0
Your cart

Your cart is empty

Browse All Departments
  • All Departments
Price
  • R1,000 - R2,500 (1)
  • -
Status
Brand

Showing 1 - 1 of 1 matches in All Departments

Estimating Parentage Relationships Using Molecular Markers in Aquaculture (Paperback): Paulino Martinez, Jesus Fernandez Estimating Parentage Relationships Using Molecular Markers in Aquaculture (Paperback)
Paulino Martinez, Jesus Fernandez
R1,216 R1,093 Discovery Miles 10 930 Save R123 (10%) Ships in 12 - 17 working days

The inference of parentage relationships between individuals from their molecular resemblance represents a useful methodology for genetic improvement in Aquaculture. This makes possible the reorganisation of broodstock in groups with low relatedness, as well as the identification of families in selection programs to avoid the harmful effects of inbreeding and to maintain the highest diversity as possible across generations. The choice of the appropriate genetic marker and the statistical methodology is essential to get the best solution for the questions considered. Depending on the availability of previous information on the genealogy, paternity or kinship analysis will be applied. The simplest approach to paternity inference, involves parent identification through the exclusion of the remaining candidates. However, this can lead to more than one solution, solvable after application of maximum likelihood procedures. The ability to identify the parents of each offspring depends on the sampling scenario (number of candidate parents and the fraction sampled), on the potential of the markers used (polymorphism, genotyping errors), and on the conformance to theoretical assumptions of the statistical models applied. A large number of paternity programs are freely available. They display usually complementary performances, and there is not the best software for all situations. When the authors dealt with a single group of individuals belonging to the same generation or that could not be separated into known generations, the aim was just to estimate the degree of genetic relationship between them, usually expressed as the coancestry coefficient. The basic idea is to determine how much of the molecular similarity (Identity By State) is due to the Identity By Descent (the really important parameter). There are two groups of relationship estimators from the molecular information. One of them includes methods directed at estimating coancestry for only a pair of individuals at a time, usually relaying on the knowledge of the allele frequencies of the reference population. Estimators within this group can be further divided into those called Method of Moments Estimators (MME) and those based on Maximum Likelihood (MLE). The other group of methods uses jointly the information of all individuals to determine the more probable population/familiar structure. They perform an explicit reconstruction of the genealogy leading to the observed population (at least for one generation above). Depending on the type of estimator and the assumptions used in their development, each of them presents some advantages and/or limitations which should be taken into account when choosing the one to use. In the present study, the most relevant estimators are presented and, also, a list of free software available for their application.

Free Delivery
Pinterest Twitter Facebook Google+
You may like...
Gym Towel & Bag
R78 Discovery Miles 780
Elektra Comfort 2720 Anti-Mozz Mosquito…
 (17)
R200 R189 Discovery Miles 1 890
Hermione Granger Wizard Wand - In…
 (1)
R834 Discovery Miles 8 340
Loot
Nadine Gordimer Paperback  (2)
R398 R330 Discovery Miles 3 300
Loot
Nadine Gordimer Paperback  (2)
R398 R330 Discovery Miles 3 300
Casio LW-200-7AV Watch with 10-Year…
R999 R884 Discovery Miles 8 840
Colleen Pencil Crayons - Assorted…
R127 Discovery Miles 1 270
Snappy Tritan Bottle (1.5L)(Green)
R229 R180 Discovery Miles 1 800
Aerolatte Cappuccino Art Stencils (Set…
R110 R95 Discovery Miles 950
American Crime Story - The People v O.J…
Cuba Gooding Jr, John Travolta, … DVD  (2)
R67 Discovery Miles 670

 

Partners