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凡纳滨对虾生长和抗病性状的全基因组关联分析与基因组选择育种研究
王全超
学位类型博士
导师李富花
2017-05-18
学位授予单位中国科学院大学
学位授予地点北京
学位专业海洋生物学
关键词Snp标记 遗传育种 全基因组关联分析 基因组选择 对虾
摘要凡纳滨对虾(Litopenaeus vannamei)作为世界重要的海水养殖种类之一,其良种选育是产业发展的基石。过去十多年间,利用传统选择方法,凡纳滨对虾重要经济性状的遗传改良取得显著成效。然而,基于传统选择方法的遗传改良项目面临着选育周期长、成本高和选择准确性低等问题。因此,引进新的选育方法和技术对加快凡纳滨对虾经济性状的遗传改良具有重要意义。本文将全基因组关联分析(GWAS)和基因组选择(GS)引入到凡纳滨对虾经济性状遗传选育研究中,以期为凡纳滨对虾的遗传改良提供重要技术支撑。本论文取得的主要进展如下:
  1. 通过对凡纳滨对虾单个全同胞家系体长和体重的全基因组关联分析,获得52个与体长性状显著相关SNPs,47个与体重性状相关SNPs。通过基因注释、基因的SNPs发掘和群体水平统计验证,发现位于PKC基因的标记M1286-15-3与体重存在显著相关性,该标记的CC基因型个体平均体重明显高于CT型和TT型个体。通过分析PKC基因在对虾不同组织的转录表达水平,发现其在肌肉组织中的表达量最高,提示其可能是调控凡纳滨对虾生长的重要候选基因。
  2. 利用2b-RAD测序分型技术对由多家系组成的凡纳滨对虾混合群体进行SNP分型,在此基础上对体长和体重等生长性状进行全基因组关联分析。结果显示,与生长性状显著相关的SNPs分布于对虾基因组的多个连锁群上且数量较多,表明凡纳滨对虾生长相关性状可能由大量的具有微小效应的基因所控制。此外,通过对该混合群体的连锁不平衡分析,发现该群体的连锁不平衡衰减较快,当标记间物理距离升至18 kb时,r2便降至0.2。而本次研究,相邻标记间的平均距离约为226.12 kb,致使标记间的连锁不平衡较弱,降低了全基因组关联分析对生长相关基因的定位能力。因此,在未来研究中提高标记密度有助于提高标记间的连锁不平衡强度,从而提高全基因组关联分析的分辨率和准确性。
  3. 通过对多家系混合群体实施副溶血弧菌的人工感染实验,制备了凡纳滨对虾对弧菌的易感材料和抗性材料,在此基础上对弧菌抗性性状进行全基因组关联分析。结果显示,在基因组显著性水平为P<0.001时,总计筛选到8个与弧菌抗性相关联的SNPs。在建议显著性水平为P<0.01时,共筛选到187个显著性SNPs,其中108个SNPs成功定位至不同的连锁群上,且不同连锁群上显著相关的SNPs数量介于1至9个,说明对虾的弧菌抗性性状可能是一个由微效多基因控制的复杂数量性状。
  4. 为了解基因组选择应用于凡纳滨对虾生长性状遗传改良的可行性以及基因组预测模型对基因组选择准确性的影响,以来自于一个全同胞家系的凡纳滨对虾体长和体重为目标性状,利用分布于对虾全基因组的3 960个SNPs,对三个基因组预测模型(RR-BLUP,BayesA和Bayesian LASSO)的预测能力进行了评估。结果显示,三个模型对体长和体重预测的基因组估计育种值(GEBV)可靠性均值分别为0.296和0.411;对每个性状,三个基因组预测模型的表现极其相似;实际表型对预测表型的回归分析显示,三个模型的回归系数均接近于1,表明三个基因组模型对生长性状的预测均为无偏估计。因此,三个模型均可作为凡纳滨对虾生长性状基因组选择的候选模型。
  5. 为进一步了解基因组预测模型、标记密度和参考群体与验证群体之间的遗传关系对基因组选择准确性的影响,本研究在构建的多家系混合群体基础上,通过设计不同的交叉验证方案和评价策略对凡纳滨对虾生长性状的基因组选择进行了初步研究。结果显示,三个模型(RR-BLUP、BayesA和Bayesian LASSO)对体长和体重两个性状具有相似的基因组预测能力,因此它们都可作为凡纳滨对虾生长性状基因组选择的候选模型;相对较低的标记密度(3.2 K)可以用来实现对凡纳滨对虾生长性状的精确基因组选择;参考群体与候选群体之间的遗传关系能够极大地影响凡纳滨对虾生长性状的基因组选择准确性,且当参考群体与候选群体之间关系较远时,基因组选择的准确性会降低。因此,在实际应用时,在对选育基础群的群体结构进行分析的基础上优化参考群体的构成对保障基因组选择准确性具有决定性作用。此外,利用多家系混合材料及其基因组范围内的SNP分型数据,对凡纳滨对虾体重和体长的狭义遗传力进行了估算。结果显示,其体重和体长的遗传力分别为0.321和0.452,与多数基于系谱的研究结果相吻合,表明利用分子标记进行遗传力估算具有可行性,为后续遗传力等遗传参数的估计提供了新的选择。
其他摘要Selective breeding for important economic traits of Pacific white shrimp Litopenaeus vannamei (L. vannamei) is the foundation of shrimp aquaculture industry. During the past decade, the genetic improvement of important economic traits has made remarkable achievements by using traditional selective breeding approaches. However, the longtime breeding interval, high costs and low selection accuracy restricted the further development of selective breeding in L. vannamei. Therefore, it is extremely valuable to introduce new approaches to accelerate the process of genetic improvement of important economic traits in L. vannamei. Recently, the methods based on molecular markers, including genome-wide association study (GWAS) and genomic selection (GS), have been turned out to be promising candidate for the future application of selective breeding. In the present study, GWAS and GS has been evaluated in the breeding of L. vannamei. The main progresses achieved in this thesis are as follows:
  1. GWAS has been used to detect the markers associated with body length and body weight based on the analyses of 3 960 SNPs in a full-sib family of L. vannamei  The results showed that 52 SNPs were significantly associated with body length and 47 SNPs associated with body weight. Through further gene annotation and validation, we found that the SNP marker (M1286-15-3) located on protein kinase C (PKC) was significantly associated with body weight. The average body weight of individuals with CC genotype was significantly higher than that of the individuals with CT and TT genotype. The highest expression of PKC gene in the muscle of L. vannamei suggested that PKC might be an important gene in regulating the growth of shrimp.
  2. Through GWAS analyses, SNP markers associated with 10 growth-related traits were identified using a 2b-RAD genotyping platform based on a multi-family population These markers located on many linkage groups which suggested that the growth traits of L. vannamei were controlled by minor-polygenes. Besides, linkage disequilibrium (LD) analysis based on the multi-family population showed that the decay of LD was very fast. When the distance between markers was 18 kb, the value of r2 was 0.2. Considersing the average distance between adjacent markers was 226.12 kb in the current study, the marker density must be improved to increase the reliability of GWAS for the important economic traits of L. vannamei.
  3. The disease-resistance traits of L. vannamei were analyzed by GWAS to identify the related markers based on the resistant group and sensitve groups to Vibrio parahaemolyticus (V. parahaemolyticus) obtained by challenge test. The results showed that 8 SNPs were significantly associated with the resistance of L. vannamei to V. parahaemolyticus at genome-wide significance level with P<0.001 , and 187 SNPs were associated with the resistance at P<0.01. Through the positioning analysis of SNPs on the linkage groups, 108 SNPs associated with the resistance to V. parahaemolyticus at P<0.01 were mapped to 30 linkage groups, and the number of significantly associated SNPs in these linkage groups ranged from 1 to 9. These data gave us a hint that the resistance trait of L. vannamei to V. parahaemolyticus is a quantitative trait which was controled by a lot of QTLs with small effects.
  4. The performance of GS models was evaluated for the body length and body weight of L. vannamei using 3 960 SNPs genotyped in 205 individuals from a full-sib family. Three GS models (RR-BLUP, BayesA, and Bayesian LASSO) were used to calculate the GEBV, and their predictive ability was assessed by the reliability of the GEBV and the bias of the predicted phenotypes. The mean reliability of the GEBVs for body length and body weight predicted by different models was 0.296 and 0.411, respectively. For each trait, three models showed very similar performance with respect to the predictability. The regression coefficients estimated by three models were very close, Therefore, we suggested that three models appeared practicable when GS was applied in a L. vannamei population.
The potential factors that may influence the accuracy of GS in L. vannamei were investigated by different design of cross-validation in a multi-family population. At first, the heritability for L. vannamei based on the full set of markers (23K) was estimated to be 0.321 for body weight, and 0.452 for body length. The estimated heritability increased rapidly with the increase of the marker density from 0.05K to 3.2K, and then it tended to be stable for both traits. For genomic prediction on the growth traits of L. vannamei, three statistic models (RR-BLUP, BayesA and Bayesian LASSO) showed similar performance for the prediction accuracy of genomic estimated breeding value (GEBV). The prediction accuracy will be increased with the increasing of marker density. However, the marker density would bring a weak effect on the prediction accuracy when the marker number increased to 3.2K. In addition, genetic distance can influence the GS accuracy significantly. A distant genetic relationship between reference and validation population would result in a poor performance of genomic prediction for growth traits in L. vannamei.
语种中文
文献类型学位论文
条目标识符http://ir.qdio.ac.cn/handle/337002/136530
专题实验海洋生物学重点实验室
作者单位中国科学院海洋研究所
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王全超. 凡纳滨对虾生长和抗病性状的全基因组关联分析与基因组选择育种研究[D]. 北京. 中国科学院大学,2017.
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