Construction of genetic map and QTL analysis of carotenoid-related trait based on EST markers in noble scallop Chlamys nobilis
Introduction
Carotenoids are well-known as highly bioactive pigments, ranging in color from yellow to red (Vílchez et al., 2011), which not only play important roles in animals and human health (Ribeiro et al., 2018; Rodriguez-Concepcion et al., 2018; Tan et al., 2020a), but also an important indicator for meat quality of aquatic species (Shahidi and Brown, 1998; Lehnert et al., 2019). As an important trait, carotenoids have been focused on animals and plants genetic and breeding in recent years (Zhang et al., 2018; Colasuonno et al., 2019; Tan et al., 2020b). Although some arthropods can make their own carotenoids by transferring genes from fungus (Boto, 2014), such as pea aphid Acyrthosiphon pisum (Moran and Jarvik, 2010), spider mite Tetranychus urticae (Altincicek et al., 2011), whitefly Bemisia tabaci (Sloan and Moran, 2012) and Cecidomyiidae (Cobbs et al., 2013), but it is traditionally believed that animals do not biosynthesize carotenoids de novo and can only obtain directly from food or partly modified through metabolic reactions (Maoka, 2011; Walsh et al., 2012; Schweiggert and Carle, 2015). However, studies have shown that some genes involve in carotenoids accumulation process in animals (Liu et al., 2015; Li et al., 2019; Lehnert et al., 2019). Therefore, exploration and identification of genes related to carotenoids accumulation is very important for genetic and breeding in animals.
Carotenoids content is a typical quantitative trait that varies with individuals (Liu et al., 2015; Gemenet et al., 2019). Genetic linkage map is an important tool for studying quantitative traits, which has been widely applied to study the mechanism of carotenoids accumulation in plants, such as maize Zea mays L (Yan et al., 2010), sweetpotato Ipomoea batatas (L.) Lam. (Gemenet et al., 2019), durum wheat Triticum turgidum L. var. durum (Colasuonno et al., 2019) and tomato Lycopersicon esculentum (Gao et al., 2019). In animals, although genetic map has been applied to study traits related to growth (Qin et al., 2007; Shi et al., 2014; Li et al., 2014; Wang et al., 2018), disease resistance (Sauvage et al., 2010), color (Bai et al., 2016; Nie et al., 2017), sex-identification (Feng et al., 2018), etc., carotenoid content has not been involved.
Noble scallop Chlamys nobilis is widely distributed in China, Thailand, Vietnam, Japan, etc. Because of its good taste, rich nutrition, rapid growth and easy breeding, it has been an important marine bivalve farmed in southern coasts of China since 1980s (Zheng et al., 2010; Tan et al., 2020b). The scallop is famous for its brilliant shell colors with high polymorphism (golden/orange, yellow, orange-purple, brown, etc.). Moreover, the scallop also displays different colors (golden and white) in muscle as a result of the different carotenoids content (Zheng et al., 2010; Zheng et al., 2013). Our previous studies have shown that these mutations were determined by complex network of genes (Zheng et al., 2013; Liu et al., 2015). To date, there are few molecular markers (Ma and Yu, 2009a, Ma and Yu, 2009b; Fan et al., 2017) and a genetic map (Yuan et al., 2010) were developed, but no information is available for carotenoids.
Expressed sequence tags (ESTs), due to their origin of exonic sequences, which are more likely to be conserved and transferable across related species and genera than markers from genomic library sources (Varshney et al., 2005). Thereby, making them well suited for population genomics, comparative mapping and QTL localization, especially for non-model organisms (Yu et al., 2016). Simple sequence repeat (SSR) is the most commonly used marker for linkage maps constructing because of its multiple alleles, co-dominant and transferability (Yu and Guo, 2003; Guichoux et al., 2011). In recent years, the single nucleotide polymorphism (SNP) has been used extensively in linkage mapping due to their abundance, high reproducibility and high-throughput (Semagn et al., 2006; Yue, 2013; Wu et al., 2018). Further, the high-resolution melting curve (HRM) is an efficient, economical and stable method for SNP genotyping, which has been widely used in genetic studies of many species, including Citrus (Distefano et al., 2013), Pacific oyster Crassostrea gigas (Wang et al., 2015a, Wang et al., 2015b; Wang et al., 2018) and pearl oyster Pinctada fucata (Zhan et al., 2016). Although the insertion and deletion (InDel) is not as well applied as other DNA markers, it is the second most abundant type of genetic variation in eukaryotic genome after SNP (Yu et al., 2016; Da Silva et al., 2016). InDel markers are well studied in plant genetics, such as wheat (Raman et al., 2006), rice Oryza sativa (Ramkumar et al., 2010; Liu et al., 2012; Wu et al., 2013), Arabidopsis thaliana (Păcurar et al., 2012) and Eucalyptus (Yu et al., 2016), and have been applied to construction of human linkage map (Mills et al., 2006). Currently, InDels have also been found abundantly on the genomes of some aquatic organisms by transcriptomic analysis, such as Yesso scallop Patinopecten yessoensis (Hou et al., 2011), Blunt snout bream Megalobrama amblycephala (Gao et al., 2012) and noble scallop (Liu et al., 2015), but further studies are lacking.
Here, we developed and validated novel EST-based SSR, SNP and InDel markers and constructed the sex-specific and integrated genetic map of the noble scallop Chlamys nobilis using a F2 population. QTL (Quantitative trait loci) localization was then performed for carotenoids content in the adductor (AC) and mantle (MC). The construction of genetic map and identification of QTLs associated with total carotenoids content (TCC) can provide new insights for further understanding the genetic mechanism of carotenoids deposition and provide the basis of marker-assisted selection (MAS) breeding for the noble scallop in the future.
Section snippets
Mapping population construction
According to our previous studies (Zheng et al., 2013; Liu et al., 2015), golden shell colors in noble scallop (the golden trait determinant gene is abbreviated “G”) is dominant to brown shell colors (the brown trait determinant gene is abbreviated “B”), and golden muscle colors (“g” represented the gene that determined the golden trait) is dominant to white muscle colors (“w” represented the gene that determined the white trait). We found that the two golden traits almost consistently occur
Shell color ratio and TCC
Only two kinds of shell colors were found in F2 (Fig. 2) in a ratio of 1:1. The TCC was continuously distributed in both adductor and mantle of the offspring (Fig. 3). However, the TCC showed shell-color and tissue specificity, which was significantly higher in golden scallops than in brown scallops and in mantle than in adductor (P < 0.05) (Fig. 4). In addition, the Pearson correlation coefficient between adductor and mantle of TCC was 0.704 (r = 0.704, P < 0.05).
Marker analysis
A total of 401 SNPs was
Linkage map construction
The noble scallop Chlamys nobilis is one of the major farmed bivalves in China. Therefore, constructing genetic mapping and screening molecular markers for importantly economic traits are essential for MAS of this species. Although some DNA markers (Ma and Yu, 2009a, Ma and Yu, 2009b; Fan et al., 2017) and a linkage map (Yuan et al., 2010) have been developed, they only involved in population genomic construction and growth trait. In the present study, two importantly economic traits of color
Conclusion
In conclusion, the sex-specific and integration maps in the noble scallop Chlamys nobilis were constructed with EST-based SNP, InDel and SSR markers. Based on the integration map, five QTLs for carotenoid content in adductor and mantle muscle were detected. Furthermore, the QTL of qAC_3 (PVE = 28.0%) and qMC_2 (PVE = 55.6%) was the same locus, containing key genes associated carotenoid content. These results are the first reported in animals. They may also provide a good starting point for
Declaration of Competing Interest
All authors of this work declare that they have no potential conflict of interest and that there is no financial, consultant, institutional or other relationships that might lead to bias or conflicts of interest in this research. Financial grants supporting this work are described in the acknowledgements section.
Acknowledgments
Present study was financially supported by the National Natural Science Foundation of China (31872563) and China Modern Agro-industry Technology Research System (CARS-49).
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