Construction of a large collection of small genome variations in French dairy and beef breeds using whole-genome sequences

Boussaha, Mekki; Michot, Pauline; Letaïef, Rabia; Hozé, Chris; Fritz, Sébastien; Grohs, Cécile; Esquerré, Diane; Duchesne, Amandine; Philippe, Romain; Blanquet, Véronique; Phocas, Florence; Floriot, Sandrine; Rocha, Dominique; Klopp, Christophe; Capitan, Aurélien; Boichard, Didier

doi:10.1186/s12711-016-0268-z

Cited by 19 publications

(27 citation statements)

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“…On average, depending on the breed, between 60 and 73% of the QTL variants that we detected in the GWAS were located in genes; this is about twice as high as the percentage of genic variants at the whole-genome scale (35%; [ 15 ]). The most significant variants were located in 49 distinct genes, of which 22 were of particular interest, either because they were found in more than one breed or associated with several traits, or because they were previously described as influencing milk composition.…”

Section: Discussionmentioning

confidence: 99%

“…The protocol used was defined in the “1000 bull genomes” consortium [ 9 ]. Whole-genomes of all individuals were used for 2 × 100 bp paired-end sequencing using Illumina sequencing-by-synthesis technology and sequence reads were further filtered for quality and subsequently aligned to the UMD3.1 reference sequence, as previously described [ 9 , 15 ]. Small genomic variations (SNPs and InDel) were detected using SAMtools 0.0.18 [ 16 ].…”

Section: Methodsmentioning

confidence: 99%

“…Small genomic variations (SNPs and InDel) were detected using SAMtools 0.0.18 [ 16 ]. Raw variants were further filtered to produce 27,754,235 autosomal variants [ 15 ]. Filtered variants were subsequently annotated with the Ensembl variant effect predictor (VEP) pipeline v81 [ 17 ] and effect of the amino acid changes was predicted using the SIFT tool [ 18 ].…”

Section: Methodsmentioning

confidence: 99%

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Within-breed and multi-breed GWAS on imputed whole-genome sequence variants reveal candidate mutations affecting milk protein composition in dairy cattle

et al. 2017

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BackgroundGenome-wide association studies (GWAS) were performed at the sequence level to identify candidate mutations that affect the expression of six major milk proteins in Montbéliarde (MON), Normande (NOR), and Holstein (HOL) dairy cattle. Whey protein (α-lactalbumin and β-lactoglobulin) and casein (αs1, αs2, β, and κ) contents were estimated by mid-infrared (MIR) spectrometry, with medium to high accuracy (0.59 ≤ R2 ≤ 0.92), for 848,068 test-day milk samples from 156,660 cows in the first three lactations. Milk composition was evaluated as average test-day measurements adjusted for environmental effects. Next, we genotyped a subset of 8080 cows (2967 MON, 2737 NOR, and 2306 HOL) with the BovineSNP50 Beadchip. For each breed, genotypes were first imputed to high-density (HD) using HD single nucleotide polymorphisms (SNPs) genotypes of 522 MON, 546 NOR, and 776 HOL bulls. The resulting HD SNP genotypes were subsequently imputed to the sequence level using 27 million high-quality sequence variants selected from Run4 of the 1000 Bull Genomes consortium (1147 bulls). Within-breed, multi-breed, and conditional GWAS were performed.ResultsThirty-four distinct genomic regions were identified. Three regions on chromosomes 6, 11, and 20 had very significant effects on milk composition and were shared across the three breeds. Other significant effects, which partially overlapped across breeds, were found on almost all the autosomes. Multi-breed analyses provided a larger number of significant genomic regions with smaller confidence intervals than within-breed analyses. Combinations of within-breed, multi-breed, and conditional analyses led to the identification of putative causative variants in several candidate genes that presented significant protein–protein interactions enrichment, including those with previously described effects on milk composition (SLC37A1, MGST1, ABCG2, CSN1S1, CSN2, CSN1S2, CSN3, PAEP, DGAT1, AGPAT6) and those with effects reported for the first time here (ALPL, ANKH, PICALM).ConclusionsGWAS applied to fine-scale phenotypes, multiple breeds, and whole-genome sequences seems to be effective to identify candidate gene variants. However, although we identified functional links between some candidate genes and milk phenotypes, the causality between candidate variants and milk protein composition remains to be demonstrated. Nevertheless, the identification of potential causative mutations that underlie milk protein composition may have immediate applications for improvements in cheese-making.Electronic supplementary materialThe online version of this article (doi:10.1186/s12711-017-0344-z) contains supplementary material, which is available to authorized users.

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Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

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Within-breed and multi-breed GWAS on imputed whole-genome sequence variants reveal candidate mutations affecting milk protein composition in dairy cattle

et al. 2017

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“…Most whole-genome sequences used in this study were already available in our laboratory (see [ 19 ] for more details), and thus no animal experimentation was necessary for this study. A small part of our dataset was generated from 23 genomic DNA samples that were obtained from muscle tissue collected at commercial slaughterhouses.…”

Section: Methodsmentioning

confidence: 99%

Identification of copy number variation in French dairy and beef breeds using next-generation sequencing

et al. 2017

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BackgroundCopy number variations (CNV) are known to play a major role in genetic variability and disease pathogenesis in several species including cattle. In this study, we report the identification and characterization of CNV in eight French beef and dairy breeds using whole-genome sequence data from 200 animals. Bioinformatics analyses to search for CNV were carried out using four different but complementary tools and we validated a subset of the CNV by both in silico and experimental approaches. ResultsWe report the identification and localization of 4178 putative deletion-only, duplication-only and CNV regions, which cover 6% of the bovine autosomal genome; they were validated by two in silico approaches and/or experimentally validated using array-based comparative genomic hybridization and single nucleotide polymorphism genotyping arrays. The size of these variants ranged from 334 bp to 7.7 Mb, with an average size of ~ 54 kb. Of these 4178 variants, 3940 were deletions, 67 were duplications and 171 corresponded to both deletions and duplications, which were defined as potential CNV regions. Gene content analysis revealed that, among these variants, 1100 deletions and duplications encompassed 1803 known genes, which affect a wide spectrum of molecular functions, and 1095 overlapped with known QTL regions.ConclusionsOur study is a large-scale survey of CNV in eight French dairy and beef breeds. These CNV will be useful to study the link between genetic variability and economically important traits, and to improve our knowledge on the genomic architecture of cattle.Electronic supplementary materialThe online version of this article (doi:10.1186/s12711-017-0352-z) contains supplementary material, which is available to authorized users.

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“…The sequencing of important ancestors of many cattle breeds revealed millions of sequence variants that are polymorphic in dairy and beef populations [1][2][3][4]. In order to compile an exhaustive catalog of polymorphic sites that segregate in Bos taurus, the 1000 Bull Genomes consortium was established [5,6].…”

Section: Introductionmentioning

confidence: 99%

Accurate sequence variant genotyping in cattle using variation-aware genome graphs

Crysnanto

Wurmser

Pausch

2018

Preprint

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Background:The genotyping of sequence variants typically involves as a first step the alignment of sequencing reads to a linear reference genome. Because a linear reference genome represents only a small fraction of sequence variation within a species, reference allele bias may occur at highly polymorphic or diverged regions of the genome. Graph-based methods facilitate to compare sequencing reads to a variation-aware genome graph that incorporates a collection of non-redundant DNA sequences that segregate within a species.We compared accuracy and sensitivity of graph-based sequence variant genotyping using the Graphtyper software to two widely used methods, i.e., GATK and SAMtools, that rely on linear reference genomes using whole-genomes sequencing data of 49 Original Braunvieh cattle. Results:We discovered 21,140,196, 20,262,913 and 20,668,459 polymorphic sites using GATK, Graphtyper, and SAMtools, respectively. Comparisons between sequence variant and microarray-derived genotypes showed that Graphtyper outperformed both GATK and SAMtools in terms of genotype concordance, non-reference sensitivity, and non-reference discrepancy. The sequence variant genotypes that were obtained using Graphtyper had the lowest number of mendelian inconsistencies for both SNPs and indels in nine sire-son pairs with sequence data. Genotype phasing and imputation using the Beagle software improved the quality of the sequence variant genotypes for all tools evaluated particularly for animals that have been sequenced at low coverage. Following imputation, the concordance between sequence-and microarray-derived genotypes was almost identical for the three methods evaluated, i.e., 99.32, 99.46, and 99.24 % for GATK, Graphtyper, and SAMtools, respectively. Variant filtration based on commonly used criteria improved the genotype concordance slightly but it also decreased sensitivity. Graphtyper required considerably more computing resources than SAMtools but it required less than GATK.Conclusions: Sequence variant genotyping using Graphtyper is accurate, sensitive and computationally feasible in cattle. Graph-based methods enable sequence variant genotyping from variation-aware reference genomes that may incorporate cohort-specific sequence variants which is not possible with the current implementations of state-of-the-art methods that rely on linear reference genomes.

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Construction of a large collection of small genome variations in French dairy and beef breeds using whole-genome sequences

Cited by 19 publications

References 45 publications

Within-breed and multi-breed GWAS on imputed whole-genome sequence variants reveal candidate mutations affecting milk protein composition in dairy cattle

Within-breed and multi-breed GWAS on imputed whole-genome sequence variants reveal candidate mutations affecting milk protein composition in dairy cattle

Identification of copy number variation in French dairy and beef breeds using next-generation sequencing

Accurate sequence variant genotyping in cattle using variation-aware genome graphs

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