scholarly journals Identification of genetic factors controlling domestication-related traits in cowpea (Vigna unguiculata L. Walp)

2017 ◽  
Author(s):  
Sassoum Lo ◽  
María Muñoz-Amatriaín ◽  
Ousmane Boukar ◽  
Ira Herniter ◽  
Ndiaga Cisse ◽  
...  
Keyword(s):  
Flowering Time ◽  
Candidate Genes ◽  
Vigna Unguiculata ◽  
Recombinant Inbred Lines ◽  
Warm Season ◽  
Leaf Length ◽  
Organ Size ◽  
Chromosome 8 ◽  
Nucleotide Polymorphisms ◽  
Pod Shattering

AbstractCowpea (Vigna unguiculata L. Walp) is a warm-season legume with a genetically diverse gene-pool composed of wild and cultivated forms. Cowpea domestication involved considerable phenotypic changes from the wild progenitor, including reduction of pod shattering, increased organ size, and changes in flowering time. Little is known about the genetic basis underlying these changes. In this study, 215 recombinant inbred lines derived from a cross between a cultivated and a wild cowpea accession were used to evaluate nine domestication-related traits (pod shattering, peduncle length, flower color, flowering time, 100-seed weight, pod length, leaf length, leaf width and seed number per pod). A high-density genetic map containing 17,739 single nucleotide polymorphisms was constructed and used to identify 16 quantitative trait loci (QTL) for these nine domestication-related traits. Candidate genes underlying each of those 16 QTL were identified. Four regions with clusters of QTL were identified, including one on chromosome 8 related to increased organ size. This study provides new knowledge of the genomic regions controlling domestication-related traits in cowpea as well as candidate genes underlying those QTL. This information can help to exploit wild relatives in cowpea breeding programs.Key messageThis study identified regions of the cowpea genome that played an important role in cowpea domestication, including a hotspot region for increased organ size

scholarly journals Genome-wide association study reveals candidate genes for flowering time in cowpea (Vigna unguiculata [L.] Walp)

2021 ◽  
Author(s):  
Dev Paudel ◽  
Rocheteau Dareus ◽  
Julia Rosenwald ◽  
Maria Munoz-Amatriain ◽  
Esteban Rios
Keyword(s):  
Flowering Time ◽  
Candidate Genes ◽  
Vigna Unguiculata ◽  
Association Studies ◽  
Snp Markers ◽  
Genome Wide Association ◽  
Human Consumption ◽  
Phenotypic Variance ◽  
Genome Wide Association Studies ◽  
Genome Wide

Cowpea (Vigna unguiculata [L.] Walp., diploid, 2n = 22) is a major crop used as a protein source for human consumption as well as a quality feed for livestock. It is drought and heat tolerant and has been bred to develop varieties that are resilient to changing climates. Plant adaptation to new climates and their yield are strongly affected by flowering time. Therefore, understanding the genetic basis of flowering time is critical to advance cowpea breeding. The aim of this study was to perform genome-wide association studies (GWAS) to identify marker trait associations for flowering time in cowpea using single nucleotide polymorphism (SNP) markers. A total of 367 accessions from a cowpea mini-core collection were evaluated in Ft. Collins, CO in 2019 and 2020, and 292 accessions were evaluated in Citra, FL in 2018. These accessions were genotyped using the Cowpea iSelect Consortium Array that contained 51,128 SNPs. GWAS revealed seven reliable SNPs for flowering time that explained 8-12% of the phenotypic variance. Candidate genes including FT, GI, CRY2, LSH3, UGT87A2, LIF2, and HTA9 that are associated with flowering time were identified for the significant SNP markers. Further efforts to validate these loci will help to understand their role in flowering time in cowpea, and it could facilitate the transfer of some of this knowledge to other closely related legume species.

Quantitative trait loci analysis of flowering time related traits identified in recombinant inbred lines of cowpea (Vigna unguiculata)

Genome ◽  
2013 ◽  
Vol 56 (5) ◽  
pp. 289-294 ◽  
Author(s):  
Mebeasealassie Andargie ◽  
Remy S. Pasquet ◽  
Geoffrey M. Muluvi ◽  
Michael P. Timko
Keyword(s):  
Flowering Time ◽  
Vigna Unguiculata ◽  
Phenotypic Variation ◽  
Recombinant Inbred Lines ◽  
Selection Criterion ◽  
Wild Plants ◽  
Wild Accession ◽  
Flower Opening ◽  
Crop Species ◽  
Long Duration

Flowering time is a major adaptive trait in plants and an important selection criterion in the breeding for genetic improvement of crop species. QTLs for the time of flower opening and days to flower were identified in a cross between a short duration domesticated cowpea (Vigna unguiculata (L.) Walp.) variety, 524B, and a relatively long duration wild accession, 219-01. A set of 159 F7 lines was grown under greenhouse conditions and scored for the flowering time associated phenotypes of time of flower opening and days to flower. Using a LOD threshold of 2.0, putative QTLs were identified and placed on a linkage map consisting of 202 SSR markers and four morphological loci. A total of five QTLs related to the time of flower opening were identified, accounting for 8.8%–29.8% of the phenotypic variation. Three QTLs for days to flower were detected, accounting for 5.7%–18.5% of the phenotypic variation. The major QTL of days to flower and time of flower opening were both mapped on linkage group 1. The QTLs identified in this study provide a strong foundation for further validation and fine mapping for developing an efficient way to restrain the gene flow between the cultivated and wild plants.

scholarly journals QTL Analysis of Stem Elongation and Flowering Time in Lettuce Using Genotyping-by-Sequencing

Genes ◽  
2021 ◽  
Vol 12 (6) ◽  
pp. 947
Author(s):  
O New Lee ◽  
Keita Fukushima ◽  
Han Yong Park ◽  
Saneyuki Kawabata
Keyword(s):  
Flowering Time ◽  
Candidate Genes ◽  
Genomic Sequence ◽  
Stem Elongation ◽  
Recombinant Inbred Lines ◽  
Genotyping By Sequencing ◽  
Stem Growth ◽  
Number Of Leaves ◽  
Leaf Lettuce ◽  
Mapping Populations

Lettuce plants tend to undergo floral initiation by elongation of flower stalks (bolting) under high-temperature and long-day conditions, which is a serious problem for summer lettuce production. Our objective was to generate a high-density genetic map using SNPs obtained from genotyping-by-sequencing (GBS) analysis of F5 recombinant inbred lines (RILs) and to map QTLs involved in stem growth and flowering time in lettuce. A set of 127 intra-specific RIL mapping populations derived from a cross between two varieties, green and red leaf lettuce, were used to identify QTLs related to the number of days from sowing to bolting (DTB), to flowering of the first flower (DTF), to seed-setting of the first flower (DTS), and the total number of leaves (LN), plant height (PH), and total number of branches of main inflorescence (BN) for two consecutive years. Of the 15 QTLs detected, one that controls DTB, DTF, DTS, LN, and PH detected on LG 7, and another QTL that controls DTF, DTS, and PH detected on LG 1. Analysis of the genomic sequence corresponding to the QTL detected on LG 7 led to the identification of 22 putative candidate genes. A consistent QTL related to bolting and flowering time, and corresponding candidate genes has been reported. This study will be valuable in revealing the genetic basis of stem growth and flowering time in lettuce.

scholarly journals Rapid Excavating a FLOWERING LOCUS T-Regulator NF-YA Using Genotyping-by-Sequencing

2021 ◽  
Author(s):  
Shichen Li ◽  
Tong Su ◽  
Lingshuang Wang ◽  
Kun Kou ◽  
Lingping Kong ◽  
...  
Keyword(s):  
Flowering Time ◽  
Candidate Genes ◽  
Recombinant Inbred Lines ◽  
Genotyping By Sequencing ◽  
High Yield ◽  
Human Consumption ◽  
Flowering Locus T ◽  
Transient Transfection Assay ◽  
Soybean Cultivars ◽  
Stable Qtls

Abstract Soybean [Glycine max (L.) Merrill] is one of the most important crop plants in the world as an important source of protein for both human consumption and livestock fodder. Soybean flowering time is beneficial to the improvement of soybean yield. Therefore, finding new QTLs and further identifying candidate genes associated with various flowering time are fundamental approaches in enhancing the yield of soybean. In this study, a set of 120 recombinant inbred lines (RILs) which developed from a cross of two soybean cultivars, Suinong4 (SN4) and ZK168, were genotyped by genotyping-by-sequencing (GBS) approach and phenotyped to expand the cognitive of flowering time (R1) by Quantitative Trait Loci (QTL) analysis. Eventually, we detected three stable QTLs related to R1 separately located on chromosome 14, 18, and 19 under long-day conditions. The candidate genes of the three QTLs were predicted, and association analysis of the candidate genes related to flowering time was carried out. Moreover, a transient transfection assay was performed and showed that a candidate gene of the QTL on chromosome 19, GmNF-YA21 (Nuclear factor YA21), might affect flowering by suppressing the expression of GmFTs. QTLs detected in this study will provide fundamental resources for finding candidate genes and clarify the mechanisms of flowering which would be helpful for breeding novel high-yield soybean cultivars.

scholarly journals Genome-Wide Association Study Reveals Candidate Genes for Flowering Time in Cowpea (Vigna unguiculata [L.] Walp.)

2021 ◽  
Vol 12 ◽  
Author(s):  
Dev Paudel ◽  
Rocheteau Dareus ◽  
Julia Rosenwald ◽  
María Muñoz-Amatriaín ◽  
Esteban F. Rios
Keyword(s):  
Flowering Time ◽  
Candidate Genes ◽  
Vigna Unguiculata ◽  
Association Studies ◽  
Snp Markers ◽  
Genome Wide Association ◽  
Human Consumption ◽  
Phenotypic Variance ◽  
Genome Wide Association Studies ◽  
Genome Wide

Cowpea (Vigna unguiculata [L.] Walp., diploid, 2n = 22) is a major crop used as a protein source for human consumption as well as a quality feed for livestock. It is drought and heat tolerant and has been bred to develop varieties that are resilient to changing climates. Plant adaptation to new climates and their yield are strongly affected by flowering time. Therefore, understanding the genetic basis of flowering time is critical to advance cowpea breeding. The aim of this study was to perform genome-wide association studies (GWAS) to identify marker trait associations for flowering time in cowpea using single nucleotide polymorphism (SNP) markers. A total of 368 accessions from a cowpea mini-core collection were evaluated in Ft. Collins, CO in 2019 and 2020, and 292 accessions were evaluated in Citra, FL in 2018. These accessions were genotyped using the Cowpea iSelect Consortium Array that contained 51,128 SNPs. GWAS revealed seven reliable SNPs for flowering time that explained 8–12% of the phenotypic variance. Candidate genes including FT, GI, CRY2, LSH3, UGT87A2, LIF2, and HTA9 that are associated with flowering time were identified for the significant SNP markers. Further efforts to validate these loci will help to understand their role in flowering time in cowpea, and it could facilitate the transfer of some of this knowledge to other closely related legume species.

New Nucleotide Polymorphisms in the BTC1 gene of Sugar Beet

2020 ◽  
Vol 36 (6) ◽  
pp. 49-54
Author(s):  
A.A. Nalbandyan ◽  
T.P. Fedulova ◽  
I.V. Cherepukhina ◽  
T.I. Kryukova ◽  
N.R. Mikheeva ◽  
...  
Keyword(s):  
Sugar Beet ◽  
Flowering Time ◽  
Molecular Genetic ◽  
Bioinformatic Analysis ◽  
Early Flowering ◽  
Nucleotide Polymorphisms ◽  
Nucleotide Substitutions ◽  
Time Control ◽  
Flowering Time Control ◽  
Exon 10

The flowering time control gene of various sugar beet plants has been studied. The BTC1 gene is a regulator for the suppressor (flowering time 1) and inducer (flowering time 2) genes of this physiological process. The F9/R9 primer pair was used for polymerase chain reaction; these primers are specific to the BTC1 gene region containing exon 9, as well as intron and exon 10. For the first time, nucleotide substitutions in exon 10 of BTC1 gene were identified in bolting sensitive samples (HF1 and BF1), which led to a change in the amino acid composition of the coded polypeptide chain. Based on the results of bioinformatic analysis, it can be assumed that certain nucleotide polymorphisms in the BTC1 gene may determine with a high probability the predisposition of sugar beet genotypes to early flowering. The use of the Geneious Prime tool for the analysis of the BTC1 gene sequences may allow the culling of genotypes prone to early flowering at early stages of selection. sugar beet, flowering gene, BTC1, genetic polymorphism, PCR, molecular genetic markers, selection

scholarly journals QTL Analysis of Five Morpho-Physiological Traits in Bread Wheat Using Two Mapping Populations Derived from Common Parents

Genes ◽  
2021 ◽  
Vol 12 (4) ◽  
pp. 604
Author(s):  
Paolo Vitale ◽  
Fabio Fania ◽  
Salvatore Esposito ◽  
Ivano Pecorella ◽  
Nicola Pecchioni ◽  
...  
Keyword(s):  
Candidate Genes ◽  
Recombinant Inbred Lines ◽  
Snp Array ◽  
Heading Date ◽  
Tiller Number ◽  
Genetic Maps ◽  
Yield Potential ◽  
Adaptation To Climate Change ◽  
Map Resolution ◽  
Mapping Populations

Traits such as plant height (PH), juvenile growth habit (GH), heading date (HD), and tiller number are important for both increasing yield potential and improving crop adaptation to climate change. In the present study, these traits were investigated by using the same bi-parental population at early (F2 and F2-derived F3 families) and late (F6 and F7, recombinant inbred lines, RILs) generations to detect quantitative trait loci (QTLs) and search for candidate genes. A total of 176 and 178 lines were genotyped by the wheat Illumina 25K Infinium SNP array. The two genetic maps spanned 2486.97 cM and 3732.84 cM in length, for the F2 and RILs, respectively. QTLs explaining the highest phenotypic variation were found on chromosomes 2B, 2D, 5A, and 7D for HD and GH, whereas those for PH were found on chromosomes 4B and 4D. Several QTL detected in the early generations (i.e., PH and tiller number) were not detected in the late generations as they were due to dominance effects. Some of the identified QTLs co-mapped to well-known adaptive genes (i.e., Ppd-1, Vrn-1, and Rht-1). Other putative candidate genes were identified for each trait, of which PINE1 and PIF4 may be considered new for GH and TTN in wheat. The use of a large F2 mapping population combined with NGS-based genotyping techniques could improve map resolution and allow closer QTL tagging.

scholarly journals Genome-Wide Association Analysis of Growth Curve Parameters in Chinese Simmental Beef Cattle

Animals ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 192
Author(s):  
Xinghai Duan ◽  
Bingxing An ◽  
Lili Du ◽  
Tianpeng Chang ◽  
Mang Liang ◽  
...  
Keyword(s):  
Beef Cattle ◽  
Candidate Genes ◽  
Growth Curve ◽  
Growth And Development ◽  
Genome Wide Association Study ◽  
Genome Wide Association ◽  
Coefficient Of Determination ◽  
Nucleotide Polymorphisms ◽  
Genome Wide ◽  
A Genome

The objective of the present study was to perform a genome-wide association study (GWAS) for growth curve parameters using nonlinear models that fit original weight–age records. In this study, data from 808 Chinese Simmental beef cattle that were weighed at 0, 6, 12, and 18 months of age were used to fit the growth curve. The Gompertz model showed the highest coefficient of determination (R2 = 0.954). The parameters’ mature body weight (A), time-scale parameter (b), and maturity rate (K) were treated as phenotypes for single-trait GWAS and multi-trait GWAS. In total, 9, 49, and 7 significant SNPs associated with A, b, and K were identified by single-trait GWAS; 22 significant single nucleotide polymorphisms (SNPs) were identified by multi-trait GWAS. Among them, we observed several candidate genes, including PLIN3, KCNS3, TMCO1, PRKAG3, ANGPTL2, IGF-1, SHISA9, and STK3, which were previously reported to associate with growth and development. Further research for these candidate genes may be useful for exploring the full genetic architecture underlying growth and development traits in livestock.

Dementia key gene identification with multi-layered SNP-gene-disease network

2020 ◽  
Vol 36 (Supplement_2) ◽  
pp. i831-i839
Author(s):  
Dong-gi Lee ◽  
Myungjun Kim ◽  
Sang Joon Son ◽  
Chang Hyung Hong ◽  
Hyunjung Shin
Keyword(s):  
Candidate Genes ◽  
Learning Algorithm ◽  
Search Space ◽  
Supplementary Information ◽  
Gene Identification ◽  
Nucleotide Polymorphisms ◽  
Disease Network ◽  
Single Nucleotide ◽  
Key Genes ◽  
Significant Attention

Abstract Motivation Recently, various approaches for diagnosing and treating dementia have received significant attention, especially in identifying key genes that are crucial for dementia. If the mutations of such key genes could be tracked, it would be possible to predict the time of onset of dementia and significantly aid in developing drugs to treat dementia. However, gene finding involves tremendous cost, time and effort. To alleviate these problems, research on utilizing computational biology to decrease the search space of candidate genes is actively conducted. In this study, we propose a framework in which diseases, genes and single-nucleotide polymorphisms are represented by a layered network, and key genes are predicted by a machine learning algorithm. The algorithm utilizes a network-based semi-supervised learning model that can be applied to layered data structures. Results The proposed method was applied to a dataset extracted from public databases related to diseases and genes with data collected from 186 patients. A portion of key genes obtained using the proposed method was verified in silico through PubMed literature, and the remaining genes were left as possible candidate genes. Availability and implementation The code for the framework will be available at http://www.alphaminers.net/. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Transcriptomic profiling of wheat near-isogenic lines reveals candidate genes on chromosome 3A for pre-harvest sprouting resistance

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Xingyi Wang ◽  
Hui Liu ◽  
Kadambot H. M. Siddique ◽  
Guijun Yan
Keyword(s):  
Candidate Genes ◽  
Quantitative Trait ◽  
Genomic Region ◽  
Nucleotide Polymorphisms ◽  
Near Isogenic Lines ◽  
Gene Effects ◽  
Isogenic Lines ◽  
Trait Locus ◽  
Grain Yield And Quality ◽  
Sprouting Resistance

Abstract Background Pre-harvest sprouting (PHS) in wheat can cause severe damage to both grain yield and quality. Resistance to PHS is a quantitative trait controlled by many genes located across all 21 wheat chromosomes. The study targeted a large-effect quantitative trait locus (QTL) QPhs.ccsu-3A.1 for PHS resistance using several sets previously developed near-isogenic lines (NILs). Two pairs of NILs with highly significant phenotypic differences between the isolines were examined by RNA sequencing for their transcriptomic profiles on developing seeds at 15, 25 and 35 days after pollination (DAP) to identify candidate genes underlying the QTL and elucidate gene effects on PHS resistance. At each DAP, differentially expressed genes (DEGs) between the isolines were investigated. Results Gene ontology and KEGG pathway enrichment analyses of key DEGs suggested that six candidate genes underlie QPhs.ccsu-3A.1 responsible for PHS resistance in wheat. Candidate gene expression was further validated by quantitative RT-PCR. Within the targeted QTL interval, 16 genetic variants including five single nucleotide polymorphisms (SNPs) and 11 indels showed consistent polymorphism between resistant and susceptible isolines. Conclusions The targeted QTL is confirmed to harbor core genes related to hormone signaling pathways that can be exploited as a key genomic region for marker-assisted selection. The candidate genes and SNP/indel markers detected in this study are valuable resources for understanding the mechanism of PHS resistance and for marker-assisted breeding of the trait in wheat.

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