Genome-wide association analysis reveals QTL and candidate mutations involved in white spotting in cattle
Swati JivanjiG.M. WorthThomas LopdellAnna YeatesChristine CouldreyEdwardo ReynoldsKathryn TipladyLorna R. McNaughtonThomas JohnsonStephen R. DavisB.L. HarrisRichard SpelmanRussell G. SnellDorian J. GarrickMathew D. Littlejohn
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White spotting of the coat is a characteristic trait of various domestic species including cattle and other mammals. It is a hallmark of Holstein-Friesian cattle, and several previous studies have detected genetic loci with major effects for white spotting in animals with Holstein-Friesian ancestry. Here, our aim was to better understand the underlying genetic and molecular mechanisms of white spotting, by conducting the largest mapping study for this trait in cattle, to date.Using imputed whole-genome sequence data, we conducted a genome-wide association analysis in 2973 mixed-breed cows and bulls. Highly significant quantitative trait loci (QTL) were found on chromosomes 6 and 22, highlighting the well-established coat color genes KIT and MITF as likely responsible for these effects. These results are in broad agreement with previous studies, although we also report a third significant QTL on chromosome 2 that appears to be novel. This signal maps immediately adjacent to the PAX3 gene, which encodes a known transcription factor that controls MITF expression and is the causal locus for white spotting in horses. More detailed examination of these loci revealed a candidate causal mutation in PAX3 (p.Thr424Met), and another candidate mutation (rs209784468) within a conserved element in intron 2 of MITF transcripts expressed in the skin. These analyses also revealed a mechanistic ambiguity at the chromosome 6 locus, where highly dispersed association signals suggested multiple or multiallelic QTL involving KIT and/or other genes in this region.Our findings extend those of previous studies that reported KIT as a likely causal gene for white spotting, and report novel associations between candidate causal mutations in both the MITF and PAX3 genes. The sizes of the effects of these QTL are substantial, and could be used to select animals with darker, or conversely whiter, coats depending on the desired characteristics.Keywords:
Candidate gene
White (mutation)
Coat
Genome-wide Association Study
Genetic Association
Abstract Objectives : To investigate possible obesity candidate genes in regions of porcine quantitative trait loci (QTL) for fat deposition and obesity‐related phenotypes. Research Methods and Procedures : Chromosome mapping and QTL analyses of obesity candidate genes were performed using DNA panels from a reference pig family. Statistical association analyses of these genes were performed for fat deposition phenotypes in several other commercial pig populations. Results : Eight candidate genes were mapped to QTL regions of pig chromosomes in this study. These candidate genes also served as anchor loci to determine homologous human chromosomal locations of pig fat deposition QTL. Preliminary analyses of relationships among polymorphisms of individual candidate genes and a variety of phenotypic measurements in a large number of pigs were performed. On the basis of available data, gene‐gene interactions were also studied. Discussion : Comparative analysis of obesity‐related genes in the pig is not only important for development of marker‐assisted selection on growth and fat deposition traits in the pig but also provides for an understanding of their genetic roles in the development of human obesity.
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Almost all crops have been studied on QTL(quantitative trait loci) mapping with many QTL mapping methods,such as IM(interval mapping),CIM(composite interval mapping),MCIM(mixed-model based composite interval mapping) and Bayesian QTL mapping having been developed.However,these methods have had shortcomings,namey,the genomic region of the QTL detected,within which there were probably hundreds of candidate genes was still too large.In this paper,a better understanding of the molecular functions of QTLs was obtained by first briefly reviewing methods of analyzing the candidate gene within QTL intervals based on bioinformatics.Then,in order to provide a new analytical method for better use of QTLs in the future,the genetics,genome organization,gene expression and function of candidate genes located on QTL region were analyzed.
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Phytophthora infestans, the causal agent of late blight, threatens potato production worldwide. Many quantitative trait loci (QTL) for late blight resistance have been mapped in several potato populations. At the same time, numerous expressed sequences tags (EST) related to late blight resistance have been deposited in databases. In order to screen for putative candidate genes associated with late blight resistance, 65 candidate genes were selected for mapping and investigation of their relationship with QTL in three diploid potato populations PCC1, BCT, and PD. In total, 26 primers from the 65 selected genes that showed PCR length polymorphism were mapped on the linkage groups of three populations. Further comparison between map location of QTL and candidate gene loci indicated that three candidate gene markers were placed in a QTL region. The locus of a putative receptor-like protein kinase b co-localized with an important QTL region on chromosome XI of PCC1. In the PD population, the Lox gene was in a QTL with moderate effect on chromosome III and two protein phosphatase loci were localized in a QTL with the largest effect on chromosome XII. These mapped candidate gene markers could be used as a bridge to other genetic maps of potato. The association of candidate genes with QTL forms the basis for further studies on the contributions of these candidate genes to natural variation for potato late blight resistance. Key words: Candidate gene, quantitative resistance loci, late blight, potato
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A systematic study has been conducted of all available reports in PubMed and OMIM (Online Mendelian Inheritance in Man) to examine the genetic and molecular basis of quantitative genetic loci (QTL) of diabetes with the main focus on genes and polymorphisms. The major question is, What can the QTL tell us? Specifically, we want to know whether those genome regions differ from other regions in terms of genes relevant to diabetes. Which genes are within those QTL regions, and, among them, which genes have already been linked to diabetes? whether more polymorphisms have been associated with diabetes in the QTL regions than in the non-QTL regions.Our search revealed a total of 9038 genes from 26 type 1 diabetes QTL, which cover 667,096,006 bp of the mouse genomic sequence. On one hand, a large number of candidate genes are in each of these QTL; on the other hand, we found that some obvious candidate genes of QTL have not yet been investigated. Thus, the comprehensive search of candidate genes for known QTL may provide unexpected benefit for identifying QTL genes for diabetes.
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Feed efficiency (FE) is a very important trait in livestock industry. Identification of the candidate genes could be of benefit for the improvement of FE trait. Mouse is used as the model for many studies in mammals. In this study, the candidate genes related to FE and coat color were identified using C57BL/6J (C57) × Kunming (KM) F2 mouse population. GWAS results showed that 61 and 2 SNPs were genome-wise suggestive significantly associated with feed conversion ratio (FCR) and feed intake (FI) traits, respectively. Moreover, the Erbin, Msrb2, Ptf1a, and Fgf10 were considered as the candidate genes of FE. The Lpl was considered as the candidate gene of FI. Further, the coat color trait was studied. KM mice are white and C57 ones are black. The GWAS results showed that the most significant SNP was located at chromosome 7, and the closely linked gene was Tyr. Therefore, our study offered useful target genes related to FE in mice; these genes may play similar roles in FE of livestock. Also, we identified the major gene of coat color in mice, which would be useful for better understanding of natural mutation of the coat color in mice.
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Reduced bull fertility imposes economic losses in bovine herds. Specifically, testicular and spermatic traits are important indicators of reproductive efficiency. Several genome-wide association studies (GWAS) have identified genomic regions associated with these fertility traits. The aims of this study were as follows: 1) to perform a systematic review of GWAS results for spermatic and testicular traits in cattle and 2) to identify key functional candidate genes for these traits. The identification of functional candidate genes was performed using a systems biology approach, where genes shared between traits and studies were evaluated by a guilt by association gene prioritization (GUILDify and ToppGene software) in order to identify the best functional candidates. These candidate genes were integrated and analyzed in order to identify overlapping patterns among traits and breeds. Results showed that GWAS for testicular-related traits have been developed for beef breeds only, whereas the majority of GWAS for spermatic-related traits were conducted using dairy breeds. When comparing traits measured within the same study, the highest number of genes shared between different traits was observed, indicating a high impact of the population genetic structure and environmental effects. Several chromosomal regions were enriched for functional candidate genes associated with fertility traits. Moreover, multiple functional candidate genes were enriched for markers in a species-specific basis, taurine (Bos taurus) or indicine (Bos indicus). For the different candidate regions identified in the GWAS in the literature, functional candidate genes were detected as follows: B. Taurus chromosome X (BTX) (TEX11, IRAK, CDK16, ATP7A, ATRX, HDAC6, FMR1, L1CAM, MECP2, etc.), BTA17 (TRPV4 and DYNLL1), and BTA14 (MOS, FABP5, ZFPM2). These genes are responsible for regulating important metabolic pathways or biological processes associated with fertility, such as progression of spermatogenesis, control of ciliary activity, development of Sertoli cells, DNA integrity in spermatozoa, and homeostasis of testicular cells. This study represents the first systematic review on male fertility traits in cattle using a system biology approach to identify key candidate genes for these traits.
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Runs of Homozygosity
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Leaf size is a crucial component of sesame ( Sesamum indicum L.) plant architecture and further influences yield potential. Despite that it is well known that leaf size traits are quantitative traits controlled by large numbers of genes, quantitative trait loci (QTL) and candidate genes for sesame leaf size remain poorly understood. In the present study, we combined the QTL-seq approach and SSR marker mapping to identify the candidate genomic regions harboring QTL controlling leaf size traits in an RIL population derived from a cross between sesame varieties Zhongzhi No. 13 (with big leaves) and ZZM2289 (with small leaves). The QTL mapping revealed 56 QTL with phenotypic variation explained (PVE) from 1.87 to 27.50% for the length and width of leaves at the 1/3 and 1/2 positions of plant height. qLS15-1 , a major and environmentally stable pleiotropic locus for both leaf length and width explaining 5.81 to 27.50% phenotypic variation, was located on LG15 within a 408-Kb physical genomic region flanked by the markers ZMM6185 and ZMM6206. In this region, a combination of transcriptome analysis with gene annotations revealed three candidate genes SIN_1004875 , SIN_1004882 , and SIN_1004883 associated with leaf growth and development in sesame. These findings provided insight into the genetic characteristics and variability for sesame leaf and set up the foundation for future genomic studies on sesame leaves and will serve as gene resources for improvement of sesame plant architecture.
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Abstract Background Meta-analysis of quantitative trait locus (QTL) is a computational technique to identify consensus QTL and refine QTL positions on the consensus map from multiple mapping studies. The combination of meta-QTL intervals, significant SNPs and transcriptome analysis has been widely used to identify candidate genes in various plants. Results In our study, 884 QTL associated with cotton fiber quality traits from 12 studies were used for meta-QTL analysis based on reference genome TM-1, as a result, 74 meta-QTL were identified, including 19 meta-QTL for fiber length (FL), 18 meta-QTL for fiber strength (FS), 11 meta-QTL for fiber uniformity (FU), 11 meta-QTL for fiber elongation (FE), and 15 meta-QTL for micronaire (MIC). Combined with 8589 significant SNPs associated with fiber quality traits collected from 15 studies, 297 candidate genes were identified in the meta-QTL intervals, 20 of which showed high expression specifically in the developing fibers. According to the function annotations, some of the 20 key candidate genes are associated with the fiber development. Conclusions This study provides not only stable QTLs used for marker-assisted selection (MAS), but also candidate genes to uncover the molecular mechanisms for cotton fiber development.
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Congenic
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Positional cloning
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