This paper reviews genetics of fibre production and fleece characteristics in small ruminants, Angora rabbit and South American camelids with a special distinction between single-coated (SC) and double-coated (DC) species. Considering the biology of fibre production, there are variations in coat composition and structure, fibre growth pattern and fibre structure and quality between these two main kinds of fibre-producing animals. In SC species, all fibres are nearly similar in dimensions and are produced from individual follicles that have a very long period, essentially permanent, of active growth without a synchronous phase of rest between follicles. In contrast, in DC species the fleece comprises a coarse outer coat and a fine inner coat with variations of coat composition and structure, and fibre growth pattern according to the season with a well-defined duration of fibre growth. Genetic basis of hair growth pattern, coat composition and fibre structure are different between species. In small ruminants, these coat characters are additive and because of several genes whereas in rabbit, several autosomal recessive genes determine fibre growth, coat composition and structure. In alpaca, the fleece type (Suri or Huacaya) is determined by a single dominant gene. This paper also reviews genetic parameters of fibre production traits in Angora goat, Angora rabbit and alpaca in which many aspects of the genetic basis of fibre production are analogous. There are many traits controlling both fibre quality and fibre quantity, and most of these traits tend to be moderately to strongly inherited so that a rapid genetic progress in any traits is possible and indeed has been achieved. However, there are differences in breeding programmes. In DC Angora rabbit, selection for one single trait, the easy measurable total fleece weight has general beneficial effects on fleece quality. However, because of antagonistic relations between qualitative and quantitative traits in SC species, achieving this goal requires a multi-trait selection index approach. Gene mapping studies have recently identified several putative quantitative trait loci and major genes affecting fibre and fleece characteristics in sheep, goat and rabbit are reviewed. The whole genome sequence of sheep and rabbit will be available in the near future and the use of high-density single nucleotide polymorphism chip will allow fine mapping and dissection of the genetic basis of many production traits including fibre production and fleece characteristics. The application of these techniques will thus contribute to improving the efficiency, profitability and sustainability of small ruminant and rabbit fibre production.

The EU project Welfare Quality® proposes an overall assessment system for animal welfare based on animal outcomes. The objective of this study was to test inter-observer reliability (IOR) when assessing lameness, fear and slipping and falling scores as parameters for monitoring the welfare of killing pigs during arrival at the slaughterhouse. Two Belgian and two Spanish slaughterhouses were visited by six to seven observers. Lameness, slipping and falling were assessed twice; during unloading and in the passageway to the lairage zone (lairage). Fear, which was assessed in the unloading area, was based on four indicators: reluctance to move, retreat attempts, turning back and vocalisations. Lameness had low-to-moderate IOR when observed in the passageway to lairage (r = 0.46), but the IOR was low during unloading (r = 0.25). IOR for slipping and falling was moderate to high (r = 0.71 and r = 0.50, respectively), when assessed in the unloading area, but low for observations in the passageway (r = 0.13). Fear indicators had only moderate or low IOR. Turning back was the measure with the highest IOR (r = 0.43) and retreat attempts had the lowest IOR (r = 0.25). Based on these results, we concluded that scoring lameness could be reliable when assessed from the unloading bay to lairage, whereas slipping and falling should be scored in the unloading area of the slaughterhouse. We suggest scoring a maximum of two measures of fear on the same animals at the unloading area, with the most reliable parameters being turning back and reluctance to move. The three indicators of animal welfare (lameness, fear and slipping and falling) should be measured in a way to reduce overtax of the observers in order to achieve accurate results.

The patterns of linkage disequilibrium (LD) between dense polymorphic markers are shaped by the ancestral population history. It is therefore possible to use multilocus predictors of LD to infer past population history and to infer sharing of identical alleles in quantitative trait locus (QTL) studies. We develop a multilocus predictor of LD for pairs of haplotypes, which we term haplotype homozygosity (HHn): the probability that any two haplotypes share a given number of n adjacent identical markers or ‘runs of homozygosity’. Our method, based on simplified coalescence theory, accounts for recombination and mutation. We compare our HHn predictions, with HHn in simulated populations and with two published predictors of HHn. Our method performs consistently better across a range of population parameters, including populations with a severe bottleneck followed by expansion, compared to two published methods. We demonstrate that we can predict the pattern of HHn observed in dense single nucleotide polymorphisms (SNPs) genotyped in a cattle population, given appropriate historical changes in population size. Our method is practical for use with very large numbers of individuals and dense genome wide polymorphic DNA data. It has potential applications in inferring ancestral population history and QTL mapping studies.

Effective population size (Ne) is an important parameter in the conservation of genetic diversity. Comparative studies of empirical data that gauge the relative accuracy of Ne methods are limited, and a better understanding of the limitations and potential of Ne estimators is needed. This paper investigates genetic diversity and Ne in four populations of wild anadromous Atlantic salmon (Salmo salar L.) in Europe, from the Rivers Oir and Scorff (France) and Spey and Shin (Scotland). We aimed to understand present diversity and historical processes influencing current population structure. Our results showed high genetic diversity for all populations studied, despite their wide range of current effective sizes. To improve understanding of high genetic diversity observed in the populations with low effective size, we developed a model predicting present diversity as a function of past demographic history. This suggested that high genetic diversity could be explained by a bottleneck occurring within recent centuries rather than by gene flow. Previous studies have demonstrated the efficiency of coalescence models to estimate Ne. Using nine subsets from 37 microsatellite DNA markers from the four salmon populations, we compared three coalescence estimators based on single and dual samples. Comparing Ne estimates confirmed the efficiency of increasing the number and variability of microsatellite markers. This efficiency was more accentuated for the smaller populations. Analysis with low numbers of neutral markers revealed uneven distributions of allelic frequencies and overestimated short-term Ne. In addition, we found evidence of artificial stock enhancement using native and non-native origin. We propose estimates of Ne for the four populations, and their applications for salmon conservation and management are discussed.

We used a least absolute shrinkage and selection operator (LASSO) approach to estimate marker effects for genomic selection. The least angle regression (LARS) algorithm and cross-validation were used to define the best subset of markers to include in the model. The LASSO–LARS approach was tested on two data sets: a simulated data set with 5865 individuals and 6000 Single Nucleotide Polymorphisms (SNPs); and a mouse data set with 1885 individuals genotyped for 10 656 SNPs and phenotyped for a number of quantitative traits. In the simulated data, three approaches were used to split the reference population into training and validation subsets for cross-validation: random splitting across the whole population; random sampling of validation set from the last generation only, either within or across families. The highest accuracy was obtained by random splitting across the whole population. The accuracy of genomic estimated breeding values (GEBVs) in the candidate population obtained by LASSO–LARS was 0·89 with 156 explanatory SNPs. This value was higher than those obtained by Best Linear Unbiased Prediction (BLUP) and a Bayesian method (BayesA), which were 0·75 and 0·84, respectively. In the mouse data, 1600 individuals were randomly allocated to the reference population. The GEBVs for the remaining 285 individuals estimated by LASSO–LARS were more accurate than those obtained by BLUP and BayesA for weight at six weeks and slightly lower for growth rate and body length. It was concluded that LASSO–LARS approach is a good alternative method to estimate marker effects for genomic selection, particularly when the cost of genotyping can be reduced by using a limited subset of markers.

The X-linked telomeric P elements TP5 and TP6 interact synergistically with non-telomeric P elements to repress hybrid dysgenesis. In this repression, the telomeric P elements exert maternal effects, which, however, are not sufficient to establish synergism with the non-telomeric P elements. Once synergism is established, the capacity to repress dysgenesis in the offspring of a cross persists for at least two generations after removing the telomeric P element from the genotype. At the molecular level, synergism between telomeric and non-telomeric P elements is correlated with effective elimination of P-element mRNA in the germ line. Maternally transmitted mutations in the genes aubergine, piwi and Suppressor of variegation 205 [Su(var)205] block the establishment of synergism between telomeric and non-telomeric P elements, and paternally transmitted mutations in piwi and Su(var)205 disrupt synergism that has already been established. These findings are discussed in terms of a model of cytotype regulation of P elements based on Piwi-interacting RNAs (piRNAs) that are amplified by cycling between sense and antisense species.