Rapid Assessment of Genetic Ancestry in Populations of Unknown Origin by Genome-Wide Genotyping of Pooled Samples
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{"title"=>"Rapid assessment of genetic ancestry in populations of unknown origin by genome-wide genotyping of pooled samples", "type"=>"journal", "authors"=>[{"first_name"=>"Charleston W.K.", "last_name"=>"Chiang", "scopus_author_id"=>"22966008500"}, {"first_name"=>"Zofia K.Z.", "last_name"=>"Gajdos", "scopus_author_id"=>"25824942200"}, {"first_name"=>"Joshua M.", "last_name"=>"Korn", "scopus_author_id"=>"57196077669"}, {"first_name"=>"Finny G.", "last_name"=>"Kuruvilla", "scopus_author_id"=>"6507031480"}, {"first_name"=>"Johannah L.", "last_name"=>"Butler", "scopus_author_id"=>"8763183400"}, {"first_name"=>"Rachel", "last_name"=>"Hackett", "scopus_author_id"=>"57197366712"}, {"first_name"=>"Candace", "last_name"=>"Guiducci", "scopus_author_id"=>"15047991900"}, {"first_name"=>"Thutrang T.", "last_name"=>"Nguyen", "scopus_author_id"=>"55353167300"}, {"first_name"=>"Rainford", "last_name"=>"Wilks", "scopus_author_id"=>"7005994235"}, {"first_name"=>"Terrence", "last_name"=>"Forrester", "scopus_author_id"=>"7005754404"}, {"first_name"=>"Christopher A.", "last_name"=>"Haiman", "scopus_author_id"=>"6701722861"}, {"first_name"=>"Katherine D.", "last_name"=>"Henderson", "scopus_author_id"=>"35240168000"}, {"first_name"=>"Loic", "last_name"=>"Le Marchand", "scopus_author_id"=>"7006229986"}, {"first_name"=>"Brian E.", "last_name"=>"Henderson", "scopus_author_id"=>"55659755700"}, {"first_name"=>"Mark R.", "last_name"=>"Palmert", "scopus_author_id"=>"7003867085"}, {"first_name"=>"Colin A.", "last_name"=>"McKenzie", "scopus_author_id"=>"7101970338"}, {"first_name"=>"Helen N.", "last_name"=>"Lyon", "scopus_author_id"=>"7006097279"}, {"first_name"=>"Richard S.", "last_name"=>"Cooper", "scopus_author_id"=>"56662407500"}, {"first_name"=>"Xiaofeng", "last_name"=>"Zhu", "scopus_author_id"=>"55643999549"}, {"first_name"=>"Joel N.", "last_name"=>"Hirschhorn", "scopus_author_id"=>"7006710354"}], "year"=>2010, "source"=>"PLoS Genetics", "identifiers"=>{"issn"=>"15537390", "pui"=>"358568997", "sgr"=>"77950420274", "doi"=>"10.1371/journal.pgen.1000866", "scopus"=>"2-s2.0-77950420274", "isbn"=>"1553-7404 (Electronic)\\r1553-7390 (Linking)", "pmid"=>"20221249"}, "id"=>"412180eb-f1c4-3ec5-be5d-2b9e513fc417", "abstract"=>"As we move forward from the current generation of genome-wide association (GWA) studies, additional cohorts of different ancestries will be studied to increase power, fine map association signals, and generalize association results to additional populations. Knowledge of genetic ancestry as well as population substructure will become increasingly important for GWA studies in populations of unknown ancestry. Here we propose genotyping pooled DNA samples using genome-wide SNP arrays as a viable option to efficiently and inexpensively estimate admixture proportion and identify ancestry informative markers (AIMs) in populations of unknown origin. We constructed DNA pools from African American, Native Hawaiian, Latina, and Jamaican samples and genotyped them using the Affymetrix 6.0 array. Aided by individual genotype data from the African American cohort, we established quality control filters to remove poorly performing SNPs and estimated allele frequencies for the remaining SNPs in each panel. We then applied a regression-based method to estimate the proportion of admixture in each cohort using the allele frequencies estimated from pooling and populations from the International HapMap Consortium as reference panels, and identified AIMs unique to each population. In this study, we demonstrated that genotyping pooled DNA samples yields estimates of admixture proportion that are both consistent with our knowledge of population history and similar to those obtained by genotyping known AIMs. Furthermore, through validation by individual genotyping, we demonstrated that pooling is quite effective for identifying SNPs with large allele frequency differences (i.e., AIMs) and that these AIMs are able to differentiate two closely related populations (HapMap JPT and CHB).", "link"=>"http://www.mendeley.com/research/rapid-assessment-genetic-ancestry-populations-unknown-origin-genomewide-genotyping-pooled-samples", "reader_count"=>61, "reader_count_by_academic_status"=>{"Unspecified"=>1, "Professor > Associate Professor"=>4, "Researcher"=>18, "Student > Doctoral Student"=>1, "Student > Ph. D. Student"=>18, "Student > Postgraduate"=>1, "Student > Master"=>2, "Other"=>5, "Student > Bachelor"=>3, "Lecturer"=>1, "Lecturer > Senior Lecturer"=>1, "Professor"=>6}, "reader_count_by_user_role"=>{"Unspecified"=>1, "Professor > Associate Professor"=>4, "Researcher"=>18, "Student > Doctoral Student"=>1, "Student > Ph. D. Student"=>18, "Student > Postgraduate"=>1, "Student > Master"=>2, "Other"=>5, "Student > Bachelor"=>3, "Lecturer"=>1, "Lecturer > Senior Lecturer"=>1, "Professor"=>6}, "reader_count_by_subject_area"=>{"Unspecified"=>4, "Biochemistry, Genetics and Molecular Biology"=>3, "Agricultural and Biological Sciences"=>46, "Medicine and Dentistry"=>5, "Physics and Astronomy"=>1, "Social Sciences"=>2}, "reader_count_by_subdiscipline"=>{"Medicine and Dentistry"=>{"Medicine and Dentistry"=>5}, "Social Sciences"=>{"Social Sciences"=>2}, "Physics and Astronomy"=>{"Physics and Astronomy"=>1}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>46}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>3}, "Unspecified"=>{"Unspecified"=>4}}, "reader_count_by_country"=>{"Austria"=>1, "Netherlands"=>1, "United States"=>4, "Brazil"=>3, "Switzerland"=>1}, "group_count"=>0}

Scopus | Further Information

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  • {"month"=>"5", "year"=>"2020", "pdf_views"=>"8", "xml_views"=>"0", "html_views"=>"29"}

Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/860408"], "description"=>"<p>Results from EIGENSTRAT were based on (A) 420 putative AIMs selected by comparing the MEC-J pools to the CHD population from HapMap phase 3 and (B) 420 random SNPs. Differentiation between JPT and CHB is clear when using the set of putative AIMs, compared to that using the same number of random SNPs. Note that the two CHB individuals within the JPT cluster in (A) would also cluster with JPT individuals if genome-wide data were used (data not shown). Similar differentiation using random SNPs could also be achieved when ∼3,100 random SNPs were used (data not shown).</p>", "links"=>[], "tags"=>["axes", "jpt"], "article_id"=>530845, "categories"=>["Genetics"], "users"=>["Charleston W. K. Chiang", "Zofia K. Z. Gajdos", "Joshua M. Korn", "Finny G. Kuruvilla", "Johannah L. Butler", "Rachel Hackett", "Candace Guiducci", "Thutrang T. Nguyen", "Rainford Wilks", "Terrence Forrester", "Christopher A. Haiman", "Katherine D. Henderson", "Loic Le Marchand", "Brian E. Henderson", "Mark R. Palmert", "Colin A. McKenzie", "Helen N. Lyon", "Richard S. Cooper", "Xiaofeng Zhu", "Joel N. Hirschhorn"], "doi"=>"https://dx.doi.org/10.1371/journal.pgen.1000866.g004", "stats"=>{"downloads"=>0, "page_views"=>1, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_The_top_two_axes_of_variation_from_principal_component_analysis_of_JPT_and_CHB_/530845", "title"=>"The top two axes of variation from principal component analysis of JPT and CHB.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2010-03-05 00:14:05"}
  • {"files"=>["https://ndownloader.figshare.com/files/427401", "https://ndownloader.figshare.com/files/427429", "https://ndownloader.figshare.com/files/427474", "https://ndownloader.figshare.com/files/427504", "https://ndownloader.figshare.com/files/427543", "https://ndownloader.figshare.com/files/427585", "https://ndownloader.figshare.com/files/427634", "https://ndownloader.figshare.com/files/427674", "https://ndownloader.figshare.com/files/427690", "https://ndownloader.figshare.com/files/427802"], "description"=>"<div><p>As we move forward from the current generation of genome-wide association (GWA) studies, additional cohorts of different ancestries will be studied to increase power, fine map association signals, and generalize association results to additional populations. Knowledge of genetic ancestry as well as population substructure will become increasingly important for GWA studies in populations of unknown ancestry. Here we propose genotyping pooled DNA samples using genome-wide SNP arrays as a viable option to efficiently and inexpensively estimate admixture proportion and identify ancestry informative markers (AIMs) in populations of unknown origin. We constructed DNA pools from African American, Native Hawaiian, Latina, and Jamaican samples and genotyped them using the Affymetrix 6.0 array. Aided by individual genotype data from the African American cohort, we established quality control filters to remove poorly performing SNPs and estimated allele frequencies for the remaining SNPs in each panel. We then applied a regression-based method to estimate the proportion of admixture in each cohort using the allele frequencies estimated from pooling and populations from the International HapMap Consortium as reference panels, and identified AIMs unique to each population. In this study, we demonstrated that genotyping pooled DNA samples yields estimates of admixture proportion that are both consistent with our knowledge of population history and similar to those obtained by genotyping known AIMs. Furthermore, through validation by individual genotyping, we demonstrated that pooling is quite effective for identifying SNPs with large allele frequency differences (i.e., AIMs) and that these AIMs are able to differentiate two closely related populations (HapMap JPT and CHB).</p></div>", "links"=>[], "tags"=>["ancestry", "populations", "genome-wide", "genotyping", "pooled", "samples"], "article_id"=>144362, "categories"=>["Genetics"], "users"=>["Charleston W. K. Chiang", "Zofia K. Z. Gajdos", "Joshua M. Korn", "Finny G. Kuruvilla", "Johannah L. Butler", "Rachel Hackett", "Candace Guiducci", "Thutrang T. Nguyen", "Rainford Wilks", "Terrence Forrester", "Christopher A. Haiman", "Katherine D. Henderson", "Loic Le Marchand", "Brian E. Henderson", "Mark R. Palmert", "Colin A. McKenzie", "Helen N. Lyon", "Richard S. Cooper", "Xiaofeng Zhu", "Joel N. Hirschhorn"], "doi"=>["https://dx.doi.org/10.1371/journal.pgen.1000866.s001", "https://dx.doi.org/10.1371/journal.pgen.1000866.s002", "https://dx.doi.org/10.1371/journal.pgen.1000866.s003", "https://dx.doi.org/10.1371/journal.pgen.1000866.s004", "https://dx.doi.org/10.1371/journal.pgen.1000866.s005", "https://dx.doi.org/10.1371/journal.pgen.1000866.s006", "https://dx.doi.org/10.1371/journal.pgen.1000866.s007", "https://dx.doi.org/10.1371/journal.pgen.1000866.s008", "https://dx.doi.org/10.1371/journal.pgen.1000866.s009", "https://dx.doi.org/10.1371/journal.pgen.1000866.s010"], "stats"=>{"downloads"=>33, "page_views"=>9, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/Rapid_Assessment_of_Genetic_Ancestry_in_Populations_of_Unknown_Origin_by_Genome_Wide_Genotyping_of_Pooled_Samples/144362", "title"=>"Rapid Assessment of Genetic Ancestry in Populations of Unknown Origin by Genome-Wide Genotyping of Pooled Samples", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2010-03-05 01:12:42"}
  • {"files"=>["https://ndownloader.figshare.com/files/860211"], "description"=>"<p>The distribution of the corrected allele frequency differences between the estimated pooled allele frequency and that expected based on each population's respective pseudopopulation among the top 200 putative AIMs is shown for the MEC-AA, MEC-H, and MEC-L pools. Corrected pooled AF difference was calculated by fixing the AF in the pseudopopulation, computing the pooled AF in the appropriate direction given the deflated χ<sup>2</sup> statistic, and then taking the difference. The distribution observed in the MAY pool represents the null distribution in which few additional validated AIMs are expected. To provide an estimate of the expected AF difference in a scenario where only sampling variation is responsible for the allele frequency difference between a population and its pseudopopulation, we simulated genotypes at ∼382 K SNPs for 521 individuals (the same number of post-QC SNPs and individuals as used in the MAY pools), drawing from the allele frequency in YRI 82% of the time and CEU 18% of the time, and compared the allele frequency of the simulated genotypes to that expected based on a 82%–18% mix of YRI and CEU. From this comparison, the top “AIMs” would only have an allele frequency difference of < ∼0.08.</p>", "links"=>[], "tags"=>["allele", "differences", "200"], "article_id"=>530647, "categories"=>["Genetics"], "users"=>["Charleston W. K. Chiang", "Zofia K. Z. Gajdos", "Joshua M. Korn", "Finny G. Kuruvilla", "Johannah L. Butler", "Rachel Hackett", "Candace Guiducci", "Thutrang T. Nguyen", "Rainford Wilks", "Terrence Forrester", "Christopher A. Haiman", "Katherine D. Henderson", "Loic Le Marchand", "Brian E. Henderson", "Mark R. Palmert", "Colin A. McKenzie", "Helen N. Lyon", "Richard S. Cooper", "Xiaofeng Zhu", "Joel N. Hirschhorn"], "doi"=>"https://dx.doi.org/10.1371/journal.pgen.1000866.g002", "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Distribution_of_allele_frequency_differences_among_the_top_200_AIMs_/530647", "title"=>"Distribution of allele frequency differences among the top 200 AIMs.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2010-03-05 00:10:47"}
  • {"files"=>["https://ndownloader.figshare.com/files/860080"], "description"=>"<p>Estimated allele frequencies for 100,000 random SNPs from the two MEC-H pools were plotted against each other (A) before SNP QC filtering and (B) after applying all four SNP QC filters. There were ∼869 K autosomal SNPs pre-QC filtering, and ∼306 K SNPs post-QC filtering (see <a href=\"http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1000866#s4\" target=\"_blank\">Methods</a>). Among the 5,000 SNPs with the largest AF differences between the two pools, the mean AF difference in the post-QC filtered dataset was significantly reduced (0.604 pre-QC versus 0.186 post-QC, <i>P</i>≪10<sup>−15</sup> by unpaired two-tailed t-test). Note that this comparison is based only on the average of allele frequency estimates, without taking into account the error involved in such estimates, which is compensated for when calculating the association χ<sup>2</sup> statistic (see <a href=\"http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1000866#s4\" target=\"_blank\">Methods</a>).</p>", "links"=>[], "tags"=>["allele", "frequencies", "mec-h", "qc"], "article_id"=>530518, "categories"=>["Genetics"], "users"=>["Charleston W. K. Chiang", "Zofia K. Z. Gajdos", "Joshua M. Korn", "Finny G. Kuruvilla", "Johannah L. Butler", "Rachel Hackett", "Candace Guiducci", "Thutrang T. Nguyen", "Rainford Wilks", "Terrence Forrester", "Christopher A. Haiman", "Katherine D. Henderson", "Loic Le Marchand", "Brian E. Henderson", "Mark R. Palmert", "Colin A. McKenzie", "Helen N. Lyon", "Richard S. Cooper", "Xiaofeng Zhu", "Joel N. Hirschhorn"], "doi"=>"https://dx.doi.org/10.1371/journal.pgen.1000866.g001", "stats"=>{"downloads"=>0, "page_views"=>1, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Estimated_allele_frequencies_in_MEC_H_pool_1_versus_MEC_H_pool_2_before_and_after_application_of_QC_filters_/530518", "title"=>"Estimated allele frequencies in MEC-H pool 1 versus MEC-H pool 2 before and after application of QC filters.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2010-03-05 00:08:38"}
  • {"files"=>["https://ndownloader.figshare.com/files/860495"], "description"=>"<p>The proportion of admixture for each of the admixed populations pooled in this study was estimated using a regression-based method (see <a href=\"http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1000866#s4\" target=\"_blank\">Methods</a>). Wherever possible, we also estimated the proportion of admixture using genotypes at AIMs known to distinguish the HapMap populations. β<sub>YRI</sub>, β<sub>CEU</sub>, and β<sub>CHB/JPT</sub> are the regression coefficients, which are taken as the proportion of ancestry contributed by each of the YRI, CEU, and CHB/JPT populations. The standard error (s.e.) of the regression coefficient is also listed when available. Note that the s.e. may be biased downward, due to LD between SNPs. However, the s.e. estimates based on the LD-pruned set of SNPs are on the order of 10<sup>−3</sup> (data not shown). Intercept is the regression intercept, which in this case is half of the unexplained ancestry in the model, as the average allele frequency for the population of interest and each of HapMap populations is ∼0.5 (<a href=\"http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1000866#pgen.1000866.s010\" target=\"_blank\">Text S2</a>). N<sub>SNP</sub> is number of SNPs used to generate the ancestry estimates (see <a href=\"http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1000866#s4\" target=\"_blank\">Methods</a>). The “method” column indicates the method used to generate the admixture estimates: “pooling” indicates that estimates are based on regression from pooled allele frequencies, “genotype” indicates that estimates are based on regression from individual genotype data, and “AIMs” indicates that estimates are were generated using STRUCTURE and individual genotype data from a small number of AIMs (see <a href=\"http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1000866#pgen.1000866.s009\" target=\"_blank\">Text S1</a>). n.d. denotes not determined; n.a. denotes not available. Estimates based on the regression approach do not appear to be confounded by issues due to collinearity (data not shown). For MAY, GXE, and SPT, when SNP allele frequencies from CHB/JPT were included in the model, β<sub>YRI</sub> was be largely unchanged, but a small contribution (<0.025) from CHB/JPT was estimated. This small admixture contribution from CHB/JPT appears to be largely an artifact due to sampling variation of the CEU and CHB/JPT reference populations (C.W.K.C., unpublished).</p>", "links"=>[], "tags"=>["estimates", "admixture"], "article_id"=>530931, "categories"=>["Genetics"], "users"=>["Charleston W. K. Chiang", "Zofia K. Z. Gajdos", "Joshua M. Korn", "Finny G. Kuruvilla", "Johannah L. Butler", "Rachel Hackett", "Candace Guiducci", "Thutrang T. Nguyen", "Rainford Wilks", "Terrence Forrester", "Christopher A. Haiman", "Katherine D. Henderson", "Loic Le Marchand", "Brian E. Henderson", "Mark R. Palmert", "Colin A. McKenzie", "Helen N. Lyon", "Richard S. Cooper", "Xiaofeng Zhu", "Joel N. Hirschhorn"], "doi"=>"https://dx.doi.org/10.1371/journal.pgen.1000866.t001", "stats"=>{"downloads"=>1, "page_views"=>6, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Comparison_of_estimates_of_admixture_proportion_/530931", "title"=>"Comparison of estimates of admixture proportion.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2010-03-05 00:15:31"}
  • {"files"=>["https://ndownloader.figshare.com/files/860315"], "description"=>"<p>The actual AF difference between the population AF and that of the pseudopopulation was plotted against the corrected AF difference predicted by pooling for 25, 28, 26, and 19 of the top candidate AIMs in MEC-L, GXE, SPT, and MEC-H, respectively. Corrected pooled AF difference was calculated as in <a href=\"http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1000866#pgen-1000866-g002\" target=\"_blank\">Figure 2</a>. Filled circles represent results from GXE, unfilled circles are those from SPT, filled triangles are those from MEC-H, and unfilled triangles are those from MEC-L. In all three populations the classification of a putative AIM as either “encouraging” or “inconclusive” (see <a href=\"http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1000866#s4\" target=\"_blank\">Methods</a>) did not appear to correlate with the probability of successful validation (data not shown).</p>", "links"=>[], "tags"=>["genotyping", "putative", "aims", "individuals", "comprised"], "article_id"=>530753, "categories"=>["Genetics"], "users"=>["Charleston W. K. Chiang", "Zofia K. Z. Gajdos", "Joshua M. Korn", "Finny G. Kuruvilla", "Johannah L. Butler", "Rachel Hackett", "Candace Guiducci", "Thutrang T. Nguyen", "Rainford Wilks", "Terrence Forrester", "Christopher A. Haiman", "Katherine D. Henderson", "Loic Le Marchand", "Brian E. Henderson", "Mark R. Palmert", "Colin A. McKenzie", "Helen N. Lyon", "Richard S. Cooper", "Xiaofeng Zhu", "Joel N. Hirschhorn"], "doi"=>"https://dx.doi.org/10.1371/journal.pgen.1000866.g003", "stats"=>{"downloads"=>0, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Validation_by_individual_genotyping_of_the_top_putative_AIMs_in_the_individuals_that_comprised_the_pools_/530753", "title"=>"Validation by individual genotyping of the top putative AIMs in the individuals that comprised the pools.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2010-03-05 00:12:33"}

PMC Usage Stats | Further Information

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  • {"unique-ip"=>"4", "full-text"=>"5", "pdf"=>"1", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2020", "month"=>"4"}

Relative Metric

{"start_date"=>"2010-01-01T00:00:00Z", "end_date"=>"2010-12-31T00:00:00Z", "subject_areas"=>[{"subject_area"=>"/Biology and life sciences", "average_usage"=>[288, 576, 733, 867, 984, 1087, 1182, 1267, 1346, 1424, 1501, 1577, 1646, 1711, 1778, 1841, 1908, 1970, 2034, 2102, 2162, 2227, 2296, 2359, 2422, 2482, 2550, 2610, 2679, 2747, 2820, 2887, 2955, 3009, 3067, 3130, 3200, 3257, 3322, 3379, 3443, 3507, 3571, 3632, 3683, 3753, 3822, 3877]}, {"subject_area"=>"/Biology and life sciences/Cell biology", "average_usage"=>[280, 562, 725, 863, 974, 1083, 1177, 1268, 1347, 1421, 1489, 1570, 1638, 1706, 1763, 1823, 1890, 1951, 2016, 2076, 2134, 2192, 2257, 2319, 2378, 2438, 2501, 2572, 2634, 2700, 2759, 2825, 2887, 2936, 3007, 3070, 3121, 3184, 3237, 3304, 3363, 3425, 3484, 3531, 3612, 3663, 3718, 3771]}, {"subject_area"=>"/Biology and life sciences/Population biology", "average_usage"=>[336, 599, 748, 884, 971, 1067, 1170, 1240, 1328, 1415, 1474, 1553, 1615, 1677, 1758, 1821, 1885, 1938, 2007, 2079, 2139, 2216, 2302, 2408, 2462, 2535, 2577, 2636, 2711, 2793, 2863, 2916, 2984, 3040, 3093, 3144, 3209, 3281, 3345, 3417, 3465, 3516, 3565, 3646, 3710, 3753, 3813, 3850, 3906]}, {"subject_area"=>"/People and places/Population groupings", "average_usage"=>[304, 560, 714, 827, 946, 1046, 1150, 1244, 1322, 1408, 1484, 1558, 1621, 1693, 1757, 1815, 1874, 1948, 2005, 2085, 2139, 2219, 2279, 2346, 2401, 2469, 2533, 2588, 2680, 2736, 2797, 2901, 2956, 2990, 3068, 3166, 3223, 3286, 3345, 3419, 3469, 3533, 3583, 3648, 3694, 3765, 3818, 3884]}]}
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