Genome-wide Association Analysis
1.Service Advantages
● Yakawanda Project Cases: kubvira payakavambwa muna 2009, BMKGENE yapedza mazana emapurojekiti ezvipenyu mukutsvagisa kwehuwandu hweGWAS, yakabatsira vaongorori kutsikisa zvinopfuura zvinyorwa zve100, uye kuwedzera kwemhedzisiro yakasvika mazana mashanu.
● Nyanzvi dzekuongorora.
● Nguva pfupi yekuongorora.
● Kuchera data kwakarurama.
2. Zvinyorwa zveSevhisi
| Type | Population Scale | Sequencing strategy nekudzika |
| SLAF-GWAS | Nhamba yemuenzaniso ≥200 | Genome size <400M, ine ref-genome, WGS inokurudzirwa |
| Genome size ≤ 1G, 100K Tags uye 10X | ||
| 1G ≤ Saizi yeGenome ≤ 2G, 200K Tags uye 10X | ||
| Genome size> 2G, 300K Tags uye 10X | ||
| WGS-GWAS | Nhamba yemuenzaniso ≥200 | 10X yemuenzaniso wega wega |
3. Kusarudzwa kwezvinhu
Mhando dzakasiyana, subspecies, landraces / genebanks / mhuri dzakasanganiswa / zviwanikwa zvemusango
Mhando dzakasiyana, subspecies, landraces
Half-sib family/full-sib family/wild resources
4. Bioinformation Analysis
● Genome-wide association analysis
● Kuongorora uye kuongororwa kweSNP inokosha
● Kushanda annotation yejini yemumiriri
5. Kuyerera Kwebasa Rebasa
Kuedza kugadzira
Muenzaniso wekutumira
RNA kubviswa
Kuvakwa kweraibhurari
Sequencing
Data analysis
Mushure mekutengesa masevhisi
a.Phenotype QC
Frequency distribution histogram
Phenotype nhamba
b.Ongororo yemubatanidzwa (Muenzaniso: GEMMA, FaST-LMM, EMMAX)
Nhoroondo yeQQ
Manhattan Plot
| Gore | Journal | IF | Title |
| 2022 | NC | 17.69 | Genomic hwaro hwegiga-chromosomes uye giga-genome yemuti peony Paeonia ostii |
| 2015 | NP | 7.43 | Domestication footprints anchor genomic regions of agronomic value musoya beans |
| 2018 | MP | 9.32 | Yese-genome requencing yepasi rose muunganidzwa wezvakabatwa chibharo zvinoburitsa genetic hwaro hwekusiyana kwavo ecotype. |
| 2022 | HR | 7.29 | Kuongororwa kweGenome-wide association kunopa ma molecular nzwisiso mukusiyana kwechisikigo kwekukura kwembeu yemavito |
