多鱗(Sillago sihama)高密度遺傳連鎖圖譜構建及生長性狀QTL定位分析*

田昌緒 朱奕安 鐘 鍵 林星樺 葉明慧 黃 洋 張玉蕾 朱春華 李廣麗

田昌緒1, 2朱奕安1鐘 鍵3林星樺1葉明慧1黃 洋1, 2張玉蕾1朱春華1, 2李廣麗1, 2①

(1. 廣東海洋大學水產學院 廣東省名特優魚類生殖調控與繁育工程技術研究中心 廣東省水產動物病害防控與健康養殖重點實驗室 廣東湛江 524088; 2. 南方海洋科學與工程廣東省實驗室(湛江) 廣東湛江 524088; 3. 湛江海關技術中心 廣東湛江 524022)

1 材料與方法

1.1 作圖家系及DNA提取

1.2 GBS文庫構建及高通量測序

1.3 SNP標記篩選與過濾

使用FASTP(0.18.0) (Chen, 2018)對測序后的raw data進行SNP過濾。篩選標準為: (1) 去除含有未知核苷酸(N)≥10%的reads; (2) 去除phred質量評分≤20及堿基≥50%的reads; (3) 刪除含接頭的reads。過濾后的clean reads用于組裝分析。使用Burrows-Wheeler Aligner (BWA) (Li, 2009) (0.7.12; 比對參數為-k 32 -M)采用mem算法將過濾后的reads比對到參考基因組(SRA PRJNA642704); 比對后結果使用軟件picard (http://sourceforge.net/ projects/picard/.) (1.129)進行標記。使用變異檢測軟件GATK (Van Der Auwera, 2013) (3.4～46) (設置參數: -Window 4, -G_filter “QD<2.0 || FS>60.0 || MQ<40.0”)進行群體SNP檢測, SNP標記過濾標準為: 去除分型比例低于30%的位點, 去除雜合比例大于75%的位點, 按理論比對標記位點的基因型比例進行卡方檢驗,值小于0.001的位點視為嚴重偏分離位點并去除, 保留分離類型為母本雜合型lmxll、父本雜合型nnxnp和雙親雜合型hkxhk的標記。使用ANNOVAR軟件(Wang, 2010)進行功能注釋SNP。

1.4 遺傳圖譜構建

1.5 生長相關性狀QTL定位及候選基因預測

2 結果

2.1 生長相關性狀的表型參數

圖1 多鱗F1代全同胞家系體重(a)、體長(b)、體厚(c)、體高(d)、背鰭前長(e)及眼徑(f)性狀表型數據頻率分布(n=161)

2.2 多鱗作圖家系GBS測序數據及SNP篩選

群體變異檢測共獲得205 471個SNP位點, 這些位點中轉換標記有120 302個, 占58.54%, 顛換標記有85 169個, 占41.46%。根據親本的基因型確定標記的分離類型(親本測序深度不低于4), 保留分離類型為母本雜合型lmxll、父本雜合型nnxnp和雙親雜合型hkxhk的標記, 共篩選獲得143 886個多態性SNP位點(表1); 隨后, 對標記進一步過濾, 去除分型比例低于30%、或雜合率大于75%的位點、或嚴重偏分離的位點, 共保留107 406個高質量的SNP標記用于后續作圖分析。

表1 多鱗作圖群體中雜合子SNP位點的分離模式

2.3 多鱗遺傳連鎖圖譜構建

如表2所示, 24個連鎖群長度介于65.059 cM (LG23)與114.276 cM (LG08)之間, 平均長度89.783 cM,各連鎖群標記平均遺傳距離介于0.383 cM (LG04)至0.554 cM (LG22)之間。其中, LG01連鎖群分布有最多的SNP標記(232個), 其連鎖群長度為112.766 cM, 標記平均距離為0.486 cM; 而LG23上分布有最少的SNP標記(131個), 其長度為65.059 cM, 平均遺傳距離為0.497 cM。

2.4 生長相關性狀QTL的定位

2.5 候選基因的預測

表2 多鱗整合遺傳圖譜基本信息統計

圖2 多鱗高密度遺傳連鎖圖譜

注: 遺傳圖譜展示了24條連鎖群(LG01～LG24)的SNP標記分布及其遺傳距離(cM)。遺傳距離由左側的比例尺表示, 單位為厘摩(cM)。連鎖群上的單條線表示SNP標記

圖3 多鱗體重(a)、體高(b)、體厚(c)、眼徑(d)、體長(e)、背鰭前長(f)性狀的QTL定位以及關聯分析

注: LOD曲線,軸和軸分別對應所在染色體位置和LOD值。紅色水平虛線表示LOD顯著性閾值3.0

表3 復合區間定位法定位多鱗生長性狀相關QTL結果

表4 多鱗20個QTL區間內已知生長相關基因信息

3 討論

4 結論

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CONSTRUCTION OF A HIGH-DENSITY GENETIC LINKAGE MAP AND QTL DETECTION OF GROWTH TRAITS OF SILVER SILLAGO ()

TIAN Chang-Xu1, 2, ZHU Yi-An1, ZHONG Jian3, LIN Xing-Hua1, YE Ming-Hui1, HUANG Yang1, 2, ZHANG Yu-Lei1, 2, ZHU Chun-Hua1, 2, LI Guang-Li1, 2

(1. Guangdong Provincial Key Laboratory of Aquatic Animal Disease Control and Healthy Culture, Guangdong Research Center on Reproductive Control and Breeding Technology of Indigenous Valuable Fish Species, Fisheries College, Guangdong Ocean University, Zhanjiang 524088, China; 2. Southern Marine Science and Engineering Guangdong Laboratory (Zhanjiang), Zhanjiang 524088, China;3. Zhanjiang Customs District Technology Center, Zhanjiang 524022, China)

Construction of high-density genetic map and quantitative trait loci (QTL) mapping are powerful tools for identifying genetic markers and candidate genes that may be responsible for such polygenic trait as growth. The first SNP-based high-density genetic linkage map was constructed by sequencing 163 silver sillago () individuals (2 parents and 161 F1offspring) according to a genotyping-by-sequencing (GBS) method. The consensus map spanned 2 154.803 cM, on average marker interval of 0.455 cM. In total, 4 735 SNPs were assigned to 24 linkage groups (LGs). Then, the QTL of 6 growth related traits was mapped via composite interval mapping (CIM), including body weight, body length, body thickness, body height, pre-dorsal length, and eye diameter. Twenty significant QTLs were identified on 8 LGs and explained 0.14%～8.42% of the phenotypic variance. The logarithm of odds (LOD) value ranged from 3.02 to 4.23. Specially, 8 QTLs were distributed on one linkage group (LG08), and the regions showed overlapping on LG08. Through the functional annotation of the genes in the candidate QTL interval, 19 potential growth-related genes were screened, including,,,,,,,,,,,, and. These genetic markers and candidate genes are useful genomic resources for marker-assisted selection (MAS) in silver sillago and the QTLs are useful tools for growth mechanism analysis of this fish.Key words; genotyping-by-sequencing (GBS); quantitative trait loci (QTL); growth-related traits; candidate genes

Q953; S917.4; S965

10.11693/hyhz20220500118

*廣東省基礎與應用基礎研究基金, 2021A1515010733號, 2019A1515110619號; 廣東海洋大學創新強校工程項目, 2019KTSCX060號; 2021年廣東省科技創新專項資金, SDZX2021041號; 廣東省南美白對蝦現代種業產業園項目, K22221號; 廣東海洋大學科研啟動經費資助項目, R19026號; 廣東大學生科技創新培育專項資金資助項目, pdjh2022b0239號; 2022年國家級大學生創新創業訓練計劃項目, 202210566003號; 海關總署2021年科技項目, 2021HK205號。田昌緒, 博士, E-mail: tiancx@gdou.edu.cn

李廣麗, 教授, E-mail: ligl@gdou.edu.cn

2022-05-04,

2022-07-04