Candidate gene-based association mapping of growth and wood quality traits in Eucalyptus globulusLabill

Identification of superior haplotypes for flowering time in pigeonpea through candidate gene-based association study of a diverse minicore collection

KEY MESSAGE

In current study candidate gene (261 genes) based association mapping on 144 pigeonpea accessions for flowering time and related traits and 29 MTAs producing eight superior haplotypes were identified. In the current study, we have conducted an association analysis for flowering-associated traits in a diverse pigeonpea mini-core collection comprising 144 accessions using the SNP data of 261 flowering-related genes. In total, 13,449 SNPs were detected in the current study, which ranged from 743 (ICP10228) to 1469 (ICP6668) among the individuals. The nucleotide diversity (0.28) and Watterson estimates (0.34) reflected substantial diversity, while Tajima's D (-0.70) indicated the abundance of rare alleles in the collection. A total of 29 marker trait associations (MTAs) were identified, among which 19 were unique to days to first flowering (DOF) and/or days to fifty percent flowering (DFF), 9 to plant height (PH), and 1 to determinate (Det) growth habit using 3 years of phenotypic data. Among these MTAs, six were common to DOF and/or DFF, and four were common to DOF/DFF along with the PH, reflecting their pleiotropic action. These 29 MTAs spanned 25 genes, among which 10 genes clustered in the protein-protein network analysis, indicating their concerted involvement in floral induction. Furthermore, we identified eight haplotypes, four of which regulate late flowering, while the remaining four regulate early flowering using the MTAs. Interestingly, haplotypes conferring late flowering (H001, H002, and H008) were found to be taller, while those involved in early flowering (H003) were shorter in height. The expression pattern of these genes, as inferred from the transcriptome data, also underpinned their involvement in floral induction. The haplotypes identified will be highly useful to the pigeonpea breeding community for haplotype-based breeding.

GHRH, PRP-PACAP and GHRHR Target Sequencing via an Ion Torrent Personal Genome Machine Reveals an Association with Growth in Orange-Spotted Grouper (Epinephelus coioides)

Growth hormone-releasing hormone (GHRH) and the receptor, GHRHR, constitute important components of the hypothalamus-pituitary growth axis and act on the downstream growth hormone (GH). PACAP-related peptide/pituitary adenylate cyclase activating polypeptide (PRP-PACAP) is a paralog of GHRH. These genes all play key roles in development and growth patterns. To improve the quality of cultured fish strains, natural genetic variation must be examined and understood. A mixed linear model has been widely used in association mapping, taking the population structures and pairwise kinship patterns into consideration. In this study, a mass cross population of orange-spotted grouper (Epinephelus coioides) was examined. These candidate genes were found to harbor low nucleotide diversity (θ_w from 0.00154 to 0.00388) and linkage disequilibrium levels (delay of 50% within 2 kbp). Association mapping was employed, and two single-nucleotide polymorphisms (KR269823.1:g.475A>C and KR269823.1:g.2143T>C) were found to be associated with growth (false discovery rate Q < 0.05), explaining 9.0%–17.0% of the phenotypic variance. The association of KR269823.1:g.2143T>C was also found via haplotype-based association (p < 0.05). The identified associations offer new insights into gene functions, and the associated single-nucleotide polymorphisms (SNPs) may be used for breeding purposes.

Mapping of yellow mosaic virus (YMV) resistance in soybean (Glycine max L. Merr.) through association mapping approach

Yellow Mosaic Virus (YMV) is a serious disease of soybean. Resistance to YMV was mapped in 180 soybean genotypes through association mapping approach using 121 simple sequence repeats (SSR) and four resistance gene analogue (RGA)-based markers. The association mapping population (AMP) (96 genotypes) and confirmation population (CP) (84 genotypes) was tested for resistance to YMV at hot-spot consecutively for 3 years (2007-2009). The genotypes exhibited significant variability for YMV resistance (P < 0.01). Molecular genotyping and population structure analysis with 'admixture' co-ancestry model detected seven optimal sub-populations in the AMP. Linkage disequilibrium (LD) between the markers extended up to 35 and 10 cM with r2 > 0.15, and >0.25, respectively. The 4 RGA-based markers showed no association with YMV resistance. Two SSR markers, Satt301 and GMHSP179 on chromosome 17 were found to be in significant LD with YMV resistance. Contingency Chi-square test confirmed the association (P < 0.01) and the utility of the markers was validated in the CP. It would pave the way for marker assisted selection for YMV resistance in soybean. This is the first report of its kind in soybean.