Three breeds of Javanese sheep are described briefly and data suggesting the segregation of a gene with large effect on ovulation rate and litter size are presented. The three breeds are Javanese Thin Tail (JTT), Javanese Fat Tail (JFT) and Semarang (SEM), the last possibly a substrain of JTT. All three breeds have mean mature ewe weights under 30 kg. Ovulation rate and litter size did not differ significantly among the three; all had litter sizes of up to 4 or 5 with a mean for mature ewes of approximately 2. Ovulation rate ranged from 1 to 5 and had an average within-breed repeatability of .8 within season and .65 between seasons. Within-breed repeatability of litter size was .35 +/- .06. Prenatal survival in pregnant ewes with two, three and four or more ovulations averaged 93, 88 and 86% over two seasons. Dams that had at least one ovulation rate or litter size record greater than or equal to 3 produced two groups of daughters in approximately equal numbers: one group with many records greater than or equal to 3 and mean ovulation rate and litter size of 2.73 and 2.31, respectively, and one group with ovulation rates and litter sizes of 1 or 2 and corresponding means of 1.39 and 1.38. Dams with ovulation rate or litter size records of only 1 or 2 produced daughters in which over 90% had records of only 1 or 2. Estimated heritabilities for the mean of approximately three ovulation rate or litter size records from these daughter-dam comparisons exceeded .7. These results suggest segregation of a Booroola-type gene, one copy of which increases ovulation rate by about 1.3 and litter size by .9 to 1.0. Relationships between duration of estrus and ovulation rate, and between timing of release of luteinizing hormone and number of eggs shed, resemble the pattern in Booroola Merino more closely than that in Finnish Landrace or Romanov, supporting the hypothesis of a major gene.

Objective Single nucleotide polymorphisms (SNPs) contribute to complex disorders such as ischemic stroke (IS). Since SNPs could affect IS by altering gene expression, we studied the association of common SNPs with changes in mRNA expression (i.e. expression quantitative trait loci; eQTL) in blood after IS. Methods RNA and DNA were isolated from 137 patients with acute IS and 138 vascular risk factor controls (VRFC). Gene expression was measured using Affymetrix HTA 2.0 microarrays and SNP variants were assessed with Axiom Biobank Genotyping microarrays. A linear model with a genotype (SNP) × diagnosis (IS and VRFC) interaction term was fit for each SNP‐gene pair. Results The eQTL interaction analysis revealed significant genotype × diagnosis interaction for four SNP‐gene pairs as cis‐eQTL and 70 SNP‐gene pairs as trans‐eQTL. Cis‐eQTL involved in the inflammatory response to IS included rs56348411 which correlated with neurogranin expression (NRGN), rs78046578 which correlated with CXCL10 expression, rs975903 which correlated with SMAD4 expression, and rs62299879 which correlated with CD38 expression. These four genes are important in regulating inflammatory response and BBB stabilization. SNP rs148791848 was a strong trans‐eQTL for anosmin‐1 (ANOS1) which is involved in neural cell adhesion and axonal migration and may be important after stroke. Interpretation This study highlights the contribution of genetic variation to regulating gene expression following IS. Specific inflammatory response to stroke is at least partially influenced by genetic variation. This has implications for progressing toward personalized treatment strategies. Additional research is required to investigate these genes as therapeutic targets.

Objective: Single nucleotide polymorphism (SNP) is one of the most common types of genetic variation and likely has a contributing role in ischemic stroke (IS). The influence of SNPs on changes of gene expression in blood after IS remains largely unknown. Thus, we evaluated the association of genetic variants with changes in mRNA expression levels (i.e. expression quantitative trait loci;eQTL) in blood after IS. Methods: RNA and DNA were isolated from blood samples collected from 137 IS patients and 138 vascular risk factor controls (VRFC). Gene expression of protein-coding transcripts was quantified by Affymetrix HTA 2.0 microarrays and SNP variants assessed by Axiom Biobank Genotyping microarrays. A linear model with a genotype (SNP)х diagnosis (IS or VRFC) interaction was fit for each SNP-gene pair to identify novel IS diagnosis-dependent eQTL. Results: Our trans- eQTL interaction analysis found 70 significant SNP-gene pairs (FDR<0.01). Our observations indicated that 24 mRNAs were associated with significant genotype х diagnosis interaction. Among these genes, two X-linked genes ANOS1 and POF1B were found. Expression of ANOS1 was significantly associated with SNPs rs148791848 and rs149957475. The SNP, rs950391, was significantly associated with expression of POF1B, a gene previously shown as sexually dimorphic in stroke. Interestingly, some of the eQTL SNPs affected multiple genes in trans that are known to be altered after IS. For example, X-linked SNP rs950391, altered expression of ABCA6, CLNK, EML6, POF1B, and WNT16. Conclusions: To our knowledge, this is the first whole-genome study to examine the effect of genotype х diagnosis on gene expression of blood after IS. Some SNP-gene pairs are X-linked and may account for aspects of sexual dimorphism in stroke. Our findings facilitate better understanding of trans effects of genetic variation on gene expression in stroke.