渔业科学进展
漁業科學進展
어업과학진전
MARINE FISHERIES RESEARCH
2014年
6期
133-140
,共8页
栾生%隋娟%孟宪红%罗坤%曹宝祥%孔杰
欒生%隋娟%孟憲紅%囉坤%曹寶祥%孔傑
란생%수연%맹헌홍%라곤%조보상%공걸
最佳遗传贡献%优化算法%选择育种%水产动物
最佳遺傳貢獻%優化算法%選擇育種%水產動物
최가유전공헌%우화산법%선택육충%수산동물
Optimum contribution theory%Optimization algorithm%Selective breeding%Aquatic animal
水产动物多性状复合育种技术已发展成为国内水产选择育种的重要技术体系。在限定的近交水平下，如何选种和配种实现遗传进展最大化是当前该体系亟待解决的一个突出问题。在动植物选择育种中，最佳遗传贡献理论(Optimum Contribution, OC)已成为平衡育种核心群长期遗传进展与近交水平的有效工具。本文论述了OC理论的提出背景和发展过程、不同优化算法的特点和该理论在动植物选择育种中的应用进展，并进一步综述了基于基因组信息的OC理论研究新进展。遗传贡献目标函数的优化算法主要包括拉格朗日乘数法、半正定规划法和差分进化算法等。基于拉格朗日乘数法，执行 OC 选择10代后获得的遗传进展要比最佳线性无偏预测法(Best Linear Unbiased Prediction, BLUP)育种值直接选择高21%?60%。针对水产动物等高繁殖力大群体，育种学家进一步改进了算法，利用候选亲本父母本群体的加性遗传相关矩阵来计算候选亲本群体的加性遗传相关矩阵和逆矩阵，降低了逆矩阵的维数，提高了最佳遗传贡献值的计算效率。但是拉格朗日乘数法并不能保证求解出的遗传贡献值为全局最大值，而半正定规划方法利用内点算法可以获得候选亲本的最佳遗传贡献值，与前者相比遗传进展可进一步提高1.5%?9%。差分进化算法可将遗传进展、遗传多样性、后代近交、场间遗传联系、多阶段选择、分子标记利用和成本等多种因素纳入目标函数进行优化，同时完成个体选择和交配方案制定两个关键任务。复合系谱和基因组信息，在限定的近交水平下，可以获得更为准确的遗传贡献值，遗传进展可进一步提高。OC选择已经应用在畜牧、林木育种研究中，育种群体的近交水平得到了有效控制，与BLUP直接选择相比，目标性状的遗传进展进一步提高(17%?30%)。针对水产动物多性状复合育种技术体系的特点，本文分析了OC理论应用的紧迫性和可行性，提出了亟待解决的关键技术问题和解决方案，为下一步在水产动物选择育种中应用OC理论提供借鉴和指导。
水產動物多性狀複閤育種技術已髮展成為國內水產選擇育種的重要技術體繫。在限定的近交水平下，如何選種和配種實現遺傳進展最大化是噹前該體繫亟待解決的一箇突齣問題。在動植物選擇育種中，最佳遺傳貢獻理論(Optimum Contribution, OC)已成為平衡育種覈心群長期遺傳進展與近交水平的有效工具。本文論述瞭OC理論的提齣揹景和髮展過程、不同優化算法的特點和該理論在動植物選擇育種中的應用進展，併進一步綜述瞭基于基因組信息的OC理論研究新進展。遺傳貢獻目標函數的優化算法主要包括拉格朗日乘數法、半正定規劃法和差分進化算法等。基于拉格朗日乘數法，執行 OC 選擇10代後穫得的遺傳進展要比最佳線性無偏預測法(Best Linear Unbiased Prediction, BLUP)育種值直接選擇高21%?60%。針對水產動物等高繁殖力大群體，育種學傢進一步改進瞭算法，利用候選親本父母本群體的加性遺傳相關矩陣來計算候選親本群體的加性遺傳相關矩陣和逆矩陣，降低瞭逆矩陣的維數，提高瞭最佳遺傳貢獻值的計算效率。但是拉格朗日乘數法併不能保證求解齣的遺傳貢獻值為全跼最大值，而半正定規劃方法利用內點算法可以穫得候選親本的最佳遺傳貢獻值，與前者相比遺傳進展可進一步提高1.5%?9%。差分進化算法可將遺傳進展、遺傳多樣性、後代近交、場間遺傳聯繫、多階段選擇、分子標記利用和成本等多種因素納入目標函數進行優化，同時完成箇體選擇和交配方案製定兩箇關鍵任務。複閤繫譜和基因組信息，在限定的近交水平下，可以穫得更為準確的遺傳貢獻值，遺傳進展可進一步提高。OC選擇已經應用在畜牧、林木育種研究中，育種群體的近交水平得到瞭有效控製，與BLUP直接選擇相比，目標性狀的遺傳進展進一步提高(17%?30%)。針對水產動物多性狀複閤育種技術體繫的特點，本文分析瞭OC理論應用的緊迫性和可行性，提齣瞭亟待解決的關鍵技術問題和解決方案，為下一步在水產動物選擇育種中應用OC理論提供藉鑒和指導。
수산동물다성상복합육충기술이발전성위국내수산선택육충적중요기술체계。재한정적근교수평하，여하선충화배충실현유전진전최대화시당전해체계극대해결적일개돌출문제。재동식물선택육충중，최가유전공헌이론(Optimum Contribution, OC)이성위평형육충핵심군장기유전진전여근교수평적유효공구。본문논술료OC이론적제출배경화발전과정、불동우화산법적특점화해이론재동식물선택육충중적응용진전，병진일보종술료기우기인조신식적OC이론연구신진전。유전공헌목표함수적우화산법주요포괄랍격랑일승수법、반정정규화법화차분진화산법등。기우랍격랑일승수법，집행 OC 선택10대후획득적유전진전요비최가선성무편예측법(Best Linear Unbiased Prediction, BLUP)육충치직접선택고21%?60%。침대수산동물등고번식력대군체，육충학가진일보개진료산법，이용후선친본부모본군체적가성유전상관구진래계산후선친본군체적가성유전상관구진화역구진，강저료역구진적유수，제고료최가유전공헌치적계산효솔。단시랍격랑일승수법병불능보증구해출적유전공헌치위전국최대치，이반정정규화방법이용내점산법가이획득후선친본적최가유전공헌치，여전자상비유전진전가진일보제고1.5%?9%。차분진화산법가장유전진전、유전다양성、후대근교、장간유전련계、다계단선택、분자표기이용화성본등다충인소납입목표함수진행우화，동시완성개체선택화교배방안제정량개관건임무。복합계보화기인조신식，재한정적근교수평하，가이획득경위준학적유전공헌치，유전진전가진일보제고。OC선택이경응용재축목、림목육충연구중，육충군체적근교수평득도료유효공제，여BLUP직접선택상비，목표성상적유전진전진일보제고(17%?30%)。침대수산동물다성상복합육충기술체계적특점，본문분석료OC이론응용적긴박성화가행성，제출료극대해결적관건기술문제화해결방안，위하일보재수산동물선택육충중응용OC이론제공차감화지도。
Aquatic multi-trait integrated breeding system is an important selective breeding technology to improve economic traits of aquatic animals in China. It has been a vital issue how to select and mate the broodstock candidates to maximize the genetic gain at a defined rate of inbreeding in the breeding system. The optimum contribution theory (OC) has become an effective tool to establish equilibrium between the genetic gain and the inbreeding in the nucleus population. In this review we introduced the establishment and development of optimum contribution theory, the characteristics of different optimization algorithms, and its application in selective breeding of plants and animals. Three algorithms, Lagrange multipliers, Semidefinite programming and Differential evolution, have been used in the calculation of optimum genetic contribution. At equal rates of inbreeding, genetic gains calculated with Lagrange multipliers were 21%–60%greater than that with selection for BLUP-EBV. An improved algorithm based on Lagrange multipliers was invented for the calculation of optimal genetic contributions in the case of large number of candidates in the aquatic animal population. The additive relationship matrix between the selection candidates and the inverse of this matrix was replaced with the relationship matrix between the parents of the selection candidates and its inverse in the calculation of the optimal genetic contribution of the selection candidates to the next generation. Lagrange multipliers did not guarantee that the final solution is the global maximum;on the contrast the SDP method could always find the optimum solution that maximized the genetic gain using the interior point algorithms. The expected gains obtained from the Semidifinite programming were 1.5%–9% greater than that from Lagrange multipliers. Individual selection and mate allocation could be performed using Differential evolution algorithm. Many issues including genetic gain, diversity, progeny inbreeding, connections among farms, multi-stage selection, management of genetic marker, and various types of costs could be contained in the object function and be optimized. Genetic gain and the accuracy of optimum contribution could be increased using the pedigree and genomic information at predefined rate of inbreeding. The inbreeding level of selective breeding population was effectively controlled and genetic gains of object traits were 17%–30% greater than that of selection for BLUP-EBV in the livestock and forest breeding. New progress on the OC theory based on genomic information was also reviewed. The prospect of application of optimum contribution theory in aquatic selective breeding was analyzed in order to provide reference and guidance in aquatic animal breeding.
