数量性状位点的相对选择效率

从理论上采用蒙特卡罗(Monte Carlo)模拟的方法研究了不同遗传力条件下数量性状位点的直接选择(DSQ)和以表型为基础的选择(TBS)在10个不重叠世代中的选择反应以及DSQ相对于TBS的优势。结果表明,在10个世代中DSQ的选择进展在几乎总是大于TBS的选择进展,说明DSQ较TBS具有优越性;但DSQ的相对选择效率(RSE)会随着世代数的增加而呈现较迅速下降的趋势,单个性状情况下RSE则呈直线下降的趋势。随着选择代数的增加,DSQ将失去其优越性,TBS在遗传进展上将超过DSQ。     

数量性状位点的相对选择效率

从理论上采用蒙特卡罗（Monte Carlo）模拟的方法研究了不同遗传力条件下数量性状位点的直接选择（DSQ）和以表型为基础的选择（TBS）在10个不重叠世代中的选择反应以及DSQ相对于TBS的优势。结果表明，在10个世代中DSQ的选择进展在几乎总是大于TBS的选择进展，说明DSQ较TBS具有优越性；但DSQ的相对选择效率（RSE）会随着世代数的增加而呈现较迅速下降的趋势，单个性状情况下RSE则呈直线下降的趋势。随着选择代数的增加，DSQ将失去其优越性，TBS在遗传进展上将超过DSQ。     

猪雌激素受体(ESR)基因的多态性分析

母猪的产仔数是一个重要的经济性状 ,产仔数的提高将大大增加肉猪的产量 ,给养猪业带来巨大的经济效益 ,因此 ,有效地提高猪的产仔数一直是猪育种的主要目标之一。由于猪产仔数的遗传力很低 (约为 0 .1 ) ,并且要等到母猪产仔后才能度量 ,这种传统的选育方法其育种周期长、遗传进展小 ,因此开发和利用新的选育标记来提高猪的繁殖性就倍受重视。随着现代分子生物学和分子遗传学的发展 ,使得寻找多仔基因的遗传标记和标记辅助选择(Ｍａｒｋｅｒａｓｓｉｓｔｅｄｓｅｌｅｃｔｉｏｎ ,ＭＡＳ)成为可能。 1 994年Ｒｏｔｈｓｃｈｉｌｄ通过候选基…     

马氏珠母贝早期生长性状的遗传参数估计

以马氏珠母贝选育系F6代为亲本,采用巢式设计方法和人工解剖授精技术,依照1雄配3雌的原则,建立了8个父系半同胞家系和24个母系全同胞家系,在第8、21、35和50天测定了每个母系全同胞个体的壳长和壳高,以全同胞组内相关分析法估计马氏珠母贝早期生长性状的遗传参数。结果表明,母系半同胞个体具有较大的变异程度,存在着较大的母性效应,父系半同胞组内相关分析法估算的狭义遗传力是马氏珠母贝遗传力的估计值。8-50日龄壳长狭义遗传力估计值为0.11~1.14,壳高狭义遗传力估计值为0.12~1.04,其中利用父系半同胞组内相关法估计壳长的遗传力依次为0.17、0.19、0.12、0.11,壳高的遗传力依次为0.20、0.23、0.13、0.12,属于中等遗传力。马氏珠母贝早期生长性状的遗传相关和表型相关表现为一定的正相关,相关系数的范围分别为0.528~0.746和0.747~0.921。在早期生长阶段以壳长或壳高为参数进行选择育种时,具有较大的遗传改良潜力。     

九孔鲍生长性状的遗传力及其相关性分析

采用平衡巢式设计方法和人工授精技术,构建九孔鲍(Haliotis diversicolor supertexta)12个半同胞家系和36个全同胞家系(每个雄鲍配3个雌鲍),分别测定每个母系生长到8月龄的全同胞个体30个后代的壳长、壳宽和体质量,应用数量遗传学的全同胞组内相关分析法,利用SPSS软件的GLM过程计算表型变量的原因方差组分,估算九孔鲍8月龄生长性状的遗传力以及性状间遗传相关和表型相关。结果表明:利用父系半同胞组内相关法估计的遗传力是九孔鲍各生长性状遗传力的无偏估计值,其中壳长、壳宽和体质量性状的狭义遗传力的估计值分别为0.285、0.264和0.343,属于中高等遗传力,显示出较高的选择育种潜力;基于父系半同胞遗传协方差组分及表型协方差分别估计的各性状间的遗传相关和表型相关表明,各性状间均表现出高的正相关,其中壳长―壳宽、壳长―体质量和壳宽―体质量性状间遗传相关的相关系数分别为0.947、0.934、0.902,表型相关的相关系数分别为0.910、0.791、0.760。经t检验,各性状间遗传相关和表型相关均有统计学意义(P<0.01)。研究表明,以任何一个生长性状为参数进行选育,均可达到改良九孔鲍生长的效果。     

军曹鱼群体遗传结构的AFLP分析

筛选出10对扩增片段长度多态分析技术(Amplified fragment length polymorphism,AFLP)的选择性扩增引物(E-aga/M-cgt、E-aga/M-cga、E-agc/M-cga、E-agg/M-cga、E-act/M-cgc、E-aag/M-cgc、E-aca/M-cga、E-aac/M-cgc、E-aac/M-cac和E-aac/M-cat),分析了4个军曹鱼(Rachycentron canadum)全人工繁育群体海南1(HN1)、海南2(HN2)、湛江(ZJ)和流沙湾(LS)的遗传结构。结果表明:总体多态位点比例(83.9%)、分化指数(0.427 8)和Shannon信息指数(0.614 9)均处于较高水平,遗传多样性丰富;主坐标分析和邻位连接树中LS-HN2支与ZJ-HN1支明显分离,各群体内多样性水平存在差异(遗传多样性大小依次为HN1、HN2、LS、ZJ),但总体基因流仍然较大(Nm=10.327),分子方差分析(AMOVA)获得的群内方差(53%)也略大于群间(47%)。     

凡纳滨对虾过氧化氢酶基因单核苷酸多态性及其与耐低溶氧性状的相关性

采用直接测序法研究凡纳滨对虾(Litopenaeus vannamei)过氧化氢酶(CAT)基因的单核苷酸多态性(SNP),并分析得到的基因型与凡纳滨对虾低溶氧耐受性状的关联性,寻找与凡纳滨对虾耐低溶氧性状相关的SNP标记。结果显示:在CAT基因外显子1第155碱基处发现1个SNP位点,为A→G颠换,表现为同义突变。在凡纳滨对虾群体中该位点等位基因A和G的频率分别为0.146和0.854,多态信息含量PIC值为0.218,属于低度多态性,群体在该基因座上符合哈温(Hardy-Weinberg)平衡(P0.05)。关联分析表明,CAT基因SNP位点不同基因型与低溶氧耐受性状关联性有统计学意义(χ~2=9.277,P=0.002),其中AG型在应激耐受组中占优势地位(52.17%)。CAT基因多态性与凡纳滨对虾低溶氧耐受性相关,可作为影响凡纳滨对虾耐低溶氧性状的候选基因,为凡纳滨对虾选育提供分子遗传标记。     

对流参数主分量旋转法在西昌地区雷暴预报中的应用

为研究对流参数主分量旋转方案对西昌地区雷暴预报的影响,利用2006~2008年雨季(6~9月)T213模式输出产品,采用F-分值法和主分量旋转法,分别初选和精选因子,并结合二元Logistic回归分析,建立了西昌北郊某站的雷暴释用预报的模型,并对该站2010年雨季雷暴进行预报试验。试验结果表明:精选因子的KMO检验值在0.65~0.85,且Bartlett球形度检验显著,说明该站的雷暴对流参数适用于因子分析;极大方差旋转能够较好地分离因子载荷,对雷暴信息的提取能力较强;试报的TS评分在0.3左右,24小时预报的Hedike评分可达0.337,模型的预报准确率较高,持续性较好。综上所述,采用主分量旋转法对雷暴的MOS预报有一定的改善效果。     

湖南省生态风险源-暴露-效应模型评价

生态风险是指在一定区域内,具有不确定性的事故或灾害对生态系统及其组分可能产生的作用.基于风险表征=风险源表征×暴露表征×生态效应表征理论框架模型,综合多风险源、风险暴露性、风险效应3方面因素,建立湖南省域生态风险评价指标体系;利用主成分分析法和地理信息系统技术,构建生态风险综合评价模型;计算综合生态风险值并识别湖南省域...     

翡翠贻贝三个野生种群形态性状的差异分析

运用差异系数检验、主成分分析、判别分析和聚类分析等4种多元统计分析方法,采用5个比例性状,比较研究了广西北海、广东湛江和汕尾的3个翡翠贻贝野生种群的形态性状差异。结果表明:(1)3个种群间5个比例性状的差异系数在0.024～1.134之间,种群间尚未达到亚种差异水平;(2)主成分分析构建了3个主成分,PC1、PC2和PC3贡献率分别为40.134%、27.956%和20.614%,累计贡献率为88.704%;(3)利用逐步判别法选择3个贡献率较大的性状进行判别分析,建立了3种群判别函数,判别准确率为P1为73.0%～88.0%,P2为74.6%～86.8%,综合判别率为79.7%;(4)聚类分析显示,北海种群与汕尾种群形态较为接近,湛江种群趋异程度最大。各种分析方法从不同角度反映了群体间的形态学差异,这种差异是环境和遗传共同作用的结果。     

Selection for growth performance of tank-reared Pacific white shrimp, Litopenaeus vannamei

Seven growth-related traits were measured to assess the selection response and genetic parameters of the growth of Pacific white shrimp, Litopenaeus vannamei, which had been domesticated in tanks for more than four generations. Phenotypic and genetic parameters were evaluated and fitted to an animal model. Realized response was measured from the difference between the mean growth rates of selected and control families. Realized heritability was determined from the ratio of the selection responses and selection differentials. The animal model heritability estimate over generations was 0.44±0.09 for body weight (BW), and ranged from 0.21±0.08 to 0.37±0.06 for size traits. Genetic correlations of phenotypic traits were more variable (0.51–0.97), although correlations among various traits were high (>0.83). Across generations, BW and size traits increased, while selection response and heritability gradually decreased. Selection responses were 12.28%-23.35% for harvest weight and 3.58%–13.53% for size traits. Heritability estimates ranged from 0.34±0.09 to 0.48±0.15 for harvest weight and 0.17±0.01–0.38±0.11 for size traits. All phenotypic and genetic parameters differed between various treatments. To conclude, the results demonstrated a potential for mass selection of growth traits in L. vannamei. A breeding scheme could use this information to integrate the effectiveness constituent traits into an index to achieve genetic progress.     

Growth performance of larval and juvenile manila clam (<Emphasis Type="Italic">Ruditapes philippinarum</Emphasis>) from divergently selected individuals of a full-sib family

In this study, the method of divergent selection was employed to test the larval and juvenile growth performance within a full-sib family of Manila clam Ruditapes philippinarum. The 10% largest and 10% smallest clam individuals (on the basis of shell length) of a full-sib family were selected as parents for the fast and slow growing lines, respectively. The difference in shell length was significant among the three lines (fast, control, and slow) tested. The sequence of shell length were fast line > control line > slow line. The responses to selection, realized heritability, and genetic gain were 0.06%–0.81%, 0.04%–0.47% and 0.58%–18.89% in the fast direction, respectively; and were 0.14%–1.27%, 0.08%–0.73%, and 0.31%–49.03% in the slow direction, respectively. The results suggested that there was a large portion of additive genetic variance affecting the growth in the full-sib family. Selection in the fast direction within the full-sib family would greatly improve the growth of R. philippinarum.     

Genetic mapping and QTL analysis for body weight in Jian carp (Cyprinus carpio var. Jian) compared with mirror carp (Cyprinus carpio L.)

We report the genetic linkage map of Jian carp(C yprinus carpio var. Jian). An F1 population comprising 94 Jian carp individuals was mapped using 254 microsatellite markers. The genetic map spanned 1 381.592 c M and comprised 44 linkage groups,with an average marker distance of 6.58 c M. We identified eight quantitative trait loci(QTLs) for body weight(BW) in seven linkage groups,explaining 12.6% to 17.3% of the phenotypic variance. Comparative mapping was performed between Jian carp and mirror carp( Cyprinus carpio L.),which both have 50 chromosomes. One hundred and ninety-eight Jian carp marker loci were found in common with the mirror carp map,with 186(93.94%) showing synteny. All 44 Jian carp linkage groups could be one-to-one aligned to the 44 mirror carp linkage groups,mostly sharing two or more common loci. Three QTLs for BW in Jian carp were conserved in mirror carp. QTL comparison suggested that the QTL confidence interval in mirror carp was more precise than the homologous interval in Jian carp,which was contained within the QTL interval in Jian carp. The syntenic relationship and consensus QTLs between the two varieties provide a foundation for genomic research and genetic breeding in common carp.     

Response to selection for fast growth in the second generation of Pacific oyster (Crassostrea gigas)

Mass selection for fast growth was conducted in three Pacific oyster (Crassostrea gigas) stocks from China, Japan and Korea using previously established lines (CS1, JS1, and KS1). To determine whether continuous progress can be achieved by selection for growth, the progeny of three second-generation Pacific oyster lines was selected for shell height and evaluated via a 400-day farming experiment. When harvested at the end of the experiment, the selected crosses of CS2, JS2, and KS2 lines grew by 9.2%, 10.2% and 9.6% larger than the control crosses, respectively. During grow-out stage, the genetic gain of three selected lines was (10.2 ± 1.4)%, (10.4 ± 0.3)%, and (8.4 ± 1.6)%, respectively; and the corresponding realized heritability was 0.457 ± 0.143, 0.312 ± 0.071 and 0.332 ± 0.009, respectively. These results indicated that the selection for fast growth achieved steady progress in the second generation of oyster. Our work provides supportive evidence for the continuity of the Pacific oyster selective breeding program.     

Mass Selection for Fast Growth in the Third Generation of the Orange Line of the Manila Clam Ruditapes philippinarum

The Manila clam Ruditapes philippinarum is natively distributed along the Pacific coast of Asia, where it is one of the most important bivalve species for local fisheries. This species has been intentionally introduced due to its high adaptability to various coastal environments and is currently widely cultivated in Europe and North America. We have initiated a selective breeding program to improve the growth rate of the Manila clam since 2007, and a full-sib family with orange shell color was selected. This family features high survival but slow growth. Thereafter, two generations of mass selection were conducted in this family by 10% upward selection for faster growth. In 2011, three types of lines were produced by selecting the breeder from the second-generation of selected lines. These lines are SS(subject to three generations of selection for growth in shell length), SC(selected for the second but not the third generation), and C(randomly sampled individuals from the national population). The genetic parameters of the shell length including hR2(realized heritability), SR(selection response), and GG(genetic gain) were analyzed. Results showed that the shell length of the SS line was significantly larger than those of the SC and C lines at all developmental stages(P 0.05). For the larval stage, the values of hR2, SR, and GG were 0.42, 0.73, and 6.66, respectively. For the juvenile stage, the values of hR2, SR, and GG were 0.40, 0.69, 21.76, respectively. For grow-out stage, the values of hR2, SR, and GG were 0.48, 0.83, and 18.22, respectively. The results of hR2 indicated the good potential of the SS line in selective breeding. The level of GG improvement was encouraging and consistent with the previous expectations. No inbreeding depressions in the shell length were observed in the SS and SC lines at all sampling days. All of the results indicate that maintaining selection pressure in successive generations may be effective in the selective breeding program of this family.     

Performance Comparison of Two Efficient Genomic Selection Methods(gsbay & MixP ) Applied in Aquacultural Organisms

Genomic selection is more and more popular in animal and plant breeding industries all around the world, as it can be applied early in life without impacting selection candidates. The objective of this study was to bring the advantages of genomic selection to scallop breeding. Two different genomic selection tools Mix P and gsbay were applied on genomic evaluation of simulated data and Zhikong scallop(Chlamys farreri) field data. The data were compared with genomic best linear unbiased prediction(GBLUP) method which has been applied widely. Our results showed that both Mix P and gsbay could accurately estimate single-nucleotide polymorphism(SNP) marker effects, and thereby could be applied for the analysis of genomic estimated breeding values(GEBV). In simulated data from different scenarios, the accuracy of GEBV acquired was ranged from 0.20 to 0.78 by Mix P; it was ranged from 0.21 to 0.67 by gsbay; and it was ranged from 0.21 to 0.61 by GBLUP. Estimations made by Mix P and gsbay were expected to be more reliable than those estimated by GBLUP. Predictions made by gsbay were more robust, while with Mix P the computation is much faster, especially in dealing with large-scale data. These results suggested that both algorithms implemented by Mix P and gsbay are feasible to carry out genomic selection in scallop breeding, and more genotype data will be necessary to produce genomic estimated breeding values with a higher accuracy for the industry.     

Performance comparison of two efficient genomic selection methods (gsbay &amp; MixP) applied in aquacultural organisms

Genomic selection is more and more popular in animal and plant breeding industries all around the world, as it can be applied early in life without impacting selection candidates. The objective of this study was to bring the advantages of genomic selection to scallop breeding. Two different genomic selection tools MixP and gsbay were applied on genomic evaluation of simulated data and Zhikong scallop (Chlamys farreri) field data. The data were compared with genomic best linear unbiased prediction (GBLUP) method which has been applied widely. Our results showed that both MixP and gsbay could accurately estimate single-nucleotide polymorphism (SNP) marker effects, and thereby could be applied for the analysis of genomic estimated breeding values (GEBV). In simulated data from different scenarios, the accuracy of GEBV acquired was ranged from 0.20 to 0.78 by MixP; it was ranged from 0.21 to 0.67 by gsbay; and it was ranged from 0.21 to 0.61 by GBLUP. Estimations made by MixP and gsbay were expected to be more reliable than those estimated by GBLUP. Predictions made by gsbay were more robust, while with MixP the computation is much faster, especially in dealing with large-scale data. These results suggested that both algorithms implemented by MixP and gsbay are feasible to carry out genomic selection in scallop breeding, and more genotype data will be necessary to produce genomic estimated breeding values with a higher accuracy for the industry.