دانلود رایگان مقاله لاتین برآورد پارامتر ژنتیکی در سپر ماهی از سایت الزویر
عنوان فارسی مقاله:
برآورد پارامترهای ژنتیکی صفات رشد با ارتباط مولکولی در سپر ماهی (Scophthalmus maximus, Linnaeus)
عنوان انگلیسی مقاله:
Estimating genetic parameters for growth traits with molecular relatedness in turbot (Scophthalmus maximus, Linnaeus)
سال انتشار : 2017
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مقدمه انگلیسی مقاله:
1. Introduction
Turbot (Scophthalmus maximus, Linnaeus, 1758) is a marine fish distributed in the Atlantic coast of Europe, containing Baltic, Black, and Mediterranean seas (Blanquer et al., 1992; Lei and Liu, 1995). With fast growth, strong tolerance to cold water, and delicious flavor turbot is the most widely cultured commercial flatfish in the world. From its introduction into China in 1992, turbot aquaculture has developed into an important mariculture industry (especially in northern China) with an annual production of N60,000 t in 2010 (Lei et al., 2012). However, as an introduced fish species, turbot farming is restricted by less genetic diversity and lack of provenance (Shen et al., 2004). Moreover, systematic artificial breeding has not received sufficient attention in the early years (Guan et al., 2012). For these reasons, turbot germplasm resources have degenerated, resulting in a decline in the main economic traits resulting in longer growth period, lower seedling production, and disease susceptibility (Shen et al., 2004; Guan et al., 2012). To continue developing the turbot industry, improving its economic traits through selective breeding and genetic improvement is particularly important. Growth traits are important economic traits, because the commercial value of a turbot depends primarily on its body weight. The animal model BLUP (Best Linear Unbiased Prediction) method, involving mixed model equations (Henderson, 1975), has been widely used in the estimation of genetic parameters in aquatic species (Blonk et al., 2010; Gall and Bakar, 2002; Shikano, 2007). To apply BLUP one must first know the relationship coefficients between individuals. Traditionally, geneticists and breeders have inferred this as pedigree relatedness from certain pedigrees in studies of either laboratory or domesticated populations (Falconer and Mackay, 1996; Lynch and Walsh, 1998; Wright, 1922). If pedigree information is lacking but all of the parents are known, genetic marker data can be used for parental allocation to obtain pedigree information (Duchesne and Bernatchez, 2002; Marshall et al., 1998). Over the last decade, many new methods that use molecular markers to directly calculate paired molecular relatedness have been developed (Wang, 2007). The biggest advantage of these methods is that pedigree and parent information are not necessary (Wang, 2007). The molecular maker-based relatedness estimators can be divided into two types: method-of-moment estimators (MOM) (Queller and Goodnight, 1989; Wang, 2002; Li et al., 1993; Lynch and Ritland,1999; Ritland, 1996) and maximum-likelihood estimators (ML) (Milligan, 2003; Wang, 2007). Most MOM methods obtain relatedness by calculating shared codominant marker alleles between pairs, while ML methods mainly calculate the probability of a pair falling into each of a number of different relationship categories and then either obtaining the weighted average or adopting the most likely category (Mousseau et al., 1998; Thomas and Hill, 2000). Numerous studies have assessed the performance of different molecular relatedness estimators. One of the conclusions drawn was that their performance rank order depends on many factors, such as population structure and size, number of markers, and alleles, no single factor was universally superior to the others (Milligan, 2003; Casteele et al., 2001; Wang, 2007). Compared with moment estimators, ML methods have the advantage of automatically weighing information among alleles and among loci and showing smaller mean squared errors (Wang, 2007), but they may also overestimate relatedness, especially for low related dyads (Milligan, 2003). Besides, ML methods yield more biased estimates than MOM, because the values obtained by likelihood estimators are restricted within the theoretical bounds [0–1], but if the number of markers used in the analysis is large enough they tend to close (Milligan, 2003).
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کلمات کلیدی:
Estimation of genetic parameters for early ... - Wiley Online Library onlinelibrary.wiley.com/doi/10.1111/are.12673/abstract Jan 22, 2015 - Two sorts of relatedness, including pedigree relatedness (PR) from a complete pedigree and average molecular relatedness (AMR) from molecular markers, ... Heritability estimates from AMR and PR methods based on their ... Estimation of genetic parameters for early ... - Wiley Online Library onlinelibrary.wiley.com/doi/10.1111/are.12673/pdf by J Guan - 2015 - Cited by 3 - Related articles Estimation of genetic parameters for early growth trait of turbot (Scophthalmus maximus L.) using molecular relatedness. Jiantao Guan1,2, Weiji Wang2, Sheng ... An estimation of genetic parameters of growth traits ... - Search ProQuest search.proquest.com/openview/b3d830adeed98a6685244cf986ed877e/1.pdf?pq... by Y Hu - 2016 - Related articles An estimation of genetic parameters of growth traits in juvenile turbot (Scophthalmus maximus L.) using parental molecular relatedness. HU Yulong1, GUAN ... Estimation of Quantitative Genetic Parameters Using Marker-Inferred ... jhered.oxfordjournals.org/content/99/2/94.full by T Shikano - 2008 - Cited by 20 - Related articles Jan 21, 2008 - Marker-based methods for estimating heritability have been ... made to use molecular markers for estimating relatedness among individuals of .... Quantitative traits examined in laboratory populations were growth-related traits ... Aquaculture Research Trends - Page 111 - Google Books Result https://books.google.com/books?isbn=160456217X Stephen H. Schwartz - 2008 - Aquaculture Thomas S.C. (2005) The estimation of genetic relationships using molecular ... A comparison of microsatellite- based pairwise relatedness estimators. ... Linhart O. and Chevassus B. (2005) Heritability estimates for growth-related traits using ...
