Genetic engineering applications in animal breeding

This paper discusses the use of genetic engineering applications in animal breeding, including a description of the methods, their potential and current uses and ethical issues. Genetic engineering is the name of a group of techniques used to identify, replicate, modify and transfer the genetic material of cells, tissues or complete organisms. Important applications of genetic engineering in animal breeding are: 1) Marker-assisted selection (MAS). The objective of this technology is to increase disease resistance, productivity and product quality in economically important animals by adding information of DNA markers to phenotypes and genealogies for selection decisions. 2) Transgenesis, the direct transfer of specific genes/alleles between individuals, species, or even Kingdoms, in order to change their phenotypic expression in the recipients. Compared to the 'traditional' improvement techniques based on phenotypic information only, these gene-by-gene techniques allow theoretically a more complete management of animal genomes for animal breeding. In spite of high expectations and new technical developments, its actual efficiency is not always high, as they require a thorough knowledge of functional genomics, and pose additional technical, economical and ethical problems. The possible role for cloning adult animals in breeding is also discussed

Use of molecular markers and major genes in the genetic improvement of livestock

Recent developments in molecular biology and statistics have opened the possibility of identifying and using genomic variation and major genes for the genetic improvement of livestock. Information concerning the basis of these techniques and their applications to the genetic improvement of animals is reviewed. Main marker molecular marker systems in animals (RFPL and microsatellites), genome maps, methods for detecting marker major gene linkages and use of marker assisted selection, genetic fingerprinting and mixture models based on segregation analysis are analyzed. The characteristics where the application of marker assisted selection can be more effective are those that are expressed late in the life of the animal, or controlled by a few pairs of genes. The first example correspond to the longevity and carcass characteristics in meat producing animals, the second, to the resistance to certain diseases or defects of simple inheritance. The detection of major genes using mixture models with segregation analysis can direct the work of identification of DNA marker genotypes towards populations and characteristics with greater probability of detecting a major gene using molecular markers. The present trend indicates that molecular, pedigree and phenotypic information will be integrated in the future through mixture models of segregation analysis that might contain major gene effects through the markers, polygenic inheritance and uses powerful and flexible methods of estimation such as Gibbs Sampling

Opportunities and challenges from the use of genomic selection for beef cattle breeding in Latin America

In 2009, Latin American countries had approximately 401 million cattle (29% of the world’s total cattle population) and produced 8.2 million tonnes of beef, equivalent to 29% of the world’s total production (FAO, 2011). Beef in Latin American countries is produced under widely differing climates (ranging from tropical to temperate), resources available (vegetation, food), types of markets, and genetic backgrounds of the animals. The main production systems are classified as beef and dual-purpose cattle. The genetic backgrounds of animals vary from purebred European (Bos taurus taurus) or Zebu (Bos taurus indicus) to crossbreeds (Figures 1 and 2). Beef production systems may also be characterized by their management intensification levels as grazing only, grazing with food supplementation, and feedlot production. The main beef-producing countries are Brazil (51.6% of the total Latin American beef production), Argentina (18.5%), Mexico (9.4%), and Colombia (5.1%). Other countries contributing more than 1% of the total regional production are Uruguay, Venezuela, Paraguay, Bolivia, Ecuador, and Chile (Table 1). Latin America is a region of the world that can significantly increase its production in response to beef demand. Brazil has a mature beef cattle industry based on grass-fed cattle, in which feeding B. taurus indicus cattle, especially the Nellore breed, is a common practice. Over the last 8 years, beef production in Brazil has become one of the most important activities for employment and wealth creation. Foot-and-mouth disease issues are still a factor limiting the increase in Latin American beef exports (Ferraz and de Felício, 2010; Domingues Millen et al., 2011). Only a few Latin American countries, including Chile and Mexico, have the status of being free of this disease without vaccination. In most countries, the disease is controlled using a combination of free areas without vaccination and areas with vaccination. Other countries with a strong B. taurus indicus background in their beef cattle populations are those with large tropical areas dedicated to beef cattle production, such as Colombia, Venezuela, and Paraguay. Beef production in Argentina, Chile, Uruguay, and some portions of Brazil and Mexico is based mainly around the production of B. taurus taurus cattle (Peel et al., 2010; Arelovich et al., 2011; Domingues Millen et al., 2011). The Mexican beef cattle industry consists of 2 nearly separate market components. Beef producers in the northern part of Mexico have largely focused on the production of calves for export to the United States (Galyean et al., 2011). European beef genetics have been widely used in the region, beginning with importations of Hereford cattle and continuing with today’s popularity of Angus and Brangus along with several continental breeds, such as Charolais and Simmental. The central and southern regions of Mexico have historically produced grass-fed beef for the national market as well as dual-purpose dairy-Zebu crossbred cattle to produce milk and beef (Peel et al., 2010). Currently, breeding programs for the genetic evaluation of beef cattle in Latin America are based on statistical analyses in which performance and pedigree information are integrated. These analyses are based on a mixed model methodology, in particular the animal model statistical approach using best linear unbiased prediction methods to obtain estimated breeding values (EBV) for economically important traits. This methodology for obtaining EBV has been set up in Argentina, Brazil, Colombia, Mexico, Uruguay, Venezuela, and other countries. It has been established for specific purebred populations and also for some crossbred populations, such as multibreed populations with a dual purpose (beef and milk) in the Latin American humid tropics, which involve animals crossbred between B. taurus taurus and B. taurus indicus and composite breeds. Most programs focus on evaluating growth and reproductive traits, although a few have included longevity (stayability), heifer pregnancy, conformation, and carcass and meat quality traits

Decline of genetic variability in a captive population of Pacific white shrimp Penaeus (Litopenaeus) vannamei using microsatellite and pedigree information

Background: The objective of this study was to estimate the decline of genetic variability and the changes in effective population size in three shrimp populations. One was a wild population collected at several points in the Mexican Pacific Ocean. The other two populations were different generations (7 and 9) from a captive population selected for growth and survival. Microsatellite markers and pedigree were both used to assess genetic variability and effective population size. Results: Using 26 loci, both captive populations showed a decline in the expected heterozygosity (20%) and allelic diversity indices (48 to 91%) compared to the wild population (P < 0.05). The studied captive populations did not differ significantly from each other regarding their expected heterozygosity or allelic diversity indices (P > 0.05). Effective population size estimates based on microsatellites declined from 48.2 to 64.0% in cultured populations (P < 0.05) compared to the wild population. Conclusions: An important decline of genetic variability in the cultured selected population due to domestication, and evidence of a further smaller decline in effective population size across generations in the selected population were observed when analyzing pedigree (41%) and microsatellite data (37%). Pedigree keeping is required to prevent the decline of effective population size and maintain genetic variability in shrimp breeding programs, while microsatellites are useful to assess effective population size changes at the population level

Morfología del sistema reproductor y del espermatóforo de Litopenaeus vannamei, camarón blanco del Pacífico

In order to advance in the knowledge of the male reproductive system of Litopanaeus vannamei, the anatomical description of its reproductive system in sexually mature animals was performed. Animals were obtained from a Mexican shrimp hatchery, located in Sinaloa, Mexico. To describe the anatomy, a) 8 male reproductive systems were removed; b) 10 spermatophores compounds were extracted from naturally inseminated females; and c) 40 sperm sacs derived from the right and the left ampulla were manually extracted. In general, the reproductive system was found similar to the observed in other species of the genus Penaeus. However, differences in the shape of the testes and of the terminal ampulla that are characteristic of this species were observed. An area located between the anterior vas deferens and the middle duct, known in other species as blind pouch, was observed. The compound spermatophore is a structure that has been described anatomically, although when freshly extracted it is difficult to observe because the type of substances that compose it and because of the morphological changes introduced when it contacts water. In each sperm sac of the spermatophore, sperm chamber is located from its medial to its distal part, with the highest concentration of sperm in the distal region.Con el objetivo de aportar información al conocimiento del sistema reproductor en machos de Litopenaeus vannamei, se elaboró la descripción anatómica de su sistema reproductor, empleando para ello machos sexualmente maduros, obtenidos de un laboratorio productor de larvas ubicado en Sinaloa, México. Para hacer la descripción, se obtuvieron por disección: a) los órganos reproductores completos de 8 machos; b) 10 espermatóforos compuestos que fueron extraídos de hembras inseminadas naturalmente; y c) 40 sacos espermáticos extraídos manualmente de las ámpulas derecha e izquierda. El sistema reproductor se asemeja al de otras especies del género Penaeus, sin embargo, posee diferencias en la forma de los testículos y del ámpula terminal, que lo hace característico de esta especie. También se localizó un área diferenciada entre el conducto deferente anterior y el conducto deferente medio que ha sido denominada en otras especies como saco ciego. El espermatóforo compuesto es una estructura que ha sido descrita anatómicamente, aunque su observación en fresco es difícil de realizar por el tipo de sustancias que lo forman y los cambios morfológicos que presenta al tener contacto con el agua. En cada uno de las sacos espermáticos del espermatóforo, la cámara espermática abarca desde la parte media hasta la parte distal del mismo, encontrándose la mayor concentración de espermatozoides en la región distal

Detección y uso de Genes Mayores en Animales

This paper reviews some methods for major gene detection in animal populations using phenotypic and genetic relationship (pedigree) information only. The key methods are regression (eg. Findgene) and Gibbs sampling. Both methods use segregation analysis and a mixed linear model fitting the major gene effects and probabilities, polygenic effects and the fixed environmental effects in the analysis of one quantitative trait. Segregation analysis by peeling gives probability for each genotype configuration for each individual, conditional on phenotypic information and genetic relationships in pedigreed data sets across the population. The limitations and advantages of this method compared to quantitative trait loci (QTL) detection with molecular markers are analysed. The use of this methods in the design of more efficient genome screening studies for QTL detection are discussed. El presente trabajo revisa algunos métodos de detección de genes mayores en poblaciones animales, usando solamente información fenotípica y de relaciones genéticas (pedigrí). Estos métodos incluyen regresión (vg. Findgene) y muestreo de Gibbs. Ambos usan análisis de segregación y un modelo lineal mixto que incluye los efectos de un gen mayor y sus probabilidades, la variación poligénica y los efectos ambientales fijos en el análisis de un carácter cuantitativo. El análisis de segregación por capas, da las probabilidades de la configuración genotípica para cada individuo, condicional en la información fenotípica y las relaciones genéticas en datos con genealogía a través de la población. Se analizan las limitaciones y ventajas de esta metodología comparada con la detección de loci con efecto en caracteres cuantitativos (QTL) usando marcadores moleculares. Se discute el uso de estos métodos en el diseño de estudios mas eficaces de revisión genómica para detectar QTL. </span

Factors affecting genetic correlation estimates from dairy sires&apos; genetic evaluations to assess genotype-environment interaction*

Effects of trait heritability (0.05 or 0.25), effective daughters number (30 to 500), sires number (10 to 500), and sire selection (selecting or not the top 50% sires), were evaluated based upon standard error (SE) and bias of genetic correlations (r G ) between countries estimated from Calo&apos;s method (r G ) using simulated data. Calo&apos;s method is based on correlations between sire&apos;s predicted transmitting abilities (PTA) in two countries adjusted for reliabilities. Unselected sire&apos;s data analysis gave nearly unbiased r G in all cases, but selected sire&apos;s data analysis gave underestimates. Bias was from -0.34 to -0.05 for the 0.25 heritability trait (milk yield), and from -0.42 to -0.17 for the 0.05 heritability trait (functional). Underestimation of r G decreased with increased effective number of daughters (PTA&apos;s reliability), but was quite insensitive to number of sires. The SE of genetic correlations estimates decreased with increased PTA&apos;s reliability and sires number, and was higher for selected sires. Approximately 50 sires with PTA&apos;s reliabilities≥0.97 on each country are required to obtain accurate (SE≤0.02) and unbiased (bias≤0.05|) r G with Calo&apos;s method using the best 50% selected sires. Many genetic correlation estimates between countries, already published using the Calo&apos;s method, may be underestimates, particularly for low heritability traits, and with low number of effective daughters in the importing country. Therefore, caution is required before interpreting the published r G &lt;1 as evidence for genotype-environment interaction

Use of molecular markers and major genes in the genetic improvement of livestock

Recent developments in molecular biology and statistics have opened the possibility of identifying and using genomic variation and major genes for the genetic improvement of livestock. Information concerning the basis of these techniques and their applications to the genetic improvement of animals is reviewed. Main marker molecular marker systems in animals (RFPL and microsatellites), genome maps, methods for detecting marker major gene linkages and use of marker assisted selection, genetic fingerprinting and mixture models based on segregation analysis are analyzed. The characteristics where the application of marker assisted selection can be more effective are those that are expressed late in the life of the animal, or controlled by a few pairs of genes. The first example correspond to the longevity and carcass characteristics in meat producing animals, the second, to the resistance to certain diseases or defects of simple inheritance. The detection of major genes using mixture models with segregation analysis can direct the work of identification of DNA marker genotypes towards populations and characteristics with greater probability of detecting a major gene using molecular markers. The present trend indicates that molecular, pedigree and phenotypic information will be integrated in the future through mixture models of segregation analysis that might contain major gene effects through the markers, polygenic inheritance and uses powerful and flexible methods of estimation such as Gibbs Sampling