多鱗(Sillago sihama)高密度遺傳連鎖圖譜構(gòu)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(chǎn)學院 廣東省名特優(yōu)魚類生殖調(diào)控與繁育工程技術(shù)研究中心 廣東省水產(chǎn)動物病害防控與健康養(yǎng)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(guān)技術(shù)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(gòu)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(zhì)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(shù)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(jié)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(shè)置參數(shù): -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(gòu)建

1.5 生長相關(guān)性狀QTL定位及候選基因預(yù)測

2 結(jié)果

2.1 生長相關(guān)性狀的表型參數(shù)

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(shù)據(jù)頻率分布(n=161)

2.2 多鱗作圖家系GBS測序數(shù)據(jù)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(zhuǎn)換標記有120 302個, 占58.54%, 顛換標記有85 169個, 占41.46%。根據(jù)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(tài)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(zhì)量的SNP標記用于后續(xù)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(gòu)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(guān)性狀QTL的定位

2.5 候選基因的預(yù)測

表2 多鱗整合遺傳圖譜基本信息統(tǒng)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(cè)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(guān)聯(lián)分析

注: LOD曲線,軸和軸分別對應(yīng)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(fù)合區(qū)間定位法定位多鱗生長性狀相關(guān)QTL結(jié)果

表4 多鱗20個QTL區(qū)間內(nèi)已知生長相關(guān)基因信息

3 討論

4 結(jié)論

葉華, 王志勇, 2011. 水產(chǎn)動物遺傳連鎖圖譜構(gòu)建和QTL研究現(xiàn)狀[J]. 海洋科學, 35(1): 105-110.

李進波, 盛婧, 李想, 等, 2014. 五種DNA提取方法對魚加工制品DNA提取效果的比較[J]. 生物技術(shù)通報(4): 43-49.

陳軍平, 胡玉潔, 王磊, 等, 2020. 魚類遺傳連鎖圖譜構(gòu)建及QTL定位的研究進展[J]. 水產(chǎn)科學, 39(4): 620-630.

桂建芳, 包振民, 張曉娟, 2016. 水產(chǎn)遺傳育種與水產(chǎn)種業(yè)發(fā)展戰(zhàn)略研究[J]. 中國工程科學, 18(3): 8-14.

BROMAN K W, WU H, SEN ?,, 2003. R/qtl: QTL mapping in experimental crosses [J]. Bioinformatics, 19(7): 889-890.

CHEN S F, ZHOU Y Q, CHEN Y R,, 2018. fastp: an ultra-fast all-in-one FASTQ preprocessor [J]. Bioinformatics, 34(17): i884-i890.

DONG C J, JIANG P, ZHANG J F,, 2019. High-density linkage map and mapping for sex and growth-related traits of largemouth bass () [J]. Frontiers in Genetics, 10: 960.

ELSHIRE R J, GLAUBITZ J C, SUN Q,, 2011. A robust, simple genotyping-by-sequencing (GBS) approach for high diversity species [J]. PLoS One, 6(5): e19379.

FENG X, YU X M, FU B D,, 2018. A high-resolution genetic linkage map and QTL fine mapping for growth-related traits and sex in the Yangtze River common carp () [J]. BMC Genomics, 19(1): 230.

GUO W J, HE S, LIANG X F,, 2021. A high-density genetic linkage map for Chinese perch () using 2.3K genotyping-by-sequencing SNPs [J]. Animal Genetics, 52(3): 311-320.

HUANG Q C, ZHANG S, DU T,, 2020. Modulation of growth, immunity and antioxidant-related gene expressions in the liver and intestine of juvenileby dietary vitamin C [J]. Aquaculture Nutrition, 26(2): 338-350.

KAIZUKA T, HARA T, OSHIRO N,, 2010Tti1 and Tel2 are critical factors in mammalian target of rapamycin complex assembly [J]. Journal of Biological Chemistry, 285(26): 20109-20116.

KESSUWAN K, KUBOTA S, LIU Q,, 2016. Detection of growth-related quantitative trait loci and high-resolution genetic linkage maps using simple sequence repeat markers in the kelp grouper () [J]. Marine Biotechnology, 18(1): 57-84.

LI H, DURBIN L R, 2009. Fast and accurate short read alignment with Burrows–Wheeler transform [J]. Bioinformatics, 25(14): 1754-1760.

LI Z Q, XUE Q, XU J X,, 2020. The role of RBM10 mutations in the development, treatment, and prognosis of lung adenocarcinoma [J]. Cell Cycle, 19(21): 2918-2926.

LIN X H, HUANG Y, JIANG D N,, 2021Chromosomal-level genome assembly of silver sillago () [J]. Genome Biology and Evolution, 13(2): evaa272.

LIU H Y, FU B D, PANG M X,, 2016. QTL fine mapping and identification of candidate genes for growth-related traits in bighead carp () [J]. Aquaculture, 465: 134-143.

LIU D, GUO Y S, WANG Z D,, 2012. Phylogenetics inferred from mitogenome and control region of Silver Sillago,[J]. Mitochondrial DNA, 23(4): 255-263.

PAN Y Y, LIN X H, CHEN F Y,, 2021. Genome-wide identification and expression profiling of glutathione S-transferase family under hypoxia stress in silver sillago () [J]. Comparative Biochemistry and Physiology Part D: Genomics and Proteomics, 40: 100920.

PENG W Z, XU J, ZHANG Y,, 2016. An ultra-high density linkage map and QTL mapping for sex and growth-related traits of common carp () [J]. Scientific Reports, 6(1): 26693.

SHEN H F, ZHANG W J, HUANG Y,, 2021. The dual function of KDM5C in both gene transcriptional activation and repression promotes breast cancer cell growth and tumorigenesis [J]. Advanced Science, 8(9): 2004635.

TSIGENOPOULOS C S, LOURO B, CHATZIPLIS D,, 2014. Second generation genetic linkage map for the gilthead sea breamL [J]. Marine Genomics, 18: 77-82.

TIAN C X, LIN X H, SAETAN W,, 2020. Transcriptome analysis of liver provides insight into metabolic and translation changes under hypoxia and reoxygenation stress in silver sillago () [J]. Comparative Biochemistry and Physiology Part D: Genomics and Proteomics, 36: 100715.

VAN DER AUWERA G A, CARNEIRO M O, HARTL C,, 2013. From FastQ data to high-confidence variant calls: the genome analysis toolkit best practices pipeline [J]. Current Protocols in Bioinformatics, 43(1110): 11.10.1-11.10.33.

VAN OOIJEN J W, 2011. Multipoint maximum likelihood mapping in a full-sib family of an outbreeding species [J]. Genetics Research, 93(5): 343-349.

WANG X H, FU B D, YU X M,, 2018. Fine mapping of growth-related quantitative trait loci in Yellow River carp () [J]. Aquaculture, 484: 277-285.

WANG K, LI M Y, HAKONARSON H, 2010. ANNOVAR: functional annotation of genetic variants from high-throughput sequencing data [J]. Nucleic Acids Research, 38(16): e164.

WENG Z Y, YANG Y, WANG X,, 2021. Parentage analysis in giant grouper () using microsatellite and SNP markers from genotyping-by-sequencing data [J]. Genes, 12(7): 1042.

XU D D, ZHANG W C, CHEN R Y,, 2021Chromosome-scale assembly and high-density genetic map of the yellow drum,[J]. Scientific Data, 8(1): 268.

YANG W, WANG Y R, JIANG D N,, 2020. ddRADseq- assisted construction of a high-density SNP genetic map and QTL fine mapping for growth-related traits in the spotted scat () [J]. BMC Genomics, 21(1): 278.

YOU X X, SHAN X X, SHI Q, 2020. Research advances in the genomics and applications for molecular breeding of aquaculture animals [J]. Aquaculture, 526: 735357.

ZHANG G S, LI J, ZHANG J J,, 2020. A high-density SNP-based genetic map and several economic traits-related loci in[J]. BMC Genomics, 21(1): 700.

ZHANG S Y, ZHANG X H, CHEN X H,, 2019Construction of a high-density linkage map and QTL fine mapping for growth- and sex-related traits in channel catfish () [J]. Frontiers in Genetics, 10: 251.

ZHANG G Q, ZHANG X H, YE H Z,, 2018Construction of high-density genetic linkage maps and QTL mapping in the golden pompano [J]. Aquaculture, 482: 90-95.

ZHOU Y L, WANG Z W, GUO X F,, 2021. Construction of a high-density genetic linkage map and fine mapping of QTLs for growth and sex-related traits in red-tail catfish () [J]. Aquaculture, 531: 735892.

ZHU C, TONG J, YU X,, 2014. A second-generation genetic linkage map for bighead carp () based on microsatellite markers [J]. Animal Genetics, 45(5): 699-708.

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(chǔ)與應(yīng)用基礎(chǔ)研究基金, 2021A1515010733號, 2019A1515110619號; 廣東海洋大學創(chuàng)新強校工程項目, 2019KTSCX060號; 2021年廣東省科技創(chuàng)新專項資金, SDZX2021041號; 廣東省南美白對蝦現(xiàn)代種業(yè)產(chǎn)業(yè)園項目, K22221號; 廣東海洋大學科研啟動經(jīng)費資助項目, R19026號; 廣東大學生科技創(chuàng)新培育專項資金資助項目, pdjh2022b0239號; 2022年國家級大學生創(chuàng)新創(chuàng)業(yè)訓(xùn)練計劃項目, 202210566003號; 海關(guān)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