Towards effective genomic information retrieval: The impact of query complexity and expansion strategies

2010 ◽  
Vol 36 (2) ◽  
pp. 194-208 ◽  
Author(s):  
Xiangming Mu ◽  
Kun Lu
Keyword(s):  
Information Retrieval ◽  
Query Complexity ◽  
Genomic Information ◽  
The Impact ◽  
Expansion Strategies

Genomic Information Retrieval

2007 ◽  
Vol 2 (3) ◽  
pp. 9-14
Author(s):  
Jacinth Salome ◽  
◽  
Ramya Ravishankar ◽  
Keyword(s):  
Information Retrieval ◽  
Genomic Information

scholarly journals Grid search approach to discriminate between old and recent inbreeding using phenotypic, pedigree and genomic information

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Pattarapol Sumreddee ◽  
El Hamidi Hay ◽  
Sajjad Toghiani ◽  
Andrew Roberts ◽  
Samuel E. Aggrey ◽  
...  
Keyword(s):  
Common Ancestor ◽  
Growth Traits ◽  
Average Daily Gain ◽  
Recent Common Ancestor ◽  
Pedigree Information ◽  
Grid Search ◽  
Genomic Information ◽  
The Impact ◽  
Daily Gain ◽  
Harmful Effects

Abstract Background Although inbreeding caused by the mating of animals related through a recent common ancestor is expected to have more harmful effects on phenotypes than ancient inbreeding (old inbreeding), estimating these effects requires a clear definition of recent (new) and ancient (old) inbreeding. Several methods have been proposed to classify inbreeding using pedigree and genomic data. Unfortunately, these methods are largely based on heuristic criteria such as the number of generations from a common ancestor or length of runs of homozygosity (ROH) segments. To mitigate these deficiencies, this study aimed to develop a method to classify pedigree and genomic inbreeding into recent and ancient classes based on a grid search algorithm driven by the assumption that new inbreeding tends to have a more pronounced detrimental effect on traits. The proposed method was tested using a cattle population characterized by a deep pedigree. Results Effects of recent and ancient inbreeding were assessed on four growth traits (birth, weaning and yearling weights and average daily gain). Thresholds to classify inbreeding into recent and ancient classes were trait-specific and varied across traits and sources of information. Using pedigree information, inbreeding generated in the last 10 to 11 generations was considered as recent. When genomic information (ROH) was used, thresholds ranged between four to seven generations, indicating, in part, the ability of ROH segments to characterize the harmful effects of inbreeding in shorter periods of time. Nevertheless, using the proposed classification method, the discrimination between new and old inbreeding was less robust when ROH segments were used compared to pedigree. Using several model comparison criteria, the proposed approach was generally better than existing methods. Recent inbreeding appeared to be more harmful across the growth traits analyzed. However, both new and old inbreeding were found to be associated with decreased yearling weight and average daily gain. Conclusions The proposed method provided a more objective quantitative approach for the classification of inbreeding. The proposed method detected a clear divergence in the effects of old and recent inbreeding using pedigree data and it was superior to existing methods for all analyzed traits. Using ROH data, the discrimination between old and recent inbreeding was less clear and the proposed method was superior to existing approaches for two out of the four analyzed traits. Deleterious effects of recent inbreeding were detected sooner (fewer generations) using genomic information than pedigree. Difference in the results using genomic and pedigree information could be due to the dissimilarity in the number of generations to a common ancestor. Additionally, the uncertainty associated with the identification of ROH segments and associated inbreeding could have an effect on the results. Potential biases in the estimation of inbreeding effects may occur when new and old inbreeding are discriminated based on arbitrary thresholds. To minimize the impact of inbreeding, mating designs should take the different inbreeding origins into consideration.

36 Effect of Blending and Tuning Relationship Matrices in Single-step Genomic BLUP

2021 ◽  
Vol 99 (Supplement_3) ◽  
pp. 19-20
Author(s):  
Taylor M McWhorter ◽  
Andre Garcia ◽  
Matias Bermann ◽  
Andres Legarra ◽  
Ignacio Aguilar ◽  
...  
Keyword(s):  
Single Step ◽  
Fixation Index ◽  
Genomic Information ◽  
Software Suite ◽  
Genetic Base ◽  
Actual Difference ◽  
The Impact ◽  
Genomic Predictions

Abstract Single-step GBLUP (ssGBLUP) relies on the combination of genomic (G) and pedigree relationships for all (A) and genotyped animals (A22). The procedure implemented in the BLUPF90 software suite first involves combining a small percentage of A22 into G (blending) to avoid singularity problems, then an adjustment to account for the fact the genetic base in G and A22 is different (tuning). However, blending before tuning may not reflect the actual difference between pedigree and genomic base because the blended matrix already contains a portion of A22. The objective of this study was to evaluate the impact of tuning before blending on predictivity, bias, and inflation of GEBV, indirect predictions (IP), and SNP effects from ssGBLUP using American Angus and US Holstein data. We used four different scenarios to obtain genomic predictions: BlendFirst_TunedG2, TuneFirst_TunedG2, BlendFirst_TunedG4, and TuneFirst_TunedG4. TunedG2 adjusts mean diagonals and off-diagonals of G to be similar to the ones in A22, whereas TunedG4 adjusts based on the fixation index. Over 6 million growth records were available for Angus and 5.9 million udder depth records for Holsteins. Genomic information was available on 51,478 Angus and 105,116 Holstein animals. Predictivity and reliability were obtained for 19,056 and 1,711 validation Angus and Holsteins, respectively. We observed the same predictivity and reliability for GEBV or IP in all four scenarios, ranging from 0.47 to 0.60 for Angus and was 0.67 for Holsteins. Slightly less bias was observed when tuning was done before blending. Correlation of SNP effects between scenarios was > 0.99. Refined tuning before blending had no impact on GEBV and marginally reduced the bias. This option will be implemented in the BLUPF90 software suite.

scholarly journals Applying the Metafounders Approach for Genomic Evaluation in a Multibreed Beef Cattle Population

2020 ◽  
Vol 11 ◽  
Author(s):  
Vinícius Silva Junqueira ◽  
Paulo Sávio Lopes ◽  
Daniela Lourenco ◽  
Fabyano Fonseca e Silva ◽  
Fernando Flores Cardoso
Keyword(s):  
Beef Cattle ◽  
Variance Components ◽  
Genetic Relationships ◽  
A Priori ◽  
Predictive Ability ◽  
Single Step ◽  
Pedigree Information ◽  
Phenotypic Variance ◽  
Genomic Information ◽  
The Impact

Pedigree information is incomplete by nature and commonly not well-established because many of the genetic ties are not known a priori or can be wrong. The genomic era brought new opportunities to assess relationships between individuals. However, when pedigree and genomic information are used simultaneously, which is the case of single-step genomic BLUP (ssGBLUP), defining the genetic base is still a challenge. One alternative to overcome this challenge is to use metafounders, which are pseudo-individuals that describe the genetic relationship between the base population individuals. The purpose of this study was to evaluate the impact of metafounders on the estimation of breeding values for tick resistance under ssGBLUP for a multibreed population composed by Hereford, Braford, and Zebu animals. Three different scenarios were studied: pedigree-based model (BLUP), ssGBLUP, and ssGBLUP with metafounders (ssGBLUPm). In ssGBLUPm, a total of four different metafounders based on breed of origin (i.e., Hereford, Braford, Zebu, and unknown) were included for the animals with missing parents. The relationship coefficient between metafounders was in average 0.54 (ranging from 0.34 to 0.96) suggesting an overlap between ancestor populations. The estimates of metafounder relationships indicate that Hereford and Zebu breeds have a possible common ancestral relationship. Inbreeding coefficients calculated following the metafounder approach had less negative values, suggesting that ancestral populations were large enough and that gametes inherited from the historical population were not identical. Variance components were estimated based on ssGBLUPm, ssGBLUP, and BLUP, but the values from ssGBLUPm were scaled to provide a fair comparison with estimates from the other two models. In general, additive, residual, and phenotypic variance components in the Hereford population were smaller than in Braford across different models. The addition of genomic information increased heritability for Hereford, possibly because of improved genetic relationships. As expected, genomic models had greater predictive ability, with an additional gain for ssGBLUPm over ssGBLUP. The increase in predictive ability was greater for Herefords. Our results show the potential of using metafounders to increase accuracy of GEBV, and therefore, the rate of genetic gain in beef cattle populations with partial levels of missing pedigree information.

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