Pea Grain Protein Content Across Italian Environments: Genetic Relationship With Grain Yield, and Opportunities for Genome-Enabled Selection for Protein Yield

Wider pea (Pisum sativum L.) cultivation has great interest for European agriculture, owing to its favorable environmental impact and provision of high-protein feedstuff. This work aimed to investigate the extent of genotype × environment interaction (GEI), genetically based trade-offs and polygenic control for crude protein content and grain yield of pea targeted to Italian environments, and to assess the efficiency of genomic selection (GS) as an alternative to phenotypic selection (PS) to increase protein yield per unit area. Some 306 genotypes belonging to three connected recombinant inbred line (RIL) populations derived from paired crosses between elite cultivars were genotyped through genotyping-by-sequencing and phenotyped for grain yield and protein content on a dry matter basis in three autumn-sown environments of northern or central Italy. Line variation for mean protein content ranged from 21.7 to 26.6%. Purely genetic effects, compared with GEI effects, were over two-fold larger for protein content, and over 2-fold smaller for grain and protein yield per unit area. Grain yield and protein content exhibited no inverse genetic correlation. A genome-wide association study revealed a definite polygenic control not only for grain yield but also for protein content, with small amounts of trait variation accounted for by individual loci. On average, the GS predictive ability for individual RIL populations based on the rrBLUP model (which was selected out of four tested models) using by turns two environments for selection and one for validation was moderately high for protein content (0.53) and moderate for grain yield (0.40) and protein yield (0.41). These values were about halved for inter-environment, inter-population predictions using one RIL population for model construction to predict data of the other populations. The comparison between GS and PS for protein yield based on predicted gains per unit time and similar evaluation costs indicated an advantage of GS for model construction including the target RIL population and, in case of multi-year PS, even for model training based on data of a non-target population. In conclusion, protein content is less challenging than grain yield for phenotypic or genome-enabled improvement, and GS is promising for the simultaneous improvement of both traits.

Analyzing Quantitative Trait Loci for Fiber Quality and Yield-Related Traits From a Recombinant Inbred Line Population With Gossypium hirsutum Race palmeri as One Parent

Fiber quality and yield-related traits are important agronomic traits in cotton breeding. To detect the genetic basis of fiber quality and yield related traits, a recombinant inbred line (RIL) population consisting of 182 lines was established from a cross between Gossypium hirsutum cultivar CCRI35 and G. hirsutum race palmeri accession TX-832. The RIL population was deeply genotyped using SLAF-seq and was phenotyped in six environments. A high-density genetic linkage map with 15,765 SNP markers and 153 SSR markers was constructed, with an average distance of 0.30 cM between adjacent markers. A total of 210 fiber quality quantitative trait loci (QTLs) and 73 yield-related QTLs were identified. Of the detected QTLs, 62 fiber quality QTLs and 10 yield-related QTLs were stable across multiple environments. Twelve and twenty QTL clusters were detected on the At and Dt subgenome, respectively. Twenty-three major QTL clusters were further validated through associated analysis and five candidate genes of four stable fiber quality QTLs were identified. This study revealed elite loci influencing fiber quality and yield and significant phenotypic selection regions during G. hirsutum domestication, and set a stage for future utilization of molecular marker assisted breeding in cotton breeding programs.

Quantitative Trait Loci and Transcriptome Analysis Reveal Genetic Basis of Fiber Quality Traits in CCRI70 RIL Population of Gossypium hirsutum

Upland cotton (Gossypium hirsutum) is widely planted around the world for its natural fiber, and producing high-quality fiber is essential for the textile industry. CCRI70 is a hybrid cotton plant harboring superior yield and fiber quality, whose recombinant inbred line (RIL) population was developed from two upland cotton varieties (sGK156 and 901-001) and were used here to investigate the source of high-quality related alleles. Based on the material of the whole population, a high-density genetic map was constructed using specific locus-amplified fragment sequencing (SLAF-seq). It contained 24,425 single nucleotide polymorphism (SNP) markers, spanning a distance of 4,850.47 centimorgans (cM) over 26 chromosomes with an average marker interval of 0.20 cM. In evaluating three fiber quality traits in nine environments to detect multiple environments stable quantitative trait loci (QTLs), we found 289 QTLs, of which 36 of them were stable QTLs and 18 were novel. Based on the transcriptome analysis for two parents and two RILs, 24,941 unique differentially expressed genes (DEGs) were identified, 473 of which were promising genes. For the fiber strength (FS) QTLs, 320 DEGs were identified, suggesting that pectin synthesis, phenylpropanoid biosynthesis, and plant hormone signaling pathways could influence FS, and several transcription factors may regulate fiber development, such as GAE6, C4H, OMT1, AFR18, EIN3, bZIP44, and GAI. Notably, the marker D13_56413025 in qFS-chr18-4 provides a potential basis for enhancing fiber quality of upland cotton via marker-assisted breeding and gene cloning of important fiber quality traits.

De novo QTL-seq Identifies Loci Linked to Blanchability in Peanut (Arachis hypogaea) and Refines Previously Identified QTL with Low Coverage Sequence

Blanchability is an often overlooked, but important trait for peanut breeding. The process of blanching, removing the skin, is an important step in the processing of raw nuts for manufacturing. Under strong genetic control and requiring considerable effort to phenotype, blanchability is conducive for marker-assisted selection. We used QTL sequencing (QTL-seq) to identify two QTLs related to blanchability using previously phenotyped breeding populations. To validate the QTLs, we show that two markers can select for significantly increased blanchability in an independent recombinant inbred line (RIL) population. Two wild introgressions from Arachis cardenasii conferring strong disease resistance were segregated in the population and were found to negatively impact blanchability. Finally, we show that by utilizing highly accurate sequence analysis pipelines, low coverage sequencing can be used to genotype whole populations with increased power and precision. This study highlights the potential to mine breeding data to identify and develop useful markers for genetic improvement programs, and provide powerful tools for breeding for processing and quality traits.

Identification of Genomic Regions Controlling Chalkiness and Grain Characteristics in a Recombinant Inbred Line Rice Population Based on High-Throughput SNP Markers

Rice (Oryza sativa L.) is the primary food for half of the global population. Recently, there has been increasing concern in the rice industry regarding the eating and milling quality of rice. This study was conducted to identify genetic information for grain characteristics using a recombinant inbred line (RIL) population from a japonica/indica cross based on high-throughput SNP markers and to provide a strategy for improving rice quality. The RIL population used was derived from a cross of “Kaybonnet (KBNT lpa)” and “ZHE733” named the K/Z RIL population, consisting of 198 lines. A total of 4133 SNP markers were used to identify quantitative trait loci (QTLs) with higher resolution and to identify more accurate candidate genes. The characteristics measured included grain length (GL), grain width (GW), grain length to width ratio (RGLW), hundred grain weight (HGW), and percent chalkiness (PC). QTL analysis was performed using QTL IciMapping software. Continuous distributions and transgressive segregations of all the traits were observed, suggesting that the traits were quantitatively inherited. A total of twenty-eight QTLs and ninety-two candidate genes related to rice grain characteristics were identified. This genetic information is important to develop rice varieties of high quality.

Quantitative traits loci mapping and molecular marker development for total glutenin and glutenin fraction contents in wheat

Background Glutenin contents and compositions are crucial factors influencing the end-use quality of wheat. Although the composition of glutenin fractions is well known, there has been relatively little research on the genetic basis of glutenin fractions in wheat. Results To elucidate the genetic basis for the contents of glutenin and its fractions, a population comprising 196 recombinant inbred lines (RILs) was constructed from two parents, Luozhen No.1 and Zhengyumai 9987, which differ regarding their total glutenin and its fraction contents (except for the By fraction). Forty-one additive Quantitative Trait Loci (QTL) were detected in four environments over two years. These QTL explained 1.3% - 53.4% of the phenotypic variation in the examined traits. Forty-three pairs of epistatic QTL (E-QTL) were detected in the RIL population across four environments. The QTL controlling the content of total glutenin and its seven fractions were detected in clusters. Seven clusters enriched with QTL for more than three traits were identified, including a QTL cluster 6AS-3, which was revealed as a novel genetic locus for glutenin and related traits. Kompetitive Allele-Specific PCR (KASP) markers developed from the main QTL cluster 1DL-2 and the previously developed KASP marker for the QTL cluster 6AS-3 were validated as significantly associated with the target traits in the RIL population and in natural varieties. Conclusions This study identified novel genetic loci related to glutenin and its seven fractions. Additionally, the developed KASP markers may be useful for the marker-assisted selection of varieties with high glutenin fraction content and for identifying individuals in the early developmental stages without the need for phenotyping mature plants. On the basis of the results of this study and the KASP markers described herein, breeders will be able to efficiently select wheat lines with favorable glutenin properties and develop elite lines with high glutenin subunit contents.

Mapping of Quantitative Trait Loci for Exserted Stigma Rate By Using (ZS97B/MH63) Ril Population

For increasing pollination and seed set, stigma exsertion has been identified as a major component in hybrid rice. By using a recombinant inbred line (RIL) population derived from an important Indica rice cross between Zhenshan97 and Minghui63, a molecular marker-based analysis of quantitative trait loci (QTL) for stigma exsertion was performed. As a result, six prominent QTL were detected for the exserted stigma rate on chromosome 6, 2, 9, 3, 5 and 1, respectively. qSER-1-1, qSER-2-1, qSER-5-1, qSER-6-1, qSER-15-1, and qSER-18-1 explained 8.1515, 4.6657, 7.2387, 4.8997, 6.925 and 6.9291% of the total phenotypic variance, respectively. In addition, for the qSER-1-1 and qSER-2-1, the ZS97B allele increased exserted stigma rate by about 4.3484 and 3.2836%, respectively; while for qSER-5-1, qSER-6-1, qSER-15-1 and qSER-18-1, the MH63 allele increased exserted stigma rate by approx. 4.1527, 3.4243, 3.9801 and 4.0025%, respectively. Bangladesh J. Bot. 50(3): 551-556, 2021 (September)

Verification and dissection of one quantitative trait locus for grain size and weight on chromosome 1 in rice

Grain size and weight are the key traits determining rice quality and yield and are mainly controlled by quantitative trait loci (QTL). In this study, one minor QTL that was previously mapped in the marker interval of JD1009-JD1019 using the Huanghuazhan/Jizi1560 (HHZ/JZ1560) recombinant inbred line (RIL) population, qTGW1-2, was validated to regulate grain size and weight across four rice-growing seasons using twenty-one near isogenic line (NIL)-F2 populations. The twenty-one populations were in two types of genetic background that were derived from the same parents HHZ and JZ1560. Twelve F9, F10 or F11 NIL-F2 populations with the sequential residual heterozygous regions covering JD1009-RM6840 were developed from one residual heterozygote (RH) in the HHZ/JZ1560 RIL population, and the remaining nine BC3F3, BC3F4 or BC3F5 NIL-F2 populations with the sequential residual heterozygous regions covering JD1009-RM6840 were constructed through consecutive backcrosses to the recurrent parent HHZ followed with marker assistant selection in each generation. Based on the QTL analysis of these genetic populations, qTGW1-2 was successfully confirmed to control grain length, width and weight and further dissected into two QTLs, qTGW1-2a and qTGW1-2b, which were respectively narrowed down to the marker intervals of JD1139-JD1127 (~ 978.2-kb) and JD1121-JD1102 (~ 54.8-kb). Furthermore, the two types of NIL-F2 populations were proved to be able to decrease the genetic background noise and increase the detection power of minor QTL. These results provided an important basis for further map-based cloning and molecular design breeding with the two QTLs in rice.