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Detection of Selection Signatures in Piemontese and Marchigiana Cattle, Two Breeds with Similar Production Aptitudes but Differe

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Detection of Selection Signatures in Piemontese and Marchigiana Cattle, Two Breeds with Similar Production Aptitudes but Differe et al. Genetics Selection Evolution Sorbolini (2015) 47:52 Genetics DOI 10.1186/s12711-015-0128-2 Selection Evolution RESEARCH ARTICLE Open Access Detection of selection signatures in Piemontese and Marchigiana cattle, two breeds with similar production aptitudes but different selection histories Silvia Sorbolini1*, Gabriele Marras1, Giustino Gaspa1, Corrado Dimauro1, Massimo Cellesi1, Alessio Valentini2 and Nicolò PP Macciotta1 Abstract Background: Domestication and selection are processes that alter the pattern of within- and between-population genetic variability. They can be investigated at the genomic level by tracing the so-called selection signatures. Recently, sequence polymorphisms at the genome-wide level have been investigated in a wide range of animals. A common approach to detect selection signatures is to compare breeds that have been selected for different breeding goals (i.e. dairy and beef cattle). However, genetic variations in different breeds with similar production aptitudes and similar phenotypes can be related to differences in their selection history. Methods: In this study, we investigated selection signatures between two Italian beef cattle breeds, Piemontese and Marchigiana, using genotyping data that was obtained with the Illumina BovineSNP50 BeadChip. The comparison was based on the fixation index (Fst), combined with a locally weighted scatterplot smoothing (LOWESS) regression and a control chart approach. In addition, analyses of Fst were carried out to confirm candidate genes. In particular, data were processed using the varLD method, which compares the regional variation of linkage disequilibrium between populations. Results: Genome scans confirmed the presence of selective sweeps in the genomic regions that harbour candidate genes that are known to affect productive traits in cattle such as DGAT1, ABCG2, CAPN3, MSTN and FTO. In addition, several new putative candidate genes (for example ALAS1, ABCB8, ACADS and SOD1) were detected. Conclusions: This study provided evidence on the different selection histories of two cattle breeds and the usefulness of genomic scans to detect selective sweeps even in cattle breeds that are bred for similar production aptitudes. Background have changed the frequency of mutations that affect After domestication, natural and artificial selection have phenotypic traits [3]. Understanding how and where selec- led to different animal strains. During the industrial revo- tion has shaped the patterns of genetic variation remains lution (200 to 250 years ago), these animal strains were ar- one of the most challenging topics in genetics [3]. Thanks tificially clustered into breeds based on their phenotypic to their great phenotypic variability, domestic animals characteristics and the environmental conditions in which offer the opportunity to explore genotype-phenotype rela- they are raised. Animals have been selected for traits that tionships and represent excellent models for studies on are important for various human communities [1, 2]. Do- evolutionary biology [4–6]. According to the theory of mestication and subsequent natural and artificial selection genetic hitch-hiking [7], when the favourable allele of a gene spreads in a population, the sequences that are up- stream and downstream of this gene also undergo an in- * Correspondence: [email protected] crease in frequency until fixation [8]. The integration of 1Dipartimento di Agraria, Sezione di Scienze Zootecniche Università degli Studi di Sassari, 07100 Sassari, Italy disciplines such as quantitative genetics and population Full list of author information is available at the end of the article © 2015 Sorbolini et al. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http:// creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. Sorbolini et al. Genetics Selection Evolution (2015) 47:52 Page 2 of 13 genetics has made the study of species’ variability easier and their interpretation followed the approach of Pintus and more reliable [5]. For example, association and hitch- et al. [23]. In order to confirm the results obtained with hiking mapping allow the identification of quantitative the LOWESS/control chart procedure, we performed an trait nucleotides (QTN) that are responsible for differ- analysis with the varLD software that measures the gen- ences in economically important traits [9]. etic variability between populations by comparing the The recent advances in genetics and statistical method- differences in regional LD patterns [31]. ologies contribute to the characterization of biological di- versity, animal domestication, and breed development [4]. Methods In particular, the availability of high-density single nucleo- Samples, genotyping and data editing tide polymorphism (SNP) panels provides an exciting op- A total of 364 Piemontese and 410 Marchigiana bulls were portunity to identify genomic regions under selection [10]. sampled for this study. Animals were genotyped using the The abundance of SNPs throughout the genome makes Illumina Infinium Bovine BeadChip that includes 54 001 these genetic makers particularly suitable for the detection SNPs (http://www.illumina.com). SNPs that were not lo- of genomic regions where a reduction in heterozygosity cated on the 29 autosomes of the Bos taurus UMD 3.1/bos- (selective sweep) occurred [11]. In mammals, several Tau6 build of the bovine genome assembly were excluded. methods based on the measurement of differences in allele Quality controls removed SNPs that were monomorphic in frequency, and on linkage disequilibrium (LD) patterns both breeds and that had more than 2.5% missing data or a and haplotype structures have been used to examine se- minor allele frequency less than 1%. Missing data were re- lective sweeps or patterns of diversity [12–16]. In popula- placed with the most frequent allele at that specific locus tion genetics, the most commonly used statistics to detect for each breed. After quality control, 43 009 SNPs were signatures of selection are the calculation of the fixation retained for the analysis. index (Fst) [17], composite log likelihood (CLL) [18] and extended haplotype homozygosity (EHH) [19]. Recently, Detection of relevant signals using the LOWESS/control in humans, intra- and inter-population genetic diversity chart procedure was investigated by comparing continuous stretches of First, allele frequencies and observed and expected het- diploid DNA sequences that are identical on each strand erozygosities were calculated separately for each breed. [20] and that are called runs of homozygosity (ROH) Then, total allele frequencies at each locus, fp and fq, [21].These methods can help to identify genomic regions were calculated by considering all animals as a single that have undergone selection (natural or artificial) and to population as follows: detect associations between traits of economic interest ½ðÞþðÞ and genes present in these regions. In cattle, most studies ¼ f Pm 2nPm f Ma 2nMa ; f p ðÞþ have compared breeds with different production aptitudes, 2 nPm nMa for example dairy and beef breeds [18, 22, 23], in order to where fPm and fMa and nPm and nMa areallelefrequencies detect signatures of selective breeding [22, 24, 25]. As and number of individuals in the Piemontese and March- expected, these comparisons highlighted genes that have a igiana breeds, respectively. huge effect on phenotypes (i.e. DGAT1 or ABCG2 for ¼ − : dairy and MSTN for beef cattle, respectively). However, f q 1 f p there is a wide range of bovine breeds with different selec- tion histories some of which have the same production Expected heterozygosity in the populations (Hs)and aptitudes. For example, some dairy breeds have been se- overall heterozygosity (Ht) were calculated. Finally, Fst was lected mainly to improve milk yield, whereas other breeds calculated according to Weir and Cockerham [30] as: have been privileged for milk composition or functional ðÞHt−Hs traits. Therefore, studies that compare breeds with similar Fst ¼ : H production aptitudes [13, 26–29] can be considered highly t informative to investigate their genetic variability for Fst computation generates Fst data patterns along the breeding purposes. Here, we studied the genetic differ- chromosome that are usually highly variable and thus ences between two Italian beef cattle breeds, Piemontese difficult to interpret. and Marchigiana. These two populations exhibit similar In this study, in order to smooth Fst data patterns and to morphological and productive traits, but have different simplify graphical presentations, values were fitted with a origins and selection histories. We analyzed the genetic locally weighted scatterplot smoothing (LOWESS) regres- variation between these two breeds that were genotyped sion [32], separately for each autosome, using the PROC withtheIlluminaBovineSNP50BeadChipassay(http:// LOESS procedure in SAS 9.2 (SAS/STAT® Software version www.illumina.com) by comparing the SNP allele fre- 9.2, SAS Institute, Inc., Cary, NC, USA) as suggested by quencies. We used smoothed fixation indices (Fst)[30] Pintus et al. [23]. The number of local regressions varied Sorbolini et al. Genetics Selection Evolution (2015) 47:52 Page
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