scholarly journals Genome-Wide Variation, Candidate Regions and Genes Associated With Fat Deposition and Tail Morphology in Ethiopian Indigenous Sheep

2019 ◽  
Vol 9 ◽  
Author(s):  
Abulgasim Ahbara ◽  
Hussain Bahbahani ◽  
Faisal Almathen ◽  
Mohammed Al Abri ◽  
Mukhtar Omar Agoub ◽  
...  
Keyword(s):  
Fat Deposition ◽  
Indigenous Sheep ◽  
Genome Wide ◽  
Candidate Regions

scholarly journals Genome-wide insights on gastrointestinal nematode resistance in autochthonous Tunisian sheep

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
A. M. Ahbara ◽  
M. Rouatbi ◽  
M. Gharbi ◽  
M. Rekik ◽  
A. Haile ◽  
...  
Keyword(s):  
Animal Health ◽  
Gastrointestinal Nematode ◽  
Nematode Resistance ◽  
Indigenous Sheep ◽  
Genome Wide ◽  
Population Structure Analysis ◽  
Genetic Mechanisms ◽  
Negative Impacts ◽  
Candidate Regions ◽  
Genomic Regions

AbstractGastrointestinal nematode (GIN) infections have negative impacts on animal health, welfare and production. Information from molecular studies can highlight the underlying genetic mechanisms that enhance host resistance to GIN. However, such information often lacks for traditionally managed indigenous livestock. Here, we analysed 600 K single nucleotide polymorphism genotypes of GIN infected and non-infected traditionally managed autochthonous Tunisian sheep grazing communal natural pastures. Population structure analysis did not find genetic differentiation that is consistent with infection status. However, by contrasting the infected versus non-infected cohorts using ROH, LR-GWAS, FST and XP-EHH, we identified 35 candidate regions that overlapped between at least two methods. Nineteen regions harboured QTLs for parasite resistance, immune capacity and disease susceptibility and, ten regions harboured QTLs for production (growth) and meat and carcass (fatness and anatomy) traits. The analysis also revealed candidate regions spanning genes enhancing innate immune defence (SLC22A4, SLC22A5, IL-4, IL-13), intestinal wound healing/repair (IL-4, VIL1, CXCR1, CXCR2) and GIN expulsion (IL-4, IL-13). Our results suggest that traditionally managed indigenous sheep have evolved multiple strategies that evoke and enhance GIN resistance and developmental stability. They confirm the importance of obtaining information from indigenous sheep to investigate genomic regions of functional significance in understanding the architecture of GIN resistance.

scholarly journals Integration of genome wide association studies and whole genome sequencing provides novel insights into fat deposition in chicken

2018 ◽  
Vol 8 (1) ◽  
Author(s):  
Gabriel Costa Monteiro Moreira ◽  
Clarissa Boschiero ◽  
Aline Silva Mello Cesar ◽  
James M. Reecy ◽  
Thaís Fernanda Godoy ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Association Studies ◽  
Fat Deposition ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Whole Genome ◽  
Genome Wide

scholarly journals Were genome-wide linkage studies a waste of time? Exploiting candidate regions within genome-wide association studies

2009 ◽  
Vol 34 (2) ◽  
pp. 107-118 ◽  
Author(s):  
Yun J. Yoo ◽  
Shelley B. Bull ◽  
Andrew D. Paterson ◽  
Daryl Waggott ◽  
Lei Sun
Keyword(s):  
Association Studies ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Linkage Studies ◽  
Genome Wide ◽  
Candidate Regions

Pool-based genome-wide association study identified novel candidate regions on BTA9 and 14 for oleic acid percentage in Japanese Black cattle

2018 ◽  
Vol 89 (8) ◽  
pp. 1060-1066 ◽  
Author(s):  
Fuki Kawaguchi ◽  
Hiroto Kigoshi ◽  
Ayaka Nakajima ◽  
Yuta Matsumoto ◽  
Yoshinobu Uemoto ◽  
...  
Keyword(s):  
Oleic Acid ◽  
Association Study ◽  
Genome Wide Association Study ◽  
Genome Wide Association ◽  
Japanese Black Cattle ◽  
Genome Wide ◽  
Candidate Regions ◽  
Acid Percentage

Parallel Evolutionary Computation in R

2013 ◽  
pp. 105-129 ◽  
Author(s):  
Cedric Gondro ◽  
Paul Kwan
Keyword(s):  
Evolutionary Algorithms ◽  
Evolutionary Computation ◽  
Genome Wide Association Study ◽  
Optimization Methods ◽  
Large Field ◽  
Search Spaces ◽  
Parallel Evolutionary Algorithms ◽  
Genome Wide ◽  
Statistical Programming ◽  
Candidate Regions

Evolutionary Computation (EC) is a branch of Artificial Intelligence which encompasses heuristic optimization methods loosely based on biological evolutionary processes. These methods are efficient in finding optimal or near-optimal solutions in large, complex non-linear search spaces. While evolutionary algorithms (EAs) are comparatively slow in comparison to deterministic or sampling approaches, they are also inherently parallelizable. As technology shifts towards multicore and cloud computing, this overhead becomes less relevant, provided a parallel framework is used. In this chapter the authors discuss how to implement and run parallel evolutionary algorithms in the popular statistical programming language R. R has become the de facto language for statistical programming and it is widely used in biostatistics and bioinformatics due to the availability of thousands of packages to manipulate and analyze data. It is also extremely easy to parallelize routines within R, which makes it a perfect environment for evolutionary algorithms. EC is a large field of research, and many different algorithms have been proposed. While there is no single silver bullet that can handle all classes of problems, an algorithm that is extremely simple, efficient, and with good generalization properties is Differential Evolution (DE). Herein the authors discuss step-by-step how to implement DE in R and how to parallelize it. They then illustrate with a toy genome-wide association study (GWAS) how to identify candidate regions associated with a quantitative trait of interest.

scholarly journals Genome-wide scan for runs of homozygosity identifies potential candidate regions associated with growth traits in beef cattle

2020 ◽  
Author(s):  
Guoyao Zhao ◽  
Tianliu Zhang ◽  
Yuqiang Liu ◽  
Zezhao Wang ◽  
Lei Xu ◽  
...  
Keyword(s):  
Beef Cattle ◽  
Candidate Genes ◽  
Growth Traits ◽  
Farm Animals ◽  
Valuable Insight ◽  
Potential Candidate ◽  
Cattle Population ◽  
Runs Of Homozygosity ◽  
Genome Wide ◽  
Candidate Regions

Abstract Background: Runs of homozygosity (ROH) are continuous homozygous regions that generally exist in the DNA sequence of diploid organisms. Identifications of regions of the genome lead to reduction in performance can provide valuable insight into the genetic architecture of complex traits. Here, we evaluated genome-wide patterns of homozygosity and their association with growth traits in a commercial beef cattle population.Results: We identified a total of 29,271 ROH segments with an average number of 63.36 and an average length of 0.98 Mb in this commercial beef cattle population, representing ~2.53% (~63.36Mb) of the genome. To evaluate the enrichment of ROH across genomes, we initially identified 280 ROH regions by merging ROH events identified across all individuals. Of these, nine regions were significantly associated with six growth phenotype traits (body height, chest circumference, fat coverage, backfat thickness, ribeye area, carcass length; P<0.01), which contain 187 candidate genes. Furthermore, we found 26 consensus ROH regions with frequencies exceeding 10%, and several of these consensus overlapped with QTLs which are associated with weight gain, calving difficulty and stillbirth. To precisely locate locus within each ROH for every studied trait, we further utilized loci-based methods for association analysis among these identified regions. Totally, we obtained 9,360 loci within ROH, and 1,631 loci displaying significant association (P<0.01) for eight traits. In addition, we found that 67 genes embedded with homozygous loci. Several identified candidate genes, including EBF2, SLC20A2, SH3BGRL2, HMGA1 and ACSL1, were related to growth traits.Conclusions: This study assessed genome-wide autozygosity pattern and inbreeding level in a commercial beef cattle population. Our study identified many candidate regions and genes with ROH for growth traits in beef cattle, which can provide important insights into investigating homozygosity across genome in other farm animals. Our findings may further be unitized to assist the design of selection mating strategy.

scholarly journals Genome Variation in Tick Infestation and Cryptic Divergence in Tunisian Indigenous Sheep

2021 ◽  
Author(s):  
Abulgasim M. Ahbara ◽  
Médiha Khamassi Khbou ◽  
Rihab Rhomdhane ◽  
Limam Sassi ◽  
Mohamed Gharbi ◽  
...  
Keyword(s):  
Tick Infestation ◽  
Growth Traits ◽  
Genome Structure ◽  
High Confidence ◽  
Indigenous Sheep ◽  
Genome Wide ◽  
Global Concern ◽  
Multiple Pathogens ◽  
Tick Resistance ◽  
Cryptic Divergence

Abstract Background: Ticks are obligate haematophagous ectoparasites considered second to mosquitos as vectors and reservoirs of multiple pathogens of global concern. Individual variation in tick infestation has been reported in indigenous sheep, but the genes regulating the trait are poorly understood.Results: Here, we report 397 genome-wide signatures of selection overlapping 991 genes from the analysis, using four methods (ROH, LR-GWAS, XP-EHH, FST), of 600K SNP genotype data from 170 Tunisian sheep exhibiting high and low resistance to ticks. We considered 45 signatures detected by consensus results of at least two methods as high-confidence selection sweep regions. These spanned 104 genes which included immune system function genes, solute carriers and chemokine receptor. One region spanned STX5, that has been associated with tick resistance in cattle, implicating it as a prime candidate in sheep. We also observed RAB6B and TF in a high confidence candidate region that has been associated with growth traits suggesting natural selection is enhancing growth and developmental stability under tick challenge. The analysis also reveals fine-scale genome structure suggesting the existence of cryptic divergence in the Tunisian sheep.Conclusion: Our findings provide genomic reference that could enhance our understanding of the genetic architecture of tick resistance and cryptic divergence in indigenous sheep.

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