A novel variant of Gh_D02G0276 is required for root-knot nematode resistance on chromosome 14 (D02) in Upland cotton.

KEY MESSAGE: MAGIC population sequencing and virus-induced gene silencing identify Gh_D02G0276 as a novel root-knot nematode resistance gene on chromosome 14 in Upland cotton. The southern root-knot nematode [RKN; Meloidogyne incognita (Kofoid & White)] remains the primary yield-limiting biotic stress to Upland cotton (Gossypium hirsutum L.) throughout the southeastern USA. While useful genetic markers have been developed for two major RKN resistance loci on chromosomes 11 (A11) and 14 (D02), these markers are not completely effective because the causative genes have not been identified. Here, we sequenced 550 recombinant inbred lines (RILs) from a multi-parent advanced generation intercross (MAGIC) population to identify five RILs that had informative recombinations near the D02-RKN resistance locus. The RKN resistance phenotypes of these five RILs narrowed the D02-RKN locus to a 30-kb region with four candidate genes. We conducted virus-induced gene silencing (VIGS) on each of these genes and found that Gh_D02G0276 was required for suppression of RKN egg production conferred by the Chr. D02 resistance gene. The resistant lines all possessed an allele of Gh_D02G0276 that showed non-synonymous mutations and was prematurely truncated. Furthermore, a Gh_D02G0276-specific marker for the resistance allele variant was able to identify RKN-resistant germplasm from a collection of 367 cotton accessions. The Gh_D02G0276 peptide shares similarity with domesticated hAT-like transposases with additional novel N- and C-terminal domains that resemble the target of known RKN effector molecules and a prokaryotic motif, respectively. The truncation in the resistance allele results in a loss of a plant nuclear gene-specific C-terminal motif, potentially rendering this domain antigenic due to its high homology with bacterial proteins. The conclusive identification of this RKN resistance gene opens new avenues for understanding plant resistance mechanisms to RKN as well as opportunities to develop more efficient marker-assisted selection in cotton breeding programs.

Effects of Low-Grade Weirs on Soil Microbial Communities in Agricultural Drainage Ditches.

Agricultural fertilizer application throughout the Mississippi River basin has been identified as a major source of N pollution to the Gulf of Mexico. Using best management practices, such as low-grade weirs, has been identified as a potential solution to mitigate nutrient loads in agricultural runoff. This study assessed impacts of weir implementation in four agricultural drainage ditches (three with weirs and one control site) in the Mississippi Delta. Soil samples collected from field locations in spring 2013 were analyzed for denitrifier abundance using genes (16s ribosomal RNA [rRNA] genes, , , and ) via quantitative polymerase chain reaction (qPCR), microbial community profiles via terminal-restriction fragment length polymorphism (T-RFLP) of 16s rRNA genes, soil parameters (C, N, and moisture), and vegetation presence at sample locations. Gene quantification was successful, except for , which was found below detection limits (5000 gene copies g soil). Distance from weirs was negatively correlated with 16S rRNA genes and soil moisture, and soil moisture was positively correlated with 16s rRNA and S gene abundance. Results of empirical Bayesian kriging did not exhibit obvious patterns of microbial diversity in relation to weir proximity. Preliminary assessment of seasonal trends showed genes 16s rRNA and , soil N, and mean T-RF values to be greater in fall than in spring. Results highlight that weirs had no direct impact on microbial diversity or denitrification functional gene abundance. Correlations between microbial measures and environmental parameters suggest that adequate management of N runoff from agricultural landscapes will require ecological engineering beyond weirs to optimize N mitigation.

A High-Throughput Standard PCR-Based Genotyping Method for Determining Transgene Zygosity in Segregating Plant Populations.

In crop research programs that implement transgene-based strategies for trait improvement it is necessary to distinguish between transgene homozygous and hemizygous individuals in segregating populations. Direct methods for determining transgene zygosity are technically challenging, expensive, and require specialized equipment. In this report, we describe a standard PCR-based protocol coupled with capillary electrophoresis that can identify transgene homozygous and hemizygous individuals in a segregating population without knowledge of transgene insertion site. PCR primers were designed to amplify conserved T-DNA segments of the 35S promoter, OCS terminator, and NPTII kanamycin resistance gene in the pHellsgate-8 RNAi construct for the Gossypium hirsutum phytochrome A1 gene. Using an optimized multiplexed reaction mixture and an amplification program of only 10 cycles we could discriminate between transgene homozygous and hemizygous cotton control DNA samples based on PCR product peak characteristics gathered by capillary electrophoresis. The protocol was refined by evaluating segregating transgenic progeny from nine BC1S1 populations derived from crosses between the transgenic cotton parent 'E-1-7-6' and other cotton cultivars. OCS PCR product peak height and peak area, normalized by amplification of the native cotton gene GhUBC1, revealed clear bimodal distributions of OCS product characteristics for each BC1S1 population indicating the presence of homozygous and hemizygous clusters which was further confirmed via K-means clustering. BC1S1 plants identified as homozygous or hemizygous were self-fertilized to produce BC1S2 progeny. For the homozygous class, 19/20 BC1S2 families confirmed the homozygous BC1S1 prediction while 21/21 BC1S2 families confirmed the hemizygous prediction of the original parent. This relatively simple protocol provides a reliable, rapid, and high-throughput way of evaluating segregating transgenic populations using methods and equipment common to crop molecular breeding labs.

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

BACKGROUND: Cotton supplies a great majority of natural fiber for the global textile industry. The negative correlation between yield and fiber quality has hindered breeders' ability to improve these traits simultaneously. A multi-parent advanced generation inter-cross (MAGIC) population developed through random-mating of multiple diverse parents has the ability to break this negative correlation. Genotyping-by-sequencing (GBS) is a method that can rapidly identify and genotype a large number of single nucleotide polymorphisms (SNP). Genotyping a MAGIC population using GBS technologies will enable us to identify marker-trait associations with high resolution. RESULTS: An Upland cotton MAGIC population was developed through random-mating of 11 diverse cultivars for five generations. In this study, fiber quality data obtained from four environments and 6071 SNP markers generated via GBS and 223 microsatellite markers of 547 recombinant inbred lines (RILs) of the MAGIC population were used to conduct a genome wide association study (GWAS). By employing a mixed linear model, GWAS enabled us to identify markers significantly associated with fiber quantitative trait loci (QTL). We identified and validated one QTL cluster associated with four fiber quality traits [short fiber content (SFC), strength (STR), length (UHM) and uniformity (UI)] on chromosome A07. We further identified candidate genes related to fiber quality attributes in this region. Gene expression and amino acid substitution analysis suggested that a regeneration of bulb biogenesis 1 (GhRBB1_A07) gene is a candidate for superior fiber quality in Upland cotton. The DNA marker CFBid0004 designed from an 18 bp deletion in the coding sequence of GhRBB1_A07 in Acala Ultima is associated with the improved fiber quality in the MAGIC RILs and 105 additional commercial Upland cotton cultivars. CONCLUSION: Using GBS and a MAGIC population enabled more precise fiber QTL mapping in Upland cotton. The fiber QTL and associated markers identified in this study can be used to improve fiber quality through marker assisted selection or genomic selection in a cotton breeding program. Target manipulation of the GhRBB1_A07 gene through biotechnology or gene editing may potentially improve cotton fiber quality.

Coupling of MIC-3 overexpression with the chromosomes 11 and 14 root-knot nematode (RKN) (Meloidogyne incognita) resistance QTLs provides insights into the regulation of the RKN resistance response in Upland cotton (Gossypium hirsutum).

KEY MESSAGE: Genetic analysis of MIC-3 transgene with RKN resistance QTLs provides insight into the resistance regulatory mechanism and provides a framework for testing additional hypotheses. Resistance to root-knot nematode (RKN) (Meloidogyne incognita) in Upland cotton (Gossypium hirsutum) is mediated by two major quantitative trait loci (QTL) located on chromosomes 11 and 14. The MIC-3 (Meloidogyne Induced Cotton3) protein accumulates specifically within the immature galls of RKN-resistant plants that possess these QTLs. Recently, we showed that MIC-3 overexpression in an RKN-susceptible cotton genotype suppressed RKN egg production but not RKN-induced root galling. In this study, the MIC-3 overexpression construct T-DNA in the single-copy transgenic line '14-7-1' was converted into a codominant molecular marker that allowed the marker assisted selection of F2:3 cotton lines, derived from a cross between 14-7-1 and M-240 RNR, having all possible combinations of the chromosomes 11 and 14 QTLs with and without the MIC-3 overexpression construct. Root-knot nematode reproduction (eggs g(-1) root) and severity of RKN-induced root galling were assessed in these lines. We discovered that the addition of MIC-3 overexpression suppressed RKN reproduction in lines lacking both resistance QTLs and in lines having only the chromosome 14 QTL, suggesting an additive effect of the MIC-3 construct with this QTL. In contrast, MIC-3 overexpression did not improve resistance in lines having the single chromosome 11 QTL or in lines having both resistance QTLs, suggesting an epistatic interaction between the chromosome 11 QTL and the MIC-3 construct. Overexpression of MIC-3 did not affect the severity of RKN-induced root galling regardless of QTL genotype. These data provide new insights into the relative order of action of the chromosomes 11 and 14 QTLs and their potential roles in regulating MIC-3 expression as part of the RKN resistance response.

Quantitative trait loci analysis of fiber quality traits using a random-mated recombinant inbred population in Upland cotton (Gossypium hirsutum L.).

BACKGROUND: Upland cotton (Gossypium hirsutum L.) accounts for about 95% of world cotton production. Improving Upland cotton cultivars has been the focus of world-wide cotton breeding programs. Negative correlation between yield and fiber quality is an obstacle for cotton improvement. Random-mating provides a potential methodology to break this correlation. The suite of fiber quality traits that affect the yarn quality includes the length, strength, maturity, fineness, elongation, uniformity and color. Identification of stable fiber quantitative trait loci (QTL) in Upland cotton is essential in order to improve cotton cultivars with superior quality using marker-assisted selection (MAS) strategy. RESULTS: Using 11 diverse Upland cotton cultivars as parents, a random-mated recombinant inbred (RI) population consisting of 550 RI lines was developed after 6 cycles of random-mating and 6 generations of self-pollination. The 550 RILs were planted in triplicates for two years in Mississippi State, MS, USA to obtain fiber quality data. After screening 15538 simple sequence repeat (SSR) markers, 2132 were polymorphic among the 11 parents. One thousand five hundred eighty-two markers covering 83% of cotton genome were used to genotype 275 RILs (Set 1). The marker-trait associations were analyzed using the software program TASSEL. At p < 0.01, 131 fiber QTLs and 37 QTL clusters were identified. These QTLs were responsible for the combined phenotypic variance ranging from 62.3% for short fiber content to 82.8% for elongation. The other 275 RILs (Set 2) were analyzed using a subset of 270 SSR markers, and the QTLs were confirmed. Two major QTL clusters were observed on chromosomes 7 and 16. Comparison of these 131 QTLs with the previously published QTLs indicated that 77 were identified before, and 54 appeared novel. CONCLUSIONS: The 11 parents used in this study represent a diverse genetic pool of the US cultivated cotton, and 10 of them were elite commercial cultivars. The fiber QTLs, especially QTL clusters reported herein can be readily implemented in a cotton breeding program to improve fiber quality via MAS strategy. The consensus QTL regions warrant further investigation to better understand the genetics and molecular mechanisms underlying fiber development.