Grass carp (Ctenopharyngodon idella) is a highly productive freshwater fish species that is widely cultivated worldwide, contributing substantial economic value to the aquaculture industry annually. Recently, a breeding program for grass carp has progressed to the fourth generation (F4) after four consecutive generations of family selection. To further assess the growth performance of the genetically selected grass carp F4, a 90-day consecutive growth comparison experiment was conducted between the selected population and a wild base population. The results showed that the selected grass carp F4 had better growth performance. Whole-genome resequencing of both wild and selected populations of grass carp yielded a total of 4,354,416 high-quality single nucleotide polymorphisms (SNPs). Parameters of genetic diversity including observed heterozygosity (Ho), expected heterozygosity (He), nucleotide diversity (pi), and polymorphic information content (PIC) were slightly decreased in the selected population compared to the wild population. The fixation index (Fst) indicated a low level of genetic differentiation (Fst = 0.021). Selection signatures analysis identified a total of 173 candidate selected regions with a cumulative size of 23.75 Mb, and 912 candidate genes including igf-1r, igfbp-2, igfbp-5 and itga6. This study provides valuable insights into the growth performance and the genetic basis of selection signatures in the process of grass carp selective breeding, and offers guidance for future breeding programs.

Grass carp (Ctenopharyngodon idella) is a highly productive freshwater fish species that annually contributes significant economic value to the aquaculture industry. However, its production is frequently affected by grass carp haemorrhagic disease (GCHD), which is caused by grass carp reovirus (GCRV). To elucidate the molecular mechanism of GCRV resistance in C. idella, whole-genome resequencing of both susceptible and resistant C. idella was conducted, yielding a total of 3,941,776 high quality single nucleotide polymorphisms (SNPs). A genome-wide association study (GWAS) then identified five significant SNPs, located on chromosomes 2, 3, 5, 6 and 10, associated with the trait of GCRV resistance. An integrative analysis of the GWAS and a previous transcriptome study was performed, and five common genes were identified, including b4galt2 (β-1,4-galactosyltransferase 2), kif2c (Kinesin family member 2C), jmjd8 (JmjC domain containing 8), selenom (Selenoprotein M), and znfx1 (Zinc finger NFX1-type containing 1). This study serves as a valuable basis for implementing marker-assisted selection (MAS) to improve GCRV resistance in C. idella breeding programs, and provides insight into developing methods to control the spread of GCHD.

Grass carp ( Ctenopharyngodon idella ) is one of the most economically important fish in China, and its production is commonly lost due to GCRV infection. To understand the molecular mechanism of GCRV resistance in grass carp, we compared the spleen transcriptome of the GCRV-resistant and susceptible individuals under GCRV infection (Res-Sus) and the GCRV-resistant individuals under different conditions of injection with GCRV and PBS (Res-Ctl). A total of 87.56 GB of clean data were obtained from 12 transcriptomic libraries of spleen tissues. A total of 379 DEGs (156 upregulated genes and 223 downregulated genes) were identified in the comparison group Res-Ctl. A total of 1207 DEGs (633 upregulated genes and 574 downregulated genes) were identified in the comparison group Res-Sus. And 54 DEGs were shared including immune-related genes of stc2 (stanniocalcin 2), plxna1 (plexin A1), ifnα (interferon alpha), cxcl 11 (C-X-C motif chemokine ligand 11), ngfr (nerve growth factor receptor), mx (MX dynamin-like GTPase), crim1 (cysteine-rich transmembrane BMP regulator 1), plxnb2 (plexin B2), and slit2 (slit guidance ligand 2). KEGG pathway analysis revealed significant differences in the expression of genes mainly involved in immune system and signal transduction, including antigen processing and presentation, Toll-like receptor signaling pathway, natural killer cell-mediated cytotoxicity, and Hippo signaling pathway. This study investigates the immune mechanism of the resistance to GCRV infection in grass carp and provides useful information for the development of methods to control the spread of the GCRV infection.

为了分析草鱼(Ctenopharyngodon idella)选育群体不同世代的遗传变异和遗传结构,本研究利用了已建立的一套标准微卫星标记对草鱼长江选育群体F0、F3、F4进行了遗传变异的评估,并与黑龙江选育群体和珠江选育群体进行了遗传变异的比较分析.实验结果表明长江选育群体的各世代均具有高度的遗传多样性(PIC＞0.05),且长江选育群体的遗传多样性相对于黑龙江和珠江选育群体的遗传多样性水平更高(P＜0.05).遗传分化指数(Fst)分析结果表明,长江选育群体F0、F3、F4之间遗传分化的水平较低(0＜Fst＜0.05);长江选育群体,与黑龙江和珠江选育群体之间都具有中等程度的遗传分化水平(0.05＜Fst＜0.15).分子方差分析(AMOVA)显示了长江选育群体各世代之间4.05％的变异来自于群体间,95.95％的变异来自于群体内;而对于草鱼5个群体,AMOVA显示了 8.46％的变异来自于群体间,91.54％的变异来自于群体内.Structure分析显示出草鱼5个群体可以划分为3个聚类簇.通过基于Fst距离矩阵构建的5个草鱼群体的UPGMA系统发育树,结果显示长江选育群体F0、F3聚为一支后与长江选育群体F4聚类为一支,再与黑龙江选育群体聚为一支,最后与珠江选育群体聚为一支.该研究结果将为草鱼选育工作的进一步开展提供参考.

生长性状是水产动物遗传育种中的重要经济性状,利用与性状相关的分子标记与育种相结合的手段,可以大大加速育种进程.在对草鱼生长性状的前期研究中,采用数量性状位点(QTL)定位的方法,在1号连锁群中发现了2个与生长相关的QTL.在此基础上,实验利用这2个QTL侧翼的2对微卫星标记(CID391_2、CID1512、CID973_1和CID254_1),对长江草鱼选育群体的480个个体进行分析,以期基于草鱼QTL定位结果,对草鱼生长相关的微卫星标记在选育群体中进行验证.结果 显示:①4个微卫星标记在该群体中均具有高度多态性,其中各位点观测等位基因数(Na)为12 ～ 23个,有效等位基因数(Ne)为4～12个,观测杂合度(Ho)为0.607 ～0.904,期望杂合度(Hre)为0.751 ～ 0.902;②利用方差分析及多重比较对4个多态性的微卫星标记与选育草鱼群体的生长性状(体质量和体长)进行关联分析,发现CID391_2在雌性个体中,各基因型与体质量和体长之间均无显著差异;而在雄性个体中,各基因型与体质量和体长之间差异显著.CID1512、CID973_1和CID254_1在雌性或雄性个体中,各基因型与体质量和体长之间均具有显著差异.研究表明,对草鱼生长相关的微卫星标记在选育群体中的验证结果,为进一步开展草鱼生长性状QTL定位研究和基于QTL结果的分子标记辅助育种(MAS)实践奠定理论基础.

Growth-related traits are economically important in aquaculture, and their variation is linked to quantitative loci (QTLs). For exploring genetic basis of genetic breeding and improvement of grass carp (Ctenopharyngodon idellus), QTL mapping for growth-related traits was performed with an F2 family of grass carp from the Yangtze River system, including 360 offspring. In this study, we mapped QTLs for body weight, body length, body height, and body width using 99 previously published microsatellite loci. A total of 15 growth-related QTLs were found in 7 linkage groups (LG1, LG2, LG14, LG15, LG16, LG18, and LG21). Four QTLs were related to body weight (qBWH1, qBWH14, qBWH15, and qBWH16), and explained 3.1 to 7.7% of the phenotypic variance. Six QTLs were related to body length (qBL1, qBL2, qBL14, qBL15, qBL16, and qBL18), and these QTLs explained 2.8 to 8.9% of the phenotypic variance. Three QTLs affecting body height (qBH14, qBH15, and qBH16) explained 3.2 to 9.2% of the phenotypic variance. Two QTLs affecting body width (qBW15 and qBW21) accounted for 9.2% and 3.3% of the phenotypic variance, respectively. In order to fine map the QTL affecting body weight on LG1 (qBWH1), 14 additional novel microsatellites were included, and the qBWH1 was relocated with a narrower flanking marker interval of 7.5 cM. This is the first study of QTL mapping in grass carp and provides new insights for the application of molecular marker–assisted breeding in this species.