features commonly found in domesticated strains of mammals, seemingly as a result of selection for reduced aggression). Signals of domestication, notably brain size reduction, have increased in recent times. METHODS: In this paper, we compare whole-genome data between the Late Neolithic/Bronze Age individuals and modern Europeans. RESULTS: We show that genes associated with mammal domestication and with neural crest development and function are significantly differently enriched in nonsynonymous single nucleotide polymorphisms between these two groups. CONCLUSION: We hypothesise that these changes might account for the increased features of self-domestication in modern humans and, ultimately, for subtle recent changes in human cognition and behaviour, including language.

Detection of genomic regions associated malformations in newborn piglets: a machine-learning approach.

BACKGROUND: A significant proportion of perinatal losses in pigs occurs due to congenital malformations. The purpose of this study is the identification of genomic loci associated with fetal malformations in piglets. METHODS: The malformations were divided into two groups: associated with limb defects (piglet splay leg) and associated with other congenital anomalies found in newborn piglets. 148 Landrace and 170 Large White piglets were selected for the study. A genome-wide association study based on the gradient boosting machine algorithm was performed to identify markers associated with congenital anomalies and piglet splay leg. RESULTS: Forty-nine SNPs (23 SNPs in Landrace pigs and 26 SNPs in Large White) were associated with congenital anomalies, 22 of which were localized in genes. A total of 156 SNPs (28 SNPs in Landrace; 128 in Large White) were identified for piglet splay leg, of which 79 SNPs were localized in genes. We have demonstrated that the gradient boosting machine algorithm can identify SNPs and their combinations associated with significant selection indicators of studied malformations and productive characteristics. DATA AVAILABILITY: Genotyping and phenotyping data are available at http://www.compubioverne.group/data-and-software/.

Prediction of Rice Transcription Start Sites Using TransPrise: A Novel Machine Learning Approach.

As the interest in genetic resequencing increases, so does the need for effective mathematical, computational, and statistical approaches. One of the difficult problems in genome annotation is determination of precise positions of transcription start sites. In this paper, we present TransPrise-an efficient deep learning tool for predicting positions of eukaryotic transcription start sites. TransPrise offers significant improvement over existing promoter-prediction methods. To illustrate this, we compared predictions of TransPrise with the TSSPlant approach for well-annotated genome of Oryza sativa. Using a computer with a graphics processing unit, the run time of TransPrise is 250 min on a genome of 374 Mb long.We provide the full basis for the comparison and encourage users to freely access a set of our computational tools to facilitate and streamline their own analyses. The ready-to-use Docker image with all the necessary packages, models, and code as well as the source code of the TransPrise algorithm are available at http://compubioverne.group/ . The source code is ready to use and to be customized to predict TSS in any eukaryotic organism.

Local ancestry prediction with PyLAE.

SUMMARY: We developed PyLAE, a new tool for determining local ancestry along a genome using whole-genome sequencing data or high-density genotyping experiments. PyLAE can process an arbitrarily large number of ancestral populations (with or without an informative prior). Since PyLAE does not involve estimating many parameters, it can process thousands of genomes within a day. PyLAE can run on phased or unphased genomic data. We have shown how PyLAE can be applied to the identification of differentially enriched pathways between populations. The local ancestry approach results in higher enrichment scores compared to whole-genome approaches. We benchmarked PyLAE using the 1000 Genomes dataset, comparing the aggregated predictions with the global admixture results and the current gold standard program RFMix. Computational efficiency, minimal requirements for data pre-processing, straightforward presentation of results, and ease of installation make PyLAE a valuable tool to study admixed populations. AVAILABILITY AND IMPLEMENTATION: The source code and installation manual are available at https://github.com/smetam/pylae.

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.