nav emailalert searchbtn searchbox tablepage yinyongbenwen piczone journalimg journalInfo journalinfonormal searchdiv qikanlogo popupnotification paper paperNew
2025, 12, v.55 64-78
基于全基因组关联分析挖掘条斑紫菜配子体生长性状遗传位点
基金项目(Foundation): 国家重点研究发展计划项目(2023YFD2400101)资助~~
邮箱(Email): yxmao@ouc.edu.cn;
DOI: 10.16441/j.cnki.hdxb.20240294
摘要:

为解决条斑紫菜(Neopyropia yezoensis)遗传育种研究中缺乏生长性状遗传位点的问题,本研究针对条斑紫菜配子体的4个重要生长性状展开了全基因组关联分析(Genome-wide association study, GWAS)。首先,在相同环境下纯化培养了130个单一基因型条斑紫菜个体,并测量了叶长、叶宽、鲜质量和干质量这4个与生长相关的表型数据,进而分析并发现条斑紫菜不同生长性状的变异系数(Coefficient of variation)为32.63%~50.95%,各性状之间存在显著的相关性。利用全基因组重测序技术获得每个个体的基因型。对重测序数据质检后,共得到405 999个高质量的单核苷酸多态性(Single nucleotide polymorphism, SNP)位点,其中53 077个位点位于外显子区域,SNPs位点转换与颠换的数量之比为1.23。群体结构分析发现,研究群体可以分为4个亚群,不同亚群之间存在明显的遗传差异,而分群情况并非严格按照地理位置划分。测序个体之间的亲缘关系较远,连锁不平衡(Linkage disequilibrium, LD)衰减距离较小,这表明样本的遗传变异比较丰富。本研究利用混合线性模型(Q+K)进行了性状关联位点的筛选,共筛选出90个显著关联位点,其中67个位点与叶长显著相关,17个位点与叶宽显著相关,4个位点与鲜质量显著相关,2个位点与干质量显著相关,这些位点能够解释16.12%~24.85%的表型变异。在显著性位点上、下游20 kb范围内筛选,得到39个可能与生长性状相关的候选基因,基因功能涉及细胞增殖、控制细胞代谢途径以及调控植物的生长发育等。本文为条斑紫菜分子育种研究的开展提供了候选遗传位点和重要依据。

Abstract:

In order to address the paucity of genetic loci associated with growth traits in the genetic breeding studies of Neopyropia yezoensis, the genome-wide association study(GWAS) was conducted for 4 important growth traits in gametophytes of N. yezoensis. One hundred and thirty thalli of N. yezoensis with single genotype were cultured under the same environment. Four growth-related phenotypic values of thallus length, thallus width, fresh mass and dry mass were measured. Study revealed that the coefficient of variation of different growth traits of thalli ranged from 32.63% to 50.95%, and there were significant correlations among the four traits. The genotype of each individual were obtained by whole genome re-sequencing. After quality inspection of the re-sequencing data, a total of 405 999 high-quality SNPs were obtained, of which 53 077 sites were in the exon region, and the ratio of SNPs transitions to translocations was 1.23. Population structure analysis found that the population in this work could be divided into 4 subgroups, and there were obvious genetic differences between any two different subgroups. The subgroups division were not in accordance with geographical location. The relatively distant phylogenetic relationship among the individuals and the short range of LD decay distance indicated that the genetic variation was relatively rich in the population. The mixed linear model(Q+K) was used to screen the associated loci of traits. A total of 90 significant SNP markers were detected, of which 67 loci were correlated with thallus length, 17 loci were correlated with thallus width, 4 loci were correlated with fresh mass, and 2 loci were correlated with dry mass, which could explain 16.12% to 24.85% of the observed phenotypic variation. A total of 39 candidate genes were identified within a 20 kb range upstream and downstream of the SNP site with significant association. The gene functions involved cell proliferation, control of cell metabolic pathways, and regulation of plant growth and development. This study furnishes a set of candidate genetic markers and crucial evidence for molecular breeding of N. yezoensis.

参考文献

[1] 周伟,胡传明,陆勤勤,等.条斑紫菜的种质创新与应用[J].广西科学院学报,2021,37(1):46-52.Zhou W,Hu C M,Lu Q Q,et al.Germplasm innovation and application of Pyropia yezoensis[J].Journal of Guangxi Academy of Sciences,2021,37(1):46-52.

[2] Collard B C Y,Mackill D J.Marker-assisted selection:An approach for precision plant breeding in the twenty-first century[J].Philosophical Transactions of the Royal Society B:Biological Sciences,2007,363(1491):557-572.

[3] Raina V S,Kour A,Chakravarty A K,et al.Marker-assisted selection vis-à-vis bull fertility:Coming full circle-a review[J].Molecular Biology Reports,2020,47(11):9123-9133.

[4] Fujino K,Hirayama Y,Kaji R.Marker-assisted selection in rice breeding programs in Hokkaido[J].Breeding Science,2019,69(3):383-392.

[5] Uffelmann E,Huang Q Q,Munung N S,et al.Genome-wide association studies[J].Nature Reviews Methods Primers,2021,1(1):59.

[6] Risch N,Merikangas K.The future of genetic studies of complex human diseases[J].Science,1996,273(5281):1516-1517.

[7] Ozaki K,Ohnishi Y,Iida A,et al.Functional SNPs in the lymphotoxin-α gene that are associated with susceptibility to myocardial infarction[J].Nature Genetics,2002,32(4):650-654.

[8] Doebley J,Aranzana M J,Kim S,et al.Genome-wide association mapping in Arabidopsis identifies previously known flowering time and pathogen resistance genes[J].PLoS Genetics,2005,1(5):e60.

[9] Tibbs Cortes L,Zhang Z,Yu J.Status and prospects of genome-wide association studies in plants[J].The Plant Genome,2021,14(1):e20077.

[10] Aulchenko Y S,De Koning D J,Haley C.Genomewide rapid association using mixed model and regression:A fast and simple method for genomewide pedigree-based quantitative trait loci association analysis[J].Genetics,2007,177(1):577-585.

[11] Beló A,Zheng P,Luck S,et al.Whole genome scan detects an allelic variant of fad2 associated with increased oleic acid levels in maize[J].Molecular Genetics and Genomics,2007,279(1):1-10.

[12] Ersoz E S,Yu J,Buckler E S.Applications of linkage disequilibrium and association mapping in crop plants[M]// Tuberosa R Genomics-Assisted Crop Improvement:Vol 1:Genomics Approaches and Platforms.[s.l.]:Springer,2007:97-119.

[13] Liu H J,Yan J.Crop genome-wide association study:A harvest of biological relevance[J].The Plant Journal,2018,97(1):8-18.

[14] Jin Y,Zhou T,Geng X,et al.A genome-wide association study of heat stress-associated SNPs in catfish[J].Animal Genetics,2016,48(2):233-236.

[15] Geng X,Sha J,Liu S,et al.A genome-wide association study in catfish reveals the presence of functional hubs of related genes within QTLs for columnaris disease resistance[J].BMC Genomics,2015,16(1):196.

[16] Feng X,Xiao B,Jiang M,et al.Identification of candidate genes related to two economic traits using GWAS in Gracilariopsis lemaneiformis (Rhodophyta)[J].Algal Research,2023,76:103309.

[17] Chen S F,Zhou Y Q,Chen Y R,et al.fastp:An ultra-fast all-in-one FASTQ preprocessor[J].Bioinformatics,2018,34(17):884-890.

[18] de Sena Brandine G,Smith A D.Falco:High-speed FastQC emulation for quality control of sequencing data[J].F1000 Research,2019,8:1874.

[19] Ewels P,Magnusson M,Lundin S,et al.MultiQC:Summarize analysis results for multiple tools and samples in a single report[J].Bioinformatics,2016,32(19):3047-3048.

[20] Li H,Handsaker B,Wysoker A,et al.The sequence alignment/map format and SAMtools[J].Bioinformatics,2009,25(16):2078-2079.

[21] Van Der Auwera G A,Carneiro M O,Hartl C,et al.From fastQ data to high-confidence variant calls:The genome analysis toolkit best practices pipeline[J].Current Protocols in Bioinformatics,2013,43(1110):1-33.

[22] Danecek P,Auton A,Abecasis G,et al.The variant call format and VCFtools[J].Bioinformatics,2011,27(15):2156-2158.

[23] Wang K,Li M,Hakonarson H.ANNOVAR:Functional annotation of genetic variants from high-throughput sequencing data[J].Nucleic Acids Research,2010,38(16):e164.

[24] Nguyen L T,Schmidt H A,Von Haeseler A,et al.IQ-TREE:A fast and effective stochastic algorithm for estimating maximum-likelihood phylogenies[J].Molecular Biology and Evolution,2015,32(1):268-274.

[25] Nagy P,Szabó á,Váradi T,et al.Maximum likelihood estimation of FRET efficiency and its implications for distortions in pixelwise calculation of FRET in microscopy[J].Cytometry Part A,2014,85(11):942-952.

[26] Dominguez Mantes A,Mas Montserrat D,Bustamante C D,et al.Neural ADMIXTURE for rapid genomic clustering[J].Nature Computational Science,2023,3(7):621-629.

[27] Zhang C,Dong S S,Xu J Y,et al.PopLDdecay:A fast and effective tool for linkage disequilibrium decay analysis based on variant call format files[J].Bioinformatics,2019,35(10):1786-1788.

[28] Vogt F,Shirsekar G,Weigel D,et al.vcf2gwas:Python API for comprehensive GWAS analysis using GEMMA[J].Bioinformatics,2022,38(3):839-840.

[29] Curtin F,Schulz P.Multiple correlations and bonferroni’s correction[J].Biological Psychiatry,1998,44(8):775-777.

[30] Aspichueta P,Shim H,Chasman D I,et al.A multivariate genome-wide association analysis of 10 LDL subfractions,and their response to statin treatment,in 1868 caucasians[J].PLoS One,2015,10(4):e0120758.

[31] 肖扬,陈康,丛倩倩,等.平菇品种的黄斑病抗病性及其与主要农艺性状相关性分析[J].食药用菌,2021,29(6):509-512.Xiao Y,Chen K,Cong Q Q,et al.Analysis of resistance to yellow blotch disease of Pleurotus ostreatus and its correlation with the main agronomic characters[J].Edible and Medicinal Mushrooms,2021,29(6):509-512.

[32] Zhou X,Stephens M.Genome-wide efficient mixed-model analysis for association studies[J].Nature Genetics,2012,44(7):821-824.

[33] Barsh G S,Sul J H,Martin L S,et al.Population structure in genetic studies:Confounding factors and mixed models[J].PLoS Genetics,2018,14(12):e1007309.

[34] Yu J,Pressoir G,Briggs W H,et al.A unified mixed-model method for association mapping that accounts for multiple levels of relatedness[J].Nature Genetics,2005,38(2):203-208.

[35] Zhu F,Sun H,Jiang L,et al.Genome-wide association study for growth-related traits in golden pompano (Trachinotus ovatus)[J].Aquaculture,2023,572:739549.

[36] Wang D,Yu X,Xu K,et al.Pyropia yezoensis genome reveals diverse mechanisms of carbon acquisition in the intertidal environment[J].Nature Communications,2020,11(1):4028.

[37] Zhang M,Su J,Zhang Y,et al.Conveying endogenous and exogenous signals:MAPK cascades in plant growth and defense[J].Current Opinion in Plant Biology,2018,45:1-10.

[38] Zhu Z,Wang T,Lan J,et al.Rice MPK17 plays a negative role in the Xa21-mediated resistance against Xanthomonas oryzae pv.oryzae[J].Rice,2022,15(1):41.

[39] Mulichak A M,Theisen M J,Essigmann B,et al.Crystal structure of SQD1,an enzyme involved in the biosynthesis of the plant sulfolipid headgroup donor UDP-sulfoquinovose[J].Proceedings of the National Academy of Sciences,1999,96(23):13097-13102.

[40] Sun Y,Jain A,Xue Y,et al.OsSQD1 at the crossroads of phosphate and sulfur metabolism affects plant morphology and lipid composition in response to phosphate deprivation[J].Plant,Cell & Environment,2020,43(7):1669-1690.

[41] Den Boer B G W,Murray J A H.Control of plant growth and development through manipulation of cell-cycle genes[J].Current Opinion in Biotechnology,2000,11(2):138-145.

[42] Strzalka W,Ziemienowicz A.Proliferating cell nuclear antigen (PCNA):A key factor in DNA replication and cell cycle regulation[J].Annals of Botany,2011,107(7):1127-1140.

[43] Jackson S P,Bartek J.The DNA-damage response in human biology and disease[J].Nature,2009,461(7267):1071-1078.

[44] Chatterjee N,Walker G C.Mechanisms of DNA damage,repair,and mutagenesis[J].Environmental and Molecular Mutagenesis,2017,58(5):235-263.

[45] Kow Y W.Repair of deaminated bases in DNA[J].Free Radical Biology and Medicine,2002,33(7):886-893.

[46] Krasikova Y,Rechkunova N,Lavrik O.Nucleotide excision repair:From molecular defects to neurological abnormalities[J].International Journal of Molecular Sciences,2021,22(12):6220.

[47] Jiricny J.The multifaceted mismatch-repair system[J].Nature Reviews Molecular Cell Biology,2006,7(5):335-346.

[48] Fang C,Fernie A R,Luo J.Exploring the diversity of plant metabolism[J].Trends in Plant Science,2019,24(1):83-98.

[49] Zhou X,Liu Z.Unlocking plant metabolic diversity:A (pan)-genomic view[J].Plant Communications,2022,3(2):100300.

[50] Huang A C,Jiang T,Liu Y X,et al.A specialized metabolic network selectively modulates Arabidopsis root microbiota[J].Science,2019,364(6440):eaau6389.

[51] Bai Y,Fernández-Calvo P,Ritter A,et al.Modulation of Arabidopsis root growth by specialized triterpenes[J].New Phytologist,2021,230(1):228-243.

[52] Shanti B,Joy Y L.Riboflavin metabolism:Role in mitochondrial function[J].Journal of Translational Genetics and Genomics,2020,4(4):285-306.

基本信息:

DOI:10.16441/j.cnki.hdxb.20240294

中图分类号:S917.3

引用信息:

[1]王士宽,唐磊,王俊皓,等.基于全基因组关联分析挖掘条斑紫菜配子体生长性状遗传位点[J].中国海洋大学学报(自然科学版),2025,55(12):64-78.DOI:10.16441/j.cnki.hdxb.20240294.

基金信息:

国家重点研究发展计划项目(2023YFD2400101)资助~~

检 索 高级检索

引用

GB/T 7714-2015 格式引文
MLA格式引文
APA格式引文