Linkage disequilibrium and haplotype block patterns in popcorn populations

Autoři: Andréa Carla Bastos Andrade aff001;  José Marcelo Soriano Viana aff001;  Helcio Duarte Pereira aff001;  Vitor Batista Pinto aff001;  Fabyano Fonseca e Silva aff002
Působiště autorů: Federal University of Viçosa, Department of General Biology, Viçosa, MG, Brazil aff001;  Federal University of Viçosa, Department of Animal Science, Viçosa, MG, Brazil aff002
Vyšlo v časopise: PLoS ONE 14(9)
Kategorie: Research Article
prolekare.web.journal.doi_sk: 10.1371/journal.pone.0219417


Linkage disequilibrium (LD) analysis provides information on the evolutionary aspects of populations. Recently, haplotype blocks have been used to increase the power of quantitative trait loci detection in genome-wide association studies and the prediction accuracy of genomic selection. Our objectives were as follows: to compare the degree of LD, LD decay, and LD decay extent in popcorn populations; to characterize the number and length of haplotype blocks in the populations; and to determine whether maize chromosomes also have a pattern of interspaced regions of high and low rates of recombination. We used a biparental population, a synthetic, and a breeding population, genotyped for approximately 75,000 single nucleotide polymorphisms (SNPs). The sample size ranged from 190 to 192 plants. For the whole-genome LD and haplotype block analyses, we assumed a window of 500 kb. To characterize the block and step patterns of LD in the populations, we constructed LD maps by chromosome, defining a cold spot as a chromosome segment including SNPs with the same LDU position. The LD and haplotype block analyses were also performed at the intragenic level, selecting 12 genes related to zein, starch, cellulose, and fatty acid biosynthesis. The populations with the higher and lower frequencies of |D'| values greater than 0.75 were the biparental (65–74%) and the breeding population (26–58%), respectively. There were slight differences between the populations regarding the average distance for SNPs with |D'| values greater than 0.75 (in the range of approximately 207 to 229 kb). The level of LD expressed by the r2 values was low in the populations (0.02, 0.04, and 0.04, on average) but comparable to some non-isolated human populations. The frequency of r2 values greater than 0.75 was lower in the biparental population (0.2–0.5%) and higher in the other populations (0.2–1.6%). The average distance for SNPs with r2 values greater than 0.75 was much higher in the biparental population (approximately 80 to 126 kb). In the other populations, the ranges were approximately 6 to 19 and 6 to 35 kb. The heatmaps for the regions covered by the first 100 SNPs in each chromosome, in each population (1 to 3.3 Mb, approximately), provided evidence that the comparatively few high r2 values (close to 1.0) occurred only for SNPs in close proximity, especially in the synthetic and breeding populations. Due to the reduced number of SNPs in the haplotype blocks (2 to 3) in the populations, it is not expected advantage of a haplotype-based association study as well as genomic selection along generations. The results concerning LD decay (rapid decay after 5–10 kb) and LD decay extent (along up to 300 kb) are in the range observed with maize inbred line panels. The LD maps indicate that maize chromosomes had a pattern of regions of extensive LD interspaced with regions of low LD. However, our simulated LD map provides evidence that this pattern can reflect regions with differences in allele frequencies and LD levels (expressed by |D'|) and not regions with high and low rates of recombination.

Klíčová slova:

Animal sexual behavior – Genome-wide association studies – Haplotypes – Chromosome mapping – Inbred strains – Maize – Molecular genetics – Plant genomics


1. Wall JD, Pritchard JK. Haplotype blocks and linkage disequilibrium in the human genome. Nature Reviews Genetics. 2003;4(8):587–97. doi: 10.1038/nrg1123 PubMed PMID: WOS:000184491300011. 12897771

2. Lewontin R. The interaction of selection and linkage. I. General considerations; heterotic models. Genetics. 1964;49(1):49. 17248194

3. Weir BS. Linkage disequilibrium and association mapping. Annual review of genomics and human genetics. 2008;9:129–42. doi: 10.1146/annurev.genom.9.081307.164347 18505378.

4. Maldonado C, Mora F, Scapim CA, Coan M. Genome-wide haplotype-based association analysis of key traits of plant lodging and architecture of maize identifies major determinants for leaf angle: hapLA4. PloS one. 2019;14(3). doi: 10.1371/journal.pone.0212925 PubMed PMID: WOS:000460372100053. 30840677

5. Hess M, Druet T, Hess A, Garrick D. Fixed-length haplotypes can improve genomic prediction accuracy in an admixed dairy cattle population. Genetics Selection Evolution. 2017;49. doi: 10.1186/s12711-017-0329-y PubMed PMID: WOS:000405342400001. 28673233

6. Gabriel SB, Schaffner SF, Nguyen H, Moore JM, Roy J, Blumenstiel B, et al. The structure of haplotype blocks in the human genome. Science. 2002;296(5576):2225–9. doi: 10.1126/science.1069424 PubMed PMID: WOS:000176379000060. 12029063

7. Thirunavukkarasu N, Hossain F, Shiriga K, Mittal S, Arora K, Rathore A, et al. Unraveling the genetic architecture of subtropical maize (Zea mays L.) lines to assess their utility in breeding programs. BMC genomics. 2013;14. doi: 10.1186/1471-2164-14-877 PubMed PMID: WOS:000328649800002. 24330649

8. Truntzler M, Ranc N, Sawkins MC, Nicolas S, Manicacci D, Lespinasse D, et al. Diversity and linkage disequilibrium features in a composite public/private dent maize panel: consequences for association genetics as evaluated from a case study using flowering time. Theoretical and Applied Genetics. 2012;125(4):731–47. doi: 10.1007/s00122-012-1866-y PubMed PMID: WOS:000307294600009. 22622520

9. Anderson SL, Mahan AL, Murray SC, Klein PE. Four Parent Maize (FPM) Population: Effects of Mating Designs on Linkage Disequilibrium and Mapping Quantitative Traits. Plant Genome. 2018;11(2). doi: 10.3835/plantgenome2017.11.0102 PubMed PMID: WOS:000450929300013. 30025026

10. Tapper WJ, Maniatis N, Morton NE, Collins A. A metric linkage disequilibrium map of a human chromosome. Annals of Human Genetics. 2003;67:487–94. doi: 10.1046/j.1469-1809.2003.00050.x PubMed PMID: WOS:000187442000001. 14641236

11. Zhang WH, Collins A, Maniatis N, Tapper W, Morton NE. Properties of linkage disequilibrium (LD) maps. Proceedings of the National Academy of Sciences of the United States of America. 2002;99(26):17004–7. doi: 10.1073/pnas.012672899 PubMed PMID: WOS:000180101600089. 12486239

12. Jiao YP, Peluso P, Shi JH, Liang T, Stitzer MC, Wang B, et al. Improved maize reference genome with single-molecule technologies. Nature. 2017;546(7659):524-+. doi: 10.1038/nature22971 PubMed PMID: WOS:000403814100037. 28605751

13. Knaus BJ, Grünwald NJ. vcfr: a package to manipulate and visualize variant call format data in R. Molecular Ecology Resources. 2017;17(1):44–53. doi: 10.1111/1755-0998.12549 27401132

14. Knueppel S, Rohde K, Knueppel MS. Package ‘HapEstXXR’. 2015.

15. Browning BL, Browning SR. A unified approach to genotype imputation and haplotype-phase inference for large data sets of trios and unrelated individuals. Am J Hum Genet. 2009;84(2):210–23. doi: 10.1016/j.ajhg.2009.01.005 19200528; PubMed Central PMCID: PMC2668004.

16. Wimmer V, Albrecht T, Auinger H-J, Schön C-C. synbreed: a framework for the analysis of genomic prediction data using R. Bioinformatics. 2012;28(15):2086–7. doi: 10.1093/bioinformatics/bts335 22689388

17. Maniatis N, Collins A, Xu CF, McCarthy LC, Hewett DR, Tapper W, et al. The first linkage disequilibrium (LD) maps: Delineation of hot and cold blocks by diplotype analysis. Proceedings of the National Academy of Sciences of the United States of America. 2002;99(4):2228–33. doi: 10.1073/pnas.042680999 PubMed PMID: WOS:000174031100086. 11842208

18. Viana JMS, Valente MSF, Silva FF, Mundim GB, Paes GP. Efficacy of population structure analysis with breeding populations and inbred lines. Genetica. 2013;141(7–9):389–99. doi: 10.1007/s10709-013-9738-1 PubMed PMID: WOS:000325780600013. 24057807

19. Viana JMS, Silva FF, Mundim GB, Azevedo CF, Jan HU. Efficiency of low heritability QTL mapping under high SNP density. Euphytica. 2017;213(1). doi: 10.1007/s10681-016-1800-5 PubMed PMID: WOS:000392317900013.

20. Viana JMS, Pereira HD, Mundim GB, Piepho HP, Silva FFE. Efficiency of genomic prediction of non-assessed single crosses. Heredity. 2018;120(4):283–95. doi: 10.1038/s41437-017-0027-0 PubMed PMID: WOS:000426887000001. 29180718

21. Viana JMS, Mundim GB, Pereira HD, Andrade ACB, Silva FFE. Efficiency of genome-wide association studies in random cross populations. Molecular Breeding. 2017;37(8). doi: 10.1007/s11032-017-0700-2 WOS:000407491600010.

22. Barrett JC, Fry B, Maller J, Daly MJ. Haploview: analysis and visualization of LD and haplotype maps. Bioinformatics. 2005;21(2):263–5. doi: 10.1093/bioinformatics/bth457 15297300

23. Qin ZS, Niu T, Liu JS. Partition-ligation–expectation-maximization algorithm for haplotype inference with single-nucleotide polymorphisms. The American Journal of Human Genetics. 2002;71(5):1242–7. doi: 10.1086/344207 12452179

24. Barrett JC. Haploview: Visualization and analysis of SNP genotype data. Cold Spring Harbor Protocols. 2009;2009(10):pdb. ip71. doi: 10.1101/pdb.ip71 20147036

25. Pengelly RJ, Tapper W, Gibson J, Knut M, Tearle R, Collins A, et al. Whole genome sequences are required to fully resolve the linkage disequilibrium structure of human populations. BMC genomics. 2015;16. doi: 10.1186/s12864-015-1854-0 PubMed PMID: WOS:000360607100006. 26335686

26. Angius A, Hyland FCL, Persico I, Pirastu N, Woodage T, Pirastu M, et al. Patterns of linkage disequilibrium between SNPs in a sardinian population isolate and the selection of markers for association studies. Human Heredity. 2008;65(1):9–22. doi: 10.1159/000106058 PubMed PMID: WOS:000249305300002. 17652959

27. Evans DM, Cardon LR. A comparison of linkage disequilibrium patterns and estimated population recombination rates across multiple populations. American Journal of Human Genetics. 2005;76(4):681–7. doi: 10.1086/429274 PubMed PMID: WOS:000227516000014. 15719321

28. Pardo L, Bochdanovits Z, de Geus E, Hottenga JJ, Sullivan P, Posthuma D, et al. Global similarity with local differences in linkage disequilibrium between the Dutch and HapMap-CEU populations. European Journal of Human Genetics. 2009;17(6):802–10. doi: 10.1038/ejhg.2008.248 PubMed PMID: WOS:000266289100016. 19127282

29. Collins A. Allelic association: linkage disequilibrium structure and gene mapping. Mol Biotechnol. 2009;41(1):83–9. doi: 10.1007/s12033-008-9110-3 18841501.

30. Yan JB, Shah T, Warburton ML, Buckler ES, McMullen MD, Crouch J. Genetic Characterization and Linkage Disequilibrium Estimation of a Global Maize Collection Using SNP Markers. PloS one. 2009;4(12). doi: 10.1371/journal.pone.0008451 PubMed PMID: WOS:000273104000015. 20041112

31. Gore MA, Chia JM, Elshire RJ, Sun Q, Ersoz ES, Hurwitz BL, et al. A First-Generation Haplotype Map of Maize. Science. 2009;326(5956):1115–7. doi: 10.1126/science.1177837 PubMed PMID: WOS:000271951000045. 19965431

32. Qanbari S, Hansen M, Weigend S, Preisinger R, Simianer H. Linkage disequilibrium reveals different demographic history in egg laying chickens. BMC genetics. 2010;11. doi: 10.1186/1471-2156-11-103 PubMed PMID: WOS:000285302100001. 21078133

33. Qanbari S, Pimentel ECG, Tetens J, Thaller G, Lichtner P, Sharifi AR, et al. The pattern of linkage disequilibrium in German Holstein cattle. Animal Genetics. 2010;41(4):346–56. doi: 10.1111/j.1365-2052.2009.02011.x PubMed PMID: WOS:000279717800002. 20055813

34. Khatkar MS, Nicholas FW, Collins AR, Zenger KR, Al Cavanagh J, Barris W, et al. Extent of genome-wide linkage disequilibrium in Australian Holstein-Friesian cattle based on a high-density SNP panel. BMC genomics. 2008;9. doi: 10.1186/1471-2164-9-187 PubMed PMID: WOS:000256398400001. 18435834

35. McKay SD, Schnabel RD, Murdoch BM, Matukumalli LK, Aerts J, Coppieters W, et al. Whole genome linkage disequilibrium maps in cattle. BMC genetics. 2007;8. doi: 10.1186/1471-2156-8-74 PubMed PMID: WOS:000252442300001. 17961247

36. Shifman S, Kuypers J, Kokoris M, Yakir B, Darvasi A. Linkage disequilibrium patterns of the human genome across populations. Human Molecular Genetics. 2003;12(7):771–6. doi: 10.1093/hmg/ddg088 PubMed PMID: WOS:000181981400008. 12651872

37. Jonas D, Ducrocq V, Fouilloux MN, Croiseau P. Alternative haplotype construction methods for genomic evaluation. Journal of dairy science. 2016;99(6):4537–46. doi: 10.3168/jds.2015-10433 PubMed PMID: WOS:000375876600041. 26995132

38. Ma YS, Reif JC, Jiang Y, Wen ZX, Wang DC, Liu ZX, et al. Potential of marker selection to increase prediction accuracy of genomic selection in soybean (Glycine max L.). Molecular Breeding. 2016;36(8). doi: 10.1007/s11032-016-0504-9 PubMed PMID: WOS:000382144700013. 27524935

39. Evseeva I, Nicodemus KK, Bonilla C, Tonks S, Bodmer WF. Linkage disequilibrium and age of HLA region SNPs in relation to classic HLA gene alleles within Europe. European Journal of Human Genetics. 2010;18(8):924–32. doi: 10.1038/ejhg.2010.32 PubMed PMID: WOS:000280145100011. 20354563

40. Nuchnoi P, Ohashi J, Naka I, Nacapunchai D, Tokunaga K, Nishida N, et al. Linkage disequilibrium structure of the 5q31-33 region in a Thai population. Journal of Human Genetics. 2008;53(9):850–6. doi: 10.1007/s10038-008-0309-8 PubMed PMID: WOS:000258615100008. 18574552

41. Akesaka T, Lee SG, Ohashi J, Bannai M, Tsuchiya N, Yoon Y, et al. Comparative study of the haplotype structure and linkage disequilibrium of chromosome 1p36.2 region in the Korean and Japanese populations. Journal of Human Genetics. 2004;49(11):603–9. doi: 10.1007/s10038-004-0195-7 PubMed PMID: WOS:000225238200003. 15480877

42. Jeffreys AJ, Holloway JK, Kauppi L, May CA, Neumann R, Slingsby MT, et al. Meiotic recombination hot spots and human DNA diversity. Philosophical Transactions of the Royal Society of London Series B-Biological Sciences. 2004;359(1441):141–52. doi: 10.1098/rstb.2003.1372 PubMed PMID: WOS:000188425400017. 15065666

Článok vyšiel v časopise


2019 Číslo 9

Najčítanejšie v tomto čísle

Tejto téme sa ďalej venujú…


Zvýšte si kvalifikáciu online z pohodlia domova

Faktory ovlivňující léčbu levotyroxinem
nový kurz

Kurz originály vs. generika

Autori: MUDr. Petr Výborný, CSc., FEBO

Autori: MUDr. Jiří Horažďovský, Ph.D

Klinická farmakokinetika betablokátorů

Všetky kurzy
Zabudnuté heslo

Nemáte účet?  Registrujte sa

Zabudnuté heslo

Zadajte e-mailovú adresu, s ktorou ste vytvárali účet. Budú Vám na ňu zasielané informácie k nastaveniu nového hesla.


Nemáte účet?  Registrujte sa