نقشه یابی ارتباطی در گیاهان

نوع مقاله : مروری

نویسندگان

1 استادیار، موسسه تحقیقات اصلاح و تهیه نهال و بذر، سازمان تحقیقات، آموزش و ترویج کشاورزی، کرج، ایران

2 دانشیار، پردیس کشاورزی و منابع طبیعی دانشگاه تهران، کرج، ایران

چکیده

تنوع فنوتیپی موجود در بسیاری از صفات مهم در گیاهان تحت تأثیر چندین جایگاه ژنی، عوامل محیطی و اثرات متقابل این دو می‌باشد. نقشه‌یابی ارتباطی یکی از روش‌هایی است که در دهه‌های اخیر برای مطالعه ژنتیکی و تعیین تعداد مکانهای ژنی کنترل کننده صفات کمی پیشنهاد شده است. این روش برای اولین بار در ژنتیک انسانی و برای صفاتی کیفی (مانند بیماری‌های ژنتیکی) مورد استفاده قرار گرفت اما امروزه به دلیل پیشرفت‌های چشمگیر در تکنولوژی توالی‌یابی DNA، علاقمندی برای شناسایی ژن‌های جدید و بهبود روش‌های آماری استفاده از آن در جمعیت‌های گیاهی رو به افزایش است. نقشه‌یابی ارتباطی روشی هدفمند برای شناسایی ارتباط آماری بین آلل‌های نشانگری و صفات کمی بر اساس عدم تعادل لینکاژی است. برخلاف نقشه‌یابی لینکاژی، این روش با بهره‌گیری از تنوع موجود در جمعیت‌های طبیعی و لحاظ کردن تمامی وقایعی که در طول تکامل افراد رخ داده است، ارتباط بین تنوع فنوتیپی و چندشکلی موجود در ژنوم را شناسایی می‌کند و روشی امیدوارکننده برای غلبه بر محدودیت‌های نقشه‌یابی لینکاژی است. علی‌رغم اینکه نقشه‌یابی ارتباطی از توان آماری بالایی برخوردار است اما کاربرد این روش در جمعیت‌های دارای ساختار، در گونه‌های با میزان کم عدم تعادل لینکاژی و در صفاتی که توسط آلل‌های نادر کنترل می‌شود بسیار پیچیده و دشوار است. در این مقاله وضعیت کلی نقشه‌یابی ارتباطی، نحوه کاربرد آن در جمعیت و محدودیت‌های آن در گیاهان مورد بررسی قرار خواهد گرفت.

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

Association Mapping in Plants

نویسندگان [English]

  • Reza Ataei 1
  • Majid Gholamhoseini 1
  • Valiollah Mohammadi 2
1 Assistant Professor, Seed and Plant Improvement Institute (SPII), Agriculture Research, Education and Extension (AREEO), Karaj, Iran
2 Associate Professor, College of Agriculture and Natural Resources, University of Tehran, Karaj, Iran
چکیده [English]

The phenotypic diversity of many important traits in plants is influenced by several loci, environmental factors and their interactions. Association mapping is one of the methods proposed in recent decades for genetic study and detection of quantitative trait loci (QTLs). Association mapping was used in human genetics and qualitative traits (such as diseases), but recently its use is increasing in the plant science because of advances in high throughput genomic technologies, interests in identifying novel and superior alleles, and improvements in statistical methods. Association mapping through linkage disequilibrium analysis is a purposeful method for identifying marker alleles and quantitative traits association. Unlike linkage mapping, this method identifies the association between phenotypic and polymorphic diversity in the genome by exploiting the diversity of natural populations and taking into account all the events that occurred during the evolution and is a promising approach for overcoming the limitations of linkage mapping. Despite association mapping has high statistical power, the application of this method in structured populations, species with low level of linkage disequilibrium and in traits controlled by rare alleles is complicated and difficult. In this review, we will present a comprehensive view, its application in population, current status and limitation of association mapping in plant science

کلیدواژه‌ها [English]

  • Population structure
  • Linkage disequilibrium
  • Association mapping
  • QTL

مراجع

Agrama H, Eizenga G, Yan W (2007) Association mapping of yield and its components in rice cultivars. Molecular Breeding 19: 341-356.
Aranzana MJ, Kim S, Zhao K, Bakker E, Horton M, Jakob K, Lister C, Molitor J, Shindo C, Tang C (2005) Genome-wide association mapping in Arabidopsis identifies previously known flowering time and pathogen resistance genes. PLoS Genetics 1: 531-539.
Arbelbide M, Yu J, Bernardo R (2006) Power of mixed-model QTL mapping from phenotypic, pedigree and marker data in self-pollinated crops. Theoretical and Applied Genetics 112: 876-884.
Ataei R, Mohammadi V, Talei AR, Naghavi MR (2016) Association mapping of yield and some important agronomic traits in barley (Hordeum vulgare L.). Modern Genetics Journal 11: 411-423.
Bernardo R (2002) Breeding for quantitative traits in plants. Stemma press Woodburypp.
Bradbury PJ, Zhang Z, Kroon DE, Casstevens T M, Ramdoss Y, Buckler ES (2007) TASSEL: software for association mapping of complex traits in diverse samples. Bioinformatics 23: 2633-2635.
Breseghello F, Sorrells ME (2006) Association analysis as a strategy for improvement of quantitative traits in plants. Crop Science 46: 1323-1330.
Caldwell KS, Russell J, Langridge P, Powell W (2006) Extreme population-dependent linkage disequilibrium detected in an inbreeding plant species, Hordeum vulgare. Genetics 172: 557-567.
Chandler VL, Brendel V (2002) The maize genome sequencing project. Plant Physiology 130: 1594-1597.
Dunning AM, Durocher F, Healey CS, Teare MD, McBride S E, Carlomagno F, Xu C-F, Dawson E, Rhodes S, Ueda S (2000) The extent of linkage disequilibrium in four populations with distinct demographic histories. The American Journal of Human Genetics 67: 1544-1554.
Falconer DS (1981) Introduction to quantitative genetics. Longman.pp.
Falconer D S, Mackay T F, Frankham R (1996) Introduction to Quantitative Genetics (4th edn). Trends in Genetics 12: 280.
Falush D, Stephens M, Pritchard JK (2007) Inference of population structure using multilocus genotype data: dominant markers and null alleles. Molecular Ecology Notes 7: 574-578.
Ferreira JR, Pereira JF, Turchetto C, Minella E, Consoli L, Delatorre CA (2016) Assessment of genetic diversity in Brazilian barley using SSR markers. Genetics and molecular biology 39: 86-96.
Flint-Garcia SA, Thornsberry JM, IV B (2003) Structure of Linkage Disequilibrium in Plants. Annual Review of Plant Biology 54: 357-374.
Flint‐Garcia SA, Thuillet AC, Yu J, Pressoir G, Romero SM, Mitchell SE, Doebley J, Kresovich S, Goodman M M, Buckler ES (2005) Maize association population: a high‐resolution platform for quantitative trait locus dissection. The Plant Journal 44: 1054-1064.
Gupta PK, Rustgi S, Kulwal PL (2005) Linkage disequilibrium and association studies in higher plants: present status and future prospects. Plant Molecular Biology 57: 461-485.
Hardy OJ, Vekemans X (2002) SPAGeDi: a versatile computer program to analyse spatial genetic structure at the individual or population levels. Molecular Ecology Notes 2: 618-620.
Hill W, Robertson A (1968) Linkage disequilibrium in finite populations. Theoretical and Applied Genetics 38: 226-231.
Jorde L (2000) Linkage disequilibrium and the search for complex disease genes. Genome Research 10: 1435-1444.
Kearsey M, Farquhar A (1998) QTL analysis in plants; where are we now? Heredity 80: 137-142.
Knowler WC, Williams R, Pettitt D, Steinberg AG (1988) Gm3; 5, 13, 14 and type 2 diabetes mellitus: an association in American Indians with genetic admixture. American Journal of Human Genetics 43: 520.
Laurentin H (2009) Data analysis for molecular characterization of plant genetic resources. Genetic Resources and Crop Evolution 56: 277-292.
Lawrence CJ, Harper LC, Schaeffer ML, Sen TZ, Seigfried TE, Campbell DA (2008) MaizeGDB: the maize model organism database for basic, translational, and applied research. International Journal of Plant Genomics 2008: 496957.
Maher B (2008) The case of the missing heritability. Nature 456: 18-21.
Moose SP, Mumm RH (2008) Molecular plant breeding as the foundation for 21st century crop improvement. Plant Physiology 147: 969-977.
Morrell PL, Toleno DM, Lundy KE, Clegg MT (2005) Low levels of linkage disequilibrium in wild barley (Hordeum vulgare ssp. spontaneum) despite high rates of self-fertilization. Proceedings of the National Academy of Sciences of the United States of America 102: 2442-2447.
Myles S, Peiffer J, Brown PJ, Ersoz ES, Zhang Z, Costich DE, Buckler ES (2009) Association mapping: critical considerations shift from genotyping to experimental design. The Plant Cell Online. 21: 2194-2202.
Nordborg M (2000) Linkage disequilibrium, gene trees and selfing: an ancestral recombination graph with partial self-fertilization. Genetics 154: 923-929.
Pritchard JK, Rosenberg NA (1999) Use of unlinked genetic markers to detect population stratification in association studies. The American Journal of Human Genetics. 65: 220-228.
Pritchard J K, Stephens M, Donnelly P (2000) Inference of population structure using multilocus genotype data. Genetics. 155: 945-959.
Reich DE, Cargill M, Bolk S, Ireland J, Sabeti PC, Richter DJ, Lavery T, Kouyoumjian R, Farhadian SF, Ward R (2001) Linkage disequilibrium in the human genome. Nature 411: 199-204.
Ritland K (2005) Multilocus estimation of pairwise relatedness with dominant markers. Molecular Ecology 14: 3157-3165.
Spielman RS, McGinnis RE, Ewens WJ (1993) Transmission test for linkage disequilibrium: the insulin gene region and insulin-dependent diabetes mellitus (IDDM). American Journal of Human Genetics 52: 506-516.
Stich B, Melchinger AE (2010) An introduction to association mapping in plants. CAB Rev 5: 1-9.
Tenaillon MI, Sawkins MC, Long AD, Gaut RL, Doebley JF, Gaut BS (2001) Patterns of DNA sequence polymorphism along chromosome 1 of maize (Zea mays ssp. mays L.). Proceedings of the National Academy of Sciences 98: 9161-9166.
Thornsberry JM, Goodman MM, Doebley J, Kresovich S, Nielsen D, Buckler ES (2001) Dwarf8 polymorphisms associate with variation in flowering time. Nature Genetics 28: 286-289.
Weir BS (1996) Genetic data analysis 2: methods for discrete population genetic data. Sinauer, Massachusetts.
Yu J, Buckler ES (2006) Genetic association mapping and genome organization of maize. Current Opinion in Biotechnology 17: 155-160.
Yu J, Pressoir G, Briggs WH, Bi IV, Yamasaki M, Doebley JF, McMullen MD, Gaut BS, Nielsen DM, Holland JB (2005) A unified mixed-model method for association mapping that accounts for multiple levels of relatedness. Nature Genetics 38: 203-208.
Zhu C, Gore M, Buckler ES, Yu J (2008) Status and prospects of association mapping in plants. The Plant Genome 1: 5-20.

فایل ها

هم رسانی

ارجاع به این مقاله

آمار