scholarly journals Genome-Wide SNP Analysis for Milk Performance Traits in Indigenous Sheep: A Case Study in the Egyptian Barki Sheep

Animals ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 1671
Author(s):  
Ibrahim Abousoliman ◽  
Henry Reyer ◽  
Michael Oster ◽  
Eduard Murani ◽  
Ismail Mohamed ◽  
...  
Keyword(s):  
Candidate Genes ◽  
Milk Yield ◽  
Milk Composition ◽  
Sheep Breed ◽  
Snp Analysis ◽  
Quality Traits ◽  
Genome Wide ◽  
Performance Traits ◽  
Milk Performance ◽  
Genomic Regions

Sheep milk yield and milk composition traits play an important role in supplying newborn lambs with essential components such as amino acids, energy, vitamins and immune antibodies and are also of interest in terms of the nutritional value of the milk for human consumption. The aim of this study was to identify genomic regions and candidate genes for milk yield and milk composition traits through genome-wide SNP analyses between high and low performing ewes of the Egyptian Barki sheep breed, which is well adapted to the harsh conditions of North-East Africa. Therefore, out of a herd of 111 ewes of the Egyptian Barki sheep breed (IBD = 0.08), ewes representing extremes in milk yield and milk quality traits (n = 25 for each group of animals) were genotyped using the Illumina OvineSNP50 V2 BeadChip. The fixation index (FST) for each SNP was calculated between the diversified groups. FST values were Z-transformed and used to identify putative SNPs for further analysis (Z(FST) > 10). Genome-wide SNP analysis revealed genomic regions covering promising candidate genes related to milk performance traits such as SLC5A8, NUB1, TBC1D1, KLF3 and ABHD5 for milk yield and PPARA and FBLN1 genes for milk quality trait. The results of this study may contribute to the genetic improvement of milk performance traits in Barki sheep breed and to the general understanding of the genetic contribution to variability in milk yield and quality traits.

scholarly journals Single-step genome-wide association studies (GWAS) and post-GWAS analyses to identify genomic regions and candidate genes for milk yield in Brazilian Girolando cattle

2020 ◽  
Vol 103 (11) ◽  
pp. 10347-10360
Author(s):  
Pamela I. Otto ◽  
Simone E.F. Guimarães ◽  
Mario P.L. Calus ◽  
Jeremie Vandenplas ◽  
Marco A. Machado ◽  
...  
Keyword(s):  
Candidate Genes ◽  
Milk Yield ◽  
Association Studies ◽  
Single Step ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Genomic Regions

scholarly journals Genome-Wide Analysis for Early Growth-Related Traits of the Locally Adapted Egyptian Barki Sheep

Genes ◽  
2021 ◽  
Vol 12 (8) ◽  
pp. 1243
Author(s):  
Ibrahim Abousoliman ◽  
Henry Reyer ◽  
Michael Oster ◽  
Eduard Murani ◽  
Ismail Mohamed ◽  
...  
Keyword(s):  
Candidate Genes ◽  
Growth Traits ◽  
Critical Role ◽  
Fixation Index ◽  
Meat Production ◽  
Livestock Sector ◽  
Genome Wide ◽  
A Genome ◽  
Performance Traits ◽  
Genomic Regions

Sheep play a critical role in the agricultural and livestock sector in Egypt. For sheep meat production, growth traits such as birth and weaning weights are very important and determine the supply and income of local farmers. The Barki sheep originates from the northeastern coastal zone of Africa, and due to its good adaptation to the harsh environmental conditions, it contributes significantly to the meat production in these semi-arid regions. This study aimed to use a genome-wide SNP panel to identify genomic regions that are diversified between groups of individuals of Egyptian Barki sheep with high and low growth performance traits. In this context, from a phenotyped population of 140 lambs of Barki sheep, 69 lambs were considered for a genome-wide scan with the Illumina OvineSNP50 V2 BeadChip. The selected lambs were grouped into divergent subsets with significantly different performance for birth weight and weaning weight. After quality control, 63 animals and 40,383 SNPs were used for analysis. The fixation index (FST) for each SNP was calculated between the groups. The results verified genomic regions harboring some previously proposed candidate genes for traits related to body growth, i.e., EYA2, GDF2, GDF10, MEF2B, SLC16A7, TBX15, TFAP2B, and TNNC2. Moreover, novel candidate genes were proposed with known functional implications on growth processes such as CPXM2 and LRIG3. Subsequent association analysis showed significant effects of the considered SNPs on birth and weaning weights. Results highlight the genetic diversity associated with performance traits and thus the potential to improve growth traits in the Barki sheep breed.

scholarly journals Genome-Wide Association Study (GWAS) to Identify Salt-Tolerance QTLs Carrying Novel Candidate Genes in Rice During Early Vegetative Stage

Rice ◽  
2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Leila Nayyeripasand ◽  
Ghasem Ali Garoosi ◽  
Asadollah Ahmadikhah
Keyword(s):  
Association Study ◽  
Candidate Gene ◽  
Candidate Genes ◽  
Salinity Tolerance ◽  
Genome Wide Association Study ◽  
Dry Weight ◽  
Genome Wide Association ◽  
Vegetative Stage ◽  
Genome Wide ◽  
Genomic Regions

Abstract Background Rice is considered as a salt-sensitive plant, particularly at early vegetative stage, and its production is suffered from salinity due to expansion of salt affected land in areas under cultivation. Hence, significant increase of rice productivity on salinized lands is really necessary. Today genome-wide association study (GWAS) is a method of choice for fine mapping of QTLs involved in plant responses to abiotic stresses including salinity stress at early vegetative stage. In this study using > 33,000 SNP markers we identified rice genomic regions associated to early stage salinity tolerance. Eight salinity-related traits including shoot length (SL), root length (RL), root dry weight (RDW), root fresh weight (RFW), shoot fresh weight (SFW), shoot dry weight (SDW), relative water content (RWC) and TW, and 4 derived traits including SL-R, RL-R, RDW-R and RFW-R in a diverse panel of rice were evaluated under salinity (100 mM NaCl) and normal conditions in growth chamber. Genome-wide association study (GWAS) was applied based on MLM(+Q + K) model. Results Under stress conditions 151 trait-marker associations were identified that were scattered on 10 chromosomes of rice that arranged in 29 genomic regions. A genomic region on chromosome 1 (11.26 Mbp) was identified which co-located with a known QTL region SalTol1 for salinity tolerance at vegetative stage. A candidate gene (Os01g0304100) was identified in this region which encodes a cation chloride cotransporter. Furthermore, on this chromosome two other candidate genes, Os01g0624700 (24.95 Mbp) and Os01g0812000 (34.51 Mbp), were identified that encode a WRKY transcription factor (WRKY 12) and a transcriptional activator of gibberellin-dependent alpha-amylase expression (GAMyb), respectively. Also, a narrow interval on the same chromosome (40.79–42.98 Mbp) carries 12 candidate genes, some of them were not so far reported for salinity tolerance at seedling stage. Two of more interesting genes are Os01g0966000 and Os01g0963000, encoding a plasma membrane (PM) H+-ATPase and a peroxidase BP1 protein. A candidate gene was identified on chromosome 2 (Os02g0730300 at 30.4 Mbp) encoding a high affinity K+ transporter (HAK). On chromosome 6 a DnaJ-encoding gene and pseudouridine synthase gene were identified. Two novel genes on chromosome 8 including the ABI/VP1 transcription factor and retinoblastoma-related protein (RBR), and 3 novel genes on chromosome 11 including a Lox, F-box and Na+/H+ antiporter, were also identified. Conclusion Known or novel candidate genes in this research were identified that can be used for improvement of salinity tolerance in molecular breeding programmes of rice. Further study and identification of effective genes on salinity tolerance by the use of candidate gene-association analysis can help to precisely uncover the mechanisms of salinity tolerance at molecular level. A time dependent relationship between salt tolerance and expression level of candidate genes could be recognized.

scholarly journals Genome-wide analysis of expression QTL (eQTL) and allele-specific expression (ASE) in pig muscle identifies candidate genes for meat quality traits

2020 ◽  
Vol 52 (1) ◽  
Author(s):  
Yan Liu ◽  
Xiaolei Liu ◽  
Zhiwei Zheng ◽  
Tingting Ma ◽  
Ying Liu ◽  
...  
Keyword(s):  
Candidate Genes ◽  
Meat Quality ◽  
Quality Traits ◽  
Q Value ◽  
Specific Expression ◽  
Allele Specific Expression ◽  
Meat Quality Traits ◽  
Genome Wide ◽  
A Genome ◽  
Allele Specific

Abstract Background Genetic analysis of gene expression level is a promising approach for characterizing candidate genes that are involved in complex economic traits such as meat quality. In the present study, we conducted expression quantitative trait loci (eQTL) and allele-specific expression (ASE) analyses based on RNA-sequencing (RNAseq) data from the longissimus muscle of 189 Duroc × Luchuan crossed pigs in order to identify some candidate genes for meat quality traits. Results Using a genome-wide association study based on a mixed linear model, we identified 7192 cis-eQTL corresponding to 2098 cis-genes (p ≤ 1.33e-3, FDR ≤ 0.05) and 6400 trans-eQTL corresponding to 863 trans-genes (p ≤ 1.13e-6, FDR ≤ 0.05). ASE analysis using RNAseq SNPs identified 9815 significant ASE-SNPs in 2253 unique genes. Integrative analysis between the cis-eQTL and ASE target genes identified 540 common genes, including 33 genes with expression levels that were correlated with at least one meat quality trait. Among these 540 common genes, 63 have been reported previously as candidate genes for meat quality traits, such as PHKG1 (q-value = 1.67e-6 for the leading SNP in the cis-eQTL analysis), NUDT7 (q-value = 5.67e-13), FADS2 (q-value = 8.44e-5), and DGAT2 (q-value = 1.24e-3). Conclusions The present study confirmed several previously published candidate genes and identified some novel candidate genes for meat quality traits via eQTL and ASE analyses, which will be useful to prioritize candidate genes in further studies.

scholarly journals GWAS-Based Identification of New Loci for Milk Yield, Fat, and Protein in Holstein Cattle

Animals ◽  
2020 ◽  
Vol 10 (11) ◽  
pp. 2048
Author(s):  
Liyuan Liu ◽  
Jinghang Zhou ◽  
Chunpeng James Chen ◽  
Juan Zhang ◽  
Wan Wen ◽  
...  
Keyword(s):  
Candidate Genes ◽  
Milk Yield ◽  
Milk Fat ◽  
Association Studies ◽  
High Yield ◽  
Holstein Cattle ◽  
Genome Wide Association Studies ◽  
Genetic Loci ◽  
Breeding Values ◽  
Genome Wide

High-yield and high-quality of milk are the primary goals of dairy production. Understanding the genetic architecture underlying these milk-related traits is beneficial so that genetic variants can be targeted toward the genetic improvement. In this study, we measured five milk production and quality traits in Holstein cattle population from China. These traits included milk yield, fat, and protein. We used the estimated breeding values as dependent variables to conduct the genome-wide association studies (GWAS). Breeding values were estimated through pedigree relationships by using a linear mixed model. Genotyping was carried out on the individuals with phenotypes by using the Illumina BovineSNP150 BeadChip. The association analyses were conducted by using the fixed and random model Circulating Probability Unification (FarmCPU) method. A total of ten single-nucleotide polymorphisms (SNPs) were detected above the genome-wide significant threshold (p < 4.0 × 10−7), including six located in previously reported quantitative traits locus (QTL) regions. We found eight candidate genes within distances of 120 kb upstream or downstream to the associated SNPs. The study not only identified the effect of DGAT1 gene on milk fat and protein, but also discovered novel genetic loci and candidate genes related to milk traits. These novel genetic loci would be an important basis for molecular breeding in dairy cattle.

Parallel Analyses Disclose Novel Genomic Imbalances in Acute Myeloid Leukemia with Complex Karyotypes.

Blood ◽  
2005 ◽  
Vol 106 (11) ◽  
pp. 2357-2357
Author(s):  
Frank G. Rucker ◽  
Lars Bullinger ◽  
Hans A. Kestler ◽  
Peter Lichter ◽  
Konstanze Dohner ◽  
...  
Keyword(s):  
Gene Expression ◽  
Acute Myeloid Leukemia ◽  
High Resolution ◽  
Candidate Genes ◽  
Myeloid Leukemia ◽  
Parallel Analysis ◽  
Genomic Imbalances ◽  
Genome Wide ◽  
Genomic Regions ◽  
Acute Myeloid

Abstract Approximately 10 to 15 % of acute myeloid leukemia (AML) cases exhibit complex karyotypes, i.e., three or more chromosome abnormalities without presence of a specific fusion transcript. To identify novel genomic regions of interest in AML with complex karyotypes we applied comparative genomic hybridization to microarrays (matrix-CGH) allowing high-resolution genome-wide screening of genomic imbalances. We designed a microarray consisting of 2799 different BAC- or PAC-vectors. A set of 1500 of these clones covers the whole human genome with a physical distance of approximately 1.5 Mb. The remaining 1299 clones either contiguously span genomic regions known to be frequently involved in hematologic malignancies (e.g., 1p, 2p, 3q, 7q, 9p, 11q, 12q, 13q, 17p, 18q) (n=600) or contain oncogenes or tumor suppressor genes (n=699). Using this microarray platform, 83 AML cases with complex karyotypes were analyzed. Genomic losses were found more frequently than gains; the most frequent losses were deletions of 5q (71%), 17p (53%), 7q (48%); followed by deletions of 18q (30%), 16q (28%), 3p and 12q (20% each), 12p (18%), 20q (17%), and 11q (12%). The most frequent genomic gains were trisomies of 11q (39%) and 8q (31%); followed by trisomies of 1p (22%), 21q (20%), 9p (14%), 22q (13%), 13q (12%), and 6p (10%). In part, some critical segments were delineated to genomic fragments of 0.8 to a few megabase pairs in size. In lost/gained regions parallel analysis of gene expression using microarray technology detected a gene dosage effect with significant lower/higher average gene expression levels across the genes located in the respective regions. Furthermore, 47 high-level DNA amplifications in 19 different regions were identified; amplifications occurring in at least two cases mapped to (candidate genes in the amplicon) 11q23.3-q24.1 (n=10; ETS, FLI1); 11q23.3 (n=8; MLL, DDX6); 21q22 (n=5; ERG, ETS2); 13q12 (n=3; CDX2, FLT1, FLT3, PAN3); 8q24 (n=3; C8FW, MYC); 9p24 (n=2; JAK2); 12p13 (n=2; FGF6, CCND2); and 20q11 (n=2; ID1, BCL2L1). Parallel analysis displayed overexpressed candidate genes in critical amplified region, e.g., C8FW and MYC in 8q24. In conclusion, using high-resolution genome-wide screening tools such as matrix-CGH allows to unravel the enormous genetic diversity of AML cases with complex karyotypes, and correlation with global gene expression studies facilitates the delineation of disease-related candidate genes located in the critical regions.

scholarly journals Ten Genetic Loci Identified for Milk Yield, Fat, and Protein in Holstein Cattle

2020 ◽  
Author(s):  
Liyuan Liu ◽  
Jinghang Zhou ◽  
Chunpeng James Chen ◽  
Juan Zhang ◽  
Wan Wen ◽  
...  
Keyword(s):  
Candidate Genes ◽  
Milk Production ◽  
Milk Yield ◽  
Genetic Variants ◽  
Holstein Cattle ◽  
Genome Wide Association Studies ◽  
Production Traits ◽  
Milk Production Traits ◽  
Breeding Values ◽  
Genome Wide

AbstractHigh-yield and high-quality of milk are the primary goals of dairy production. Understanding the genetic architecture underlying these milk production traits is beneficial so that genetic variants can be targeted toward the genetic improvement. In this study, we measured five milk production traits in Holstein cattle population from China. These traits included milk yield, protein yield, fat yields; fat percentage and protein percentages. We used the estimated breeding values as dependent variables to conduct the genome-wide association studies (GWAS). Breeding values were estimated through pedigree relationships by using a mixed linear model for individuals with and without phenotypic data. Genotyping was carried out on the individuals with phenotypes by using the Illumina BovineSNP150 BeadChip. The association analyses were conducted by using the Fixed and random model Circulating Probability Unification (FarmCPU) method. A total of ten SNPs was detected above the genome-wide significant threshold, including six located in previously reported QTL regions. We found eight candidate genes within distances of 120 kb upstream or downstream to the associated SNPs. The most significant SNP is on DGAT1 gene affecting milk fat and protein percentage. These genetic variants and candidate genes would be valuable resources to enhance dairy cattle breeding.

scholarly journals Genome-wide association study (GWAS) for morphological and yield-related traits in an oil palm hybrid (Elaeis oleifera x Elaeis guineensis) population

2019 ◽  
Author(s):  
Jaime Osorio ◽  
Gina Garzón ◽  
Paola Delgadillo ◽  
Silvio Bastidas ◽  
Leidy Moreno ◽  
...  
Keyword(s):  
Association Mapping ◽  
Candidate Genes ◽  
Oil Palm ◽  
Plant Architecture ◽  
Elaeis Guineensis ◽  
Genotyping By Sequencing ◽  
Genome Wide Association ◽  
Elaeis Oleifera ◽  
Genome Wide ◽  
Genomic Regions

Abstract Background The genus Elaeis has two species of economic importance for the oil palm agroindustry: Elaeis oleifera (O), native to the Americas, and Elaeis guineensis (G), native to Africa. This work provides to our knowledge, the first association mapping study in an interspecific OxG oil palm population, which shows tolerance to pests and diseases, high oil quality, and acceptable fruit bunch production. Results Using genotyping-by-sequencing (GBS), we identified a total of 3,776 single nucleotide polymorphisms (SNPs) that were used to perform a genome-wide association analysis (GWAS) in 378 OxG hybrid population for 10 agronomic traits. Twelve genomic regions (SNPs) were located near candidate genes implicated in multiple functional categories, such as tissue growth, cellular trafficking, and physiological processes. Conclusions We provide new insights on genomic regions that mapped on candidate genes involved in plant architecture and yield. These potential candidate genes need to be confirmed for future targeted functional analyses. Associated markers to the traits of interest may be valuable resources for the development of marker-assisted selection in oil palm breeding. Keywords: Association mapping, Elaeis guineensis , Elaeis oleifera , genotyping-by-sequencing, plant architecture, yield.

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