Roles of hCG in Advancing Follicular Growth to Ovulation after Concurrent Injections of PGF2α and GnRH in Postpubertal Holstein Heifers Bearing a CL

A study was conducted to test the hypothesis that injecting Gonadotropin-releasing hormone (GnRH) concurrently with Prostaglandin F2 alpha (PGF2α) followed by an injection of human Chorionic Gonadotropin (hCG), would advance follicular growth to ovulation in Holstein heifers bearing a corpus luteum (CL). After manual examination of the CL, group 1 (PGF; n = 12) received an injection of PGF2α (25 mg, im). Group 2 (PGF + GnRH; n = 13) received an injection of GnRH (100 μg, im) immediately after an injection of PGF2α. Group 3 (PGF + GnRH + hCG; n = 12) received concurrent injections of PGF2α and GnRH followed with hCG (1500 IU, im) two days later. Follicular size and day of ovulation were monitored by daily ultrasonographic examination from days 1 to 10. Blood was collected on days-7, 0 (PGF2α administration), 2, and 7. Progesterone was not different (P > .05) on days-7, 0, and 2 between the experimental groups. However, it was higher (P < .005) in the PGF + GnRH + hCG group on day 7 compared to PGF + GnRH heifers, but not significantly higher than the PGF. Additionally, heifers in the PGF + GnRH + hCG group ovulated earlier (P < .05) than heifers in the PGF + GnRH and the PGF group. This data indicates that hCG advances follicular growth to ovulation in spite of high levels of progesterone when injected 48 h after concurrent treatments of GnRH and PGF2α on heifers bearing a CL

Confirmation of QTL that Underlie Resistance to Soybean Sudden Death Syndrome using NILs and SNPs

Soybean (Glycine max (L.) Merr.) cultivars differ in their resistance to sudden death syndrome (SDS), caused by Fusarium virguliforme (Aoki). Breeding for improving SDS response has been challenging, due to the large number of known resistance loci (more than 43) and interactions among them. The aims here were to compare the inheritance of resistance to SDS in a near isogenic line (NIL) population that was fixed for 91.5% of the genome but appeared to segregated at loci underlying partial resistance to SDS; to examine the interaction with the loci; and to identify regions containing candidate genes underlying QTL. Used were; a NIL population derived from residual heterozygosity in an F5:9 recombinant inbred line EF60 (lines 1-40). The SDS disease index (DX) data were from two locations but two different years. There were 4 of 400 microsatellite and 456 of 5,361 SNP markers tested that were polymorphic (8-10%). The SNPs clustered into 23 genomic regions. Significantly associated with resistance to SDS (0.005 \u3c P \u3e 0.0001) were regions from 2,788 Kbp to 8,938 Kbp on chromosome (Chr.) 18 and 33,100 Kbp to 34,943 Kbp on Chr. 20. The marker to trait association values suggested that the two closely linked loci on Chr. 18 were really three loci (cqRfs1, cqRfs, and now Rfs19). They were clustered within 20 cM of the rhg1 locus underlying resistance to soybean cyst nematode (SCN; HgType 7). An epistatic interaction between the Chr18 loci and the Chr 20 locus were inferred. Therefore, QTL for resistance to SDS were shown to be both internally complex and interacting

Quantitative Trait Loci Associated with Foliar Trigonelline Accumulation in Glycine Max L

The objective of this study was to utilize a Glycine max RIL population to (1) evaluate foliar trigonelline (TRG) content in field-grown soybean, (2) determine the heritability of TRG accumulation, and (3) identify DNA markers linked to quantitative trait loci (QTLs) conditioning variation in TRG accumulation. Frequency distributions of 70 recombinant inbred lines showed statistically no significant departure from normality (P > .05) for TRG accumulation measured at pod development stage (R4). Six different molecular linkage groups (LGs) (B2, C2, D2, G, J, and K) were identified to be linked to QTLs for foliar TRG accumulation. Two unique microsatellite markers (SSR) on two different linkage groups identified QTL significantly associated with foliar TRG accumulation: a region on LG J (Satt285) (P = .0019, R(2) = 15.9%) and a second region on LG C2 (Satt079) (P = .0029, R(2) = 13.4%)

Additional Quantitative Trait Loci and Candidate Genes for Seed Isoflavone Content in Soybean

Seed isoflavone content of soybean (Glycine max L. Merr.) is a trait of moderate heritablity and an ideal target for marker selection. To date over 20 QTL have been identified underlying this trait among seven populations. The objectives of this study were to identify additional QTL and candidate genes controlling isoflavone content in a set of recombinant inbred line (RIL) populations of soybean grown in two different seasons. Variations of isoflavones namely daidzein, glycitein and genistein contents over two growing seasons and locations suggests that isoflavones are influenced by both genes and environments. Six QTL were identified on five different chromosomes (Chr) or linkage groups (LG) that controlled daidzein (Chr_2/LG-M; Chr_17a/LG-D2), glycitein (Chr_2/LG-D1b; Chr_8/LG-A2) and genistein (Chr_8/LG-A2; Chr_12/LG-H) respectively in the seeds grown in season 2010. Two QTL were identified for daidzein (Chr_6/LG-C2; Chr_13b/LG-F), two QTLs for glycitein (Chr_1/LG-D1a; Chr_17c/LG-D2) and five QTLs for genistein (Chr_3/ LG-N; Chr_8/LG-A2; Chr_9/LG-K; Chr_18/LG-G) in the seeds of the 2011 growing season. Genes located within QTL confidence intervals were retrieved and gene ontology (GO) terms were used to identify those related to the flavonoid biosynthesis process. Twenty six candidate genes were identified that may be involved in isoflavones accumulation in soybean seeds

Roles of hCG in advancing follicular growth to ovulation after concurrent injections of PGF 2 and GnRH in postpubertal holstein heifers bearing a CL

A study was conducted to test the hypothesis that injecting Gonadotropin-releasing hormone (GnRH) concurrently with Prostaglandin F2 alpha (PGF2) followed by an injection of human Chorionic Gonadotropin (hCG), would advance follicular growth to ovulation in Holstein heifers bearing a corpus luteum (CL). After manual examination of the CL, group 1 (PGF; n=12) received an injection of PGF2 (25mg, im). Group 2 (PGF + GnRH; n=13) received an injection of GnRH (100g, im) immediately after an injection of PGF2. Group 3 (PGF + GnRH + hCG; n=12) received concurrent injections of PGF2 and GnRH followed with hCG (1500IU, im) two days later. Follicular size and day of ovulation were monitored by daily ultrasonographic examination from days 1 to 10. Blood was collected on days-7, 0 (PGF2 administration), 2, and 7. Progesterone was not different (P\u3e.05) on days-7, 0, and 2 between the experimental groups. However, it was higher (P\u3c.005) in the PGF + GnRH + hCG group on day 7 compared to PGF + GnRH heifers, but not significantly higher than the PGF. Additionally, heifers in the PGF + GnRH + hCG group ovulated earlier (P\u3c.05) than heifers in the PGF + GnRH and the PGF group. This data indicates that hCG advances follicular growth to ovulation in spite of high levels of progesterone when injected 48 h after concurrent treatments of GnRH and PGF2 on heifers bearing a CL. Copyright © 2010 Ricky Johnson et al

The ‘PI 438489B’ by ‘Hamilton’ SNP-Based Genetic Linkage Map of Soybean [\u3ci\u3eGlycine max\u3c/i\u3e (L.) Merr.] Identified Quantitative Trait Loci that Underlie Seedling SDS Resistance

Soybeans [Glycine max (L.) Merr.] are susceptible to many diseases including fungal diseases such as soybean sudden death syndrome (SDS). Several studies reported SDS resistance quantitative trait loci (QTL) on the soybean genome using different recombinant inbred line (RIL) populations and low density genetic linkage maps. High density exclusively single nucleotide polymorphisms-based (SNP-based) maps were not yet reported in soybean. The objectives of this study were (1) to construct a high density SNP-based genetic linkage map of soybean using the ‘PI438489B’ by ‘Hamilton’ (PIxH, n=50) recombinant inbred line population, and (2) to map QTL for SDS resistance using this high-density reliable genetic SNP-based map. The PI438489B by Hamilton high-density SNP-based genetic map was a high density map composed of 31 LGs, 648 SNPs, and covered 1,524.7 cM with an average of 2.37 cM between two adjacent SNP markers. Fourteen significant QTL were identified for SDS resistance using interval mapping (IM) and composite interval mapping (CIM) with LOD scores that ranged between 2.6 and 5.0. Twelve QTL were identified for foliar disease severity (FDS) and three QTL for root rot severity (RRS) of which one QTL underlain both FDS and RRS. The fourteen QTL were mapped onto ten separate chromosomes of the soybean genome. Seven of the intervals encompassing the QTL had been identified previously (on LGs C1, C2, D1b, G, L, N and O) associated with resistance to SDS but seven were novel (LGs A2 (2), B1, C2, D1a, D1b and O). We constructed the first PI438489B by Hamilton exclusively SNP-Based map and identified fourteen QTL that underlie SDS resistance including both resistances to foliar and root rot symptoms caused by Fusarium virguliforme infection. The QTL discovered here for SDS resistance could be useful to include in breeding programs in developing soybean cultivars resistant to SDS

Quantitative Trait Loci (QTL) that Underlie SCN Resistance in Soybean [\u3ci\u3eGlycine max\u3c/i\u3e (L.) Merr.] PI438489B by ‘Hamilton’ Recombinant Inbred Line (RIL) Population

Soybean cyst nematode caused by Heterodera glycines Ichinohe is the most devastating pest in soybean [Glycine max (L.) Merr.]. Resistance to SCN is complex, polygenic, race and cultivar specific, and it is controlled by several quantitative trait loci (QTL). Our objective was to identify and map QTL for SCN resistance to races 3 (HG Type 0) and 5 (HG Type 2.5.7) using a high density SNP-based genetic linkage map based on the PI438489B by ‘Hamilton’ (PIxH, n=50) recombinant inbred line population. The PI438489B by Hamilton map contained 648 SNPs distributed on 31 LGs with coverage of 1,524.7 cM and an average distance of 2.35 cM between two markers (Kassem et al., 2011). Using interval mapping (IM) and composite interval mapping (CIM), eight QTL were identified for SCN resistance to races 3 and 5 on 7 different soybean chromosomes. Four QTL for resistance to SCN race 3 were identified and mapped on chromosomes 7, 13, 15, and 16. Similarly, four QTL for resistance to SCN race 5 were identified and mapped on chromosomes 5, 8, and 11. The QTL identified here will be highly beneficial in breeding programs to develop cultivars with resistance to both SCN races 3 and 5