The 'heritability' of domestication and its functional partitioning in the pig.

We propose to estimate the proportion of variance explained by regression on genome-wide markers (or genomic heritability) when wild/domestic status is considered the phenotype of interest. This approach differs from the standard Fst in that it can accommodate genetic similarity between individuals in a general form. We apply this strategy to complete genome data from 47 wild and domestic pigs from Asia and Europe. When we partitioned the total genomic variance into components associated to subsets of single nucleotide polymorphisms (SNPs) defined in terms of their annotation, we found that potentially deleterious non-synonymous mutations (9566 SNPs) explained as much genetic variance as the whole set of 25 million SNPs. This suggests that domestication may have affected protein sequence to a larger extent than regulatory or other kinds of mutations. A pathway-guided analysis revealed ovarian steroidogenesis and leptin signaling as highly relevant in domestication. The genomic regression approach proposed in this study revealed molecular processes not apparent through typical differentiation statistics. We propose that at least some of these processes are likely new discoveries because domestication is a dynamic process of genetic selection, which may not be completely characterized by a static metric like Fst. Nevertheless, and despite some particularly influential mutation types or pathways, our analyses tend to rule out a simplistic genetic basis for the domestication process: neither a single pathway nor a unique set of SNPs can explain the process as a whole.

A combined coalescence gene-dropping tool for evaluating genomic selection in complex scenarios (ms2gs).

We present ms2gs, a combined coalescence - gene dropping (i.e. backward-forward) simulator for complex traits. It therefore aims at combining the advantages of both approaches. It is primarily conceived for very short term, recent scenarios such as those that are of interest in animal and plant breeding. It is very flexible in terms of defining QTL architecture and SNP ascertainment bias, and it allows for easy modelling of alternative markers such as RADs. It can use real sequence or chip data or generate molecular polymorphisms via the coalescence. It can generate QTL conditional on extant molecular information, such as low-density genotyping. It models (simplistically) sequence, imputation or genotyping errors. It requires as input both genotypic data in plink or ms formats, and a pedigree that is used to perform the gene dropping. By default, it compares accuracy for BLUP, SNP ascertained data, sequence, and causal SNPs. It employs VanRaden's linear (GBLUP) and nonlinear method for incorporating molecular information. To illustrate the program, we present a small application in a half-sib population and a multiparental (MAGIC) cross. The program, manual and examples are available at https://github.com/mperezenciso/ms2gs.

The chimerical genome of Isla del Coco feral pigs (Costa Rica), an isolated population since 1793 but with remarkable levels of diversity.

The history of domestic species and of their wild ancestors is not a simple one, and feral processes can clarify key aspects of this history, including the adaptive processes triggered by new environments. Here, we provide a comprehensive genomic study of Isla del Coco (Costa Rica) feral pigs, a unique population that was allegedly founded by two individuals and has remained isolated since 1793. Using SNP arrays and genome sequencing, we show that Cocos pigs are hybrids between Asian and European pigs, as are modern international pig breeds. This conclusively shows that, as early as the 18th century, British vessels were loading crossbred pigs in Great Britain and transporting them overseas. We find that the Y chromosome has Asian origin, which has not been reported in any international pig breed. Chinese haplotypes seem to have been transmitted independently between Cocos and other pig breeds, suggesting independent introgression events and a complex pattern of admixing. Although data are compatible with a founder population of N = 2, variability levels are as high in Cocos pigs as in international pig breeds (~1.9 SNPs/kb) and higher than in European wild boars or local breeds (~1.7 SNPs/kb). Nevertheless, we also report a 10-Mb region with a marked decrease in variability across all samples that contains four genes (CPE, H3F3C, SC4MOL and KHL2) previously identified as highly differentiated between wild and domestic pigs. This work therefore illustrates how feral population genomic studies can help to resolve the history of domestic species and associated admixture events.

Genome data from a sixteenth century pig illuminate modern breed relationships.

Ancient DNA (aDNA) provides direct evidence of historical events that have modeled the genome of modern individuals. In livestock, resolving the differences between the effects of initial domestication and of subsequent modern breeding is not straight forward without aDNA data. Here, we have obtained shotgun genome sequence data from a sixteenth century pig from Northeastern Spain (Montsoriu castle), the ancient pig was obtained from an extremely well-preserved and diverse assemblage. In addition, we provide the sequence of three new modern genomes from an Iberian pig, Spanish wild boar and a Guatemalan Creole pig. Comparison with both mitochondrial and autosomal genome data shows that the ancient pig is closely related to extant Iberian pigs and to European wild boar. Although the ancient sample was clearly domestic, admixture with wild boar also occurred, according to the D-statistics. The close relationship between Iberian, European wild boar and the ancient pig confirms that Asian introgression in modern Iberian pigs has not existed or has been negligible. In contrast, the Guatemalan Creole pig clusters apart from the Iberian pig genome, likely due to introgression from international breeds.

Pipeliner: software to evaluate the performance of bioinformatics pipelines for next-generation resequencing.

The choice of technology and bioinformatics approach is critical in obtaining accurate and reliable information from next-generation sequencing (NGS) experiments. An increasing number of software and methodological guidelines are being published, but deciding upon which approach and experimental design to use can depend on the particularities of the species and on the aims of the study. This leaves researchers unable to produce informed decisions on these central questions. To address these issues, we developed pipeliner - a tool to evaluate, by simulation, the performance of NGS pipelines in resequencing studies. Pipeliner provides a graphical interface allowing the users to write and test their own bioinformatics pipelines with publicly available or custom software. It computes a number of statistics summarizing the performance in SNP calling, including the recovery, sensitivity and false discovery rate for heterozygous and homozygous SNP genotypes. Pipeliner can be used to answer many practical questions, for example, for a limited amount of NGS effort, how many more reliable SNPs can be detected by doubling coverage and halving sample size or what is the false discovery rate provided by different SNP calling algorithms and options. Pipeliner thus allows researchers to carefully plan their study's sampling design and compare the suitability of alternative bioinformatics approaches for their specific study systems. Pipeliner is written in C++ and is freely available from http://github.com/brunonevado/Pipeliner.

Resequencing studies of nonmodel organisms using closely related reference genomes: optimal experimental designs and bioinformatics approaches for population genomics.

Decreasing costs of next-generation sequencing (NGS) experiments have made a wide range of genomic questions open for study with nonmodel organisms. However, experimental designs and analysis of NGS data from less well-known species are challenging because of the lack of genomic resources. In this work, we investigate the performance of alternative experimental designs and bioinformatics approaches in estimating variability and neutrality tests based on the site-frequency-spectrum (SFS) from individual resequencing data. We pay particular attention to challenges faced in the study of nonmodel organisms, in particular the absence of a species-specific reference genome, although phylogenetically close genomes are assumed to be available. We compare the performance of three alternative bioinformatics approaches ­ genotype calling, genotype­haplotype calling and direct estimation without calling genotypes. We find that relying on genotype calls provides biased estimates of population genetic statistics at low to moderate read depth (2­8X). Genotype­haplotype calling returns more accurate estimates irrespective of the divergence to the reference genome, but requires moderate depth (8­20X). Direct estimation without calling genotypes returns the most accurate estimates of variability and of most SFS tests investigated, including at low read depth (2­4X). Studies without species-specific reference genome should thus aim for low read depth and avoid genotype calling whenever individual genotypes are not essential. Otherwise, aiming for moderate to high depth at the expense of number of individuals, and using genotype­haplotype calling, is recommended.

Genomic relationships computed from either next-generation sequence or array SNP data.

The use of sequence data in genomic prediction models is a topic of high interest, given the decreasing prices of current 'next'-generation sequencing technologies (NGS) and the theoretical possibility of directly interrogating the genomes for all causal mutations. Here, we compare by simulation how well genetic relationships (G) could be estimated using either NGS or ascertained SNP arrays. DNA sequences were simulated using the coalescence according to two scenarios: a 'cattle' scenario that consisted of a bottleneck followed by a split in two breeds without migration, and a 'pig' model where Chinese introgression into international pig breeds was simulated. We found that introgression results in a large amount of variability across the genome and between individuals, both in differentiation and in diversity. In general, NGS data allowed the most accurate estimates of G, provided enough sequencing depth was available, because shallow NGS (4×) may result in highly distorted estimates of G elements, especially if not standardized by allele frequency. However, high-density genotyping can also result in accurate estimates of G. Given that genotyping is much less noisy than NGS data, it is suggested that specific high-density arrays (~3M SNPs) that minimize the effects of ascertainment could be developed in the population of interest by sequencing the most influential animals and rely on those arrays for implementing genomic selection.

Worldwide genetic relationships of pigs as inferred from X chromosome SNPs.

The phylogeography of the porcine X chromosome has not been studied despite the unique characteristics of this chromosome. Here, we genotyped 59 single nucleotide polymorphisms (SNPs) in 312 pigs from around the world, representing 39 domestic breeds and wild boars in 30 countries. Overall, widespread commercial breeds showed the highest heterozygosity values, followed by African and American populations. Structuring, as inferred from FST and analysis of molecular variance, was consistently larger in the non-pseudoautosomal (NPAR) than in the pseudoautosomal regions (PAR). Our results show that genetic relationships between populations can vary widely between the NPAR and the PAR, underscoring the fact that their genetic trajectories can be quite different. NPAR showed an increased commercial-like genetic component relative to the PAR, probably because human selection processes to obtain individuals with high productive parameters were mediated by introgressing boars rather than sows.

Porcine colonization of the Americas: a 60k SNP story.

The pig, Sus scrofa, is a foreign species to the American continent. Although pigs originally introduced in the Americas should be related to those from the Iberian Peninsula and Canary islands, the phylogeny of current creole pigs that now populate the continent is likely to be very complex. Because of the extreme climates that America harbors, these populations also provide a unique example of a fast evolutionary phenomenon of adaptation. Here, we provide a genome wide study of these issues by genotyping, with a 60k SNP chip, 206 village pigs sampled across 14 countries and 183 pigs from outgroup breeds that are potential founders of the American populations, including wild boar, Iberian, international and Chinese breeds. Results show that American village pigs are primarily of European ancestry, although the observed genetic landscape is that of a complex conglomerate. There was no correlation between genetic and geographical distances, neither continent wide nor when analyzing specific areas. Most populations showed a clear admixed structure where the Iberian pig was not necessarily the main component, illustrating how international breeds, but also Chinese pigs, have contributed to extant genetic composition of American village pigs. We also observe that many genes related to the cardiovascular system show an increased differentiation between altiplano and genetically related pigs living near sea level.

Genome-wide association study for intramuscular fatty acid composition in an Iberian × Landrace cross.

The lipid content and fatty acid (FA) profile have an important impact in human health as well as in the technological transformation and nutritional and organoleptic quality of meat. A genome-wide association study (GWAS) on 144 backcross pigs (25% Iberian × 75% Landrace) was performed for 32 traits associated with intramuscular FA composition and indices of FA metabolism. The GWAS was carried out using Qxpak 5.0 and the genotyping information obtained from the Porcine SNP60K BeadChip (Illumina Inc., San Diego, CA). Signals of significant association considering a false- discovery rate (q-value < 0.05) were observed in 15 of the 32 analyzed traits, and a total of 813 trait-associated SNP (TAS), distributed in 43 chromosomal intervals on almost all autosomes, were annotated. According to the clustering analysis based on functional classification, several of the annotated genes are related to FA composition and lipid metabolism. Some interesting positional concordances among TAS and previously reported QTL for FA compositions and/or other lipid traits were also found. These common genomic regions for different traits suggest pleiotropic effects for FA composition and were found primarily on SSC4, SSC8, and SSC16. These results contribute to our understanding of the complex genetic basis of FA composition and FA metabolism.

Building phenotype networks to improve QTL detection: a comparative analysis of fatty acid and fat traits in pigs.

Models in QTL mapping can be improved by considering all potential variables, i.e. we can use remaining traits other than the trait under study as potential predictors. QTL mapping is often conducted by correcting for a few fixed effects or covariates (e.g. sex, age), although many traits with potential causal relationships between them are recorded. In this work, we evaluate by simulation several procedures to identify optimum models in QTL scans: forward selection, undirected dependency graph and QTL-directed dependency graph (QDG). The latter, QDG, performed better in terms of power and false discovery rate and was applied to fatty acid (FA) composition and fat deposition traits in two pig F2 crosses from China and Spain. Compared with the typical QTL mapping, QDG approach revealed several new QTL. To the contrary, several FA QTL on chromosome 4 (e.g. Palmitic, C16:0; Stearic, C18:0) detected by typical mapping vanished after adjusting for phenotypic covariates in QDG mapping. This suggests that the QTL detected in typical mapping could be indirect. When a QTL is supported by both approaches, there is an increased confidence that the QTL have a primary effect on the corresponding trait. An example is a QTL for C16:1 on chromosome 8. In conclusion, mapping QTL based on causal phenotypic networks can increase power and help to make more biologically sound hypothesis on the genetic architecture of complex traits.

Partial short-read sequencing of a highly inbred Iberian pig and genomics inference thereof.

Despite dramatic reduction in sequencing costs with the advent of next generation sequencing technologies, obtaining a complete mammalian genome sequence at sufficient depth is still costly. An alternative is partial sequencing. Here, we have sequenced a reduced representation library of an Iberian sow from the Guadyerbas strain, a highly inbred strain that has been used in numerous QTL studies because of its extreme phenotypic characteristics. Using the Illumina Genome Analyzer II (San Diego, CA, USA), we resequenced ∼ 1% of the genome with average 4 × depth, identifying 68,778 polymorphisms. Of these, 55,457 were putative fixed differences with respect to the assembly, based on the genome of a Duroc pig, and 13,321 were heterozygous positions within Guadyerbas. Despite being highly inbred, the estimate of heterozygosity within Guadyerbas was ∼ 0.78 kb(-1) in autosomes, after correcting for low depth. Nucleotide variability was consistently higher at the telomeric regions than on the rest of the chromosome, likely a result of increased recombination rates. Further, variability was 50% lower in the X-chromosome than in autosomes, which may be explained by a recent bottleneck or by selection. We divided the whole genome in 500 kb windows and we analyzed overrepresented gene ontology terms in regions of low and high variability. Multi organism process, pigmentation and cell killing were overrepresented in high variability regions and metabolic process ontology, within low variability regions. Further, a genome wide Hudson-Kreitman-Aguadé test was carried out per window; overall, variability was in agreement with neutral expectations.

Evolutionary study of a potential selection target region in the pig.

Domestication, modern breeding and artificial selection have shaped dramatically the genomic variability of domestic animals. In livestock, the so-called FAT1 quantitative trait locus (QTL) in porcine chromosome 4 was the first QTL uncovered although, to date, its precise molecular nature has remained elusive. Here, we characterize the nucleotide variability of 13 fragments of ∼500 bp equally spaced in a 2 Mb region in the vicinity of the FAT1 region in a wide-diversity panel of 32 pigs. Asian and European animals, including local Mediterranean and international pig breeds, were sequenced. Patterns of genetic variability were very complex and varied largely across loci and populations; they did not reveal overall a clear signal of a selective sweep in any breed, although FABP4 fragment showed a significantly higher diversity. We used an approximate Bayesian computation approach to infer the evolutionary history of this SSC4 region. Notably, we found that European pig populations have a much lower effective size than their Asian counterparts: in the order of hundreds vs hundreds of thousands. We show also an important part of extant European variability is actually due to introgression of Asian germplasm into Europe. This study shows how a potential loss in diversity caused by bottlenecks and possible selective sweeps associated with domestication and artificial selection can be counterbalanced by migration, making it much more difficult the identification of selection footprints based on naive demographic assumptions. Given the small fragment analyzed here, it remains to be studied how these conclusions apply to the rest of the genome.

Mitochondrial DNA diversity in wild boar from the Primorsky Krai Region (East Russia).

We have studied the cytochrome B gene and control region DNA variability in 14 wild boars from the Primorsky Region, in the far east corner of Russia. Variability was low (π = 0.00248 overall) compared with the usual estimates in these loci, indicating that this is a rather closed population. Seven haplotypes were found, and one was identical to a Chinese wild boar. Phylogeographically, the sequences clustered among several Asian clades, primarily Chinese domestic pigs and Japanese and Chinese wild boars, and are positioned within the D2 clade reported by Larson et al. [Science307, 2005; 1618]. Although North Korean pigs should be studied, our data suggest that the Primorsky mtDNA signature is absent from domestic pigs. Sequences are available through GenBank identifiers HM010461-HM010488.

Nucleotide variability of the porcine SERPINA6 gene and the origin of a putative causal mutation associated with meat quality.

The serpin peptidase inhibitor, clade A, member 6 gene (SERPINA6), also known as corticosteroid-binding globulin or CBG, is involved in obesity and stress sensitivity. Previous studies have reported putative causal mutations within that gene in the porcine species. To characterize a hypothetical selective footprint, we have resequenced approximately 6 kb of coding and non-coding fragments in 20 pigs comprising domestic breeds and wild boars from Asia and Europe. Nucleotide variability was found to be far greater within Asian pig breeds than European breeds (π = 1% vs. 0.05%, respectively), which is consistent with pig evolutionary history. The putative causal amino acid substitution p.Gly307Arg (SNP c.919G>A) associated with meat quality (drip loss) was only detected in European domestic pig breeds, suggesting a very recent mutation that appeared after domestication in Europe. No support for positive selection was detected, as no reduction in levels of diversity surrounding the mutation was found in lean breeds with respect to wild boar.

Massive parallel sequencing in animal genetics: wherefroms and wheretos.

Next generation sequencing (NGS) has revolutionized genomics research, making it difficult to overstate its impact on studies of Biology. NGS will immediately allow researchers working in non-mainstream species to obtain complete genomes together with a comprehensive catalogue of variants. In addition, RNA-seq will be a decisive way to annotate genes that cannot be predicted purely by computational or comparative approaches. Future applications include whole genome sequence association studies, as opposed to classical SNP-based association, and implementing this new source of information into breeding programmes. For these purposes, one of the main advantages of sequencing vs. genotyping is the possibility of identifying copy number variants. Currently, experimental design is a topic of utmost interest, and here we discuss some of the options available, including pools and reduced representation libraries. Although bioinformatics is still an important bottleneck, this limitation is only transient and should not deter animal geneticists from embracing these technologies.

Large-scale SNP genotyping in crosses between outbred lines: how useful is it?

Although genome-wide association (GWA) studies are not worth the effort in crosses between inbred lines, many crosses are actually made up of divergent yet outbred populations. Despite its relevance, however, this experimental setting has not been studied at a time when SNP microarrays are available in many species. To assess whether GWA can be useful in this setting, we performed combined coalescence--gene dropping simulations. We studied the influence of marker density, QTL effect and QTL allele frequency on power, false discovery rate (FDR) and accuracy. Our results suggest that GWA in outbred F(2) crosses is useful, especially in large populations. Under these circumstances, accuracy increased and FDR decreased as compared with classical linkage analysis. However, current SNP densities (in the order of 30-60 K SNPs/genome or equivalent to 10-20 SNPs per cM) may not be much better than linkage analysis and higher SNP densities may be required. SNP ascertainment had an important effect; the best option was to select SNPs as uniformly as possible without setting any restriction on allele frequency. Using only SNPs with fixed alternative alleles in each breed controlled false positive rate but was not useful to detect variability within lines. Finally, the most significant SNP was not necessarily the closest to the causal SNP, although the closest SNPs were usually above the significance threshold; thus, it is prudent to follow-up significant signals located in regions of interest even if they do not correspond to absolute maxima.

A non-synonymous mutation in a conserved site of the MTTP gene is strongly associated with protein activity and fatty acid profile in pigs.

Despite the economic interest of the fatty acid profile in pigs, no gene has been convincingly associated with this trait so far. Here, the porcine microsomal triglyceride transfer protein (MTTP) gene, which plays a crucial role in the assembly of nascent lipoproteins, has been analysed as a positional candidate gene for a QTL affecting the fatty acid composition that was previously identified on chromosome 8 in an Iberian by Landrace F(2) cross. By resequencing a panel of different breeds, a non-synonymous polymorphism in a conserved residue of the lipid transfer domain of MTTP was identified. Association analyses with this polymorphism showed a strong association with the fatty acid composition of porcine fat, much stronger than the QTL effect, in the F(2) cross and in a synthetic Sino-European line. In addition, in vitro activity assays in liver protein extracts have shown that this mutation is also associated with the lipid transfer activity of the MTTP protein (P < 0.1). These results suggest that the detected polymorphism is a potential causal factor of the fatty acid composition QTL. There appears to be an interaction between the porcine MTTP genotype and the type of fat source in the pig diet, which would agree with the previous results on the biology of MTTP biology.