@article{14689,
  author       = {Ing-Simmons, Elizabeth and Machnik, Nick N and Vaquerizas, Juan M.},
  issn         = {1546-1718},
  journal      = {Nature Genetics},
  number       = {12},
  pages        = {2053--2055},
  publisher    = {Springer Nature},
  title        = {{Reply to: Revisiting the use of structural similarity index in Hi-C}},
  doi          = {10.1038/s41588-023-01595-5},
  volume       = {55},
  year         = {2023},
}

@article{12158,
  abstract     = {Post-translational histone modifications modulate chromatin activity to affect gene expression. How chromatin states underlie lineage choice in single cells is relatively unexplored. We develop sort-assisted single-cell chromatin immunocleavage (sortChIC) and map active (H3K4me1 and H3K4me3) and repressive (H3K27me3 and H3K9me3) histone modifications in the mouse bone marrow. During differentiation, hematopoietic stem and progenitor cells (HSPCs) acquire active chromatin states mediated by cell-type-specifying transcription factors, which are unique for each lineage. By contrast, most alterations in repressive marks during differentiation occur independent of the final cell type. Chromatin trajectory analysis shows that lineage choice at the chromatin level occurs at the progenitor stage. Joint profiling of H3K4me1 and H3K9me3 demonstrates that cell types within the myeloid lineage have distinct active chromatin but share similar myeloid-specific heterochromatin states. This implies a hierarchical regulation of chromatin during hematopoiesis: heterochromatin dynamics distinguish differentiation trajectories and lineages, while euchromatin dynamics reflect cell types within lineages.},
  author       = {Zeller, Peter and Yeung, Jake and Viñas Gaza, Helena and de Barbanson, Buys Anton and Bhardwaj, Vivek and Florescu, Maria and van der Linden, Reinier and van Oudenaarden, Alexander},
  issn         = {1546-1718},
  journal      = {Nature Genetics},
  keywords     = {Genetics},
  pages        = {333--345},
  publisher    = {Springer Nature},
  title        = {{Single-cell sortChIC identifies hierarchical chromatin dynamics during hematopoiesis}},
  doi          = {10.1038/s41588-022-01260-3},
  volume       = {55},
  year         = {2023},
}

@article{7722,
  abstract     = {We develop a Bayesian mixed linear model that simultaneously estimates single-nucleotide polymorphism (SNP)-based heritability, polygenicity (proportion of SNPs with nonzero effects), and the relationship between SNP effect size and minor allele frequency for complex traits in conventionally unrelated individuals using genome-wide SNP data. We apply the method to 28 complex traits in the UK Biobank data (N = 126,752) and show that on average, 6% of SNPs have nonzero effects, which in total explain 22% of phenotypic variance. We detect significant (P < 0.05/28) signatures of natural selection in the genetic architecture of 23 traits, including reproductive, cardiovascular, and anthropometric traits, as well as educational attainment. The significant estimates of the relationship between effect size and minor allele frequency in complex traits are consistent with a model of negative (or purifying) selection, as confirmed by forward simulation. We conclude that negative selection acts pervasively on the genetic variants associated with human complex traits.},
  author       = {Zeng, Jian and de Vlaming, Ronald and Wu, Yang and Robinson, Matthew Richard and Lloyd-Jones, Luke R. and Yengo, Loic and Yap, Chloe X. and Xue, Angli and Sidorenko, Julia and McRae, Allan F. and Powell, Joseph E. and Montgomery, Grant W. and Metspalu, Andres and Esko, Tonu and Gibson, Greg and Wray, Naomi R. and Visscher, Peter M. and Yang, Jian},
  issn         = {1061-4036},
  journal      = {Nature Genetics},
  number       = {5},
  pages        = {746--753},
  publisher    = {Springer Nature},
  title        = {{Signatures of negative selection in the genetic architecture of human complex traits}},
  doi          = {10.1038/s41588-018-0101-4},
  volume       = {50},
  year         = {2018},
}

@article{12193,
  abstract     = {DNA methylation regulates eukaryotic gene expression and is extensively reprogrammed during animal development. However, whether developmental methylation reprogramming during the sporophytic life cycle of flowering plants regulates genes is presently unknown. Here we report a distinctive gene-targeted RNA-directed DNA methylation (RdDM) activity in the Arabidopsis thaliana male sexual lineage that regulates gene expression in meiocytes. Loss of sexual-lineage-specific RdDM causes mis-splicing of the MPS1 gene (also known as PRD2), thereby disrupting meiosis. Our results establish a regulatory paradigm in which de novo methylation creates a cell-lineage-specific epigenetic signature that controls gene expression and contributes to cellular function in flowering plants.},
  author       = {Walker, James and Gao, Hongbo and Zhang, Jingyi and Aldridge, Billy and Vickers, Martin and Higgins, James D. and Feng, Xiaoqi},
  issn         = {1546-1718},
  journal      = {Nature Genetics},
  keywords     = {Genetics},
  number       = {1},
  pages        = {130--137},
  publisher    = {Nature Research},
  title        = {{Sexual-lineage-specific DNA methylation regulates meiosis in Arabidopsis}},
  doi          = {10.1038/s41588-017-0008-5},
  volume       = {50},
  year         = {2017},
}

@article{7737,
  abstract     = {Genome-wide association studies (GWAS) have identified thousands of genetic variants associated with human complex traits. However, the genes or functional DNA elements through which these variants exert their effects on the traits are often unknown. We propose a method (called SMR) that integrates summary-level data from GWAS with data from expression quantitative trait locus (eQTL) studies to identify genes whose expression levels are associated with a complex trait because of pleiotropy. We apply the method to five human complex traits using GWAS data on up to 339,224 individuals and eQTL data on 5,311 individuals, and we prioritize 126 genes (for example, TRAF1 and ANKRD55 for rheumatoid arthritis and SNX19 and NMRAL1 for schizophrenia), of which 25 genes are new candidates; 77 genes are not the nearest annotated gene to the top associated GWAS SNP. These genes provide important leads to design future functional studies to understand the mechanism whereby DNA variation leads to complex trait variation.},
  author       = {Zhu, Zhihong and Zhang, Futao and Hu, Han and Bakshi, Andrew and Robinson, Matthew Richard and Powell, Joseph E and Montgomery, Grant W and Goddard, Michael E and Wray, Naomi R and Visscher, Peter M and Yang, Jian},
  issn         = {1061-4036},
  journal      = {Nature Genetics},
  number       = {5},
  pages        = {481--487},
  publisher    = {Springer Nature},
  title        = {{Integration of summary data from GWAS and eQTL studies predicts complex trait gene targets}},
  doi          = {10.1038/ng.3538},
  volume       = {48},
  year         = {2016},
}

@article{7742,
  abstract     = {Across-nation differences in the mean values for complex traits are common1,2,3,4,5,6,7,8, but the reasons for these differences are unknown. Here we find that many independent loci contribute to population genetic differences in height and body mass index (BMI) in 9,416 individuals across 14 European countries. Using discovery data on over 250,000 individuals and unbiased effect size estimates from 17,500 sibling pairs, we estimate that 24% (95% credible interval (CI) = 9%, 41%) and 8% (95% CI = 4%, 16%) of the captured additive genetic variance for height and BMI, respectively, reflect population genetic differences. Population genetic divergence differed significantly from that in a null model (height, P < 3.94 × 10−8; BMI, P < 5.95 × 10−4), and we find an among-population genetic correlation for tall and slender individuals (r = −0.80, 95% CI = −0.95, −0.60), consistent with correlated selection for both phenotypes. Observed differences in height among populations reflected the predicted genetic means (r = 0.51; P < 0.001), but environmental differences across Europe masked genetic differentiation for BMI (P < 0.58).},
  author       = {Robinson, Matthew Richard and Hemani, Gibran and Medina-Gomez, Carolina and Mezzavilla, Massimo and Esko, Tonu and Shakhbazov, Konstantin and Powell, Joseph E and Vinkhuyzen, Anna and Berndt, Sonja I and Gustafsson, Stefan and Justice, Anne E and Kahali, Bratati and Locke, Adam E and Pers, Tune H and Vedantam, Sailaja and Wood, Andrew R and van Rheenen, Wouter and Andreassen, Ole A and Gasparini, Paolo and Metspalu, Andres and Berg, Leonard H van den and Veldink, Jan H and Rivadeneira, Fernando and Werge, Thomas M and Abecasis, Goncalo R and Boomsma, Dorret I and Chasman, Daniel I and de Geus, Eco J C and Frayling, Timothy M and Hirschhorn, Joel N and Hottenga, Jouke Jan and Ingelsson, Erik and Loos, Ruth J F and Magnusson, Patrik K E and Martin, Nicholas G and Montgomery, Grant W and North, Kari E and Pedersen, Nancy L and Spector, Timothy D and Speliotes, Elizabeth K and Goddard, Michael E and Yang, Jian and Visscher, Peter M},
  issn         = {1061-4036},
  journal      = {Nature Genetics},
  number       = {11},
  pages        = {1357--1362},
  publisher    = {Springer Nature},
  title        = {{Population genetic differentiation of height and body mass index across Europe}},
  doi          = {10.1038/ng.3401},
  volume       = {47},
  year         = {2015},
}

@misc{9504,
  author       = {Zilberman, Daniel},
  booktitle    = {Nature Genetics},
  issn         = {1546-1718},
  number       = {4},
  pages        = {442--443},
  publisher    = {Nature Publishing Group},
  title        = {{The human promoter methylome}},
  doi          = {10.1038/ng0407-442},
  volume       = {39},
  year         = {2007},
}

@article{9505,
  abstract     = {Cytosine methylation, a common form of DNA modification that antagonizes transcription, is found at transposons and repeats in vertebrates, plants and fungi. Here we have mapped DNA methylation in the entire Arabidopsis thaliana genome at high resolution. DNA methylation covers transposons and is present within a large fraction of A. thaliana genes. Methylation within genes is conspicuously biased away from gene ends, suggesting a dependence on RNA polymerase transit. Genic methylation is strongly influenced by transcription: moderately transcribed genes are most likely to be methylated, whereas genes at either extreme are least likely. In turn, transcription is influenced by methylation: short methylated genes are poorly expressed, and loss of methylation in the body of a gene leads to enhanced transcription. Our results indicate that genic transcription and DNA methylation are closely interwoven processes.},
  author       = {Zilberman, Daniel and Gehring, Mary and Tran, Robert K. and Ballinger, Tracy and Henikoff, Steven},
  issn         = {1546-1718},
  journal      = {Nature Genetics},
  number       = {1},
  pages        = {61--69},
  publisher    = {Nature Publishing Group},
  title        = {{Genome-wide analysis of Arabidopsis thaliana DNA methylation uncovers an interdependence between methylation and transcription}},
  doi          = {10.1038/ng1929},
  volume       = {39},
  year         = {2006},
}