CNV DETECTION AND ASSOCIATION STUDIES IN THE BROWN SWISS CATTLE BREED

Sintesi \u2013 Italiano Gli scopi, i materiali, i metodi usati, i risultati e le conclusioni dei tre studi sono organizzati in tre capitoli. La sintesi generale dei tre studi e quindi divisa in base a questi tre capitoli. Capitolo 1 La determinazione dei \u201ccopy number variants\u201d (CNV) \ue8 fondamentale per la valutazione dei tratti genomici in diverse specie in quanto rappresentano una fonte principale della variabilit\ue0 genetica, influenzando l\u2019espressione genica, la variabilit\ue0 fenotipica, la adattabilit\ue0 e la predisposizione all\u2019insorgenza di malattie. Lo scopo di questo studio \ue8 stato quello di ottenere una mappa genomica di CNV utilizzando i dati ottenuti dall\u2019Illumina Bovine SNP50 BeadChip di 651 tori di razza Bruna Italiana. Per l\u2019identificazione dei CNV e delle regioni CNV (CNVR) sono stati usati i software PennCNV e SVS7 (Golden Helix). Sono stati identificati un totale di 5,099 e 1,289 CNVs con i software PennCNV ed SVS7 rispettivamente. Questi CNV sono stati raggruppati a livello di popolazione in 1,101 (220 delezioni, 774 duplicazioni e 107 complex) e 277 (185 delezioni, 56 duplicazioni e 36 complex) CNVR. Dieci dei CNVR selezionati sono stati validati sperimentalmente attraverso qPCR. La GO e la pathway analysis effettuate hanno identificato i geni (corretti per la false discovery rate) localizzati nelle CNVR e correlati a diversi processi biologici, componenti cellulari, funzioni metaboliche e vie metaboliche. Tra questi, sono stati identificati i geni FCGR2B, PPARalpha, KATNAL1, DNAJC15, PTK2, TG, STAT family, NPM1, GATA2, LMF1 e ECHS1, gi\ue0 noti in letteratura, per la loro associazione con diversi caratteri quantitativi nei bovinia. Sebbene ci sia una variabilit\ue0 nell\u2019identificazione dei CNVR attraverso l\u2019utilizzo di diversi metodi e piattaforme, questo studio ha permesso l\u2019identificazione dei CNVR nella Bruna Italiana, sovrapponendo quelli gi\ue0 identificati in altre razze e identificandone dei nuovi, producendo quindi nuove conoscenze per gli studi di associazione con caratteri quantitativi di interesse nei bovini. Capitolo 2 Scoprire variazioni genetiche come i Copy Number Variants (CNVs) nei bovini, fornisce l\u2019opportinit\ue0 di studiare la loro associazione con caratteri quantitativi. I CNVs sono sequenze di DNA di lunghezza 50 bp fino a diverse Mb, che possono variare in numero di copie rispetto ad un genoma di riferimento. Lo scopo di questo studio \ue8 stato quello di identificare i CNVs in 1,410 campioni di razza Bruna Svizzera usando informazioni derivanti dall\u2019 Illumina Bovine HD SNP chip, che include 777,962 SNPs. Dopo uno stringente controllo di qualit\ue0, i CNVs sono stati identificati con i software Golden Helix SVS 8.3.1 (SVS) e PennCNV e sono stati raggruppati in regioni CNV (CNVRs) a livello di popolazione (i.e. CNVs sovrapposti) utilizzando il software BEDTools. I CNVR comuni ai due software sono stati definiti come regioni consensus. I geni all\u2019interno delle CNVR consensus sono stati annotati con un\u2019analisi GO utilizzando DAVID Bioinformatics Resources 6.7. Per poter validare i risultati, sono state eseguite PCR quantitative su 15 CNVR selezionate. Con il software SVS sono stati identificati 25,030 CNVs successivamente raggruppati in 398 CNVR, che comprendevano 30 duplicazioni, 344 delezioni e 24 complex CNVR (che contenevano sia duplicazioni che delezioni) coprendo il 3.92% del genoma bovino. Il software PennCNV ha identificato 62,341 CNV, corrispondenti a 5,578 CNVRs che comprendevano 2,638 duplicazioni, 2,404 delezioni e 537 complex CNVR, coprendo il 7.68% del genoma bovino. La lunghezza di queste CNVR variava da 1,244 bp a 1,381,355 bp. Sono state trovate 563 CNVR consensus che coprivano il 2.29% del UMD 3.1 bovine genome assembly. Di queste, 24 erano duplicazioni, 300 erano delezioni e 239 erano CNVR complex. Un totale di 775 official gene IDs sono stati annotati nelle CNVR consensus. Tra i 537 geni con informazioni funzionali, la GO e la pathway analysis \ue8 stata riportata per quelli che clusterizzavano con un p-value < 0.05. Le PCR quantitative hanno validato con successo 14 delle 15 CNVR selezionate. Il risultato di questo studio \ue8 una prima analisi genomica integrale della razza Bruna Svizzera basata sull\u2019Illumina Bovine HD SNP chip su un numero cosi grande di animali che arricchisce la mappa CNV nel genoma bovino. I risultati forniscono inoltre informazioni preziose per successivi studi sui CNV. Infine, i risultati della mappa CNVR sono informativi per i caratteri funzionali, produttivi e sanitari considerati nei programmi di selezione nella razza Bruna Svizzera. Capitolo 3 I Copy Number Variations (CNV) possono essere usati negli studi di associazione per rivelare la base genetica della variazione fenotipica di caratteri quantitativi. I CNV sono sequenze di DNA di 50 bp fino a qualche Mb, che possono variare in numero di copie rispetto ad un genoma di riferimento. Fino ad oggi, nessuno studio di associazione genome-wide (GWAS) con i CNV e caratteri quantitavivi \ue8 stato descritto in una popolazione cosi ampia (cio\ue8 di 1,116 campioni) della razza bovina Bruna Svizzera. Lo scopo di questo studio era quello di eseguire delle GWAS utilizzando i CNV precedentemente mappati, con caratteri funzionali, produttivi e sanitari al fine di valutare il loro impatto sull\u2019allevamento e sulla selezione. Gli studi di associazione con i CNV sono stati effettuati con il software Golden Helix SVS 8.4.4 utilizzando un correlation-trend test model. I geni all\u2019interno dei CNV significativamente associati per ogni carattere sono stati annotati con un\u2019analisi GO usando DAVID Bioinformatics Resources 6.7. Sono stati identificati 56 CNV significativamente associati con uno o pi\uf9 degli otto caratteri valutati. I segnali di associazione pi\uf9 forti erano dati da tre CNV sul cromosoma 12 per il carattere grasso. I CNV associati si sovrappongono con 23 geni diversi, annotati sul Bos taurus genome assembly (UMD3.1).Abstract \u2013 English The aims, material and methods, results and conclusions of the three studies are organized in three different chapters. The general abstract is therefore divided according to these chapters. Chapter 1 The determination of copy number variation (CNV) is very important for the evaluation of genomic traits in several species because they are a major source for the genetic variation, influencing gene expression, phenotypic variation, adaptation and the development of diseases. The aim of this study was to obtain a CNV genome map using the Illumina Bovine SNP50 BeadChip data of 651 bulls of the Italian Brown Swiss breed. PennCNV and SVS7 (Golden Helix) software were used for the detection of the CNVs and Copy Number Variation Regions (CNVRs). A total of 5,099 and 1,289 CNVs were identified with PennCNV and SVS7 software, respectively. These were grouped at the population level into 1101 (220losses, 774 gains, 107 complex) and 277 (185losses, 56 gains and 36 complex) CNVRs. Ten of the selected CNVRs were experimentally validated with a qPCR experiment. The GO and pathway analyses were conducted and they identified genes (false discovery rate corrected) in the CNVR related to biological processes, cellular component, molecular function and metabolic pathways. Among those, we found the FCGR2B, PPARalpha, KATNAL1, DNAJC15, PTK2, TG, STAT family, NPM1, GATA2, LMF1, ECHS1 genes, already known in literature because of their association with various traits in cattle. Although there is variability in the CNVRs detection across methods and platforms, this study allowed the identification of CNVRs in Italian Brown Swiss, overlapping those already detected in other breeds and finding additional ones, thus producing new knowledge for association studies with traits of interest in cattle. Chapter 2 Detecting genetic variation such as Copy Number Variants (CNVs) in cattle provides the opportunity to study their association with quantitative traits. CNVs are DNA sequences of 50 bp up to several Mb long, which can vary in copy number in comparison with a reference genome. The aim of this study was to investigate CNVs in 1,410 samples of the Brown Swiss cattle breed using Illumina Bovine HD SNP chip information, which includes 777,962 SNPs. After stringent quality control, CNVs were called with the Golden Helix SVS 8.3.1 (SVS) and PennCNV software and were summarized to CNV regions (CNVRs) at a population level (i.e. overlapping CNVs), using BEDTools. Additionally, common CNVRs between the two software were set as consensus regions. Genes within consensus CNVRs were annotated with a GO analysis using the DAVID Bioinformatics Resources 6.7. In order to validate these results, quantitative PCRs were executed on 15 selected CNVRs. The SVS software identified 25,030 CNVs summarized to 398 CNVRs, which comprised 30 gains, 344 losses and 24 complex CNVRs (i.e. containing both losses and gains), covering 3.92% of the bovine genome. The PennCNV software identified 6,2341 CNVs summarized to 5,578 CNVRs, which comprised 2,638 gains, 2,404 losses and 537 complex CNVRs, covering 7.68% of the bovine genome. The length of these CNVRs ranged from 1,244 bp to 1,381,355 bp. A total of 563 consensus CNVRs were found covering 2.29 % of the UMD 3.1 bovine genome assembly. Of these, 24 were gains, 300 were losses and 239 were complex CNVRs. A total of 775 official gene IDs were annotated in the consensus CNVRs. Among the 537 genes with functional information, the GO and pathway analysis was reported for those who clustered with a p-value < 0.05. The quantitative PCRs successfully validated 14 (93.33%) of the selected CNVRs. The result of this study is the first comprehensive genomic analysis of the Brown Swiss breed based on the Illumina Bovine HD SNP chip on such a large number of animals that enriches the CNV map in the bovine genome. These findings also provide valuable information for further CNV studies. Finally, the results of the CNVR map delivers new information for functional, health and productive traits considered in selection programs of the Brown Swiss breed. Chapter 3 Copy Number Variation (CNV) can be used in association studies to disclose genetic basis of quantitative traits phenotypic variation. CNVs are DNA sequences of 50 bp up to several Mb long, which can vary in number of copies in comparison with a reference genome. Up to date, no genome-wide association study (GWAS) with CNVs and quantitative traits in such a large Brown Swiss population (i.e. with 1,116 samples) has been described. The purpose of this study was to perform a GWAS using CNVs with functional, health and productive traits and to asses the impact on farming and breeding practices. The CNV \u2013 association studies were performed with the Golden Helix SVS 8.4.4 software using a correlation-trend test model. Genes within significant associated CNVs for each trait were annotated with a GO analysis using the DAVID Bioinformatics Resources 6.7. A total of 56 CNVs were significantly associated with one or more of the eight evaluated traits. The greatest association signals were given by three CNVs on chromosome 12 for the fat yield trait and on BTA23 for udder traits. The associated CNVs overlap with 23 different genes annotated on the Bos taurus genome assembly (UMD3.1)

Mitochondrial DNA genetic diversity in six Italian donkey breeds (Equus asinus)

Donkeys have played an important role in agricultural land practices and in human historical periods of recent past and, still today, are used as a working power in several world areas. The objective of this study was to identify genetic variability in six Italian donkey breeds using mtDNA D-loop. Fifteen haplotypes, grouped in three haplogroups, were identified. The genetic indices were informative and showed a high population genetic variability. The results of AMOVA analyses based on geographic structuring of Italian populations highlighted that the majority of the observed variance is due to differences among samples within breeds. Comparison among Italian haplotypes and mtDNA D-loop sequences belonging to European domestic and Ethiopian donkeys and wild asses, clearly define two clades referred to Nubian lineage. The results can be useful to complement safeguard planes for donkey breeds that are considered to extinction endangered

Identification and validation of copy number variants in Italian Brown Swiss dairy cattle using Illumina Bovine SNP50 Beadchip&#174;

The determination of copy number variation (CNV) is very important for the evaluation of genomic traits in several species because they are a major source for the genetic variation, influencing gene expression, phenotypic variation, adaptation and the development of diseases. The aim of this study was to obtain a CNV genome map using the Illumina Bovine SNP50 BeadChip data of 651 bulls of the Italian Brown Swiss breed. PennCNV and SVS7 (Golden Helix) software were used for the detection of the CNVs and Copy Number Variation Regions (CNVRs). A total of 5,099 and 1,289 CNVs were identified with PennCNV and SVS7 software, respectively. These were grouped at the population level into 1101 (220 losses, 774 gains, 107 complex) and 277 (185 losses, 56 gains and 36 complex) CNVR. Ten of the selected CNVR were experimentally validated with a qPCR experiment. The GO and pathway analyses were conducted and they identified genes (false discovery rate corrected) in the CNVR related to biological processes cellular component, molecular function and metabolic pathways. Among those, we found the FCGR2B, PPAR\u3b1, KATNAL1, DNAJC15, PTK2, TG, STAT family, NPM1, GATA2, LMF1, ECHS1 genes, already known in literature because of their association with various traits in cattle. Although there is variability in the CNVRs detection across methods and platforms, this study allowed the identification of CNVRs in Italian Brown Swiss, overlapping those already detected in other breeds and finding additional ones, thus producing new knowledge for association studies with traits of interest in cattle

Copy number variation in cattle breeds

Detecting all classes of genetic variation in livestock species, such as cattle, is a pre-requisite to studying their association to traits of interest. Copy Number Variations (CNVs) are classes of polymorphic DNA regions including deletions, duplications and insertions of DNA fragments of at least 0.5 kb to several Mb, that are copy number variable when compared to a reference genome. CNVs can be identified using various approaches, among those the SNP array data are low cost, dense coverage, and high throughput. The aim of this study was to obtain a consensus genome map of Copy Number Variable Regions (CNVRs) in the Brown Swiss (dataset of 192 bulls), Red Pied Valdostana (dataset of 143 bulls) and Finnish Ayrshire (dataset of 243 bulls) cattle breeds all genotyped on the Illumina Bovine HD BeadChip, and two SNP based CNV calling algorithms. Brown Swiss cattle originated in the Swiss Alps, kept as a triple purpose breed. Once imported in the US, it was mainly selected for increased milk production. The Valdostana Red Pied cattle is the most common autochthonous dual purpose breed in the region Valle d\u2019Aosta in Italy (13,000 animals in 2013, almost all of them registered in the Herd Book). The Finnish Ayrshire is the most common cattle in Finland. CNVs were called with the PennCNV and SVS7 software and were summarized to CNVRs at the population level as overlapping CNV calls within breed. PennCNV identified 2,377, 1,723 and 1,689 for the Italian Brown Swiss, the Red Pied Valdostana and the Finnish Ayrshire, respectively. SVS7 detected 370, 235 and 2,063 for the three cattle breeds. These regions were annotated with Ensembl v78 Bos taurus gene set (UMD3.1) and genomic regions harboring QTL for production and functional traits. The comparison among CNVRs here identified provided common regions in the breeds. The results of this study are a comprehensive genomic analysis of cattle CNVs derived from SNP data, which will be a valuable genomic variation resource and will enrich the bovine CNV map in the cattle genome, providing new information for association studies with traits included in the selection programs

О некоторых тождествах на полугруппах линейных отношений

Copy Number Variations (CNVs) are DNA sequences of 50 bp up to several Mb long, which can vary in number of copies in comparison with a reference genome. CNVs can be used in association studies to disclose genetic basis of quantitative traits phenotypic variation. Up to date, no genome-wide association study (GWAS) with CNVs and quantitative traits in such a large Brown Swiss population (i.e. with 1116 samples) has been described. The purpose of this study was to perform a GWAS using CNVs with functional, health and productive traits and to asses the impact on farming and breeding practices. The CNV \u2013 association studies were performed with the Golden Helix SVS 8.4.4 software using a correlation-trend test model. Genes within significant associated CNVs for each trait were annotated with a GO analysis using the DAVID Bioinformatics Resources 6.7. A total of 56 CNVs were significantly associated with one or more of the eight evaluated traits. The greatest association signals were given by three CNVs on chromosome 12 for the fat yield trait and on BTA23 for udder traits. The associated CNVs overlap with 23 different genes annotated on the Bos taurus genome assembly (UMD3.1)

Molecular tests for horse coat color determination

Wild animals often have muted colors that allow them to blend into the background. During the domestication, people delight in selecting for color variants, so that domestic animals, including cats, dogs, cows, sheep, horses and goats exhibit a wide range of color patterns, even though they belong to the same species. The horse basic coat colors (chestnut, bay and black) are controlled by the interaction between two genes: Melanocortin-1-Receptor [MC1R; Extension (E,e)] and Agouti Signaling Protein [ASIP; Agouti (A,a)]. The Extension gene (red factor) controls the production of red and black pigment. Agouti controls the distribution of black pigment either to a point pattern (mane, tail, lower legs, ear rims) or uniformly over the body. Ten other genes may modify the distribution, production and quantity of these pigments and are responsible for the large variety of horse coat colors. Most of coat colors may be detected based on physical appearance or phenotype alone. The aim of this study is to develop molecular tests in order to define phenotypes that are visually ambiguous and identify the correct coat color phenotype for the four dilute phenotypes palomino, buckskin, cremello and perlino due to the effects of Membrane Associated Transporter Protein gene [MATP/SLC45A2; Cream (Cr,cr)] on basic colors. We demonstrate the effect of polymorphisms of MC1R, ASIP and MATP/SLC45A2 genes on 26 Akhal-Tek\ue8 horses bred in Italy with defined phenotypes bay, chestnut, black, buckskin, cremello and perlino. The 38.46% of horses tested, show a discrepancy between the phenotype reported on the certificate and the result of analyses carried out. On 11,54 % of the horses certificate is indicated any color. With the genetic analysis we can determine the correct genetic basis of the coat color and thus complete in a correct manner the certificate with the phenotype description

A genome-wide association study using CNVs for production traits in Brown Swiss dairy cattle

Detecting genetic variation such as Copy Number Variation (CNV) in cattle provides the opportunity to study their association with productive traits. The aim of this study was to investigate CNVs in 1,410 samples of the Brown Swiss cattle breed using Illumina BovineHD Genotyping BeadChip data and to perform a genomewide association analysis for three production traits: milk yield (MY), fat yield (FY) and protein yield (PY). After severe quality control, CNVs were called with the Golden Helix SVS 8.3.1 and PennCNV software and were summarized to CNV regions (CNVRs) at a population level, i.e. overlapping CNVs, using BEDTools. Additionally common CNVRs between the two software were set as consensus. CNV-association studies were executed with the CNVRuler software using a linear regression model. Genes within significant associated CNVRs for each trait were annotated with a GO analysis using the DAVID Bioinformatics Resources 6.7. The quality control filtered out 294 samples. The GoldenHelix software identified 25,030 CNVs summarized to 398 CNVRs while PennCNV identified 62,341 CNVs summarized to 5,578 CNVRs. A total of 132 CNVRs were identified to be significantly associated with one or more of the three evaluated traits. The greatest association signal was given by a CNVR on chromosome 4 for MY. The associated regions overlap with 256 genes annotated on the Bos taurus genome assembly (UMD3.1). The result of this study is a comprehensive genomic analysis of the Brown Swiss breed, which enriches the bovine CNV map in its genome. Finally, the results of the association studies deliver new information for productive traits considered in selection programs of the Brown Swiss breed

Imputation of microsatellite from dense SNP in the Valdostana Red Pied cattle - A Master thesis in Animal Production

Microsatellite markers (MS) have been used efficiently for parentage verification in various livestock species and their impact on the industry to certify exact pedigree information has been massive for long time. In cattle, the International Society of Animal Genetics (ISAG) recommended a panel of 12 bovine MS markers for the individual parentage verification testing and a large MS database contains the historical data of populations. Recently, there is an increasing interest from the stakeholders in agriculture and the research community to use Single Nucleotide Polymorphism (SNP) for parental verification due to their higher genotyping accuracies, speed of genotyping, lower overall cost per genotype, and simplicity of automation. Thus, ISAG opened the parentage testing in cattle to SNP chips methodology. A tool to link the MS database to SNP markers tool have been developed in USA for main populations such as the Holstein and Brown Swiss cattle. The objective of the thesis is to develop a SNP-MS haplotype reference panel set in the Valdostana Red Pied cattle (the most common autochthonous dual purpose breed in the region Valle d\u2019Aosta in Italy). The information on MS alleles recognized from ISAG are available from the National Association of Valdostana Breeders (A.N.A.Bo.Ra.Va.) and the genotypes obtained from the llumina BovineHD BeadChip (777,962 SNPs) array for 143 bulls are already accessible at UNIMI. Specific imputation software (e.g.: Beagle) and pipelines will be used for the haplotype estimation. This strategy may be employed in any species that has dense SNP genotypes and MS alleles information on a subset of the population large enough to define phase associations among MS alleles and SNP haplotypes. Moreover, this methodology will validate the parentage among individuals when different genotyping platforms have been used through the generations and will assess the sensitivity of such a conversion system using HD SNP data

Интегрирование функций комплексной переменной: учеб.-метод. пособие / Н. И. Ильинкова, О. А. Кононова, Н. К. Филиппова. – Минск : БГУ, 2012

Настоящее учебно-методическое пособие составлено на материале занятий по курсу математического анализа, изучаемого в третьем семестре на физическом факультете университета. В нем излагаются необходимые теоретические сведения из раздела «Интегрирование функций комплексной переменной» в виде определений, формул, теорем и замечаний. Приводится значительное количество наиболее характерных примеров с подробным описанием их решения. Для организации самостоятельной работы студентов физических и радиофизических специальностей

Variation of milk components in the Italian Brown cattle

The aim of this study was to evaluate the variations of protein, casein, saturated (SFA), unsaturated (UFA), monounsaturated (MUFA), polyunsaturated (PUFA) fatty acids contents and cheese yield in the milk of two groups of Italian Brown cows conventionally reared in indoor period of housing or consuming pasture during the summer months in 2008 and 2013. Milk components were obtained from samples collected during the national routine (conventionally reared) and 'extraordinary' (pasture period) milk recording scheme in herds located near Sondrio (Lombardia, Italy). Milk samples were processed with the MilkoScanTM FT6000 for the identification of milk casein, SFA, UFA, MUFA and PUFA composition. The groups were analysed separately per year and the environmental factors affecting milk protein, casein, and fatty acids contents (pasture/indoor, parity, data of sampling, days in milk, days from collection to analysis) were included in the MIXED procedure of SAS 9.3. A total of 778 milk samples were available, including 234 records from indoor and 544 observations from pasture feeding. Pasture intake affected the content of casein (%) and the proportion of fat in milk (g/100 g), enhancing milk casein levels (from 2.90 to 3) and reducing the concentration of milk SFA in milk from grazing cows (from 2.29 to 1.92). Additionally, the cheese yield was calculated as 'kg of cheese per 100 kg of milk' and resulted to be 10.4 and 12 in 2008 from milk of cows reared indoor and with pasture based diet, respectively. The dairy industry should take advantage of the milk production during grazing periods from which high quality products may be obtained