Biology subjects

Bett, K. E.

Publications and source records attributed to Bett, K. E..

9 recordsLinked to original sources

bioRxiv2026

Screening for Pea Seed-borne Mosaic Virus Resistance (PSbMV) in Lentil and Development of Associated KASP Markers

Lentil (Lens culinaris M.) is one of the most important legume crops grown worldwide, valued for its high nutritional content and its role in improving soil health. Pea seed-borne mosaic virus (PSbMV) poses a significant threat to lentil production worldwide, highlighting the need to identify resistant germplasm and incorporate the trait into breeding programs for sustainable disease management. Although lentil lines carrying recessive resistance to PSbMV have been reported, the underlying resistance genes have not been characterized in detail, and no resistance-associated molecular markers are currently available. In this study, a diversity panel of 86 lentil lines was screened using rub inoculation under controlled conditions, followed by phenotyping through quantitative PCR assays. Virus titer in the inoculated and upper systemically infected leaves was measured and normalized with the expression of host reference gene as an internal control. Inoculated leaves showed higher virus titers, but titers in systemically infected leaves were low in some, but not all, lines, including the previously reported lines carrying the recessive gene sbv, which grouped as resistant lines. In pea, certain amino acid substitutions in eIF4E are associated with recessive resistance to PSbMV. To test if the lentil homolog acts in similar fashion, cDNAs from selected resistant and susceptible lines were sequenced and analyzed. Consistent with pea, several amino acid substitutions in lentil eIF4E were associated with resistance. Nucleotide polymorphisms underlying these amino acid substitutions were used to develop Kompetitive Allele-Specific PCR (KASP) primer sets, which effectively distinguished resistant from susceptible lentil lines.

plant biology↗

bioRxiv2024

Evaluating the breeding potential of cultivated lentils for increasing protein and amino acid concentration in the Northern Great Plains

The rising demand for plant-based proteins has intensified interest in pulse crops due to their high protein concentration. However, few studies have evaluated protein and amino acid composition/variability in cultivated lentil (Lens culinaris Medik.). We evaluated protein and amino acid composition using near-infrared reflectance spectroscopy (NIRS) in a diversity panel grown in four site-years in Saskatchewan, Canada, followed by genome-wide association analyses with phenology-related traits as covariates. We found little correlation between days from sowing to flowering, region of origin, cotyledon color, or seed size, and protein concentration. Reproductive period was correlated with protein concentration. We also observed large variability between environments and more variability within market classes than among them. Our results demonstrate the potential for breeders to identify germplasm and select for increased protein and amino acid concentration and quality using a high-throughput NIRS method. We were able to identify numerous molecular markers for use in marker-assisted breeding. Our approach could be replicated by breeders from other regions or with other pulse crops to help meet the demand for plant-based protein and improvements in protein quality.

plant biology↗

bioRxiv2023

Understanding Genome Structure Facilitates the Use of Wild Lentil Germplasm for Breeding: A Case Study with Shattering Loci

Plant breeders are generally reluctant to cross elite crop cultivars with their wild relatives to introgress novel desirable traits due to associated negative traits such as pod shattering. This results in a genetic bottleneck that could be reduced through better understanding of the genomic locations of the gene(s) controlling this trait. We integrated information on parental genomes, pod shattering data from multiple environments, and high-density genetic linkage maps to identify pod shattering QTLs in three lentil interspecific recombinant inbred line (RIL) populations. The broad-sense heritability on a multi-environment basis varied from 0.46 (in LR-70, Lens culinaris x L. odemensis) to 0.77 (in LR-68, L. orientalis x L. culinaris). Genetic linkage maps of the interspecific populations revealed reciprocal translocations of chromosomal segments that differed among the populations, and which were associated with reduced recombination. Segregation distortion was also observed for clusters of SNPs on multiple chromosomes per population, further affecting introgression. Two major QTL, on chromosomes 4 and 7, were repeatedly detected in the three populations and contain several candidate genes. These findings will be of significant value for lentil breeders to strategically access novel superior alleles while minimizing the genetic impact of pod shattering from wild parents.

plant biology↗

bioRxiv2023

QTL Mapping of Seed Fe Concentration in an Interspecific RIL Population Derived from Lens culinaris x Lens ervoides

Biofortification of lentil (Lens culinaris Medik.) was investigated to potentially increase bioavailable iron (Fe) in the human diet. This study assessed the genetic variation for seed Fe concentration (SFeC) and identified the genomic regions associated with SFeC in an interspecific mapping population derived from crossing between L. culinaris cv. Eston and L. ervoides accession IG 72815. A total of 134 RILs were evaluated in three environments. The SFeC data for individual environments and best linear unbiased prediction (BLUP) of the SFeC across environments were used for QTL analysis. The seeds of the RILs exhibited variation for SFeC from 47.0 to 102.9 mg kg-1 and several RILs showed transgressive segregation for SFeC. QTL analysis identified two QTLs on chromosomes 2 and 6 that accounted for 11.9-14.0% and 12.5-20.5%, respectively, of the total phenotypic variation for SFeC. The SNP markers linked to the identified QTLs may prove useful for increasing SFeC via marker-assisted selection. RILs with high SFeC can be incorporated into the lentil breeding program to broaden the genetic base of the breeding pool and/or used for the development of genetic resources for future genomic studies.

genomics↗

bioRxiv2021

Genomic rearrangements have consequences for introgression breeding as revealed by genome assemblies of wild and cultivated lentil species

Understanding the genomic relationship between wild and cultivated genomes would facilitate access to the untapped variability found in crop wild relatives. We developed genome assemblies of a cultivated lentil (Lens culinaris) as well as a wild relative (L. ervoides). Comparative analyses revealed large-scale structural rearrangements and additional repetitive DNA in the cultivated genome, resulting in regions of reduced recombination, segregation distortion and permanent heterozygosity in the offspring of a cross between the two species. These novel findings provide plant breeders with better insight into how best to approach accessing the novel variability available in wild relatives.

plant biology↗

bioRxiv2021

Genetic Basis for Lentil Adaptation to Summer Cropping in Northern Temperate Environments

The continued success of lentil (Lens culinaris Medik.) genetic improvement relies on the availability of broad genetic diversity and new alleles need to be identified and incorporated into the cultivated gene pool. Availability of robust and predictive markers greatly enhances the precise transfer of genomic regions from unadapted germplasm. Quantitative trait loci (QTLs) for key phenological traits in lentil were located using a recombinant inbreed line (RIL) population derived from a cross between an Ethiopian landrace (ILL 1704) and a northern temperate cultivar (CDC Robin). Field experiments were conducted at Sutherland research farm in Saskatoon and at Rosthern, Saskatchewan, Canada during 2018 and 2019. A linkage map was constructed using 21,634 SNPs located on seven linkage groups (LGs) which correspond to the seven haploid chromosomes of lentil. Eight QTL were identified for six phenological traits. Flowering related QTL were identified at two regions on LG6. FLOWERING LOCUS T (FT) genes were annotated within the flowering time QTL interval based on the lentil reference genome. Similarly, a major QTL for post-flowering developmental processes was located on LG5 with several senescence-associated genes annotated within the QTL interval. The flowering time QTL was validated in a different genetic background indicating the potential use of the identified markers for marker-assisted selection to precisely transfer genomic regions from exotic germplasm into elite crop cultivars without disrupting adaptation. Core IdeasO_LIStable QTL were located for key phenological traits in lentil that lead to regional adaptation. C_LIO_LIFT genes are candidates for controlling flowering time in lentil grown in temperate environments. C_LIO_LIA major locus controlling post-flowering developmental processes was located on lentil LG5 with several senescence-associated genes annotated within the QTL interval. C_LIO_LIMarkers identified in this study can be useful for marker-assisted selection to precisely transfer genomic regions from exotic germplasm into elite lentil cultivars without disrupting adaptation. C_LI

molecular biology↗

bioRxiv2021

Genetic and gene expression analysis of flowering time regulation by light quality in lentil

Flowering time is important due to its roles in adaptation to different environments and subsequent formation of crop yield. Changes in light quality affect a range of developmental processes including flowering time, however little is known about light quality induced flowering time control in lentil. This study aims to investigate the genetic basis for differences in flowering response to light quality in lentil. We explored variation in flowering time caused by changes in red/far-red related light quality environments of a lentil interspecific recombinant inbred line population developed from a cross between Lens culinaris cv. Lupa and L. orientalis accession BGE 016880. A genetic linkage map was constructed and then used for identifying QTL associated with flowering time regulation under different light quality environments. Differential gene expression analysis through transcriptomic study and RT-qPCR were used to identify potential candidate genes. QTL mapping located 13 QTLs controlling flower time under different light quality environments, with phenotypic variance explained ranging from 1.7 to 62.9%. Transcriptomic profiling and gene expression analysis for both parents of this interspecific RIL population identified flowering-related genes showing environment-specific differential expression (flowering DEGs). One of these, a member of the florigen gene family FTa1 (LcFTa1) was located close to 3 major QTLs. Furthermore, gene expression results suggests two other florigen genes (LcFTb1 and LcFTb2), MADS-box transcription factors like LcAGL6/13d, LcSVPb, LcSOC1b and LcFULb, as well as bHLH transcription factor LcPIF6 and Gibberellin 20 oxidase LcGA20oxC,G, may be involved in the light quality response as well. Our results show that a major component of flowering time sensitivity to light quality is tightly linked to LcFTa1 and associated with changes in its expression. This work provides a foundation for crop improvement of lentil with better adaptation to variable light environments.

plant biology↗

bioRxiv2020

STRATEGIC IDENTIFICATION OF NEW GENETIC DIVERSITY TO EXPAND LENTIL (Lens culinaris Medik.) PRODUCTION USING NEPAL AS AN EXAMPLE

This article is written to disseminate descriptive results obtained from field experiments conducted at Bardiya, Nepal, during winter 2016 and 2017 on 324 diverse lentil (L. culinaris Medik.) genotypes obtained from genebanks and breeding programs around the world. Lentil genotypes were examined for phenological traits related to adaptation, and recommendations for potential incorporation of new exotic genotypes into Nepalese breeding programs are presented. In addition, predictions of days to flowering based on temperature and photoperiod are used to identify genotypes that hold suitability for specific growing regions in Nepal, allowing for the potential expansion of growing regions. From this study we found many potentially adapted genotypes for terai, mid-hill and high hill growing regions, the list consists of a number of large-seeded lines with yellow cotyledons, an entirely new market class of lentils in Nepal. This paper primarily targets lentil breeders and agronomists; furthermore, it can be equally informative to extension workers involved in the pulse crop research and development in Nepal and other countries with similar climatic conditions.

plant biology↗

bioRxiv2019

Genomic selection for lentil breeding: empirical evidence

Genomic selection (GS) is a type of marker-based selection which was initially suggested for livestock breeding and is being encouraged for crop breeding. Several statistical models and approaches have been developed to implement GS; however, none of these methods have been tested for use in lentil breeding. This study was conducted to evaluate different GS models and prediction scenarios based on empirical data and to make recommendations for designing genomic selection strategies for lentil breeding. We evaluated nine single-trait models, two multiple-trait models, and models that account for population structure and genotype-by-environment interaction (GEI) using a lentil diversity panel and two recombinant inbred lines (RIL) populations that were genotyped using a custom exome capture assay. Within-population, across-population and across-environment predictions were made for five phenology traits. Prediction accuracy varied among the evaluated models, populations, prediction scenarios, traits, and statistical models. Single-trait models showed similar accuracy for each trait in the absence of large effect QTL but BayesB outperformed all models when there were QTL with relatively large effects. Models that accounted for GEI and multiple-trait (MT) models increased prediction accuracy for a low heritability trait by up to 66% and 14% but accuracy did not improve for traits of high heritability. Moderate to high accuracies were obtained for within-population and across-environment predictions but across-population prediction accuracy was very low. This suggests that GS can be implemented in lentil to make predictions within populations and across environments, but across-population prediction should not be considered when the population size is small.

genomics↗