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The Genome Variation Map (GVM; http://bigd.big.ac.cn/gvm/) is a public data repository of genome variations. It aims to collect and integrate genome variations for a wide range of species, accepts submissions of different variation types from all over the world and provides free open access to all publicly available data in support of worldwide research activities. Compared with the previous version, particularly, a total of 22 species, 115 projects, 55 935 samples, 463 429 609 variants, 66 220 associations and 56 submissions (as of 7 September 2020) were newly added in the current version of GVM. In the current release, GVM houses a total of ∼960 million variants from 41 species, including 13 animals, 25 plants and 3 viruses. Moreover, it incorporates 64 819 individual genotypes and 260 393 manually curated high-quality genotype-to-phenotype associations. Since its inception, GVM has archived genomic variation data of 43 754 samples submitted by worldwide users and served >1 million data download requests. Collectively, as a core resource in the National Genomics Data Center, GVM provides valuable genome variations for a diversity of species and thus plays an important role in both functional genomics studies and molecular breeding.

Bursaphelenchus xylophilus is an emerging pathogenic nematode that is responsible for a devastating epidemic of pine wilt disease worldwide, causing severe ecological damage and economic losses to forestry. Two forms of this nematode have been reported, i.e., with strong and weak virulence, commonly referred as virulent and avirulent strains. However, the pathogenicity-related genes of B. xylophilus are not sufficiently characterized. In this study, to find pathogenesis related genes we re-sequenced and compared genomes of two virulent and two avirulent populations. We identified genes affected by genomic variation, and functional annotation of those genes indicated that some of them might play potential roles in pathogenesis. The performed analysis showed that both avirulent populations differed from the virulent ones by 1576 genes with high impact variants. Demonstration of genetic differences between virulent and avirulent strains will provide effective methods to distinguish these two nematode virulence forms at the molecular level. The reported results provide basic information that can facilitate development of a better diagnosis for B. xylophilus isolates/strains which present different levels of virulence and better understanding of the molecular mechanism involved in the development of the PWD. Electronic supplementary material The online version of this article (10.1007/s00438-020-01739-w) contains supplementary material, which is available to authorized users.

Significance The accuracy of the nucleotide sequence of genomes is of utmost importance. The Perfect Match Genomic Landscape (PMGL) is a precise, sensitive, and nonstatistical strategy to detect genome variation. We used this strategy to refine reference genomes from microorganisms belonging to the three domains of life. Our studies show as well that the PMGL can be useful to detect variants in pathogen agents during a pandemic, and to isolate mutations generated during any desired stage of experimental evolution studies. We propose that the PMGL strategy could be the final step in the refinement of any haploid genome, independently of the methodology and algorithms used for its assembly., When addressing a genomic question, having a reliable and adequate reference genome is of utmost importance. This drives the necessity to refine and customize reference genomes (RGs). Our laboratory has recently developed a strategy, the Perfect Match Genomic Landscape (PMGL), to detect variation between genomes [K. Palacios-Flores et al.. Genetics 208, 1631–1641 (2018)]. The PMGL is precise and sensitive and, in contrast to most currently used algorithms, is nonstatistical in nature. Here we demonstrate the power of PMGL to refine and customize RGs. As a proof-of-concept, we refined different versions of the Saccharomyces cerevisiae RG. We applied the automatic PMGL pipeline to refine the genomes of microorganisms belonging to the three domains of life: the archaea Methanococcus maripaludis and Pyrococcus furiosus; the bacteria Escherichia coli, Staphylococcus aureus, and Bacillus subtilis; and the eukarya Schizosaccharomyces pombe, Aspergillus oryzae, and several strains of Saccharomyces paradoxus. We analyzed the reference genome of the virus SARS-CoV-2 and previously published viral genomes from patients’ samples with COVID-19. We performed a mutation-accumulation experiment in E. coli and show that the PMGL strategy can detect specific mutations generated at any desired step of the whole procedure. We propose that PMGL can be used as a final step for the refinement and customization of any haploid genome, independently of the strategies and algorithms used in its assembly.

Deciphering the functional impact of genetic variation is required to understand phenotypic diversity and the molecular mechanisms of inherited disease and cancer. While millions of genetic variants are now mapped in genome sequencing projects, distinguishing functional variants remains a major challenge. Protein-coding variation can be interpreted using post-translational modification (PTM) sites that are core components of cellular signaling networks controlling molecular processes and pathways. ActiveDriverDB is an interactive proteo-genomics database that uses more than 260,000 experimentally detected PTM sites to predict the functional impact of genetic variation in disease, cancer and the human population. Using machine learning tools, we prioritize proteins and pathways with enriched PTM-specific amino acid substitutions that potentially rewire signaling networks via induced or disrupted short linear motifs of kinase binding. We then map these effects to site-specific protein interaction networks and drug targets. In the 2021 update, we increased the PTM datasets by nearly 50%, included glycosylation, sumoylation and succinylation as new types of PTMs, and updated the workflows to interpret inherited disease mutations. We added a recent phosphoproteomics dataset reflecting the cellular response to SARS-CoV-2 to predict the impact of human genetic variation on COVID-19 infection and disease course. Overall, we estimate that 16-21% of known amino acid substitutions affect PTM sites among pathogenic disease mutations, somatic mutations in cancer genomes and germline variants in the human population. These data underline the potential of interpreting genetic variation through the lens of PTMs and signaling networks. The open-source database is freely available at www.ActiveDriverDB.org.

The human genome contains the instructions for the development and biological homeostasis of the human organism and the genetic transmission of traits. Genome variation in human populations is the basis of evolution; individual or personal genomes vary tremendously, making each of us truly unique.Assaying this individual variation using genomic technologies has many applications in clinical medicine, from elucidating the biology of disease to designing strategies to ameliorate perturbations from homeostasis. Detecting pathogenic rare variation in a genome may provide a molecular diagnosis that can be informative for patient management and family healthcare.Despite the increasing clinical use of unbiased genomic testing, including chromosome microarray analysis (CMA) with array comparative genomic hybridization (aCGH) or SNP arrays, clinical exome sequencing (cES), and whole-genome sequencing (WGS), to survey genome-wide for molecular aberrations, clinical acumen paired with an understanding of the limitations of each testing type will be needed to achieve molecular diagnoses. Potential opportunities for improving case solved rates, functionally annotating the majority of genes in the human genome, and further understanding genetic contributions to disease will empower clinical genomics and the precision medicine initiative.

Indonesian cacao productivity is still low mainly due to the lack availability of superior cacao planting materials. A new breeding method is necessary to expedite cacao yield improvement programs. To date, no study has yet been done to characterize Indonesian cacao varieties at the whole genome level. The objective of this study was to characterize genomic variation of five superior Indonesian cacao varieties using next-generation sequencing. Genetic materials used were five Indonesian cacao varieties, i.e. ICCRI2, ICCRI3, ICCRI4, SUL2 and ICS13. Genome sequences were mapped to the cacao reference genome sequence of Criollo variety. Sequence alignment and genomic variation discovery were done using Bowtie2 and mpileup software of Samtools, respectively. A total of 2,326,088 single nucleotide polymorphisms (SNPs) and 362,081 insertions and deletions (Indels) were obtained from this study. In average, a DNA variant was identified in every 121 nucleotides of the genome sequence. Most of the DNA variants were located outside the genes. Only 347,907 SNPs and Indels (13.18%) were located within protein coding region (exon). Among the DNA variations within exon, 188,949 SNPs caused missense mutation and 1,535 SNPs induced nonsense mutation. Unique gene-based SNPs were also discovered from this study that can be used as fingerprints for the particular cacao variety. The DNA variants obtained were excellent DNA marker resources to support cacao breeding programs. The SNPs discovered are useful as materials for genome-wide SNP chip development to be used for gene and QTL tagging of important traits for expediting national cacao breeding program.

Background: Chronic infections by one of the oncogenic human papillomaviruses (HPVs) are responsible for near 5% of the global cancer burden and HPV16 is the type most often found in cancers. HPV genomes displayunexpected levels of variation when deep-sequenced. Minor nucleotide variations (MNVs) may reveal HPVgenomic instability and HPV-related carcinogenic transformation of host cells. Objectives: The objective of this study was to investigate HPV16 genome variation at the minor variant level onpersisting HPV16 cervical infections from a population of young Dutch women. Study design:15 HPV16 infections were sequenced using a whole-HPV genome deep sequencing protocol (TaME-seq). One infection was followed over a three-year period, eight were followed over a two-year period, threewere followed over a one-year period and three infections had a single sampling point. Results and conclusions: Using a 1% variant frequency cutoff, we find on average 48 MNVs per HPV16 genomeand 1717 MNVs in total when sequencing coverage was > 100 × . Wefind the transition mutation T > C to be the most common, in contrast to other studies detecting APOBEC-related C > T mutation profiles in pre-cancerous and cancer samples. Our results suggest that the relative mutagenic footprint of HPV16 genomes may differ between the infections in this study and transforming lesions. In addition, we identify a number of MNVs that have previously been associated with higher incidence of high-grade lesions (CIN3+) in a population study. These findings may provide a starting point for future studies exploring causality between emerging HPV minorgenomic variants and cancer development. Ministry of Health, Welfare and Sports, the Netherlands and the South-Eastern Norway Regional Health Authority (Grant ID 2016020) are greatly acknowledged for funding.

Candida glabrata is an opportunistic fungal pathogen that currently ranks as the second most common cause of candidiasis. Although the mechanisms underlying virulence and drug resistance in C. glabrata are now starting to be elucidated, we still lack a good understanding of how this yeast adapts during the course of an infection. Outstanding questions are whether the observed genomic plasticity of C. glabrata plays a role during infection, or what levels of genetic variation exist within an infecting clonal population. To shed light onto the genomic variation within infecting C. glabrata populations, we compared the genomes of 11 pairs and one trio of serial clinical isolates, each obtained from a single patient. Our results provide a catalog of genetic variations existing within clonal infecting isolates, and reveal an enrichment of non-synonymous changes in genes encoding cell-wall proteins. Genetic variation and the presence of non-synonymous mutations and copy number variations accumulated within the host, suggest that clonal populations entail a non-negligible level of genetic variation that may reflect selection processes that occur within the human body. As we show here, these genomic changes can underlie phenotypic differences in traits that are relevant for infection. TG group acknowledges support from the Spanish Ministry of Economy, Industry, and Competitiveness (MEIC) for the EMBL partnership, and grants “Centro de Excelencia Severo Ochoa 2013–2017” SEV-2012-0208, and BFU2015-67107 cofunded by European Regional Development Fund (ERDF), from the CERCA Programme/Generalitat de Catalunya; from the Catalan Research Agency (AGAUR) SGR857, and grant from the European Union’s Horizon 2020 research and innovation programme under the grant agreement ERC-2016-724173 the Marie Sklodowska-Curie grant agreement No. H2020-MSCA-ITN-2014-642095. This project received support from the INB Grant (PT17/0009/0023 – ISCIII-SGEFI/ERDF).

Background The genomes of halophilic archaea (haloarchaea) often comprise multiple replicons. Genomic variation in haloarchaea has been linked to viral infection pressure and, in the case of Antarctic communities, can be caused by intergenera gene exchange. To expand understanding of genome variation and biogeography of Antarctic haloarchaea, here we assessed genomic variation between two strains of Halorubrum lacusprofundi that were isolated from Antarctic hypersaline lakes from different regions (Vestfold Hills and Rauer Islands). To assess variation in haloarchaeal populations, including the presence of genomic islands, metagenomes from six hypersaline Antarctic lakes were characterised. Results The sequence of the largest replicon of each Hrr. lacusprofundi strain (primary replicon) was highly conserved, while each of the strains’ two smaller replicons (secondary replicons) were highly variable. Intergenera gene exchange was identified, including the sharing of a type I-B CRISPR system. Evaluation of infectivity of an Antarctic halovirus provided experimental evidence for the differential susceptibility of the strains, bolstering inferences that strain variation is important for modulating interactions with viruses. A relationship was found between genomic structuring and the location of variation within replicons and genomic islands, demonstrating that the way in which haloarchaea accommodate genomic variability relates to replicon structuring. Metagenome read and contig mapping and clustering and scaling analyses demonstrated biogeographical patterning of variation consistent with environment and distance effects. The metagenome data also demonstrated that specific haloarchaeal species dominated the hypersaline systems indicating they are endemic to Antarctica. Conclusion The study describes how genomic variation manifests in Antarctic-lake haloarchaeal communities and provides the basis for future assessments of Antarctic regional and global biogeography of haloarchaea. Electronic supplementary material The online version of this article (10.1186/s40168-018-0495-3) contains supplementary material, which is available to authorized users.

RNA editing is a post-transcriptional or cotranscriptional process that changes the sequence of the precursor transcript by substitutions, insertions, or deletions. Almost all of the land plants undergo RNA editing in organelles (plastids and mitochondria). Although several software tools have been developed to identify RNA editing events, there has been a great challenge to distinguish true RNA editing events from genome variation, sequencing errors, and other factors. Here we introduce REDO, a comprehensive application tool for identifying RNA editing events in plant organelles based on variant call format files from RNA-sequencing data. REDO is a suite of Perl scripts that illustrate a bunch of attributes of RNA editing events in figures and tables. REDO can also detect RNA editing events in multiple samples simultaneously and identify the significant differential proportion of RNA editing loci. Comparing with similar tools, such as REDItools, REDO runs faster with higher accuracy, and more specificity at the cost of slightly lower sensitivity. Moreover, REDO annotates each RNA editing site in RNAs, whereas REDItools reports only possible RNA editing sites in genome, which need additional steps to obtain RNA editing profiles for RNAs. Overall, REDO can identify potential RNA editing sites easily and provide several functions such as detailed annotations, statistics, figures, and significantly differential proportion of RNA editing sites among different samples.

Plasmodium vivax is the most prevalent human malaria parasite outside of Africa. Yet, studies aimed to identify genes with signatures consistent with natural selection are rare. Here, we present a comparative analysis of the pattern of genetic variation of five sequenced isolates of P. vivax and its divergence with two closely related species, Plasmodium cynomolgi and Plasmodium knowlesi, using a set of orthologous genes. In contrast to Plasmodium falciparum, the parasite that causes the most lethal form of human malaria, we did not find significant constraints on the evolution of synonymous sites genome wide in P. vivax. The comparative analysis of polymorphism and divergence across loci allowed us to identify 87 genes with patterns consistent with positive selection, including genes involved in the "exportome" of P. vivax, which are potentially involved in evasion of the host immune system. Nevertheless, we have found a pattern of polymorphism genome wide that is consistent with a significant amount of constraint on the replacement changes and prevalent negative selection. Our analyses also show that silent polymorphism tends to be larger toward the ends of the chromosomes, where many genes involved in antigenicity are located, suggesting that natural selection acts not only by shaping the patterns of variation within the genes but it also affects genome organization.

Apple (Malus domestica Borkh.) is a commercially important fruit worldwide. Detailed information on genomic DNA polymorphisms, which are important for understanding phenotypic traits, is lacking for the apple. We re-sequenced two elite apple varieties, ‘Nagafu No. 2’ and ‘Qinguan,’ which have different characteristics. We identified many genomic variations, including 2,771,129 single nucleotide polymorphisms (SNPs), 82,663 structural variations (SVs), and 1,572,803 insertion/deletions (INDELs) in ‘Nagafu No. 2’ and 2,262,888 SNPs, 63,764 SVs, and 1,294,060 INDELs in ‘Qinguan.’ The ‘SNP,’ ‘INDEL,’ and ‘SV’ distributions were non-random, with variation-rich or -poor regions throughout the genomes. In ‘Nagafu No. 2’ and ‘Qinguan’ there were 171,520 and 147,090 non-synonymous SNPs spanning 23,111 and 21,400 genes, respectively; 3,963 and 3,196 SVs in 3,431 and 2,815 genes, respectively; and 1,834 and 1,451 INDELs in 1,681 and 1,345 genes, respectively. Genetic linkage maps of 190 flowering genes associated with multiple flowering pathways in ‘Nagafu No. 2,’ ‘Qinguan,’ and ‘Golden Delicious,’ identified complex regulatory mechanisms involved in floral induction, flower bud formation, and flowering characteristics, which might reflect the genetic variation of the flowering genes. Expression profiling of key flowering genes in buds and leaves suggested that the photoperiod and autonomous flowering pathways are major contributors to the different floral-associated traits between ‘Nagafu No. 2’ and ‘Qinguan.’ The genome variation data provided a foundation for the further exploration of apple diversity and gene–phenotype relationships, and for future research on molecular breeding to improve apple and related species.

Key Points Hybridization between complementary strands of DNA enables the interrogation of unknown DNA by comparison with DNA of known sequence or genomic context.DNA microarrays containing hundreds of thousands or millions of probes can be used to interrogate genomic sequence. Advances in array-based approaches have enabled detection of the main forms of genomic variation: amplifications, deletions, insertions, rearrangements and base-pair changes.Structural variation in the genome — deletions and duplications, copy number variation, insertions, inversions and chromosomal translocations — can be detected using array comparative genome hybridization. For this application it is often sufficient to have large probes (such as PCR products, cDNA clones or long oligonucleotides) that allow for hybridization despite some sequence differences.When DNA probes are short, hybridization efficiency is acutely sensitive to mismatches; such probes therefore facilitate comparison of genomes at the nucleotide level.Global mapping of insertion sites is performed by isolating the insertion element and its immediately neighbouring DNA. The DNA is then hybridized to a whole-genome array to identify its genomic location.Comprehensive detection of mutations in a complex genome is carried out using whole-genome overlapping tiling arrays, which provide multiple measurements of the effect of an SNP on hybridization.Resequencing arrays use at least four probes per interrogated base and have been used to resequence small genomes.Microarrays offer a relatively inexpensive and efficient means of comparing all known classes of genomic diversity between closely related genomes. However, they are not appropriate for some applications, such as detecting unknown sequences or interrogating highly repetitive or low-complexity sequences., Microarray-based approaches are a fast, flexible and inexpensive alternative to genome sequencing for characterizing the genomes of many individuals within a species. This article reviews the advances that are making microarrays a viable choice for detecting all forms of genetic diversity., The rapid accumulation of complete genomic sequences offers the opportunity to carry out an analysis of inter- and intra-individual genome variation within a species on a routine basis. Sequencing whole genomes requires resources that are currently beyond those of a single laboratory and therefore it is not a practical approach for resequencing hundreds of individual genomes. DNA microarrays present an alternative way to study differences between closely related genomes. Advances in microarray-based approaches have enabled the main forms of genomic variation (amplifications, deletions, insertions, rearrangements and base-pair changes) to be detected using techniques that are readily performed in individual laboratories using simple experimental approaches.

Background Sorghum (Sorghum bicolor) is one of the most important cereal crops globally and a potential energy plant for biofuel production. In order to explore genetic gain for a range of important quantitative traits, such as drought and heat tolerance, grain yield, stem sugar accumulation, and biomass production, via the use of molecular breeding and genomic selection strategies, knowledge of the available genetic variation and the underlying sequence polymorphisms, is required. Results Based on the assembled and annotated genome sequences of Sorghum bicolor (v2.1) and the recently published sorghum re-sequencing data, ~62.9 M SNPs were identified among 48 sorghum accessions and included in a newly developed sorghum genome SNP database SorGSD (http://sorgsd.big.ac.cn). The diverse panel of 48 sorghum lines can be classified into four groups, improved varieties, landraces, wild and weedy sorghums, and a wild relative Sorghum propinquum. SorGSD has a web-based query interface to search or browse SNPs from individual accessions, or to compare SNPs among several lines. The query results can be visualized as text format in tables, or rendered as graphics in a genome browser. Users may find useful annotation from query results including type of SNPs such as synonymous or non-synonymous SNPs, start, stop of splice variants, chromosome locations, and links to the annotation on Phytozome (www.phytozome.net) sorghum genome database. In addition, general information related to sorghum research such as online sorghum resources and literature references can also be found on the website. All the SNP data and annotations can be freely download from the website. Conclusions SorGSD is a comprehensive web-portal providing a database of large-scale genome variation across all racial types of cultivated sorghum and wild relatives. It can serve as a bioinformatics platform for a range of genomics and molecular breeding activities for sorghum and for other C4 grasses.

The most striking characteristic of CHO cells is their adaptability, which enables efficient production of proteins as well as growth under a variety of culture conditions, but also results in genomic and phenotypic instability. To investigate the relative contribution of genomic and epigenetic modifications towards phenotype evolution, comprehensive genome and epigenome data are presented for six related CHO cell lines, both in response to perturbations (different culture conditions and media as well as selection of a specific phenotype with increased transient productivity) and in steady state (prolonged time in culture under constant conditions). Clear transitions were observed in DNA‐methylation patterns upon each perturbation, while few changes occurred over time under constant conditions. Only minor DNA‐methylation changes were observed between exponential and stationary growth phase; however, throughout a batch culture the histone modification pattern underwent continuous adaptation. Variation in genome sequence between the six cell lines on the level of SNPs, InDels, and structural variants is high, both upon perturbation and under constant conditions over time. The here presented comprehensive resource may open the door to improved control and manipulation of gene expression during industrial bioprocesses based on epigenetic mechanisms. Biotechnol. Bioeng. 2016;113: 2241–2253. © 2016 The Authors. Biotechnology and Bioengineering Published by Wiley Periodicals, Inc.

The International Rice Functional Genomics Consortium (IRFGC) has initiated a project to provide the rice research community with access to extensive information on genetic variation present within and between diverse rice cultivars and landraces, as well as the genetic resources to exploit that

The theoretical view that genome aberrations rather than gene mutations cause a majority of cancers has gained increasing support from recent experimental data. Genetic aberration at the chromosome level is a key aspect of genome aberration and the systematic definition of chromosomal aberrations with their impact on genome variation and cancer genome evolution is of great importance. However, traditionally, efforts have focused on recurrent clonal chromosome aberrations (CCAs). The significance of stochastic non-clonal chromosome aberrations (NCCAs) is discussed in this paper with emphasis on the simple types of NCCAs that have until recently been considered "non-significant background". Comparison of various subtypes of transitional and late-stage CCAs with simple and complex types of NCCAs has uncovered a dynamic relationship among NCCAs, CCAs, overall genomic instability, and karyotypic evolution, as well as the stochastic nature of cancer evolution. Here, we review concepts and methodologies to measure NCCAs and discuss the possible causative mechanism and consequences of NCCAs. This study raises challenging questions regarding the concept of cancer evolution driven by stochastic chromosomal aberration mediated genome irregularities that could have repercussions reaching far beyond cancer and organismal genomes.Key words: clonal chromosome aberration (CCA), transitional CCA, non-clonal chromosome aberration (NCCA), karyotype, cancer evolution, genome aberration and variation.

Penicillium digitatum and Penicillium expansum are two closely related fungal plant pathogens causing green and blue mold in harvested fruit, respectively. The two species differ in their host specificity, being P. digitatum restricted to citrus fruits and P. expansum able to infect a wide range of fruits after harvest. Although host-specific Penicillium species have been found to have a smaller gene content, it is so far unclear whether these different host specificities impact genome variation at the intraspecific level. Here we assessed genome variation across four P. digitatum and seven P. expansum isolates from geographically distant regions. Our results show very high similarity (average 0.06 SNPs [single nucleotide polymorphism] per kb) between globally distributed isolates of P. digitatum pointing to a recent expansion of a single lineage. This low level of genetic variation found in our samples contrasts with the higher genetic variability observed in the similarly distributed P. expansum isolates (2.44 SNPs per kb). Patterns of polymorphism in P. expansum indicate that recombination exists between genetically diverged strains. Consistent with the existence of sexual recombination and heterothallism, which was unknown for this species, we identified the two alternative mating types in different P. expansum isolates. Patterns of polymorphism in P. digitatum indicate a recent clonal population expansion of a single lineage that has reached worldwide distribution. We suggest that the contrasting patterns of genomic variation between the two species reflect underlying differences in population dynamics related with host specificities and related agricultural practices. It should be noted, however, that this results should be confirmed with a larger sampling of strains, as new strains may broaden the diversity so far found in P. digitatum. This work was supported in part by Grants from the Spanish Ministry of Economy and Competitiveness: “Centro de Excelencia Severo Ochoa 2013–2017” SEV-2012-0208, and BIO2012-37161 cofounded by European Regional Development Fund (ERDF); from the European Union and ERC Seventh Framework Programme (FP7/2007-2013) under grant agreement ERC-2012-StG-310325, and grant from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No H2020-MSCA-ITN-2014-642095; and Peruvian Ministry of Education: “Beca Presidente de la República” (2013-III).

Given the importance of Africa to studies of human origins and disease susceptibility, detailed characterization of African genetic diversity is needed. The African Genome Variation Project provides a resource with which to design, implement and interpret genomic studies in sub-Saharan Africa and worldwide. The African Genome Variation Project represents dense genotypes from 1,481 individuals and whole-genome sequences from 320 individuals across sub-Saharan Africa. Using this resource, we find novel evidence of complex, regionally distinct hunter-gatherer and Eurasian admixture across sub-Saharan Africa. We identify new loci under selection, including loci related to malaria susceptibility and hypertension. We show that modern imputation panels (sets of reference genotypes from which unobserved or missing genotypes in study sets can be inferred) can identify association signals at highly differentiated loci across populations in sub-Saharan Africa. Using whole-genome sequencing, we demonstrate further improvements in imputation accuracy, strengthening the case for large-scale sequencing efforts of diverse African haplotypes. Finally, we present an efficient genotype array design capturing common genetic variation in Africa.

In response to a need for a general catalog of genome variation to address the large-scale sampling designs required by association studies, gene mapping and evolutionary biology, the National Center for Biotechnology Information (NCBI) has established the dbSNP database [S.T.Sherry, M.Ward and K.Sirotkin (1999) Genome Res., 9, 677–679]. Submissions to dbSNP will be integrated with other sources of information at NCBI such as GenBank, PubMed, LocusLink and the Human Genome Project data. The complete contents of dbSNP are available to the public at website: http://www.ncbi.nlm.nih.gov/SNP. The complete contents of dbSNP can also be downloaded in multiple formats via anonymous FTP at ftp://ncbi.nlm.nih.gov/snp/.

DNA methylation is an essential epigenetic mark whose role in gene regulation and its dependency on genomic sequence and environment are not fully understood. In this study we provide novel insights into the mechanistic relationships between genetic variation, DNA methylation and transcriptome sequencing data in three different cell-types of the GenCord human population cohort. We find that the association between DNA methylation and gene expression variation among individuals are likely due to different mechanisms from those establishing methylation-expression patterns during differentiation. Furthermore, cell-type differential DNA methylation may delineate a platform in which local inter-individual changes may respond to or act in gene regulation. We show that unlike genetic regulatory variation, DNA methylation alone does not significantly drive allele specific expression. Finally, inferred mechanistic relationships using genetic variation as well as correlations with TF abundance reveal both a passive and active role of DNA methylation to regulatory interactions influencing gene expression. DOI: http://dx.doi.org/10.7554/eLife.00523.001, eLife digest Variations occur throughout our genome. These variations can cause genes to be expressed (switched on) in slightly different ways among individuals. Moreover, the same gene can also be expressed in different ways in different cells within an individual. A third level of variation is supplied by epigenetic markers: these are molecules that bind to the DNA at specific points and can have profound effects on the expression of nearby genes. One such epigenetic marker is the addition of a methyl group to a cytosine base, a process that is known as DNA methylation. DNA methylation usually happens when a cytosine base is next to a guanine base, forming a CpG site. In mammals, most CpG sites have methyl groups attached, although regions with a lot of CpG sites (called CpG islands) are mostly unmethylated. Initial studies suggested that methylation prevented particular genes from being expressed, but more recent work has indicated that methylation can be associated with both reduced and increased expression of genes. Moreover, it is not clear if this association is active (i.e., changes in methylation drive changes in gene expression) or passive (DNA methylation is the result of gene regulation). Now, Gutierrez-Arcelus et al. have carried out a large-scale study to clarify the relationships between three different types of gene-related variations among individuals. They extracted fibroblasts, T-cells and lymphoblastoid cells from the umbilical cords of 204 babies, and analysed them for variations in DNA sequence, gene expression and DNA methylation. Their results show that the associations between the three are more complex than was previously thought. Gutierrez-Arcelus et al. show that the mechanisms that control the association between the variations in DNA methylation and gene expression in individuals are likely to be different to those that are responsible for the establishment of methylation patterns during the process of cell differentiation. They also find that the association between DNA methylation and gene expression can be either active or passive, and can depend on the context in which they occur in our genome. Finally, where the two copies or alleles of a gene are not equally expressed in a given cell, the difference in expression is primarily regulated by DNA sequence variation, with DNA methylation having little or no role on its own. Equally complex interactions and effects are expected in further studies of genetic and epigenetic variation. DOI: http://dx.doi.org/10.7554/eLife.00523.002

Genomic variation, through effects on gene structure and expression, plays an important role in understanding disease predisposition, biology and clinical response to therapy. Transforming this knowledge into clinically relevant information that tailors interventions to an individual's specific genetic, physical, social and environmental profile is challenging. To illustrate how research initiatives at preclinical phases of development are attempting to address clinically important issues in oncology, six clinical problems related to cancers of the colon, prostate, breast, pancreas and brain (medulloblastoma) as well as metastatic disease of different origins are described. A unifying theme across applications is that healthy individuals previously indistinguishable in regards to cancer risk and patients with cancer previously categorized as similar with regard to prognosis or drug response are being stratified into more refined subgroups with different clinical profiles. Effective matching of a broad range of tests with more tailored strategies for prevention and/or treatment will require well-designed clinical studies to evaluate benefits and costs.

Variations occur throughout our genome. These variations can cause genes to be expressed (switched on) in slightly different ways among individuals. Moreover, the same gene can also be expressed in different ways in different cells within an individual. A third level of variation is supplied by epigenetic markers: these are molecules that bind to the DNA at specific points and can have profound effects on the expression of nearby genes. One such epigenetic marker is the addition of a methyl group to a cytosine base, a process that is known as DNA methylation. DNA methylation usually happens when a cytosine base is next to a guanine base, forming a CpG site. In mammals, most CpG sites have methyl groups attached, although regions with a lot of CpG sites (called CpG islands) are mostly unmethylated. Initial studies suggested that methylation prevented particular genes from being expressed, but more recent work has indicated that methylation can be associated with both reduced and increased expression of genes. Moreover, it is not clear if this association is active (i.e., changes in methylation drive changes in gene expression) or passive (DNA methylation is the result of gene regulation). Now, Gutierrez-Arcelus et al. have carried out a large-scale study to clarify the relationships between three different types of gene-related variations among individuals. They extracted fibroblasts, T-cells and lymphoblastoid cells from the umbilical cords of 204 babies, and analysed them for variations in DNA sequence, gene expression and DNA methylation. Their results show that the associations between the three are more complex than was previously thought. Gutierrez-Arcelus et al. show that the mechanisms that control the association between the variations in DNA methylation and gene expression in individuals are likely to be different to those that are responsible for the establishment of methylation patterns during the process of cell differentiation. They also find that the association between DNA methylation and gene expression can be either active or passive, and can depend on the context in which they occur in our genome. Finally, where the two copies or alleles of a gene are not equally expressed in a given cell, the difference in expression is primarily regulated by DNA sequence variation, with DNA methylation having little or no role on its own. Equally complex interactions and effects are expected in further studies of genetic and epigenetic variation.

Most vegetables in our daily diet are the result of domestication and breeding. Here we report a map of genome variation of a major vegetable that encompasses 3.6 million variants generated by deep resequencing of 115 cucumber lines sampled from 3342 accessions worldwide. Comparative analysis suggests that vegetable crops underwent narrower bottlenecks during domestication than grain crops. We identified 112 putative domestication sweeps; one of these regions contains a gene involved in the loss of bitterness in fruits an essential domestication trait of cucumber. We also investigated the genomic basis of divergence among the cultivated populations and subsequently discovered a natural genetic variant in a ß carotene hydroxylase gene that could be used to breed cucumbers with enhanced nutritional value. The genomic history of cucumber evolution uncovered here provides the basis for future genomics enabled breeding.

The advances in bioinformatics required to annotate human genomic variants and to place them in public data repositories have not kept pace with their discovery. Moreover, a law of diminishing returns has begun to operate both in terms of data publication and submission. Although the continued deposition of such data in the public domain is essential to maximize both their scientific and clinical utility, rewards for data sharing are few, representing a serious practical impediment to data submission. To date, two main strategies have been adopted as a means to encourage the submission of human genomic variant data: (1) database journal linkups involving the affiliation of a scientific journal with a publicly available database and (2) microattribution, involving the unambiguous linkage of data to their contributors via a unique identifier. The latter could in principle lead to the establishment of a microcitation-tracking system that acknowledges individual endeavor and achievement. Both approaches could incentivize potential data contributors, thereby encouraging them to share their data with the scientific community. Here, we summarize and critically evaluate approaches that have been proposed to address current deficiencies in data attribution and discuss ways in which they could become more widely adopted as novel scientific publication modalities. Hum Mutat 33:15031512, 2012. (c) 2012 Wiley Periodicals, Inc.

Ultra-high-throughput sequencing (UHTS) techniques are evolving rapidly and may soon become an affordable and routine tool for sequencing plant DNA, even in smaller plant biology labs. Here we review recent insights into intraspecific genome variation gained from UHTS, which offers a glimpse of the rather unexpected levels of structural variability among Arabidopsis thaliana accessions. The challenges that will need to be addressed to efficiently assemble and exploit this information are also discussed.

Understanding genetic variation between populations is important because it affects the portability of human genome wide analytical methods. We compared genetic variation and substructure between Malawians and other African and non-African HapMap populations. Allele frequencies and adjacent linkage disequilibrium (LD) were measured for 617,715 single nucleotide polymorphisms (SNPs) across subject genomes. Allele frequencies in the Malawian population (N = 226) were highly correlated with allele frequencies in HapMap populations of African Ancestry (AFA, N = 376), namely Yoruban in Ibadan, Nigeria (Spearman’s r2 = 0.97), Luhya in Webuye, Kenya (r2 = 0.97), African Americans in the southwest United States (r2 = 0.94), and Maasai in Kinyawa, Kenya (r2 = 0.91). This correlation was much lower between Malawians and other ancestry populations (r2 < 0.52). LD correlations between Malawians and HapMap populations were strongest for the populations of African ancestry (AFA r2 > 0.82, other ancestries r2 < 0.57). Principal components analyses revealed little population substructure within our Malawi sample but provided clear distinction between Malawians, AFA populations, and two European populations. Five SNPs within the lactase gene (LCT) had substantially different allele frequencies between the Malawi population and Maasai in Kenyawa, Kenya (rs3769013, rs730005, rs3769012, rs2304370; p values < 1×10−33).

Background The first Korean individual diploid genome sequence data (KOREF) was publicized in December 2008. Results A Korean genome variation analysis and browsing server (Gevab) was constructed as a database and web server for the exploration and downloading of Korean personal genome(s). Information in the Gevab includes SNPs, short indels, and structural variation (SV) and comparison analysis between the NCBI human reference and the Korean genome(s). The user can find information on assembled consensus sequences, sequenced short reads, genetic variations, and relationships between genotype and phenotypes. Conclusion This server is openly and publicly available online at http://koreagenome.org/en/ or directly http://gevab.org.

While high quality information regarding variation in genes is currently available in locus-specific or specialized mutation databases, the need remains for a general catalog of genome variation to address the large-scale sampling designs required by association studies, gene mapping, and evolutionary biology. In response to this need, the National Center for Biotechnology Information (NCBI) has established the dbSNP database http://ncbi. nlm.nih.gov/SNP/ to serve as a generalized, central variation database. Submissions to dbSNP will be integrated with other sources of information at NCBI such as GenBank, PubMed, LocusLink, and the Human Genome Project data, and the complete contents of dbSNP are available to the public via anonymous FTP. Hum Mutat 15:68-75, 2000. Published 2000 Wiley-Liss, Inc.

The recent cloning of several disease genes has identified the instability of trinucleotide repeats as a fundamental mechanism for variation within the human genome. This mutation mechanism explains the unique inheritance characteristics of the diseases it causes, and there is a significant potential that this mechanism is involved in the pathogenesis of other, as yet uncharacterized, genetic diseases.

Background Bursaphelenchus xylophilus is an emerging pathogenic nematode that is responsible for a devastating epidemic of pine wilt disease across Asia and Europe. In this study, we report the first genome-wide variation analysis of the nematode with an aim to obtain a full picture of its diversity. Methods We sequenced six key B. xylophilus strains using Illumina HiSeq sequencer. All the strains were isolated in Japan and have been widely used in previous studies. Detection of genomic variations were done by mapping the reads to the reference genome. Results Over 3 Mb of genetic variations, accounting for 4.1 % of the total genome, were detected as single nucleotide polymorphisms or small indels, suggesting multiple introductions of this invaded species from its native area into the country. The high level of genetic diversity of the pine wood nematode was related to its pathogenicity and ecological trait differences. Moreover, we identified a gene set affected by genomic variation, and functional annotation of those genes indicated that some of them had potential roles in pathogenesis. Conclusions This study provides an important resource for understanding the population structure, pathogenicity and evolutionary ecology of the nematode, and further analysis based on this study with geographically diverse B. xylophilus populations will greatly accelerate our understanding of the complex evolutionary/epidemic history of this emerging pathogen. Electronic supplementary material The online version of this article (doi:10.1186/s12864-015-2085-0) contains supplementary material, which is available to authorized users.