scholarly journals Accelerated deciphering of the genetic architecture of agricultural economic traits in pigs using a low-coverage whole-genome sequencing strategy

GigaScience ◽  
2021 ◽  
Vol 10 (7) ◽  
Author(s):  
Ruifei Yang ◽  
Xiaoli Guo ◽  
Di Zhu ◽  
Cheng Tan ◽  
Cheng Bian ◽  
...  

Abstract Background Uncovering the genetic architecture of economic traits in pigs is important for agricultural breeding. However, high-density haplotype reference panels are unavailable in most agricultural species, limiting accurate genotype imputation in large populations. Moreover, the infinitesimal model of quantitative traits implies that weak association signals tend to be spread across most of the genome, further complicating the genetic analysis. Hence, there is a need to develop new methods for sequencing large cohorts without large reference panels. Results We describe a Tn5-based highly accurate, cost- and time-efficient, low-coverage sequencing method to obtain 11.3 million whole-genome single-nucleotide polymorphisms in 2,869 Duroc boars at a mean depth of 0.73×. On the basis of these single-nucleotide polymorphisms, a genome-wide association study was performed, resulting in 14 quantitative trait loci (QTLs) for 7 of 21 important agricultural traits in pigs. These QTLs harbour genes, such as ABCD4 for total teat number and HMGA1 for back fat thickness, and provided a starting point for further investigation. The inheritance models of the different traits varied greatly. Most follow the minor-polygene model, but this can be attributed to different reasons, such as the shaping of genetic architecture by artificial selection for this population and sufficiently interconnected minor gene regulatory networks. Conclusions Genome-wide association study results for 21 important agricultural traits identified 14 QTLs/genes and showed their genetic architectures, providing guidance for genetic improvement harnessing genomic features. The Tn5-based low-coverage sequencing method can be applied to large-scale genome studies for any species without a good reference panel and can be used for agricultural breeding.

2019 ◽  
Vol 32 (12) ◽  
pp. 1146-1153
Author(s):  
Marguerite R Irvin ◽  
Colleen M Sitlani ◽  
James S Floyd ◽  
Bruce M Psaty ◽  
Joshua C Bis ◽  
...  

Abstract BACKGROUND Only a handful of genetic discovery efforts in apparent treatment-resistant hypertension (aTRH) have been described. METHODS We conducted a case–control genome-wide association study of aTRH among persons treated for hypertension, using data from 10 cohorts of European ancestry (EA) and 5 cohorts of African ancestry (AA). Cases were treated with 3 different antihypertensive medication classes and had blood pressure (BP) above goal (systolic BP ≥ 140 mm Hg and/or diastolic BP ≥ 90 mm Hg) or 4 or more medication classes regardless of BP control (nEA = 931, nAA = 228). Both a normotensive control group and a treatment-responsive control group were considered in separate analyses. Normotensive controls were untreated (nEA = 14,210, nAA = 2,480) and had systolic BP/diastolic BP < 140/90 mm Hg. Treatment-responsive controls (nEA = 5,266, nAA = 1,817) had BP at goal (<140/90 mm Hg), while treated with one antihypertensive medication class. Individual cohorts used logistic regression with adjustment for age, sex, study site, and principal components for ancestry to examine the association of single-nucleotide polymorphisms with case–control status. Inverse variance-weighted fixed-effects meta-analyses were carried out using METAL. RESULTS The known hypertension locus, CASZ1, was a top finding among EAs (P = 1.1 × 10−8) and in the race-combined analysis (P = 1.5 × 10−9) using the normotensive control group (rs12046278, odds ratio = 0.71 (95% confidence interval: 0.6–0.8)). Single-nucleotide polymorphisms in this locus were robustly replicated in the Million Veterans Program (MVP) study in consideration of a treatment-responsive control group. There were no statistically significant findings for the discovery analyses including treatment-responsive controls. CONCLUSION This genomic discovery effort for aTRH identified CASZ1 as an aTRH risk locus.


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