Novel insights into the genetic relationship between growth and disease resistance in an aquaculture strain of Coho salmon (Oncorhynchus kisutch)
Novel insights into the genetic relationship between growth and disease resistance in an aquaculture strain of Coho salmon (Oncorhynchus kisutch)
复制标题
对银鲑鱼（Oncorhynchus kisutch）水产养殖品种生长和抗病性之间遗传关系的新见解
DOI：
10.1016/j.aquaculture.2019.734207
复制
发表时间：
2019
期刊：
影响因子：
4.5
通讯作者：
Barría A
中科院分区：
文献类型：
--
作者：
Barría A
为了减轻水产养殖中的传染病问题，抗病育种已成为一种非常可取的策略。然而，在将抗病纳入育种目标之前，了解抗病与其他重要经济性状(如生长)之间的遗传关系是很重要的。我们的研究在一个大型细菌感染挑战实验中评估了生长和生存特征之间的遗传相关性。来自107个全同胞家庭的2606条大马哈鱼个体被用鲑鱼双胞菌进行挑战。生长以实验感染前(ADG0)和感染期间(ADGi)的平均日增重(ADG0)和收获重(HW)来测量。以生存时间(ST)和二项生存时间(BS)作为耐药指标。此外，细菌负荷(BL)的个体测量被评估为新的耐药表型，并提供了鲑鱼物种耐受性的遗传变异的指示。抗性家系的细菌载量低于敏感家系。鲑鱼。此外，一些属于抗药性家族的幸存鱼类被认为是无细菌的，因为它们的细菌负荷低于检测阈值。将LogBL作为一个协变量加入到感染下的生长和存活模型中，显示出显著的遗传变异，其中ADG0(0.30 ± 0.05)、HW(0.38 ± 0.03)、存活性状ST(0.16 ± 0.03)和BS(0.18 ± 0.03)具有显著的中等遗传力。相反，仅对存活者的性状进行评估时，日增重和对数转化的体重的遗传力较低(分别为0.07 ± 0.02(显著)和0.04 ± 0.03)，但这两个遗传力提高到中等显著水平(分别为0.20 ± 0.09和0.12 ± 0.05)。ADG0与ADGi(0.40 ± 0.16)、HW(0.64 ± 0.09)以及抗性与ST(0.43 ± 0.18)之间存在显著的遗传相关，表明在感染早期和感染前遗传增长率较高的鱼类不仅倾向于在收获前保持其遗传生长优势，而且在感染期间生长更快，存活时间更长。尽管HW和ST之间存在显著的不良相关性(−0.50 ± 0.13)，但仅使用来自死亡患者的未经审查的数据，该值降至−0.35 ± 0.20。同样，ADG0与LogBL或ADG0与本研究中考虑的任何其他性状之间没有明显的不利遗传相关性。这些结果表明，在当前的鲑鱼种群中，为早期生长而进行的选择性繁殖有望在感染鲑鱼的情况下同时延长存活时间和生长性能，而不会对病原体负担产生负面影响。
Breeding for disease resistance has become a highly desirable strategy for mitigating infectious disease problems in aquaculture. However, knowledge of the genetic relationship between resistance and other economically important traits, such as growth, is important to assess prior to including disease resistance into the breeding goal. Our study assessed the genetic correlations between growth and survival traits in a large bacterial infection challenge experiment. A population of 2606 coho salmon individuals from 107 full-sibling families were challenged with the bacteriaPiscirickettsia salmonis. Growth was measured as average daily gain prior (ADG0) and during (ADGi) the experimental infection and as harvest weight (HW). Resistance was measured as Survival time (ST) and binary survival (BS). Furthermore, individual measures of bacterial load (BL) were assessed as new resistance phenotypes and to provide an indication of genetic variation in tolerance in salmonid species. Resistant families showed lower bacterial load than those susceptible toP. salmonis. Furthermore, some surviving fish belonging to resistant families, were considered as bacterial-free because their bacterial load was below the detection threshold. Adding logBL as a covariate into the models for growth under infection and survival indicated significant genetic variation in tolerance.Significant moderate heritabilities were estimated for ADG0 (0.30 ± 0.05), HW (0.38 ± 0.03), and for the survival traits ST (0.16 ± 0.03) and BS (0.18 ± 0.03). In contrast, heritabilities for ADGi and log-transformed BL were low (0.07 ± 0.02 (significant) and 0.04 ± 0.03, respectively), although these increased to moderate significant levels (0.20 ± 0.09 and 0.12 ± 0.05, respectively) when traits were assessed in survivors only. Significant favorable genetic correlations were found between ADG0 and ADGi (0.40 ± 0.16), HW (0.64 ± 0.09), and with resistance as ST (0.43 ± 0.18), indicating that fish with higher genetic growth rate early on and prior to infection not only tend to maintain their genetic growth advantage until harvest, but also tend to grow faster and survive longer during infection. Although a significant unfavorable correlation (−0.50 ± 0.13) between HW and ST was found, this value decreased to −0.35 ± 0.20 using uncensored data from non-survivors only. Similarly, no robust unfavorable genetic correlations between ADG0 and LogBL, or ADG0 and any of the other traits considered in this study, was identified. These results suggest that selective breeding for early growth, in the current coho salmon population, would be expected to simultaneously increase survival time and growth performance during an infection withPiscirickettsia salmonis, without negatively impacting on pathogen burden.
登录
查看更多内容
影响因子：
4.4
作者：
Correa K;Lhorente JP;López ME;Bassini L;Naswa S;Deeb N;Di Genova A;Maass A;Davidson WS;Yáñez JM
通讯作者：
Yáñez JM
影响因子：
6.7
作者：
Cunnington AJ
通讯作者：
Cunnington AJ
受新城疫病毒挑战的商业产蛋线的遗传分析
影响因子：
3.7
作者：
K. Rowland;A. Wolc;R. Gallardo;T. Kelly;Huaijun Zhou;J. Dekkers;S. Lamont
通讯作者：
S. Lamont
DOI：
10.1186/s12711-017-0312-7
发表时间：
2017-04-19
期刊：
Genetics, selection, evolution : GSE
影响因子：
--
作者：
Lough G;Rashidi H;Kyriazakis I;Dekkers JCM;Hess A;Hess M;Deeb N;Kause A;Lunney JK;Rowland RRR;Mulder HA;Doeschl-Wilson A
通讯作者：
Doeschl-Wilson A
DOI：
10.1017/s1357729800053972
发表时间：
2004-04-01
期刊：
ANIMAL SCIENCE
影响因子：
--
作者：
Bishop, SC;Jackson, F;Stear, MJ
通讯作者：
Stear, MJ