Genetic Analysis of Relative Water Content (RWC) in Two Recombinant Inbred Line Populations of Soybean [Glycine max (L.) Merr.]

Drought affects soybean [Glycine max (L.) Merr.] and other crops productivity in the US and other parts of the world. Relative water content (RWC) is an important indicator for plant water deficit tolerance (WDT). The objective of this study is to map quantitative trait loci (QTL) for RWC and several other leaf traits such as leaf dry weight (LDW), leaf fresh weight (LFW), and leaf turgid weight (LTW) in two soybean recombinant inbred line (RIL) populations, one derived from a cross of ‘Essex’ and ‘Forrest’ (ExF, n=94) and the other is derived from a cross of ‘PI 438489B’ and ‘Hamilton’ (PIxH, n=50). In the PIxH RIL population, eight QTL were identified and mapped on 6 different linkage groups (LGs) of the soybean genome. No QTL for LFW were identified in this population. In the ExF RIL population, 10 QTL were identified and mapped on 5 different LGs of soybean. Chromosome 18 (LG G) contains clusters of QTL for LFW, LTW, and RWC in the ExF RIL population. This same chromosome contains a QTL for RWC in the PIxH RIL population. The QTL found here are important to be included in breeding programs for soybean water deficit tolerance (WDT)

Quantitative Trait Loci Underlying Seed Sugars Content in “MD96-5722” by “Spencer” Recombinant Inbred Line Population of Soybean

Sucrose, raffinose, and stachyose are important soluble sugars in soybean [Glycine max (L.) Merr.] seeds. Seed sucrose is a desirable trait for taste and flavor. Raffinose and stachyose are undesirable in diets of monogastric animals, acting as anti-nutritional factors that cause flatulence and abdominal discomfort. Therefore, reducing raffinose and stachyose biosynthesis is considered as a key quality trait goal in soy food and feed industries. The objective of this study was to identify genomic regions containing quantitative trait loci (QTL) controlling sucrose, raffinose, and stachyose in a set of 92 F5:7 recombinant inbred lines (RILs) derived from a cross between the lines “MD96- 5722” and “Spencer” by using 5376 Single Nucleotide Polymorphism (SNP) markers from the Illumina Infinium SoySNP6K BeadChip array. Fourteen significant QTL were identified and mapped on eight different linkage groups (LGs) and chromosomes (Chr). Three QTL for seed sucrose content were identified on LGs N (Chr3), K (Chr9), and E (Chr15). Seven QTL were identified for raffinose content on LGs D1a (Chr1), N (Chr3), C2 (Chr6), K (Chr9), B2 (Chr14), and J (Chr16). Four QTL for stachyose content were identified on LG D1a (Chr1), C2 (Chr6), H (Chr12), and B2 (Chr14). Selection for beneficial alleles of these QTLs could facilitate breeding strategies to develop soybean lines with higher concentrations of sucrose and lower levels of raffinose and stachyose

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

Identification of Quantitative Trait Loci (QTL) Underlying Protein, Oil, and Five Major Fatty Acids’ Contents in Soybean

Improved seed composition in soybean [Glycine max (L.) Merr.] for protein and oil quality is one of the major goals of soybean breeders. A group of genes that act as quantitative traits with their effects can alter protein, oil, palmitic, stearic, oleic, linoleic, and linolenic acids percentage in soybean seeds. The objective of this study was to identify Quantitative Trait Loci (QTL) controlling protein, oil, and fatty acids content in a set of F5:8 RILs de-rived from a cross between lines, ‘MD 96-5722’ and ‘Spencer’ using 5376 Single Nucleotide Polymorphism (SNP) markers from the Illumina Infinium SoySNP6K BeadChip array. QTL analysis used WinQTL Cart 2.5 software for composite interval mapping (CIM). Identified, were; one protein content QTL on linkage group (LG-) B2 or chromosome (Chr_) 14; 11 QTL associated with oil content on six linkage groups LG-N (Chr_3), LG-A1 (Chr_5), LG-K (Chr_9), LG-F (Chr_13), LG-B2 (Chr_14), and LG-J (Chr_16); and sixteen QTL for five major fatty acids (palmitic, stearic, oleic, linoleic, and linolenic acids) on LG-N (Chr_3), LG-F (Chr_13), LG-B2 (Chr_14), LG-E (Chr_15), LG-J (Chr_16), and LG-G (Chr_18). The SNP markers closely linked to the QTL reported here will be useful for development of cultivars with altered oil and fatty acid compositions in soybean breeding programs

Genetic Analysis of Root and Shoot Traits in the ‘Essex’ By ‘Forrest’ Recombinant Inbred Line (RIL) Population of Soybean [Glycine max (L.) Merr.]

Crop productivity is severely reduced by water deficit and drought in many plant species including soybean. Improved root and shoot traits can contribute to drought tolerance ability of the plant. This research was conducted to identify QTL that underlie several root and shoot traits in the ‘Essex’ by ‘Forrest’ (ExF RILs, n=94) recombinant inbred line (RIL) soybean population. Field collected samples were used for gathering phenotypic data of basal root thickness (BRT), lateral root number (LRN), maximum root length (MRL), root fresh weight (RFW), root dry weight (RDW), shoot fresh weight (SFW), shoot dry weight (SDW), and calculating RFW/SFW, and RDW/SDW ratios. All traits and ratios were compared against DNA markers using the composite interval mapping (CIM). A total of 12 QTL: 3 for MRL, 1 QTL for LRN, 1 QTL for BRT, 2 QTL for RFW, 2 QTL for RDW, 4 QTL for SFW, 3 QTL for SDW, and 3 QTL for SFW/SDW were identified and mapped on different linkage groups (LGs) A2, B2, C2, D1a, F, G, and N. The LOD scores of these QTL ranged from 2.5 to 6.0. No QTL were associated with RFW/RDW. The root and shoot trait QTL of this study may benefit breeding programs for producing cultivars tolerant to water deficit and high yield. Preliminary analyses of genes the QTL regions using GO annotation gave insight into genes that may underlie some of these QTLs

SNP-Based Genetic Linkage Map of Soybean Using the SoySNP6K Illumina Infinium BeadChip Genotyping Array

This study reports a high density genetic linkage map based on the ‘Maryland 96-5722’ by ‘Spencer’ recombinant inbred line (RIL) population of soybean [Glycine max (L.) Merr.] and constructed exclusively with single nucleotide polymorphism (SNP) markers. The Illumina Infinium SoySNP6K BeadChip genotyping array produced 5,376 SNPs in the mapping population, with a 96.75% success rate. Significant level of goodness-of-fit for each locus was tested based on the observed vs. expected ratio (1:1). Out of 5,376 markers, 1,465 SNPs fit the 1:1 segregation rate having ≤20% missing data plus heterozygosity among the RILs. Among this 1,456 just 657 were polymorphic between the parents DNAs tested. These 657 SNPs were mapped using the JoinMap 4.0 software and 550 SNPs were distributed on 16 linkage groups (LGs) among the 20 chromosomes of the soybean genome. The total map length was just 201.57 centiMorgans (cM) with an average marker density of 0.37 cM. This is one of the high density SNP-based genetic linkage maps of soybean that will be used by the scientific community to map quantitative trait loci (QTL) and identify candidate genes for important agronomic traits in soybean

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

Genetic Architecture of Soybean Yield and Agronomic Traits

Soybean is the world’s leading source of vegetable protein and demand for its seed continues to grow. Breeders have successfully increased soybean yield, but the genetic architecture of yield and key agronomic traits is poorly understood. We developed a 40-mating soybean nested association mapping (NAM) population of 5,600 inbred lines that were characterized by single nucleotide polymorphism (SNP) markers and six agronomic traits in field trials in 22 environments. Analysis of the yield, agronomic, and SNP data revealed 23 significant marker-trait associations for yield, 19 for maturity, 15 for plant height, 17 for plant lodging, and 29 for seed mass. A higher frequency of estimated positive yield alleles was evident from elite founder parents than from exotic founders, although unique desirable alleles from the exotic group were identified, demonstrating the value of expanding the genetic base of US soybean breeding

Study of Factors Affecting Students' Performance in three Sci- ence Classes: General Biology, Botany, and Microbiology at Fayetteville State University

Abstract Several studies have reported the effects of class time on overall students' performances, but there are just few on the influence of factors as absences, gender, class section, class difficulty or semester. The objectives of this study were to analyze the effects of the above mentioned factors (absences, class time, gender, class difficulty and semester) on college students' performance in three science classes: Principles of Biology (BIOL 150), General Botany (BOTN 210), and Microbiology & Immunology (BIOL 330) over a period of 3 years. Analysis of variance (ANOVA) for absences showed significant differences for the number of those between the different semesters (fall, spring, and summer) and that students tend to miss more classes (P>0.05) during fall and spring than summer semesters. Gender (P>0.3515) and class section (P>0.0608) do not seem to significantly affect the average grades in general biology and microbiology. Regarding gender, significant differences were observed in BOTN 210 between females and males average grades. Females tend to do better than males at least in this class. There was a moderate but strongly significant negative correlation (-0.59, P>0.0001***) between the average grades and the number of absences in almost all classes. ANOVA also showed significant differences for the average grades between the different class times at P>0.0020*. The Tukey-Kramer test revealed that students perform better in morning classes compared to afternoon classes. The class time plays a significant role in the number of absences as well. Analysis showed that the most "convenient" time for students is late morning or after __________________________________________________ E-mail: [email protected] noon given that they tend to result in fewer absences. In addition, students tend to receive better grades in BOTN 210 that they do in BIOL 330 and BIOL 150 (Means 77.33, 69.42, and 67.82, respectively) which can be justified by the fact that the latter two are more intense than the first. Overall, absences are the only factor among those studied (absences, gender, class section, class difficulty and semester) that seem to affect student's grades negatively in all three classes (BIOL 150, BOTN 210 and BIOL 330). Typically, factors such as gender, and class section do not have any effect on students' performance. Results for class time show that students may perform better in morning or evening classes. In other cases time does not play any significant role to efficiency