Bert Dibbits

Genome‐wide SNP detection in the great tit Parus major using high throughput sequencing

Identifying genes that underlie ecological traits will open exiting possibilities to study gene–environment interactions in shaping phenotypes and in measuring natural selection on genes. Evolutionary ecology has been pursuing these objectives for decades, but they come into reach now that next generation sequencing technologies have dramatically lowered the costs to obtain the genomic sequence information that is currently lacking for most ecologically important species. Here we describe how we generated over 2 billion basepairs of novel sequence information for an ecological model species, the great tit Parus major. We used over 16 million short sequence reads for the de novo assembly of a reference sequence consisting of 550 000 contigs, covering 2.5% of the genome of the great tit. This reference sequence was used as the scaffold for mapping of the sequence reads, which allowed for the detection of over 20 000 novel single nucleotide polymorphisms. Contigs harbouring 4272 of the single nucleotide polymorphisms could be mapped to a unique location on the recently sequenced zebra finch genome. Of all the great tit contigs, significantly more were mapped to the microchromosomes than to the intermediate and the macrochromosomes of the zebra finch, indicating a higher overall level of sequence conservation on the microchromosomes than on the other types of chromosomes. The large number of great tit contigs that can be aligned to the zebra finch genome shows that this genome provides a valuable framework for large scale genetics, e.g. QTL mapping or whole genome association studies, in passerines.

Application of massive parallel sequencing to whole genome SNP discovery in the porcine genome

BackgroundAlthough the Illumina 1 G Genome Analyzer generates billions of base pairs of sequence data, challenges arise in sequence selection due to the varying sequence quality. Therefore, in the framework of the International Porcine SNP Chip Consortium, this pilot study aimed to evaluate the impact of the quality level of the sequenced bases on mapping quality and identification of true SNPs on a large scale.ResultsDNA pooled from five animals from a commercial boar line was digested with Dra I; 150–250-bp fragments were isolated and end-sequenced using the Illumina 1 G Genome Analyzer, yielding 70,348,064 sequences 36-bp long. Rules were developed to select sequences, which were then aligned to unique positions in a reference genome. Sequences were selected based on quality, and three thresholds of sequence quality (SQ) were compared. The highest threshold of SQ allowed identification of a larger number of SNPs (17,489), distributed widely across the pig genome. In total, 3,142 SNPs were validated with a success rate of 96%. The correlation between estimated minor allele frequency (MAF) and genotyped MAF was moderate, and SNPs were highly polymorphic in other pig breeds. Lowering the SQ threshold and maintaining the same criteria for SNP identification resulted in the discovery of fewer SNPs (16,768), of which 259 were not identified using higher SQ levels. Validation of SNPs found exclusively in the lower SQ threshold had a success rate of 94% and a low correlation between estimated MAF and genotyped MAF. Base change analysis suggested that the rate of transitions in the pig genome is likely to be similar to that observed in humans. Chromosome X showed reduced nucleotide diversity relative to autosomes, as observed for other species.ConclusionLarge numbers of SNPs can be identified reliably by creating strict rules for sequence selection, which simultaneously decreases sequence ambiguity. Selection of sequences using a higher SQ threshold leads to more reliable identification of SNPs. Lower SQ thresholds can be used to guarantee sufficient sequence coverage, resulting in high success rate but less reliable MAF estimation. Nucleotide diversity varies between porcine chromosomes, with the X chromosome showing less variation as observed in other species.

The design and cross-population application of a genome-wide SNP chip for the great tit Parus major

The vast amount of phenotypic information collected in some wild animal populations makes them extremely valuable for unravelling the genetics of ecologically important traits and understanding how populations adapt to changes in their environment. Next generation sequencing has revolutionized the development of large marker panels in species previously lacking genomic resources. In this study, a unique genomics toolkit was developed for the great tit (Parus major), a model species in ecology and behavioural biology. This toolkit consists of nearly 100 000 SNPs, over 250 million nucleotides of assembled genomic DNA and more than 80 million nucleotides of assembled expressed sequences. A SNP chip with 9193 SNP markers expected to be spaced evenly along the great tit genome was used to genotype 4702 birds from two of the most intensively studied natural vertebrate populations [Wytham Woods/Bagley Woods (United Kingdom) and de Hoge Veluwe/Westerheide (The Netherlands)]. We show that (i) SNPs identified in either of the two populations have a high genotyping success in the other population, (ii) the minor allele frequencies of the SNPs are highly correlated between the two populations and (iii) despite this high correlation, a large number of SNPs display significant differentiation (FST) between the populations, with an overrepresentation of genes involved in cardiovascular development close to these SNPs. The developed resources provide the basis for unravelling the genetics of important traits in many long‐term studies of great tits. More generally, the protocols and pitfalls encountered will be of use for those developing similar resources.

SNP marker detection and genotyping in tilapia

We have generated a unique resource consisting of nearly 175 000 short contig sequences and 3569 SNP markers from the widely cultured GIFT (Genetically Improved Farmed Tilapia) strain of Nile tilapia (Oreochromis niloticus). In total, 384 SNPs were selected to monitor the wider applicability of the SNPs by genotyping tilapia individuals from different strains and different geographical locations. In all strains and species tested (O. niloticus, O. aureus and O. mossambicus), the genotyping assay was working for a similar number of SNPs (288–305 SNPs). The actual number of polymorphic SNPs was, as expected, highest for individuals from the GIFT population (255 SNPs). In the individuals from an Egyptian strain and in individuals caught in the wild in the basin of the river Volta, 197 and 163 SNPs were polymorphic, respectively. A pairwise calculation of Nei’s genetic distance allowed the discrimination of the individual strains and species based on the genotypes determined with the SNP set. We expect that this set will be widely applicable for use in tilapia aquaculture, e.g. for pedigree reconstruction. In addition, this set is currently used for assaying the genetic diversity of native Nile tilapia in areas where tilapia is, or will be, introduced in aquaculture projects. This allows the tracing of escapees from aquaculture and the monitoring of effects of introgression and hybridization.

Association of bovine β‐casein protein variant I with milk production and milk protein composition

The aim of this study was to detect new polymorphisms in the bovine β-casein (β-CN) gene and to evaluate association of (new) β-CN protein variants with milk production traits and milk protein composition. Screening of the β-CN gene in genomic DNA from 72 Holstein Friesian (HF) bulls resulted in detection of 19 polymorphisms and revealed the presence of β-CN protein variant I in the Dutch HF population. Studies of association of β-CN protein variants with milk composition usually do not discriminate protein variant I from variant A2. Association of β-CN protein variants with milk composition was studied in 1857 first-lactation HF cows and showed that associations of protein variants A2 and I were quite different for several traits. β-CN protein variant I was significantly associated with protein percentage and protein yield, and with αs1 -casein (αs1 -CN), αs2 -casein (αs2 -CN), κ-casein (κ-CN), α-lactalbumin (α-LA), β-lactoglobulin (β-LG), casein index and casein yield. Inferring β-κ-CN haplotypes showed that β-CN protein variant I occurred only with κ-CN variant B. Consequently, associations of β-κ-CN haplotype IB with protein percentage, κ-CN, α-LA, β-LG and casein index are likely resulting from associations of κ-CN protein variant B, while associations of β-κ-CN haplotype IB with αs1 -CN and αs2 -CN seem to be resulting from associations of β-CN variant I.

Structural variation in the chicken genome identified by paired-end next-generation DNA sequencing of reduced representation libraries

BackgroundVariation within individual genomes ranges from single nucleotide polymorphisms (SNPs) to kilobase, and even megabase, sized structural variants (SVs), such as deletions, insertions, inversions, and more complex rearrangements. Although much is known about the extent of SVs in humans and mice, species in which they exert significant effects on phenotypes, very little is known about the extent of SVs in the 2.5-times smaller and less repetitive genome of the chicken.ResultsWe identified hundreds of shared and divergent SVs in four commercial chicken lines relative to the reference chicken genome. The majority of SVs were found in intronic and intergenic regions, and we also found SVs in the coding regions. To identify the SVs, we combined high-throughput short read paired-end sequencing of genomic reduced representation libraries (RRLs) of pooled samples from 25 individuals and computational mapping of DNA sequences from a reference genome.ConclusionWe provide a first glimpse of the high abundance of small structural genomic variations in the chicken. Extrapolating our results, we estimate that there are thousands of rearrangements in the chicken genome, the majority of which are located in non-coding regions. We observed that structural variation contributes to genetic differentiation among current domesticated chicken breeds and the Red Jungle Fowl. We expect that, because of their high abundance, SVs might explain phenotypic differences and play a role in the evolution of the chicken genome. Finally, our study exemplifies an efficient and cost-effective approach for identifying structural variation in sequenced genomes.

The imprinted gene DIO3 is a candidate gene for litter size in pigs.

Genomic imprinting is an important epigenetic phenomenon, which on the phenotypic level can be detected by the difference between the two heterozygote classes of a gene. Imprinted genes are important in both the development of the placenta and the embryo, and we hypothesized that imprinted genes might be involved in female fertility traits. We therefore performed an association study for imprinted genes related to female fertility traits in two commercial pig populations. For this purpose, 309 SNPs in fifteen evolutionary conserved imprinted regions were genotyped on 689 and 1050 pigs from the two pig populations. A single SNP association study was used to detect additive, dominant and imprinting effects related to four reproduction traits; total number of piglets born, the number of piglets born alive, the total weight of the piglets born and the total weight of the piglets born alive. Several SNPs showed significant () additive and dominant effects and one SNP showed a significant imprinting effect. The SNP with a significant imprinting effect is closely linked to DIO3, a gene involved in thyroid metabolism. The imprinting effect of this SNP explained approximately 1.6% of the phenotypic variance, which corresponded to approximately 15.5% of the additive genetic variance. In the other population, the imprinting effect of this QTL was not significant (), but had a similar effect as in the first population. The results of this study indicate a possible association between the imprinted gene DIO3 and female fertility traits in pigs.

Mapping carcass and meat quality QTL on Sus scrofa chromosome 2 in commercial finishing pigs.

Quantitative trait loci (QTL) affecting carcass and meat quality located on SSC2 were identified using variance component methods. A large number of traits involved in meat and carcass quality was detected in a commercial crossbred population: 1855 pigs sired by 17 boars from a synthetic line, which where homozygous (A/A) for IGF2. Using combined linkage and linkage disequilibrium mapping (LDLA), several QTL significantly affecting loin muscle mass, ham weight and ham muscles (outer ham and knuckle ham) and meat quality traits, such as Minolta-L* and -b*, ultimate pH and Japanese colour score were detected. These results agreed well with previous QTL-studies involving SSC2. Since our study is carried out on crossbreds, different QTL may be segregating in the parental lines. To address this question, we compared models with a single QTL-variance component with models allowing for separate sire and dam QTL-variance components. The same QTL were identified using a single QTL variance component model compared to a model allowing for separate variances with minor differences with respect to QTL location. However, the variance component method made it possible to detect QTL segregating in the paternal line (e.g. HAMB), the maternal lines (e.g. Ham) or in both (e.g. pHu). Combining association and linkage information among haplotypes improved slightly the significance of the QTL compared to an analysis using linkage information only.

A nonsense mutation in B3GALNT2 is concordant with hydrocephalus in Friesian horses.

BackgroundHydrocephalus in Friesian horses is a developmental disorder that often results in stillbirth of affected foals and dystocia in dams. The occurrence is probably related to a founder effect and inbreeding in the population. The aim of our study was to find genomic associations, to investigate the mode of inheritance, to allow a DNA test for hydrocephalus in Friesian horses to be developed. In case of a monogenic inheritance we aimed to identify the causal mutation.ResultsA genome-wide association study of hydrocephalus in 13 cases and 69 controls using 29,720 SNPs indicated the involvement of a region on ECA1 (P <1.68 × 10−6). Next generation DNA sequence analysis of 4 cases and 6 controls of gene exons within the region revealed a mutation in β-1,3-N-acetylgalactosaminyltransferase 2 (B3GALNT2) as the likely cause of hydrocephalus in Friesian horses. The nonsense mutation XM_001491545 c.1423C>T corresponding to XP_001491595 p.Gln475* was identical to a B3GALNT2 mutation identified in a human case of muscular dystrophy-dystroglycanopathy with hydrocephalus. All 16 available cases and none of the controls were homozygous for the mutation, and all 17 obligate carriers (= dams of cases) were heterozygous. A random sample of the Friesian horse population (n = 865) was tested for the mutation in a commercial laboratory. One-hundred and forty-seven horses were carrier and 718 horses were homozygous for the normal allele; the estimated allele frequency in the Friesian horse population is 0.085.ConclusionsHydrocephalus in Friesian horses has an autosomal recessive mode of inheritance. A nonsense mutation XM_001491545 c.1423C>T corresponding to XP_001491595 p.Gln475* in B3GALNT2 (1:75,859,296–75,909,376) is concordant with hydrocephalus in Friesian horses. Application of a DNA test in the breeding programme will reduce the losses caused by hydrocephalus in the Friesian horse population.

CNVs are associated with genomic architecture in a songbird

BackgroundUnderstanding variation in genome structure is essential to understand phenotypic differences within populations and the evolutionary history of species. A promising form of this structural variation is copy number variation (CNV). CNVs can be generated by different recombination mechanisms, such as non-allelic homologous recombination, that rely on specific characteristics of the genome architecture. These structural variants can therefore be more abundant at particular genes ultimately leading to variation in phenotypes under selection. Detailed characterization of CNVs therefore can reveal evolutionary footprints of selection and provide insight in their contribution to phenotypic variation in wild populations.ResultsHere we use genotypic data from a long-term population of great tits (Parus major), a widely studied passerine bird in ecology and evolution, to detect CNVs and identify genomic features prevailing within these regions. We used allele intensities and frequencies from high-density SNP array data from 2,175 birds. We detected 41,029 CNVs concatenated into 8,008 distinct CNV regions (CNVRs). We successfully validated 93.75% of the CNVs tested by qPCR, which were sampled at different frequencies and sizes. A mother-daughter family structure allowed for the evaluation of the inheritance of a number of these CNVs. Thereby, only CNVs with 40 probes or more display segregation in accordance with Mendelian inheritance, suggesting a high rate of false negative calls for smaller CNVs. As CNVRs are a coarse-grained map of CNV loci, we also inferred the frequency of coincident CNV start and end breakpoints. We observed frequency-dependent enrichment of these breakpoints at homologous regions, CpG sites and AT-rich intervals. A gene ontology enrichment analyses showed that CNVs are enriched in genes underpinning neural, cardiac and ion transport pathways.ConclusionGreat tit CNVs are present in almost half of the genes and prominent at repetitive-homologous and regulatory regions. Although overlapping genes under selection, the high number of false negatives make neutrality or association tests on CNVs detected here difficult. Therefore, CNVs should be further addressed in the light of their false negative rate and architecture to improve the comprehension of their association with phenotypes and evolutionary history.