TESTING VARIANCE COMPONENTS BY TWO JACKKNIFE METHODS

The jackknife method, a resampling technique, has been widely used for statistical tests for years. The pseudo value based jackknife method (defined as pseudo jackknife method) is commonly used to reduce the bias for an estimate; however, sometimes it could result in large variation for an estimate and thus reduce the power for parameters of interest. In this study, a non-pseudo value based jackknife method (defined as non-pseudo jackknife method) was used for testing variance components under mixed linear models. We compared this non-pseudo value based jackknife method and the pseudo value based method by simulation regarding their biases, Type I errors, and powers. Our simulated results showed that biases obtained by the two jackknife methods are very similar; however, the non-pseudo value based method had higher testing powers than the pseudo value based method while the non-pseudo value based method had lower Type I error rates than the preset nomial probability values. Thus, we concluded that the non-pseudo value based jackknife method is superior to the pseudo value based method for testing variance components under a general mixed linear model

A GENERALIZED APPROACH AND COMPUTER TOOL FOR QUANTITATIVE GENETICS STUDY

Quantitative genetics is one of the most important components to provide valuable genetic information for improving production and quality of plants and animals. The research history of quantitative genetics study could be traced back more than one hundred years. Since the Analysis of Variance (ANOVA) methods were proposed by Fisher in 1925, several useful genetic models have been proposed and have been widely applied in both plant and animal quantitative genetics studies. Useful examples included various North Carolina (NC) and diallel cross mating designs. However, many genetic models derived from these mating designs are ANOVA method based, so there are several major limitations. For example, ANOVA based methods are constricted to simple genetic models and specific mating designs and require balanced data structures. Though mixed linear model approaches were proposed in the 1960s, their applications in quantitative genetics study were limited until the early 1990s. The advantages of the mixed linear model approaches include the flexibility for unbalanced genetic data structures and complex genetic model systems. In the past years the mixed linear models have been applied to analyze various useful genetic models and a number of computer programs have been developed. In addition, researchers are not only interested in finding appropriate data structures needed for specific genetic models but also want to identify appropriate genetic models suitable for a specific data structure. Therefore, a generalized computer tool has been developed for both model evaluations and actual data analyses. In this paper, various genetic models will be detailed and generalized by mixed linear model approaches and the features of the new computer tool GenMod will be described

DISTRIBUTION OF BOLL NUMBER AND LINT YIELD BY TIME AND POSITION IN UPLAND COTTON CULTIVATORS

The time period and position which make the major contribution to total yield and to its variation is important for the field management and breeding for upland cotton, Gossypium hirsutum, L. Two-year end-of-season plant mapping data from 11 upland cotton cultivars were analyzed by position and by week. The data showed that the first position in the second and third weeks made the largest contribution to the total boll number and lint yield. The eleven cultivars differed with respect to the earliness but they had similar lint yield at harvest. The early season cultivars produce more yield and more bolls than late season cultivars in the first week of blooming, while the late season cultivars produce more yield and more bolls in the fourth week and later. The genotypic variance was the largest in week 5 and later for both lint yield and boll number. Thus, these results suggested that appropriate field management is required to maintain high yield in weeks 2 and 3 and to obtain maximum yield at late season, especially for late season cultivars. Breeders could be able to cross two cultivars which differ in earliness to obtain high yielding lines

VARIATION ANALYSIS FOR FIBER QUALITY TRAITS AMONG DIFFERENT POSITIONSIN EIGHT UPLAND COTTON CULTIVARS

Equivalencyof fiber quality within a plant of upland cotton, Gossypium hirsutum L., is very important. There are several traits within a plant that can be used to measure fiber quality and five of those traits will be investigated. Eight representative upland cultivars were grown at the Plant Science Research Farm at Mississippi State University in 1986 and five fiber traits: micronaire, fiber elongation, 2.5% and 50% span length, and fiber strength, were measured at different plant locations. The analysis of the study was modeled after a crop stability analysis with plant locations being treated as environments in the analysis. Three methodsof stability analyses were investigated:Francis and Kannenberg’s (F-K), Finlay and Wilkinson’s (F-W), and additive main effect and multiplication interaction (AMMI).The results showed that cultivar ST213 was stable for micronaire, MC235 for fiber span length, DPNSL and DES119 for fiber elongation, and CAMD-E for fiber strength

A MAGIC population-based genome-wide association study reveals functional association of GhRBB1_A07 gene with superior fiber quality in cotton

Title: Quantile-quantile (Q-Q) Plot of six fiber traits generated from GWAS analysis following mixed linear model (MLM) using GAPIT software. A) Fiber elongation (ELO), B) Micronaire (MIC), C) Short fiber content (SFC), D) Fiber strength (STR), E) Upper half mean fiber length (UHM), and F) Uniformity index (UI). Description of data: Q-Q plots of six fiber traits generated from GWAS analysis following MLM are included in this figure. The X and Y axis have the expected and observed negative logarithm 10 of p value, respectively generated during GWAS analysis. (DOCX 207 kb

Recent Developments in Fiber Genomics of Tetraploid Cotton Species

Cotton (Gossypium spp.) produces naturally soft, single-celled trichomes as fiber on the seed coat supplying the main source of natural raw material for the textile industry. It is economically considered as one of the most leading cash crops in the world and evolutionarily very important as a model system for detailed scientific investigations. Cotton production is going through a big transition stage such as losing the market share in competition with the synthetic fibers, high popularity of Bt and herbicide resistance genes in cotton cultivars, and the recent shift of fiber demands to meet the standard fiber quality due to change of textile technologies to produce high superior quality of fibers in the global market. Recently, next-generation sequencing technologies through high-throughput sequencing at greatly reduced costs provided opportunities to sequence the diploid and tetraploid cotton genomes. With the availability of large volume of literatures on molecular mapping, new genomic resources, characterization of cotton genomes, discoveries of many novel genes, regulatory elements including small and microRNAs and new genetic tools such as gene silencing or gene editing technique for genome manipulation, this report attempted to provide the readers a comprehensive review on the recent advances of cotton fiber genomics research

POPcorn: An Online Resource Providing Access to Distributed and Diverse Maize Project Data

The purpose of the online resource presented here, POPcorn (Project Portal for corn), is to enhance accessibility of maize genetic and genomic resources for plant biologists. Currently, many online locations are difficult to find, some are best searched independently, and individual project websites often degrade over time—sometimes disappearing entirely. The POPcorn site makes available (1) a centralized, web-accessible resource to search and browse descriptions of ongoing maize genomics projects, (2) a single, stand-alone tool that uses web Services and minimal data warehousing to search for sequence matches in online resources of diverse offsite projects, and (3) a set of tools that enables researchers to migrate their data to the long-term model organism database for maize genetic and genomic information: MaizeGDB. Examples demonstrating POPcorn's utility are provided herein

Subsequent Surgery After Revision Anterior Cruciate Ligament Reconstruction: Rates and Risk Factors From a Multicenter Cohort

BACKGROUND: While revision anterior cruciate ligament reconstruction (ACLR) can be performed to restore knee stability and improve patient activity levels, outcomes after this surgery are reported to be inferior to those after primary ACLR. Further reoperations after revision ACLR can have an even more profound effect on patient satisfaction and outcomes. However, there is a current lack of information regarding the rate and risk factors for subsequent surgery after revision ACLR. PURPOSE: To report the rate of reoperations, procedures performed, and risk factors for a reoperation 2 years after revision ACLR. STUDY DESIGN: Case-control study; Level of evidence, 3. METHODS: A total of 1205 patients who underwent revision ACLR were enrolled in the Multicenter ACL Revision Study (MARS) between 2006 and 2011, composing the prospective cohort. Two-year questionnaire follow-up was obtained for 989 patients (82%), while telephone follow-up was obtained for 1112 patients (92%). If a patient reported having undergone subsequent surgery, operative reports detailing the subsequent procedure(s) were obtained and categorized. Multivariate regression analysis was performed to determine independent risk factors for a reoperation. RESULTS: Of the 1112 patients included in the analysis, 122 patients (11%) underwent a total of 172 subsequent procedures on the ipsilateral knee at 2-year follow-up. Of the reoperations, 27% were meniscal procedures (69% meniscectomy, 26% repair), 19% were subsequent revision ACLR, 17% were cartilage procedures (61% chondroplasty, 17% microfracture, 13% mosaicplasty), 11% were hardware removal, and 9% were procedures for arthrofibrosis. Multivariate analysis revealed that patients aged <20 years had twice the odds of patients aged 20 to 29 years to undergo a reoperation. The use of an allograft at the time of revision ACLR (odds ratio [OR], 1.79; P = .007) was a significant predictor for reoperations at 2 years, while staged revision (bone grafting of tunnels before revision ACLR) (OR, 1.93; P = .052) did not reach significance. Patients with grade 4 cartilage damage seen during revision ACLR were 78% less likely to undergo subsequent operations within 2 years. Sex, body mass index, smoking history, Marx activity score, technique for femoral tunnel placement, and meniscal tearing or meniscal treatment at the time of revision ACLR showed no significant effect on the reoperation rate. CONCLUSION: There was a significant reoperation rate after revision ACLR at 2 years (11%), with meniscal procedures most commonly involved. Independent risk factors for subsequent surgery on the ipsilateral knee included age <20 years and the use of allograft tissue at the time of revision ACLR