Since 1999, various forward- and reverse-genetic approaches have uncovered nearly 200 genes required for symbiotic nitrogen fixation (SNF) in legumes. These discoveries advanced our understanding of ...the evolution of SNF in plants and its relationship to other beneficial endosymbioses, signaling between plants and microbes, the control of microbial infection of plant cells, the control of plant cell division leading to nodule development, autoregulation of nodulation, intracellular accommodation of bacteria, nodule oxygen homeostasis, the control of bacteroid differentiation, metabolism and transport supporting symbiosis, and the control of nodule senescence. This review catalogs and contextualizes all of the plant genes currently known to be required for SNF in two model legume species,
and
, and two crop species,
(soybean) and
(common bean). We also briefly consider the future of SNF genetics in the era of pan-genomics and genome editing.
Efforts to link variation in the human genome to phenotypes have progressed at a tremendous pace in recent decades. Most human traits have been shown to be affected by a large number of genetic ...variants across the genome. To interpret these associations and to use them reliably-in particular for phenotypic prediction-a better understanding of the many sources of genotype-phenotype associations is necessary. We summarize the progress that has been made in this direction in humans, notably in decomposing direct and indirect genetic effects as well as population structure confounding. We discuss the natural next steps in data collection and methodology development, with a focus on what can be gained by analyzing genotype and phenotype data from close relatives.
Copy number variation (CNV) analysis is an integral component of the study of human genomes in both research and clinical settings. Array-based CNV analysis is the current first-tier approach in ...clinical cytogenetics. Decreasing costs in high-throughput sequencing and cloud computing have opened doors for the development of sequencing-based CNV analysis pipelines with fast turnaround times. We carry out a systematic and quantitative comparative analysis for several low-coverage whole-genome sequencing (WGS) strategies to detect CNV in the human genome.
We compared the CNV detection capabilities of WGS strategies (short insert, 3 kb insert mate pair and 5 kb insert mate pair) each at 1×, 3× and 5× coverages relative to each other and to 17 currently used high-density oligonucleotide arrays. For benchmarking, we used a set of gold standard (GS) CNVs generated for the 1000 Genomes Project CEU subject NA12878.
Overall, low-coverage WGS strategies detect drastically more GS CNVs compared with arrays and are accompanied with smaller percentages of CNV calls without validation. Furthermore, we show that WGS (at ≥1× coverage) is able to detect all seven GS deletion CNVs >100 kb in NA12878, whereas only one is detected by most arrays. Lastly, we show that the much larger 15 Mbp Cri du chat deletion can be readily detected with short-insert paired-end WGS at even just 1× coverage.
CNV analysis using low-coverage WGS is efficient and outperforms the array-based analysis that is currently used for clinical cytogenetics.
Epigenetic modifications, including DNA methylation, represent a potential mechanism for environmental impacts on human disease. Maternal smoking in pregnancy remains an important public health ...problem that impacts child health in a myriad of ways and has potential lifelong consequences. The mechanisms are largely unknown, but epigenetics most likely plays a role. We formed the Pregnancy And Childhood Epigenetics (PACE) consortium and meta-analyzed, across 13 cohorts (n = 6,685), the association between maternal smoking in pregnancy and newborn blood DNA methylation at over 450,000 CpG sites (CpGs) by using the Illumina 450K BeadChip. Over 6,000 CpGs were differentially methylated in relation to maternal smoking at genome-wide statistical significance (false discovery rate, 5%), including 2,965 CpGs corresponding to 2,017 genes not previously related to smoking and methylation in either newborns or adults. Several genes are relevant to diseases that can be caused by maternal smoking (e.g., orofacial clefts and asthma) or adult smoking (e.g., certain cancers). A number of differentially methylated CpGs were associated with gene expression. We observed enrichment in pathways and processes critical to development. In older children (5 cohorts, n = 3,187), 100% of CpGs gave at least nominal levels of significance, far more than expected by chance (p value < 2.2 × 10−16). Results were robust to different normalization methods used across studies and cell type adjustment. In this large scale meta-analysis of methylation data, we identified numerous loci involved in response to maternal smoking in pregnancy with persistence into later childhood and provide insights into mechanisms underlying effects of this important exposure.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
The number of Mendelian randomization (MR) analyses including large numbers of genetic variants is rapidly increasing. This is due to the proliferation of genome‐wide association studies, and the ...desire to obtain more precise estimates of causal effects. Since it is unlikely that all genetic variants will be valid instrumental variables, several robust methods have been proposed. We compare nine robust methods for MR based on summary data that can be implemented using standard statistical software. Methods were compared in three ways: by reviewing their theoretical properties, in an extensive simulation study, and in an empirical example. In the simulation study, the best method, judged by mean squared error was the contamination mixture method. This method had well‐controlled Type 1 error rates with up to 50% invalid instruments across a range of scenarios. Other methods performed well according to different metrics. Outlier‐robust methods had the narrowest confidence intervals in the empirical example. With isolated exceptions, all methods performed badly when over 50% of the variants were invalid instruments. Our recommendation for investigators is to perform a variety of robust methods that operate in different ways and rely on different assumptions for valid inferences to assess the reliability of MR analyses.
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FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
Studies in model organisms have yielded considerable insights into the etiology of disease and our understanding of evolutionary processes. Caenorhabditis elegans is among the most powerful model ...organisms used to understand biology. However, C. elegans is not used as extensively as other model organisms to investigate how natural variation shapes traits, especially through the use of genome-wide association (GWA) analyses. Here, we introduce a new platform, the C. elegans Natural Diversity Resource (CeNDR) to enable statistical genetics and genomics studies of C. elegans and to connect the results to human disease. CeNDR provides the research community with wild strains, genome-wide sequence and variant data for every strain, and a GWA mapping portal for studying natural variation in C. elegans Additionally, researchers outside of the C. elegans community can benefit from public mappings and integrated tools for comparative analyses. CeNDR uses several databases that are continually updated through the addition of new strains, sequencing data, and association mapping results. The CeNDR data are accessible through a freely available web portal located at http://www.elegansvariation.org or through an application programming interface.
Modern tomatoes have narrow genetic diversity limiting their improvement potential. We present a tomato pan-genome constructed using genome sequences of 725 phylogenetically and geographically ...representative accessions, revealing 4,873 genes absent from the reference genome. Presence/absence variation analyses reveal substantial gene loss and intense negative selection of genes and promoters during tomato domestication and improvement. Lost or negatively selected genes are enriched for important traits, especially disease resistance. We identify a rare allele in the TomLoxC promoter selected against during domestication. Quantitative trait locus mapping and analysis of transgenic plants reveal a role for TomLoxC in apocarotenoid production, which contributes to desirable tomato flavor. In orange-stage fruit, accessions harboring both the rare and common TomLoxC alleles (heterozygotes) have higher TomLoxC expression than those homozygous for either and are resurgent in modern tomatoes. The tomato pan-genome adds depth and completeness to the reference genome, and is useful for future biological discovery and breeding.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Osteosarcoma is the most common primary malignancy of bone, typically presenting in the first or second decade of life. Unfortunately, clinical outcomes for osteosarcoma patients have not ...substantially improved in over 30 years. This stagnation in therapeutic advances is perhaps explained by the genetic, epigenetic, and biological complexities of this rare tumor. In this review we provide a general background on the biology of osteosarcoma and the clinical status quo. We go on to enumerate the genetic and epigenetic defects identified in osteosarcoma. Finally, we discuss ongoing large-scale studies in the field and potential new therapies that are currently under investigation.
Linear mixed models are a powerful statistical tool for identifying genetic associations and avoiding confounding. However, existing methods are computationally intractable in large cohorts and may ...not optimize power. All existing methods require time cost O(MN(2)) (where N is the number of samples and M is the number of SNPs) and implicitly assume an infinitesimal genetic architecture in which effect sizes are normally distributed, which can limit power. Here we present a far more efficient mixed-model association method, BOLT-LMM, which requires only a small number of O(MN) time iterations and increases power by modeling more realistic, non-infinitesimal genetic architectures via a Bayesian mixture prior on marker effect sizes. We applied BOLT-LMM to 9 quantitative traits in 23,294 samples from the Women's Genome Health Study (WGHS) and observed significant increases in power, consistent with simulations. Theory and simulations show that the boost in power increases with cohort size, making BOLT-LMM appealing for genome-wide association studies in large cohorts.
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DOBA, IJS, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SBMB, UILJ, UKNU, UL, UM, UPUK
Whole‐exome sequencing (WES) and whole‐genome sequencing (WGS) studies are underway to investigate the impact of genetic variants on complex diseases and traits. It is customary to perform ...single‐variant association tests for common variants and region‐based association tests for rare variants. The latter may target variants with similar or opposite effects, interrogate variants with different frequencies or different functional annotations, and examine a variety of regions. The large number of tests that are performed necessitates adjustment for multiple testing. The conventional Bonferroni correction is overly conservative as the test statistics are correlated. To address this challenge, we propose a simple and accurate method based on parametric bootstrap to assess genomewide significance. We show that the correlations of the test statistics are determined primarily by the genotypes, such that the same significance threshold can be used in different studies that share a common sequencing platform. We demonstrate the usefulness of the proposed method with WES data from the National Heart, Lung, and Blood Institute Exome Sequencing Project and WGS data from the 1000 Genomes Project. We recommend the p value of
5
×
1
0
−
9 as the genomewide significance threshold for testing all common and low‐frequency variants (MAFs
≥ 0.1%) in the human genome.
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FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
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