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

Agronomy ◽  
2021 ◽  
Vol 11 (11) ◽  
pp. 2201
Author(s):  
Walid Korani ◽  
Dan O’Connor ◽  
Ye Chu ◽  
Carolina Chavarro ◽  
Carolina Ballen ◽  
...  
Keyword(s):  
Marker Assisted Selection ◽  
Genetic Improvement ◽  
De Novo ◽  
Quality Traits ◽  
Considerable Effort ◽  
Breeding Populations ◽  
Ril Population ◽  
Important Trait ◽  
Improvement Programs ◽  
Low Coverage

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.

scholarly journals Trait-specific Selection Signature Detection Reveals Novel Loci of Meat Quality in Large White Pigs

2021 ◽  
Vol 12 ◽  
Author(s):  
Yu Shen ◽  
Haiyan Wang ◽  
Jiahao Xie ◽  
Zixuan Wang ◽  
Yunlong Ma
Keyword(s):  
Candidate Genes ◽  
Meat Quality ◽  
Genetic Improvement ◽  
Genetic Basis ◽  
Muscle Development ◽  
Fixation Index ◽  
Quality Traits ◽  
Selection Signatures ◽  
Meat Quality Traits ◽  
Improvement Programs

In past decades, meat quality traits have been shaped by human-driven selection in the process of genetic improvement programs. Exploring the potential genetic basis of artificial selection and mapping functional candidate genes for economic traits are of great significance in genetic improvement of pigs. In this study, we focus on investigating the genetic basis of five meat quality traits, including intramuscular fat content (IMF), drip loss, water binding capacity, pH at 45 min (pH45min), and ultimate pH (pH24h). Through making phenotypic gradient differential population pairs, Wright’s fixation index (FST) and the cross-population extended haplotype homozogysity (XPEHH) were applied to detect selection signatures for these five traits. Finally, a total of 427 and 307 trait-specific selection signatures were revealed by FST and XPEHH, respectively. Further bioinformatics analysis indicates that some genes, such as USF1, NDUFS2, PIGM, IGSF8, CASQ1, and ACBD6, overlapping with the trait-specific selection signatures are responsible for the phenotypes including fat metabolism and muscle development. Among them, a series of promising trait-specific selection signatures that were detected in the high IMF subpopulation are located in the region of 93544042-95179724bp on SSC4, and the genes harboring in this region are all related to lipids and muscle development. Overall, these candidate genes of meat quality traits identified in this analysis may provide some fundamental information for further exploring the genetic basis of this complex trait.

scholarly journals Phenotypic and genetic variation of ultraviolet–visible-infrared spectral wavelengths of bovine meat

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Giovanni Bittante ◽  
Simone Savoia ◽  
Alessio Cecchinato ◽  
Sara Pegolo ◽  
Andrea Albera
Keyword(s):  
Meat Quality ◽  
Genetic Improvement ◽  
Near Infrared ◽  
Infrared Region ◽  
Phenotypic Variance ◽  
Quality Traits ◽  
Meat Quality Traits ◽  
Infrared Spectral ◽  
Portable Spectrometers ◽  
Absorbance Spectra

AbstractSpectroscopic predictions can be used for the genetic improvement of meat quality traits in cattle. No information is however available on the genetics of meat absorbance spectra. This research investigated the phenotypic variation and the heritability of meat absorbance spectra at individual wavelengths in the ultraviolet–visible and near-infrared region (UV–Vis-NIR) obtained with portable spectrometers. Five spectra per instrument were taken on the ribeye surface of 1185 Piemontese young bulls from 93 farms (13,182 Herd-Book pedigree relatives). Linear animal model analyses of 1481 single-wavelengths from UV–Vis-NIRS and 125 from Micro-NIRS were carried out separately. In the overlapping regions, the proportions of phenotypic variance explained by batch/date of slaughter (14 ± 6% and 17 ± 7%,), rearing farm (6 ± 2% and 5 ± 3%), and the residual variances (72 ± 10% and 72 ± 5%) were similar for the UV–Vis-NIRS and Micro-NIRS, but additive genetics (7 ± 2% and 4 ± 2%) and heritability (8.3 ± 2.3% vs 5.1 ± 0.6%) were greater with the Micro-NIRS. Heritability was much greater for the visible fraction (25.2 ± 11.4%), especially the violet, blue and green colors, than for the NIR fraction (5.0 ± 8.0%). These results allow a better understanding of the possibility of using the absorbance of visible and infrared wavelengths correlated with meat quality traits for the genetic improvement in beef cattle.

scholarly journals Integration of high-density genetic mapping with transcriptome analysis uncovers numerous agronomic QTL and reveals candidate genes for the control of tillering in sorghum

2021 ◽  
Author(s):  
Rajanikanth Govindarajulu ◽  
Ashley N Hostetler ◽  
Yuguo Xiao ◽  
Srinivasa R Chaluvadi ◽  
Margarita Mauro-Herrera ◽  
...  
Keyword(s):  
Agronomic Traits ◽  
Interspecific Cross ◽  
Crop Improvement ◽  
Differentially Expressed ◽  
Plant Domestication ◽  
Sorghum Propinquum ◽  
Ril Population ◽  
Trait Locus ◽  
Genomic Regions ◽  
Low Coverage

Abstract Phenotypes such as branching, photoperiod sensitivity, and height were modified during plant domestication and crop improvement. Here, we perform quantitative trait locus (QTL) mapping of these and other agronomic traits in a recombinant inbred line (RIL) population derived from an interspecific cross between Sorghum propinquum and Sorghum bicolor inbred Tx7000. Using low-coverage Illumina sequencing and a bin-mapping approach, we generated ∼1920 bin markers spanning ∼875 cM. Phenotyping data were collected and analyzed from two field locations and one greenhouse experiment for six agronomic traits, thereby identifying a total of 30 QTL. Many of these QTL were penetrant across environments and co-mapped with major QTL identified in other studies. Other QTL uncovered new genomic regions associated with these traits, and some of these were environment-specific in their action. To further dissect the genetic underpinnings of tillering, we complemented QTL analysis with transcriptomics, identifying 6189 genes that were differentially expressed during tiller bud elongation. We identified genes such as Dormancy Associated Protein 1 (DRM1) in addition to various transcription factors that are differentially expressed in comparisons of dormant to elongating tiller buds and lie within tillering QTL, suggesting that these genes are key regulators of tiller elongation in sorghum. Our study demonstrates the usefulness of this RIL population in detecting domestication and improvement-associated genes in sorghum, thus providing a valuable resource for genetic investigation and improvement to the sorghum community.

scholarly journals Application of Tissue Culture in Plant Reproduction

Forests ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 342
Author(s):  
Elena Corredoira ◽  
Rita L. Costa
Keyword(s):  
Tissue Culture ◽  
Genetic Improvement ◽  
Plant Reproduction ◽  
Climatic Conditions ◽  
Improvement Programs

The increasing degradation of forests, together with a higher demand for wood and fruit, has led to the need for more efficient trees adapted to the current climatic conditions and, thus, to the need for genetic improvement programs [...]

scholarly journals Draft Genome Sequence of Leifsonia xyli subsp. xyli Strain gdw1

2016 ◽  
Vol 4 (5) ◽  
Author(s):  
Jihua Wang ◽  
Li Wang ◽  
Gan Cao ◽  
Muqing Zhang ◽  
Ying Guo
Keyword(s):  
Genome Sequence ◽  
Genetic Improvement ◽  
De Novo ◽  
Draft Genome ◽  
Draft Genome Sequence ◽  
Coding Sequences ◽  
Ratoon Stunting Disease

Here, we report the draft genome sequence of Leifsonia xyli subsp. xyli strain gdw1, isolated from the stem of Badila sugarcane located at the Guangdong Key Laboratory for Crops Genetic Improvement (Guanzhou, China), that causes ratoon stunting disease of sugarcane. The de novo genome of Leifsonia xyli subsp. xyli was assembled with 48 scaffolds and a G+C content of 67.68%, and contained 2.6 Mb bp and 2,838 coding sequences.

scholarly journals Population structure and genetic diversity analysis in Sali (Oryza sativa) rice germplasm of Assam using microsatellite markers

2021 ◽  
Vol 58 (2) ◽  
pp. 279-286
Author(s):  
Sandhani Saikia ◽  
Pratap Jyoti Handique ◽  
Mahendra K Modi
Keyword(s):  
Genetic Diversity ◽  
Ssr Markers ◽  
Genetic Improvement ◽  
Crop Improvement ◽  
Mean Value ◽  
Diversity Analysis ◽  
Rice Cultivars ◽  
Improvement Program ◽  
Information Index ◽  
Improvement Programs

Genetic diversity is the source of novel allelic combinations that can be efficiently utilized in any crop improvement program. To facilitate future crop improvement programs in rice, a study was designed to identify the underlying genetic variations in the Sali rice germplasms of Assam using SSR markers. The 129 SSR markers that were used in the study amplified a total of 765 fragments with an average of 5.93 alleles per locus. The Shannon's Information Index was found to be in the range from 0.533 to 1.786. The Polymorphism Information Content (PIC) fell into the range from 0.304 to 0.691 with a mean value of 0.55. The overall FST value was found to be 0.519 that indicated the presence of genetic differentiation amongst the genotypes used in the study. The Sali population was divided into two clusters. The information obtained from the present study will facilitate the genetic improvement of Sali rice cultivars.

scholarly journals Strategies to assure optimal trade-offs among competing objectives for genetic improvement of soybean

2021 ◽  
Author(s):  
Vishnu Ramasubramanian ◽  
William Beavis
Keyword(s):  
Genomic Selection ◽  
Genetic Improvement ◽  
Genetic Variance ◽  
Breeding Strategies ◽  
Short Term ◽  
Genetic Gains ◽  
Mating Design ◽  
Genetic Potential ◽  
Breeding Populations

AbstractPlant breeding is a decision making discipline based on understanding project objectives. Genetic improvement projects can have two competing objectives: maximize rate of genetic improvement and minimize loss of useful genetic variance. For commercial plant breeders competition in the marketplace forces greater emphasis on maximizing immediate genetic improvements. In contrast public plant breeders have an opportunity, perhaps an obligation, to place greater emphasis on minimizing loss of useful genetic variance while realizing genetic improvements. Considerable research indicates that short term genetic gains from Genomic Selection (GS) are much greater than Phenotypic Selection (PS), while PS provides better long term genetic gains because PS retains useful genetic diversity during the early cycles of selection. With limited resources must a soybean breeder choose between the two extreme responses provided by GS or PS? Or is it possible to develop novel breeding strategies that will provide a desirable compromise between the competing objectives? To address these questions, we decomposed breeding strategies into decisions about selection methods, mating designs and whether the breeding population should be organized as family islands. For breeding populations organized into islands decisions about possible migration rules among family islands were included. From among 60 possible strategies, genetic improvement is maximized for the first five to ten cycles using GS, a hub network mating design in breeding populations organized as fully connected family islands and migration rules allowing exchange of two lines among islands every other cycle of selection. If the objectives are to maximize both short-term and long-term gains, then the best compromise strategy is similar except a genomic mating design, instead of a hub networked mating design, is used. This strategy also resulted in realizing the greatest proportion of genetic potential of the founder populations. Weighted genomic selection applied to both non-isolated and island populations also resulted in realization of the greatest proportion of genetic potential of the founders, but required more cycles than the best compromise strategy.

scholarly journals Genetic and Genomic Resources to Study Natural Variation in Brassica rapa

2020 ◽  
Author(s):  
Ping Lou ◽  
Scott Woody ◽  
Kathleen Greenham ◽  
Robert VanBuren ◽  
Marivi Colle ◽  
...  
Keyword(s):  
Brassica Rapa ◽  
Natural Variation ◽  
De Novo ◽  
Coat Color ◽  
Current Knowledge ◽  
Genomic Structure ◽  
Close Relative ◽  
Structure Variation ◽  
Genomic Resources ◽  
Ril Population

ABSTRACTThe globally important crop Brassica rapa, a close relative of Arabidopsis, is an excellent system for modeling our current knowledge of plant growth on a morphologically diverse crop. The long history of B. rapa domestication across Asia and Europe provides a unique collection of locally adapted varieties that span large climatic regions with various abiotic and biotic stress tolerance traits. This diverse gene pool provides a rich source of targets with the potential for manipulation towards the enhancement of productivity of crops both within and outside the Brassicaceae. To expand the genetic resources available to study natural variation in B. rapa, we constructed an Advanced Intercross Recombinant Inbred (AI-RIL) population using B. rapa subsp. trilocularis (Yellow Sarson) R500 and the B. rapa subsp. parachinensis (Cai Xin) variety L58. Our current understanding of genomic structure variation across crops suggests that a single reference genome is insufficient for capturing the genetic diversity within a species. To complement this AI-RIL population and current and future B. rapa genomic resources, we generated a de novo genome assembly of the B. rapa subsp. trilocularis (Yellow Sarson) variety R500, the maternal parent of the AI-RIL population. The genetic map for the R500 x L58 population generated using this de novo genome was used to map QTL for seed coat color and revealed the improved mapping resolution afforded by this new assembly.

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