Cited by 747

The DOI matches its Crossref record; 13 of the 13 references it cites were found in a registry or an index.

De novo assembly, annotation, and comparative analysis of 26 diverse maize genomes

Hufford, Matthew B., Seetharam, Arun S., Woodhouse, Margaret R., Chougule, Kapeel M., Ou, Shujun, Liu, Jianing, Ricci, William A., Guo, Tingting, Olson, Andrew, Qiu, Yinjie, Della Coletta, Rafael, Tittes, Silas, Hudson, Asher I., Marand, Alexandre P., Wei, Sharon, Lu, Zhenyuan, Wang, Bo, Tello-Ruiz, Marcela K., Piri, Rebecca D., Wang, Na, Kim, Dong won, Zeng, Yibing, O’Connor, Christine H., Li, Xianran, Gilbert, Amanda M., Baggs, Erin, Krasileva, Ksenia V., Portwood, John L., Cannon, Ethalinda K. S., Andorf, Carson M., Manchanda, Nancy, Snodgrass, Samantha J., Hufnagel, David E., Jiang, Qiuhan, Pedersen, Sarah, Syring, Michael L., Kudrna, David A., Llaca, Victor, Fengler, Kevin, Schmitz, Robert J., Ross-Ibarra, Jeffrey, Yu, Jianming, Gent, Jonathan I., Hirsch, Candice N., Ware, Doreen, Dawe, R. Kelly·2021·Science

Published version of a preprint

Abstract

An a-maize-ing set of genomes: Maize is an important crop cultivated worldwide. As maize spread across the world, selection for local environments resulted in variation, but the impact on differences between the genome has not been quantified. By producing high-quality genomic sequences of the 26 lines used in the maize nested association mapping panel, Hufford et al . map important traits and demonstrate the diversity of maize. Examining RNA and methylation of genes across accessions, the authors identified a core set of maize genes. Beyond this core set, comparative analysis across lines identified high levels of variation in the total set of genes, the maize pan-genome. The value of this resource was further exemplified by mapping quantitative traits of interest, including those related to pathogen resistance. —LMZ

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1126/science.abg5289

Cites

13 of 13 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • With GENESPACE and the recently released NAM parent genomes, it is now possible to evaluate candidate genes present in the genomes of other NAM founder lines but either absent or unannotated in the B73 reference genome.

    “however, with GENESPACE and the recently released NAM parent genomes (Hufford et al., 2021), it is now possible to evaluate candidate genes present in the genomes of other NAM founder lines but either absent or unannotated in the B73 reference genome.”

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Flagged first, then by citations

Research works printed but not linked: 157

  1. 10.1105/tpc.113.119982 · DOI
  2. 10.1105/tpc.16.00353 · DOI
  3. 10.1038/srep18936 · DOI
  4. 10.1038/ncomms7914 · DOI
  5. 10.1038/s41477-019-0547-0 · DOI
  6. 10.1038/s41588-018-0182-0 · DOI
  7. 10.1038/s41588-020-0671-9 · DOI
  8. 10.1038/s41588-019-0427-6 · DOI
  9. 10.1186/s13059-021-02396-x · DOI
  10. 10.1038/s41588-018-0158-0 · DOI
  11. 10.1126/science.1174320 · DOI
  12. 10.1111/j.1365-313X.2005.02591.x · DOI
  13. 10.1534/genetics.107.074245 · DOI
  14. 10.1371/journal.pgen.1004845 · DOI
  15. 10.1105/tpc.113.114793 · DOI
  16. 10.1105/tpc.18.00299 · DOI
  17. 10.1038/nature22971 · DOI
  18. 10.1093/bioinformatics/btv351 · DOI · Paper page
  19. 10.1093/nar/gky730 · DOI
  20. 10.1038/s41467-020-16037-7 · DOI
  21. 10.1186/1471-2105-10-67 · DOI
  22. 10.1104/pp.114.245027 · DOI
  23. 10.1101/gr.2332504 · DOI
  24. 10.1016/j.molp.2015.04.004 · DOI
  25. 10.1073/pnas.1101368108 · DOI
  26. 10.1371/journal.pbio.1000409 · DOI
  27. 10.1093/gbe/evs009 · DOI
  28. 10.1105/tpc.110.074526 · DOI
  29. 10.1111/tpj.13765 · DOI
  30. 10.1534/genetics.111.137349 · DOI
  31. 10.1038/nplants.2016.84 · DOI
  32. 10.1038/s41477-018-0136-7 · DOI · Paper page
  33. 10.1186/s13059-019-1905-y · DOI
  34. 10.1371/journal.pgen.1000732 · DOI
  35. 10.1371/journal.pgen.1007162 · DOI
  36. 10.1016/j.cell.2018.03.009 · DOI
  37. 10.1159/000314342 · DOI
  38. 10.1073/pnas.1522008113 · DOI
  39. 10.1093/genetics/iyab020 · DOI
  40. 10.1101/gad.340679.120 · DOI
  41. 10.1186/s13059-020-02029-9 · DOI
  42. 10.1038/ng.2313 · DOI
  43. 10.1038/s41586-020-2371-0 · DOI · Paper page
  44. 10.1093/gbe/evt021 · DOI
  45. S. Seo, M. Okamoto, T. Iwai, M. Iwano, K. Fukui, A. Isogai, N. Nakajima, Y. Ohashi, Reduced levels of chloroplast FtsH protein in tobacco mosaic virus-infected tobacco leaves accelerate the hypersensitive reaction. Plant Cell 12, 917–932 (2000). 10852937
  46. 10.1038/s41598-020-57729-w · DOI
  47. 10.1186/s13059-018-1392-6 · DOI
  48. 10.1007/BF00260649 · DOI
  49. 10.1073/pnas.1718058115 · DOI
  50. 10.1073/pnas.1310949110 · DOI
  51. 10.1371/journal.pone.0043450 · DOI · Paper page
  52. 10.1111/tpj.13174 · DOI
  53. 10.1186/s13059-017-1273-4 · DOI
  54. 10.1073/pnas.2010250117 · DOI
  55. 10.1016/j.cell.2016.06.044 · DOI
  56. 10.1101/gr.146985.112 · DOI
  57. 10.1016/j.pbi.2016.12.007 · DOI
  58. 10.1038/s41467-020-19333-4 · DOI
  59. 10.1371/journal.pgen.1000734 · DOI
  60. J. J. Doyle, J. L. Doyle, A rapid DNA isolation procedure for small quantities of fresh leaf tissue. Phytochem. Bull. 19, 11–15 (1987).
  61. 10.1385/1-59259-413-1:3 · DOI
  62. M. Vasimuddin S. Misra H. Li S. Aluru in 2019 IEEE International Parallel and Distributed Processing Symposium (IPDPS 2019) pp. 314–324.
  63. R. Poplin V. Ruano-Rubio M. A. DePristo T. J. Fennell M. O. Carneiro G. A. Van der Auwera D. E. Kling L. D. Gauthier A. Levy-Moonshine D. Roazen K. Shakir J. Thibault S. Chandran C. Whelan M. Lek S. Gabriel M. J. Daly B. Neale D. G. MacArthur E. Banks Scaling Accurate Genetic Variant Discovery to Tens of Thousands of Samples. bioRxiv 201178v3 [Preprint]. 24 July 2018. https://doi.org/10.1101/201178. · DOI
  64. 10.1186/1471-2164-15-162 · DOI
  65. 10.1038/nmeth.4035 · DOI
  66. 10.1101/gr.215087.116 · DOI
  67. 10.1093/bioinformatics/bty191 · DOI · Paper page
  68. 10.1186/s13059-014-0573-1 · DOI
  69. 10.1023/A:1014893521186 · DOI
  70. 10.1038/s41467-018-07271-1 · DOI
  71. 10.1101/gr.214270.116 · DOI
  72. 10.1126/science.1178534 · DOI
  73. 10.1016/S0022-2836(05)80360-2 · DOI · Paper page
  74. 10.1186/s12864-020-6568-2 · DOI
  75. 10.1186/1471-2105-9-18 · DOI
  76. 10.1186/s13100-019-0193-0 · DOI
  77. 10.1104/pp.17.01310 · DOI
  78. A. Seetharam U. Singh J. Li P. Bhandary Z. Arendsee E. S. Wurtele Maximizing prediction of orphan genes in assembled genomes. bioRxiv 2019.12.17.880294 [Preprint]. 18 December 2019. https://doi.org/10.1101/2019.12.17.880294. · DOI
  79. 10.1038/nbt.1883 · DOI
  80. 10.1038/nbt.3122 · DOI
  81. 10.1371/journal.pcbi.1005851 · DOI
  82. 10.1038/nprot.2012.016 · DOI
  83. 10.1093/nar/gkw158 · DOI
  84. 10.1093/gigascience/giy093 · DOI
  85. 10.1093/gigascience/giy131 · DOI
  86. 10.1038/nprot.2013.084 · DOI · Paper page
  87. K. J. Hoff A. Lomsadze M. Borodovsky M. Stanke in Gene Prediction: Methods and Protocols M. Kollmar Ed. (Springer 2019) pp. 65–95. · DOI
  88. 10.1093/nar/gkg770 · DOI
  89. 10.1371/journal.pgen.1000740 · DOI
  90. 10.1101/gr.227462.117 · DOI
  91. 10.1093/bioinformatics/bti310 · DOI · Paper page
  92. 10.1038/ncomms11708 · DOI
  93. R.-G. Zhang Z.-X. Wang S. Ou G.-Y. Li TEsorter: Lineage-level classification of transposable elements using conserved protein domains. bioRxiv 800177 [Preprint]. 10 October 2019. https://doi.org/10.1101/800177. · DOI
  94. 10.1002/0471250953.bi0411s48 · DOI
  95. 10.1093/nar/gkaa979 · DOI
  96. 10.1093/bioinformatics/btq461 · DOI
  97. 10.1007/978-1-4939-8775-7_7 · DOI
  98. 10.1093/bioinformatics/btu031 · DOI
  99. A. J. Olson D. Ware Ranked choice voting for representative transcripts with TRaCE. bioRxiv 2020.12.15.422742 [Preprint]. https://doi.org/10.1101/2020.12.15.422742. · DOI
  100. 10.1101/gr.1857204 · DOI
  101. 10.1093/nar/gku365 · DOI · Paper page
  102. 10.1093/bib/bbs017 · DOI · Paper page
  103. 10.1186/1471-2164-14-774 · DOI
  104. 10.1093/bioinformatics/btx595 · DOI · Paper page
  105. W. Ricci Unmethylated regions encompass the functional space within the maize genome. bioRxiv 2021.04.21.425900 [Preprint]. 22 April 2021. https://doi.org/10.1101/2021.04.21.425900. · DOI
  106. 10.1016/j.tig.2012.10.012 · DOI
  107. 10.1371/journal.pcbi.1003118 · DOI
  108. 10.1093/bioinformatics/bty560 · DOI · Paper page
  109. 10.1038/nmeth.1923 · DOI · Paper page
  110. 10.1093/bioinformatics/btv098 · DOI
  111. J. M. Gaspar Improved peak-calling with MACS2. bioRxiv 496521v1 [Preprint]. 17 December 2018. .10.1101/496521 · DOI
  112. 10.1186/s12864-020-6696-8 · DOI
  113. 10.1371/journal.pcbi.1005944 · DOI · Paper page
  114. 10.1016/j.molp.2019.02.008 · DOI
  115. 10.1073/pnas.0403659101 · DOI
  116. 10.1093/bioinformatics/bth397 · DOI · Paper page
  117. 10.1111/j.1365-313X.2007.03326.x · DOI
  118. 10.1093/nar/gkx382 · DOI
  119. 10.1038/s41592-018-0001-7 · DOI
  120. 10.1038/ncomms14061 · DOI
  121. 10.1038/nbt.1754 · DOI · Paper page
  122. B. Steuernagel K. Witek S. G. Krattinger R. H. Ramirez-Gonzalez H. Schoonbeek Y. Guotai E. Baggs A. Witek I. Yadav K. V. Krasileva J. D. G. Jones C. Uauy B. Keller C. J. Ridout B. Wulff Physical and transcriptional organisation of the bread wheat intracellular immune receptor repertoire. King Abdullah University of Science and Technology University Library [Preprint]. 5 June 2018. https://repository.kaust.edu.sa/handle/10754/628448 · DOI
  123. 10.1038/s41467-017-02292-8 · DOI
  124. 10.1186/s12915-016-0228-7 · DOI
  125. de W. Van, F. Monteiro, O. J. Furzer, M. T. Nishimura, V. Cevik, K. Witek, J. D. G. Jones, J. L. Dangl, D. Weigel, F. Bemm, A Species-Wide Inventory of NLR Genes and Alleles in Arabidopsis thaliana. Cell 178, 126–1272.e14 (2019).
  126. 10.1093/bioinformatics/btu033 · DOI · Paper page
  127. 10.1093/nar/gkw290 · DOI
  128. 10.1371/journal.pone.0028819 · DOI
  129. 10.1186/s13059-015-0670-9 · DOI
  130. 10.1093/nar/gku104 · DOI
  131. 10.1093/bioinformatics/btw742 · DOI
  132. 10.1101/gr.113985.110 · DOI
  133. B. Song H. Wang Y. Wu E. Rees D. J. Gates M. Burch P. J. Bradbury J. Ross-Ibarra E. A. Kellogg M. B. Hufford M. Cinta Romay E. S. Buckler Constrained non-coding sequence provides insights into regulatory elements and loss of gene expression in maize. bioRxiv 2020.07.11.192575 [Preprint]. 13 July 2020. https://doi.org/10.1101/2020.07.11.192575. · DOI
  134. 10.1038/hdy.2014.123 · DOI
  135. 10.1093/molbev/msy228 · DOI
  136. 10.1038/ng.2309 · DOI
  137. 10.1093/molbev/msi228 · DOI
  138. B. C. Haller, SLiM: An Evolutionary Simulation Framework. Note: If you wish to cite SLiM 2 in a publication, please DO NOT cite this manual (unless you are, in fact, specifically referring to this manual–such as citing one of the recipes given here). We expect to have a publication on SLiM 2 out soon; in the meantime, you can cite the paper on the original version of SLiM: Messer, PW (2013). SLiM: Simulating Evolution with Selection and Linkage. Genetics 194, 1037–1039 (2016).
  139. 10.1534/genetics.108.097238 · DOI
  140. 10.1073/pnas.95.8.4441 · DOI
  141. 10.1073/pnas.0812590106 · DOI
  142. 10.1111/j.2041-210X.2011.00179.x · DOI
  143. 10.1093/bioinformatics/bts480 · DOI · Paper page
  144. 10.1126/science.1174276 · DOI
  145. 10.1038/ng.746 · DOI
  146. 10.1073/pnas.1010894108 · DOI
  147. 10.1038/hdy.2011.103 · DOI
  148. 10.1371/journal.pgen.1002383 · DOI
  149. 10.1073/pnas.1203189109 · DOI
  150. 10.1038/ng.747 · DOI
  151. 10.1093/bioinformatics/btr330 · DOI
  152. 10.1101/gr.107524.110 · DOI · Paper page
  153. 10.1111/mec.12354 · DOI
  154. 10.1101/gr.089516.108 · DOI
  155. 10.1093/bioinformatics/btm308 · DOI
  156. 10.1016/j.ajhg.2010.11.011 · DOI · Paper page
  157. 10.1111/tpj.13781 · DOI

Cited by

Sorted by citations

Metadata

Authors
Hufford, M. B., Seetharam, A. S., Woodhouse, M. R., Chougule, K. M., Ou, S., Liu, J., Ricci, W. A., Guo, T., Olson, A., Qiu, Y., Della Coletta, R., Tittes, S., Hudson, A. I., Marand, A. P., Wei, S., Lu, Z., Wang, B., Tello-Ruiz, M. K., Piri, R. D., Wang, N., Kim, D. W., Zeng, Y., O’Connor, C. H., Li, X., Gilbert, A. M., Baggs, E., Krasileva, K. V., Portwood, J. L., Cannon, E. K. S., Andorf, C. M., Manchanda, N., Snodgrass, S. J., Hufnagel, D. E., Jiang, Q., Pedersen, S., Syring, M. L., Kudrna, D. A., Llaca, V., Fengler, K., Schmitz, R. J., Ross-Ibarra, J., Yu, J., Gent, J. I., Hirsch, C. N., Ware, D., & Dawe, R. K.
Affiliations
  • Department of Ecology, Evolution, and Organismal Biology, Iowa State University, Ames, IA 50011, USA.
  • USDA-ARS Corn Insects and Crop Genetics Research Unit, Iowa State University, Ames, IA 50011, USA.
  • Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA.
  • Department of Genetics, University of Georgia, Athens, GA 30602, USA.
  • Department of Plant Biology, University of Georgia, Athens, GA 30602, USA.
  • Department of Agronomy, Iowa State University, Ames, IA 50011, USA.
  • Department of Agronomy and Plant Genetics, University of Minnesota, St. Paul, MN 55108, USA.
  • Center for Population Biology, University of California, Davis, CA 95616, USA.
  • Institute of Bioinformatics, University of Georgia, Athens, GA 30602, USA.
  • Department of Plant and Microbial Biology, University of California, Berkeley, CA 94720, USA.
  • Arizona Genomics Institute, School of Plant Sciences, University of Arizona, Tucson, AZ 85721, USA.
  • Corteva Agriscience, Johnston, IA 50131, USA.
Venue
Science
Published
2021-08-06
Volume
373
Issue
6555
Pages
655-662
ISSN
  • 0036-8075
  • 1095-9203
Cited by
747
References
13
Language
en
Funders
  • National Science Foundation (1744001, 1546727, 1127112, 1546719, 1822330, IOS-1856627, 1905869, IOS-1744001, IOS-1546727, IOS-1127112, IOS-1546719, IOS-1822330, 1744592, 58-5030-8-064, 1546657, 1650042, DBI-1905869, DGE-1545463)
  • U.S. Department of Agriculture (58-5030-8-064, 8062-21000-041-00D, 2018-67013-27571, 5030-21000-068-00D, CA-D-PLS-2066-H, USDA-ARS 8062-21000-041-00D, NSF IOS-1856627)
  • Additional (NIH-OD S10 OD028632)
  • Iowa State University Trainee SJS (USDA-ARS 58-5030-8-064)

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review