Alien Registration- Comeau, Mary E. (Old Town, Penobscot County)

https://digitalmaine.com/alien_docs/7120/thumbnail.jp

Circular 89

A yield trial in which 43 named varieties and numbered selections of potatoes were compared was conducted during the 1991 growing season at the University of Alaska Fairbanks, Agricultural and Forestry Experiment Station’s Palmer Research Center, Matanuska Research Farm, located six miles west of Palmer, Alaska. Varieties with a history of commercial production in the Matanuska Valley (Alaska 114, Bake-King, Green Mountain, and Superior) are included and serve as a comparative base for newly developed varieties, numbered selections or older varieties that have not been tested at this location. Varieties that compare favorably with the above listed standards may warrant consideration by commercial growers. Nonirrigated trials have been conducted annually since 1982, whereas irrigated trials were initiated in 1985 (AFES Circulars 49, 54, 58, 65, 71, 77, and 84). These circulars are available at the AFES Offices in Fairbanks and Palmer. Included in this report are the results of abbreviated versions of the AFES potato yield trial conducted by cooperating individuals and agencies at other locations in Alaska including Delta Junction, Fairbanks, Homer, Kenai- Soldotna, and Kodiak.[Part 1: Potato Variety Performance] -- Introduction -- Matanuska Farm Yield Trials -- Trials at Other Locations in Alaska -- [Part 2: Commercial Potato Crop Data Summary] -- Introduction -- Potato Varieties and Yields -- Acreage per grower -- Irrigation -- Seed and Planting -- Fertilizer -- Other Cultural Practices -- Chemical Contro

Trans-Ethnic Mapping of BANK1 Identifies Two Independent SLE-Risk Linkage Groups Enriched for Co-Transcriptional Splicing Marks

BANK1 is a susceptibility gene for several systemic autoimmune diseases in several populations. Using the genome-wide association study (GWAS) data from Europeans (EUR) and African Americans (AA), we performed an extensive fine mapping of ankyrin repeats 1 (BANK1). To increase the SNP density, we used imputation followed by univariate and conditional analysis, combinedwith a haplotypic and expression quantitative trait locus (eQTL) analysis. The data from Europeans showed that the associated region was restricted to a minimal and dependent set of SNPs covering introns two and three, and exon two. In AA, the signal found in the Europeans was split into two independent effects. All of the major risk associated SNPs were eQTLs, and the risks were associated with an increased BANK1 gene expression. Functional annotation analysis revealed the enrichment of repressive B cell epigenomicmarks (EZH2 and H3K27me3) and a strong enrichment of splice junctions. Furthermore, one eQTL located in intron two, rs13106926, was found within the binding site for RUNX3, a transcriptional activator. These results connect the local genome topography, chromatin structure, and the regulatory landscape of BANK1 with co-transcriptional splicing of exon two. Our data defines a minimal set of risk associated eQTLs predicted to be involved in the expression of BANK1 modulated through epigenetic regulation and splicing. These findings allow us to suggest that the increased expression of BANK1 will have an impact on B-cell mediated disease pathways.The work presented in this paper has been supported by the Ministerio de Economía y Competitividad, Spain (SAF2016-78631-P), partly co-financed by FEDER funds of the European Union, the Gustaf den V:e-80-års Fond and the Swedish Association against Rheumatism to M.E.A-R. In addition, this work was financed by the NIH P01 grant P01-AI-083194 to C.D.L., J.B.H., R.K., and M.E.A-R. JBH: NIH grants: R01 AI024717, U01 HG00866, P30 AR070549 and U01 AI130830 and the US Department of Veterans Affairs: I01 BX001834.C.D.L.: Center for Public Health Genomics. R.K.: NIH grant R01-AR33062. J.A.J.: NIH grants U54GM104938, P30AR053483

Subtype Specificity of Genetic Loci Associated With Stroke in 16 664 Cases and 32 792 Controls

Background: Genome-wide association studies have identified multiple loci associated with stroke. However, the specific stroke subtypes affected, and whether loci influence both ischemic and hemorrhagic stroke, remains unknown. For loci associated with stroke, we aimed to infer the combination of stroke subtypes likely to be affected, and in doing so assess the extent to which such loci have homogeneous effects across stroke subtypes. Methods: We performed Bayesian multinomial regression in 16 664 stroke cases and 32 792 controls of European ancestry to determine the most likely combination of stroke subtypes affected for loci with published genome-wide stroke associations, using model selection. Cases were subtyped under 2 commonly used stroke classification systems, TOAST (Trial of Org 10172 Acute Stroke Treatment) and causative classification of stroke. All individuals had genotypes imputed to the Haplotype Reference Consortium 1.1 Panel. Results: Sixteen loci were considered for analysis. Seven loci influenced both hemorrhagic and ischemic stroke, 3 of which influenced ischemic and hemorrhagic subtypes under both TOAST and causative classification of stroke. Under causative classification of stroke, 4 loci influenced both small vessel stroke and intracerebral hemorrhage. An EDNRA locus demonstrated opposing effects on ischemic and hemorrhagic stroke. No loci were predicted to influence all stroke subtypes in the same direction, and only one locus (12q24) was predicted to influence all ischemic stroke subtypes. Conclusions: Heterogeneity in the influence of stroke-associated loci on stroke subtypes is pervasive, reflecting differing causal pathways. However, overlap exists between hemorrhagic and ischemic stroke, which may reflect shared pathobiology predisposing to small vessel arteriopathy. Stroke is a complex, heterogeneous disorder requiring tailored analytic strategies to decipher genetic mechanisms

Subtype Specificity of Genetic Loci Associated With Stroke in 16 664 Cases and 32 792 Controls

Background: Genome-wide association studies have identified multiple loci associated with stroke. However, the specific stroke subtypes affected, and whether loci influence both ischemic and hemorrhagic stroke, remains unknown. For loci associated with stroke, we aimed to infer the combination of stroke subtypes likely to be affected, and in doing so assess the extent to which such loci have homogeneous effects across stroke subtypes. Methods: We performed Bayesian multinomial regression in 16 664 stroke cases and 32 792 controls of European ancestry to determine the most likely combination of stroke subtypes affected for loci with published genome-wide stroke associations, using model selection. Cases were subtyped under 2 commonly used stroke classification systems, TOAST (Trial of Org 10172 Acute Stroke Treatment) and causative classification of stroke. All individuals had genotypes imputed to the Haplotype Reference Consortium 1.1 Panel. Results: Sixteen loci were considered for analysis. Seven loci influenced both hemorrhagic and ischemic stroke, 3 of which influenced ischemic and hemorrhagic subtypes under both TOAST and causative classification of stroke. Under causative classification of stroke, 4 loci influenced both small vessel stroke and intracerebral hemorrhage. An EDNRA locus demonstrated opposing effects on ischemic and hemorrhagic stroke. No loci were predicted to influence all stroke subtypes in the same direction, and only one locus (12q24) was predicted to influence all ischemic stroke subtypes. Conclusions: Heterogeneity in the influence of stroke-associated loci on stroke subtypes is pervasive, reflecting differing causal pathways. However, overlap exists between hemorrhagic and ischemic stroke, which may reflect shared pathobiology predisposing to small vessel arteriopathy. Stroke is a complex, heterogeneous disorder requiring tailored analytic strategies to decipher genetic mechanisms

Mapping adipose and muscle tissue expression quantitative trait loci in African Americans to identify genes for type 2 diabetes and obesity

Relative to European Americans, type 2 diabetes (T2D) is more prevalent in African Americans (AAs). Genetic variation may modulate transcript abundance in insulin-responsive tissues and contribute to risk; yet published studies identifying expression quantitative trait loci (eQTLs) in African ancestry populations are restricted to blood cells. This study aims to develop a map of genetically regulated transcripts expressed in tissues important for glucose homeostasis in AAs, critical for identifying the genetic etiology of T2D and related traits. Quantitative measures of adipose and muscle gene expression, and genotypic data were integrated in 260 non-diabetic AAs to identify expression regulatory variants. Their roles in genetic susceptibility to T2D, and related metabolic phenotypes were evaluated by mining GWAS datasets. eQTL analysis identified 1,971 and 2,078 cis-eGenes in adipose and muscle, respectively. Cis-eQTLs for 885 transcripts including top cis-eGenes CHURC1, USMG5, and ERAP2, were identified in both tissues. 62.1% of top cis-eSNPs were within ±50kb of transcription start sites and cis-eGenes were enriched for mitochondrial transcripts. Mining GWAS databases revealed association of cis-eSNPs for more than 50 genes with T2D (e.g. PIK3C2A, RBMS1, UFSP1), gluco-metabolic phenotypes, (e.g. INPP5E, SNX17, ERAP2, FN3KRP), and obesity (e.g. POMC, CPEB4). Integration of GWAS meta-analysis data from AA cohorts revealed the most significant association for cis-eSNPs of ATP5SL and MCCC1 genes, with T2D and BMI, respectively. This study developed the first comprehensive map of adipose and muscle tissue eQTLs in AAs (publically accessible at https://mdsetaa.phs.wakehealth.edu) and identified genetically-regulated transcripts for delineating genetic causes of T2D, and related metabolic phenotypes

Lupus risk variants in the PXK locus alter B-cell receptor internalization

Genome wide association studies have identified variants in PXK that confer risk for humoral autoimmune diseases, including systemic lupus erythematosus (SLE or lupus), rheumatoid arthritis and more recently systemic sclerosis. While PXK is involved in trafficking of epidermal growth factor Receptor (EGFR) in COS-7 cells, mechanisms linking PXK to lupus pathophysiology have remained undefined. In an effort to uncover the mechanism at this locus that increases lupus-risk, we undertook a fine-mapping analysis in a large multi-ancestral study of lupus patients and controls. We define a large (257kb) common haplotype marking a single causal variant that confers lupus risk detected only in European ancestral populations and spans the promoter through the 3' UTR of PXK. The strongest association was found at rs6445972 with P < 4.62 × 10-10, OR 0.81 (0.75 - 0.86). Using stepwise logistic regression analysis, we demonstrate that one signal drives the genetic association in the region. Bayesian analysis confirms our results, identifying a 95% credible set consisting of 172 variants spanning 202 kb. Functionally, we found that PXK operates on the B-cell antigen receptor (BCR); we confirmed that PXK influenced the rate of BCR internalization. Furthermore, we demonstrate that individuals carrying the risk haplotype exhibited a decreased rate of BCR internalization, a process known to impact B cell survival and cell fate. Taken together, these data define a new candidate mechanism for the genetic association of variants around PXK with lupus risk and highlight the regulation of intracellular trafficking as a genetically regulated pathway mediating human autoimmunity

Differential Effects of MYH9 and APOL1 Risk Variants on FRMD3 Association with Diabetic ESRD in African Americans

Single nucleotide polymorphisms (SNPs) in MYH9 and APOL1 on chromosome 22 (c22) are powerfully associated with non-diabetic end-stage renal disease (ESRD) in African Americans (AAs). Many AAs diagnosed with type 2 diabetic nephropathy (T2DN) have non-diabetic kidney disease, potentially masking detection of DN genes. Therefore, genome-wide association analyses were performed using the Affymetrix SNP Array 6.0 in 966 AA with T2DN and 1,032 non-diabetic, non-nephropathy (NDNN) controls, with and without adjustment for c22 nephropathy risk variants. No associations were seen between FRMD3 SNPs and T2DN before adjusting for c22 variants. However, logistic regression analysis revealed seven FRMD3 SNPs significantly interacting with MYH9—a finding replicated in 640 additional AA T2DN cases and 683 NDNN controls. Contrasting all 1,592 T2DN cases with all 1,671 NDNN controls, FRMD3 SNPs appeared to interact with the MYH9 E1 haplotype (e.g., rs942280 interaction p-value = 9.3E−7 additive; odds ratio [OR] 0.67). FRMD3 alleles were associated with increased risk of T2DN only in subjects lacking two MYH9 E1 risk haplotypes (rs942280 OR = 1.28), not in MYH9 E1 risk allele homozygotes (rs942280 OR = 0.80; homogeneity p-value = 4.3E−4). Effects were weaker stratifying on APOL1. FRMD3 SNPS were associated with T2DN, not type 2 diabetes per se, comparing AAs with T2DN to those with diabetes lacking nephropathy. T2DN-associated FRMD3 SNPs were detectable in AAs only after accounting for MYH9, with differential effects for APOL1. These analyses reveal a role for FRMD3 in AA T2DN susceptibility and accounting for c22 nephropathy risk variants can assist in detecting DN susceptibility genes