Expression and Functional Analysis of AMT1 Gene Responding to High Ammonia Stress in Razor Clam (Sinonovacula constricta)

Ammonium transporter 1 (AMT1), a member of ammonia (NH₃/NH₄⁺) transport proteins, has been found to have ammonia transport activity in plants and microorganisms. However, the functional characteristics and molecular mechanisms of AMT1 in mollusks remain unclear. The razor clam (Sinonovacula constricta) is a suitable model species to explore the molecular mechanism of ammonia excretion because of the high concentration of ambient ammonia it is exposed to in the clam-fish-shrimp polyculture system. Here, the expression of AMT1 in S. constricta (Sc-AMT1) in response to high ammonia (12.85 mmol/L NH₄Cl) stress was identified by real-time quantitative PCR (qRT-PCR), Western blotting, RNA interference, and immunofluorescence analysis. Additionally, the association between the SNP_g.15211125A > T linked with Sc-AMT1 and ammonia tolerance was validated by kompetitive allele-specific PCR (KASP). A significant upregulated expression of Sc-AMT1 was observed during ammonia exposure, and Sc-AMT1 was found to be localized in the flat cells of gill. Moreover, the interference with Sc-AMT1 significantly upregulated the hemolymph ammonia levels, accompanied by the increased mRNA expression of Rhesus glycoprotein (Rh). Taken together, our findings imply that AMT1 may be a primary contributor to ammonia excretion in S. constricta, which is the basis of their ability to inhabit benthic water with high ammonia levels.

Evaluation of Different SNP Analysis Software and Optimal Mining Process in Tree Species

Single nucleotide polymorphism (SNP) is one of the most widely used molecular markers to help researchers understand the relationship between phenotypes and genotypes. SNP calling mainly consists of two steps, including read alignment and locus identification based on statistical models, and various software have been developed and applied in this issue. Meanwhile, in our study, very low agreement (<25%) was found among the prediction results generated by different software, which was much less consistent than expected. In order to obtain the optimal protocol of SNP mining in tree species, the algorithm principles of different alignment and SNP mining software were discussed in detail. And the prediction results were further validated based on in silico and experimental methods. In addition, hundreds of validated SNPs were provided along with some practical suggestions on program selection and accuracy improvement were provided, and we wish that these results could lay the foundation for the subsequent analysis of SNP mining.

Association of genetic polymorphisms related to Johne's disease with estimated breeding values of Holstein sires for milk ELISA test scores

BACKGROUND

Johne's disease (JD) is a chronic intestinal inflammatory disease caused by Mycobacterium avium subsp. paratuberculosis (MAP) infection in ruminants. Since there are currently no effective vaccine or treatment options available to control JD, genetic selection may be an alternative strategy to enhance JD resistance. Numerous Single Nucleotide Polymorphisms (SNPs) have been reported to be associated with MAP infection status based on published genome-wide association and candidate gene studies. The main objective of this study was to validate these SNPs that were previously identified to be associated with JD by testing their effect on Holstein bulls' estimated breeding values (EBVs) for milk ELISA test scores, an indirect indicator of MAP infection status in cattle.

RESULTS

Three SNPs, rs41810662, rs41617133 and rs110225854, located on Bos taurus autosomes (BTA) 16, 23 and 26, respectively, were confirmed as significantly associated with Holstein bulls' EBVs for milk ELISA test score (FDR < 0.01) based on General Quasi Likelihood Scoring analysis (GQLS) analysis. Single-SNP regression analysis identified four SNPs that were associated with sire EBVs (FDR < 0.05). This includes two SNPs that were common with GQLS (rs41810662 and rs41617133), with the other two SNPs being rs110494981 and rs136182707, located on BTA9 and BTA16, respectively.

CONCLUSIONS

The findings of this study validate the association of SNPs with JD MAP infection status and highlight the need to further investigate the genomic regions harboring these SNPs.

Across-breed validation study confirms and identifies new loci associated with sexual precocity in Brahman and Nellore cattle

The aim of this study was to identify candidate regions associated with sexual precocity in Bos indicus. Nellore and Brahman were set as validation and discovery populations, respectively. SNP selected in Brahman to validate in Nellore were from gene regions affecting reproductive traits (G1) and significant SNP (p ≤ 10^-3 ) from a meta-analysis (G2). In the validation population, early pregnancy (EP) and scrotal circumference (SC) were evaluated. To perform GWAS in validation population, we used regression and Bayes C. SNP with p ≤ 10^-3 in regression and Bayes factor ≥3 in Bayes C were deemed significant. Significant SNP (for EP or SC) or SNP in their ±250 Kb vicinity region, which were in at least one discovery set (G1 or G2), were considered validated. SNP identified in both G1 and G2 were considered candidate. For EP, 145 SNP were validated in G1 and 41 in G2, and for SC, these numbers were 14 and 2. For EP, 21 candidate SNP were detected (G1 and G2). For SC, no candidate SNP were identified. Validated SNP and their vicinity region were located close to quantitative trait loci or genes related to reproductive traits and were enriched in gene ontology terms related to reproductive success. These are therefore strong candidate regions for sexual precocity in Nellore and Brahman.

Genome-Wide Association Study for Identification and Validation of Novel SNP Markers for Sr6 Stem Rust Resistance Gene in Bread Wheat

Stem rust (caused by Puccinia graminis f. sp. tritici Erikss. & E. Henn.), is a major disease in wheat (Triticum aestivium L.). However, in recent years it occurs rarely in Nebraska due to weather and the effective selection and gene pyramiding of resistance genes. To understand the genetic basis of stem rust resistance in Nebraska winter wheat, we applied genome-wide association study (GWAS) on a set of 270 winter wheat genotypes (A-set). Genotyping was carried out using genotyping-by-sequencing and ∼35,000 high-quality SNPs were identified. The tested genotypes were evaluated for their resistance to the common stem rust race in Nebraska (QFCSC) in two replications. Marker-trait association identified 32 SNP markers, which were significantly (Bonferroni corrected P < 0.05) associated with the resistance on chromosome 2D. The chromosomal location of the significant SNPs (chromosome 2D) matched the location of Sr6 gene which was expected in these genotypes based on pedigree information. A highly significant linkage disequilibrium (LD, r2 ) was found between the significant SNPs and the specific SSR marker for the Sr6 gene (Xcfd43). This suggests the significant SNP markers are tagging Sr6 gene. Out of the 32 significant SNPs, eight SNPs were in six genes that are annotated as being linked to disease resistance in the IWGSC RefSeq v1.0. The 32 significant SNP markers were located in nine haplotype blocks. All the 32 significant SNPs were validated in a set of 60 different genotypes (V-set) using single marker analysis. SNP markers identified in this study can be used in marker-assisted selection, genomic selection, and to develop KASP (Kompetitive Allele Specific PCR) marker for the Sr6 gene.

HIGHLIGHTS

Novel SNPs for Sr6 gene, an important stem rust resistant gene, were identified and validated in this study. These SNPs can be used to improve stem rust resistance in wheat.

Genome-Wide Association Study for Identification and Validation of Novel SNP Markers for Sr6 Stem Rust Resistance Gene in Bread Wheat

Stem rust (caused by Puccinia graminis f. sp. tritici Erikss. & E. Henn.), is a major disease in wheat (Triticum aestivium L.). However, in recent years it occurs rarely in Nebraska due to weather and the effective selection and gene pyramiding of resistance genes. To understand the genetic basis of stem rust resistance in Nebraska winter wheat, we applied genome-wide association study (GWAS) on a set of 270 winter wheat genotypes (A-set). Genotyping was carried out using genotyping-by-sequencing and ∼35,000 high-quality SNPs were identified. The tested genotypes were evaluated for their resistance to the common stem rust race in Nebraska (QFCSC) in two replications. Marker-trait association identified 32 SNP markers, which were significantly (Bonferroni corrected P < 0.05) associated with the resistance on chromosome 2D. The chromosomal location of the significant SNPs (chromosome 2D) matched the location of Sr6 gene which was expected in these genotypes based on pedigree information. A highly significant linkage disequilibrium (LD, r² ) was found between the significant SNPs and the specific SSR marker for the Sr6 gene (Xcfd43). This suggests the significant SNP markers are tagging Sr6 gene. Out of the 32 significant SNPs, eight SNPs were in six genes that are annotated as being linked to disease resistance in the IWGSC RefSeq v1.0. The 32 significant SNP markers were located in nine haplotype blocks. All the 32 significant SNPs were validated in a set of 60 different genotypes (V-set) using single marker analysis. SNP markers identified in this study can be used in marker-assisted selection, genomic selection, and to develop KASP (Kompetitive Allele Specific PCR) marker for the Sr6 gene.

HIGHLIGHTS

Novel SNPs for Sr6 gene, an important stem rust resistant gene, were identified and validated in this study. These SNPs can be used to improve stem rust resistance in wheat.

Developing a 670k genotyping array to tag ~2M SNPs across 24 horse breeds

Background

To date, genome-scale analyses in the domestic horse have been limited by suboptimal single nucleotide polymorphism (SNP) density and uneven genomic coverage of the current SNP genotyping arrays. The recent availability of whole genome sequences has created the opportunity to develop a next generation, high-density equine SNP array.

Results

Using whole genome sequence from 153 individuals representing 24 distinct breeds collated by the equine genomics community, we cataloged over 23 million de novo discovered genetic variants. Leveraging genotype data from individuals with both whole genome sequence, and genotypes from lower-density, legacy SNP arrays, a subset of ~5 million high-quality, high-density array candidate SNPs were selected based on breed representation and uniform spacing across the genome. Considering probe design recommendations from a commercial vendor (Affymetrix, now Thermo Fisher Scientific) a set of ~2 million SNPs were selected for a next-generation high-density SNP chip (MNEc2M). Genotype data were generated using the MNEc2M array from a cohort of 332 horses from 20 breeds and a lower-density array, consisting of ~670 thousand SNPs (MNEc670k), was designed for genotype imputation.

Conclusions

Here, we document the steps taken to design both the MNEc2M and MNEc670k arrays, report genomic and technical properties of these genotyping platforms, and demonstrate the imputation capabilities of these tools for the domestic horse.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-017-3943-8) contains supplementary material, which is available to authorized users.