Aleutian disease: Risk factors and ImmunAD strategy for genetic improvement of tolerance in American mink (Neogale vison).

Aleutian disease (AD) is a devastating infectious disease in American mink (Neogale vison) industry caused by Aleutian mink disease virus (AMDV). Two crucial steps toward controlling infectious diseases in farm animals are: (i) assessment of the infection risk factors to minimize the likelihood of infection and (ii) selection of animals with superior immune responses against pathogens to build tolerant farms. This study aimed to investigate AD risk factors and evaluate a novel "ImmunAD" approach for genetic improvement of AD tolerance. Phenotypic records and pedigree information of 1,366 and 24,633 animals were included in this study. The risk of animal's age, sex, color type, and year of sampling on AMDV infection was assessed using a logistic regression model and counter immune-electrophoresis (CIEP) test results. ImmunAD phenotype was calculated based on AMDVG enzyme-linked immunosorbent assay (ELISA) and CIEP test results, and breeding values for ImmunAD were estimated using an animal model. Animals were classified into high-coordinated (HCIR), average-coordinated (ACIR), and low-coordinated immune responders (LCIR) using ImmunAD's breeding values, and the impact of selection of HCIR on live grade of pelt quality (PQ), harvest weight (HW), and harvest length (HL) breeding values were evaluated. Age of > 1 year, male sex, and year of sampling were identified as significant risk factors of AD (p < 0.05). A moderate-to-high heritability (0.55±0.07) was estimated for ImmunAD, while a higher heritability was observed among the CIEP-positive animals (0.76±0.06). Significantly higher breeding values were observed for PQ and HL among HCIR than those for LCIR and ACIR (p < 0.05). Our findings indicate the critical role of male breeders in AD distribution within mink farms. Regular screening of AD in male breeders before pairing them with females during breeding seasons can help disease control. ImmunAD strategy can be applied to genetic improvement of AD tolerance, with favorable impacts on some growth and production traits. Higher genetic gains can be achieved in populations with higher AD seroprevalences.

FSTest: an efficient tool for cross-population fixation index estimation on variant call format files.

Fixation index (Fst) statistics provide critical insights into evolutionary processes affecting the structure of genetic variation within and among populations. Fst statistics have been widely applied in population and evolutionary genetics to identify genomic regions targeted by selection pressures. The FSTest 1.3 software was developed to estimate four Fst statistics of Hudson, Weir and Cockerham, Nei, and Wright using high-throughput genotyping or sequencing data. Here, we introduced FSTest 1.3 and compared its performance with two widely used software VCFtools 0.1.16 and PLINK 2.0. Chromosome 1 of 1000 Genomes Phase III variant data belonging to South Asian (n = 211) and African (n = 274) populations were included as an example case in this study. Different Fst estimates were calculated for each single-nucleotide polymorphism (SNP) in a pairwise comparison of South Asian against African populations, and the results of FSTest 1.3 were confirmed by VCFtools 0.1.16 and PLINK 2.0. Two different sliding window approaches, one based on a fixed number of SNPs and another based on a fixed number of base pair (bp) were conducted using FSTest 1.3 and VCFtools 0.1.16. Our results showed that regions with low coverage genotypic data could lead to an overestimation of Fst in sliding window analysis using a fixed number of bp. FSTest 1.3 could mitigate this challenge by estimating the average of consecutive SNPs along the chromosome. FSTest 1.3 allows direct analysis of VCF files with a small amount of code and can calculate Fst estimates on a desktop computer for more than a million SNPs in a few minutes. FSTest 1.3 is freely available at https://github.com/similab/FSTest.

Population genetic analysis and scans for adaptation and contemporary selection footprints provide genomic insight into aus, indica and japonica rice cultivars diversification.

Following domestication, rice cultivars have been spread worldwide to different climates and have experienced selection pressures to improve desirable traits. This has resulted in diverse cultivars that display variations in phenotypic traits, such as stress tolerance, grain size, and yield. To better understand the genomic composition arising from cultivar's development and local adaptation, high-density genotypes (containing 286,183 single-nucleotide polymorphisms after the quality control) of 1284 rice cultivars of aus, indica, and temperate and tropical japonica were scanned for diversifying signatures by applying a pairwise comparison of fixation index (Fst) test. Each cultivar's population was investigated for contemporary selection using the integrated haplotype score test. Signatures of diversifying selection among the pairwise comparisons were found in genomic regions mainly involved in response to stress (pathogens, drought, heat, cold) and development and morphology of various structures, such as root, pollen, spikelet, and grain. The most significant diversification signal between indica and japonica cultivars was detected at the location of ROX2 gene. Aus with indica comparison detected the most divergent signal at important candidate genes of OsEXPA8 and OsEXPA9, whereas temperate with tropical japonica comparison resulted in two well-known candidate genes OsHCT4 and OsGpx4. Recent selection analysis detected different patterns of contemporary selection in genomic regions related to rice breeding standard criteria such as stress tolerance, seed germination, starch content, and flowering time. Our findings highlight the underlying molecular basis of adaptive divergence and propose that modern rice breeding may provide additional diversification among rice cultivars.

A selection signatures study among Middle Eastern and European sheep breeds.

Selection, both natural and artificial, leaves patterns on the genome during domestication of animals and leads to changes in allele frequencies among populations. Detecting genomic regions influenced by selection in livestock may assist in understanding the processes involved in genome evolution and discovering genomic regions related to traits of economic and ecological interests. In the current study, genetic diversity analyses were conducted on 34,206 quality-filtered SNP positions from 450 individuals in 15 sheep breeds, including six indigenous breeds from the Middle East, namely Iranian Balouchi, Afshari, Moghani, Qezel, Karakas and Norduz, and nine breeds from Europe, namely East Friesian Sheep, Ile de France, Mourerous, Romane, Swiss Mirror, Spaelsau, Suffolk, Comisana and Engadine Red Sheep. The SNP genotype data generated by the Illumina OvineSNP50 Genotyping BeadChip array were used in this analysis. We applied two complementary statistical analyses, FST (fixation index) and xp-EHH (cross-population extended haplotype homozygosity), to detect selection signatures in Middle Eastern and European sheep populations. FST and xp-EHH detected 629 and 256 genes indicating signatures of selection, respectively. Genomic regions identified using FST and xp-EHH contained the CIDEA, HHATL, MGST1, FADS1, RTL1 and DGKG genes, which were reported earlier to influence a number of economic traits. Both FST and xp-EHH approaches identified 60 shared genes as the signatures of selection, including four candidate genes (NT5E, ADA2, C8A and C8B) that were enriched for two significant Gene Ontology (GO) terms associated with the adenosine metabolic procedure. Knowledge about the candidate genomic regions under selective pressure in sheep breeds may facilitate identification of the underlying genes and enhance our understanding on these genes role in local adaptation.