Whole-genome sequencing of cryopreserved resources from French Large White pigs at two distinct sampling times reveals strong signatures of convergent and divergent selection between the dam and sire lines

BACKGROUND

Numerous genomic scans for positive selection have been performed in livestock species within the last decade, but often a detailed characterization of the detected regions (gene or trait under selection, timing of selection events) is lacking. Cryopreserved resources stored in reproductive or DNA gene banks offer a great opportunity to improve this characterization by providing direct access to recent allele frequency dynamics, thereby differentiating between signatures from recent breeding objectives and those related to more ancient selection constraints. Improved characterization can also be achieved by using next-generation sequencing data, which helps narrowing the size of the detected regions while reducing the number of associated candidate genes.

METHODS

We estimated genetic diversity and detected signatures of recent selection in French Large White pigs by sequencing the genomes of 36 animals from three distinct cryopreserved samples: two recent samples from dam (LWD) and sire (LWS) lines, which had diverged from 1995 and were selected under partly different objectives, and an older sample from 1977 prior to the divergence.

RESULTS

French LWD and LWS lines have lost approximately 5% of the SNPs that segregated in the 1977 ancestral population. Thirty-eight genomic regions under recent selection were detected in these lines and the corresponding selection events were further classified as convergent between lines (18 regions), divergent between lines (10 regions), specific to the dam line (6 regions) or specific to the sire line (4 regions). Several biological functions were found to be significantly enriched among the genes included in these regions: body size, body weight and growth regardless of the category, early life survival and calcium metabolism more specifically in the signatures in the dam line and lipid and glycogen metabolism more specifically in the signatures in the sire line. Recent selection on IGF2 was confirmed and several other regions were linked to a single candidate gene (ARHGAP10, BMPR1B, GNA14, KATNA1, LPIN1, PKP1, PTH, SEMA3E or ZC3HAV1, among others).

CONCLUSIONS

These results illustrate that sequencing the genome of animals at several recent time points generates considerable insight into the traits, genes and variants under recent selection in a population. This approach could be applied to other livestock populations, e.g. by exploiting the rich biological resources stored in cryobanks.

Early life microbial exposures shape the Crassostrea gigas immune system for lifelong and intergenerational disease protection

BACKGROUND

The interaction of organisms with their surrounding microbial communities influences many biological processes, a notable example of which is the shaping of the immune system in early life. In the Pacific oyster, Crassostrea gigas, the role of the environmental microbial community on immune system maturation - and, importantly, protection from infectious disease - is still an open question.

RESULTS

Here, we demonstrate that early life microbial exposure durably improves oyster survival when challenged with the pathogen causing Pacific oyster mortality syndrome (POMS), both in the exposed generation and in the subsequent one. Combining microbiota, transcriptomic, genetic, and epigenetic analyses, we show that the microbial exposure induced changes in epigenetic marks and a reprogramming of immune gene expression leading to long-term and intergenerational immune protection against POMS.

CONCLUSIONS

We anticipate that this protection likely extends to additional pathogens and may prove to be an important new strategy for safeguarding oyster aquaculture efforts from infectious disease. tag the videobyte/videoabstract in this section Video Abstract.

Heterogeneity in effective size across the genome: effects on the inverse instantaneous coalescence rate (IICR) and implications for demographic inference under linked selection

The relative contribution of selection and neutrality in shaping species genetic diversity is one of the most central and controversial questions in evolutionary theory. Genomic data provide growing evidence that linked selection, i.e. the modification of genetic diversity at neutral sites through linkage with selected sites, might be pervasive over the genome. Several studies proposed that linked selection could be modeled as first approximation by a local reduction (e.g. purifying selection, selective sweeps) or increase (e.g. balancing selection) of effective population size (Ne). At the genome-wide scale, this leads to variations of Ne from one region to another, reflecting the heterogeneity of selective constraints and recombination rates between regions. We investigate here the consequences of such genomic variations of Ne on the genome-wide distribution of coalescence times. The underlying motivation concerns the impact of linked selection on demographic inference, because the distribution of coalescence times is at the heart of several important demographic inference approaches. Using the concept of inverse instantaneous coalescence rate, we demonstrate that in a panmictic population, linked selection always results in a spurious apparent decrease of Ne along time. Balancing selection has a particularly large effect, even when it concerns a very small part of the genome. We also study more general models including genuine population size changes, population structure or transient selection and find that the effect of linked selection can be significantly reduced by that of population structure. The models and conclusions presented here are also relevant to the study of other biological processes generating apparent variations of Ne along the genome.

Genomic Uniqueness of Local Sheep Breeds From Morocco

Sheep farming is a major source of meat in Morocco and plays a key role in the country's agriculture. This study aims at characterizing the whole-genome diversity and demographic history of the main Moroccan sheep breeds, as well as to identify selection signatures within and between breeds. Whole genome data from 87 individuals representing the five predominant local breeds were used to estimate their level of neutral genetic diversity and to infer the variation of their effective population size over time. In addition, we used two methods to detect selection signatures: either for detecting selective sweeps within each breed separately or by detecting differentially selected regions by contrasting different breeds. We identified hundreds of genomic regions putatively under selection, which related to several biological terms involved in local adaptation or the expression of zootechnical performances such as Growth, UV protection, Cell maturation or Feeding behavior. The results of this study revealed selection signatures in genes that have an important role in traits of interest and increased our understanding of how genetic diversity is distributed in these local breeds. Thus, Moroccan local sheep breeds exhibit both a high genetic diversity and a large set of adaptive variations, and therefore, represent a valuable genetic resource for the conservation of sheep in the context of climate change.

Inferring number of populations and changes in connectivity under the n-island model

Inferring the demographic history of species is one of the greatest challenges in populations genetics. This history is often represented as a history of size changes, ignoring population structure. Alternatively, when structure is assumed, it is defined a priori as a population tree and not inferred. Here we propose a framework based on the IICR (Inverse Instantaneous Coalescence Rate). The IICR can be estimated for a single diploid individual using the PSMC method of Li and Durbin (2011). For an isolated panmictic population, the IICR matches the population size history, and this is how the PSMC outputs are generally interpreted. However, it is increasingly acknowledged that the IICR is a function of the demographic model and sampling scheme with limited connection to population size changes. Our method fits observed IICR curves of diploid individuals with IICR curves obtained under piecewise stationary symmetrical island models. In our models we assume a fixed number of time periods during which gene flow is constant, but gene flow is allowed to change between time periods. We infer the number of islands, their sizes, the periods at which connectivity changes and the corresponding rates of connectivity. Validation with simulated data showed that the method can accurately recover most of the scenario parameters. Our application to a set of five human PSMCs yielded demographic histories that are in agreement with previous studies using similar methods and with recent research suggesting ancient human structure. They are in contrast with the view of human evolution consisting of one ancestral population branching into three large continental and panmictic populations with varying degrees of connectivity and no population structure within each continent.

Gene Banks as Reservoirs to Detect Recent Selection: The Example of the Asturiana de los Valles Bovine Breed

Gene banks, framed within the efforts for conserving animal genetic resources to ensure the adaptability of livestock production systems to population growth, income, and climate change challenges, have emerged as invaluable resources for biodiversity and scientific research. Allele frequency trajectories over the few last generations contain rich information about the selection history of populations, which cannot be obtained from classical selection scan approaches based on present time data only. Here we apply a new statistical approach taking advantage of genomic time series and a state of the art statistic (nSL) based on present time data to disentangle both old and recent signatures of selection in the Asturiana de los Valles cattle breed. This local Spanish originally multipurpose breed native to Asturias has been selected for beef production over the last few generations. With the use of SNP chip and whole-genome sequencing (WGS) data, we detect candidate regions under selection reflecting the effort of breeders to produce economically valuable beef individuals, e.g., by improving carcass and meat traits with genes such as MSTN, FLRT2, CRABP2, ZNF215, RBPMS2, OAZ2, or ZNF609, while maintaining the ability to thrive under a semi-intensive production system, with the selection of immune (GIMAP7, GIMAP4, GIMAP8, and TICAM1) or olfactory receptor (OR2D2, OR2D3, OR10A4, and 0R6A2) genes. This kind of information will allow us to take advantage of the invaluable resources provided by gene bank collections from local less competitive breeds, enabling the livestock industry to exploit the different mechanisms fine-tuned by natural and human-driven selection on different populations to improve productivity.

The quail genome: insights into social behaviour, seasonal biology and infectious disease response

BACKGROUND

The Japanese quail (Coturnix japonica) is a popular domestic poultry species and an increasingly significant model species in avian developmental, behavioural and disease research.

RESULTS

We have produced a high-quality quail genome sequence, spanning 0.93 Gb assigned to 33 chromosomes. In terms of contiguity, assembly statistics, gene content and chromosomal organisation, the quail genome shows high similarity to the chicken genome. We demonstrate the utility of this genome through three diverse applications. First, we identify selection signatures and candidate genes associated with social behaviour in the quail genome, an important agricultural and domestication trait. Second, we investigate the effects and interaction of photoperiod and temperature on the transcriptome of the quail medial basal hypothalamus, revealing key mechanisms of photoperiodism. Finally, we investigate the response of quail to H5N1 influenza infection. In quail lung, many critical immune genes and pathways were downregulated after H5N1 infection, and this may be key to the susceptibility of quail to H5N1.

CONCLUSIONS

We have produced a high-quality genome of the quail which will facilitate further studies into diverse research questions using the quail as a model avian species.

An ABC Method for Whole-Genome Sequence Data: Inferring Paleolithic and Neolithic Human Expansions

Species generally undergo a complex demographic history consisting, in particular, of multiple changes in population size. Genome-wide sequencing data are potentially highly informative for reconstructing this demographic history. A crucial point is to extract the relevant information from these very large data sets. Here, we design an approach for inferring past demographic events from a moderate number of fully sequenced genomes. Our new approach uses Approximate Bayesian Computation, a simulation-based statistical framework that allows 1) identifying the best demographic scenario among several competing scenarios and 2) estimating the best-fitting parameters under the chosen scenario. Approximate Bayesian Computation relies on the computation of summary statistics. Using a cross-validation approach, we show that statistics such as the lengths of haplotypes shared between individuals, or the decay of linkage disequilibrium with distance, can be combined with classical statistics (e.g., heterozygosity and Tajima's D) to accurately infer complex demographic scenarios including bottlenecks and expansion periods. We also demonstrate the importance of simultaneously estimating the genotyping error rate. Applying our method on genome-wide human-sequence databases, we finally show that a model consisting in a bottleneck followed by a Paleolithic and a Neolithic expansion is the most relevant for Eurasian populations.

A guinea fowl genome assembly provides new evidence on evolution following domestication and selection in galliformes

The helmeted guinea fowl Numida meleagris belongs to the order Galliformes. Its natural range includes a large part of sub‐Saharan Africa, from Senegal to Eritrea and from Chad to South Africa. Archaeozoological and artistic evidence suggest domestication of this species may have occurred about 2,000 years BP in Mali and Sudan primarily as a food resource, although villagers also benefit from its capacity to give loud alarm calls in case of danger, of its ability to consume parasites such as ticks and to hunt snakes, thus suggesting its domestication may have resulted from a commensal association process. Today, it is still farmed in Africa, mainly as a traditional village poultry, and is also bred more intensively in other countries, mainly France and Italy. The lack of available molecular genetic markers has limited the genetic studies conducted to date on guinea fowl. We present here a first‐generation whole‐genome sequence draft assembly used as a reference for a study by a Pool‐seq approach of wild and domestic populations from Europe and Africa. We show that the domestic populations share a higher genetic similarity between each other than they do to wild populations living in the same geographical area. Several genomic regions showing selection signatures putatively related to domestication or importation to Europe were detected, containing candidate genes, most notably EDNRB2, possibly explaining losses in plumage coloration phenotypes in domesticated populations.

Identification of genomic regions and candidate genes for chicken meat ultimate pH by combined detection of selection signatures and QTL

BACKGROUND

The understanding of the biological determinism of meat ultimate pH, which is strongly related to muscle glycogen content, is a key point for the control of muscle integrity and meat quality in poultry. In the present study, we took advantage of a unique model of two broiler lines divergently selected for the ultimate pH of the pectoralis major muscle (PM-pHu) in order to decipher the genetic control of this trait. Two complementary approaches were used: detection of selection signatures generated during the first five generations and genome-wide association study for PM-pHu and Sartorius muscle pHu (SART-pHu) at the sixth generation of selection.

RESULTS

Sixty-three genomic regions showed significant signatures of positive selection. Out of the 10 most significant regions (detected by HapFLK or FLK method with a p-value below 1e-6), 4 were detected as soon as the first generation (G1) and were recovered at each of the four following ones (G2-G5). Another four corresponded to a later onset of selection as they were detected only at G5. In total, 33 SNPs, located in 24 QTL regions, were significantly associated with PM-pHu. For SART-pHu, we detected 18 SNPs located in 10 different regions. These results confirmed a polygenic determinism for these traits and highlighted two major QTL: one for PM-pHu on GGA1 (with a Bayes Factor (BF) of 300) and one for SART-pHu on GGA4 (with a BF of 257). Although selection signatures were enriched in QTL for PM-pHu, several QTL with strong effect haven't yet responded to selection, suggesting that the divergence between lines might be further increased.

CONCLUSIONS

A few regions of major interest with significant selection signatures and/or strong association with PM-pHu or SART-pHu were evidenced for the first time in chicken. Their gene content suggests several candidates associated with diseases of glycogen storage in humans. The impact of these candidate genes on meat quality and muscle integrity should be further investigated in chicken.

Meta-analysis of genome-wide association studies for cattle stature identifies common genes that regulate body size in mammals

Stature is affected by many polymorphisms of small effect in humans ¹ . In contrast, variation in dogs, even within breeds, has been suggested to be largely due to variants in a small number of genes^2,3. Here we use data from cattle to compare the genetic architecture of stature to those in humans and dogs. We conducted a meta-analysis for stature using 58,265 cattle from 17 populations with 25.4 million imputed whole-genome sequence variants. Results showed that the genetic architecture of stature in cattle is similar to that in humans, as the lead variants in 163 significantly associated genomic regions (P < 5 × 10^-8) explained at most 13.8% of the phenotypic variance. Most of these variants were noncoding, including variants that were also expression quantitative trait loci (eQTLs) and in ChIP-seq peaks. There was significant overlap in loci for stature with humans and dogs, suggesting that a set of common genes regulates body size in mammals.

Inferring Population Size History from Large Samples of Genome-Wide Molecular Data - An Approximate Bayesian Computation Approach

Inferring the ancestral dynamics of effective population size is a long-standing question in population genetics, which can now be tackled much more accurately thanks to the massive genomic data available in many species. Several promising methods that take advantage of whole-genome sequences have been recently developed in this context. However, they can only be applied to rather small samples, which limits their ability to estimate recent population size history. Besides, they can be very sensitive to sequencing or phasing errors. Here we introduce a new approximate Bayesian computation approach named PopSizeABC that allows estimating the evolution of the effective population size through time, using a large sample of complete genomes. This sample is summarized using the folded allele frequency spectrum and the average zygotic linkage disequilibrium at different bins of physical distance, two classes of statistics that are widely used in population genetics and can be easily computed from unphased and unpolarized SNP data. Our approach provides accurate estimations of past population sizes, from the very first generations before present back to the expected time to the most recent common ancestor of the sample, as shown by simulations under a wide range of demographic scenarios. When applied to samples of 15 or 25 complete genomes in four cattle breeds (Angus, Fleckvieh, Holstein and Jersey), PopSizeABC revealed a series of population declines, related to historical events such as domestication or modern breed creation. We further highlight that our approach is robust to sequencing errors, provided summary statistics are computed from SNPs with common alleles.

Molecular data sampled from extant individuals contains considerable information about their demographic history. In particular, one classical question in population genetics is to reconstruct past population size changes from such data. Relating these changes to various climatic, geological or anthropogenic events allows characterizing the main factors driving genetic diversity and can have major outcomes for conservation. Until recently, mostly very simple histories, including one or two population size changes, could be estimated from genetic data. This has changed with the sequencing of entire genomes in many species, and several methods allow now inferring complex histories consisting of several tens of population size changes. However, analyzing entire genomes, while accounting for recombination, remains a statistical and numerical challenge. These methods, therefore, can only be applied to small samples with a few diploid genomes. We overcome this limitation by using an approximate estimation approach, where observed genomes are summarized using a small number of statistics related to allele frequencies and linkage disequilibrium. In contrast to previous approaches, we show that our method allows us to reconstruct also the most recent part (the last 100 generations) of the population size history. As an illustration, we apply it to large samples of whole-genome sequences in four cattle breeds.

Genomic Signature of Selective Sweeps Illuminates Adaptation of Medicago truncatula to Root-Associated Microorganisms

Medicago truncatula is a model legume species used to investigate plant-microorganism interactions, notably root symbioses. Massive population genomic and transcriptomic data now available for this species open the way for a comprehensive investigation of genomic variations associated with adaptation of M. truncatula to its environment. Here we performed a fine-scale genome scan of selective sweep signatures in M. truncatula using more than 15 million single nucleotide polymorphisms identified on 283 accessions from two populations (Circum and Far West), and exploited annotation and published transcriptomic data to identify biological processes associated with molecular adaptation. We identified 58 swept genomic regions with a 15 kb average length and comprising 3.3 gene models on average. The unimodal sweep state probability distribution in these regions enabled us to focus on the best single candidate gene per region. We detected two unambiguous species-wide selective sweeps, one of which appears to underlie morphological adaptation. Population genomic analyses of the remaining 56 sweep signatures indicate that sweeps identified in the Far West population are less population-specific and probably more ancient than those identified in the Circum population. Functional annotation revealed a predominance of immunity-related adaptations in the Circum population. Transcriptomic data from accessions of the Far West population allowed inference of four clusters of coregulated genes putatively involved in the adaptive control of symbiotic carbon flow and nodule senescence, as well as in other root adaptations upon infection with soil microorganisms. We demonstrate that molecular adaptations in M. truncatula were primarily triggered by selective pressures from root-associated microorganisms.

Selection signatures in worldwide sheep populations

The diversity of populations in domestic species offers great opportunities to study genome response to selection. The recently published Sheep HapMap dataset is a great example of characterization of the world wide genetic diversity in sheep. In this study, we re-analyzed the Sheep HapMap dataset to identify selection signatures in worldwide sheep populations. Compared to previous analyses, we made use of statistical methods that (i) take account of the hierarchical structure of sheep populations, (ii) make use of linkage disequilibrium information and (iii) focus specifically on either recent or older selection signatures. We show that this allows pinpointing several new selection signatures in the sheep genome and distinguishing those related to modern breeding objectives and to earlier post-domestication constraints. The newly identified regions, together with the ones previously identified, reveal the extensive genome response to selection on morphology, color and adaptation to new environments.

Functional investigation of a QTL affecting resistance to Haemonchus contortus in sheep

This study reports a functional characterization of a limited segment (QTL) of sheep chromosome 12 associated with resistance to the abomasal nematode Haemonchus contortus. The first objective was to validate the identified QTL through the comparison of genetically susceptible (N) and resistant (R) sheep produced from Martinik × Romane back-cross sheep. The R and N genotype groups were then experimentally infected with 10 000 H. contortus larvae and measured for FEC (every three days from 18 to 30 days post-challenge), haematocrit, worm burden and fertility. Significant differences in FEC and haematocrit drop were found between R and N sheep. In addition, the female worms recovered from R sheep were less fecund. The second step of the characterization was to investigate functional mechanisms associated with the QTL, thanks to a gene expression analysis performed on the abomasal mucosa and the abomasal lymph node. The gene expression level of a candidate gene lying within the QTL region (PAPP-A2) was measured. In addition, putative interactions between the chromosome segment under study and the top ten differentially expressed genes between resistant MBB and susceptible RMN sheep highlighted in a previous microarray experiment were investigated. We found an induction of Th-2 related cytokine genes expression in the abomasal mucosa of R sheep. Down-regulation of the PAPP-A2 gene expression was observed between naïve and challenged sheep although no differential expression was recorded between challenged R and N sheep. The genotyping of this limited region should contribute to the ability to predict the intrinsic resistance level of sheep.

Genome-wide linkage disequilibrium in the Blonde d'Aquitaine cattle breed

We present here the first genome-wide characterization of linkage disequilibrium (LD) in the French Blonde d'Aquitaine (BLA) breed, a well-muscled breed renowned for producing high-yielding beef carcasses. To assess the pattern and extent of LD, we used a sample of 30 unrelated bulls and 36 923 single nucleotide polymorphisms (SNPs) covering all cattle autosomes. The squared correlation of the alleles at two loci (r(2) ) was used as a measure of LD. The analysis of adjacent marker pairs revealed that the level of LD decreases rapidly with physical distance between SNPs. Overall mean r(2) was 0.205 (±0.262). Strong LD (r(2)  > 0.8) and useful LD (measured as r(2 ) > 0.2) were observed within genomic regions of up to 720 and 724 kb, respectively. We analysed the genetic structure of the BLA population and found stratification. The observed genetic sub-structuring is consistent with the known recent demographic history that occurred during BLA breed formation. Our results indicate that LD mapping of phenotypic traits in the BLA population is feasible; however, because of this sub-structuring, special care is needed to reduce the likelihood of false-positive associations between marker loci and traits of interest.

Detection of signatures of selective sweeps in the Blonde d'Aquitaine cattle breed

Identifying recent positive selection signatures in domesticated animals could provide information on genome response to strong directional selection from domestication and artificial selection and therefore could help in identifying mutations responsible for improved traits. We used genotyping data generated using Illumina's BovineSNP50 Genotyping BeadChips to identify selection signatures in the Blonde d'Aquitaine breed, a well-muscled French beef breed. For this purpose, we employed a hidden Markov model-based test, which detects selection by studying local variations in the allele frequency spectrum along the genome, within a single population. Three regions containing selective sweeps were identified. Annotation of genes located within these regions revealed interesting candidate genes. For example, myostatin (also known as GDF8), a known muscle growth factor inhibitor, is located within the selection signature region found on chromosome 2. In addition, we have identified chromosomal regions that show some evidence of selection within QTL regions for economically important traits. The results of this study could help to better understand the mechanisms related to the selection of the Blonde d'Aquitaine breed.

Pool-hmm: a Python program for estimating the allele frequency spectrum and detecting selective sweeps from next generation sequencing of pooled samples

Due to its cost effectiveness, next generation sequencing of pools of individuals (Pool-Seq) is becoming a popular strategy for genome-wide estimation of allele frequencies in population samples. As the allele frequency spectrum provides information about past episodes of selection, Pool-seq is also a promising design for genomic scans for selection. However, no software tool has yet been developed for selection scans based on Pool-Seq data. We introduce Pool-hmm, a Python program for the estimation of allele frequencies and the detection of selective sweeps in a Pool-Seq sample. Pool-hmm includes several options that allow a flexible analysis of Pool-Seq data, and can be run in parallel on several processors. Source code and documentation for Pool-hmm is freely available at https://qgsp.jouy.inra.fr/.

Detecting selective sweeps from pooled next-generation sequencing samples

Due to its cost effectiveness, next-generation sequencing of pools of individuals (Pool-Seq) is becoming a popular strategy for characterizing variation in population samples. Because Pool-Seq provides genome-wide SNP frequency data, it is possible to use them for demographic inference and/or the identification of selective sweeps. Here, we introduce a statistical method that is designed to detect selective sweeps from pooled data by accounting for statistical challenges associated with Pool-Seq, namely sequencing errors and random sampling among chromosomes. This allows for an efficient use of the information: all base calls are included in the analysis, but the higher credibility of regions with higher coverage and base calls with better quality scores is accounted for. Computer simulations show that our method efficiently detects sweeps even at very low coverage (0.5× per chromosome). Indeed, the power of detecting sweeps is similar to what we could expect from sequences of individual chromosomes. Since the inference of selective sweeps is based on the allele frequency spectrum (AFS), we also provide a method to accurately estimate the AFS provided that the quality scores for the sequence reads are reliable. Applying our approach to Pool-Seq data from Drosophila melanogaster, we identify several selective sweep signatures on chromosome X that include some previously well-characterized sweeps like the wapl region.

Genome-wide analysis of the world's sheep breeds reveals high levels of historic mixture and strong recent selection

Genomic structure in a global collection of domesticated sheep reveals a history of artificial selection for horn loss and traits relating to pigmentation, reproduction, and body size.

Through their domestication and subsequent selection, sheep have been adapted to thrive in a diverse range of environments. To characterise the genetic consequence of both domestication and selection, we genotyped 49,034 SNP in 2,819 animals from a diverse collection of 74 sheep breeds. We find the majority of sheep populations contain high SNP diversity and have retained an effective population size much higher than most cattle or dog breeds, suggesting domestication occurred from a broad genetic base. Extensive haplotype sharing and generally low divergence time between breeds reveal frequent genetic exchange has occurred during the development of modern breeds. A scan of the genome for selection signals revealed 31 regions containing genes for coat pigmentation, skeletal morphology, body size, growth, and reproduction. We demonstrate the strongest selection signal has occurred in response to breeding for the absence of horns. The high density map of genetic variability provides an in-depth view of the genetic history for this important livestock species.

During the process of domestication, mankind recruited animals from the wild into a captive environment, changing their morphology, behaviour, and genetics. In the case of sheep, domestication and subsequent selection by their animal handlers over thousands of years has produced a spectrum of breeds specialised for the production of wool, milk, and meat. We sought to use this population history to search for the genes that directly underpin phenotypic variation. We collected DNA from 2,819 sheep, belonging to 74 breeds sampled from around the world, and assessed the genotype of each animal at nearly 50,000 locations across the genome. Our results show that sheep breeds have maintained high levels of genetic diversity, in contrast to other domestic animals such as dogs. We also show that particular regions of the genome contain strong evidence for accelerated change in response to artificial selection. The most prominent example was identified in response to breeding for the absence of horns, a trait now common across many modern breeds. Furthermore, we demonstrate that other genomic regions under selection in sheep contain genes controlling pigmentation, reproduction, and body size.

Epilepsy caused by an abnormal alternative splicing with dosage effect of the SV2A gene in a chicken model

Photosensitive reflex epilepsy is caused by the combination of an individual's enhanced sensitivity with relevant light stimuli, such as stroboscopic lights or video games. This is the most common reflex epilepsy in humans; it is characterized by the photoparoxysmal response, which is an abnormal electroencephalographic reaction, and seizures triggered by intermittent light stimulation. Here, by using genetic mapping, sequencing and functional analyses, we report that a mutation in the acceptor site of the second intron of SV2A (the gene encoding synaptic vesicle glycoprotein 2A) is causing photosensitive reflex epilepsy in a unique vertebrate model, the Fepi chicken strain, a spontaneous model where the neurological disorder is inherited as an autosomal recessive mutation. This mutation causes an aberrant splicing event and significantly reduces the level of SV2A mRNA in homozygous carriers. Levetiracetam, a second generation antiepileptic drug, is known to bind SV2A, and SV2A knock-out mice develop seizures soon after birth and usually die within three weeks. The Fepi chicken survives to adulthood and responds to levetiracetam, suggesting that the low-level expression of SV2A in these animals is sufficient to allow survival, but does not protect against seizures. Thus, the Fepi chicken model shows that the role of the SV2A pathway in the brain is conserved between birds and mammals, in spite of a large phylogenetic distance. The Fepi model appears particularly useful for further studies of physiopathology of reflex epilepsy, in comparison with induced models of epilepsy in rodents. Consequently, SV2A is a very attractive candidate gene for analysis in the context of both mono- and polygenic generalized epilepsies in humans.

Sparse PLS discriminant analysis: biologically relevant feature selection and graphical displays for multiclass problems

Background

Variable selection on high throughput biological data, such as gene expression or single nucleotide polymorphisms (SNPs), becomes inevitable to select relevant information and, therefore, to better characterize diseases or assess genetic structure. There are different ways to perform variable selection in large data sets. Statistical tests are commonly used to identify differentially expressed features for explanatory purposes, whereas Machine Learning wrapper approaches can be used for predictive purposes. In the case of multiple highly correlated variables, another option is to use multivariate exploratory approaches to give more insight into cell biology, biological pathways or complex traits.

Results

A simple extension of a sparse PLS exploratory approach is proposed to perform variable selection in a multiclass classification framework.

Conclusions

sPLS-DA has a classification performance similar to other wrapper or sparse discriminant analysis approaches on public microarray and SNP data sets. More importantly, sPLS-DA is clearly competitive in terms of computational efficiency and superior in terms of interpretability of the results via valuable graphical outputs. sPLS-DA is available in the R package mixOmics, which is dedicated to the analysis of large biological data sets.

Linkage disequilibrium interval mapping of quantitative trait loci

BACKGROUND

For many years gene mapping studies have been performed through linkage analyses based on pedigree data. Recently, linkage disequilibrium methods based on unrelated individuals have been advocated as powerful tools to refine estimates of gene location. Many strategies have been proposed to deal with simply inherited disease traits. However, locating quantitative trait loci is statistically more challenging and considerable research is needed to provide robust and computationally efficient methods.

RESULTS

Under a three-locus Wright-Fisher model, we derived approximate expressions for the expected haplotype frequencies in a population. We considered haplotypes comprising one trait locus and two flanking markers. Using these theoretical expressions, we built a likelihood-maximization method, called HAPim, for estimating the location of a quantitative trait locus. For each postulated position, the method only requires information from the two flanking markers. Over a wide range of simulation scenarios it was found to be more accurate than a two-marker composite likelihood method. It also performed as well as identity by descent methods, whilst being valuable in a wider range of populations.

CONCLUSION

Our method makes efficient use of marker information, and can be valuable for fine mapping purposes. Its performance is increased if multiallelic markers are available. Several improvements can be developed to account for more complex evolution scenarios or provide robust confidence intervals for the location estimates.