Combining two Meishan F2 crosses improves the detection of QTL on pig chromosomes 2, 4 and 6

<p>Abstract</p> <p>Background</p> <p>In pig, a number of experiments have been set up to identify QTL and a multitude of chromosomal regions harbouring genes influencing traits of interest have been identified. However, the mapping resolution remains limited in most cases and the detected QTL are rather inaccurately located. Mapping accuracy can be improved by increasing the number of phenotyped and genotyped individuals and/or the number of informative markers. An alternative approach to overcome the limited power of individual studies is to combine data from two or more independent designs.</p> <p>Methods</p> <p>In the present study we report a combined analysis of two independent design (a French and a Dutch F2 experimental designs), with 2000 F2 individuals. The purpose was to further map QTL for growth and fatness on pig chromosomes 2, 4 and 6. Using QTL-map software, uni- and multiple-QTL detection analyses were applied separately on the two pedigrees and then on the combination of the two pedigrees.</p> <p>Results</p> <p>Joint analyses of the combined pedigree provided (1) greater significance of shared QTL, (2) exclusion of false suggestive QTL and (3) greater mapping precision for shared QTL.</p> <p>Conclusions</p> <p>Combining two Meishan x European breeds F2 pedigrees improved the mapping of QTL compared to analysing pedigrees separately. Our work was facilitated by the access to raw phenotypic data and DNA of animals from both pedigrees and the combination of the two designs with the addition of new markers allowed us to fine map QTL without phenotyping additional animals.</p

Progeny-testing of full-sibs IBD in a SSC2 QTL region highlights epistatic interactions for fatness traits in pigs

<p>Abstract</p> <p>Background</p> <p>Many QTL have been detected in pigs, but very few of them have been fine-mapped up to the causal mutation. On SSC2, the <it>IGF2</it>-intron3-G3072A mutation has been described as the causative polymorphism for a QTL underlying muscle mass and backfat deposition, but further studies have demonstrated that at least one additional QTL should segregate downstream of this mutation. A marker-assisted backcrossing design was set up in order to confirm the segregation of this second locus, reduce its confidence interval and better understand its mode of segregation.</p> <p>Results</p> <p>Five recombinant full-sibs, with genotype G/G at the <it>IGF2 </it>mutation, were progeny-tested. Only two of them displayed significant QTL for fatness traits although four inherited the same paternal and maternal chromosomes, thus exhibiting the same haplotypic contrast in the QTL region. The hypothesis of an interaction with another region in the genome was proposed to explain these discrepancies and after a genome scan, four different regions were retained as potential interacting regions with the SSC2 QTL. A candidate interacting region on SSC13 was confirmed by the analysis of an F2 pedigree, and in the backcross pedigree one haplotype in this region was found to mask the SSC2 QTL effect.</p> <p>Conclusions</p> <p>Assuming the hypothesis of interactions with other chromosomal regions, the QTL could be unambiguously mapped to a 30 cM region delimited by recombination points. The marker-assisted backcrossing design was successfully used to confirm the segregation of a QTL on SSC2 and, because full-sibs that inherited the same alleles from their two parents were analysed, the detection of epistatic interactions could be performed between alleles and not between breeds as usually done with the traditional Line-Cross model. Additional analyses of other recombinant sires should provide more information to further improve the fine-mapping of this locus, and confirm or deny the interaction identified between chromosomes 2 and 13.</p

Development of a SNP parentage assignment panel in some North-Eastern Spanish meat sheep breeds

Aim of study: To validate two existing single nucleotide polymorphism (SNP) panels for parentage assignment in sheep, and develop a cost effective genotyping system to use in some North-Eastern Spanish meat sheep populations for accurate pedigree assignment.Area of study: SpainMaterial and methods: Nine sheep breeds were sampled: Rasa Aragonesa (n=38), Navarra (n=39), Ansotana (n=41), Xisqueta (n=41), Churra Tensina (n=38), Maellana (39), Roya Bilbilitana (n=24), Ojinegra (n=36) and Cartera (n=39), and these animals were genotyped with the Illumina OvineSNP50 BeadChip array. Genotypes were extracted from the sets of 249 SNPs and 163 SNPs for parentage assignment designed in France and North America, respectively. Validation of a selected cost-effective genotyping panel of 158 SNPs from the French panel were performed by Kompetitive allele specific PCR (KASP). Additionally, some functional SNPs (n=15) were also genotyped.Main results: The set of 249 SNPs for parentage assignment showed better diversity, probability of identity, and exclusion probabilities than the set of 163 SNPs. The average minor allele frequency for the set of 249, 163 and 158 SNPs were 0.41 + 0.01, 0.39 + 0.01 and 0.42 + 0.01, respectively. The parentage assignment rate was highly dependent to the percentage of putative sires genotyped.Research highlights: The described method is a cost-effective genotyping system combining the genotyping of SNPs for the parentage assignment with some functional SNPs, which was successfully used in some Spanish meat sheep breeds

A high density recombination map of the pig reveals a correlation between sex-specific recombination and GC content

<p>Abstract</p> <p>Background</p> <p>The availability of a high-density SNP genotyping chip and a reference genome sequence of the pig (<it>Sus scrofa</it>) enabled the construction of a high-density linkage map. A high-density linkage map is an essential tool for further fine-mapping of quantitative trait loci (QTL) for a variety of traits in the pig and for a better understanding of mechanisms underlying genome evolution.</p> <p>Results</p> <p>Four different pig pedigrees were genotyped using the Illumina PorcineSNP60 BeadChip. Recombination maps for the autosomes were computed for each individual pedigree using a common set of markers. The resulting genetic maps comprised 38,599 SNPs, including 928 SNPs not positioned on a chromosome in the current assembly of the pig genome (build 10.2). The total genetic length varied according to the pedigree, from 1797 to 2149 cM. Female maps were longer than male maps, with a notable exception for SSC1 where male maps are characterized by a higher recombination rate than females in the region between 91–250 Mb. The recombination rates varied among chromosomes and along individual chromosomes, regions with high recombination rates tending to cluster close to the chromosome ends, irrespective of the position of the centromere. Correlations between main sequence features and recombination rates were investigated and significant correlations were obtained for all the studied motifs. Regions characterized by high recombination rates were enriched for specific GC-rich sequence motifs as compared to low recombinant regions. These correlations were higher in females than in males, and females were found to be more recombinant than males at regions where the GC content was greater than 0.4.</p> <p>Conclusions</p> <p>The analysis of the recombination rate along the pig genome highlighted that the regions exhibiting higher levels of recombination tend to cluster around the ends of the chromosomes irrespective of the location of the centromere. Major sex-differences in recombination were observed: females had a higher recombination rate within GC-rich regions and exhibited a stronger correlation between recombination rates and specific sequence features.</p

Number and mode of inheritance of QTL influencing backfat thickness on SSC2p in Sino-European pig pedigrees

<p>Abstract</p> <p>Background</p> <p>In the pig, multiple QTL associated with growth and fatness traits have been mapped to chromosome 2 (SSC2) and among these, at least one shows paternal expression due to the IGF2-intron3-G3072A substitution. Previously published results on the position and imprinting status of this QTL disagree between analyses from French and Dutch F2 crossbred pig populations obtained with the same breeds (Meishan crossed with Large White or Landrace).</p> <p>Methods</p> <p>To study the role of paternal and maternal alleles at the IGF2 locus and to test the hypothesis of a second QTL affecting backfat thickness on the short arm of SSC2 (SSC2p), a QTL mapping analysis was carried out on a combined pedigree including both the French and Dutch F2 populations, on the progeny of F1 males that were heterozygous (A/G) and homozygous (G/G) at the IGF2 locus. Simulations were performed to clarify the relations between the two QTL and to understand to what extent they can explain the discrepancies previously reported.</p> <p>Results</p> <p>The QTL analyses showed the segregation of at least two QTL on chromosome 2 in both pedigrees, i.e. the IGF2 locus and a second QTL segregating at least in the G/G F1 males and located between positions 30 and 51 cM. Statistical analyses highlighted that the maternally inherited allele at the IGF2 locus had a significant effect but simulation studies showed that this is probably a spurious effect due to the segregation of the second QTL.</p> <p>Conclusions</p> <p>Our results show that two QTL on SSC2p affect backfat thickness. Differences in the pedigree structures and in the number of heterozygous females at the IGF2 locus result in different imprinting statuses in the two pedigrees studied. The spurious effect observed when a maternally allele is present at the IGF2 locus, is in fact due to the presence of a second closely located QTL. This work confirms that pig chromosome 2 is a major region associated with fattening traits.</p

AdaptMap: exploring goat diversity and adaptation

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Combining different pedigrees to fine-map QTL in the Pig

Pig domestication started around 10,000 years ago during the Neolithic age, independently in Europe and China, and most current pig breeds originate from these two areas. Among the 560 pig breeds that have been recorded over the world in 2007 by the FAO, only few of them have been intensively selected for production. Domestication and, more recently, pig breeders have relied on naturally occurring mutations to select individuals exhibiting favourable traits related to reproduction, growth, fatness, resistance to diseases and behaviour. In order to identify these mutations underlying the phenotypic variations of these traits, a number of QTL detection programs was set up, and thousands of QTLs have been detected in the 2000s. However, for only a few of them, fine-mapping has resulted in the identification of the causal polymorphism. In chapter 1, the general introduction provides an overview of QTL detection in pig in relation to the molecular tools that are available for pig geneticists and to the different mapping strategies that can be used. Major limitations to QTL fine-mapping in pig (but also valid for other livestock species) concern the number of individuals, the number of informative genetic markers and the ability to detect non-additive QTLs. To increase the statistical power by increasing the number of individuals, a combined linkage analysis is presented in chapter 2. To carry out this work, two pig F2 pedigrees comprising about a thousand individuals each and based on similar breeds (Large White and/or Landrace crossed with Meishan individuals) were combined. Both pedigrees had been developed in the late 1990s at INRA and WUR. Common QTLs segregating on SSC2, SSC4 and SSC6 were confirmed in the combined analysis, but QTLs that were specific to one pedigree disappeared or were detected at a lower significance threshold. Despite the limited benefits in term of the number of QTLs, the increase in the number of individuals, enabled us to separate two linked QTLs that were previously detected as a single one. False-positive QTLs were also detected as well as new QTLs characterised by a low frequency and/or a small effect. In addition, both pedigrees could be compared regarding the imprinting status at the IGF2-intron3-G3072A substitution, segregating on SSC2. The mutation was segregating within the European founders used in both pedigrees, Meishan individuals being all homozygous for the wild allele (G). This analysis, presented in chapter 3, shows that the structure of the pedigree (number of F1 individuals and size of half-sib families), the number of F1 heterozygous females at the IGF2 locus and the segregation of another QTL at a distance of 40 cM from the IGF2 locus influence the ability to detect imprinting at the IGF2 mutation. This spurious maternal effect can lead to incorrect conclusions regarding the imprinting status of the IGF2 mutation, with maternal effects being detected whereas they do not exist. In order to fine-map the second QTL segregating on pig chromosome 2, a backcross design was set up. Sires that were finally progeny tested were all homozygous for a Meishan haplotype in the IGF2 region, so the phenotypic variation could not be due to the IGF2-intron3-G3072A mutation. Results from the progeny-testing presented in chapter 4 confirmed that a QTL underlying fatness traits was segregating on the short arm of SSC2. However, the size of the QTL interval could not be reduced because of epistatic interactions. These epistatic effects could be detected because full-sibs with Identical-by-descent haplotypes in the QTL regions were progeny-tested. This particular design could be analysed without the strong assumptions of the line-cross models (according to which QTL alleles are fixed within breeds), so interactions could be detected. The re-analysis of one of the two F2 pedigrees confirmed that a region on SSC13 interacts with the QTL segregating in SSC2, but other candidate regions still need to be considered. The combined analysis of different pedigrees finally gives few benefits regarding the number of new QTLs that were detected. However, these combined analyses enabled to successfully consider non-additive effects such as imprinting and epistasis. During the work described in this thesis, a major technological advance occurred for pig geneticists, with the commercialisation of the Illumina PorcineSNP60 Beadchip. With this tool, the number of genotypes that can be included in a QTL analysis tremendously increased. In order to properly use this new type of information, the order of the SNPs along the genome must be reliable. In chapter 5, the first high-density genetic map of the pig is presented. This genetic map was computed using information from in silico and RH mapping of the SNPs in combination with recombination rates between them and finally comprised 38,599 SNPs. Four pig pedigrees based on different breeds were analysed separately, and the analysis of the recombination rate along the pig genome highlighted that the more recombinant regions tend to cluster around the telomeres irrespective of the location of the centromere. Two of the four analysed pedigrees comprised enough male and female meiosis to construct sex-specific maps. Major sex-differences in recombination were observed with a higher recombination rate in the females only within GC-rich regions, with females exhibiting a much stronger correlation between recombination rate and specific sequence features. This new information will be of major importance when dealing with QTL fine-mapping and pig genome evolution. Finally, in the general discussion presented in chapter 6, arguments toward further fine-mapping of QTLs in pig are given despite the increasing interest in genomic selection. Despite major improvements that have been made in the development of high-density SNP chips, efforts are still needed to overcome the biases linked to the design of the chips. In parallel to the development of high-density genotyping tools, few improvements were made regarding phenotyping. In this final chapter, various programs dedicated to the description of highly precise phenotypes and to the development of homogenous phenotyping practices are presented. Such programs, in combination with the development of appropriate genotyping tools, will facilitate the detection of causal variants. These efforts that are still necessary are not only required for pig but also to most livestock species for which QTL fine-mapping is still needed. </p

Genetic effects on lamb survival traits

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Comparison between rumen bacterial composition of growing and adult Romane sheep

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