Characterization and mapping of Dt1 locus which co-segregates with CcTFL1 for growth habit in pigeonpea

Abstract

Key message We report growth habit profiling following SEM, genetic mapping and QTL analysis. Highlighted CcTFL1 , a candidate for determinacy in pigeonpea, since an Indel marker derived from this gene co-segregated with Dt1 locus. AbstractPigeonpea (Cajanus cajan) is one of the most important legume crops grown in arid and semi-arid regions of the world. It is characterized with few unique features compared with other legume species, such as Lotus, Medicago, and Glycine. One of them is growth habit, an important agronomic trait. In the present study, identification of mutations affecting growth habit accompanied by a precise analysis of phenotype has been done which will shed more light upon developmental regulation in pigeonpea. A genetic study was conducted to examine the inheritance of growth habit and a genotyping by sequencing (GBS)-based genetic map constructed using F2 mapping population derived from crossing parents ICP 5529 and ICP 11605. Inheritance studies clearly demonstrated the dominance of indeterminate (IDT) growth habit over determinate (DT) growth habit in F2 and F2:3 progenies. A total of 787 SNP markers were mapped in the genetic map of 1454 cM map length. Growth habit locus (Dt1) was mapped on the CcLG03 contributing more than 61% of total phenotypic variations. Subsequently, QTL analysis highlighted one gene, CcTFL1, as a candidate for determinacy in pigeonpea, since an Indel marker derived from this gene co-segregated with the Dt1 locus. Ability of this Indel-derived marker to differentiate DT/IDT lines was also validated on 262 pigeonpea lines. This study clearly demonstrated that CcTFL1 is a candidate gene for growth habit in pigeonpea and a user-friendly marker was developed in the present study which will allow low-cost genotyping without need of automation.Electronic supplementary materialThe online version of this article (doi:10.1007/s00122-017-2924-2) contains supplementary material, which is available to authorized users.

Development of sequence-based markers for seed protein content in pigeonpea

“…Our initial prioritisation of the CV-detected candidate sequence variants/genes was on the basis of predicted impact Fig. 3 Five linkage groups from a genetic map of an F 2 mapping population ICP 5529 × ICP 11605 (Saxena et al 2017) indicating positions of CAPS/dCAPS markers and QTLs associated with seed protein content (Obala 2017). Bars indicate position of QTL.…”

“…The CAPS/dCAPS genotyping data generated from 188 F 2 plants derived from cross ICP 5529 × ICP 11605 were combined with a GBS-derived single nucleotide polymorphism (SNP) data already available on the same population (ICP 5529 × ICP 11605) (Saxena et al 2017). To assess cosegregation of the CAPS/dCAPS markers with SPC, single marker regression analysis (SMA) was carried out in Excel 2013 (Microsoft) using the F 2 CAPS/dCAPS marker genotypes as independent variables and the F 2 phenotypes as dependent variables.…”

“…Sixteen polymorphic CAPS/dCAPS markers in parental pair ICP 5529 and ICP 11605 (ESM 6) were combined with GBS-derived SNPs data in the population to construct an F 2 genetic map (Saxena et al 2017;Fig. 3).…”

Transcriptional signatures modulating shoot apical meristem morphometric and plant architectural traits enhance yield and productivity in chickpea

“…Efficient genetic manipulation of various major plant architectural traits is vital to achieve enhanced yield and productivity in crop plants (Pickersgill, 2007;Jin et al, 2008;Wang and Li, 2008). Plant architectural traits, including PH and width, are modulated by differentiation, proliferation and maintenance of the meristematic stem cell population, which can be primarily assessed by quantitative measurements of diverse SAM morphometric trait parameters, such as SAM volume/size (height, width, and area), in crops (Thompson et al, 2014(Thompson et al, , 2015Leiboff et al, 2015;Cai et al, 2016;Saxena et al, 2017). From this perspective, this study evaluated the multienvironment (field/ controlled condition) phenotypic variation in two vital plant architectural traits (PW and PH) and correlated the findings with seven major SAM morphometric trait parameters (SH, SWi, SMWi, SH/SWi, SA, SAL, and SR) in the constituted association panel (291 desi and kabuli germplasm accessions) and RIL/NIL mapping individuals of chickpea through histological and SEM assays.…”

“…SAM morphology, a quantitative trait defined by the descriptive measurements of SAM shape and size, can be exploited as target traits for the genetic enhancement of crop plants. Henceforth, the phenotypic variations of said SAM morphometric characteristics are correlated with allelic diversity scanned from natural and mapping populations through genetic and association mapping to successfully identify potential genomic loci governing diverse plant architectural traits in major food crops (Thompson et al, 2014(Thompson et al, , 2015Leiboff et al, 2015;Cai et al, 2016;Saxena et al, 2017). These studies evidently suggest that comprehensive genetic dissection of SAM morphometric and ideal plant architectural traits is vital for crop improvement.…”