Copy number variations in South African Nguni cattle : prevalence, characterization and genetic diversity

Thesis (PhDAgric)--Stellenbosch University, 2016.ENGLISH ABSTRACT: Copy Number Variations (CNVs) comprise of deletions, duplications and insertions larger than 1kb that occur within genomes. The identification of CNVs within regions of the bovine genome important for adaptation renders them a potential role in breed formation and adaptation. South African Nguni cattle are adapted and demonstrate an enhanced ability to endure the harsh environmental conditions of Southern Africa. This study investigated the prevalence of CNVs in the genome of South African Nguni cattle. CNV occurrence and distribution within Nguni subpopulations was assessed and comparisons with other South African cattle breeds were performed. The dynamics between CNVs and haplotype blocks (HPBs), correlations amongst CNVs and the genic locality of CNVs were investigated with the objective of determining CNV prevalence in adaptation. The Illumina BovineSNP50 beadchip was used in the first experiment to genotype 492 South African Nguni cattle sampled nationwide. PennCNV software identified 334 CNV regions (CNVRs) of between 30kb and 1Mb in length. Population structure analyses was performed and HPBs identified using ADMIXTURE and PLINK software respectively. Five subpopulations were evident with some degree of CNV segregation amongst populations. CNVRs covered or lay within 10Mb of 289 genes of which 149, 28, 44, 2 and 14 genes exclusive to the five sub-populations were identified. Some degree of overlap between CNVRs and the 541 HPBs was evident. In the second experiment, 59 Nguni genotypes were analyzed using the Bovine 50K Beadchip in conjunction with six other South African breeds. PennCNV software identified 356 unique CNVRs. One hundred and sixty three CNVRs identified in more than 1 animal were utilized as genetic markers to assess within and between breed genetic diversity (GD). Between breed group GD scores were 2.510, 6.115 and 4.233 for the Sanga, Taurine and composite breeds respectively. One hundred and two (Taurine) and seven (Sanga and composite) of the CNVRs demonstrated a significant (p≤0.05) association with one another. PANTHER overrepresentation analyses demonstrated significant representation of a number of processes, functions, components and proteins by correlated CNVR genes. CNVR based phylogenetic clustered animals of the same breed group together. In the third experiment 24 Nguni animals were sequenced at 7X coverage using illumina next generation sequencing technologies. Reads were mapped to the UMD3.1 reference genome and RAPTR-SV software was utilized to identify CNVs. CNVs identifed were filtered according to the number of reads that support the event with low (F10), medium (F45) and high stringencies (F75). Adjacent and overlapping CNVs were merged to form 399, 55 and 23 unique CNVRs that covered or lay within 1Mb of 358, 51 and 23 genes at F10, F45 and F75 stringencies respectively. NGS tools identified smaller CNVs compared to those reported from SNP data. Despite discrepancies between array and NGS methods, CNVR genes represented the same specific ontologies. The study demonstrated CNVRs to be prevalent in South African Nguni cattle, with potential role in breed formation and adaptation. CNVR GD scores, population structure, distribution and incidence dynamics were thus ascertained for the South African Nguni.AFRIKAAANS OPSOMMING: Kopie Getal Variasies (KGV) bestaan uit genomiese delesies, duplikasies of invoegings groter as 1kb in die genoom. Die identifisering van KGVs binne streke van die bees genoom, belangrik vir aanpassing, maak dat hulle 'n potensiële rol in ras vorming en aanpassing kon speel. Suid-Afrikaanse Nguni beeste is aangepas en bestand teen die harde klimaat toestande wat ervaar word in Suidelike Afrika. Hierdie studie het die teenwoordigheid van KGV’s in die genoom van Suid-Afrikaanse Nguni beeste bestudeer. Die voorkoms en verspreiding van KGV’s binne die Nguni sub-populasies is ge-assesseer en vergelyk met ander Suid- Afrikaanse bees rasse. Die dinamika tussen KGV’s en haplotipe blokke (HPB), die korrelasie tussen verskillende KGV’s en die posisie op die genoom is bestudeer met die doel om KGV voorkoms in aanpassing te bepaal. In die eerste eksperiment is die Illumina BovineSNP50 beadchip gebruik om die genotipes van 492 Nguni beeste, wat landwye ingesamel is, te bepaal. Drie honderd vier en dertig KGV Areas (KGVA) met lengtes tussen 30kb en 1Mb is met PennCNV sagteware geidentifiseer. Populasie struktuur analise sowel as HPB evaluasie is uitgevoer met onderskeidelik die ADMIXTURE en PLINK sagteware. Vyf sub-populasies is duidelik onderskeidbaar met n sekere graad van KGV segregasie. Die KGVA is waargeneem oor 10Mb van 298 gene; en onderskeidelik 149, 28, 44, 2 en 14 gene kon toegeskryf word aan elk van die vyf sub-populasies. ‘n Sekere graad van oorvleuling kon waargeneem word tussen die KGVA’s en die 541 HPB. In die tweede eksperiment is genotipes van 59 Nguni beeste ge-analiseer met die Bovine 50K Beadchip, saam met ses ander Suid-Afrikaanse bees rasse. PennCNV het 356 unieke KGVA’s ge-identifiseer. Genetiese diversiteit (GD) is bepaal op graad van 163 KGVA’s, wat versprei was oor meer as een bees. Die GD tellings tussen verskillende bees ras groepe, was 2.510, 6.115 en 4.233 vir die Sanga, Taurine en saamgestelde rasse respektiewelik. ‘n Totaal van 102 (Taurine) en sewe (Sanga en saamgestelde ras) KGVA’s het n beduidende assosiasie (p≤0.05) getoon met mekaar. Oor-representasie analise met die sagteware PANTHER, demonstreer n oorweldige verteenwoordiging van prosesse, funksies, komponente en proteïene wat korreleer met die KGVA gene. KGVA filogenetiese bome het diere van dieselfde rastipe saam groepeer. Dat spesifieke KGV’s kan onderskei tussen verskillende rasse was ook opvallend. Die derde eksperiment het die genome van 24 Nguni beeste bepaal (teen 7x dekking) deur die Illumina “Next Generation Sequencing (NGS)” tegnologie. Genomiese fragmente is toegevoeg aan die oorspronlike UMD3.1 verwysings genoom, en die RAPTR-SV sagteware is gebruik om KGV’s te identifiseer. Die KGV’s is gefilter op die hoeveelheid fragmente wat die DNA basis volgorde ondersteun met lae (F10), gemiddeld (F45) en hoë (F75) strenghede. Aangrensende en oorvleulende KGV’s was saamgesmelt om 399, 55 en 23 unieke KGVA’s te vorm wat verpreid is oor 1Mb. Ongeveer 358, 51 en 23 gene kon ge-identifiseer word by F10, F45 en F75 onderskeidelik. NGS tegnologie kon kleiner KGV’s identifiseer, wanneer vergelyk word met data vanaf SNPs. Ten spyte van teenstrydighede tussen die twee metodes, was dieselfde spesifieke ontologieë verteenwoordig deur die KGVA gene. In die geheel, demonstreer hierdie studie dat KGVA’s algemeen voorkom in Suid-Afrikaanse Nguni beeste, met potensiële rolle in ras formasie en adaptasie. KGVA GD tellings, bevolkingstruktuur, verspreiding en voorkoms dinamika is toe vasgestel vir die Suid- Afrikaanse Nguni

Ostrich (Struthio camelus) chick survival to 6 months post hatch : estimation of environmental and genetic parameters and the effect of imprinting, foster parenting and deliberate care

Thesis (MScAgric)--Stellenbosch University, 2012.ENGLISH ABSTRACT: The South African Ostrich industry was established more than 100 years ago. Despite appreciable fluctuations and modifications in demand, the industry perseveres, with meat and leather as the current primary driving force. Low and variable early chick survival is globally considered as a major constraint in the industry. In spite of obvious welfare and production implications, research findings concerning ostrich chick survival are scant. Four studies involving chick survival to 24 weeks post hatch were thus performed. South African Black ostrich (Struthio camelus var. domesticus) data obtained from a commercial pair-bred ostrich flock maintained at the Oudtshoorn Experimental Farm, South Africa comprising 10418 records were utilized to run a series of single- and multiple-trait binomial analyses using either linear models (ASREML) or threshold models (Monte Carlo Markov Chain methods, employing Gibbs sampling software) respectively. Suitable fixed and random effect models together with variance and (co)variance components were derived from these analyses. Ostrich chick survival to 24 weeks post hatch was low (28%) with a large environmental component. Preincubation storage time only affected 0 to 3 week survival, while incubator had a significant effect on cumulative survival traits to 24 weeks as well as on 13 to 24 week survival. Female chicks outperformed males at 0 to 12 weeks, 0 to 24 weeks, 4 to 12 weeks and 13 to 24 weeks with regard to survival. Hen age was significant for all traits except survival during the first week as well as for survival from 13 to 24 weeks post hatch. All analyses exhibited comparable low heritability estimates for all survival traits except for 0 to 1 week survival and 13 to 24 week survival (h2 = 0.12 and 0.10; m2 = 0.08 and 0.07 respectively) which demonstrated higher additive genetic and maternal components when threshold models, using Gibbs sampling algorithms, were employed. Neither moisture loss nor day of external pipping exhibited notable additive genetic correlations with any of the estimated survival traits. Day-old chick weight demonstrated a low correlation with early chick survival (rg = 0.24 ± 0.19) with heavier chicks tending to have a higher survival probability. The effects of rearing method on early chick survival and growth were also investigated. Comparisons between chicks reared and fostered by adult ostriches in a semiextensive environment and chicks imprinted onto humans under an intensive system and between regular human handling in an intensive rearing system and the standard farm protocol of an intensive rearing system were made. No difference in the early chick survival to 3 weeks post hatch of chicks reared by foster parents and those chicks imprinted onto humans was demonstrated. At later ages, those chicks reared by foster parents outperformed human imprinted chicks. Human imprinted chicks exposed to regular handling demonstrate an enhanced early survival when compared to chicks exposed to conventional rearing protocol in intensive systems. The study is seen to provide guidance for further research on this topic.AFRIKAANSE OPSOMMING: Die Suid-Afrikaanse volstruisbedryf is meer as 100 jaar gelede gevestig. Die bedryf is volhoubaar, ten spyte van ‘n fluktuerende aanvraag na volstruisprodukte. Vleis en leer is tans die produkte wat die meeste tot die inkomste van boere bydra. Lae en wisselende kuikenoorlewing is ‘n belangrike knelpunt in die bedryf. Navorsingsuitsette rakende kuikenoorlewing is skaars, ten spyte van ooglopende welsyns- en produksie implikasies. Kuikenoorlewing tot en met 24 weke na uitbroei is dus in vier afsondelike studies ondersoek. Data van 10418 kuikens uit ‘n kommersiële broeipaargeteelde Suid-Afrikaanse Swart (Struthio camelus var. domesticus) kudde op die Oudtshoorn Navorsingsplaas, Suid-Afrika is gebruik om enkel- en meervoudige eienskappe met of liniêre modelle (ASREML) of drempelwaarde modelle (Monte Carlo Markov Ketting metodes, met Gibbs monstering sagteware) te pas. Die metodes is gebruik om toepaslike vaste- en toevalseffekte modelle saam met (ko)variansie komponente te bekom. Kuikenoorlewing tot 24 weke na uitbroei was laag (28%), met ‘n groot omgewingsbydraende komponent. Stoor van eiers voor pak het slegs kuikenoorlewing van 0 tot 3 weke beïnvloed, terwyl die broeikas wat gebruik is ‘n betekenisvolle invloed op kuikenoorlewing tot 24 weke ouderdom, sowel as op -oorlewing van 13 tot 24 weke gehad het. Wyfiekuikens het beter oorleef as mannetjie kuikens vir oorlewing gemeet van 0 tot 12 weke, 0 tot 24 weke, 4 tot 12 weke en van 13 tot 24 weke. Broeiwyfie ouderdom het ‘n betekenisvolle invloed op kuikenoorlewing in die eerste week na uitbroei en van 13 tot 24 weke na uitbroei, gehad. Kuikenoorlewing was relatief laag oorerflik, behalwe vir oorlewing van 0 tot 1 week en vir oorlewing van 13 tot 24 weke van ouderdom (h2 = 0.12 en 0.10; m2 = 0.08 en 0.07 onderskeidelik). Drempelwaarde modelle met Gibbs monstering algoritmes het hoër additiewe en maternale variansie verhoudings in vergelyking met liniêre modelle aangedui. Genetiese korrelasies van vogverlies en die dag van uitwendige pik met kuikenoorlewing was oor die algemeen onbeduidend. Dagoudkuikengewig is laag gekorreleerd met vroeë kuikenoorlewing (rg = 0.24 ± 0.19), met swaarder kuikens wat oor die algemeen beter oorleef. Die gevolge van verskillende grootmaak metodes op vroeë kuikenoorlewing en -groei is ook ondersoek. Vergelykings tussen kuikens grootgemaak deur volwasse volstruise as pleegouers in ‘n semi-intensiewe omgewing en kuikens grootgemaak deur mense onder ‘n intensiewe stelsel en tussen kuikens grootgemaak deur gewone menslike hantering in ‘n intensiewe grootmaak sisteem onder standard plaas protokol was bestudeer. Geen verskille was gevind in vroeë kuikenoorlewing tot 3 weke na uitbroei, van die kuikens grootgemaak deur volwasse volstruise en tussen die kuikens grootgemaak deur mense . By latere ouderdomme, het die kuikens wat grootgemaak was deur volwasse volstruise beter oorlewing getoon as die kuikens grootgemaak deur mense. Kuikens grootgemaak deur mense wat blootgestel was aan gereelde hantering het verhoogde vroeë oorlewing getoon in vergelyking met kuikens grootgemaak deur konvensionele grootmaak protokol in intensiewe stelsels. Die studie kan dus beskou word om leiding te verskaf vir verdere navorsing oor hierdie onderwerp

Genomic population structure and prevalence of copy number variations in South African Nguni cattle

CITATION: Wang, M. D., Dzama, K., Hefer, C. A. & Muchadeyi, F. C. 2015. Genomic population structure and prevalence of copy number variations in South African Nguni cattle. BMC Genomics, 16:894, doi:10.1186/s12864-015-2122-z.The original publication is available at http://bmcgenomics.biomedcentral.comBackground: Copy number variations (CNVs) are modifications in DNA structure comprising of deletions, duplications, insertions and complex multi-site variants. Although CNVs are proven to be involved in a variety of phenotypic discrepancies, the full extent and consequence of CNVs is yet to be understood. To date, no such genomic characterization has been performed in indigenous South African Nguni cattle. Nguni cattle are recognized for their ability to sustain harsh environmental conditions while exhibiting enhanced resistance to disease and parasites and are thought to comprise of up to nine different ecotypes. Methods: Illumina BovineSNP50 Beadchip data was utilized to investigate genomic population structure and the prevalence of CNVs in 492 South African Nguni cattle. PLINK, ADMIXTURE, R, gPLINK and Haploview software was utilized for quality control, population structure and haplotype block determination. PennCNV hidden Markov model identified CNVs and genes contained within and 10 Mb downstream from reported CNVs. PANTHER and Ensembl databases were subsequently utilized for gene annotation analyses. Results: Population structure analyses on Nguni cattle revealed 5 sub-populations with a possible sub-structure evident at K equal to 8. Four hundred and thirty three CNVs that formed 334 CNVRs ranging from 30 kb to 1 Mb in size are reported. Only 231 of the 492 animals demonstrated CNVRs. Two hundred and eighty nine genes were observed within CNVRs identified. Of these 149, 28, 44, 2 and 14 genes were unique to sub-populations A, B, C, D and E respectively. Gene ontology analyses demonstrated a number of pathways to be represented by respective genes, including immune response, response to abiotic stress and biological regulation processess. Conclusions: CNVs may explain part of the phenotypic diversity and the enhanced adaptation evident in Nguni cattle. Genes involved in a number of cellular components, biological processes and molecular functions are reported within CNVRs identified. The significance of such CNVRs and the possible effect thereof needs to be ascertained and may hold interesting insight into the functional and adaptive consequence of CNVs in cattle.http://bmcgenomics.biomedcentral.com/articles/10.1186/s12864-015-2122-zPublisher's versio