Most genetic studies on modern cattle have established a common origin for all taurine breeds in the Near East, during the Neolithic transition about 10 thousand years (ka) ago. Yet, the possibility of independent and/or secondary domestication events is still debated and is fostered by the finding of rare mitochondrial DNA (mtDNA) haplogroups like P, Q and R. Haplogroup T1, because of its geographic distribution, has been the subject of several investigations pointing to a possible independent domestication event in Africa and suggesting a genetic contribution of African cattle to the formation of Iberian and Creole cattle. Whole mitochondrial genome sequence analysis, with its proven effectiveness in improving the resolution of phylogeographic studies, is the most appropriate tool to investigate the origin and structure of haplogroup T1. A survey of >2200 bovine mtDNA control regions representing 28 breeds (15 European, 10 African, 3 American) identified 281 subjects belonging to haplogroup T1. Fifty-four were selected for whole mtDNA genome sequencing, and combined with ten T1 complete sequences from previous studies into the most detailed T1 phylogenetic tree available to date. Phylogenetic analysis of the 64 T1 mitochondrial complete genomes revealed six distinct sub-haplogroups (T1a–T1f). Our data support the overall scenario of a Near Eastern origin of the T1 sub-haplogroups from as much as eight founding T1 haplotypes. However, the possibility that one sub-haplogroup (T1d) arose in North Africa, in domesticated stocks, shortly after their arrival from the Near East, can not be ruled out. Finally, the previously identified “African-derived American" (AA) haplotype turned out to be a sub-clade of T1c (T1c1a1). This haplotype was found here for the first time in Africa (Egypt), indicating that it probably originated in North Africa, reached the Iberian Peninsula and sailed to America, with the first European settlers.
The current extensive use of the domestic goat (Capra hircus) is the result of its medium size and high adaptability as multiple breeds. The extent to which its genetic variability was influenced by early domestication practices is largely unknown. A common standard by which to analyze maternally-inherited variability of livestock species is through complete sequencing of the entire mitogenome (mitochondrial DNA, mtDNA). We present the first extensive survey of goat mitogenomic variability based on 84 complete sequences selected from an initial collection of 758 samples that represent 60 different breeds of C. hircus, as well as its wild sister species, bezoar (Capra aegagrus) from Iran. Our phylogenetic analyses dated the most recent common ancestor of C. hircus to ~460,000 years (ka) ago and identified five distinctive domestic haplogroups (A, B1, C1a, D1 and G). More than 90 % of goats examined were in haplogroup A. These domestic lineages are predominantly nested within C. aegagrus branches, diverged concomitantly at the interface between the Epipaleolithic and early Neolithic periods, and underwent a dramatic expansion starting from ~12–10 ka ago. Domestic goat mitogenomes descended from a small number of founding haplotypes that underwent domestication after surviving the last glacial maximum in the Near Eastern refuges. All modern haplotypes A probably descended from a single (or at most a few closely related) female C. aegagrus. Zooarchaelogical data indicate that domestication first occurred in Southeastern Anatolia. Goats accompanying the first Neolithic migration waves into the Mediterranean were already characterized by two ancestral A and C variants. The ancient separation of the C branch (~130 ka ago) suggests a genetically distinct population that could have been involved in a second event of domestication. The novel diagnostic mutational motifs defined here, which distinguish wild and domestic haplogroups, could be used to understand phylogenetic relationships among modern breeds and ancient remains and to evaluate whether selection differentially affected mitochondrial genome variants during the development of economically important breeds.
28 June 2008 in Journal of Animal Breeding and Genetics
Summary: Robustness has become a highly desirable breeding goal in the globalized agricultural market. Both genotype‐by‐environment interaction (G × E) and micro‐environmental sensitivity are important robustness components of aquaculture production, in which breeding stock is often disseminated to different environments. The objectives of this study were (i) to quantify the degree of G × E by assessing the growth performance of Genetically Improved Farmed Tilapia (GIFT) across three countries (Malaysia, India and China) and (ii) to quantify the genetic heterogeneity of environmental variance for body weight at harvest (BW) in GIFT as a measure of micro‐environmental sensitivity. Selection for BW was carried out for 13 generations in Malaysia. Subsets of 60 full‐sib families from Malaysia were sent to China and India after five and nine generations respectively. First, a multi‐trait animal model was used to analyse the BW in different countries as different traits. The results indicate a strong G × E. Second, a genetically structured environmental variance model, implemented using Bayesian inference, was used to analyse micro‐environmental sensitivity of BW in each country. The analysis revealed the presence of genetic heterogeneity of both BW and its environmental variance in all environments. The presence of genetic variation in residual variance of BW implies that the residual variance can be modified by selection. Incorporating both G × E and micro‐environmental sensitivity information may help in selecting robust genotypes with high performance across environments and resilience to environmental fluctuations.
Aggression behaviour has several negative consequences on the performance and welfare of pigs. Here, the Social Network Analysis (SNA) approach was employed to (1) identify individual traits that describe the role of each animal in the aggression; (2) investigate the association of these traits with performance and feeding behaviour traits. The study was conducted on 326 Duroc pigs reared in 29 pens. Several individual centrality traits were identified and used to calculate the Social Rank Index. The Dominant, Subordinate, and Isolated animals represented 21.1%, 57.5% and 21.4%, respectively. No significant correlations were observed between out-degree (number of initiated agonistic behaviours) and growth traits, indicating the similarity of growth patterns for dominant and non-dominant animals. Furthermore, out-degree was correlated positively with average daily occupation time (time at the feeder/day) and average daily feeding frequency (number of visits to the feeder/day) but negatively with average daily feeding rate (gr/min). This may indicate the ability of non-dominant pigs to modify their behaviour to obtain their requirements. The Hamming distances between networks showed that there is no common behaviour pattern between pens. In conclusion, SNA showed the potential for extracting behaviour traits that could be used to improve pig performance and welfare.
The aim of this study was to evaluate the effect of six generations of selection for intramuscular fat (IMF) in muscle Longissimus thoracis et lumborum (LTL) at 9 wk. in IMF and fatty acid (FA) composition of muscles with diverse metabolic profile in rabbits. Direct response to selection was 0.33 g of IMF/ 100 g of LTL, around 0.4 SD per generation. A positive correlated response was observed in IMF of Biceps femoris, Supraspinatus and Semimembranosus proprius muscles at 9 wk., representing around 0.2 SD of the trait per generation. Selection affected similarly the FA composition of all muscles at 9 wk., high-IMF line showing greater monounsaturated but lower polyunsaturated FA percentages than low-IMF line, whereas no differences were observed for saturated FA. Traits were also measured at 13 wk. and correlated responses were in the same direction. Our results suggest a common genetic background for IMF and FA composition in muscles with different metabolic profile in rabbits.